diff --git a/.rat-excludes b/.rat-excludes index 88f99b6959d71..dccf2db8055ce 100644 --- a/.rat-excludes +++ b/.rat-excludes @@ -15,6 +15,7 @@ TAGS RELEASE control docs +docker.properties.template fairscheduler.xml.template spark-defaults.conf.template log4j.properties @@ -33,6 +34,9 @@ d3.min.js dagre-d3.min.js graphlib-dot.min.js sorttable.js +vis.min.js +vis.min.css +vis.map .*avsc .*txt .*json diff --git a/LICENSE b/LICENSE index 9b364a4d00079..21c42e9a20fa3 100644 --- a/LICENSE +++ b/LICENSE @@ -814,6 +814,7 @@ BSD-style licenses The following components are provided under a BSD-style license. See project link for details. (BSD 3 Clause) core (com.github.fommil.netlib:core:1.1.2 - https://github.com/fommil/netlib-java/core) + (BSD 3 Clause) JPMML-Model (org.jpmml:pmml-model:1.1.15 - https://github.com/jpmml/jpmml-model) (BSD 3-clause style license) jblas (org.jblas:jblas:1.2.3 - http://jblas.org/) (BSD License) AntLR Parser Generator (antlr:antlr:2.7.7 - http://www.antlr.org/) (BSD License) Javolution (javolution:javolution:5.5.1 - http://javolution.org) diff --git a/bin/spark-shell2.cmd b/bin/spark-shell2.cmd index 02f51fe59a911..00fd30fa38d36 100644 --- a/bin/spark-shell2.cmd +++ b/bin/spark-shell2.cmd @@ -19,7 +19,7 @@ rem set SPARK_HOME=%~dp0.. -echo "%*" | findstr " --help -h" >nul +echo "%*" | findstr " \<--help\> \<-h\>" >nul if %ERRORLEVEL% equ 0 ( call :usage exit /b 0 diff --git a/conf/docker.properties.template b/conf/docker.properties.template new file mode 100644 index 0000000000000..26e3bfd9c5b9b --- /dev/null +++ b/conf/docker.properties.template @@ -0,0 +1,3 @@ +spark.mesos.executor.docker.image: +spark.mesos.executor.docker.volumes: /usr/local/lib:/host/usr/local/lib:ro +spark.mesos.executor.home: /opt/spark diff --git a/core/pom.xml b/core/pom.xml index 459ef66712c36..2dfb00d7ecf26 100644 --- a/core/pom.xml +++ b/core/pom.xml @@ -95,6 +95,11 @@ spark-network-shuffle_${scala.binary.version} ${project.version} + + org.apache.spark + spark-unsafe_${scala.binary.version} + ${project.version} + net.java.dev.jets3t jets3t diff --git a/core/src/main/scala/org/apache/spark/storage/TachyonFileSegment.scala b/core/src/main/java/org/apache/spark/api/java/function/Function0.java similarity index 67% rename from core/src/main/scala/org/apache/spark/storage/TachyonFileSegment.scala rename to core/src/main/java/org/apache/spark/api/java/function/Function0.java index 65fa81704c365..38e410c5debe6 100644 --- a/core/src/main/scala/org/apache/spark/storage/TachyonFileSegment.scala +++ b/core/src/main/java/org/apache/spark/api/java/function/Function0.java @@ -15,16 +15,13 @@ * limitations under the License. */ -package org.apache.spark.storage +package org.apache.spark.api.java.function; -import tachyon.client.TachyonFile +import java.io.Serializable; /** - * References a particular segment of a file (potentially the entire file), based off an offset and - * a length. + * A zero-argument function that returns an R. */ -private[spark] class TachyonFileSegment(val file: TachyonFile, val offset: Long, val length: Long) { - override def toString: String = { - "(name=%s, offset=%d, length=%d)".format(file.getPath(), offset, length) - } +public interface Function0 extends Serializable { + public R call() throws Exception; } diff --git a/core/src/main/resources/org/apache/spark/ui/static/timeline-view.css b/core/src/main/resources/org/apache/spark/ui/static/timeline-view.css new file mode 100644 index 0000000000000..35ef14e5aaf1a --- /dev/null +++ b/core/src/main/resources/org/apache/spark/ui/static/timeline-view.css @@ -0,0 +1,182 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +div#application-timeline, div#job-timeline { + margin-bottom: 30px; +} + +#application-timeline div.legend-area { + margin-top: 5px; +} + +.vis.timeline div.content { + width: 100%; +} + +.vis.timeline .item.stage { + cursor: pointer; +} + +.vis.timeline .item.stage.succeeded { + background-color: #D5DDF6; +} + +.vis.timeline .item.stage.succeeded.selected { + background-color: #D5DDF6; + border-color: #97B0F8; + z-index: auto; +} + +.legend-area rect.completed-stage-legend { + fill: #D5DDF6; + stroke: #97B0F8; +} + +.vis.timeline .item.stage.failed { + background-color: #FF5475; +} + +.vis.timeline .item.stage.failed.selected { + background-color: #FF5475; + border-color: #97B0F8; + z-index: auto; +} + +.legend-area rect.failed-stage-legend { + fill: #FF5475; + stroke: #97B0F8; +} + +.vis.timeline .item.stage.running { + background-color: #FDFFCA; +} + +.vis.timeline .item.stage.running.selected { + background-color: #FDFFCA; + border-color: #97B0F8; + z-index: auto; +} + +.legend-area rect.active-stage-legend { + fill: #FDFFCA; + stroke: #97B0F8; +} + +.vis.timeline .item.job { + cursor: pointer; +} + +.vis.timeline .item.job.succeeded { + background-color: #D5DDF6; +} + +.vis.timeline .item.job.succeeded.selected { + background-color: #D5DDF6; + border-color: #97B0F8; + z-index: auto; +} + +.legend-area rect.succeeded-job-legend { + fill: #D5DDF6; + stroke: #97B0F8; +} + +.vis.timeline .item.job.failed { + background-color: #FF5475; +} + +.vis.timeline .item.job.failed.selected { + background-color: #FF5475; + border-color: #97B0F8; + z-index: auto; +} + +.legend-area rect.failed-job-legend { + fill: #FF5475; + stroke: #97B0F8; +} + +.vis.timeline .item.job.running { + background-color: #FDFFCA; +} + +.vis.timeline .item.job.running.selected { + background-color: #FDFFCA; + border-color: #97B0F8; + z-index: auto; +} + +.legend-area rect.running-job-legend { + fill: #FDFFCA; + stroke: #97B0F8; +} + +.vis.timeline .item.executor.added { + background-color: #D5DDF6; +} + +.legend-area rect.executor-added-legend { + fill: #D5DDF6; + stroke: #97B0F8; +} + +.vis.timeline .item.executor.removed { + background-color: #EBCA59; +} + +.legend-area rect.executor-removed-legend { + fill: #EBCA59; + stroke: #97B0F8; +} + +.vis.timeline .item.executor.selected { + border-color: #FFC200; + background-color: #FFF785; + z-index: 2; +} + +tr.corresponding-item-hover>td, tr.corresponding-item-hover>th { + background-color: #FFE1FA !important; +} + +#application-timeline.collapsed { + display: none; +} + +#job-timeline.collapsed { + display: none; +} + +.control-panel { + margin-bottom: 5px; +} + +span.expand-application-timeline, span.expand-job-timeline { + cursor: pointer; +} + +.control-panel input+span { + cursor: pointer; +} + +.vis.timeline .item.range .content { + position: unset; +} + +.vis.timeline .item .tooltip-inner { + max-width: unset !important; +} diff --git a/core/src/main/resources/org/apache/spark/ui/static/timeline-view.js b/core/src/main/resources/org/apache/spark/ui/static/timeline-view.js new file mode 100644 index 0000000000000..e4a891d47f035 --- /dev/null +++ b/core/src/main/resources/org/apache/spark/ui/static/timeline-view.js @@ -0,0 +1,168 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +function drawApplicationTimeline(groupArray, eventObjArray, startTime) { + var groups = new vis.DataSet(groupArray); + var items = new vis.DataSet(eventObjArray); + var container = $("#application-timeline")[0]; + var options = { + groupOrder: function(a, b) { + return a.value - b.value + }, + editable: false, + showCurrentTime: false, + min: startTime, + zoomable: false + }; + + var applicationTimeline = new vis.Timeline(container); + applicationTimeline.setOptions(options); + applicationTimeline.setGroups(groups); + applicationTimeline.setItems(items); + + setupZoomable("#application-timeline-zoom-lock", applicationTimeline); + setupExecutorEventAction(); + + function setupJobEventAction() { + $(".item.range.job.application-timeline-object").each(function() { + var getJobId = function(baseElem) { + var jobIdText = $($(baseElem).find(".application-timeline-content")[0]).text(); + var jobId = jobIdText.match("\\(Job (\\d+)\\)")[1]; + return jobId; + }; + + $(this).click(function() { + window.location.href = "job/?id=" + getJobId(this); + }); + + $(this).hover( + function() { + $("#job-" + getJobId(this)).addClass("corresponding-item-hover"); + $($(this).find("div.application-timeline-content")[0]).tooltip("show"); + }, + function() { + $("#job-" + getJobId(this)).removeClass("corresponding-item-hover"); + $($(this).find("div.application-timeline-content")[0]).tooltip("hide"); + } + ); + }); + } + + setupJobEventAction(); + + $("span.expand-application-timeline").click(function() { + $("#application-timeline").toggleClass('collapsed'); + + // Switch the class of the arrow from open to closed. + $(this).find('.expand-application-timeline-arrow').toggleClass('arrow-open'); + $(this).find('.expand-application-timeline-arrow').toggleClass('arrow-closed'); + }); +} + +function drawJobTimeline(groupArray, eventObjArray, startTime) { + var groups = new vis.DataSet(groupArray); + var items = new vis.DataSet(eventObjArray); + var container = $('#job-timeline')[0]; + var options = { + groupOrder: function(a, b) { + return a.value - b.value; + }, + editable: false, + showCurrentTime: false, + min: startTime, + zoomable: false, + }; + + var jobTimeline = new vis.Timeline(container); + jobTimeline.setOptions(options); + jobTimeline.setGroups(groups); + jobTimeline.setItems(items); + + setupZoomable("#job-timeline-zoom-lock", jobTimeline); + setupExecutorEventAction(); + + function setupStageEventAction() { + $(".item.range.stage.job-timeline-object").each(function() { + var getStageIdAndAttempt = function(baseElem) { + var stageIdText = $($(baseElem).find(".job-timeline-content")[0]).text(); + var stageIdAndAttempt = stageIdText.match("\\(Stage (\\d+\\.\\d+)\\)")[1].split("."); + return stageIdAndAttempt; + }; + + $(this).click(function() { + var idAndAttempt = getStageIdAndAttempt(this); + var id = idAndAttempt[0]; + var attempt = idAndAttempt[1]; + window.location.href = "../../stages/stage/?id=" + id + "&attempt=" + attempt; + }); + + $(this).hover( + function() { + var idAndAttempt = getStageIdAndAttempt(this); + var id = idAndAttempt[0]; + var attempt = idAndAttempt[1]; + $("#stage-" + id + "-" + attempt).addClass("corresponding-item-hover"); + $($(this).find("div.job-timeline-content")[0]).tooltip("show"); + }, + function() { + var idAndAttempt = getStageIdAndAttempt(this); + var id = idAndAttempt[0]; + var attempt = idAndAttempt[1]; + $("#stage-" + id + "-" + attempt).removeClass("corresponding-item-hover"); + $($(this).find("div.job-timeline-content")[0]).tooltip("hide"); + } + ); + }); + } + + setupStageEventAction(); + + $("span.expand-job-timeline").click(function() { + $("#job-timeline").toggleClass('collapsed'); + + // Switch the class of the arrow from open to closed. + $(this).find('.expand-job-timeline-arrow').toggleClass('arrow-open'); + $(this).find('.expand-job-timeline-arrow').toggleClass('arrow-closed'); + }); +} + +function setupExecutorEventAction() { + $(".item.box.executor").each(function () { + $(this).hover( + function() { + $($(this).find(".executor-event-content")[0]).tooltip("show"); + }, + function() { + $($(this).find(".executor-event-content")[0]).tooltip("hide"); + } + ); + }); +} + +function setupZoomable(id, timeline) { + $(id + '>input[type="checkbox"]').click(function() { + if (this.checked) { + timeline.setOptions({zoomable: false}); + } else { + timeline.setOptions({zoomable: true}); + } + }); + + $(id + ">span").click(function() { + $(this).parent().find('input:checkbox').trigger('click'); + }); +} diff --git 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m=(t-p)/(u-p),g=240*m,v=this._hsv2rgb(g,1,1);c.strokeStyle=v,c.beginPath(),c.moveTo(h,r+t),c.lineTo(a,r+t),c.stroke()}c.strokeStyle=this.colorAxis,c.strokeRect(h,r,i,n)}if(this.style===s.STYLE.DOTSIZE&&(c.strokeStyle=this.colorAxis,c.fillStyle=this.colorDot,c.beginPath(),c.moveTo(h,r),c.lineTo(a,r),c.lineTo(a-i+e,d),c.lineTo(h,d),c.closePath(),c.fill(),c.stroke()),this.style===s.STYLE.DOTCOLOR||this.style===s.STYLE.DOTSIZE){var y=5,b=new f(this.valueMin,this.valueMax,(this.valueMax-this.valueMin)/5,!0);for(b.start(),b.getCurrent()0?this.yMin:this.yMax,o=this._convert3Dto2D(new l(x,r,this.zMin)),Math.cos(2*_)>0?(g.textAlign="center",g.textBaseline="top",o.y+=b):Math.sin(2*_)<0?(g.textAlign="right",g.textBaseline="middle"):(g.textAlign="left",g.textBaseline="middle"),g.fillStyle=this.colorAxis,g.fillText(" "+this.xValueLabel(i.getCurrent())+" ",o.x,o.y),i.next()}for(g.lineWidth=1,s=void 0===this.defaultYStep,i=new f(this.yMin,this.yMax,this.yStep,s),i.start(),i.getCurrent()0?this.xMin:this.xMax,o=this._convert3Dto2D(new l(n,i.getCurrent(),this.zMin)),Math.cos(2*_)<0?(g.textAlign="center",g.textBaseline="top",o.y+=b):Math.sin(2*_)>0?(g.textAlign="right",g.textBaseline="middle"):(g.textAlign="left",g.textBaseline="middle"),g.fillStyle=this.colorAxis,g.fillText(" "+this.yValueLabel(i.getCurrent())+" ",o.x,o.y),i.next();for(g.lineWidth=1,s=void 0===this.defaultZStep,i=new f(this.zMin,this.zMax,this.zStep,s),i.start(),i.getCurrent()0?this.xMin:this.xMax,r=Math.sin(_)<0?this.yMin:this.yMax;!i.end();)t=this._convert3Dto2D(new l(n,r,i.getCurrent())),g.strokeStyle=this.colorAxis,g.beginPath(),g.moveTo(t.x,t.y),g.lineTo(t.x-b,t.y),g.stroke(),g.textAlign="right",g.textBaseline="middle",g.fillStyle=this.colorAxis,g.fillText(this.zValueLabel(i.getCurrent())+" ",t.x-5,t.y),i.next();g.lineWidth=1,t=this._convert3Dto2D(new l(n,r,this.zMin)),e=this._convert3Dto2D(new l(n,r,this.zMax)),g.strokeStyle=this.colorAxis,g.beginPath(),g.moveTo(t.x,t.y),g.lineTo(e.x,e.y),g.stroke(),g.lineWidth=1,p=this._convert3Dto2D(new l(this.xMin,this.yMin,this.zMin)),u=this._convert3Dto2D(new l(this.xMax,this.yMin,this.zMin)),g.strokeStyle=this.colorAxis,g.beginPath(),g.moveTo(p.x,p.y),g.lineTo(u.x,u.y),g.stroke(),p=this._convert3Dto2D(new l(this.xMin,this.yMax,this.zMin)),u=this._convert3Dto2D(new l(this.xMax,this.yMax,this.zMin)),g.strokeStyle=this.colorAxis,g.beginPath(),g.moveTo(p.x,p.y),g.lineTo(u.x,u.y),g.stroke(),g.lineWidth=1,t=this._convert3Dto2D(new l(this.xMin,this.yMin,this.zMin)),e=this._convert3Dto2D(new l(this.xMin,this.yMax,this.zMin)),g.strokeStyle=this.colorAxis,g.beginPath(),g.moveTo(t.x,t.y),g.lineTo(e.x,e.y),g.stroke(),t=this._convert3Dto2D(new l(this.xMax,this.yMin,this.zMin)),e=this._convert3Dto2D(new l(this.xMax,this.yMax,this.zMin)),g.strokeStyle=this.colorAxis,g.beginPath(),g.moveTo(t.x,t.y),g.lineTo(e.x,e.y),g.stroke();var w=this.xLabel;w.length>0&&(c=.1/this.scale.y,n=(this.xMin+this.xMax)/2,r=Math.cos(_)>0?this.yMin-c:this.yMax+c,o=this._convert3Dto2D(new l(n,r,this.zMin)),Math.cos(2*_)>0?(g.textAlign="center",g.textBaseline="top"):Math.sin(2*_)<0?(g.textAlign="right",g.textBaseline="middle"):(g.textAlign="left",g.textBaseline="middle"),g.fillStyle=this.colorAxis,g.fillText(w,o.x,o.y));var S=this.yLabel;S.length>0&&(d=.1/this.scale.x,n=Math.sin(_)>0?this.xMin-d:this.xMax+d,r=(this.yMin+this.yMax)/2,o=this._convert3Dto2D(new l(n,r,this.zMin)),Math.cos(2*_)<0?(g.textAlign="center",g.textBaseline="top"):Math.sin(2*_)>0?(g.textAlign="right",g.textBaseline="middle"):(g.textAlign="left",g.textBaseline="middle"),g.fillStyle=this.colorAxis,g.fillText(S,o.x,o.y));var M=this.zLabel;M.length>0&&(h=30,n=Math.cos(_)>0?this.xMin:this.xMax,r=Math.sin(_)<0?this.yMin:this.yMax,a=(this.zMin+this.zMax)/2,o=this._convert3Dto2D(new l(n,r,a)),g.textAlign="right",g.textBaseline="middle",g.fillStyle=this.colorAxis,g.fillText(M,o.x-h,o.y))},s.prototype._hsv2rgb=function(t,e,i){var s,o,n,r,a,h;switch(r=i*e,a=Math.floor(t/60),h=r*(1-Math.abs(t/60%2-1)),a){case 0:s=r,o=h,n=0;break;case 1:s=h,o=r,n=0;break;case 2:s=0,o=r,n=h;break;case 3:s=0,o=h,n=r;break;case 4:s=h,o=0,n=r;break;case 5:s=r,o=0,n=h;break;default:s=0,o=0,n=0}return"RGB("+parseInt(255*s)+","+parseInt(255*o)+","+parseInt(255*n)+")"},s.prototype._redrawDataGrid=function(){var t,e,i,o,n,r,a,h,d,c,p,u,m,f=this.frame.canvas,g=f.getContext("2d");if(!(void 0===this.dataPoints||this.dataPoints.length<=0)){for(n=0;n0}else r=!0;r?(m=(t.point.z+e.point.z+i.point.z+o.point.z)/4,c=240*(1-(m-this.zMin)*this.scale.z/this.verticalRatio),p=1,this.showShadow?(u=Math.min(1+S.x/M/2,1),a=this._hsv2rgb(c,p,u),h=a):(u=1,a=this._hsv2rgb(c,p,u),h=this.colorAxis)):(a="gray",h=this.colorAxis),d=.5,g.lineWidth=d,g.fillStyle=a,g.strokeStyle=h,g.beginPath(),g.moveTo(t.screen.x,t.screen.y),g.lineTo(e.screen.x,e.screen.y),g.lineTo(o.screen.x,o.screen.y),g.lineTo(i.screen.x,i.screen.y),g.closePath(),g.fill(),g.stroke()}}else for(n=0;np&&(p=0);var u,m,f;this.style===s.STYLE.DOTCOLOR?(u=240*(1-(d.point.value-this.valueMin)*this.scale.value),m=this._hsv2rgb(u,1,1),f=this._hsv2rgb(u,1,.8)):this.style===s.STYLE.DOTSIZE?(m=this.colorDot,f=this.colorDotBorder):(u=240*(1-(d.point.z-this.zMin)*this.scale.z/this.verticalRatio),m=this._hsv2rgb(u,1,1),f=this._hsv2rgb(u,1,.8)),i.lineWidth=1,i.strokeStyle=f,i.fillStyle=m,i.beginPath(),i.arc(d.screen.x,d.screen.y,p,0,2*Math.PI,!0),i.fill(),i.stroke()}}},s.prototype._redrawDataBar=function(){var t,e,i,o,n=this.frame.canvas,r=n.getContext("2d");if(!(void 0===this.dataPoints||this.dataPoints.length<=0)){for(t=0;t0&&(t=this.dataPoints[0],s.lineWidth=1,s.strokeStyle="blue",s.beginPath(),s.moveTo(t.screen.x,t.screen.y)),e=1;e0&&s.stroke()}},s.prototype._onMouseDown=function(t){if(t=t||window.event,this.leftButtonDown&&this._onMouseUp(t),this.leftButtonDown=t.which?1===t.which:1===t.button,this.leftButtonDown||this.touchDown){this.startMouseX=o(t),this.startMouseY=n(t),this.startStart=new Date(this.start),this.startEnd=new Date(this.end),this.startArmRotation=this.camera.getArmRotation(),this.frame.style.cursor="move";var e=this;this.onmousemove=function(t){e._onMouseMove(t)},this.onmouseup=function(t){e._onMouseUp(t)},d.addEventListener(document,"mousemove",e.onmousemove),d.addEventListener(document,"mouseup",e.onmouseup),d.preventDefault(t)}},s.prototype._onMouseMove=function(t){t=t||window.event;var e=parseFloat(o(t))-this.startMouseX,i=parseFloat(n(t))-this.startMouseY,s=this.startArmRotation.horizontal+e/200,r=this.startArmRotation.vertical+i/200,a=4,h=Math.sin(a/360*2*Math.PI);Math.abs(Math.sin(s))0?1:0>t?-1:0}var s=e[0],o=e[1],n=e[2],r=i((o.x-s.x)*(t.y-s.y)-(o.y-s.y)*(t.x-s.x)),a=i((n.x-o.x)*(t.y-o.y)-(n.y-o.y)*(t.x-o.x)),h=i((s.x-n.x)*(t.y-n.y)-(s.y-n.y)*(t.x-n.x));return!(0!=r&&0!=a&&r!=a||0!=a&&0!=h&&a!=h||0!=r&&0!=h&&r!=h)},s.prototype._dataPointFromXY=function(t,e){var i,o=100,n=null,r=null,a=null,h=new c(t,e);if(this.style===s.STYLE.BAR||this.style===s.STYLE.BARCOLOR||this.style===s.STYLE.BARSIZE)for(i=this.dataPoints.length-1;i>=0;i--){n=this.dataPoints[i];var d=n.surfaces;if(d)for(var l=d.length-1;l>=0;l--){var p=d[l],u=p.corners,m=[u[0].screen,u[1].screen,u[2].screen],f=[u[2].screen,u[3].screen,u[0].screen];if(this._insideTriangle(h,m)||this._insideTriangle(h,f))return n}}else for(i=0;ib)&&o>b&&(a=b,r=n)}}return r},s.prototype._showTooltip=function(t){var e,i,s;this.tooltip?(e=this.tooltip.dom.content,i=this.tooltip.dom.line,s=this.tooltip.dom.dot):(e=document.createElement("div"),e.style.position="absolute",e.style.padding="10px",e.style.border="1px solid #4d4d4d",e.style.color="#1a1a1a",e.style.background="rgba(255,255,255,0.7)",e.style.borderRadius="2px",e.style.boxShadow="5px 5px 10px rgba(128,128,128,0.5)",i=document.createElement("div"),i.style.position="absolute",i.style.height="40px",i.style.width="0",i.style.borderLeft="1px solid #4d4d4d",s=document.createElement("div"),s.style.position="absolute",s.style.height="0",s.style.width="0",s.style.border="5px solid #4d4d4d",s.style.borderRadius="5px",this.tooltip={dataPoint:null,dom:{content:e,line:i,dot:s}}),this._hideTooltip(),this.tooltip.dataPoint=t,e.innerHTML="function"==typeof this.showTooltip?this.showTooltip(t.point):"
x:"+t.point.x+"
y:"+t.point.y+"
z:"+t.point.z+"
",e.style.left="0",e.style.top="0",this.frame.appendChild(e),this.frame.appendChild(i),this.frame.appendChild(s);var o=e.offsetWidth,n=e.offsetHeight,r=i.offsetHeight,a=s.offsetWidth,h=s.offsetHeight,d=t.screen.x-o/2;d=Math.min(Math.max(d,10),this.frame.clientWidth-10-o),i.style.left=t.screen.x+"px",i.style.top=t.screen.y-r+"px",e.style.left=d+"px",e.style.top=t.screen.y-r-n+"px",s.style.left=t.screen.x-a/2+"px",s.style.top=t.screen.y-h/2+"px"},s.prototype._hideTooltip=function(){if(this.tooltip){this.tooltip.dataPoint=null;for(var t in this.tooltip.dom)if(this.tooltip.dom.hasOwnProperty(t)){var e=this.tooltip.dom[t];e&&e.parentNode&&e.parentNode.removeChild(e)}}},t.exports=s},function(t,e,i){function s(){this.armLocation=new o,this.armRotation={},this.armRotation.horizontal=0,this.armRotation.vertical=0,this.armLength=1.7,this.cameraLocation=new o,this.cameraRotation=new o(.5*Math.PI,0,0),this.calculateCameraOrientation()}var o=i(10);s.prototype.setArmLocation=function(t,e,i){this.armLocation.x=t,this.armLocation.y=e,this.armLocation.z=i,this.calculateCameraOrientation()},s.prototype.setArmRotation=function(t,e){void 0!==t&&(this.armRotation.horizontal=t),void 0!==e&&(this.armRotation.vertical=e,this.armRotation.vertical<0&&(this.armRotation.vertical=0),this.armRotation.vertical>.5*Math.PI&&(this.armRotation.vertical=.5*Math.PI)),(void 0!==t||void 0!==e)&&this.calculateCameraOrientation()},s.prototype.getArmRotation=function(){var t={};return t.horizontal=this.armRotation.horizontal,t.vertical=this.armRotation.vertical,t},s.prototype.setArmLength=function(t){void 0!==t&&(this.armLength=t,this.armLength<.71&&(this.armLength=.71),this.armLength>5&&(this.armLength=5),this.calculateCameraOrientation())},s.prototype.getArmLength=function(){return this.armLength},s.prototype.getCameraLocation=function(){return this.cameraLocation},s.prototype.getCameraRotation=function(){return this.cameraRotation},s.prototype.calculateCameraOrientation=function(){this.cameraLocation.x=this.armLocation.x-this.armLength*Math.sin(this.armRotation.horizontal)*Math.cos(this.armRotation.vertical),this.cameraLocation.y=this.armLocation.y-this.armLength*Math.cos(this.armRotation.horizontal)*Math.cos(this.armRotation.vertical),this.cameraLocation.z=this.armLocation.z+this.armLength*Math.sin(this.armRotation.vertical),this.cameraRotation.x=Math.PI/2-this.armRotation.vertical,this.cameraRotation.y=0,this.cameraRotation.z=-this.armRotation.horizontal},t.exports=s},function(t,e,i){function s(t,e,i){this.data=t,this.column=e,this.graph=i,this.index=void 0,this.value=void 0,this.values=i.getDistinctValues(t.get(),this.column),this.values.sort(function(t,e){return t>e?1:e>t?-1:0}),this.values.length>0&&this.selectValue(0),this.dataPoints=[],this.loaded=!1,this.onLoadCallback=void 0,i.animationPreload?(this.loaded=!1,this.loadInBackground()):this.loaded=!0}var o=i(4);s.prototype.isLoaded=function(){return this.loaded},s.prototype.getLoadedProgress=function(){for(var t=this.values.length,e=0;this.dataPoints[e];)e++;return Math.round(e/t*100)},s.prototype.getLabel=function(){return this.graph.filterLabel},s.prototype.getColumn=function(){return this.column},s.prototype.getSelectedValue=function(){return void 0===this.index?void 0:this.values[this.index]},s.prototype.getValues=function(){return this.values},s.prototype.getValue=function(t){if(t>=this.values.length)throw"Error: index out of range";return this.values[t]},s.prototype._getDataPoints=function(t){if(void 0===t&&(t=this.index),void 0===t)return[];var e;if(this.dataPoints[t])e=this.dataPoints[t];else{var i={};i.column=this.column,i.value=this.values[t];var s=new o(this.data,{filter:function(t){return t[i.column]==i.value}}).get();e=this.graph._getDataPoints(s),this.dataPoints[t]=e}return e},s.prototype.setOnLoadCallback=function(t){this.onLoadCallback=t},s.prototype.selectValue=function(t){if(t>=this.values.length)throw"Error: index out of range";this.index=t,this.value=this.values[t]},s.prototype.loadInBackground=function(t){void 0===t&&(t=0);var e=this.graph.frame;if(t0&&(t--,this.setIndex(t))},s.prototype.next=function(){var t=this.getIndex();t0?this.setIndex(0):this.index=void 0},s.prototype.setIndex=function(t){if(!(ts&&(s=0),s>this.values.length-1&&(s=this.values.length-1),s},s.prototype.indexToLeft=function(t){var e=parseFloat(this.frame.bar.style.width)-this.frame.slide.clientWidth-10,i=t/(this.values.length-1)*e,s=i+3;return s},s.prototype._onMouseMove=function(t){var e=t.clientX-this.startClientX,i=this.startSlideX+e,s=this.leftToIndex(i);this.setIndex(s),o.preventDefault()},s.prototype._onMouseUp=function(){this.frame.style.cursor="auto",o.removeEventListener(document,"mousemove",this.onmousemove),o.removeEventListener(document,"mouseup",this.onmouseup),o.preventDefault()},t.exports=s},function(t){function e(t,e,i,s){this._start=0,this._end=0,this._step=1,this.prettyStep=!0,this.precision=5,this._current=0,this.setRange(t,e,i,s)}e.prototype.setRange=function(t,e,i,s){this._start=t?t:0,this._end=e?e:0,this.setStep(i,s)},e.prototype.setStep=function(t,i){void 0===t||0>=t||(void 0!==i&&(this.prettyStep=i),this._step=this.prettyStep===!0?e.calculatePrettyStep(t):t)},e.calculatePrettyStep=function(t){var e=function(t){return Math.log(t)/Math.LN10},i=Math.pow(10,Math.round(e(t))),s=2*Math.pow(10,Math.round(e(t/2))),o=5*Math.pow(10,Math.round(e(t/5))),n=i;return Math.abs(s-t)<=Math.abs(n-t)&&(n=s),Math.abs(o-t)<=Math.abs(n-t)&&(n=o),0>=n&&(n=1),n},e.prototype.getCurrent=function(){return parseFloat(this._current.toPrecision(this.precision))},e.prototype.getStep=function(){return this._step},e.prototype.start=function(){this._current=this._start-this._start%this._step},e.prototype.next=function(){this._current+=this._step},e.prototype.end=function(){return this._current>this._end},t.exports=e},function(t,e,i){function s(t,e,i,r){if(!(this instanceof s))throw new SyntaxError("Constructor must be called with the new operator");if(!(Array.isArray(i)||i instanceof n)&&i instanceof Object){var h=r;r=i,i=h}var u=this;this.defaultOptions={start:null,end:null,autoResize:!0,orientation:"bottom",width:null,height:null,maxHeight:null,minHeight:null},this.options=o.deepExtend({},this.defaultOptions),this._create(t),this.components=[],this.body={dom:this.dom,domProps:this.props,emitter:{on:this.on.bind(this),off:this.off.bind(this),emit:this.emit.bind(this)},hiddenDates:[],util:{snap:null,toScreen:u._toScreen.bind(u),toGlobalScreen:u._toGlobalScreen.bind(u),toTime:u._toTime.bind(u),toGlobalTime:u._toGlobalTime.bind(u)}},this.range=new a(this.body),this.components.push(this.range),this.body.range=this.range,this.timeAxis=new d(this.body),this.components.push(this.timeAxis),this.body.util.snap=this.timeAxis.snap.bind(this.timeAxis),this.currentTime=new l(this.body),this.components.push(this.currentTime),this.customTime=new c(this.body),this.components.push(this.customTime),this.itemSet=new p(this.body),this.components.push(this.itemSet),this.itemsData=null,this.groupsData=null,r&&this.setOptions(r),i&&this.setGroups(i),e?this.setItems(e):this.redraw()}var o=(i(56),i(45),i(1)),n=i(3),r=i(4),a=i(17),h=i(46),d=i(30),l=i(21),c=i(22),p=i(27);s.prototype=new h,s.prototype.setItems=function(t){var e,i=null==this.itemsData;if(e=t?t instanceof n||t instanceof r?t:new n(t,{type:{start:"Date",end:"Date"}}):null,this.itemsData=e,this.itemSet&&this.itemSet.setItems(e),i)if(void 0!=this.options.start||void 0!=this.options.end){if(void 0==this.options.start||void 0==this.options.end)var s=this._getDataRange();var o=void 0!=this.options.start?this.options.start:s.start,a=void 0!=this.options.end?this.options.end:s.end;this.setWindow(o,a,{animate:!1})}else this.fit({animate:!1})},s.prototype.setGroups=function(t){var e;e=t?t instanceof n||t instanceof r?t:new n(t):null,this.groupsData=e,this.itemSet.setGroups(e)},s.prototype.setSelection=function(t,e){this.itemSet&&this.itemSet.setSelection(t),e&&e.focus&&this.focus(t,e)},s.prototype.getSelection=function(){return this.itemSet&&this.itemSet.getSelection()||[]},s.prototype.focus=function(t,e){if(this.itemsData&&void 0!=t){var i=Array.isArray(t)?t:[t],s=this.itemsData.getDataSet().get(i,{type:{start:"Date",end:"Date"}}),o=null,n=null;if(s.forEach(function(t){var e=t.start.valueOf(),i="end"in t?t.end.valueOf():t.start.valueOf();(null===o||o>e)&&(o=e),(null===n||i>n)&&(n=i)}),null!==o&&null!==n){var r=(o+n)/2,a=Math.max(this.range.end-this.range.start,1.1*(n-o)),h=e&&void 0!==e.animate?e.animate:!0;this.range.setRange(r-a/2,r+a/2,h)}}},s.prototype.getItemRange=function(){var t=this.itemsData.getDataSet(),e=null,i=null;if(t){var s=t.min("start");e=s?o.convert(s.start,"Date").valueOf():null;var n=t.max("start");n&&(i=o.convert(n.start,"Date").valueOf());var r=t.max("end");r&&(i=null==i?o.convert(r.end,"Date").valueOf():Math.max(i,o.convert(r.end,"Date").valueOf()))}return{min:null!=e?new Date(e):null,max:null!=i?new Date(i):null}},t.exports=s},function(t,e,i){function s(t,e,i,s){if(!(Array.isArray(i)||i instanceof n)&&i instanceof Object){var r=s;s=i,i=r}var h=this;this.defaultOptions={start:null,end:null,autoResize:!0,orientation:"bottom",width:null,height:null,maxHeight:null,minHeight:null},this.options=o.deepExtend({},this.defaultOptions),this._create(t),this.components=[],this.body={dom:this.dom,domProps:this.props,emitter:{on:this.on.bind(this),off:this.off.bind(this),emit:this.emit.bind(this)},hiddenDates:[],util:{snap:null,toScreen:h._toScreen.bind(h),toGlobalScreen:h._toGlobalScreen.bind(h),toTime:h._toTime.bind(h),toGlobalTime:h._toGlobalTime.bind(h)}},this.range=new a(this.body),this.components.push(this.range),this.body.range=this.range,this.timeAxis=new d(this.body),this.components.push(this.timeAxis),this.body.util.snap=this.timeAxis.snap.bind(this.timeAxis),this.currentTime=new l(this.body),this.components.push(this.currentTime),this.customTime=new c(this.body),this.components.push(this.customTime),this.linegraph=new p(this.body),this.components.push(this.linegraph),this.itemsData=null,this.groupsData=null,s&&this.setOptions(s),i&&this.setGroups(i),e?this.setItems(e):this.redraw()}var o=(i(56),i(45),i(1)),n=i(3),r=i(4),a=i(17),h=i(46),d=i(30),l=i(21),c=i(22),p=i(29);s.prototype=new h,s.prototype.setItems=function(t){var e,i=null==this.itemsData;if(e=t?t instanceof n||t instanceof r?t:new n(t,{type:{start:"Date",end:"Date"}}):null,this.itemsData=e,this.linegraph&&this.linegraph.setItems(e),i)if(void 0!=this.options.start||void 0!=this.options.end){var s=void 0!=this.options.start?this.options.start:null,o=void 0!=this.options.end?this.options.end:null;this.setWindow(s,o,{animate:!1})}else this.fit({animate:!1})},s.prototype.setGroups=function(t){var e;e=t?t instanceof n||t instanceof r?t:new n(t):null,this.groupsData=e,this.linegraph.setGroups(e)},s.prototype.getLegend=function(t,e,i){return void 0===e&&(e=15),void 0===i&&(i=15),void 0!==this.linegraph.groups[t]?this.linegraph.groups[t].getLegend(e,i):"cannot find group:"+t},s.prototype.isGroupVisible=function(t){return void 0!==this.linegraph.groups[t]?this.linegraph.groups[t].visible&&(void 0===this.linegraph.options.groups.visibility[t]||1==this.linegraph.options.groups.visibility[t]):!1},s.prototype.getItemRange=function(){var t=null,e=null;for(var i in this.linegraph.groups)if(this.linegraph.groups.hasOwnProperty(i)&&1==this.linegraph.groups[i].visible)for(var s=0;sr?r:t,e=null==e?r:r>e?r:e}return{min:null!=t?new Date(t):null,max:null!=e?new Date(e):null}},t.exports=s},function(t,e,i){var s=i(44);e.convertHiddenOptions=function(t,e){if(t.hiddenDates=[],e&&1==Array.isArray(e)){for(var i=0;i=4*a){var p=0,u=n.clone();switch(i[h].repeat){case"daily":d.day()!=l.day()&&(p=1),d.dayOfYear(o.dayOfYear()),d.year(o.year()),d.subtract(7,"days"),l.dayOfYear(o.dayOfYear()),l.year(o.year()),l.subtract(7-p,"days"),u.add(1,"weeks");break;case"weekly":var m=l.diff(d,"days"),f=d.day();d.date(o.date()),d.month(o.month()),d.year(o.year()),l=d.clone(),d.day(f),l.day(f),l.add(m,"days"),d.subtract(1,"weeks"),l.subtract(1,"weeks"),u.add(1,"weeks");break;case"monthly":d.month()!=l.month()&&(p=1),d.month(o.month()),d.year(o.year()),d.subtract(1,"months"),l.month(o.month()),l.year(o.year()),l.subtract(1,"months"),l.add(p,"months"),u.add(1,"months");break;case"yearly":d.year()!=l.year()&&(p=1),d.year(o.year()),d.subtract(1,"years"),l.year(o.year()),l.subtract(1,"years"),l.add(p,"years"),u.add(1,"years");break;default:return void console.log("Wrong repeat format, allowed are: daily, weekly, monthly, yearly. Given:",i[h].repeat)}for(;u>d;)switch(t.hiddenDates.push({start:d.valueOf(),end:l.valueOf()}),i[h].repeat){case"daily":d.add(1,"days"),l.add(1,"days");break;case"weekly":d.add(1,"weeks"),l.add(1,"weeks");break;case"monthly":d.add(1,"months"),l.add(1,"months");break;case"yearly":d.add(1,"y"),l.add(1,"y");break;default:return void console.log("Wrong repeat format, allowed are: daily, weekly, monthly, yearly. Given:",i[h].repeat)}t.hiddenDates.push({start:d.valueOf(),end:l.valueOf()})}}e.removeDuplicates(t);var g=e.isHidden(t.range.start,t.hiddenDates),v=e.isHidden(t.range.end,t.hiddenDates),y=t.range.start,b=t.range.end;1==g.hidden&&(y=1==t.range.startToFront?g.startDate-1:g.endDate+1),1==v.hidden&&(b=1==t.range.endToFront?v.startDate-1:v.endDate+1),(1==g.hidden||1==v.hidden)&&t.range._applyRange(y,b)}},e.removeDuplicates=function(t){for(var e=t.hiddenDates,i=[],s=0;s=e[s].start&&e[o].end<=e[s].end?e[o].remove=!0:e[o].start>=e[s].start&&e[o].start<=e[s].end?(e[s].end=e[o].end,e[o].remove=!0):e[o].end>=e[s].start&&e[o].end<=e[s].end&&(e[s].start=e[o].start,e[o].remove=!0));for(var s=0;s=r&&a>o){i=!0;break}}if(1==i&&o=e&&i>r&&(s+=r-n)}return s},e.correctTimeForHidden=function(t,i,o){return o=s(o).toDate().valueOf(),o-=e.getHiddenDurationBefore(t,i,o)},e.getHiddenDurationBefore=function(t,e,i){var o=0;i=s(i).toDate().valueOf();for(var n=0;n=e.start&&a=a&&(o+=a-r)}return o},e.getAccumulatedHiddenDuration=function(t,e,i){for(var s=0,o=0,n=e.start,r=0;r=e.start&&h=i)break;s+=h-a}}return s},e.snapAwayFromHidden=function(t,i,s,o){var n=e.isHidden(i,t);return 1==n.hidden?0>s?1==o?n.startDate-(n.endDate-i)-1:n.startDate-1:1==o?n.endDate+(i-n.startDate)+1:n.endDate+1:i},e.isHidden=function(t,e){for(var i=0;i=s&&o>t)return{hidden:!0,startDate:s,endDate:o}}return{hidden:!1,startDate:s,endDate:o}}},function(t){function e(t,e,i,s,o,n){this.current=0,this.autoScale=!0,this.stepIndex=0,this.step=1,this.scale=1,this.marginStart,this.marginEnd,this.deadSpace=0,this.majorSteps=[1,2,5,10],this.minorSteps=[.25,.5,1,2],this.alignZeros=n,this.setRange(t,e,i,s,o)}e.prototype.setRange=function(t,e,i,s,o){this._start=void 0===o.min?t:o.min,this._end=void 0===o.max?e:o.max,this._start==this._end&&(this._start-=.75,this._end+=1),1==this.autoScale&&this.setMinimumStep(i,s),this.setFirst(o)},e.prototype.setMinimumStep=function(t,e){var i=this._end-this._start,s=1.2*i,o=t*(s/e),n=Math.round(Math.log(s)/Math.LN10),r=-1,a=Math.pow(10,n),h=0;0>n&&(h=n);for(var d=!1,l=h;Math.abs(l)<=Math.abs(n);l++){a=Math.pow(10,l);for(var c=0;c=o){d=!0,r=c;break}}if(1==d)break}this.stepIndex=r,this.scale=a,this.step=a*this.minorSteps[r]},e.prototype.setFirst=function(t){void 0===t&&(t={});var e=void 0===t.min?this._start-2*this.scale*this.minorSteps[this.stepIndex]:t.min,i=void 0===t.max?this._end+this.scale*this.minorSteps[this.stepIndex]:t.max;this.marginEnd=void 0===t.max?this.roundToMinor(i):t.max,this.marginStart=void 0===t.min?this.roundToMinor(e):t.min,1==this.alignZeros&&(this.marginEnd-this.marginStart)%this.step!=0&&(this.marginEnd+=this.marginEnd%this.step),this.deadSpace=this.roundToMinor(i)-i+this.roundToMinor(e)-e,this.marginRange=this.marginEnd-this.marginStart,this.current=this.marginEnd},e.prototype.roundToMinor=function(t){var e=t-t%(this.scale*this.minorSteps[this.stepIndex]);return t%(this.scale*this.minorSteps[this.stepIndex])>.5*this.scale*this.minorSteps[this.stepIndex]?e+this.scale*this.minorSteps[this.stepIndex]:e},e.prototype.hasNext=function(){return this.current>=this.marginStart},e.prototype.next=function(){var t=this.current;this.current-=this.step,this.current==t&&(this.current=this._end)},e.prototype.previous=function(){this.current+=this.step,this.marginEnd+=this.step,this.marginRange=this.marginEnd-this.marginStart},e.prototype.getCurrent=function(t){var e=Math.abs(this.current)0;s--){if("0"!=i[s]){if("."==i[s]||","==i[s]){i=i.slice(0,s);break}break}i=i.slice(0,s)}}else{var o="",n=i.indexOf("e");if(-1!=n&&(o=i.slice(n),i=i.slice(0,n)),n=Math.max(i.indexOf(","),i.indexOf(".")),-1===n?(0!==t&&(i+="."),n=i.length+t):0!==t&&(n+=t+1),n>i.length)for(var r=n-i.length;r>0;r--)i+="0";else i=i.slice(0,n);i+=o}return i},e.prototype.snap=function(){},e.prototype.isMajor=function(){return this.current%(this.scale*this.majorSteps[this.stepIndex])==0},t.exports=e},function(t,e,i){function s(t,e){var i=a().hours(0).minutes(0).seconds(0).milliseconds(0);this.start=i.clone().add(-3,"days").valueOf(),this.end=i.clone().add(4,"days").valueOf(),this.body=t,this.deltaDifference=0,this.scaleOffset=0,this.startToFront=!1,this.endToFront=!0,this.defaultOptions={start:null,end:null,direction:"horizontal",moveable:!0,zoomable:!0,min:null,max:null,zoomMin:10,zoomMax:31536e10},this.options=r.extend({},this.defaultOptions),this.props={touch:{}},this.animateTimer=null,this.body.emitter.on("panstart",this._onDragStart.bind(this)),this.body.emitter.on("panmove",this._onDrag.bind(this)),this.body.emitter.on("panend",this._onDragEnd.bind(this)),this.body.emitter.on("press",this._onHold.bind(this)),this.body.emitter.on("mousewheel",this._onMouseWheel.bind(this)),this.body.emitter.on("touch",this._onTouch.bind(this)),this.body.emitter.on("pinch",this._onPinch.bind(this)),this.setOptions(e)}function o(t){if("horizontal"!=t&&"vertical"!=t)throw new TypeError('Unknown direction "'+t+'". Choose "horizontal" or "vertical".')}function n(t,e){return{x:t.x-r.getAbsoluteLeft(e),y:t.y-r.getAbsoluteTop(e)}}var r=i(1),a=(i(47),i(44)),h=i(20),d=i(15);s.prototype=new h,s.prototype.setOptions=function(t){if(t){var e=["direction","min","max","zoomMin","zoomMax","moveable","zoomable","activate","hiddenDates"];r.selectiveExtend(e,this.options,t),("start"in t||"end"in t)&&this.setRange(t.start,t.end)}},s.prototype.setRange=function(t,e,i,s){s!==!0&&(s=!1);var o=void 0!=t?r.convert(t,"Date").valueOf():null,n=void 0!=e?r.convert(e,"Date").valueOf():null;if(this._cancelAnimation(),i){var a=this,h=this.start,l=this.end,c="number"==typeof i?i:500,p=(new Date).valueOf(),u=!1,m=function(){if(!a.props.touch.dragging){var t=(new Date).valueOf(),e=t-p,i=e>c,g=i||null===o?o:r.easeInOutQuad(e,h,o,c),v=i||null===n?n:r.easeInOutQuad(e,l,n,c);f=a._applyRange(g,v),d.updateHiddenDates(a.body,a.options.hiddenDates),u=u||f,f&&a.body.emitter.emit("rangechange",{start:new Date(a.start),end:new Date(a.end),byUser:s}),i?u&&a.body.emitter.emit("rangechanged",{start:new Date(a.start),end:new Date(a.end),byUser:s}):a.animateTimer=setTimeout(m,20)}};return m()}var f=this._applyRange(o,n);if(d.updateHiddenDates(this.body,this.options.hiddenDates),f){var g={start:new Date(this.start),end:new Date(this.end),byUser:s};this.body.emitter.emit("rangechange",g),this.body.emitter.emit("rangechanged",g)}},s.prototype._cancelAnimation=function(){this.animateTimer&&(clearTimeout(this.animateTimer),this.animateTimer=null)},s.prototype._applyRange=function(t,e){var i,s=null!=t?r.convert(t,"Date").valueOf():this.start,o=null!=e?r.convert(e,"Date").valueOf():this.end,n=null!=this.options.max?r.convert(this.options.max,"Date").valueOf():null,a=null!=this.options.min?r.convert(this.options.min,"Date").valueOf():null;if(isNaN(s)||null===s)throw new Error('Invalid start "'+t+'"');if(isNaN(o)||null===o)throw new Error('Invalid end "'+e+'"');if(s>o&&(o=s),null!==a&&a>s&&(i=a-s,s+=i,o+=i,null!=n&&o>n&&(o=n)),null!==n&&o>n&&(i=o-n,s-=i,o-=i,null!=a&&a>s&&(s=a)),null!==this.options.zoomMin){var h=parseFloat(this.options.zoomMin);0>h&&(h=0),h>o-s&&(this.end-this.start===h?(s=this.start,o=this.end):(i=h-(o-s),s-=i/2,o+=i/2))}if(null!==this.options.zoomMax){var d=parseFloat(this.options.zoomMax);0>d&&(d=0),o-s>d&&(this.end-this.start===d?(s=this.start,o=this.end):(i=o-s-d,s+=i/2,o-=i/2))}var l=this.start!=s||this.end!=o;return s>=this.start&&s<=this.end||o>=this.start&&o<=this.end||this.start>=s&&this.start<=o||this.end>=s&&this.end<=o||this.body.emitter.emit("checkRangedItems"),this.start=s,this.end=o,l},s.prototype.getRange=function(){return{start:this.start,end:this.end}},s.prototype.conversion=function(t,e){return s.conversion(this.start,this.end,t,e)},s.conversion=function(t,e,i,s){return void 0===s&&(s=0),0!=i&&e-t!=0?{offset:t,scale:i/(e-t-s)}:{offset:0,scale:1}},s.prototype._onDragStart=function(t){this.deltaDifference=0,this.previousDelta=0,this.options.moveable&&this.props.touch.allowDragging&&(this.props.touch.start=this.start,this.props.touch.end=this.end,this.props.touch.dragging=!0,this.body.dom.root&&(this.body.dom.root.style.cursor="move"),t.preventDefault())},s.prototype._onDrag=function(t){if(this.options.moveable&&this.props.touch.allowDragging){var e=this.options.direction;o(e);var i="horizontal"==e?t.deltaX:t.deltaY;i-=this.deltaDifference;var s=this.props.touch.end-this.props.touch.start,n=d.getHiddenDurationBetween(this.body.hiddenDates,this.start,this.end);s-=n;var r="horizontal"==e?this.body.domProps.center.width:this.body.domProps.center.height,a=-i/r*s,h=this.props.touch.start+a,l=this.props.touch.end+a,c=d.snapAwayFromHidden(this.body.hiddenDates,h,this.previousDelta-i,!0),p=d.snapAwayFromHidden(this.body.hiddenDates,l,this.previousDelta-i,!0);if(c!=h||p!=l)return this.deltaDifference+=i,this.props.touch.start=c,this.props.touch.end=p,void this._onDrag(t);this.previousDelta=i,this._applyRange(h,l),this.body.emitter.emit("rangechange",{start:new Date(this.start),end:new Date(this.end),byUser:!0}),t.preventDefault()}},s.prototype._onDragEnd=function(){this.options.moveable&&this.props.touch.allowDragging&&(this.props.touch.dragging=!1,this.body.dom.root&&(this.body.dom.root.style.cursor="auto"),this.body.emitter.emit("rangechanged",{start:new Date(this.start),end:new Date(this.end),byUser:!0}))},s.prototype._onMouseWheel=function(t){if(this.options.zoomable&&this.options.moveable){var e=0;if(t.wheelDelta?e=t.wheelDelta/120:t.detail&&(e=-t.detail/3),e){var i;i=0>e?1-e/5:1/(1+e/5);var s=n({x:t.pageX,y:t.pageY},this.body.dom.center),o=this._pointerToDate(s);this.zoom(i,o,e)}t.preventDefault()}},s.prototype._onTouch=function(){this.props.touch.start=this.start,this.props.touch.end=this.end,this.props.touch.allowDragging=!0,this.props.touch.center=null,this.scaleOffset=0,this.deltaDifference=0},s.prototype._onHold=function(){this.props.touch.allowDragging=!1},s.prototype._onPinch=function(t){if(this.options.zoomable&&this.options.moveable){this.props.touch.allowDragging=!1,this.props.touch.center||(this.props.touch.center=n(t.center,this.body.dom.center));var e=1/(t.scale+this.scaleOffset),i=this._pointerToDate(this.props.touch.center),s=d.getHiddenDurationBetween(this.body.hiddenDates,this.start,this.end),o=d.getHiddenDurationBefore(this.body.hiddenDates,this,i),r=s-o,a=i-o+(this.props.touch.start-(i-o))*e,h=i+r+(this.props.touch.end-(i+r))*e;this.startToFront=0>=1-e,this.endToFront=0>=e-1;var l=d.snapAwayFromHidden(this.body.hiddenDates,a,1-e,!0),c=d.snapAwayFromHidden(this.body.hiddenDates,h,e-1,!0);(l!=a||c!=h)&&(this.props.touch.start=l,this.props.touch.end=c,this.scaleOffset=1-t.scale,a=l,h=c),this.setRange(a,h,!1,!0),this.startToFront=!1,this.endToFront=!0,t.preventDefault()}},s.prototype._pointerToDate=function(t){var e,i=this.options.direction;if(o(i),"horizontal"==i)return this.body.util.toTime(t.x).valueOf();var s=this.body.domProps.center.height;return e=this.conversion(s),t.y/e.scale+e.offset},s.prototype.zoom=function(t,e,i){null==e&&(e=(this.start+this.end)/2);var s=d.getHiddenDurationBetween(this.body.hiddenDates,this.start,this.end),o=d.getHiddenDurationBefore(this.body.hiddenDates,this,e),n=s-o,r=e-o+(this.start-(e-o))*t,a=e+n+(this.end-(e+n))*t;this.startToFront=i>0?!1:!0,this.endToFront=-i>0?!1:!0;var h=d.snapAwayFromHidden(this.body.hiddenDates,r,i,!0),l=d.snapAwayFromHidden(this.body.hiddenDates,a,-i,!0);(h!=r||l!=a)&&(r=h,a=l),this.setRange(r,a,!1,!0),this.startToFront=!1,this.endToFront=!0},s.prototype.move=function(t){var e=this.end-this.start,i=this.start+e*t,s=this.end+e*t;this.start=i,this.end=s},s.prototype.moveTo=function(t){var e=(this.start+this.end)/2,i=e-t,s=this.start-i,o=this.end-i;this.setRange(s,o)},t.exports=s},function(t,e){var i=.001;e.orderByStart=function(t){t.sort(function(t,e){return t.data.start-e.data.start})},e.orderByEnd=function(t){t.sort(function(t,e){var i="end"in t.data?t.data.end:t.data.start,s="end"in e.data?e.data.end:e.data.start;return i-s})},e.stack=function(t,i,s){var o,n;if(s)for(o=0,n=t.length;n>o;o++)t[o].top=null;for(o=0,n=t.length;n>o;o++){var r=t[o];if(r.stack&&null===r.top){r.top=i.axis;do{for(var a=null,h=0,d=t.length;d>h;h++){var l=t[h];if(null!==l.top&&l!==r&&l.stack&&e.collision(r,l,i.item)){a=l;break}}null!=a&&(r.top=a.top+a.height+i.item.vertical)}while(a)}}},e.nostack=function(t,e,i){var s,o,n;for(s=0,o=t.length;o>s;s++)if(void 0!==t[s].data.subgroup){n=e.axis;for(var r in i)i.hasOwnProperty(r)&&1==i[r].visible&&i[r].indexe.left&&t.top-s.vertical+ie.top}},function(t,e,i){function s(t,e,i,o){this.current=new Date,this._start=new Date,this._end=new Date,this.autoScale=!0,this.scale="day",this.step=1,this.setRange(t,e,i),this.switchedDay=!1,this.switchedMonth=!1,this.switchedYear=!1,this.hiddenDates=o,void 0===o&&(this.hiddenDates=[]),this.format=s.FORMAT}var o=i(44),n=i(15),r=i(1);s.FORMAT={minorLabels:{millisecond:"SSS",second:"s",minute:"HH:mm",hour:"HH:mm",weekday:"ddd D",day:"D",month:"MMM",year:"YYYY"},majorLabels:{millisecond:"HH:mm:ss",second:"D MMMM HH:mm",minute:"ddd D MMMM",hour:"ddd D MMMM",weekday:"MMMM YYYY",day:"MMMM YYYY",month:"YYYY",year:""}},s.prototype.setFormat=function(t){var e=r.deepExtend({},s.FORMAT);this.format=r.deepExtend(e,t)},s.prototype.setRange=function(t,e,i){if(!(t instanceof Date&&e instanceof Date))throw"No legal start or end date in method setRange";this._start=void 0!=t?new Date(t.valueOf()):new Date,this._end=void 0!=e?new Date(e.valueOf()):new Date,this.autoScale&&this.setMinimumStep(i)},s.prototype.first=function(){this.current=new Date(this._start.valueOf()),this.roundToMinor()},s.prototype.roundToMinor=function(){switch(this.scale){case"year":this.current.setFullYear(this.step*Math.floor(this.current.getFullYear()/this.step)),this.current.setMonth(0);case"month":this.current.setDate(1);case"day":case"weekday":this.current.setHours(0);case"hour":this.current.setMinutes(0);case"minute":this.current.setSeconds(0);case"second":this.current.setMilliseconds(0)}if(1!=this.step)switch(this.scale){case"millisecond":this.current.setMilliseconds(this.current.getMilliseconds()-this.current.getMilliseconds()%this.step);break;case"second":this.current.setSeconds(this.current.getSeconds()-this.current.getSeconds()%this.step);break;case"minute":this.current.setMinutes(this.current.getMinutes()-this.current.getMinutes()%this.step);break;case"hour":this.current.setHours(this.current.getHours()-this.current.getHours()%this.step);break;case"weekday":case"day":this.current.setDate(this.current.getDate()-1-(this.current.getDate()-1)%this.step+1);break;case"month":this.current.setMonth(this.current.getMonth()-this.current.getMonth()%this.step);break;case"year":this.current.setFullYear(this.current.getFullYear()-this.current.getFullYear()%this.step)}},s.prototype.hasNext=function(){return this.current.valueOf()<=this._end.valueOf()},s.prototype.next=function(){var t=this.current.valueOf();if(this.current.getMonth()<6)switch(this.scale){case"millisecond":this.current=new Date(this.current.valueOf()+this.step);break;case"second":this.current=new Date(this.current.valueOf()+1e3*this.step);break;case"minute":this.current=new Date(this.current.valueOf()+1e3*this.step*60);break;case"hour":this.current=new Date(this.current.valueOf()+1e3*this.step*60*60);var e=this.current.getHours();this.current.setHours(e-e%this.step);break;case"weekday":case"day":this.current.setDate(this.current.getDate()+this.step);break;case"month":this.current.setMonth(this.current.getMonth()+this.step);break;case"year":this.current.setFullYear(this.current.getFullYear()+this.step)}else switch(this.scale){case"millisecond":this.current=new Date(this.current.valueOf()+this.step);break;case"second":this.current.setSeconds(this.current.getSeconds()+this.step);break;case"minute":this.current.setMinutes(this.current.getMinutes()+this.step); +break;case"hour":this.current.setHours(this.current.getHours()+this.step);break;case"weekday":case"day":this.current.setDate(this.current.getDate()+this.step);break;case"month":this.current.setMonth(this.current.getMonth()+this.step);break;case"year":this.current.setFullYear(this.current.getFullYear()+this.step)}if(1!=this.step)switch(this.scale){case"millisecond":this.current.getMilliseconds()0&&(this.step=e),this.autoScale=!1},s.prototype.setAutoScale=function(t){this.autoScale=t},s.prototype.setMinimumStep=function(t){if(void 0!=t){var e=31104e6,i=2592e6,s=864e5,o=36e5,n=6e4,r=1e3,a=1;1e3*e>t&&(this.scale="year",this.step=1e3),500*e>t&&(this.scale="year",this.step=500),100*e>t&&(this.scale="year",this.step=100),50*e>t&&(this.scale="year",this.step=50),10*e>t&&(this.scale="year",this.step=10),5*e>t&&(this.scale="year",this.step=5),e>t&&(this.scale="year",this.step=1),3*i>t&&(this.scale="month",this.step=3),i>t&&(this.scale="month",this.step=1),5*s>t&&(this.scale="day",this.step=5),2*s>t&&(this.scale="day",this.step=2),s>t&&(this.scale="day",this.step=1),s/2>t&&(this.scale="weekday",this.step=1),4*o>t&&(this.scale="hour",this.step=4),o>t&&(this.scale="hour",this.step=1),15*n>t&&(this.scale="minute",this.step=15),10*n>t&&(this.scale="minute",this.step=10),5*n>t&&(this.scale="minute",this.step=5),n>t&&(this.scale="minute",this.step=1),15*r>t&&(this.scale="second",this.step=15),10*r>t&&(this.scale="second",this.step=10),5*r>t&&(this.scale="second",this.step=5),r>t&&(this.scale="second",this.step=1),200*a>t&&(this.scale="millisecond",this.step=200),100*a>t&&(this.scale="millisecond",this.step=100),50*a>t&&(this.scale="millisecond",this.step=50),10*a>t&&(this.scale="millisecond",this.step=10),5*a>t&&(this.scale="millisecond",this.step=5),a>t&&(this.scale="millisecond",this.step=1)}},s.prototype.snap=function(t){var e=new Date(t.valueOf());if("year"==this.scale){var i=e.getFullYear()+Math.round(e.getMonth()/12);e.setFullYear(Math.round(i/this.step)*this.step),e.setMonth(0),e.setDate(0),e.setHours(0),e.setMinutes(0),e.setSeconds(0),e.setMilliseconds(0)}else if("month"==this.scale)e.getDate()>15?(e.setDate(1),e.setMonth(e.getMonth()+1)):e.setDate(1),e.setHours(0),e.setMinutes(0),e.setSeconds(0),e.setMilliseconds(0);else if("day"==this.scale){switch(this.step){case 5:case 2:e.setHours(24*Math.round(e.getHours()/24));break;default:e.setHours(12*Math.round(e.getHours()/12))}e.setMinutes(0),e.setSeconds(0),e.setMilliseconds(0)}else if("weekday"==this.scale){switch(this.step){case 5:case 2:e.setHours(12*Math.round(e.getHours()/12));break;default:e.setHours(6*Math.round(e.getHours()/6))}e.setMinutes(0),e.setSeconds(0),e.setMilliseconds(0)}else if("hour"==this.scale){switch(this.step){case 4:e.setMinutes(60*Math.round(e.getMinutes()/60));break;default:e.setMinutes(30*Math.round(e.getMinutes()/30))}e.setSeconds(0),e.setMilliseconds(0)}else if("minute"==this.scale){switch(this.step){case 15:case 10:e.setMinutes(5*Math.round(e.getMinutes()/5)),e.setSeconds(0);break;case 5:e.setSeconds(60*Math.round(e.getSeconds()/60));break;default:e.setSeconds(30*Math.round(e.getSeconds()/30))}e.setMilliseconds(0)}else if("second"==this.scale)switch(this.step){case 15:case 10:e.setSeconds(5*Math.round(e.getSeconds()/5)),e.setMilliseconds(0);break;case 5:e.setMilliseconds(1e3*Math.round(e.getMilliseconds()/1e3));break;default:e.setMilliseconds(500*Math.round(e.getMilliseconds()/500))}else if("millisecond"==this.scale){var s=this.step>5?this.step/2:1;e.setMilliseconds(Math.round(e.getMilliseconds()/s)*s)}return e},s.prototype.isMajor=function(){if(1==this.switchedYear)switch(this.switchedYear=!1,this.scale){case"year":case"month":case"weekday":case"day":case"hour":case"minute":case"second":case"millisecond":return!0;default:return!1}else if(1==this.switchedMonth)switch(this.switchedMonth=!1,this.scale){case"weekday":case"day":case"hour":case"minute":case"second":case"millisecond":return!0;default:return!1}else if(1==this.switchedDay)switch(this.switchedDay=!1,this.scale){case"millisecond":case"second":case"minute":case"hour":return!0;default:return!1}switch(this.scale){case"millisecond":return 0==this.current.getMilliseconds();case"second":return 0==this.current.getSeconds();case"minute":return 0==this.current.getHours()&&0==this.current.getMinutes();case"hour":return 0==this.current.getHours();case"weekday":case"day":return 1==this.current.getDate();case"month":return 0==this.current.getMonth();case"year":return!1;default:return!1}},s.prototype.getLabelMinor=function(t){void 0==t&&(t=this.current);var e=this.format.minorLabels[this.scale];return e&&e.length>0?o(t).format(e):""},s.prototype.getLabelMajor=function(t){void 0==t&&(t=this.current);var e=this.format.majorLabels[this.scale];return e&&e.length>0?o(t).format(e):""},s.prototype.getClassName=function(){function t(t){return t/h%2==0?" even":" odd"}function e(t){return t.isSame(new Date,"day")?" today":t.isSame(o().add(1,"day"),"day")?" tomorrow":t.isSame(o().add(-1,"day"),"day")?" yesterday":""}function i(t){return t.isSame(new Date,"week")?" current-week":""}function s(t){return t.isSame(new Date,"month")?" current-month":""}function n(t){return t.isSame(new Date,"year")?" current-year":""}var r=o(this.current),a=r.locale?r.locale("en"):r.lang("en"),h=this.step;switch(this.scale){case"millisecond":return t(a.milliseconds()).trim();case"second":return t(a.seconds()).trim();case"minute":return t(a.minutes()).trim();case"hour":var d=a.hours();return 4==this.step&&(d=d+"-"+(d+4)),d+"h"+e(a)+t(a.hours());case"weekday":return a.format("dddd").toLowerCase()+e(a)+i(a)+t(a.date());case"day":var l=a.date(),c=a.format("MMMM").toLowerCase();return"day"+l+" "+c+s(a)+t(l-1);case"month":return a.format("MMMM").toLowerCase()+s(a)+t(a.month());case"year":var p=a.year();return"year"+p+n(a)+t(p);default:return""}},t.exports=s},function(t){function e(){this.options=null,this.props=null}e.prototype.setOptions=function(t){t&&util.extend(this.options,t)},e.prototype.redraw=function(){return!1},e.prototype.destroy=function(){},e.prototype._isResized=function(){var t=this.props._previousWidth!==this.props.width||this.props._previousHeight!==this.props.height;return this.props._previousWidth=this.props.width,this.props._previousHeight=this.props.height,t},t.exports=e},function(t,e,i){function s(t,e){this.body=t,this.defaultOptions={showCurrentTime:!0,locales:a,locale:"en"},this.options=o.extend({},this.defaultOptions),this.offset=0,this._create(),this.setOptions(e)}var o=i(1),n=i(20),r=i(44),a=i(48);s.prototype=new n,s.prototype._create=function(){var t=document.createElement("div");t.className="currenttime",t.style.position="absolute",t.style.top="0px",t.style.height="100%",this.bar=t},s.prototype.destroy=function(){this.options.showCurrentTime=!1,this.redraw(),this.body=null},s.prototype.setOptions=function(t){t&&o.selectiveExtend(["showCurrentTime","locale","locales"],this.options,t)},s.prototype.redraw=function(){if(this.options.showCurrentTime){var t=this.body.dom.backgroundVertical;this.bar.parentNode!=t&&(this.bar.parentNode&&this.bar.parentNode.removeChild(this.bar),t.appendChild(this.bar),this.start());var e=new Date((new Date).valueOf()+this.offset),i=this.body.util.toScreen(e),s=this.options.locales[this.options.locale],o=s.current+" "+s.time+": "+r(e).format("dddd, MMMM Do YYYY, H:mm:ss");o=o.charAt(0).toUpperCase()+o.substring(1),this.bar.style.left=i+"px",this.bar.title=o}else this.bar.parentNode&&this.bar.parentNode.removeChild(this.bar),this.stop();return!1},s.prototype.start=function(){function t(){e.stop();var i=e.body.range.conversion(e.body.domProps.center.width).scale,s=1/i/10;30>s&&(s=30),s>1e3&&(s=1e3),e.redraw(),e.currentTimeTimer=setTimeout(t,s)}var e=this;t()},s.prototype.stop=function(){void 0!==this.currentTimeTimer&&(clearTimeout(this.currentTimeTimer),delete this.currentTimeTimer)},s.prototype.setCurrentTime=function(t){var e=o.convert(t,"Date").valueOf(),i=(new Date).valueOf();this.offset=e-i,this.redraw()},s.prototype.getCurrentTime=function(){return new Date((new Date).valueOf()+this.offset)},t.exports=s},function(t,e,i){function s(t,e){this.body=t,this.defaultOptions={showCustomTime:!1,locales:h,locale:"en"},this.options=n.extend({},this.defaultOptions),this.customTime=new Date,this.eventParams={},this._create(),this.setOptions(e)}var o=i(45),n=i(1),r=i(20),a=i(44),h=i(48);s.prototype=new r,s.prototype.setOptions=function(t){t&&n.selectiveExtend(["showCustomTime","locale","locales"],this.options,t)},s.prototype._create=function(){var t=document.createElement("div");t.className="customtime",t.style.position="absolute",t.style.top="0px",t.style.height="100%",this.bar=t;var e=document.createElement("div");e.style.position="relative",e.style.top="0px",e.style.left="-10px",e.style.height="100%",e.style.width="20px",t.appendChild(e),this.hammer=new o(e),this.hammer.on("panstart",this._onDragStart.bind(this)),this.hammer.on("panmove",this._onDrag.bind(this)),this.hammer.on("panend",this._onDragEnd.bind(this)),this.hammer.on("pan",function(t){t.preventDefault()})},s.prototype.destroy=function(){this.options.showCustomTime=!1,this.redraw(),this.hammer.enable(!1),this.hammer=null,this.body=null},s.prototype.redraw=function(){if(this.options.showCustomTime){var t=this.body.dom.backgroundVertical;this.bar.parentNode!=t&&(this.bar.parentNode&&this.bar.parentNode.removeChild(this.bar),t.appendChild(this.bar));var e=this.body.util.toScreen(this.customTime),i=this.options.locales[this.options.locale],s=i.time+": "+a(this.customTime).format("dddd, MMMM Do YYYY, H:mm:ss");s=s.charAt(0).toUpperCase()+s.substring(1),this.bar.style.left=e+"px",this.bar.title=s}else this.bar.parentNode&&this.bar.parentNode.removeChild(this.bar);return!1},s.prototype.setCustomTime=function(t){this.customTime=n.convert(t,"Date"),this.redraw()},s.prototype.getCustomTime=function(){return new Date(this.customTime.valueOf())},s.prototype._onDragStart=function(t){this.eventParams.dragging=!0,this.eventParams.customTime=this.customTime,t.stopPropagation(),t.preventDefault()},s.prototype._onDrag=function(t){if(this.eventParams.dragging){var e=this.body.util.toScreen(this.eventParams.customTime)+t.deltaX,i=this.body.util.toTime(e);this.setCustomTime(i),this.body.emitter.emit("timechange",{time:new Date(this.customTime.valueOf())}),t.stopPropagation(),t.preventDefault()}},s.prototype._onDragEnd=function(t){this.eventParams.dragging&&(this.body.emitter.emit("timechanged",{time:new Date(this.customTime.valueOf())}),t.stopPropagation(),t.preventDefault())},t.exports=s},function(t,e,i){function s(t,e,i,s){this.id=o.randomUUID(),this.body=t,this.defaultOptions={orientation:"left",showMinorLabels:!0,showMajorLabels:!0,icons:!0,majorLinesOffset:7,minorLinesOffset:4,labelOffsetX:10,labelOffsetY:2,iconWidth:20,width:"40px",visible:!0,alignZeros:!0,customRange:{left:{min:void 0,max:void 0},right:{min:void 0,max:void 0}},title:{left:{text:void 0},right:{text:void 0}},format:{left:{decimals:void 0},right:{decimals:void 0}}},this.linegraphOptions=s,this.linegraphSVG=i,this.props={},this.DOMelements={lines:{},labels:{},title:{}},this.dom={},this.range={start:0,end:0},this.options=o.extend({},this.defaultOptions),this.conversionFactor=1,this.setOptions(e),this.width=Number((""+this.options.width).replace("px","")),this.minWidth=this.width,this.height=this.linegraphSVG.offsetHeight,this.hidden=!1,this.stepPixels=25,this.stepPixelsForced=25,this.zeroCrossing=-1,this.lineOffset=0,this.master=!0,this.svgElements={},this.iconsRemoved=!1,this.groups={},this.amountOfGroups=0,this._create();var n=this;this.body.emitter.on("verticalDrag",function(){n.dom.lineContainer.style.top=n.body.domProps.scrollTop+"px"})}var o=i(1),n=i(2),r=i(20),a=i(16);s.prototype=new r,s.prototype.addGroup=function(t,e){this.groups.hasOwnProperty(t)||(this.groups[t]=e),this.amountOfGroups+=1},s.prototype.updateGroup=function(t,e){this.groups[t]=e},s.prototype.removeGroup=function(t){this.groups.hasOwnProperty(t)&&(delete this.groups[t],this.amountOfGroups-=1)},s.prototype.setOptions=function(t){if(t){var e=!1;this.options.orientation!=t.orientation&&void 0!==t.orientation&&(e=!0);var i=["orientation","showMinorLabels","showMajorLabels","icons","majorLinesOffset","minorLinesOffset","labelOffsetX","labelOffsetY","iconWidth","width","visible","customRange","title","format","alignZeros"];o.selectiveExtend(i,this.options,t),this.minWidth=Number((""+this.options.width).replace("px","")),1==e&&this.dom.frame&&(this.hide(),this.show())}},s.prototype._create=function(){this.dom.frame=document.createElement("div"),this.dom.frame.style.width=this.options.width,this.dom.frame.style.height=this.height,this.dom.lineContainer=document.createElement("div"),this.dom.lineContainer.style.width="100%",this.dom.lineContainer.style.height=this.height,this.dom.lineContainer.style.position="relative",this.svg=document.createElementNS("http://www.w3.org/2000/svg","svg"),this.svg.style.position="absolute",this.svg.style.top="0px",this.svg.style.height="100%",this.svg.style.width="100%",this.svg.style.display="block",this.dom.frame.appendChild(this.svg)},s.prototype._redrawGroupIcons=function(){n.prepareElements(this.svgElements);var t,e=this.options.iconWidth,i=15,s=4,o=s+.5*i;t="left"==this.options.orientation?s:this.width-e-s;for(var r in this.groups)this.groups.hasOwnProperty(r)&&(1!=this.groups[r].visible||void 0!==this.linegraphOptions.visibility[r]&&1!=this.linegraphOptions.visibility[r]||(this.groups[r].drawIcon(t,o,this.svgElements,this.svg,e,i),o+=i+s));n.cleanupElements(this.svgElements),this.iconsRemoved=!1},s.prototype._cleanupIcons=function(){0==this.iconsRemoved&&(n.prepareElements(this.svgElements),n.cleanupElements(this.svgElements),this.iconsRemoved=!0)},s.prototype.show=function(){this.hidden=!1,this.dom.frame.parentNode||("left"==this.options.orientation?this.body.dom.left.appendChild(this.dom.frame):this.body.dom.right.appendChild(this.dom.frame)),this.dom.lineContainer.parentNode||this.body.dom.backgroundHorizontal.appendChild(this.dom.lineContainer)},s.prototype.hide=function(){this.hidden=!0,this.dom.frame.parentNode&&this.dom.frame.parentNode.removeChild(this.dom.frame),this.dom.lineContainer.parentNode&&this.dom.lineContainer.parentNode.removeChild(this.dom.lineContainer)},s.prototype.setRange=function(t,e){0==this.master&&1==this.options.alignZeros&&-1!=this.zeroCrossing&&t>0&&(t=0),this.range.start=t,this.range.end=e},s.prototype.redraw=function(){var t=!1,e=0;this.dom.lineContainer.style.top=this.body.domProps.scrollTop+"px";for(var i in this.groups)this.groups.hasOwnProperty(i)&&(1!=this.groups[i].visible||void 0!==this.linegraphOptions.visibility[i]&&1!=this.linegraphOptions.visibility[i]||e++);if(0==this.amountOfGroups||0==e)this.hide();else{this.show(),this.height=Number(this.linegraphSVG.style.height.replace("px","")),this.dom.lineContainer.style.height=this.height+"px",this.width=1==this.options.visible?Number((""+this.options.width).replace("px","")):0;var s=this.props,o=this.dom.frame;o.className="dataaxis",this._calculateCharSize();var n=this.options.orientation,r=this.options.showMinorLabels,a=this.options.showMajorLabels;s.minorLabelHeight=r?s.minorCharHeight:0,s.majorLabelHeight=a?s.majorCharHeight:0,s.minorLineWidth=this.body.dom.backgroundHorizontal.offsetWidth-this.lineOffset-this.width+2*this.options.minorLinesOffset,s.minorLineHeight=1,s.majorLineWidth=this.body.dom.backgroundHorizontal.offsetWidth-this.lineOffset-this.width+2*this.options.majorLinesOffset,s.majorLineHeight=1,"left"==n?(o.style.top="0",o.style.left="0",o.style.bottom="",o.style.width=this.width+"px",o.style.height=this.height+"px",this.props.width=this.body.domProps.left.width,this.props.height=this.body.domProps.left.height):(o.style.top="",o.style.bottom="0",o.style.left="0",o.style.width=this.width+"px",o.style.height=this.height+"px",this.props.width=this.body.domProps.right.width,this.props.height=this.body.domProps.right.height),t=this._redrawLabels(),t=this._isResized()||t,1==this.options.icons?this._redrawGroupIcons():this._cleanupIcons(),this._redrawTitle(n)}return t},s.prototype._redrawLabels=function(){var t=!1;n.prepareElements(this.DOMelements.lines),n.prepareElements(this.DOMelements.labels);var e=this.options.orientation,i=this.master?this.props.majorCharHeight||10:this.stepPixelsForced,s=new a(this.range.start,this.range.end,i,this.dom.frame.offsetHeight,this.options.customRange[this.options.orientation],0==this.master&&this.options.alignZeros);this.step=s;var o=(this.dom.frame.offsetHeight-s.deadSpace*(this.dom.frame.offsetHeight/s.marginRange))/((s.marginRange-s.deadSpace)/s.step);this.stepPixels=o;var r=this.height/o,h=0;if(0==this.master){o=this.stepPixelsForced,h=Math.round(this.dom.frame.offsetHeight/o-r);for(var d=0;.5*h>d;d++)s.previous();if(r=this.height/o,-1!=this.zeroCrossing&&1==this.options.alignZeros){var l=s.marginEnd/s.step-this.zeroCrossing;if(l>0)for(var d=0;l>d;d++)s.next();else if(0>l)for(var d=0;-l>d;d++)s.previous()}}else r+=.25;this.valueAtZero=s.marginEnd;var c,p=0,u=1;void 0!==this.options.format[e]&&(c=this.options.format[e].decimals),this.maxLabelSize=0;for(var m=0;u=0&&this._redrawLabel(m-2,s.getCurrent(c),e,"yAxis major",this.props.majorCharHeight),this._redrawLine(m,e,"grid horizontal major",this.options.majorLinesOffset,this.props.majorLineWidth)):this._redrawLine(m,e,"grid horizontal minor",this.options.minorLinesOffset,this.props.minorLineWidth),1==this.master&&0==s.current&&(this.zeroCrossing=u),u++}this.conversionFactor=0==this.master?m/(this.valueAtZero-s.current):this.dom.frame.offsetHeight/s.marginRange;var g=0;void 0!==this.options.title[e]&&void 0!==this.options.title[e].text&&(g=this.props.titleCharHeight);var v=1==this.options.icons?Math.max(this.options.iconWidth,g)+this.options.labelOffsetX+15:g+this.options.labelOffsetX+15;return this.maxLabelSize>this.width-v&&1==this.options.visible?(this.width=this.maxLabelSize+v,this.options.width=this.width+"px",n.cleanupElements(this.DOMelements.lines),n.cleanupElements(this.DOMelements.labels),this.redraw(),t=!0):this.maxLabelSizethis.minWidth?(this.width=Math.max(this.minWidth,this.maxLabelSize+v),this.options.width=this.width+"px",n.cleanupElements(this.DOMelements.lines),n.cleanupElements(this.DOMelements.labels),this.redraw(),t=!0):(n.cleanupElements(this.DOMelements.lines),n.cleanupElements(this.DOMelements.labels),t=!1),t},s.prototype.convertValue=function(t){var e=this.valueAtZero-t,i=e*this.conversionFactor;return i},s.prototype._redrawLabel=function(t,e,i,s,o){var r=n.getDOMElement("div",this.DOMelements.labels,this.dom.frame);r.className=s,r.innerHTML=e,"left"==i?(r.style.left="-"+this.options.labelOffsetX+"px",r.style.textAlign="right"):(r.style.right="-"+this.options.labelOffsetX+"px",r.style.textAlign="left"),r.style.top=t-.5*o+this.options.labelOffsetY+"px",e+="";var a=Math.max(this.props.majorCharWidth,this.props.minorCharWidth);this.maxLabelSized;d++){var c=this.visibleItems[d];c.repositionY(e)}return s},s.prototype._calculateHeight=function(t){var e,i=this.visibleItems;this.resetSubgroups();var s=this;if(i.length){var n=i[0].top,r=i[0].top+i[0].height;if(o.forEach(i,function(t){n=Math.min(n,t.top),r=Math.max(r,t.top+t.height),void 0!==t.data.subgroup&&(s.subgroups[t.data.subgroup].height=Math.max(s.subgroups[t.data.subgroup].height,t.height),s.subgroups[t.data.subgroup].visible=!0)}),n>t.axis){var a=n-t.axis;r-=a,o.forEach(i,function(t){t.top-=a})}e=r+t.item.vertical/2}else e=t.axis+t.item.vertical;return e=Math.max(e,this.props.label.height)},s.prototype.show=function(){this.dom.label.parentNode||this.itemSet.dom.labelSet.appendChild(this.dom.label),this.dom.foreground.parentNode||this.itemSet.dom.foreground.appendChild(this.dom.foreground),this.dom.background.parentNode||this.itemSet.dom.background.appendChild(this.dom.background),this.dom.axis.parentNode||this.itemSet.dom.axis.appendChild(this.dom.axis)},s.prototype.hide=function(){var t=this.dom.label;t.parentNode&&t.parentNode.removeChild(t);var e=this.dom.foreground;e.parentNode&&e.parentNode.removeChild(e);var i=this.dom.background;i.parentNode&&i.parentNode.removeChild(i);var s=this.dom.axis;s.parentNode&&s.parentNode.removeChild(s)},s.prototype.add=function(t){if(this.items[t.id]=t,t.setParent(this),void 0!==t.data.subgroup&&(void 0===this.subgroups[t.data.subgroup]&&(this.subgroups[t.data.subgroup]={height:0,visible:!1,index:this.subgroupIndex,items:[]},this.subgroupIndex++),this.subgroups[t.data.subgroup].items.push(t)),this.orderSubgroups(),-1==this.visibleItems.indexOf(t)){var e=this.itemSet.body.range;this._checkIfVisible(t,this.visibleItems,e)}},s.prototype.orderSubgroups=function(){if(void 0!==this.subgroupOrderer){var t=[];if("string"==typeof this.subgroupOrderer){for(var e in this.subgroups)t.push({subgroup:e,sortField:this.subgroups[e].items[0].data[this.subgroupOrderer]});t.sort(function(t,e){return t.sortField-e.sortField})}else if("function"==typeof this.subgroupOrderer){for(var e in this.subgroups)t.push(this.subgroups[e].items[0].data);t.sort(this.subgroupOrderer)}if(t.length>0)for(var i=0;it?-1:l>=t?0:1};if(e.length>0)for(n=0;nl}),1==this.checkRangedItems)for(this.checkRangedItems=!1,n=0;nl})}for(n=0;n=0&&(n=e[r],!o(n));r--)void 0===s[n.id]&&(s[n.id]=!0,i.push(n));for(r=t+1;rs;s++){var n=this.visibleItems[s];n.repositionY(e)}return i},s.prototype.show=function(){this.dom.background.parentNode||this.itemSet.dom.background.appendChild(this.dom.background)},t.exports=s},function(t,e,i){function s(t,e){this.body=t,this.defaultOptions={type:null,orientation:"bottom",align:"auto",stack:!0,groupOrder:null,selectable:!0,editable:{updateTime:!1,updateGroup:!1,add:!1,remove:!1},onAdd:function(t,e){e(t)},onUpdate:function(t,e){e(t)},onMove:function(t,e){e(t)},onRemove:function(t,e){e(t)},onMoving:function(t,e){e(t)},margin:{item:{horizontal:10,vertical:10},axis:20},padding:5},this.options=n.extend({},this.defaultOptions),this.itemOptions={type:{start:"Date",end:"Date"}},this.conversion={toScreen:t.util.toScreen,toTime:t.util.toTime},this.dom={},this.props={},this.hammer=null;var i=this;this.itemsData=null,this.groupsData=null,this.itemListeners={add:function(t,e){i._onAdd(e.items)},update:function(t,e){i._onUpdate(e.items)},remove:function(t,e){i._onRemove(e.items)}},this.groupListeners={add:function(t,e){i._onAddGroups(e.items)},update:function(t,e){i._onUpdateGroups(e.items)},remove:function(t,e){i._onRemoveGroups(e.items)}},this.items={},this.groups={},this.groupIds=[],this.selection=[],this.stackDirty=!0,this.touchParams={},this._create(),this.setOptions(e)}var o=i(45),n=i(1),r=i(3),a=i(4),h=i(20),d=i(25),l=i(26),c=i(33),p=i(34),u=i(35),m=i(32),f="__ungrouped__",g="__background__";s.prototype=new h,s.types={background:m,box:c,range:u,point:p},s.prototype._create=function(){var t=document.createElement("div");t.className="itemset",t["timeline-itemset"]=this,this.dom.frame=t;var e=document.createElement("div");e.className="background",t.appendChild(e),this.dom.background=e;var i=document.createElement("div");i.className="foreground",t.appendChild(i),this.dom.foreground=i;var s=document.createElement("div");s.className="axis",this.dom.axis=s;var n=document.createElement("div");n.className="labelset",this.dom.labelSet=n,this._updateUngrouped();var r=new l(g,null,this);r.show(),this.groups[g]=r,this.hammer=new o(this.body.dom.centerContainer),this.hammer.on("hammer.input",function(t){t.isFirst&&this._onTouch(t)}.bind(this)),this.hammer.on("panstart",this._onDragStart.bind(this)),this.hammer.on("panmove",this._onDrag.bind(this)),this.hammer.on("panend",this._onDragEnd.bind(this)),this.hammer.on("tap",this._onSelectItem.bind(this)),this.hammer.on("press",this._onMultiSelectItem.bind(this)),this.hammer.on("doubletap",this._onAddItem.bind(this)),this.show()},s.prototype.setOptions=function(t){if(t){var e=["type","align","orientation","padding","stack","selectable","groupOrder","dataAttributes","template","hide"];n.selectiveExtend(e,this.options,t),"margin"in t&&("number"==typeof t.margin?(this.options.margin.axis=t.margin,this.options.margin.item.horizontal=t.margin,this.options.margin.item.vertical=t.margin):"object"==typeof t.margin&&(n.selectiveExtend(["axis"],this.options.margin,t.margin),"item"in t.margin&&("number"==typeof t.margin.item?(this.options.margin.item.horizontal=t.margin.item,this.options.margin.item.vertical=t.margin.item):"object"==typeof t.margin.item&&n.selectiveExtend(["horizontal","vertical"],this.options.margin.item,t.margin.item)))),"editable"in t&&("boolean"==typeof t.editable?(this.options.editable.updateTime=t.editable,this.options.editable.updateGroup=t.editable,this.options.editable.add=t.editable,this.options.editable.remove=t.editable):"object"==typeof t.editable&&n.selectiveExtend(["updateTime","updateGroup","add","remove"],this.options.editable,t.editable));var i=function(e){var i=t[e];if(i){if(!(i instanceof Function))throw new Error("option "+e+" must be a function "+e+"(item, callback)");this.options[e]=i}}.bind(this);["onAdd","onUpdate","onRemove","onMove","onMoving"].forEach(i),this.markDirty()}},s.prototype.markDirty=function(){this.groupIds=[],this.stackDirty=!0},s.prototype.destroy=function(){this.hide(),this.setItems(null),this.setGroups(null),this.hammer=null,this.body=null,this.conversion=null},s.prototype.hide=function(){this.dom.frame.parentNode&&this.dom.frame.parentNode.removeChild(this.dom.frame),this.dom.axis.parentNode&&this.dom.axis.parentNode.removeChild(this.dom.axis),this.dom.labelSet.parentNode&&this.dom.labelSet.parentNode.removeChild(this.dom.labelSet)},s.prototype.show=function(){this.dom.frame.parentNode||this.body.dom.center.appendChild(this.dom.frame),this.dom.axis.parentNode||this.body.dom.backgroundVertical.appendChild(this.dom.axis),this.dom.labelSet.parentNode||this.body.dom.left.appendChild(this.dom.labelSet)},s.prototype.setSelection=function(t){var e,i,s,o;for(void 0==t&&(t=[]),Array.isArray(t)||(t=[t]),e=0,i=this.selection.length;i>e;e++)s=this.selection[e],o=this.items[s],o&&o.unselect();for(this.selection=[],e=0,i=t.length;i>e;e++)s=t[e],o=this.items[s],o&&(this.selection.push(s),o.select())},s.prototype.getSelection=function(){return this.selection.concat([])},s.prototype.getVisibleItems=function(){var t=this.body.range.getRange(),e=this.body.util.toScreen(t.start),i=this.body.util.toScreen(t.end),s=[];for(var o in this.groups)if(this.groups.hasOwnProperty(o))for(var n=this.groups[o],r=n.visibleItems,a=0;ae&&s.push(h.id)}return s},s.prototype._deselect=function(t){for(var e=this.selection,i=0,s=e.length;s>i;i++)if(e[i]==t){e.splice(i,1);break}},s.prototype.redraw=function(){var t=this.options.margin,e=this.body.range,i=n.option.asSize,s=this.options,o=s.orientation,r=!1,a=this.dom.frame,h=s.editable.updateTime||s.editable.updateGroup;this.props.top=this.body.domProps.top.height+this.body.domProps.border.top,this.props.left=this.body.domProps.left.width+this.body.domProps.border.left,a.className="itemset"+(h?" editable":""),r=this._orderGroups()||r;var d=e.end-e.start,l=d!=this.lastVisibleInterval||this.props.width!=this.props.lastWidth;l&&(this.stackDirty=!0),this.lastVisibleInterval=d,this.props.lastWidth=this.props.width;var c=this.stackDirty,p=this._firstGroup(),u={item:t.item,axis:t.axis},m={item:t.item,axis:t.item.vertical/2},f=0,v=t.axis+t.item.vertical;return this.groups[g].redraw(e,m,c),n.forEach(this.groups,function(t){var i=t==p?u:m,s=t.redraw(e,i,c);r=s||r,f+=t.height}),f=Math.max(f,v),this.stackDirty=!1,a.style.height=i(f),this.props.width=a.offsetWidth,this.props.height=f,this.dom.axis.style.top=i("top"==o?this.body.domProps.top.height+this.body.domProps.border.top:this.body.domProps.top.height+this.body.domProps.centerContainer.height),this.dom.axis.style.left="0",r=this._isResized()||r},s.prototype._firstGroup=function(){var t="top"==this.options.orientation?0:this.groupIds.length-1,e=this.groupIds[t],i=this.groups[e]||this.groups[f];return i||null},s.prototype._updateUngrouped=function(){{var t,e,i=this.groups[f];this.groups[g]}if(this.groupsData){if(i){i.hide(),delete this.groups[f];for(e in this.items)if(this.items.hasOwnProperty(e)){t=this.items[e],t.parent&&t.parent.remove(t);var s=this._getGroupId(t.data),o=this.groups[s];o&&o.add(t)||t.hide()}}}else if(!i){var n=null,r=null;i=new d(n,r,this),this.groups[f]=i;for(e in this.items)this.items.hasOwnProperty(e)&&(t=this.items[e],i.add(t));i.show()}},s.prototype.getLabelSet=function(){return this.dom.labelSet},s.prototype.setItems=function(t){var e,i=this,s=this.itemsData;if(t){if(!(t instanceof r||t instanceof a))throw new TypeError("Data must be an instance of DataSet or DataView");this.itemsData=t}else this.itemsData=null;if(s&&(n.forEach(this.itemListeners,function(t,e){s.off(e,t)}),e=s.getIds(),this._onRemove(e)),this.itemsData){var o=this.id;n.forEach(this.itemListeners,function(t,e){i.itemsData.on(e,t,o)}),e=this.itemsData.getIds(),this._onAdd(e),this._updateUngrouped()}},s.prototype.getItems=function(){return this.itemsData},s.prototype.setGroups=function(t){var e,i=this;if(this.groupsData&&(n.forEach(this.groupListeners,function(t,e){i.groupsData.unsubscribe(e,t)}),e=this.groupsData.getIds(),this.groupsData=null,this._onRemoveGroups(e)),t){if(!(t instanceof r||t instanceof a))throw new TypeError("Data must be an instance of DataSet or DataView");this.groupsData=t}else this.groupsData=null;if(this.groupsData){var s=this.id;n.forEach(this.groupListeners,function(t,e){i.groupsData.on(e,t,s)}),e=this.groupsData.getIds(),this._onAddGroups(e)}this._updateUngrouped(),this._order(),this.body.emitter.emit("change",{queue:!0})},s.prototype.getGroups=function(){return this.groupsData},s.prototype.removeItem=function(t){var e=this.itemsData.get(t),i=this.itemsData.getDataSet();e&&this.options.onRemove(e,function(e){e&&i.remove(t)})},s.prototype._getType=function(t){return t.type||this.options.type||(t.end?"range":"box")},s.prototype._getGroupId=function(t){var e=this._getType(t);return"background"==e&&void 0==t.group?g:this.groupsData?t.group:f},s.prototype._onUpdate=function(t){var e=this;t.forEach(function(t){var i=e.itemsData.get(t,e.itemOptions),o=e.items[t],n=e._getType(i),r=s.types[n];if(o&&(r&&o instanceof r?e._updateItem(o,i):(e._removeItem(o),o=null)),!o){if(!r)throw new TypeError("rangeoverflow"==n?'Item type "rangeoverflow" is deprecated. Use css styling instead: .vis.timeline .item.range .content {overflow: visible;}':'Unknown item type "'+n+'"');o=new r(i,e.conversion,e.options),o.id=t,e._addItem(o)}}),this._order(),this.stackDirty=!0,this.body.emitter.emit("change",{queue:!0})},s.prototype._onAdd=s.prototype._onUpdate,s.prototype._onRemove=function(t){var e=0,i=this;t.forEach(function(t){var s=i.items[t];s&&(e++,i._removeItem(s))}),e&&(this._order(),this.stackDirty=!0,this.body.emitter.emit("change",{queue:!0}))},s.prototype._order=function(){n.forEach(this.groups,function(t){t.order()})},s.prototype._onUpdateGroups=function(t){this._onAddGroups(t)},s.prototype._onAddGroups=function(t){var e=this;t.forEach(function(t){var i=e.groupsData.get(t),s=e.groups[t];if(s)s.setData(i);else{if(t==f||t==g)throw new Error("Illegal group id. "+t+" is a reserved id.");var o=Object.create(e.options);n.extend(o,{height:null}),s=new d(t,i,e),e.groups[t]=s;for(var r in e.items)if(e.items.hasOwnProperty(r)){var a=e.items[r];a.data.group==t&&s.add(a)}s.order(),s.show()}}),this.body.emitter.emit("change",{queue:!0})},s.prototype._onRemoveGroups=function(t){var e=this.groups;t.forEach(function(t){var i=e[t];i&&(i.hide(),delete e[t])}),this.markDirty(),this.body.emitter.emit("change",{queue:!0})},s.prototype._orderGroups=function(){if(this.groupsData){var t=this.groupsData.getIds({order:this.options.groupOrder}),e=!n.equalArray(t,this.groupIds);if(e){var i=this.groups;t.forEach(function(t){i[t].hide()}),t.forEach(function(t){i[t].show()}),this.groupIds=t}return e}return!1},s.prototype._addItem=function(t){this.items[t.id]=t;var e=this._getGroupId(t.data),i=this.groups[e];i&&i.add(t)},s.prototype._updateItem=function(t,e){var i=t.data.group;if(t.setData(e),i!=t.data.group){var s=this.groups[i];s&&s.remove(t);var o=this._getGroupId(t.data),n=this.groups[o];n&&n.add(t)}},s.prototype._removeItem=function(t){t.hide(),delete this.items[t.id];var e=this.selection.indexOf(t.id);-1!=e&&this.selection.splice(e,1),t.parent&&t.parent.remove(t)},s.prototype._constructByEndArray=function(t){for(var e=[],i=0;i0||o.length>0)&&this.body.emitter.emit("select",{items:a})}},s.prototype._onAddItem=function(t){if(this.options.selectable&&this.options.editable.add){var e=this,i=this.body.util.snap||null,o=s.itemFromTarget(t);if(o){var r=e.itemsData.get(o.id);this.options.onUpdate(r,function(t){t&&e.itemsData.getDataSet().update(t)})}else{var a=n.getAbsoluteLeft(this.dom.frame),h=t.center.x-a,d=this.body.util.toTime(h),l={start:i?i(d):d,content:"new item"};if("range"===this.options.type){var c=this.body.util.toTime(h+this.props.width/5);l.end=i?i(c):c}l[this.itemsData._fieldId]=n.randomUUID();var p=s.groupFromTarget(t);p&&(l.group=p.groupId),this.options.onAdd(l,function(t){t&&e.itemsData.getDataSet().add(t)})}}},s.prototype._onMultiSelectItem=function(t){if(this.options.selectable){var e,i=s.itemFromTarget(t);if(i){e=this.getSelection();var o=t.srcEvent&&t.srcEvent.shiftKey||!1;if(o){e.push(i.id);var n=s._getItemRange(this.itemsData.get(e,this.itemOptions));e=[];for(var r in this.items)if(this.items.hasOwnProperty(r)){var a=this.items[r],h=a.data.start,d=void 0!==a.data.end?a.data.end:h;h>=n.min&&d<=n.max&&e.push(a.id)}}else{var l=e.indexOf(i.id);-1==l?e.push(i.id):e.splice(l,1)}this.setSelection(e),this.body.emitter.emit("select",{items:this.getSelection()})}}},s._getItemRange=function(t){var e=null,i=null;return t.forEach(function(t){(null==i||t.starte)&&(e=t.end):(null==e||t.start>e)&&(e=t.start)}),{min:i,max:e}},s.itemFromTarget=function(t){for(var e=t.target;e;){if(e.hasOwnProperty("timeline-item"))return e["timeline-item"];e=e.parentNode}return null},s.groupFromTarget=function(t){for(var e=t.target;e;){if(e.hasOwnProperty("timeline-group"))return e["timeline-group"];e=e.parentNode}return null},s.itemSetFromTarget=function(t){for(var e=t.target;e;){if(e.hasOwnProperty("timeline-itemset"))return e["timeline-itemset"];e=e.parentNode}return null},t.exports=s},function(t,e,i){function s(t,e,i,s){this.body=t,this.defaultOptions={enabled:!0,icons:!0,iconSize:20,iconSpacing:6,left:{visible:!0,position:"top-left"},right:{visible:!0,position:"top-left"}},this.side=i,this.options=o.extend({},this.defaultOptions),this.linegraphOptions=s,this.svgElements={},this.dom={},this.groups={},this.amountOfGroups=0,this._create(),this.setOptions(e)}var o=i(1),n=i(2),r=i(20);s.prototype=new r,s.prototype.clear=function(){this.groups={},this.amountOfGroups=0},s.prototype.addGroup=function(t,e){this.groups.hasOwnProperty(t)||(this.groups[t]=e),this.amountOfGroups+=1},s.prototype.updateGroup=function(t,e){this.groups[t]=e},s.prototype.removeGroup=function(t){this.groups.hasOwnProperty(t)&&(delete this.groups[t],this.amountOfGroups-=1)},s.prototype._create=function(){this.dom.frame=document.createElement("div"),this.dom.frame.className="legend",this.dom.frame.style.position="absolute",this.dom.frame.style.top="10px",this.dom.frame.style.display="block",this.dom.textArea=document.createElement("div"),this.dom.textArea.className="legendText",this.dom.textArea.style.position="relative",this.dom.textArea.style.top="0px",this.svg=document.createElementNS("http://www.w3.org/2000/svg","svg"),this.svg.style.position="absolute",this.svg.style.top="0px",this.svg.style.width=this.options.iconSize+5+"px",this.svg.style.height="100%",this.dom.frame.appendChild(this.svg),this.dom.frame.appendChild(this.dom.textArea)},s.prototype.hide=function(){this.dom.frame.parentNode&&this.dom.frame.parentNode.removeChild(this.dom.frame)},s.prototype.show=function(){this.dom.frame.parentNode||this.body.dom.center.appendChild(this.dom.frame)},s.prototype.setOptions=function(t){var e=["enabled","orientation","icons","left","right"];o.selectiveDeepExtend(e,this.options,t)},s.prototype.redraw=function(){var t=0;for(var e in this.groups)this.groups.hasOwnProperty(e)&&(1!=this.groups[e].visible||void 0!==this.linegraphOptions.visibility[e]&&1!=this.linegraphOptions.visibility[e]||t++);if(0==this.options[this.side].visible||0==this.amountOfGroups||0==this.options.enabled||0==t)this.hide();else{if(this.show(),"top-left"==this.options[this.side].position||"bottom-left"==this.options[this.side].position?(this.dom.frame.style.left="4px",this.dom.frame.style.textAlign="left",this.dom.textArea.style.textAlign="left",this.dom.textArea.style.left=this.options.iconSize+15+"px",this.dom.textArea.style.right="",this.svg.style.left="0px",this.svg.style.right=""):(this.dom.frame.style.right="4px",this.dom.frame.style.textAlign="right",this.dom.textArea.style.textAlign="right",this.dom.textArea.style.right=this.options.iconSize+15+"px",this.dom.textArea.style.left="",this.svg.style.right="0px",this.svg.style.left=""),"top-left"==this.options[this.side].position||"top-right"==this.options[this.side].position)this.dom.frame.style.top=4-Number(this.body.dom.center.style.top.replace("px",""))+"px",this.dom.frame.style.bottom="";else{var i=this.body.domProps.center.height-this.body.domProps.centerContainer.height;this.dom.frame.style.bottom=4+i+Number(this.body.dom.center.style.top.replace("px",""))+"px",this.dom.frame.style.top=""}0==this.options.icons?(this.dom.frame.style.width=this.dom.textArea.offsetWidth+10+"px",this.dom.textArea.style.right="",this.dom.textArea.style.left="",this.svg.style.width="0px"):(this.dom.frame.style.width=this.options.iconSize+15+this.dom.textArea.offsetWidth+10+"px",this.drawLegendIcons());var s="";for(var e in this.groups)this.groups.hasOwnProperty(e)&&(1!=this.groups[e].visible||void 0!==this.linegraphOptions.visibility[e]&&1!=this.linegraphOptions.visibility[e]||(s+=this.groups[e].content+"
"));this.dom.textArea.innerHTML=s,this.dom.textArea.style.lineHeight=.75*this.options.iconSize+this.options.iconSpacing+"px"}},s.prototype.drawLegendIcons=function(){if(this.dom.frame.parentNode){n.prepareElements(this.svgElements);var t=window.getComputedStyle(this.dom.frame).paddingTop,e=Number(t.replace("px","")),i=e,s=this.options.iconSize,o=.75*this.options.iconSize,r=e+.5*o+3;this.svg.style.width=s+5+e+"px";for(var a in this.groups)this.groups.hasOwnProperty(a)&&(1!=this.groups[a].visible||void 0!==this.linegraphOptions.visibility[a]&&1!=this.linegraphOptions.visibility[a]||(this.groups[a].drawIcon(i,r,this.svgElements,this.svg,s,o),r+=o+this.options.iconSpacing));n.cleanupElements(this.svgElements)}},t.exports=s},function(t,e,i){function s(t,e){this.id=o.randomUUID(),this.body=t,this.defaultOptions={yAxisOrientation:"left",defaultGroup:"default",sort:!0,sampling:!0,graphHeight:"400px",shaded:{enabled:!1,orientation:"bottom"},style:"line",barChart:{width:50,handleOverlap:"overlap",align:"center"},catmullRom:{enabled:!0,parametrization:"centripetal",alpha:.5},drawPoints:{enabled:!0,size:6,style:"square"},dataAxis:{showMinorLabels:!0,showMajorLabels:!0,icons:!1,width:"40px",visible:!0,alignZeros:!0,customRange:{left:{min:void 0,max:void 0},right:{min:void 0,max:void 0}}},legend:{enabled:!1,icons:!0,left:{visible:!0,position:"top-left"},right:{visible:!0,position:"top-right"}},groups:{visibility:{}}},this.options=o.extend({},this.defaultOptions),this.dom={},this.props={},this.hammer=null,this.groups={},this.abortedGraphUpdate=!1,this.updateSVGheight=!1,this.updateSVGheightOnResize=!1;var i=this;this.itemsData=null,this.groupsData=null,this.itemListeners={add:function(t,e){i._onAdd(e.items)},update:function(t,e){i._onUpdate(e.items)},remove:function(t,e){i._onRemove(e.items)}},this.groupListeners={add:function(t,e){i._onAddGroups(e.items)},update:function(t,e){i._onUpdateGroups(e.items)},remove:function(t,e){i._onRemoveGroups(e.items)}},this.items={},this.selection=[],this.lastStart=this.body.range.start,this.touchParams={},this.svgElements={},this.setOptions(e),this.groupsUsingDefaultStyles=[0],this.COUNTER=0,this.body.emitter.on("rangechanged",function(){i.lastStart=i.body.range.start,i.svg.style.left=o.option.asSize(-i.props.width),i.redraw.call(i,!0)}),this._create(),this.framework={svg:this.svg,svgElements:this.svgElements,options:this.options,groups:this.groups},this.body.emitter.emit("change")}var o=i(1),n=i(2),r=i(3),a=i(4),h=i(20),d=i(23),l=i(24),c=i(28),p=i(52),u="__ungrouped__";s.prototype=new h,s.prototype._create=function(){var t=document.createElement("div");t.className="LineGraph",this.dom.frame=t,this.svg=document.createElementNS("http://www.w3.org/2000/svg","svg"),this.svg.style.position="relative",this.svg.style.height=(""+this.options.graphHeight).replace("px","")+"px",this.svg.style.display="block",t.appendChild(this.svg),this.options.dataAxis.orientation="left",this.yAxisLeft=new d(this.body,this.options.dataAxis,this.svg,this.options.groups),this.options.dataAxis.orientation="right",this.yAxisRight=new d(this.body,this.options.dataAxis,this.svg,this.options.groups),delete this.options.dataAxis.orientation,this.legendLeft=new c(this.body,this.options.legend,"left",this.options.groups),this.legendRight=new c(this.body,this.options.legend,"right",this.options.groups),this.show()},s.prototype.setOptions=function(t){if(t){var e=["sampling","defaultGroup","height","graphHeight","yAxisOrientation","style","barChart","dataAxis","sort","groups"];void 0===t.graphHeight&&void 0!==t.height&&void 0!==this.body.domProps.centerContainer.height?(this.updateSVGheight=!0,this.updateSVGheightOnResize=!0):void 0!==this.body.domProps.centerContainer.height&&void 0!==t.graphHeight&&parseInt((t.graphHeight+"").replace("px",""))0){var d=this.body.util.toGlobalTime(-this.body.domProps.root.width),l=this.body.util.toGlobalTime(2*this.body.domProps.root.width),c={};for(this._getRelevantData(a,c,d,l),this._applySampling(a,c),e=0;eu&&console.log("WARNING: there may be an infinite loop in the _updateGraph emitter cycle."),this.COUNTER=0,this.abortedGraphUpdate=!1,e=0;e0)for(r=0;rs){d.push(h);break}d.push(h)}}else for(a=0;ai&&h.x0)for(var s=0;s0){var n=1,r=o.length,a=this.body.util.toGlobalScreen(o[o.length-1].x)-this.body.util.toGlobalScreen(o[0].x),h=r/a;n=Math.min(Math.ceil(.2*r),Math.max(1,Math.round(h)));for(var d=[],l=0;r>l;l+=n)d.push(o[l]);e[t[s]]=d}}},s.prototype._getYRanges=function(t,e,i){var s,o,n,r,a=[],h=[];if(t.length>0){for(n=0;n0&&(o=this.groups[t[n]],"stack"==r.barChart.handleOverlap&&"bar"==r.style?"left"==r.yAxisOrientation?a=a.concat(o.getYRange(s)):h=h.concat(o.getYRange(s)):i[t[n]]=o.getYRange(s,t[n]));p.getStackedBarYRange(a,i,t,"__barchartLeft","left"),p.getStackedBarYRange(h,i,t,"__barchartRight","right")}},s.prototype._updateYAxis=function(t,e){var i,s,o=!1,n=!1,r=!1,a=1e9,h=1e9,d=-1e9,l=-1e9;if(t.length>0){for(var c=0;ci?i:a,d=s>d?s:d):(r=!0,h=h>i?i:h,l=s>l?s:l));1==n&&this.yAxisLeft.setRange(a,d),1==r&&this.yAxisRight.setRange(h,l)}return o=this._toggleAxisVisiblity(n,this.yAxisLeft)||o,o=this._toggleAxisVisiblity(r,this.yAxisRight)||o,1==r&&1==n?(this.yAxisLeft.drawIcons=!0,this.yAxisRight.drawIcons=!0):(this.yAxisLeft.drawIcons=!1,this.yAxisRight.drawIcons=!1),this.yAxisRight.master=!n,0==this.yAxisRight.master?(this.yAxisLeft.lineOffset=1==r?this.yAxisRight.width:0,o=this.yAxisLeft.redraw()||o,this.yAxisRight.stepPixelsForced=this.yAxisLeft.stepPixels,this.yAxisRight.zeroCrossing=this.yAxisLeft.zeroCrossing,o=this.yAxisRight.redraw()||o):o=this.yAxisRight.redraw()||o,-1!=t.indexOf("__barchartLeft")&&t.splice(t.indexOf("__barchartLeft"),1),-1!=t.indexOf("__barchartRight")&&t.splice(t.indexOf("__barchartRight"),1),o},s.prototype._toggleAxisVisiblity=function(t,e){var i=!1;return 0==t?e.dom.frame.parentNode&&0==e.hidden&&(e.hide(),i=!0):e.dom.frame.parentNode||1!=e.hidden||(e.show(),i=!0),i},s.prototype._convertXcoordinates=function(t){for(var e,i,s=[],o=this.body.util.toScreen,n=0;ny;)y++,l=h.getCurrent(),c=h.isMajor(),u=h.getClassName(),f=m,m=this.body.util.toScreen(l),g=m-f,p&&(p.style.width=g+"px"),this.options.showMinorLabels&&this._repaintMinorText(m,h.getLabelMinor(),t,u),c&&this.options.showMajorLabels?(m>0&&(void 0==v&&(v=m),this._repaintMajorText(m,h.getLabelMajor(),t,u)),p=this._repaintMajorLine(m,t,u)):p=this._repaintMinorLine(m,t,u),h.next();if(this.options.showMajorLabels){var b=this.body.util.toTime(0),_=h.getLabelMajor(b),x=_.length*(this.props.majorCharWidth||10)+10;(void 0==v||v>x)&&this._repaintMajorText(0,_,t,u)}o.forEach(this.dom.redundant,function(t){for(;t.length;){var e=t.pop();e&&e.parentNode&&e.parentNode.removeChild(e)}})},s.prototype._repaintMinorText=function(t,e,i,s){var o=this.dom.redundant.minorTexts.shift();if(!o){var n=document.createTextNode("");o=document.createElement("div"),o.appendChild(n),this.dom.foreground.appendChild(o)}this.dom.minorTexts.push(o),o.childNodes[0].nodeValue=e,o.style.top="top"==i?this.props.majorLabelHeight+"px":"0",o.style.left=t+"px",o.className="text minor "+s},s.prototype._repaintMajorText=function(t,e,i,s){var o=this.dom.redundant.majorTexts.shift();if(!o){var n=document.createTextNode(e);o=document.createElement("div"),o.appendChild(n),this.dom.foreground.appendChild(o)}this.dom.majorTexts.push(o),o.childNodes[0].nodeValue=e,o.className="text major "+s,o.style.top="top"==i?"0":this.props.minorLabelHeight+"px",o.style.left=t+"px"},s.prototype._repaintMinorLine=function(t,e,i){var s=this.dom.redundant.lines.shift();s||(s=document.createElement("div"),this.dom.background.appendChild(s)),this.dom.lines.push(s);var o=this.props;return s.style.top="top"==e?o.majorLabelHeight+"px":this.body.domProps.top.height+"px",s.style.height=o.minorLineHeight+"px",s.style.left=t-o.minorLineWidth/2+"px",s.className="grid vertical minor "+i,s},s.prototype._repaintMajorLine=function(t,e,i){var s=this.dom.redundant.lines.shift();s||(s=document.createElement("div"),this.dom.background.appendChild(s)),this.dom.lines.push(s);var o=this.props;return s.style.top="top"==e?"0":this.body.domProps.top.height+"px",s.style.left=t-o.majorLineWidth/2+"px",s.style.height=o.majorLineHeight+"px",s.className="grid vertical major "+i,s},s.prototype._calculateCharSize=function(){this.dom.measureCharMinor||(this.dom.measureCharMinor=document.createElement("DIV"),this.dom.measureCharMinor.className="text minor measure",this.dom.measureCharMinor.style.position="absolute",this.dom.measureCharMinor.appendChild(document.createTextNode("0")),this.dom.foreground.appendChild(this.dom.measureCharMinor)),this.props.minorCharHeight=this.dom.measureCharMinor.clientHeight,this.props.minorCharWidth=this.dom.measureCharMinor.clientWidth,this.dom.measureCharMajor||(this.dom.measureCharMajor=document.createElement("DIV"),this.dom.measureCharMajor.className="text major measure",this.dom.measureCharMajor.style.position="absolute",this.dom.measureCharMajor.appendChild(document.createTextNode("0")),this.dom.foreground.appendChild(this.dom.measureCharMajor)),this.props.majorCharHeight=this.dom.measureCharMajor.clientHeight,this.props.majorCharWidth=this.dom.measureCharMajor.clientWidth},s.prototype.snap=function(t){return this.step.snap(t)},t.exports=s},function(t,e,i){function s(t,e,i){this.id=null,this.parent=null,this.data=t,this.dom=null,this.conversion=e||{},this.options=i||{},this.selected=!1,this.displayed=!1,this.dirty=!0,this.top=null,this.left=null,this.width=null,this.height=null}var o=i(45),n=i(1);s.prototype.stack=!0,s.prototype.select=function(){this.selected=!0,this.dirty=!0,this.displayed&&this.redraw()},s.prototype.unselect=function(){this.selected=!1,this.dirty=!0,this.displayed&&this.redraw()},s.prototype.setData=function(t){this.data=t,this.dirty=!0,this.displayed&&this.redraw()},s.prototype.setParent=function(t){this.displayed?(this.hide(),this.parent=t,this.parent&&this.show()):this.parent=t},s.prototype.isVisible=function(){return!1},s.prototype.show=function(){return!1},s.prototype.hide=function(){return!1},s.prototype.redraw=function(){},s.prototype.repositionX=function(){},s.prototype.repositionY=function(){},s.prototype._repaintDeleteButton=function(t){if(this.selected&&this.options.editable.remove&&!this.dom.deleteButton){var e=this,i=document.createElement("div");i.className="delete",i.title="Delete this item",new o(i).on("tap",function(t){e.parent.removeFromDataSet(e),t.stopPropagation(),t.preventDefault()}),t.appendChild(i),this.dom.deleteButton=i}else!this.selected&&this.dom.deleteButton&&(this.dom.deleteButton.parentNode&&this.dom.deleteButton.parentNode.removeChild(this.dom.deleteButton),this.dom.deleteButton=null)},s.prototype._updateContents=function(t){var e;if(this.options.template){var i=this.parent.itemSet.itemsData.get(this.id);e=this.options.template(i)}else e=this.data.content;if(e!==this.content){if(e instanceof Element)t.innerHTML="",t.appendChild(e);else if(void 0!=e)t.innerHTML=e;else if("background"!=this.data.type||void 0!==this.data.content)throw new Error('Property "content" missing in item '+this.id);this.content=e}},s.prototype._updateTitle=function(t){null!=this.data.title?t.title=this.data.title||"":t.removeAttribute("title")},s.prototype._updateDataAttributes=function(t){if(this.options.dataAttributes&&this.options.dataAttributes.length>0){var e=[];if(Array.isArray(this.options.dataAttributes))e=this.options.dataAttributes;else{if("all"!=this.options.dataAttributes)return;e=Object.keys(this.data)}for(var i=0;it.start},s.prototype.redraw=function(){var t=this.dom;if(t||(this.dom={},t=this.dom,t.box=document.createElement("div"),t.content=document.createElement("div"),t.content.className="content",t.box.appendChild(t.content),this.dirty=!0),!this.parent)throw new Error("Cannot redraw item: no parent attached");if(!t.box.parentNode){var e=this.parent.dom.background;if(!e)throw new Error("Cannot redraw item: parent has no background container element");e.appendChild(t.box)}if(this.displayed=!0,this.dirty){this._updateContents(this.dom.content),this._updateTitle(this.dom.content),this._updateDataAttributes(this.dom.content),this._updateStyle(this.dom.box);var i=(this.data.className?" "+this.data.className:"")+(this.selected?" selected":"");t.box.className=this.baseClassName+i,this.overflow="hidden"!==window.getComputedStyle(t.content).overflow,this.props.content.width=this.dom.content.offsetWidth,this.height=0,this.dirty=!1}},s.prototype.show=r.prototype.show,s.prototype.hide=r.prototype.hide,s.prototype.repositionX=r.prototype.repositionX,s.prototype.repositionY=function(t){var e="top"===this.options.orientation;this.dom.content.style.top=e?"":"0",this.dom.content.style.bottom=e?"0":"";var i;if(void 0!==this.data.subgroup){var s=this.data.subgroup,o=this.parent.subgroups,r=o[s].index;if(1==e){i=this.parent.subgroups[s].height+t.item.vertical,i+=0==r?t.axis-.5*t.item.vertical:0;var a=this.parent.top;for(var h in o)o.hasOwnProperty(h)&&1==o[h].visible&&o[h].indexr&&(a+=o[h].height+t.item.vertical);i=this.parent.subgroups[s].height+t.item.vertical,this.dom.box.style.top=a+"px",this.dom.box.style.bottom=""}}else this.parent instanceof n?(i=Math.max(this.parent.height,this.parent.itemSet.body.domProps.center.height,this.parent.itemSet.body.domProps.centerContainer.height),this.dom.box.style.top=e?"0":"",this.dom.box.style.bottom=e?"":"0"):(i=this.parent.height,this.dom.box.style.top=this.parent.top+"px",this.dom.box.style.bottom="");this.dom.box.style.height=i+"px"},t.exports=s},function(t,e,i){function s(t,e,i){if(this.props={dot:{width:0,height:0},line:{width:0,height:0}},t&&void 0==t.start)throw new Error('Property "start" missing in item '+t);o.call(this,t,e,i)}{var o=i(31);i(1)}s.prototype=new o(null,null,null),s.prototype.isVisible=function(t){var e=(t.end-t.start)/4;return this.data.start>t.start-e&&this.data.startt.start-e&&this.data.startt.start},s.prototype.redraw=function(){var t=this.dom;if(t||(this.dom={},t=this.dom,t.box=document.createElement("div"),t.content=document.createElement("div"),t.content.className="content",t.box.appendChild(t.content),t.box["timeline-item"]=this,this.dirty=!0),!this.parent)throw new Error("Cannot redraw item: no parent attached");if(!t.box.parentNode){var e=this.parent.dom.foreground;if(!e)throw new Error("Cannot redraw item: parent has no foreground container element");e.appendChild(t.box)}if(this.displayed=!0,this.dirty){this._updateContents(this.dom.content),this._updateTitle(this.dom.box),this._updateDataAttributes(this.dom.box),this._updateStyle(this.dom.box);var i=(this.data.className?" "+this.data.className:"")+(this.selected?" selected":"");t.box.className=this.baseClassName+i,this.overflow="hidden"!==window.getComputedStyle(t.content).overflow,this.dom.content.style.maxWidth="none",this.props.content.width=this.dom.content.offsetWidth,this.height=this.dom.box.offsetHeight,this.dom.content.style.maxWidth="",this.dirty=!1}this._repaintDeleteButton(t.box),this._repaintDragLeft(),this._repaintDragRight()},s.prototype.show=function(){this.displayed||this.redraw()},s.prototype.hide=function(){if(this.displayed){var t=this.dom.box;t.parentNode&&t.parentNode.removeChild(t),this.top=null,this.left=null,this.displayed=!1}},s.prototype.repositionX=function(){var t,e,i=this.parent.width,s=this.conversion.toScreen(this.data.start),o=this.conversion.toScreen(this.data.end);-i>s&&(s=-i),o>2*i&&(o=2*i);var n=Math.max(o-s,1);switch(this.overflow?(this.left=s,this.width=n+this.props.content.width,e=this.props.content.width):(this.left=s,this.width=n,e=Math.min(o-s-2*this.options.padding,this.props.content.width)),this.dom.box.style.left=this.left+"px",this.dom.box.style.width=n+"px",this.options.align){case"left":this.dom.content.style.left="0";break;case"right":this.dom.content.style.left=Math.max(n-e-2*this.options.padding,0)+"px";break;case"center":this.dom.content.style.left=Math.max((n-e-2*this.options.padding)/2,0)+"px";break;default:t=this.overflow?o>0?Math.max(-s,0):-e:0>s?Math.min(-s,o-s-e-2*this.options.padding):0,this.dom.content.style.left=t+"px"}},s.prototype.repositionY=function(){var t=this.options.orientation,e=this.dom.box;e.style.top="top"==t?this.top+"px":this.parent.height-this.top-this.height+"px"},s.prototype._repaintDragLeft=function(){if(this.selected&&this.options.editable.updateTime&&!this.dom.dragLeft){var t=document.createElement("div");t.className="drag-left",t.dragLeftItem=this,this.dom.box.appendChild(t),this.dom.dragLeft=t}else!this.selected&&this.dom.dragLeft&&(this.dom.dragLeft.parentNode&&this.dom.dragLeft.parentNode.removeChild(this.dom.dragLeft),this.dom.dragLeft=null)},s.prototype._repaintDragRight=function(){if(this.selected&&this.options.editable.updateTime&&!this.dom.dragRight){var t=document.createElement("div");t.className="drag-right",t.dragRightItem=this,this.dom.box.appendChild(t),this.dom.dragRight=t}else!this.selected&&this.dom.dragRight&&(this.dom.dragRight.parentNode&&this.dom.dragRight.parentNode.removeChild(this.dom.dragRight),this.dom.dragRight=null)},t.exports=s},function(t,e,i){function s(t,e,i){if(!(this instanceof s))throw new SyntaxError("Constructor must be called with the new operator");this._determineBrowserMethod(),this._initializeMixinLoaders(),this.containerElement=t,this.renderRefreshRate=60,this.renderTimestep=1e3/this.renderRefreshRate,this.renderTime=0,this.physicsTime=0,this.runDoubleSpeed=!1,this.physicsDiscreteStepsize=.5,this.initializing=!0,this.triggerFunctions={add:null,edit:null,editEdge:null,connect:null,del:null},this.defaultOptions={nodes:{mass:1,radiusMin:10,radiusMax:30,radius:10,shape:"ellipse",image:void 0,widthMin:16,widthMax:64,fontColor:"black",fontSize:14,fontFace:"verdana",fontFill:void 0,fontStrokeWidth:0,fontStrokeColor:"white",level:-1,color:{border:"#2B7CE9",background:"#97C2FC",highlight:{border:"#2B7CE9",background:"#D2E5FF"},hover:{border:"#2B7CE9",background:"#D2E5FF"}},group:void 0,borderWidth:1,borderWidthSelected:void 0},edges:{widthMin:1,widthMax:15,width:1,widthSelectionMultiplier:2,hoverWidth:1.5,style:"line",color:{color:"#848484",highlight:"#848484",hover:"#848484"},fontColor:"#343434",fontSize:14,fontFace:"arial",fontFill:"white",fontStrokeWidth:0,fontStrokeColor:"white",labelAlignment:"horizontal",arrowScaleFactor:1,dash:{length:10,gap:5,altLength:void 0},inheritColor:"from"},configurePhysics:!1,physics:{barnesHut:{enabled:!0,thetaInverted:2,gravitationalConstant:-2e3,centralGravity:.3,springLength:95,springConstant:.04,damping:.09},repulsion:{centralGravity:0,springLength:200,springConstant:.05,nodeDistance:100,damping:.09},hierarchicalRepulsion:{enabled:!1,centralGravity:0,springLength:100,springConstant:.01,nodeDistance:150,damping:.09},damping:null,centralGravity:null,springLength:null,springConstant:null},clustering:{enabled:!1,initialMaxNodes:100,clusterThreshold:500,reduceToNodes:300,chainThreshold:.4,clusterEdgeThreshold:20,sectorThreshold:100,screenSizeThreshold:.2,fontSizeMultiplier:4,maxFontSize:1e3,forceAmplification:.1,distanceAmplification:.1,edgeGrowth:20,nodeScaling:{width:1,height:1,radius:1},maxNodeSizeIncrements:600,activeAreaBoxSize:80,clusterLevelDifference:2},navigation:{enabled:!1},keyboard:{enabled:!1,speed:{x:10,y:10,zoom:.02}},dataManipulation:{enabled:!1,initiallyVisible:!1},hierarchicalLayout:{enabled:!1,levelSeparation:150,nodeSpacing:100,direction:"UD",layout:"hubsize"},freezeForStabilization:!1,smoothCurves:{enabled:!0,dynamic:!0,type:"continuous",roundness:.5},maxVelocity:30,minVelocity:.1,stabilize:!0,stabilizationIterations:1e3,zoomExtentOnStabilize:!0,locale:"en",locales:_,tooltip:{delay:300,fontColor:"black",fontSize:14,fontFace:"verdana",color:{border:"#666",background:"#FFFFC6"}},dragNetwork:!0,dragNodes:!0,zoomable:!0,hover:!1,hideEdgesOnDrag:!1,hideNodesOnDrag:!1,width:"100%",height:"100%",selectable:!0},this.constants=a.extend({},this.defaultOptions),this.pixelRatio=1,this.hoverObj={nodes:{},edges:{}},this.controlNodesActive=!1,this.navigationHammers={existing:[],_new:[]},this.animationSpeed=1/this.renderRefreshRate,this.animationEasingFunction="easeInOutQuint",this.easingTime=0,this.sourceScale=0,this.targetScale=0,this.sourceTranslation=0,this.targetTranslation=0,this.lockedOnNodeId=null,this.lockedOnNodeOffset=null,this.touchTime=0;var o=this;this.groups=new u,this.images=new m,this.images.setOnloadCallback(function(){o._redraw()}),this.xIncrement=0,this.yIncrement=0,this.zoomIncrement=0,this._loadPhysicsSystem(),this._create(),this._loadSectorSystem(),this._loadClusterSystem(),this._loadSelectionSystem(),this._loadHierarchySystem(),this._setTranslation(this.frame.clientWidth/2,this.frame.clientHeight/2),this._setScale(1),this.setOptions(i),this.freezeSimulation=!1,this.cachedFunctions={},this.startedStabilization=!1,this.stabilized=!1,this.stabilizationIterations=null,this.draggingNodes=!1,this.calculationNodes={},this.calculationNodeIndices=[],this.nodeIndices=[],this.nodes={},this.edges={},this.canvasTopLeft={x:0,y:0},this.canvasBottomRight={x:0,y:0},this.pointerPosition={x:0,y:0},this.areaCenter={},this.scale=1,this.previousScale=this.scale,this.nodesData=null,this.edgesData=null,this.nodesListeners={add:function(t,e){o._addNodes(e.items),o.start()},update:function(t,e){o._updateNodes(e.items,e.data),o.start()},remove:function(t,e){o._removeNodes(e.items),o.start()}},this.edgesListeners={add:function(t,e){o._addEdges(e.items),o.start()},update:function(t,e){o._updateEdges(e.items),o.start()},remove:function(t,e){o._removeEdges(e.items),o.start()}},this.moving=!0,this.timer=void 0,this.setData(e,this.constants.clustering.enabled||this.constants.hierarchicalLayout.enabled),this.initializing=!1,1==this.constants.hierarchicalLayout.enabled?this._setupHierarchicalLayout():0==this.constants.stabilize&&this.zoomExtent(void 0,!0,this.constants.clustering.enabled),this.constants.clustering.enabled&&this.startWithClustering()}var o=i(56),n=i(45),r=i(58),a=i(1),h=i(47),d=i(3),l=i(4),c=i(42),p=i(43),u=i(38),m=i(39),f=i(40),g=i(37),v=i(41),y=i(54),b=i(55),_=i(49);i(50),o(s.prototype),s.prototype._determineBrowserMethod=function(){var t=navigator.userAgent.toLowerCase();this.requiresTimeout=!1,-1!=t.indexOf("msie 9.0")?this.requiresTimeout=!0:-1!=t.indexOf("safari")&&t.indexOf("chrome")<=-1&&(this.requiresTimeout=!0)},s.prototype._getScriptPath=function(){for(var t=document.getElementsByTagName("script"),e=0;et.boundingBox.left&&(s=t.boundingBox.left),ot.boundingBox.bottom&&(e=t.boundingBox.bottom),i=this.constants.clustering.initialMaxNodes?49.07548/(n+142.05338)+91444e-8:12.662/(n+7.4147)+.0964822:1==this.constants.clustering.enabled&&n>=this.constants.clustering.initialMaxNodes?77.5271985/(n+187.266146)+476710517e-13:30.5062972/(n+19.93597763)+.08413486;var r=Math.min(this.frame.canvas.clientWidth/600,this.frame.canvas.clientHeight/600);s*=r}else{var a=1.1*Math.abs(o.maxX-o.minX),h=1.1*Math.abs(o.maxY-o.minY),d=this.frame.canvas.clientWidth/a,l=this.frame.canvas.clientHeight/h;s=l>=d?d:l}s>1&&(s=1);var c=this._findCenter(o);if(0==i){var p={position:c,scale:s,animation:t};this.moveTo(p),this.moving=!0,this.start()}else c.x*=s,c.y*=s,c.x-=.5*this.frame.canvas.clientWidth,c.y-=.5*this.frame.canvas.clientHeight,this._setScale(s),this._setTranslation(-c.x,-c.y)},s.prototype._updateNodeIndexList=function(){this._clearNodeIndexList();for(var t in this.nodes)this.nodes.hasOwnProperty(t)&&this.nodeIndices.push(t)},s.prototype.setData=function(t,e){if(void 0===e&&(e=!1),this.initializing=!0,t&&t.dot&&(t.nodes||t.edges))throw new SyntaxError('Data must contain either parameter "dot" or parameter pair "nodes" and "edges", but not both.');if(1==this.constants.dataManipulation.enabled&&this._createManipulatorBar(),this.setOptions(t&&t.options),t&&t.dot){if(t&&t.dot){var i=c.DOTToGraph(t.dot);return void this.setData(i)}}else if(t&&t.gephi){if(t&&t.gephi){var s=p.parseGephi(t.gephi);return void this.setData(s)}}else this._setNodes(t&&t.nodes),this._setEdges(t&&t.edges);this._putDataInSector(),0==e&&(1==this.constants.hierarchicalLayout.enabled?(this._resetLevels(),this._setupHierarchicalLayout()):this.constants.stabilize&&this._stabilize(),this.start()),this.initializing=!1},s.prototype.setOptions=function(t){if(t){var e,i=["nodes","edges","smoothCurves","hierarchicalLayout","clustering","navigation","keyboard","dataManipulation","onAdd","onEdit","onEditEdge","onConnect","onDelete","clickToUse"];if(a.selectiveNotDeepExtend(i,this.constants,t),a.selectiveNotDeepExtend(["color"],this.constants.nodes,t.nodes),a.selectiveNotDeepExtend(["color","length"],this.constants.edges,t.edges),t.physics&&(a.mergeOptions(this.constants.physics,t.physics,"barnesHut"),a.mergeOptions(this.constants.physics,t.physics,"repulsion"),t.physics.hierarchicalRepulsion)){this.constants.hierarchicalLayout.enabled=!0,this.constants.physics.hierarchicalRepulsion.enabled=!0,this.constants.physics.barnesHut.enabled=!1;for(e in t.physics.hierarchicalRepulsion)t.physics.hierarchicalRepulsion.hasOwnProperty(e)&&(this.constants.physics.hierarchicalRepulsion[e]=t.physics.hierarchicalRepulsion[e]) +}if(t.onAdd&&(this.triggerFunctions.add=t.onAdd),t.onEdit&&(this.triggerFunctions.edit=t.onEdit),t.onEditEdge&&(this.triggerFunctions.editEdge=t.onEditEdge),t.onConnect&&(this.triggerFunctions.connect=t.onConnect),t.onDelete&&(this.triggerFunctions.del=t.onDelete),a.mergeOptions(this.constants,t,"smoothCurves"),a.mergeOptions(this.constants,t,"hierarchicalLayout"),a.mergeOptions(this.constants,t,"clustering"),a.mergeOptions(this.constants,t,"navigation"),a.mergeOptions(this.constants,t,"keyboard"),a.mergeOptions(this.constants,t,"dataManipulation"),t.dataManipulation&&(this.editMode=this.constants.dataManipulation.initiallyVisible),t.edges&&(void 0!==t.edges.color&&(a.isString(t.edges.color)?(this.constants.edges.color={},this.constants.edges.color.color=t.edges.color,this.constants.edges.color.highlight=t.edges.color,this.constants.edges.color.hover=t.edges.color):(void 0!==t.edges.color.color&&(this.constants.edges.color.color=t.edges.color.color),void 0!==t.edges.color.highlight&&(this.constants.edges.color.highlight=t.edges.color.highlight),void 0!==t.edges.color.hover&&(this.constants.edges.color.hover=t.edges.color.hover)),this.constants.edges.inheritColor=!1),t.edges.fontColor||void 0!==t.edges.color&&(a.isString(t.edges.color)?this.constants.edges.fontColor=t.edges.color:void 0!==t.edges.color.color&&(this.constants.edges.fontColor=t.edges.color.color))),t.nodes&&t.nodes.color){var s=a.parseColor(t.nodes.color);this.constants.nodes.color.background=s.background,this.constants.nodes.color.border=s.border,this.constants.nodes.color.highlight.background=s.highlight.background,this.constants.nodes.color.highlight.border=s.highlight.border,this.constants.nodes.color.hover.background=s.hover.background,this.constants.nodes.color.hover.border=s.hover.border}if(t.groups)for(var o in t.groups)if(t.groups.hasOwnProperty(o)){var n=t.groups[o];this.groups.add(o,n)}if(t.tooltip){for(e in t.tooltip)t.tooltip.hasOwnProperty(e)&&(this.constants.tooltip[e]=t.tooltip[e]);t.tooltip.color&&(this.constants.tooltip.color=a.parseColor(t.tooltip.color))}if("clickToUse"in t&&(t.clickToUse?this.activator||(this.activator=new b(this.frame),this.activator.on("change",this._createKeyBinds.bind(this))):this.activator&&(this.activator.destroy(),delete this.activator)),t.labels)throw new Error('Option "labels" is deprecated. Use options "locale" and "locales" instead.');this._loadPhysicsSystem(),this._loadNavigationControls(),this._loadManipulationSystem(),this._configureSmoothCurves(),this._createKeyBinds(),this.setSize(this.constants.width,this.constants.height),this.moving=!0,this.start()}},s.prototype._create=function(){for(;this.containerElement.hasChildNodes();)this.containerElement.removeChild(this.containerElement.firstChild);if(this.frame=document.createElement("div"),this.frame.className="vis network-frame",this.frame.style.position="relative",this.frame.style.overflow="hidden",this.frame.canvas=document.createElement("canvas"),this.frame.canvas.style.position="relative",this.frame.appendChild(this.frame.canvas),this.frame.canvas.getContext){var t=this.frame.canvas.getContext("2d");this.pixelRatio=(window.devicePixelRatio||1)/(t.webkitBackingStorePixelRatio||t.mozBackingStorePixelRatio||t.msBackingStorePixelRatio||t.oBackingStorePixelRatio||t.backingStorePixelRatio||1),this.frame.canvas.getContext("2d").setTransform(this.pixelRatio,0,0,this.pixelRatio,0,0)}else{var e=document.createElement("DIV");e.style.color="red",e.style.fontWeight="bold",e.style.padding="10px",e.innerHTML="Error: your browser does not support HTML canvas",this.frame.canvas.appendChild(e)}var i=this;this.drag={},this.pinch={},this.hammer=new n(this.frame.canvas),this.hammer.get("pinch").set({enable:!0}),this.hammer.on("tap",i._onTap.bind(i)),this.hammer.on("doubletap",i._onDoubleTap.bind(i)),this.hammer.on("press",i._onHold.bind(i)),this.hammer.on("pinch",i._onPinch.bind(i)),h.onTouch(this.hammer,i._onTouch.bind(i)),this.hammer.on("panstart",i._onDragStart.bind(i)),this.hammer.on("panmove",i._onDrag.bind(i)),this.hammer.on("panend",i._onDragEnd.bind(i)),this.frame.canvas.addEventListener("mousemove",i._onMouseMoveTitle.bind(i)),this.frame.canvas.addEventListener("mousewheel",i._onMouseWheel.bind(i)),this.frame.canvas.addEventListener("DOMMouseScroll",i._onMouseWheel.bind(i)),this.containerElement.appendChild(this.frame)},s.prototype._createKeyBinds=function(){var t=this;void 0!==this.keycharm&&this.keycharm.destroy(),this.keycharm=r(),this.keycharm.reset(),this.constants.keyboard.enabled&&this.isActive()&&(this.keycharm.bind("up",this._moveUp.bind(t),"keydown"),this.keycharm.bind("up",this._yStopMoving.bind(t),"keyup"),this.keycharm.bind("down",this._moveDown.bind(t),"keydown"),this.keycharm.bind("down",this._yStopMoving.bind(t),"keyup"),this.keycharm.bind("left",this._moveLeft.bind(t),"keydown"),this.keycharm.bind("left",this._xStopMoving.bind(t),"keyup"),this.keycharm.bind("right",this._moveRight.bind(t),"keydown"),this.keycharm.bind("right",this._xStopMoving.bind(t),"keyup"),this.keycharm.bind("=",this._zoomIn.bind(t),"keydown"),this.keycharm.bind("=",this._stopZoom.bind(t),"keyup"),this.keycharm.bind("num+",this._zoomIn.bind(t),"keydown"),this.keycharm.bind("num+",this._stopZoom.bind(t),"keyup"),this.keycharm.bind("num-",this._zoomOut.bind(t),"keydown"),this.keycharm.bind("num-",this._stopZoom.bind(t),"keyup"),this.keycharm.bind("-",this._zoomOut.bind(t),"keydown"),this.keycharm.bind("-",this._stopZoom.bind(t),"keyup"),this.keycharm.bind("[",this._zoomIn.bind(t),"keydown"),this.keycharm.bind("[",this._stopZoom.bind(t),"keyup"),this.keycharm.bind("]",this._zoomOut.bind(t),"keydown"),this.keycharm.bind("]",this._stopZoom.bind(t),"keyup"),this.keycharm.bind("pageup",this._zoomIn.bind(t),"keydown"),this.keycharm.bind("pageup",this._stopZoom.bind(t),"keyup"),this.keycharm.bind("pagedown",this._zoomOut.bind(t),"keydown"),this.keycharm.bind("pagedown",this._stopZoom.bind(t),"keyup")),1==this.constants.dataManipulation.enabled&&(this.keycharm.bind("esc",this._createManipulatorBar.bind(t)),this.keycharm.bind("delete",this._deleteSelected.bind(t)))},s.prototype.destroy=function(){this.start=function(){},this.redraw=function(){},this.timer=!1,this._cleanupPhysicsConfiguration(),this.keycharm.reset(),this.hammer.destroy(),this.off(),this._recursiveDOMDelete(this.containerElement)},s.prototype._recursiveDOMDelete=function(t){for(;1==t.hasChildNodes();)this._recursiveDOMDelete(t.firstChild),t.removeChild(t.firstChild)},s.prototype._getPointer=function(t){return{x:t.x-a.getAbsoluteLeft(this.frame.canvas),y:t.y-a.getAbsoluteTop(this.frame.canvas)}},s.prototype._onTouch=function(t){(new Date).valueOf()-this.touchTime>100&&(this.drag.pointer=this._getPointer(t.center),this.drag.pinched=!1,this.pinch.scale=this._getScale(),this.touchTime=(new Date).valueOf(),this._handleTouch(this.drag.pointer))},s.prototype._onDragStart=function(t){this._handleDragStart(t)},s.prototype._handleDragStart=function(t){void 0===this.drag.pointer&&this._onTouch(t);var e=this._getNodeAt(this.drag.pointer);if(this.drag.dragging=!0,this.drag.selection=[],this.drag.translation=this._getTranslation(),this.drag.nodeId=null,this.draggingNodes=!1,null!=e&&1==this.constants.dragNodes){this.draggingNodes=!0,this.drag.nodeId=e.id,e.isSelected()||this._selectObject(e,!1),this.emit("dragStart",{nodeIds:this.getSelection().nodes});for(var i in this.selectionObj.nodes)if(this.selectionObj.nodes.hasOwnProperty(i)){var s=this.selectionObj.nodes[i],o={id:s.id,node:s,x:s.x,y:s.y,xFixed:s.xFixed,yFixed:s.yFixed};s.xFixed=!0,s.yFixed=!0,this.drag.selection.push(o)}}t.preventDefault()},s.prototype._onDrag=function(t){this._handleOnDrag(t)},s.prototype._handleOnDrag=function(t){if(!this.drag.pinched){this.releaseNode();var e=this._getPointer(t.center),i=this,s=this.drag,o=s.selection;if(o&&o.length&&1==this.constants.dragNodes){var n=e.x-s.pointer.x,r=e.y-s.pointer.y;o.forEach(function(t){var e=t.node;t.xFixed||(e.x=i._XconvertDOMtoCanvas(i._XconvertCanvasToDOM(t.x)+n)),t.yFixed||(e.y=i._YconvertDOMtoCanvas(i._YconvertCanvasToDOM(t.y)+r))}),this.moving||(this.moving=!0,this.start())}else if(1==this.constants.dragNetwork){if(void 0===this.drag.pointer)return void this._handleDragStart(t);var a=e.x-this.drag.pointer.x,h=e.y-this.drag.pointer.y;this._setTranslation(this.drag.translation.x+a,this.drag.translation.y+h),this._redraw()}t.preventDefault()}},s.prototype._onDragEnd=function(t){this._handleDragEnd(t)},s.prototype._handleDragEnd=function(t){this.drag.dragging=!1;var e=this.drag.selection;e&&e.length?(e.forEach(function(t){t.node.xFixed=t.xFixed,t.node.yFixed=t.yFixed}),this.moving=!0,this.start()):this._redraw(),0==this.draggingNodes?this.emit("dragEnd",{nodeIds:[]}):this.emit("dragEnd",{nodeIds:this.getSelection().nodes}),t.preventDefault()},s.prototype._onTap=function(t){var e=this._getPointer(t.center);this.pointerPosition=e,this._handleTap(e)},s.prototype._onDoubleTap=function(t){var e=this._getPointer(t.center);this._handleDoubleTap(e)},s.prototype._onHold=function(t){var e=this._getPointer(t.center);this.pointerPosition=e,this._handleOnHold(e)},s.prototype._onRelease=function(t){var e=this._getPointer(t.center);this._handleOnRelease(e)},s.prototype._onPinch=function(t){var e=this._getPointer(t.center);this.drag.pinched=!0,"scale"in this.pinch||(this.pinch.scale=1);var i=this.pinch.scale*t.scale;this._zoom(i,e)},s.prototype._zoom=function(t,e){if(1==this.constants.zoomable){var i=this._getScale();1e-5>t&&(t=1e-5),t>10&&(t=10);var s=null;void 0!==this.drag&&1==this.drag.dragging&&(s=this.DOMtoCanvas(this.drag.pointer));var o=this._getTranslation(),n=t/i,r=(1-n)*e.x+o.x*n,a=(1-n)*e.y+o.y*n;if(this.areaCenter={x:this._XconvertDOMtoCanvas(e.x),y:this._YconvertDOMtoCanvas(e.y)},this._setScale(t),this._setTranslation(r,a),this.updateClustersDefault(),null!=s){var h=this.canvasToDOM(s);this.drag.pointer.x=h.x,this.drag.pointer.y=h.y}return this._redraw(),t>i?this.emit("zoom",{direction:"+"}):this.emit("zoom",{direction:"-"}),t}},s.prototype._onMouseWheel=function(t){var e=0;if(t.wheelDelta?e=t.wheelDelta/120:t.detail&&(e=-t.detail/3),e){var i=this._getScale(),s=e/10;0>e&&(s/=1-s),i*=1+s;var o=this._getPointer({x:t.pageX,y:t.pageY});this._zoom(i,o)}t.preventDefault()},s.prototype._onMouseMoveTitle=function(t){var e=this._getPointer({x:t.pageX,y:t.pageY});this.popupObj&&this._checkHidePopup(e);var i=this,s=function(){i._checkShowPopup(e)};if(this.popupTimer&&clearInterval(this.popupTimer),this.drag.dragging||(this.popupTimer=setTimeout(s,this.constants.tooltip.delay)),1==this.constants.hover){for(var o in this.hoverObj.edges)this.hoverObj.edges.hasOwnProperty(o)&&(this.hoverObj.edges[o].hover=!1,delete this.hoverObj.edges[o]);var n=this._getNodeAt(e);null==n&&(n=this._getEdgeAt(e)),null!=n&&this._hoverObject(n);for(var r in this.hoverObj.nodes)this.hoverObj.nodes.hasOwnProperty(r)&&(n instanceof f&&n.id!=r||n instanceof g||null==n)&&(this._blurObject(this.hoverObj.nodes[r]),delete this.hoverObj.nodes[r]);this.redraw()}},s.prototype._checkShowPopup=function(t){var e,i={left:this._XconvertDOMtoCanvas(t.x),top:this._YconvertDOMtoCanvas(t.y),right:this._XconvertDOMtoCanvas(t.x),bottom:this._YconvertDOMtoCanvas(t.y)},s=this.popupObj,o=!1;if(void 0==this.popupObj){var n=this.nodes,r=[];for(e in n)if(n.hasOwnProperty(e)){var a=n[e];a.isOverlappingWith(i)&&void 0!==a.getTitle()&&r.push(e)}r.length>0&&(this.popupObj=this.nodes[r[r.length-1]],o=!0)}if(void 0===this.popupObj&&0==o){var h=this.edges,d=[];for(e in h)if(h.hasOwnProperty(e)){var l=h[e];l.connected&&void 0!==l.getTitle()&&l.isOverlappingWith(i)&&d.push(e)}d.length>0&&(this.popupObj=this.edges[d[d.length-1]])}if(this.popupObj){if(this.popupObj!=s){var c=this;c.popup||(c.popup=new v(c.frame,c.constants.tooltip)),c.popup.setPosition(t.x-3,t.y-3),c.popup.setText(c.popupObj.getTitle()),c.popup.show()}}else this.popup&&this.popup.hide()},s.prototype._checkHidePopup=function(t){this.popupObj&&this._getNodeAt(t)||(this.popupObj=void 0,this.popup&&this.popup.hide())},s.prototype.setSize=function(t,e){var i=!1,s=this.frame.canvas.width,o=this.frame.canvas.height;t!=this.constants.width||e!=this.constants.height||this.frame.style.width!=t||this.frame.style.height!=e?(this.frame.style.width=t,this.frame.style.height=e,this.frame.canvas.style.width="100%",this.frame.canvas.style.height="100%",this.frame.canvas.width=this.frame.canvas.clientWidth*this.pixelRatio,this.frame.canvas.height=this.frame.canvas.clientHeight*this.pixelRatio,this.constants.width=t,this.constants.height=e,i=!0):(this.frame.canvas.width!=this.frame.canvas.clientWidth*this.pixelRatio&&(this.frame.canvas.width=this.frame.canvas.clientWidth*this.pixelRatio,i=!0),this.frame.canvas.height!=this.frame.canvas.clientHeight*this.pixelRatio&&(this.frame.canvas.height=this.frame.canvas.clientHeight*this.pixelRatio,i=!0)),1==i&&this.emit("resize",{width:this.frame.canvas.width*this.pixelRatio,height:this.frame.canvas.height*this.pixelRatio,oldWidth:s*this.pixelRatio,oldHeight:o*this.pixelRatio})},s.prototype._setNodes=function(t){var e=this.nodesData;if(t instanceof d||t instanceof l)this.nodesData=t;else if(Array.isArray(t))this.nodesData=new d,this.nodesData.add(t);else{if(t)throw new TypeError("Array or DataSet expected");this.nodesData=new d}if(e&&a.forEach(this.nodesListeners,function(t,i){e.off(i,t)}),this.nodes={},this.nodesData){var i=this;a.forEach(this.nodesListeners,function(t,e){i.nodesData.on(e,t)});var s=this.nodesData.getIds();this._addNodes(s)}this._updateSelection()},s.prototype._addNodes=function(t){for(var e,i=0,s=t.length;s>i;i++){e=t[i];var o=this.nodesData.get(e),n=new f(o,this.images,this.groups,this.constants);if(this.nodes[e]=n,!(0!=n.xFixed&&0!=n.yFixed||null!==n.x&&null!==n.y)){var r=1*t.length+10,a=2*Math.PI*Math.random();0==n.xFixed&&(n.x=r*Math.cos(a)),0==n.yFixed&&(n.y=r*Math.sin(a))}this.moving=!0}this._updateNodeIndexList(),1==this.constants.hierarchicalLayout.enabled&&0==this.initializing&&(this._resetLevels(),this._setupHierarchicalLayout()),this._updateCalculationNodes(),this._reconnectEdges(),this._updateValueRange(this.nodes),this.updateLabels()},s.prototype._updateNodes=function(t,e){for(var i=this.nodes,s=0,o=t.length;o>s;s++){var n=t[s],r=i[n],a=e[s];r?r.setProperties(a,this.constants):(r=new f(properties,this.images,this.groups,this.constants),i[n]=r)}this.moving=!0,1==this.constants.hierarchicalLayout.enabled&&0==this.initializing&&(this._resetLevels(),this._setupHierarchicalLayout()),this._updateNodeIndexList(),this._updateValueRange(i)},s.prototype._removeNodes=function(t){for(var e=this.nodes,i=0,s=t.length;s>i;i++){var o=t[i];delete e[o]}this._updateNodeIndexList(),1==this.constants.hierarchicalLayout.enabled&&0==this.initializing&&(this._resetLevels(),this._setupHierarchicalLayout()),this._updateCalculationNodes(),this._reconnectEdges(),this._updateSelection(),this._updateValueRange(e)},s.prototype._setEdges=function(t){var e=this.edgesData;if(t instanceof d||t instanceof l)this.edgesData=t;else if(Array.isArray(t))this.edgesData=new d,this.edgesData.add(t);else{if(t)throw new TypeError("Array or DataSet expected");this.edgesData=new d}if(e&&a.forEach(this.edgesListeners,function(t,i){e.off(i,t)}),this.edges={},this.edgesData){var i=this;a.forEach(this.edgesListeners,function(t,e){i.edgesData.on(e,t)});var s=this.edgesData.getIds();this._addEdges(s)}this._reconnectEdges()},s.prototype._addEdges=function(t){for(var e=this.edges,i=this.edgesData,s=0,o=t.length;o>s;s++){var n=t[s],r=e[n];r&&r.disconnect();var a=i.get(n,{showInternalIds:!0});e[n]=new g(a,this,this.constants)}this.moving=!0,this._updateValueRange(e),this._createBezierNodes(),this._updateCalculationNodes(),1==this.constants.hierarchicalLayout.enabled&&0==this.initializing&&(this._resetLevels(),this._setupHierarchicalLayout())},s.prototype._updateEdges=function(t){for(var e=this.edges,i=this.edgesData,s=0,o=t.length;o>s;s++){var n=t[s],r=i.get(n),a=e[n];a?(a.disconnect(),a.setProperties(r,this.constants),a.connect()):(a=new g(r,this,this.constants),this.edges[n]=a)}this._createBezierNodes(),1==this.constants.hierarchicalLayout.enabled&&0==this.initializing&&(this._resetLevels(),this._setupHierarchicalLayout()),this.moving=!0,this._updateValueRange(e)},s.prototype._removeEdges=function(t){for(var e=this.edges,i=0,s=t.length;s>i;i++){var o=t[i],n=e[o];n&&(null!=n.via&&delete this.sectors.support.nodes[n.via.id],n.disconnect(),delete e[o])}this.moving=!0,this._updateValueRange(e),1==this.constants.hierarchicalLayout.enabled&&0==this.initializing&&(this._resetLevels(),this._setupHierarchicalLayout()),this._updateCalculationNodes()},s.prototype._reconnectEdges=function(){var t,e=this.nodes,i=this.edges;for(t in e)e.hasOwnProperty(t)&&(e[t].edges=[],e[t].dynamicEdges=[]);for(t in i)if(i.hasOwnProperty(t)){var s=i[t];s.from=null,s.to=null,s.connect()}},s.prototype._updateValueRange=function(t){var e,i=void 0,s=void 0;for(e in t)if(t.hasOwnProperty(e)){var o=t[e].getValue();void 0!==o&&(i=void 0===i?o:Math.min(o,i),s=void 0===s?o:Math.max(o,s))}if(void 0!==i&&void 0!==s)for(e in t)t.hasOwnProperty(e)&&t[e].setValueRange(i,s)},s.prototype.redraw=function(){this.setSize(this.constants.width,this.constants.height),this._redraw()},s.prototype._redraw=function(t){var e=this.frame.canvas.getContext("2d");e.setTransform(this.pixelRatio,0,0,this.pixelRatio,0,0);var i=this.frame.canvas.width*this.pixelRatio,s=this.frame.canvas.height*this.pixelRatio;e.clearRect(0,0,i,s),e.save(),e.translate(this.translation.x,this.translation.y),e.scale(this.scale,this.scale),this.canvasTopLeft={x:this._XconvertDOMtoCanvas(0),y:this._YconvertDOMtoCanvas(0)},this.canvasBottomRight={x:this._XconvertDOMtoCanvas(this.frame.canvas.clientWidth*this.pixelRatio),y:this._YconvertDOMtoCanvas(this.frame.canvas.clientHeight*this.pixelRatio)},1!=t&&(this._doInAllSectors("_drawAllSectorNodes",e),(0==this.drag.dragging||void 0===this.drag.dragging||0==this.constants.hideEdgesOnDrag)&&this._doInAllSectors("_drawEdges",e)),(0==this.drag.dragging||void 0===this.drag.dragging||0==this.constants.hideNodesOnDrag)&&this._doInAllSectors("_drawNodes",e,!1),1!=t&&1==this.controlNodesActive&&this._doInAllSectors("_drawControlNodes",e),e.restore(),1==t&&e.clearRect(0,0,i,s)},s.prototype._setTranslation=function(t,e){void 0===this.translation&&(this.translation={x:0,y:0}),void 0!==t&&(this.translation.x=t),void 0!==e&&(this.translation.y=e),this.emit("viewChanged")},s.prototype._getTranslation=function(){return{x:this.translation.x,y:this.translation.y}},s.prototype._setScale=function(t){this.scale=t},s.prototype._getScale=function(){return this.scale},s.prototype._XconvertDOMtoCanvas=function(t){return(t-this.translation.x)/this.scale},s.prototype._XconvertCanvasToDOM=function(t){return t*this.scale+this.translation.x},s.prototype._YconvertDOMtoCanvas=function(t){return(t-this.translation.y)/this.scale},s.prototype._YconvertCanvasToDOM=function(t){return t*this.scale+this.translation.y},s.prototype.canvasToDOM=function(t){return{x:this._XconvertCanvasToDOM(t.x),y:this._YconvertCanvasToDOM(t.y)}},s.prototype.DOMtoCanvas=function(t){return{x:this._XconvertDOMtoCanvas(t.x),y:this._YconvertDOMtoCanvas(t.y)}},s.prototype._drawNodes=function(t,e){void 0===e&&(e=!1);var i=this.nodes,s=[];for(var o in i)i.hasOwnProperty(o)&&(i[o].setScaleAndPos(this.scale,this.canvasTopLeft,this.canvasBottomRight),i[o].isSelected()?s.push(o):(i[o].inArea()||e)&&i[o].draw(t));for(var n=0,r=s.length;r>n;n++)(i[s[n]].inArea()||e)&&i[s[n]].draw(t)},s.prototype._drawEdges=function(t){var e=this.edges;for(var i in e)if(e.hasOwnProperty(i)){var s=e[i];s.setScale(this.scale),s.connected&&e[i].draw(t)}},s.prototype._drawControlNodes=function(t){var e=this.edges;for(var i in e)e.hasOwnProperty(i)&&e[i]._drawControlNodes(t)},s.prototype._stabilize=function(){1==this.constants.freezeForStabilization&&this._freezeDefinedNodes();for(var t=0;this.moving&&t0)for(t in i)i.hasOwnProperty(t)&&(i[t].discreteStepLimited(e,this.constants.maxVelocity),s=!0);else for(t in i)i.hasOwnProperty(t)&&(i[t].discreteStep(e),s=!0);if(1==s){var o=this.constants.minVelocity/Math.max(this.scale,.05);return o>.5*this.constants.maxVelocity?!0:this._isMoving(o)}return!1},s.prototype._revertPhysicsState=function(){var t=this.nodes;for(var e in t)t.hasOwnProperty(e)&&t[e].revertPosition()},s.prototype._revertPhysicsTick=function(){this._doInAllActiveSectors("_revertPhysicsState"),1==this.constants.smoothCurves.enabled&&1==this.constants.smoothCurves.dynamic&&this._doInSupportSector("_revertPhysicsState")},s.prototype._physicsTick=function(){if(!this.freezeSimulation&&1==this.moving){var t=!1,e=!1;this._doInAllActiveSectors("_initializeForceCalculation");var i=this._doInAllActiveSectors("_discreteStepNodes");1==this.constants.smoothCurves.enabled&&1==this.constants.smoothCurves.dynamic&&(e=this._doInSupportSector("_discreteStepNodes"));for(var s=0;s2*e||1==this.runDoubleSpeed)&&1==this.moving&&(this._physicsTick(),0!=this.renderTime&&(this.runDoubleSpeed=!0));var i=Date.now();this._redraw(),this.renderTime=Date.now()-i,this.start()},"undefined"!=typeof window&&(window.requestAnimationFrame=window.requestAnimationFrame||window.mozRequestAnimationFrame||window.webkitRequestAnimationFrame||window.msRequestAnimationFrame),s.prototype.start=function(){if(1==this.moving||0!=this.xIncrement||0!=this.yIncrement||0!=this.zoomIncrement)this.timer||(this.timer=1==this.requiresTimeout?window.setTimeout(this._animationStep.bind(this),this.renderTimestep):window.requestAnimationFrame(this._animationStep.bind(this)));else if(this._redraw(),this.stabilizationIterations>1){var t=this,e={iterations:t.stabilizationIterations};this.stabilizationIterations=0,this.startedStabilization=!1,setTimeout(function(){t.emit("stabilized",e)},0)}else this.stabilizationIterations=0},s.prototype._handleNavigation=function(){if(0!=this.xIncrement||0!=this.yIncrement){var t=this._getTranslation();this._setTranslation(t.x+this.xIncrement,t.y+this.yIncrement)}if(0!=this.zoomIncrement){var e={x:this.frame.canvas.clientWidth/2,y:this.frame.canvas.clientHeight/2};this._zoom(this.scale*(1+this.zoomIncrement),e)}},s.prototype.toggleFreeze=function(){0==this.freezeSimulation?this.freezeSimulation=!0:(this.freezeSimulation=!1,this.start())},s.prototype._configureSmoothCurves=function(t){if(void 0===t&&(t=!0),1==this.constants.smoothCurves.enabled&&1==this.constants.smoothCurves.dynamic){this._createBezierNodes();for(var e in this.sectors.support.nodes)this.sectors.support.nodes.hasOwnProperty(e)&&void 0===this.edges[this.sectors.support.nodes[e].parentEdgeId]&&delete this.sectors.support.nodes[e]}else{this.sectors.support.nodes={};for(var i in this.edges)this.edges.hasOwnProperty(i)&&(this.edges[i].via=null)}this._updateCalculationNodes(),t||(this.moving=!0,this.start())},s.prototype._createBezierNodes=function(){if(1==this.constants.smoothCurves.enabled&&1==this.constants.smoothCurves.dynamic)for(var t in this.edges)if(this.edges.hasOwnProperty(t)){var e=this.edges[t];if(null==e.via){var i="edgeId:".concat(e.id);this.sectors.support.nodes[i]=new f({id:i,mass:1,shape:"circle",image:"",internalMultiplier:1},{},{},this.constants),e.via=this.sectors.support.nodes[i],e.via.parentEdgeId=e.id,e.positionBezierNode()}}},s.prototype._initializeMixinLoaders=function(){for(var t in y)y.hasOwnProperty(t)&&(s.prototype[t]=y[t])},s.prototype.storePosition=function(){console.log("storePosition is deprecated: use .storePositions() from now on."),this.storePositions()},s.prototype.storePositions=function(){var t=[];for(var e in this.nodes)if(this.nodes.hasOwnProperty(e)){var i=this.nodes[e],s=!this.nodes.xFixed,o=!this.nodes.yFixed;(this.nodesData._data[e].x!=Math.round(i.x)||this.nodesData._data[e].y!=Math.round(i.y))&&t.push({id:e,x:Math.round(i.x),y:Math.round(i.y),allowedToMoveX:s,allowedToMoveY:o})}this.nodesData.update(t)},s.prototype.getPositions=function(t){var e={};if(void 0!==t){if(1==Array.isArray(t)){for(var i=0;i=1&&(this.easingTime=0,this._redraw=null!=this.lockedOnNodeId?this._lockedRedraw:this._classicRedraw,this.emit("animationFinished"))},s.prototype._classicRedraw=function(){},s.prototype.isActive=function(){return!this.activator||this.activator.active},s.prototype.setScale=function(){return this._setScale()},s.prototype.getScale=function(){return this._getScale()},s.prototype.getCenterCoordinates=function(){return this.DOMtoCanvas({x:.5*this.frame.canvas.clientWidth,y:.5*this.frame.canvas.clientHeight})},s.prototype.getBoundingBox=function(t){return void 0!==this.nodes[t]?this.nodes[t].boundingBox:void 0},t.exports=s},function(t,e,i){function s(t,e,i){if(!e)throw"No network provided";var s=["edges","physics"],n=o.selectiveBridgeObject(s,i);this.options=n.edges,this.physics=n.physics,this.options.smoothCurves=i.smoothCurves,this.network=e,this.id=void 0,this.fromId=void 0,this.toId=void 0,this.title=void 0,this.widthSelected=this.options.width*this.options.widthSelectionMultiplier,this.value=void 0,this.selected=!1,this.hover=!1,this.labelDimensions={top:0,left:0,width:0,height:0,yLine:0},this.dirtyLabel=!0,this.from=null,this.to=null,this.via=null,this.fromBackup=null,this.toBackup=null,this.originalFromId=[],this.originalToId=[],this.connected=!1,this.widthFixed=!1,this.lengthFixed=!1,this.setProperties(t),this.controlNodesEnabled=!1,this.controlNodes={from:null,to:null,positions:{}},this.connectedNode=null}var o=i(1),n=i(40);s.prototype.setProperties=function(t){if(t){var e=["style","fontSize","fontFace","fontColor","fontFill","fontStrokeWidth","fontStrokeColor","width","widthSelectionMultiplier","hoverWidth","arrowScaleFactor","dash","inheritColor","labelAlignment"];switch(o.selectiveDeepExtend(e,this.options,t),void 0!==t.from&&(this.fromId=t.from),void 0!==t.to&&(this.toId=t.to),void 0!==t.id&&(this.id=t.id),void 0!==t.label&&(this.label=t.label,this.dirtyLabel=!0),void 0!==t.title&&(this.title=t.title),void 0!==t.value&&(this.value=t.value),void 0!==t.length&&(this.physics.springLength=t.length),void 0!==t.color&&(this.options.inheritColor=!1,o.isString(t.color)?(this.options.color.color=t.color,this.options.color.highlight=t.color):(void 0!==t.color.color&&(this.options.color.color=t.color.color),void 0!==t.color.highlight&&(this.options.color.highlight=t.color.highlight),void 0!==t.color.hover&&(this.options.color.hover=t.color.hover))),this.connect(),this.widthFixed=this.widthFixed||void 0!==t.width,this.lengthFixed=this.lengthFixed||void 0!==t.length,this.widthSelected=this.options.width*this.options.widthSelectionMultiplier,this.options.style){case"line":this.draw=this._drawLine;break;case"arrow":this.draw=this._drawArrow;break;case"arrow-center":this.draw=this._drawArrowCenter;break;case"dash-line":this.draw=this._drawDashLine;break;default:this.draw=this._drawLine}}},s.prototype.connect=function(){this.disconnect(),this.from=this.network.nodes[this.fromId]||null,this.to=this.network.nodes[this.toId]||null,this.connected=this.from&&this.to,this.connected?(this.from.attachEdge(this),this.to.attachEdge(this)):(this.from&&this.from.detachEdge(this),this.to&&this.to.detachEdge(this))},s.prototype.disconnect=function(){this.from&&(this.from.detachEdge(this),this.from=null),this.to&&(this.to.detachEdge(this),this.to=null),this.connected=!1},s.prototype.getTitle=function(){return"function"==typeof this.title?this.title():this.title +},s.prototype.getValue=function(){return this.value},s.prototype.setValueRange=function(t,e){if(!this.widthFixed&&void 0!==this.value){var i=(this.options.widthMax-this.options.widthMin)/(e-t);this.options.width=(this.value-t)*i+this.options.widthMin,this.widthSelected=this.options.width*this.options.widthSelectionMultiplier}},s.prototype.draw=function(){throw"Method draw not initialized in edge"},s.prototype.isOverlappingWith=function(t){if(this.connected){var e=10,i=this.from.x,s=this.from.y,o=this.to.x,n=this.to.y,r=t.left,a=t.top,h=this._getDistanceToEdge(i,s,o,n,r,a);return e>h}return!1},s.prototype._getColor=function(){var t=this.options.color;return"to"==this.options.inheritColor?t={highlight:this.to.options.color.highlight.border,hover:this.to.options.color.hover.border,color:this.to.options.color.border}:("from"==this.options.inheritColor||1==this.options.inheritColor)&&(t={highlight:this.from.options.color.highlight.border,hover:this.from.options.color.hover.border,color:this.from.options.color.border}),1==this.selected?t.highlight:1==this.hover?t.hover:t.color},s.prototype._drawLine=function(t){if(t.strokeStyle=this._getColor(),t.lineWidth=this._getLineWidth(),this.from!=this.to){var e,i=this._line(t);if(this.label){if(1==this.options.smoothCurves.enabled&&null!=i){var s=.5*(.5*(this.from.x+i.x)+.5*(this.to.x+i.x)),o=.5*(.5*(this.from.y+i.y)+.5*(this.to.y+i.y));e={x:s,y:o}}else e=this._pointOnLine(.5);this._label(t,this.label,e.x,e.y)}}else{var n,r,a=this.physics.springLength/4,h=this.from;h.width||h.resize(t),h.width>h.height?(n=h.x+h.width/2,r=h.y-a):(n=h.x+a,r=h.y-h.height/2),this._circle(t,n,r,a),e=this._pointOnCircle(n,r,a,.5),this._label(t,this.label,e.x,e.y)}},s.prototype._getLineWidth=function(){return 1==this.selected?Math.max(Math.min(this.widthSelected,this.options.widthMax),.3*this.networkScaleInv):1==this.hover?Math.max(Math.min(this.options.hoverWidth,this.options.widthMax),.3*this.networkScaleInv):Math.max(this.options.width,.3*this.networkScaleInv)},s.prototype._getViaCoordinates=function(){if(1==this.options.smoothCurves.dynamic&&1==this.options.smoothCurves.enabled)return this.via;if(0==this.options.smoothCurves.enabled)return{x:0,y:0};var t=null,e=null,i=this.options.smoothCurves.roundness,s=this.options.smoothCurves.type,o=Math.abs(this.from.x-this.to.x),n=Math.abs(this.from.y-this.to.y);return"discrete"==s||"diagonalCross"==s?Math.abs(this.from.x-this.to.x)this.to.y?this.from.xthis.to.x&&(t=this.from.x-i*n,e=this.from.y-i*n):this.from.ythis.to.x&&(t=this.from.x-i*n,e=this.from.y+i*n)),"discrete"==s&&(t=i*n>o?this.from.x:t)):Math.abs(this.from.x-this.to.x)>Math.abs(this.from.y-this.to.y)&&(this.from.y>this.to.y?this.from.xthis.to.x&&(t=this.from.x-i*o,e=this.from.y-i*o):this.from.ythis.to.x&&(t=this.from.x-i*o,e=this.from.y+i*o)),"discrete"==s&&(e=i*o>n?this.from.y:e)):"straightCross"==s?Math.abs(this.from.x-this.to.x)Math.abs(this.from.y-this.to.y)&&(t=this.from.xthis.to.y?this.from.xthis.to.x&&(t=this.from.x-i*n,e=this.from.y-i*n,t=this.to.x>t?this.to.x:t):this.from.ythis.to.x&&(t=this.from.x-i*n,e=this.from.y+i*n,t=this.to.x>t?this.to.x:t)):Math.abs(this.from.x-this.to.x)>Math.abs(this.from.y-this.to.y)&&(this.from.y>this.to.y?this.from.xe?this.to.y:e):this.from.x>this.to.x&&(t=this.from.x-i*o,e=this.from.y-i*o,e=this.to.y>e?this.to.y:e):this.from.ythis.to.x&&(t=this.from.x-i*o,e=this.from.y+i*o,e=this.to.yd;d++){var l=t.measureText(n[d]).width;h=l>h?l:h}var c=this.options.fontSize*r,p=i-h/2,u=s-c/2;this.labelDimensions={top:u,left:p,width:h,height:c,yLine:o}}var o=this.labelDimensions.yLine;t.save(),"horizontal"!=this.options.labelAlignment&&(t.translate(i,o),this._rotateForLabelAlignment(t),i=0,o=0),this._drawLabelRect(t),this._drawLabelText(t,i,o,n,r,a),t.restore()}},s.prototype._rotateForLabelAlignment=function(t){var e=this.from.y-this.to.y,i=this.from.x-this.to.x,s=Math.atan2(e,i);(-1>s&&0>i||s>0&&0>i)&&(s+=Math.PI),t.rotate(s)},s.prototype._drawLabelRect=function(t){if(void 0!==this.options.fontFill&&null!==this.options.fontFill&&"none"!==this.options.fontFill){t.fillStyle=this.options.fontFill;var e=2;"line-center"==this.options.labelAlignment?t.fillRect(.5*-this.labelDimensions.width,.5*-this.labelDimensions.height,this.labelDimensions.width,this.labelDimensions.height):"line-above"==this.options.labelAlignment?t.fillRect(.5*-this.labelDimensions.width,-(this.labelDimensions.height+e),this.labelDimensions.width,this.labelDimensions.height):"line-below"==this.options.labelAlignment?t.fillRect(.5*-this.labelDimensions.width,e,this.labelDimensions.width,this.labelDimensions.height):t.fillRect(this.labelDimensions.left,this.labelDimensions.top,this.labelDimensions.width,this.labelDimensions.height)}},s.prototype._drawLabelText=function(t,e,i,s,o,n){if(t.fillStyle=this.options.fontColor||"black",t.textAlign="center","horizontal"!=this.options.labelAlignment){var r=2;"line-above"==this.options.labelAlignment?(t.textBaseline="alphabetic",i-=2*r):"line-below"==this.options.labelAlignment?(t.textBaseline="hanging",i+=2*r):t.textBaseline="middle"}else t.textBaseline="middle";this.options.fontStrokeWidth>0&&(t.lineWidth=this.options.fontStrokeWidth,t.strokeStyle=this.options.fontStrokeColor,t.lineJoin="round");for(var a=0;o>a;a++)this.options.fontStrokeWidth>0&&t.strokeText(s[a],e,i),t.fillText(s[a],e,i),i+=n},s.prototype._drawDashLine=function(t){t.strokeStyle=this._getColor(),t.lineWidth=this._getLineWidth();var e=null;if(void 0!==t.setLineDash){t.save();var i=[0];i=void 0!==this.options.dash.length&&void 0!==this.options.dash.gap?[this.options.dash.length,this.options.dash.gap]:[5,5],t.setLineDash(i),t.lineDashOffset=0,e=this._line(t),t.setLineDash([0]),t.lineDashOffset=0,t.restore()}else t.beginPath(),t.lineCap="round",void 0!==this.options.dash.altLength?t.dashedLine(this.from.x,this.from.y,this.to.x,this.to.y,[this.options.dash.length,this.options.dash.gap,this.options.dash.altLength,this.options.dash.gap]):void 0!==this.options.dash.length&&void 0!==this.options.dash.gap?t.dashedLine(this.from.x,this.from.y,this.to.x,this.to.y,[this.options.dash.length,this.options.dash.gap]):(t.moveTo(this.from.x,this.from.y),t.lineTo(this.to.x,this.to.y)),t.stroke();if(this.label){var s;if(1==this.options.smoothCurves.enabled&&null!=e){var o=.5*(.5*(this.from.x+e.x)+.5*(this.to.x+e.x)),n=.5*(.5*(this.from.y+e.y)+.5*(this.to.y+e.y));s={x:o,y:n}}else s=this._pointOnLine(.5);this._label(t,this.label,s.x,s.y)}},s.prototype._pointOnLine=function(t){return{x:(1-t)*this.from.x+t*this.to.x,y:(1-t)*this.from.y+t*this.to.y}},s.prototype._pointOnCircle=function(t,e,i,s){var o=2*(s-3/8)*Math.PI;return{x:t+i*Math.cos(o),y:e-i*Math.sin(o)}},s.prototype._drawArrowCenter=function(t){var e;if(t.strokeStyle=this._getColor(),t.fillStyle=t.strokeStyle,t.lineWidth=this._getLineWidth(),this.from!=this.to){var i=this._line(t),s=Math.atan2(this.to.y-this.from.y,this.to.x-this.from.x),o=(10+5*this.options.width)*this.options.arrowScaleFactor;if(1==this.options.smoothCurves.enabled&&null!=i){var n=.5*(.5*(this.from.x+i.x)+.5*(this.to.x+i.x)),r=.5*(.5*(this.from.y+i.y)+.5*(this.to.y+i.y));e={x:n,y:r}}else e=this._pointOnLine(.5);t.arrow(e.x,e.y,s,o),t.fill(),t.stroke(),this.label&&this._label(t,this.label,e.x,e.y)}else{var a,h,d=.25*Math.max(100,this.physics.springLength),l=this.from;l.width||l.resize(t),l.width>l.height?(a=l.x+.5*l.width,h=l.y-d):(a=l.x+d,h=l.y-.5*l.height),this._circle(t,a,h,d);var s=.2*Math.PI,o=(10+5*this.options.width)*this.options.arrowScaleFactor;e=this._pointOnCircle(a,h,d,.5),t.arrow(e.x,e.y,s,o),t.fill(),t.stroke(),this.label&&(e=this._pointOnCircle(a,h,d,.5),this._label(t,this.label,e.x,e.y))}},s.prototype._pointOnBezier=function(t){var e=this._getViaCoordinates(),i=Math.pow(1-t,2)*this.from.x+2*t*(1-t)*e.x+Math.pow(t,2)*this.to.x,s=Math.pow(1-t,2)*this.from.y+2*t*(1-t)*e.y+Math.pow(t,2)*this.to.y;return{x:i,y:s}},s.prototype._findBorderPosition=function(t,e){var i,s,o,n,r,a=10,h=0,d=0,l=1,c=.2,p=this.to;for(1==t&&(p=this.from);l>=d&&a>h;){var u=.5*(d+l);if(i=this._pointOnBezier(u),s=Math.atan2(p.y-i.y,p.x-i.x),o=p.distanceToBorder(e,s),n=Math.sqrt(Math.pow(i.x-p.x,2)+Math.pow(i.y-p.y,2)),r=o-n,Math.abs(r)r?0==t?d=u:l=u:0==t?l=u:d=u,h++}return i.t=u,i},s.prototype._drawArrow=function(t){t.strokeStyle=this._getColor(),t.fillStyle=t.strokeStyle,t.lineWidth=this._getLineWidth();var e,i,s;if(this.from!=this.to){if(this._line(t),1==this.options.smoothCurves.enabled){var o=this._getViaCoordinates();s=this._findBorderPosition(!1,t);var n=this._pointOnBezier(Math.max(0,s.t-.1));e=Math.atan2(s.y-n.y,s.x-n.x)}else{e=Math.atan2(this.to.y-this.from.y,this.to.x-this.from.x);var r=this.to.x-this.from.x,a=this.to.y-this.from.y,h=Math.sqrt(r*r+a*a),d=this.to.distanceToBorder(t,e),l=(h-d)/h;s={},s.x=(1-l)*this.from.x+l*this.to.x,s.y=(1-l)*this.from.y+l*this.to.y}if(i=(10+5*this.options.width)*this.options.arrowScaleFactor,t.arrow(s.x,s.y,e,i),t.fill(),t.stroke(),this.label){var c;c=1==this.options.smoothCurves.enabled&&null!=o?this._pointOnBezier(.5):this._pointOnLine(.5),this._label(t,this.label,c.x,c.y)}}else{var p,u,m,f=this.from,g=.25*Math.max(100,this.physics.springLength);f.width||f.resize(t),f.width>f.height?(p=f.x+.5*f.width,u=f.y-g,m={x:p,y:f.y,angle:.9*Math.PI}):(p=f.x+g,u=f.y-.5*f.height,m={x:f.x,y:u,angle:.6*Math.PI}),t.beginPath(),t.arc(p,u,g,0,2*Math.PI,!1),t.stroke();var i=(10+5*this.options.width)*this.options.arrowScaleFactor;t.arrow(m.x,m.y,m.angle,i),t.fill(),t.stroke(),this.label&&(c=this._pointOnCircle(p,u,g,.5),this._label(t,this.label,c.x,c.y))}},s.prototype._getDistanceToEdge=function(t,e,i,s,o,n){var r=0;if(this.from!=this.to)if(1==this.options.smoothCurves.enabled){var a,h;if(1==this.options.smoothCurves.enabled&&1==this.options.smoothCurves.dynamic)a=this.via.x,h=this.via.y;else{var d=this._getViaCoordinates();a=d.x,h=d.y}var l,c,p,u,m,f,g,v=1e9;for(c=0;10>c;c++)p=.1*c,u=Math.pow(1-p,2)*t+2*p*(1-p)*a+Math.pow(p,2)*i,m=Math.pow(1-p,2)*e+2*p*(1-p)*h+Math.pow(p,2)*s,c>0&&(l=this._getDistanceToLine(f,g,u,m,o,n),v=v>l?l:v),f=u,g=m;r=v}else r=this._getDistanceToLine(t,e,i,s,o,n);else{var u,m,y,b,_=.25*this.physics.springLength,x=this.from;x.width>x.height?(u=x.x+.5*x.width,m=x.y-_):(u=x.x+_,m=x.y-.5*x.height),y=u-o,b=m-n,r=Math.abs(Math.sqrt(y*y+b*b)-_)}return this.labelDimensions.lefto&&this.labelDimensions.topn?0:r},s.prototype._getDistanceToLine=function(t,e,i,s,o,n){var r=i-t,a=s-e,h=r*r+a*a,d=((o-t)*r+(n-e)*a)/h;d>1?d=1:0>d&&(d=0);var l=t+d*r,c=e+d*a,p=l-o,u=c-n;return Math.sqrt(p*p+u*u)},s.prototype.setScale=function(t){this.networkScaleInv=1/t},s.prototype.select=function(){this.selected=!0},s.prototype.unselect=function(){this.selected=!1},s.prototype.positionBezierNode=function(){null!==this.via&&null!==this.from&&null!==this.to?(this.via.x=.5*(this.from.x+this.to.x),this.via.y=.5*(this.from.y+this.to.y)):(this.via.x=0,this.via.y=0)},s.prototype._drawControlNodes=function(t){if(1==this.controlNodesEnabled){if(null===this.controlNodes.from&&null===this.controlNodes.to){var e="edgeIdFrom:".concat(this.id),i="edgeIdTo:".concat(this.id),s={nodes:{group:"",radius:7,borderWidth:2,borderWidthSelected:2},physics:{damping:0},clustering:{maxNodeSizeIncrements:0,nodeScaling:{width:0,height:0,radius:0}}};this.controlNodes.from=new n({id:e,shape:"dot",color:{background:"#ff0000",border:"#3c3c3c",highlight:{background:"#07f968"}}},{},{},s),this.controlNodes.to=new n({id:i,shape:"dot",color:{background:"#ff0000",border:"#3c3c3c",highlight:{background:"#07f968"}}},{},{},s)}this.controlNodes.positions={},0==this.controlNodes.from.selected&&(this.controlNodes.positions.from=this.getControlNodeFromPosition(t),this.controlNodes.from.x=this.controlNodes.positions.from.x,this.controlNodes.from.y=this.controlNodes.positions.from.y),0==this.controlNodes.to.selected&&(this.controlNodes.positions.to=this.getControlNodeToPosition(t),this.controlNodes.to.x=this.controlNodes.positions.to.x,this.controlNodes.to.y=this.controlNodes.positions.to.y),this.controlNodes.from.draw(t),this.controlNodes.to.draw(t)}else this.controlNodes={from:null,to:null,positions:{}}},s.prototype._enableControlNodes=function(){this.fromBackup=this.from,this.toBackup=this.to,this.controlNodesEnabled=!0},s.prototype._disableControlNodes=function(){this.fromId=this.from.id,this.toId=this.to.id,this.fromId!=this.fromBackup.id?this.fromBackup.detachEdge(this):this.toId!=this.toBackup.id&&this.toBackup.detachEdge(this),this.fromBackup=null,this.toBackup=null,this.controlNodesEnabled=!1},s.prototype._getSelectedControlNode=function(t,e){var i=this.controlNodes.positions,s=Math.sqrt(Math.pow(t-i.from.x,2)+Math.pow(e-i.from.y,2)),o=Math.sqrt(Math.pow(t-i.to.x,2)+Math.pow(e-i.to.y,2));return 15>s?(this.connectedNode=this.from,this.from=this.controlNodes.from,this.controlNodes.from):15>o?(this.connectedNode=this.to,this.to=this.controlNodes.to,this.controlNodes.to):null},s.prototype._restoreControlNodes=function(){1==this.controlNodes.from.selected?(this.from=this.connectedNode,this.connectedNode=null,this.controlNodes.from.unselect()):1==this.controlNodes.to.selected&&(this.to=this.connectedNode,this.connectedNode=null,this.controlNodes.to.unselect())},s.prototype.getControlNodeFromPosition=function(t){var e;if(1==this.options.smoothCurves.enabled)e=this._findBorderPosition(!0,t);else{var i=Math.atan2(this.to.y-this.from.y,this.to.x-this.from.x),s=this.to.x-this.from.x,o=this.to.y-this.from.y,n=Math.sqrt(s*s+o*o),r=this.from.distanceToBorder(t,i+Math.PI),a=(n-r)/n;e={},e.x=a*this.from.x+(1-a)*this.to.x,e.y=a*this.from.y+(1-a)*this.to.y}return e},s.prototype.getControlNodeToPosition=function(t){var e;if(1==this.options.smoothCurves.enabled)e=this._findBorderPosition(!1,t);else{var i=Math.atan2(this.to.y-this.from.y,this.to.x-this.from.x),s=this.to.x-this.from.x,o=this.to.y-this.from.y,n=Math.sqrt(s*s+o*o),r=this.to.distanceToBorder(t,i),a=(n-r)/n;e={},e.x=(1-a)*this.from.x+a*this.to.x,e.y=(1-a)*this.from.y+a*this.to.y}return e},t.exports=s},function(t,e,i){function s(){this.clear(),this.defaultIndex=0}i(1);s.DEFAULT=[{border:"#2B7CE9",background:"#97C2FC",highlight:{border:"#2B7CE9",background:"#D2E5FF"},hover:{border:"#2B7CE9",background:"#D2E5FF"}},{border:"#FFA500",background:"#FFFF00",highlight:{border:"#FFA500",background:"#FFFFA3"},hover:{border:"#FFA500",background:"#FFFFA3"}},{border:"#FA0A10",background:"#FB7E81",highlight:{border:"#FA0A10",background:"#FFAFB1"},hover:{border:"#FA0A10",background:"#FFAFB1"}},{border:"#41A906",background:"#7BE141",highlight:{border:"#41A906",background:"#A1EC76"},hover:{border:"#41A906",background:"#A1EC76"}},{border:"#E129F0",background:"#EB7DF4",highlight:{border:"#E129F0",background:"#F0B3F5"},hover:{border:"#E129F0",background:"#F0B3F5"}},{border:"#7C29F0",background:"#AD85E4",highlight:{border:"#7C29F0",background:"#D3BDF0"},hover:{border:"#7C29F0",background:"#D3BDF0"}},{border:"#C37F00",background:"#FFA807",highlight:{border:"#C37F00",background:"#FFCA66"},hover:{border:"#C37F00",background:"#FFCA66"}},{border:"#4220FB",background:"#6E6EFD",highlight:{border:"#4220FB",background:"#9B9BFD"},hover:{border:"#4220FB",background:"#9B9BFD"}},{border:"#FD5A77",background:"#FFC0CB",highlight:{border:"#FD5A77",background:"#FFD1D9"},hover:{border:"#FD5A77",background:"#FFD1D9"}},{border:"#4AD63A",background:"#C2FABC",highlight:{border:"#4AD63A",background:"#E6FFE3"},hover:{border:"#4AD63A",background:"#E6FFE3"}}],s.prototype.clear=function(){this.groups={},this.groups.length=function(){var t=0;for(var e in this)this.hasOwnProperty(e)&&t++;return t}},s.prototype.get=function(t){var e=this.groups[t];if(void 0==e){var i=this.defaultIndex%s.DEFAULT.length;this.defaultIndex++,e={},e.color=s.DEFAULT[i],this.groups[t]=e}return e},s.prototype.add=function(t,e){return this.groups[t]=e,e},t.exports=s},function(t){function e(){this.images={},this.imageBroken={},this.callback=void 0}e.prototype.setOnloadCallback=function(t){this.callback=t},e.prototype.load=function(t,e){var i=this.images[t];if(void 0===i){var s=this;i=new Image,i.onload=function(){0==this.width&&(document.body.appendChild(this),this.width=this.offsetWidth,this.height=this.offsetHeight,document.body.removeChild(this)),s.callback&&(s.images[t]=i,s.callback(this))},i.onerror=function(){void 0===e?(console.error("Could not load image:",t),delete this.src,s.callback&&s.callback(this)):s.imageBroken[t]===!0?(console.error("Could not load brokenImage:",e),delete this.src,s.callback&&s.callback(this)):(this.src=e,s.imageBroken[t]=!0)},i.src=t}return i},t.exports=e},function(t,e,i){function s(t,e,i,s){var n=o.selectiveBridgeObject(["nodes"],s);this.options=n.nodes,this.selected=!1,this.hover=!1,this.edges=[],this.dynamicEdges=[],this.reroutedEdges={},this.fontDrawThreshold=3,this.id=void 0,this.allowedToMoveX=!1,this.allowedToMoveY=!1,this.xFixed=!1,this.yFixed=!1,this.horizontalAlignLeft=!0,this.verticalAlignTop=!0,this.baseRadiusValue=s.nodes.radius,this.radiusFixed=!1,this.level=-1,this.preassignedLevel=!1,this.hierarchyEnumerated=!1,this.labelDimensions={top:0,left:0,width:0,height:0,yLine:0},this.boundingBox={top:0,left:0,right:0,bottom:0},this.imagelist=e,this.grouplist=i,this.fx=0,this.fy=0,this.vx=0,this.vy=0,this.x=null,this.y=null,this.previousState={vx:0,vy:0,x:0,y:0},this.damping=s.physics.damping,this.fixedData={x:null,y:null},this.setProperties(t,n),this.resetCluster(),this.dynamicEdgesLength=0,this.clusterSession=0,this.clusterSizeWidthFactor=s.clustering.nodeScaling.width,this.clusterSizeHeightFactor=s.clustering.nodeScaling.height,this.clusterSizeRadiusFactor=s.clustering.nodeScaling.radius,this.maxNodeSizeIncrements=s.clustering.maxNodeSizeIncrements,this.growthIndicator=0,this.networkScaleInv=1,this.networkScale=1,this.canvasTopLeft={x:-300,y:-300},this.canvasBottomRight={x:300,y:300},this.parentEdgeId=null}var o=i(1);s.prototype.revertPosition=function(){this.x=this.previousState.x,this.y=this.previousState.y,this.vx=this.previousState.vx,this.vy=this.previousState.vy},s.prototype.resetCluster=function(){this.formationScale=void 0,this.clusterSize=1,this.containedNodes={},this.containedEdges={},this.clusterSessions=[]},s.prototype.attachEdge=function(t){-1==this.edges.indexOf(t)&&this.edges.push(t),-1==this.dynamicEdges.indexOf(t)&&this.dynamicEdges.push(t),this.dynamicEdgesLength=this.dynamicEdges.length},s.prototype.detachEdge=function(t){var e=this.edges.indexOf(t);-1!=e&&this.edges.splice(e,1),e=this.dynamicEdges.indexOf(t),-1!=e&&this.dynamicEdges.splice(e,1),this.dynamicEdgesLength=this.dynamicEdges.length},s.prototype.setProperties=function(t,e){if(t){var i=["borderWidth","borderWidthSelected","shape","image","brokenImage","radius","fontColor","fontSize","fontFace","fontFill","fontStrokeWidth","fontStrokeColor","group","mass"];if(o.selectiveDeepExtend(i,this.options,t),void 0!==t.id&&(this.id=t.id),void 0!==t.label&&(this.label=t.label,this.originalLabel=t.label),void 0!==t.title&&(this.title=t.title),void 0!==t.x&&(this.x=t.x),void 0!==t.y&&(this.y=t.y),void 0!==t.value&&(this.value=t.value),void 0!==t.level&&(this.level=t.level,this.preassignedLevel=!0),void 0!==t.horizontalAlignLeft&&(this.horizontalAlignLeft=t.horizontalAlignLeft),void 0!==t.verticalAlignTop&&(this.verticalAlignTop=t.verticalAlignTop),void 0!==t.triggerFunction&&(this.triggerFunction=t.triggerFunction),void 0===this.id)throw"Node must have an id";if("number"==typeof this.options.group||"string"==typeof this.options.group&&""!=this.options.group){var s=this.grouplist.get(this.options.group);o.deepExtend(this.options,s),this.options.color=o.parseColor(this.options.color)}if(void 0!==t.radius&&(this.baseRadiusValue=this.options.radius),void 0!==t.color&&(this.options.color=o.parseColor(t.color)),void 0!==this.options.image&&""!=this.options.image){if(!this.imagelist)throw"No imagelist provided";this.imageObj=this.imagelist.load(this.options.image,this.options.brokenImage)}switch(void 0!==t.allowedToMoveX?(this.xFixed=!t.allowedToMoveX,this.allowedToMoveX=t.allowedToMoveX):void 0!==t.x&&0==this.allowedToMoveX&&(this.xFixed=!0),void 0!==t.allowedToMoveY?(this.yFixed=!t.allowedToMoveY,this.allowedToMoveY=t.allowedToMoveY):void 0!==t.y&&0==this.allowedToMoveY&&(this.yFixed=!0),this.radiusFixed=this.radiusFixed||void 0!==t.radius,("image"===this.options.shape||"circularImage"===this.options.shape)&&(this.options.radiusMin=e.nodes.widthMin,this.options.radiusMax=e.nodes.widthMax),this.options.shape){case"database":this.draw=this._drawDatabase,this.resize=this._resizeDatabase;break;case"box":this.draw=this._drawBox,this.resize=this._resizeBox;break;case"circle":this.draw=this._drawCircle,this.resize=this._resizeCircle;break;case"ellipse":this.draw=this._drawEllipse,this.resize=this._resizeEllipse;break;case"image":this.draw=this._drawImage,this.resize=this._resizeImage;break;case"circularImage":this.draw=this._drawCircularImage,this.resize=this._resizeCircularImage;break;case"text":this.draw=this._drawText,this.resize=this._resizeText;break;case"dot":this.draw=this._drawDot,this.resize=this._resizeShape;break;case"square":this.draw=this._drawSquare,this.resize=this._resizeShape;break;case"triangle":this.draw=this._drawTriangle,this.resize=this._resizeShape;break;case"triangleDown":this.draw=this._drawTriangleDown,this.resize=this._resizeShape;break;case"star":this.draw=this._drawStar,this.resize=this._resizeShape;break;default:this.draw=this._drawEllipse,this.resize=this._resizeEllipse}this._reset()}},s.prototype.select=function(){this.selected=!0,this._reset()},s.prototype.unselect=function(){this.selected=!1,this._reset()},s.prototype.clearSizeCache=function(){this._reset()},s.prototype._reset=function(){this.width=void 0,this.height=void 0},s.prototype.getTitle=function(){return"function"==typeof this.title?this.title():this.title},s.prototype.distanceToBorder=function(t,e){var i=1;switch(this.width||this.resize(t),this.options.shape){case"circle":case"dot":return this.options.radius+i;case"ellipse":var s=this.width/2,o=this.height/2,n=Math.sin(e)*s,r=Math.cos(e)*o;return s*o/Math.sqrt(n*n+r*r);case"box":case"image":case"text":default:return this.width?Math.min(Math.abs(this.width/2/Math.cos(e)),Math.abs(this.height/2/Math.sin(e)))+i:0}},s.prototype._setForce=function(t,e){this.fx=t,this.fy=e},s.prototype._addForce=function(t,e){this.fx+=t,this.fy+=e},s.prototype.storeState=function(){this.previousState.x=this.x,this.previousState.y=this.y,this.previousState.vx=this.vx,this.previousState.vy=this.vy},s.prototype.discreteStep=function(t){if(this.storeState(),this.xFixed)this.fx=0,this.vx=0;else{var e=this.damping*this.vx,i=(this.fx-e)/this.options.mass;this.vx+=i*t,this.x+=this.vx*t}if(this.yFixed)this.fy=0,this.vy=0;else{var s=this.damping*this.vy,o=(this.fy-s)/this.options.mass;this.vy+=o*t,this.y+=this.vy*t}},s.prototype.discreteStepLimited=function(t,e){if(this.storeState(),this.xFixed)this.fx=0,this.vx=0;else{var i=this.damping*this.vx,s=(this.fx-i)/this.options.mass;this.vx+=s*t,this.vx=Math.abs(this.vx)>e?this.vx>0?e:-e:this.vx,this.x+=this.vx*t}if(this.yFixed)this.fy=0,this.vy=0;else{var o=this.damping*this.vy,n=(this.fy-o)/this.options.mass;this.vy+=n*t,this.vy=Math.abs(this.vy)>e?this.vy>0?e:-e:this.vy,this.y+=this.vy*t}},s.prototype.isFixed=function(){return this.xFixed&&this.yFixed},s.prototype.isMoving=function(t){var e=Math.sqrt(Math.pow(this.vx,2)+Math.pow(this.vy,2));return e>t},s.prototype.isSelected=function(){return this.selected},s.prototype.getValue=function(){return this.value},s.prototype.getDistance=function(t,e){var i=this.x-t,s=this.y-e;return Math.sqrt(i*i+s*s)},s.prototype.setValueRange=function(t,e){if(!this.radiusFixed&&void 0!==this.value)if(e==t)this.options.radius=(this.options.radiusMin+this.options.radiusMax)/2;else{var i=(this.options.radiusMax-this.options.radiusMin)/(e-t);this.options.radius=(this.value-t)*i+this.options.radiusMin}this.baseRadiusValue=this.options.radius},s.prototype.draw=function(){throw"Draw method not initialized for node"},s.prototype.resize=function(){throw"Resize method not initialized for node"},s.prototype.isOverlappingWith=function(t){return this.leftt.left&&this.topt.top},s.prototype._resizeImage=function(){if(!this.width||!this.height){var t,e;if(this.value){this.options.radius=this.baseRadiusValue;var i=this.imageObj.height/this.imageObj.width;void 0!==i?(t=this.options.radius||this.imageObj.width,e=this.options.radius*i||this.imageObj.height):(t=0,e=0)}else t=this.imageObj.width,e=this.imageObj.height;this.width=t,this.height=e,this.growthIndicator=0,this.width>0&&this.height>0&&(this.width+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeWidthFactor,this.height+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeHeightFactor,this.options.radius+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeRadiusFactor,this.growthIndicator=this.width-t)}},s.prototype._drawImageAtPosition=function(t){if(0!=this.imageObj.width){if(this.clusterSize>1){var e=this.clusterSize>1?10:0;e*=this.networkScaleInv,e=Math.min(.2*this.width,e),t.globalAlpha=.5,t.drawImage(this.imageObj,this.left-e,this.top-e,this.width+2*e,this.height+2*e)}t.globalAlpha=1,t.drawImage(this.imageObj,this.left,this.top,this.width,this.height)}},s.prototype._drawImageLabel=function(t){var e,i=0;if(this.height){i=this.height/2;var s=this.getTextSize(t);s.lineCount>=1&&(i+=s.height/2,i+=3)}e=this.y+i,this._label(t,this.label,this.x,e,void 0)},s.prototype._drawImage=function(t){this._resizeImage(t),this.left=this.x-this.width/2,this.top=this.y-this.height/2,this._drawImageAtPosition(t),this.boundingBox.top=this.top,this.boundingBox.left=this.left,this.boundingBox.right=this.left+this.width,this.boundingBox.bottom=this.top+this.height,this._drawImageLabel(t),this.boundingBox.left=Math.min(this.boundingBox.left,this.labelDimensions.left),this.boundingBox.right=Math.max(this.boundingBox.right,this.labelDimensions.left+this.labelDimensions.width),this.boundingBox.bottom=Math.max(this.boundingBox.bottom,this.boundingBox.bottom+this.labelDimensions.height)},s.prototype._resizeCircularImage=function(t){if(this.imageObj.src&&this.imageObj.width&&this.imageObj.height)this._swapToImageResizeWhenImageLoaded&&(this.width=0,this.height=0,delete this._swapToImageResizeWhenImageLoaded),this._resizeImage(t);else if(!this.width){var e=2*this.options.radius;this.width=e,this.height=e,this.options.radius+=.5*Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeRadiusFactor,this.growthIndicator=this.options.radius-.5*e,this._swapToImageResizeWhenImageLoaded=!0}},s.prototype._drawCircularImage=function(t){this._resizeCircularImage(t),this.left=this.x-this.width/2,this.top=this.y-this.height/2;var e=this.left+this.width/2,i=this.top+this.height/2,s=Math.abs(this.height/2);this._drawRawCircle(t,e,i,s),t.save(),t.circle(this.x,this.y,s),t.stroke(),t.clip(),this._drawImageAtPosition(t),t.restore(),this.boundingBox.top=this.y-this.options.radius,this.boundingBox.left=this.x-this.options.radius,this.boundingBox.right=this.x+this.options.radius,this.boundingBox.bottom=this.y+this.options.radius,this._drawImageLabel(t),this.boundingBox.left=Math.min(this.boundingBox.left,this.labelDimensions.left),this.boundingBox.right=Math.max(this.boundingBox.right,this.labelDimensions.left+this.labelDimensions.width),this.boundingBox.bottom=Math.max(this.boundingBox.bottom,this.boundingBox.bottom+this.labelDimensions.height)},s.prototype._resizeBox=function(t){if(!this.width){var e=5,i=this.getTextSize(t);this.width=i.width+2*e,this.height=i.height+2*e,this.width+=.5*Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeWidthFactor,this.height+=.5*Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeHeightFactor,this.growthIndicator=this.width-(i.width+2*e)}},s.prototype._drawBox=function(t){this._resizeBox(t),this.left=this.x-this.width/2,this.top=this.y-this.height/2;var e=2.5,i=this.options.borderWidth,s=this.options.borderWidthSelected||2*this.options.borderWidth;t.strokeStyle=this.selected?this.options.color.highlight.border:this.hover?this.options.color.hover.border:this.options.color.border,this.clusterSize>1&&(t.lineWidth=(this.selected?s:i)+(this.clusterSize>1?e:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.roundRect(this.left-2*t.lineWidth,this.top-2*t.lineWidth,this.width+4*t.lineWidth,this.height+4*t.lineWidth,this.options.radius),t.stroke()),t.lineWidth=(this.selected?s:i)+(this.clusterSize>1?e:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.fillStyle=this.selected?this.options.color.highlight.background:this.hover?this.options.color.hover.background:this.options.color.background,t.roundRect(this.left,this.top,this.width,this.height,this.options.radius),t.fill(),t.stroke(),this.boundingBox.top=this.top,this.boundingBox.left=this.left,this.boundingBox.right=this.left+this.width,this.boundingBox.bottom=this.top+this.height,this._label(t,this.label,this.x,this.y)},s.prototype._resizeDatabase=function(t){if(!this.width){var e=5,i=this.getTextSize(t),s=i.width+2*e;this.width=s,this.height=s,this.width+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeWidthFactor,this.height+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeHeightFactor,this.options.radius+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeRadiusFactor,this.growthIndicator=this.width-s}},s.prototype._drawDatabase=function(t){this._resizeDatabase(t),this.left=this.x-this.width/2,this.top=this.y-this.height/2;var e=2.5,i=this.options.borderWidth,s=this.options.borderWidthSelected||2*this.options.borderWidth;t.strokeStyle=this.selected?this.options.color.highlight.border:this.hover?this.options.color.hover.border:this.options.color.border,this.clusterSize>1&&(t.lineWidth=(this.selected?s:i)+(this.clusterSize>1?e:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.database(this.x-this.width/2-2*t.lineWidth,this.y-.5*this.height-2*t.lineWidth,this.width+4*t.lineWidth,this.height+4*t.lineWidth),t.stroke()),t.lineWidth=(this.selected?s:i)+(this.clusterSize>1?e:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.fillStyle=this.selected?this.options.color.highlight.background:this.hover?this.options.color.hover.background:this.options.color.background,t.database(this.x-this.width/2,this.y-.5*this.height,this.width,this.height),t.fill(),t.stroke(),this.boundingBox.top=this.top,this.boundingBox.left=this.left,this.boundingBox.right=this.left+this.width,this.boundingBox.bottom=this.top+this.height,this._label(t,this.label,this.x,this.y) +},s.prototype._resizeCircle=function(t){if(!this.width){var e=5,i=this.getTextSize(t),s=Math.max(i.width,i.height)+2*e;this.options.radius=s/2,this.width=s,this.height=s,this.options.radius+=.5*Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeRadiusFactor,this.growthIndicator=this.options.radius-.5*s}},s.prototype._drawRawCircle=function(t,e,i,s){var o=2.5,n=this.options.borderWidth,r=this.options.borderWidthSelected||2*this.options.borderWidth;t.strokeStyle=this.selected?this.options.color.highlight.border:this.hover?this.options.color.hover.border:this.options.color.border,this.clusterSize>1&&(t.lineWidth=(this.selected?r:n)+(this.clusterSize>1?o:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.circle(e,i,s+2*t.lineWidth),t.stroke()),t.lineWidth=(this.selected?r:n)+(this.clusterSize>1?o:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.fillStyle=this.selected?this.options.color.highlight.background:this.hover?this.options.color.hover.background:this.options.color.background,t.circle(this.x,this.y,s),t.fill(),t.stroke()},s.prototype._drawCircle=function(t){this._resizeCircle(t),this.left=this.x-this.width/2,this.top=this.y-this.height/2,this._drawRawCircle(t,this.x,this.y,this.options.radius),this.boundingBox.top=this.y-this.options.radius,this.boundingBox.left=this.x-this.options.radius,this.boundingBox.right=this.x+this.options.radius,this.boundingBox.bottom=this.y+this.options.radius,this._label(t,this.label,this.x,this.y)},s.prototype._resizeEllipse=function(t){if(!this.width){var e=this.getTextSize(t);this.width=1.5*e.width,this.height=2*e.height,this.width1&&(t.lineWidth=(this.selected?s:i)+(this.clusterSize>1?e:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.ellipse(this.left-2*t.lineWidth,this.top-2*t.lineWidth,this.width+4*t.lineWidth,this.height+4*t.lineWidth),t.stroke()),t.lineWidth=(this.selected?s:i)+(this.clusterSize>1?e:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.fillStyle=this.selected?this.options.color.highlight.background:this.hover?this.options.color.hover.background:this.options.color.background,t.ellipse(this.left,this.top,this.width,this.height),t.fill(),t.stroke(),this.boundingBox.top=this.top,this.boundingBox.left=this.left,this.boundingBox.right=this.left+this.width,this.boundingBox.bottom=this.top+this.height,this._label(t,this.label,this.x,this.y)},s.prototype._drawDot=function(t){this._drawShape(t,"circle")},s.prototype._drawTriangle=function(t){this._drawShape(t,"triangle")},s.prototype._drawTriangleDown=function(t){this._drawShape(t,"triangleDown")},s.prototype._drawSquare=function(t){this._drawShape(t,"square")},s.prototype._drawStar=function(t){this._drawShape(t,"star")},s.prototype._resizeShape=function(){if(!this.width){this.options.radius=this.baseRadiusValue;var t=2*this.options.radius;this.width=t,this.height=t,this.width+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeWidthFactor,this.height+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeHeightFactor,this.options.radius+=.5*Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeRadiusFactor,this.growthIndicator=this.width-t}},s.prototype._drawShape=function(t,e){this._resizeShape(t),this.left=this.x-this.width/2,this.top=this.y-this.height/2;var i=2.5,s=this.options.borderWidth,o=this.options.borderWidthSelected||2*this.options.borderWidth,n=2;switch(e){case"dot":n=2;break;case"square":n=2;break;case"triangle":n=3;break;case"triangleDown":n=3;break;case"star":n=4}t.strokeStyle=this.selected?this.options.color.highlight.border:this.hover?this.options.color.hover.border:this.options.color.border,this.clusterSize>1&&(t.lineWidth=(this.selected?o:s)+(this.clusterSize>1?i:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t[e](this.x,this.y,this.options.radius+n*t.lineWidth),t.stroke()),t.lineWidth=(this.selected?o:s)+(this.clusterSize>1?i:0),t.lineWidth*=this.networkScaleInv,t.lineWidth=Math.min(this.width,t.lineWidth),t.fillStyle=this.selected?this.options.color.highlight.background:this.hover?this.options.color.hover.background:this.options.color.background,t[e](this.x,this.y,this.options.radius),t.fill(),t.stroke(),this.boundingBox.top=this.y-this.options.radius,this.boundingBox.left=this.x-this.options.radius,this.boundingBox.right=this.x+this.options.radius,this.boundingBox.bottom=this.y+this.options.radius,this.label&&(this._label(t,this.label,this.x,this.y+this.height/2,void 0,"hanging",!0),this.boundingBox.left=Math.min(this.boundingBox.left,this.labelDimensions.left),this.boundingBox.right=Math.max(this.boundingBox.right,this.labelDimensions.left+this.labelDimensions.width),this.boundingBox.bottom=Math.max(this.boundingBox.bottom,this.boundingBox.bottom+this.labelDimensions.height))},s.prototype._resizeText=function(t){if(!this.width){var e=5,i=this.getTextSize(t);this.width=i.width+2*e,this.height=i.height+2*e,this.width+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeWidthFactor,this.height+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeHeightFactor,this.options.radius+=Math.min(this.clusterSize-1,this.maxNodeSizeIncrements)*this.clusterSizeRadiusFactor,this.growthIndicator=this.width-(i.width+2*e)}},s.prototype._drawText=function(t){this._resizeText(t),this.left=this.x-this.width/2,this.top=this.y-this.height/2,this._label(t,this.label,this.x,this.y),this.boundingBox.top=this.top,this.boundingBox.left=this.left,this.boundingBox.right=this.left+this.width,this.boundingBox.bottom=this.top+this.height},s.prototype._label=function(t,e,i,s,o,n,r){if(e&&Number(this.options.fontSize)*this.networkScale>this.fontDrawThreshold){t.font=(this.selected?"bold ":"")+this.options.fontSize+"px "+this.options.fontFace;var a=e.split("\n"),h=a.length,d=Number(this.options.fontSize),l=s+(1-h)/2*d;1==r&&(l=s+(1-h)/(2*d));for(var c=t.measureText(a[0]).width,p=1;h>p;p++){var u=t.measureText(a[p]).width;c=u>c?u:c}var m=this.options.fontSize*h,f=i-c/2,g=s-m/2;"hanging"==n&&(g+=.5*d,g+=4,l+=4),this.labelDimensions={top:g,left:f,width:c,height:m,yLine:l},void 0!==this.options.fontFill&&null!==this.options.fontFill&&"none"!==this.options.fontFill&&(t.fillStyle=this.options.fontFill,t.fillRect(f,g,c,m)),t.fillStyle=this.options.fontColor||"black",t.textAlign=o||"center",t.textBaseline=n||"middle",this.options.fontStrokeWidth>0&&(t.lineWidth=this.options.fontStrokeWidth,t.strokeStyle=this.options.fontStrokeColor,t.lineJoin="round");for(var p=0;h>p;p++)this.options.fontStrokeWidth&&t.strokeText(a[p],i,l),t.fillText(a[p],i,l),l+=d}},s.prototype.getTextSize=function(t){if(void 0!==this.label){t.font=(this.selected?"bold ":"")+this.options.fontSize+"px "+this.options.fontFace;for(var e=this.label.split("\n"),i=(Number(this.options.fontSize)+4)*e.length,s=0,o=0,n=e.length;n>o;o++)s=Math.max(s,t.measureText(e[o]).width);return{width:s,height:i,lineCount:e.length}}return{width:0,height:0,lineCount:0}},s.prototype.inArea=function(){return void 0!==this.width?this.x+this.width*this.networkScaleInv>=this.canvasTopLeft.x&&this.x-this.width*this.networkScaleInv=this.canvasTopLeft.y&&this.y-this.height*this.networkScaleInv=this.canvasTopLeft.x&&this.x=this.canvasTopLeft.y&&this.ys&&(n=s-e-this.padding),no&&(r=o-i-this.padding),ri;i++)if(e.id===r.nodes[i].id){o=r.nodes[i];break}for(o||(o={id:e.id},t.node&&(o.attr=a(o.attr,t.node))),i=n.length-1;i>=0;i--){var h=n[i];h.nodes||(h.nodes=[]),-1==h.nodes.indexOf(o)&&h.nodes.push(o)}e.attr&&(o.attr=a(o.attr,e.attr))}function l(t,e){if(t.edges||(t.edges=[]),t.edges.push(e),t.edge){var i=a({},t.edge);e.attr=a(i,e.attr)}}function c(t,e,i,s,o){var n={from:e,to:i,type:s};return t.edge&&(n.attr=a({},t.edge)),n.attr=a(n.attr||{},o),n}function p(){for(N=D.NULL,k="";" "==E||" "==E||"\n"==E||"\r"==E;)o();do{var t=!1;if("#"==E){for(var e=O-1;" "==T.charAt(e)||" "==T.charAt(e);)e--;if("\n"==T.charAt(e)||""==T.charAt(e)){for(;""!=E&&"\n"!=E;)o();t=!0}}if("/"==E&&"/"==n()){for(;""!=E&&"\n"!=E;)o();t=!0}if("/"==E&&"*"==n()){for(;""!=E;){if("*"==E&&"/"==n()){o(),o();break}o()}t=!0}for(;" "==E||" "==E||"\n"==E||"\r"==E;)o()}while(t);if(""==E)return void(N=D.DELIMITER);var i=E+n();if(C[i])return N=D.DELIMITER,k=i,o(),void o();if(C[E])return N=D.DELIMITER,k=E,void o();if(r(E)||"-"==E){for(k+=E,o();r(E);)k+=E,o();return"false"==k?k=!1:"true"==k?k=!0:isNaN(Number(k))||(k=Number(k)),void(N=D.IDENTIFIER)}if('"'==E){for(o();""!=E&&('"'!=E||'"'==E&&'"'==n());)k+=E,'"'==E&&o(),o();if('"'!=E)throw x('End of string " expected');return o(),void(N=D.IDENTIFIER)}for(N=D.UNKNOWN;""!=E;)k+=E,o();throw new SyntaxError('Syntax error in part "'+w(k,30)+'"')}function u(){var t={};if(s(),p(),"strict"==k&&(t.strict=!0,p()),("graph"==k||"digraph"==k)&&(t.type=k,p()),N==D.IDENTIFIER&&(t.id=k,p()),"{"!=k)throw x("Angle bracket { expected");if(p(),m(t),"}"!=k)throw x("Angle bracket } expected");if(p(),""!==k)throw x("End of file expected");return p(),delete t.node,delete t.edge,delete t.graph,t}function m(t){for(;""!==k&&"}"!=k;)f(t),";"==k&&p()}function f(t){var e=g(t);if(e)return void b(t,e);var i=v(t);if(!i){if(N!=D.IDENTIFIER)throw x("Identifier expected");var s=k;if(p(),"="==k){if(p(),N!=D.IDENTIFIER)throw x("Identifier expected");t[s]=k,p()}else y(t,s)}}function g(t){var e=null;if("subgraph"==k&&(e={},e.type="subgraph",p(),N==D.IDENTIFIER&&(e.id=k,p())),"{"==k){if(p(),e||(e={}),e.parent=t,e.node=t.node,e.edge=t.edge,e.graph=t.graph,m(e),"}"!=k)throw x("Angle bracket } expected");p(),delete e.node,delete e.edge,delete e.graph,delete e.parent,t.subgraphs||(t.subgraphs=[]),t.subgraphs.push(e)}return e}function v(t){return"node"==k?(p(),t.node=_(),"node"):"edge"==k?(p(),t.edge=_(),"edge"):"graph"==k?(p(),t.graph=_(),"graph"):null}function y(t,e){var i={id:e},s=_();s&&(i.attr=s),d(t,i),b(t,e)}function b(t,e){for(;"->"==k||"--"==k;){var i,s=k;p();var o=g(t);if(o)i=o;else{if(N!=D.IDENTIFIER)throw x("Identifier or subgraph expected");i=k,d(t,{id:i}),p()}var n=_(),r=c(t,e,i,s,n);l(t,r),e=i}}function _(){for(var t=null;"["==k;){for(p(),t={};""!==k&&"]"!=k;){if(N!=D.IDENTIFIER)throw x("Attribute name expected");var e=k;if(p(),"="!=k)throw x("Equal sign = expected");if(p(),N!=D.IDENTIFIER)throw x("Attribute value expected");var i=k;h(t,e,i),p(),","==k&&p()}if("]"!=k)throw x("Bracket ] expected");p()}return t}function x(t){return new SyntaxError(t+', got "'+w(k,30)+'" (char '+O+")")}function w(t,e){return t.length<=e?t:t.substr(0,27)+"..."}function 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D={NULL:0,DELIMITER:1,IDENTIFIER:2,UNKNOWN:3},C={"{":!0,"}":!0,"[":!0,"]":!0,";":!0,"=":!0,",":!0,"->":!0,"--":!0},T="",O=0,E="",k="",N=D.NULL,I=/[a-zA-Z_0-9.:#]/;e.parseDOT=i,e.DOTToGraph=M},function(t,e){function i(t,e){var i=[],s=[];this.options={edges:{inheritColor:!0},nodes:{allowedToMove:!1,parseColor:!1}},void 0!==e&&(this.options.nodes.allowedToMove=e.allowedToMove|!1,this.options.nodes.parseColor=e.parseColor|!1,this.options.edges.inheritColor=e.inheritColor|!0);for(var o=t.edges,n=t.nodes,r=0;r=s&&(s=864e5),e=new Date(e.valueOf()-.05*s),i=new Date(i.valueOf()+.05*s)}return{start:e,end:i}},s.prototype.setWindow=function(t,e,i){var s=i&&void 0!==i.animate?i.animate:!0;if(1==arguments.length){var o=arguments[0];this.range.setRange(o.start,o.end,s)}else this.range.setRange(t,e,s)},s.prototype.moveTo=function(t,e){var i=this.range.end-this.range.start,s=r.convert(t,"Date").valueOf(),o=s-i/2,n=s+i/2,a=e&&void 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o=s.root.offsetHeight-s.root.clientHeight,n=s.root.offsetWidth-s.root.clientWidth;0===s.centerContainer.clientHeight&&(i.border.left=i.border.top,i.border.right=i.border.left),0===s.root.clientHeight&&(n=o),i.center.height=s.center.offsetHeight,i.left.height=s.left.offsetHeight,i.right.height=s.right.offsetHeight,i.top.height=s.top.clientHeight||-i.border.top,i.bottom.height=s.bottom.clientHeight||-i.border.bottom;var a=Math.max(i.left.height,i.center.height,i.right.height),d=i.top.height+a+i.bottom.height+o+i.border.top+i.border.bottom;s.root.style.height=r.option.asSize(e.height,d+"px"),i.root.height=s.root.offsetHeight,i.background.height=i.root.height-o;var l=i.root.height-i.top.height-i.bottom.height-o;i.centerContainer.height=l,i.leftContainer.height=l,i.rightContainer.height=i.leftContainer.height,i.root.width=s.root.offsetWidth,i.background.width=i.root.width-n,i.left.width=s.leftContainer.clientWidth||-i.border.left,i.leftContainer.width=i.left.width,i.right.width=s.rightContainer.clientWidth||-i.border.right,i.rightContainer.width=i.right.width;var c=i.root.width-i.left.width-i.right.width-n;i.center.width=c,i.centerContainer.width=c,i.top.width=c,i.bottom.width=c,s.background.style.height=i.background.height+"px",s.backgroundVertical.style.height=i.background.height+"px",s.backgroundHorizontal.style.height=i.centerContainer.height+"px",s.centerContainer.style.height=i.centerContainer.height+"px",s.leftContainer.style.height=i.leftContainer.height+"px",s.rightContainer.style.height=i.rightContainer.height+"px",s.background.style.width=i.background.width+"px",s.backgroundVertical.style.width=i.centerContainer.width+"px",s.backgroundHorizontal.style.width=i.background.width+"px",s.centerContainer.style.width=i.center.width+"px",s.top.style.width=i.top.width+"px",s.bottom.style.width=i.bottom.width+"px",s.background.style.left="0",s.background.style.top="0",s.backgroundVertical.style.left=i.left.width+i.border.left+"px",s.backgroundVertical.style.top="0",s.backgroundHorizontal.style.left="0",s.backgroundHorizontal.style.top=i.top.height+"px",s.centerContainer.style.left=i.left.width+"px",s.centerContainer.style.top=i.top.height+"px",s.leftContainer.style.left="0",s.leftContainer.style.top=i.top.height+"px",s.rightContainer.style.left=i.left.width+i.center.width+"px",s.rightContainer.style.top=i.top.height+"px",s.top.style.left=i.left.width+"px",s.top.style.top="0",s.bottom.style.left=i.left.width+"px",s.bottom.style.top=i.top.height+i.centerContainer.height+"px",this._updateScrollTop();var p=this.props.scrollTop;"bottom"==e.orientation&&(p+=Math.max(this.props.centerContainer.height-this.props.center.height-this.props.border.top-this.props.border.bottom,0)),s.center.style.left="0",s.center.style.top=p+"px",s.left.style.left="0",s.left.style.top=p+"px",s.right.style.left="0",s.right.style.top=p+"px";var u=0==this.props.scrollTop?"hidden":"",m=this.props.scrollTop==this.props.scrollTopMin?"hidden":"";if(s.shadowTop.style.visibility=u,s.shadowBottom.style.visibility=m,s.shadowTopLeft.style.visibility=u,s.shadowBottomLeft.style.visibility=m,s.shadowTopRight.style.visibility=u,s.shadowBottomRight.style.visibility=m,this.components.forEach(function(e){t=e.redraw()||t}),t){var f=3;this.redrawCount0&&(this.props.scrollTop=0),this.props.scrollTops;s++){var o=s%2===0?1.3*i:.5*i;this.lineTo(t+o*Math.sin(2*s*Math.PI/10),e-o*Math.cos(2*s*Math.PI/10))}this.closePath()},CanvasRenderingContext2D.prototype.roundRect=function(t,e,i,s,o){var n=Math.PI/180;0>i-2*o&&(o=i/2),0>s-2*o&&(o=s/2),this.beginPath(),this.moveTo(t+o,e),this.lineTo(t+i-o,e),this.arc(t+i-o,e+o,o,270*n,360*n,!1),this.lineTo(t+i,e+s-o),this.arc(t+i-o,e+s-o,o,0,90*n,!1),this.lineTo(t+o,e+s),this.arc(t+o,e+s-o,o,90*n,180*n,!1),this.lineTo(t,e+o),this.arc(t+o,e+o,o,180*n,270*n,!1)},CanvasRenderingContext2D.prototype.ellipse=function(t,e,i,s){var o=.5522848,n=i/2*o,r=s/2*o,a=t+i,h=e+s,d=t+i/2,l=e+s/2; +this.beginPath(),this.moveTo(t,l),this.bezierCurveTo(t,l-r,d-n,e,d,e),this.bezierCurveTo(d+n,e,a,l-r,a,l),this.bezierCurveTo(a,l+r,d+n,h,d,h),this.bezierCurveTo(d-n,h,t,l+r,t,l)},CanvasRenderingContext2D.prototype.database=function(t,e,i,s){var o=1/3,n=i,r=s*o,a=.5522848,h=n/2*a,d=r/2*a,l=t+n,c=e+r,p=t+n/2,u=e+r/2,m=e+(s-r/2),f=e+s;this.beginPath(),this.moveTo(l,u),this.bezierCurveTo(l,u+d,p+h,c,p,c),this.bezierCurveTo(p-h,c,t,u+d,t,u),this.bezierCurveTo(t,u-d,p-h,e,p,e),this.bezierCurveTo(p+h,e,l,u-d,l,u),this.lineTo(l,m),this.bezierCurveTo(l,m+d,p+h,f,p,f),this.bezierCurveTo(p-h,f,t,m+d,t,m),this.lineTo(t,u)},CanvasRenderingContext2D.prototype.arrow=function(t,e,i,s){var o=t-s*Math.cos(i),n=e-s*Math.sin(i),r=t-.9*s*Math.cos(i),a=e-.9*s*Math.sin(i),h=o+s/3*Math.cos(i+.5*Math.PI),d=n+s/3*Math.sin(i+.5*Math.PI),l=o+s/3*Math.cos(i-.5*Math.PI),c=n+s/3*Math.sin(i-.5*Math.PI);this.beginPath(),this.moveTo(t,e),this.lineTo(h,d),this.lineTo(r,a),this.lineTo(l,c),this.closePath()},CanvasRenderingContext2D.prototype.dashedLine=function(t,e,i,s,o){o||(o=[10,5]),0==p&&(p=.001);var n=o.length;this.moveTo(t,e);for(var r=i-t,a=s-e,h=a/r,d=Math.sqrt(r*r+a*a),l=0,c=!0;d>=.1;){var p=o[l++%n];p>d&&(p=d);var u=Math.sqrt(p*p/(1+h*h));0>r&&(u=-u),t+=u,e+=h*u,this[c?"lineTo":"moveTo"](t,e),d-=p,c=!c}})},function(t,e,i){function s(t,e){this.groupId=t,this.options=e}var o=i(2),n=i(53);s.prototype.getYRange=function(t){for(var e=t[0].y,i=t[0].y,s=0;st[s].y?t[s].y:e,i=i0){var r,a,h=Number(i.svg.style.height.replace("px",""));if(r=o.getSVGElement("path",i.svgElements,i.svg),r.setAttributeNS(null,"class",e.className),void 0!==e.style&&r.setAttributeNS(null,"style",e.style),a=1==e.options.catmullRom.enabled?s._catmullRom(t,e):s._linear(t),1==e.options.shaded.enabled){var d,l=o.getSVGElement("path",i.svgElements,i.svg);d="top"==e.options.shaded.orientation?"M"+t[0].x+",0 "+a+"L"+t[t.length-1].x+",0":"M"+t[0].x+","+h+" "+a+"L"+t[t.length-1].x+","+h,l.setAttributeNS(null,"class",e.className+" fill"),void 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g=d+(p[r].amount-p[r].resolved),v=d-(p[r].resolved+1);g0&&(n=Math.min(n,Math.abs(c[v].x-r))),a=s._getSafeDrawData(n,h,m),p[r].resolved+=1,"stack"==h.options.barChart.handleOverlap?(f=p[r].accumulated,p[r].accumulated+=h.zeroPosition-c[d].y):"sideBySide"==h.options.barChart.handleOverlap&&(a.width=a.width/p[r].amount,a.offset+=p[r].resolved*a.width-.5*a.width*(p[r].amount+1),"left"==h.options.barChart.align?a.offset-=.5*a.width:"right"==h.options.barChart.align&&(a.offset+=.5*a.width))}o.drawBar(c[d].x+a.offset,c[d].y-f,a.width,h.zeroPosition-c[d].y,h.className+" bar",i.svgElements,i.svg),1==h.options.drawPoints.enabled&&o.drawPoint(c[d].x+a.offset,c[d].y,h,i.svgElements,i.svg)}},s._getDataIntersections=function(t,e){for(var i,s=0;s0&&(i=Math.min(i,Math.abs(e[s-1].x-e[s].x))),0==i&&(void 0===t[e[s].x]&&(t[e[s].x]={amount:0,resolved:0,accumulated:0}),t[e[s].x].amount+=1)},s._getSafeDrawData=function(t,e,i){var s,o;return t0?(s=i>t?i:t,o=0,"left"==e.options.barChart.align?o-=.5*t:"right"==e.options.barChart.align&&(o+=.5*t)):(s=e.options.barChart.width,o=0,"left"==e.options.barChart.align?o-=.5*e.options.barChart.width:"right"==e.options.barChart.align&&(o+=.5*e.options.barChart.width)),{width:s,offset:o}},s.getStackedBarYRange=function(t,e,i,o,n){if(t.length>0){t.sort(function(t,e){return t.x==e.x?t.groupId-e.groupId:t.x-e.x});var r={};s._getDataIntersections(r,t),e[o]=s._getStackedBarYRange(r,t),e[o].yAxisOrientation=n,i.push(o)}},s._getStackedBarYRange=function(t,e){for(var i,s=e[0].y,o=e[0].y,n=0;ne[n].y?e[n].y:s,o=ot[r].accumulated?t[r].accumulated:s,o=ot[s].y?t[s].y:e,i=is;++s)i[s].apply(this,e)}return this},e.prototype.listeners=function(t){return this._callbacks=this._callbacks||{},this._callbacks[t]||[]},e.prototype.hasListeners=function(t){return!!this.listeners(t).length}},function(t,e,i){var s;(function(t,o){(function(n){function r(t,e,i){switch(arguments.length){case 2:return 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e=t.srcEvent,i=t.offsetDirection;if(this.manager.session.prevented)return void e.preventDefault();var s=this.actions,o=_(s,ni),n=_(s,ai),r=_(s,ri);return o||n&&i&Re||r&&i&Fe?this.preventSrc(e):void 0}},preventSrc:function(t){this.manager.session.prevented=!0,t.preventDefault()}};var hi=1,di=2,li=4,ci=8,pi=ci,ui=16,mi=32;K.prototype={defaults:{},set:function(t){return c(this.options,t),this.manager&&this.manager.touchAction.update(),this},recognizeWith:function(t){if(d(t,"recognizeWith",this))return this;var e=this.simultaneous;return t=te(t,this),e[t.id]||(e[t.id]=t,t.recognizeWith(this)),this},dropRecognizeWith:function(t){return d(t,"dropRecognizeWith",this)?this:(t=te(t,this),delete this.simultaneous[t.id],this)},requireFailure:function(t){if(d(t,"requireFailure",this))return this;var e=this.requireFail;return t=te(t,this),-1===w(e,t)&&(e.push(t),t.requireFailure(this)),this},dropRequireFailure:function(t){if(d(t,"dropRequireFailure",this))return this;t=te(t,this);var e=w(this.requireFail,t);return e>-1&&this.requireFail.splice(e,1),this},hasRequireFailures:function(){return this.requireFail.length>0},canRecognizeWith:function(t){return!!this.simultaneous[t.id]},emit:function(t){function e(e){i.manager.emit(i.options.event+(e?$(s):""),t)}var i=this,s=this.state;ci>s&&e(!0),e(),s>=ci&&e(!0)},tryEmit:function(t){return this.canEmit()?this.emit(t):void(this.state=mi)},canEmit:function(){for(var t=0;tn?Le:ze,i=n!=this.pX,s=Math.abs(t.deltaX)):(o=0===r?Ie:0>r?Pe:Ae,i=r!=this.pY,s=Math.abs(t.deltaY))),t.direction=o,i&&s>e.threshold&&o&e.direction},attrTest:function(t){return ee.prototype.attrTest.call(this,t)&&(this.state&di||!(this.state&di)&&this.directionTest(t))},emit:function(t){this.pX=t.deltaX,this.pY=t.deltaY;var e=J(t.direction);e&&this.manager.emit(this.options.event+e,t),this._super.emit.call(this,t)}}),u(se,ee,{defaults:{event:"pinch",threshold:0,pointers:2},getTouchAction:function(){return[ni]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.scale-1)>this.options.threshold||this.state&di)},emit:function(t){if(this._super.emit.call(this,t),1!==t.scale){var e=t.scale<1?"in":"out";this.manager.emit(this.options.event+e,t)}}}),u(oe,K,{defaults:{event:"press",pointers:1,time:500,threshold:5},getTouchAction:function(){return[si]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,s=t.distancee.time;if(this._input=t,!s||!i||t.eventType&(ke|Ne)&&!o)this.reset();else if(t.eventType&Oe)this.reset(),this._timer=h(function(){this.state=pi,this.tryEmit() +},e.time,this);else if(t.eventType&ke)return pi;return mi},reset:function(){clearTimeout(this._timer)},emit:function(t){this.state===pi&&(t&&t.eventType&ke?this.manager.emit(this.options.event+"up",t):(this._input.timeStamp=ve(),this.manager.emit(this.options.event,this._input)))}}),u(ne,ee,{defaults:{event:"rotate",threshold:0,pointers:2},getTouchAction:function(){return[ni]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.rotation)>this.options.threshold||this.state&di)}}),u(re,ee,{defaults:{event:"swipe",threshold:10,velocity:.65,direction:Re|Fe,pointers:1},getTouchAction:function(){return ie.prototype.getTouchAction.call(this)},attrTest:function(t){var e,i=this.options.direction;return i&(Re|Fe)?e=t.velocity:i&Re?e=t.velocityX:i&Fe&&(e=t.velocityY),this._super.attrTest.call(this,t)&&i&t.direction&&t.distance>this.options.threshold&&ge(e)>this.options.velocity&&t.eventType&ke},emit:function(t){var e=J(t.direction);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),u(ae,K,{defaults:{event:"tap",pointers:1,taps:1,interval:300,time:250,threshold:2,posThreshold:10},getTouchAction:function(){return[oi]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,s=t.distancet&&s>o;)o%3==0?(this.forceAggregateHubs(!0),this.normalizeClusterLevels()):this.increaseClusterLevel(),i=this.nodeIndices.length,o+=1;o>0&&1==e&&this.repositionNodes(),this._updateCalculationNodes()},e.openCluster=function(t){var e=this.moving;if(t.clusterSize>this.constants.clustering.sectorThreshold&&this._nodeInActiveArea(t)&&("default"!=this._sector()||1!=this.nodeIndices.length)){this._addSector(t);for(var i=0;this.nodeIndices.lengthi;)this.decreaseClusterLevel(),i+=1}else this._expandClusterNode(t,!1,!0),this._updateNodeIndexList(),this._updateDynamicEdges(),this._updateCalculationNodes(),this.updateLabels();this.moving!=e&&this.start()},e.updateClustersDefault=function(){1==this.constants.clustering.enabled&&this.updateClusters(0,!1,!1)},e.increaseClusterLevel=function(){this.updateClusters(-1,!1,!0)},e.decreaseClusterLevel=function(){this.updateClusters(1,!1,!0)},e.updateClusters=function(t,e,i,s){var o=this.moving,n=this.nodeIndices.length;this.previousScale>this.scale&&0==t&&this._collapseSector(),this.previousScale>this.scale||-1==t?this._formClusters(i):(this.previousScalethis.scale||-1==t)&&(this._aggregateHubs(i),this._updateNodeIndexList()),(this.previousScale>this.scale||-1==t)&&(this.handleChains(),this._updateNodeIndexList()),this.previousScale=this.scale,this._updateDynamicEdges(),this.updateLabels(),this.nodeIndices.lengththis.constants.clustering.chainThreshold&&this._reduceAmountOfChains(1-this.constants.clustering.chainThreshold/t)},e._aggregateHubs=function(t){this._getHubSize(),this._formClustersByHub(t,!1)},e.forceAggregateHubs=function(t){var e=this.moving,i=this.nodeIndices.length;this._aggregateHubs(!0),this._updateNodeIndexList(),this._updateDynamicEdges(),this.updateLabels(),this.nodeIndices.length!=i&&(this.clusterSession+=1),(0==t||void 0===t)&&this.moving!=e&&this.start()},e._openClustersBySize=function(){for(var t in this.nodes)if(this.nodes.hasOwnProperty(t)){var e=this.nodes[t];1==e.inView()&&(e.width*this.scale>this.constants.clustering.screenSizeThreshold*this.frame.canvas.clientWidth||e.height*this.scale>this.constants.clustering.screenSizeThreshold*this.frame.canvas.clientHeight)&&this.openCluster(e)}},e._openClusters=function(t,e){for(var i=0;i1&&(t.clusterSizei)){var r=n.from,a=n.to;n.to.options.mass>n.from.options.mass&&(r=n.to,a=n.from),1==a.dynamicEdgesLength?this._addToCluster(r,a,!1):1==r.dynamicEdgesLength&&this._addToCluster(a,r,!1)}}},e._forceClustersByZoom=function(){for(var t in this.nodes)if(this.nodes.hasOwnProperty(t)){var e=this.nodes[t];if(1==e.dynamicEdgesLength&&0!=e.dynamicEdges.length){var i=e.dynamicEdges[0],s=i.toId==e.id?this.nodes[i.fromId]:this.nodes[i.toId];e.id!=s.id&&(s.options.mass>e.options.mass?this._addToCluster(s,e,!0):this._addToCluster(e,s,!0))}}},e._clusterToSmallestNeighbour=function(t){for(var e=-1,i=null,s=0;so.clusterSessions.length&&(e=o.clusterSessions.length,i=o)}null!=o&&void 0!==this.nodes[o.id]&&this._addToCluster(o,t,!0)},e._formClustersByHub=function(t,e){for(var i in this.nodes)this.nodes.hasOwnProperty(i)&&this._formClusterFromHub(this.nodes[i],t,e)},e._formClusterFromHub=function(t,e,i,s){if(void 0===s&&(s=0),t.dynamicEdgesLength>=this.hubThreshold&&0==i||t.dynamicEdgesLength==this.hubThreshold&&1==i){for(var o,n,r,a=this.constants.clustering.clusterEdgeThreshold/this.scale,h=!1,d=[],l=t.dynamicEdges.length,c=0;l>c;c++)d.push(t.dynamicEdges[c].id);if(0==e)for(h=!1,c=0;l>c;c++){var p=this.edges[d[c]];if(void 0!==p&&p.connected&&p.toId!=p.fromId&&(o=p.to.x-p.from.x,n=p.to.y-p.from.y,r=Math.sqrt(o*o+n*n),a>r)){h=!0;break}}if(!e&&h||e)for(c=0;l>c;c++)if(p=this.edges[d[c]],void 0!==p){var u=this.nodes[p.fromId==t.id?p.toId:p.fromId];u.dynamicEdges.length<=this.hubThreshold+s&&u.id!=t.id&&this._addToCluster(t,u,e)}}},e._addToCluster=function(t,e,i){t.containedNodes[e.id]=e;for(var s=0;s1)for(var s=0;s1&&(e.label="[".concat(String(e.clusterSize),"]"))}for(t in this.nodes)this.nodes.hasOwnProperty(t)&&(e=this.nodes[t],1==e.clusterSize&&(e.label=void 0!==e.originalLabel?e.originalLabel:String(e.id)))},e.normalizeClusterLevels=function(){var t,e=0,i=1e9,s=0;for(t in this.nodes)this.nodes.hasOwnProperty(t)&&(s=this.nodes[t].clusterSessions.length,s>e&&(e=s),i>s&&(i=s));if(e-i>this.constants.clustering.clusterLevelDifference){var o=this.nodeIndices.length,n=e-this.constants.clustering.clusterLevelDifference;for(t in this.nodes)this.nodes.hasOwnProperty(t)&&this.nodes[t].clusterSessions.lengths&&(s=n.dynamicEdgesLength),t+=n.dynamicEdgesLength,e+=Math.pow(n.dynamicEdgesLength,2),i+=1}t/=i,e/=i;var r=e-Math.pow(t,2),a=Math.sqrt(r);this.hubThreshold=Math.floor(t+2*a),this.hubThreshold>s&&(this.hubThreshold=s)},e._reduceAmountOfChains=function(t){this.hubThreshold=2;var e=Math.floor(this.nodeIndices.length*t);for(var i in this.nodes)this.nodes.hasOwnProperty(i)&&2==this.nodes[i].dynamicEdgesLength&&this.nodes[i].dynamicEdges.length>=2&&e>0&&(this._formClusterFromHub(this.nodes[i],!0,!0,1),e-=1)},e._getChainFraction=function(){var t=0,e=0;for(var i in this.nodes)this.nodes.hasOwnProperty(i)&&(2==this.nodes[i].dynamicEdgesLength&&this.nodes[i].dynamicEdges.length>=2&&(t+=1),e+=1);return t/e}},function(t,e,i){var s=i(1),o=i(40);e._putDataInSector=function(){this.sectors.active[this._sector()].nodes=this.nodes,this.sectors.active[this._sector()].edges=this.edges,this.sectors.active[this._sector()].nodeIndices=this.nodeIndices},e._switchToSector=function(t,e){void 0===e||"active"==e?this._switchToActiveSector(t):this._switchToFrozenSector(t)},e._switchToActiveSector=function(t){this.nodeIndices=this.sectors.active[t].nodeIndices,this.nodes=this.sectors.active[t].nodes,this.edges=this.sectors.active[t].edges},e._switchToSupportSector=function(){this.nodeIndices=this.sectors.support.nodeIndices,this.nodes=this.sectors.support.nodes,this.edges=this.sectors.support.edges},e._switchToFrozenSector=function(t){this.nodeIndices=this.sectors.frozen[t].nodeIndices,this.nodes=this.sectors.frozen[t].nodes,this.edges=this.sectors.frozen[t].edges},e._loadLatestSector=function(){this._switchToSector(this._sector())},e._sector=function(){return this.activeSector[this.activeSector.length-1]},e._previousSector=function(){if(this.activeSector.length>1)return this.activeSector[this.activeSector.length-2];throw new TypeError("there are not enough sectors in the this.activeSector array.")},e._setActiveSector=function(t){this.activeSector.push(t)},e._forgetLastSector=function(){this.activeSector.pop()},e._createNewSector=function(t){this.sectors.active[t]={nodes:{},edges:{},nodeIndices:[],formationScale:this.scale,drawingNode:void 0},this.sectors.active[t].drawingNode=new o({id:t,color:{background:"#eaefef",border:"495c5e"}},{},{},this.constants),this.sectors.active[t].drawingNode.clusterSize=2},e._deleteActiveSector=function(t){delete this.sectors.active[t]},e._deleteFrozenSector=function(t){delete this.sectors.frozen[t]},e._freezeSector=function(t){this.sectors.frozen[t]=this.sectors.active[t],this._deleteActiveSector(t)},e._activateSector=function(t){this.sectors.active[t]=this.sectors.frozen[t],this._deleteFrozenSector(t)},e._mergeThisWithFrozen=function(t){for(var e in this.nodes)this.nodes.hasOwnProperty(e)&&(this.sectors.frozen[t].nodes[e]=this.nodes[e]);for(var i in this.edges)this.edges.hasOwnProperty(i)&&(this.sectors.frozen[t].edges[i]=this.edges[i]);for(var s=0;s1?this[t](o[0],o[1]):this[t](e))}return this._loadLatestSector(),i},e._doInSupportSector=function(t,e){var i=!1;if(void 0===e)this._switchToSupportSector(),i=this[t]();else{this._switchToSupportSector();var s=Array.prototype.splice.call(arguments,1);i=s.length>1?this[t](s[0],s[1]):this[t](e)}return this._loadLatestSector(),i},e._doInAllFrozenSectors=function(t,e){if(void 0===e)for(var i in this.sectors.frozen)this.sectors.frozen.hasOwnProperty(i)&&(this._switchToFrozenSector(i),this[t]());else for(var i in this.sectors.frozen)if(this.sectors.frozen.hasOwnProperty(i)){this._switchToFrozenSector(i);var s=Array.prototype.splice.call(arguments,1);s.length>1?this[t](s[0],s[1]):this[t](e)}this._loadLatestSector()},e._doInAllSectors=function(t,e){var i=Array.prototype.splice.call(arguments,1);void 0===e?(this._doInAllActiveSectors(t),this._doInAllFrozenSectors(t)):i.length>1?(this._doInAllActiveSectors(t,i[0],i[1]),this._doInAllFrozenSectors(t,i[0],i[1])):(this._doInAllActiveSectors(t,e),this._doInAllFrozenSectors(t,e))},e._clearNodeIndexList=function(){var t=this._sector();this.sectors.active[t].nodeIndices=[],this.nodeIndices=this.sectors.active[t].nodeIndices},e._drawSectorNodes=function(t,e){var i,s=1e9,o=-1e9,n=1e9,r=-1e9;for(var a in this.sectors[e])if(this.sectors[e].hasOwnProperty(a)&&void 0!==this.sectors[e][a].drawingNode){this._switchToSector(a,e),s=1e9,o=-1e9,n=1e9,r=-1e9;for(var h in this.nodes)this.nodes.hasOwnProperty(h)&&(i=this.nodes[h],i.resize(t),n>i.x-.5*i.width&&(n=i.x-.5*i.width),ri.y-.5*i.height&&(s=i.y-.5*i.height),o0?this.nodes[i[i.length-1]]:null},e._getEdgesOverlappingWith=function(t,e){var i=this.edges;for(var s in i)i.hasOwnProperty(s)&&i[s].isOverlappingWith(t)&&e.push(s)},e._getAllEdgesOverlappingWith=function(t){var e=[];return this._doInAllActiveSectors("_getEdgesOverlappingWith",t,e),e},e._getEdgeAt=function(t){var e=this._pointerToPositionObject(t),i=this._getAllEdgesOverlappingWith(e);return i.length>0?this.edges[i[i.length-1]]:null},e._addToSelection=function(t){t instanceof s?this.selectionObj.nodes[t.id]=t:this.selectionObj.edges[t.id]=t},e._addToHover=function(t){t instanceof s?this.hoverObj.nodes[t.id]=t:this.hoverObj.edges[t.id]=t},e._removeFromSelection=function(t){t instanceof s?delete this.selectionObj.nodes[t.id]:delete this.selectionObj.edges[t.id]},e._unselectAll=function(t){void 0===t&&(t=!1);for(var e in this.selectionObj.nodes)this.selectionObj.nodes.hasOwnProperty(e)&&this.selectionObj.nodes[e].unselect();for(var i in this.selectionObj.edges)this.selectionObj.edges.hasOwnProperty(i)&&this.selectionObj.edges[i].unselect();this.selectionObj={nodes:{},edges:{}},0==t&&this.emit("select",this.getSelection())},e._unselectClusters=function(t){void 0===t&&(t=!1);for(var e in this.selectionObj.nodes)this.selectionObj.nodes.hasOwnProperty(e)&&this.selectionObj.nodes[e].clusterSize>1&&(this.selectionObj.nodes[e].unselect(),this._removeFromSelection(this.selectionObj.nodes[e]));0==t&&this.emit("select",this.getSelection())},e._getSelectedNodeCount=function(){var t=0;for(var e in this.selectionObj.nodes)this.selectionObj.nodes.hasOwnProperty(e)&&(t+=1);return t},e._getSelectedNode=function(){for(var t in this.selectionObj.nodes)if(this.selectionObj.nodes.hasOwnProperty(t))return this.selectionObj.nodes[t];return null},e._getSelectedEdge=function(){for(var t in this.selectionObj.edges)if(this.selectionObj.edges.hasOwnProperty(t))return this.selectionObj.edges[t];return null},e._getSelectedEdgeCount=function(){var t=0;for(var e in this.selectionObj.edges)this.selectionObj.edges.hasOwnProperty(e)&&(t+=1);return t},e._getSelectedObjectCount=function(){var t=0;for(var e in this.selectionObj.nodes)this.selectionObj.nodes.hasOwnProperty(e)&&(t+=1);for(var i in this.selectionObj.edges)this.selectionObj.edges.hasOwnProperty(i)&&(t+=1);return t},e._selectionIsEmpty=function(){for(var t in this.selectionObj.nodes)if(this.selectionObj.nodes.hasOwnProperty(t))return!1;for(var e in this.selectionObj.edges)if(this.selectionObj.edges.hasOwnProperty(e))return!1;return!0},e._clusterInSelection=function(){for(var t in this.selectionObj.nodes)if(this.selectionObj.nodes.hasOwnProperty(t)&&this.selectionObj.nodes[t].clusterSize>1)return!0;return!1},e._selectConnectedEdges=function(t){for(var e=0;ei;i++){o=t[i];var n=this.nodes[o];if(!n)throw new RangeError('Node with id "'+o+'" not found');this._selectObject(n,!0,!0,e,!0)}this.redraw()},e.selectEdges=function(t){var e,i,s;if(!t||void 0==t.length)throw"Selection must be an array with ids";for(this._unselectAll(!0),e=0,i=t.length;i>e;e++){s=t[e];var o=this.edges[s];if(!o)throw new RangeError('Edge with id "'+s+'" not found');this._selectObject(o,!0,!0,!1,!0)}this.redraw()},e._updateSelection=function(){for(var t in this.selectionObj.nodes)this.selectionObj.nodes.hasOwnProperty(t)&&(this.nodes.hasOwnProperty(t)||delete this.selectionObj.nodes[t]);for(var e in this.selectionObj.edges)this.selectionObj.edges.hasOwnProperty(e)&&(this.edges.hasOwnProperty(e)||delete this.selectionObj.edges[e])}},function(t,e,i){var s=i(1),o=i(40),n=i(37);e._clearManipulatorBar=function(){this._recursiveDOMDelete(this.manipulationDiv),this.manipulationDOM={},this._manipulationReleaseOverload=function(){},delete this.sectors.support.nodes.targetNode,delete this.sectors.support.nodes.targetViaNode,this.controlNodesActive=!1,this.freezeSimulation=!1},e._restoreOverloadedFunctions=function(){for(var t in this.cachedFunctions)this.cachedFunctions.hasOwnProperty(t)&&(this[t]=this.cachedFunctions[t],delete this.cachedFunctions[t])},e._toggleEditMode=function(){this.editMode=!this.editMode;var t=this.manipulationDiv,e=this.closeDiv,i=this.editModeDiv;1==this.editMode?(t.style.display="block",e.style.display="block",i.style.display="none",e.onclick=this._toggleEditMode.bind(this)):(t.style.display="none",e.style.display="none",i.style.display="block",e.onclick=null),this._createManipulatorBar()},e._createManipulatorBar=function(){this.boundFunction&&this.off("select",this.boundFunction);var t=this.constants.locales[this.constants.locale];if(void 0!==this.edgeBeingEdited&&(this.edgeBeingEdited._disableControlNodes(),this.edgeBeingEdited=void 0,this.selectedControlNode=null,this.controlNodesActive=!1,this._redraw()),this._restoreOverloadedFunctions(),this.freezeSimulation=!1,this.blockConnectingEdgeSelection=!1,this.forceAppendSelection=!1,this.manipulationDOM={},1==this.editMode){for(;this.manipulationDiv.hasChildNodes();)this.manipulationDiv.removeChild(this.manipulationDiv.firstChild);this.manipulationDOM.addNodeSpan=document.createElement("span"),this.manipulationDOM.addNodeSpan.className="network-manipulationUI add",this.manipulationDOM.addNodeLabelSpan=document.createElement("span"),this.manipulationDOM.addNodeLabelSpan.className="network-manipulationLabel",this.manipulationDOM.addNodeLabelSpan.innerHTML=t.addNode,this.manipulationDOM.addNodeSpan.appendChild(this.manipulationDOM.addNodeLabelSpan),this.manipulationDOM.seperatorLineDiv1=document.createElement("div"),this.manipulationDOM.seperatorLineDiv1.className="network-seperatorLine",this.manipulationDOM.addEdgeSpan=document.createElement("span"),this.manipulationDOM.addEdgeSpan.className="network-manipulationUI connect",this.manipulationDOM.addEdgeLabelSpan=document.createElement("span"),this.manipulationDOM.addEdgeLabelSpan.className="network-manipulationLabel",this.manipulationDOM.addEdgeLabelSpan.innerHTML=t.addEdge,this.manipulationDOM.addEdgeSpan.appendChild(this.manipulationDOM.addEdgeLabelSpan),this.manipulationDiv.appendChild(this.manipulationDOM.addNodeSpan),this.manipulationDiv.appendChild(this.manipulationDOM.seperatorLineDiv1),this.manipulationDiv.appendChild(this.manipulationDOM.addEdgeSpan),1==this._getSelectedNodeCount()&&this.triggerFunctions.edit?(this.manipulationDOM.seperatorLineDiv2=document.createElement("div"),this.manipulationDOM.seperatorLineDiv2.className="network-seperatorLine",this.manipulationDOM.editNodeSpan=document.createElement("span"),this.manipulationDOM.editNodeSpan.className="network-manipulationUI edit",this.manipulationDOM.editNodeLabelSpan=document.createElement("span"),this.manipulationDOM.editNodeLabelSpan.className="network-manipulationLabel",this.manipulationDOM.editNodeLabelSpan.innerHTML=t.editNode,this.manipulationDOM.editNodeSpan.appendChild(this.manipulationDOM.editNodeLabelSpan),this.manipulationDiv.appendChild(this.manipulationDOM.seperatorLineDiv2),this.manipulationDiv.appendChild(this.manipulationDOM.editNodeSpan)):1==this._getSelectedEdgeCount()&&0==this._getSelectedNodeCount()&&(this.manipulationDOM.seperatorLineDiv3=document.createElement("div"),this.manipulationDOM.seperatorLineDiv3.className="network-seperatorLine",this.manipulationDOM.editEdgeSpan=document.createElement("span"),this.manipulationDOM.editEdgeSpan.className="network-manipulationUI edit",this.manipulationDOM.editEdgeLabelSpan=document.createElement("span"),this.manipulationDOM.editEdgeLabelSpan.className="network-manipulationLabel",this.manipulationDOM.editEdgeLabelSpan.innerHTML=t.editEdge,this.manipulationDOM.editEdgeSpan.appendChild(this.manipulationDOM.editEdgeLabelSpan),this.manipulationDiv.appendChild(this.manipulationDOM.seperatorLineDiv3),this.manipulationDiv.appendChild(this.manipulationDOM.editEdgeSpan)),0==this._selectionIsEmpty()&&(this.manipulationDOM.seperatorLineDiv4=document.createElement("div"),this.manipulationDOM.seperatorLineDiv4.className="network-seperatorLine",this.manipulationDOM.deleteSpan=document.createElement("span"),this.manipulationDOM.deleteSpan.className="network-manipulationUI delete",this.manipulationDOM.deleteLabelSpan=document.createElement("span"),this.manipulationDOM.deleteLabelSpan.className="network-manipulationLabel",this.manipulationDOM.deleteLabelSpan.innerHTML=t.del,this.manipulationDOM.deleteSpan.appendChild(this.manipulationDOM.deleteLabelSpan),this.manipulationDiv.appendChild(this.manipulationDOM.seperatorLineDiv4),this.manipulationDiv.appendChild(this.manipulationDOM.deleteSpan)),this.manipulationDOM.addNodeSpan.onclick=this._createAddNodeToolbar.bind(this),this.manipulationDOM.addEdgeSpan.onclick=this._createAddEdgeToolbar.bind(this),1==this._getSelectedNodeCount()&&this.triggerFunctions.edit?this.manipulationDOM.editNodeSpan.onclick=this._editNode.bind(this):1==this._getSelectedEdgeCount()&&0==this._getSelectedNodeCount()&&(this.manipulationDOM.editEdgeSpan.onclick=this._createEditEdgeToolbar.bind(this)),0==this._selectionIsEmpty()&&(this.manipulationDOM.deleteSpan.onclick=this._deleteSelected.bind(this)),this.closeDiv.onclick=this._toggleEditMode.bind(this); +var e=this;this.boundFunction=e._createManipulatorBar,this.on("select",this.boundFunction)}else{for(;this.editModeDiv.hasChildNodes();)this.editModeDiv.removeChild(this.editModeDiv.firstChild);this.manipulationDOM.editModeSpan=document.createElement("span"),this.manipulationDOM.editModeSpan.className="network-manipulationUI edit editmode",this.manipulationDOM.editModeLabelSpan=document.createElement("span"),this.manipulationDOM.editModeLabelSpan.className="network-manipulationLabel",this.manipulationDOM.editModeLabelSpan.innerHTML=t.edit,this.manipulationDOM.editModeSpan.appendChild(this.manipulationDOM.editModeLabelSpan),this.editModeDiv.appendChild(this.manipulationDOM.editModeSpan),this.manipulationDOM.editModeSpan.onclick=this._toggleEditMode.bind(this)}},e._createAddNodeToolbar=function(){this._clearManipulatorBar(),this.boundFunction&&this.off("select",this.boundFunction);var t=this.constants.locales[this.constants.locale];this.manipulationDOM={},this.manipulationDOM.backSpan=document.createElement("span"),this.manipulationDOM.backSpan.className="network-manipulationUI back",this.manipulationDOM.backLabelSpan=document.createElement("span"),this.manipulationDOM.backLabelSpan.className="network-manipulationLabel",this.manipulationDOM.backLabelSpan.innerHTML=t.back,this.manipulationDOM.backSpan.appendChild(this.manipulationDOM.backLabelSpan),this.manipulationDOM.seperatorLineDiv1=document.createElement("div"),this.manipulationDOM.seperatorLineDiv1.className="network-seperatorLine",this.manipulationDOM.descriptionSpan=document.createElement("span"),this.manipulationDOM.descriptionSpan.className="network-manipulationUI none",this.manipulationDOM.descriptionLabelSpan=document.createElement("span"),this.manipulationDOM.descriptionLabelSpan.className="network-manipulationLabel",this.manipulationDOM.descriptionLabelSpan.innerHTML=t.addDescription,this.manipulationDOM.descriptionSpan.appendChild(this.manipulationDOM.descriptionLabelSpan),this.manipulationDiv.appendChild(this.manipulationDOM.backSpan),this.manipulationDiv.appendChild(this.manipulationDOM.seperatorLineDiv1),this.manipulationDiv.appendChild(this.manipulationDOM.descriptionSpan),this.manipulationDOM.backSpan.onclick=this._createManipulatorBar.bind(this);var e=this;this.boundFunction=e._addNode,this.on("select",this.boundFunction)},e._createAddEdgeToolbar=function(){this._clearManipulatorBar(),this._unselectAll(!0),this.freezeSimulation=!0,this.boundFunction&&this.off("select",this.boundFunction);var t=this.constants.locales[this.constants.locale];this._unselectAll(),this.forceAppendSelection=!1,this.blockConnectingEdgeSelection=!0,this.manipulationDOM={},this.manipulationDOM.backSpan=document.createElement("span"),this.manipulationDOM.backSpan.className="network-manipulationUI back",this.manipulationDOM.backLabelSpan=document.createElement("span"),this.manipulationDOM.backLabelSpan.className="network-manipulationLabel",this.manipulationDOM.backLabelSpan.innerHTML=t.back,this.manipulationDOM.backSpan.appendChild(this.manipulationDOM.backLabelSpan),this.manipulationDOM.seperatorLineDiv1=document.createElement("div"),this.manipulationDOM.seperatorLineDiv1.className="network-seperatorLine",this.manipulationDOM.descriptionSpan=document.createElement("span"),this.manipulationDOM.descriptionSpan.className="network-manipulationUI none",this.manipulationDOM.descriptionLabelSpan=document.createElement("span"),this.manipulationDOM.descriptionLabelSpan.className="network-manipulationLabel",this.manipulationDOM.descriptionLabelSpan.innerHTML=t.edgeDescription,this.manipulationDOM.descriptionSpan.appendChild(this.manipulationDOM.descriptionLabelSpan),this.manipulationDiv.appendChild(this.manipulationDOM.backSpan),this.manipulationDiv.appendChild(this.manipulationDOM.seperatorLineDiv1),this.manipulationDiv.appendChild(this.manipulationDOM.descriptionSpan),this.manipulationDOM.backSpan.onclick=this._createManipulatorBar.bind(this);var e=this;this.boundFunction=e._handleConnect,this.on("select",this.boundFunction),this.cachedFunctions._handleTouch=this._handleTouch,this.cachedFunctions._manipulationReleaseOverload=this._manipulationReleaseOverload,this.cachedFunctions._handleDragStart=this._handleDragStart,this.cachedFunctions._handleDragEnd=this._handleDragEnd,this._handleTouch=this._handleConnect,this._manipulationReleaseOverload=function(){},this._handleDragStart=function(){},this._handleDragEnd=this._finishConnect,this._redraw()},e._createEditEdgeToolbar=function(){this._clearManipulatorBar(),this.controlNodesActive=!0,this.boundFunction&&this.off("select",this.boundFunction),this.edgeBeingEdited=this._getSelectedEdge(),this.edgeBeingEdited._enableControlNodes();var t=this.constants.locales[this.constants.locale];this.manipulationDOM={},this.manipulationDOM.backSpan=document.createElement("span"),this.manipulationDOM.backSpan.className="network-manipulationUI back",this.manipulationDOM.backLabelSpan=document.createElement("span"),this.manipulationDOM.backLabelSpan.className="network-manipulationLabel",this.manipulationDOM.backLabelSpan.innerHTML=t.back,this.manipulationDOM.backSpan.appendChild(this.manipulationDOM.backLabelSpan),this.manipulationDOM.seperatorLineDiv1=document.createElement("div"),this.manipulationDOM.seperatorLineDiv1.className="network-seperatorLine",this.manipulationDOM.descriptionSpan=document.createElement("span"),this.manipulationDOM.descriptionSpan.className="network-manipulationUI none",this.manipulationDOM.descriptionLabelSpan=document.createElement("span"),this.manipulationDOM.descriptionLabelSpan.className="network-manipulationLabel",this.manipulationDOM.descriptionLabelSpan.innerHTML=t.editEdgeDescription,this.manipulationDOM.descriptionSpan.appendChild(this.manipulationDOM.descriptionLabelSpan),this.manipulationDiv.appendChild(this.manipulationDOM.backSpan),this.manipulationDiv.appendChild(this.manipulationDOM.seperatorLineDiv1),this.manipulationDiv.appendChild(this.manipulationDOM.descriptionSpan),this.manipulationDOM.backSpan.onclick=this._createManipulatorBar.bind(this),this.cachedFunctions._handleTouch=this._handleTouch,this.cachedFunctions._manipulationReleaseOverload=this._manipulationReleaseOverload,this.cachedFunctions._handleTap=this._handleTap,this.cachedFunctions._handleDragStart=this._handleDragStart,this.cachedFunctions._handleOnDrag=this._handleOnDrag,this._handleTouch=this._selectControlNode,this._handleTap=function(){},this._handleOnDrag=this._controlNodeDrag,this._handleDragStart=function(){},this._manipulationReleaseOverload=this._releaseControlNode,this._redraw()},e._selectControlNode=function(t){this.edgeBeingEdited.controlNodes.from.unselect(),this.edgeBeingEdited.controlNodes.to.unselect(),this.selectedControlNode=this.edgeBeingEdited._getSelectedControlNode(this._XconvertDOMtoCanvas(t.x),this._YconvertDOMtoCanvas(t.y)),null!==this.selectedControlNode&&(this.selectedControlNode.select(),this.freezeSimulation=!0),this._redraw()},e._controlNodeDrag=function(t){var e=this._getPointer(t.center);null!==this.selectedControlNode&&void 0!==this.selectedControlNode&&(this.selectedControlNode.x=this._XconvertDOMtoCanvas(e.x),this.selectedControlNode.y=this._YconvertDOMtoCanvas(e.y)),this._redraw()},e._releaseControlNode=function(t){var e=this._getNodeAt(t);null!==e?(1==this.edgeBeingEdited.controlNodes.from.selected&&(this.edgeBeingEdited._restoreControlNodes(),this._editEdge(e.id,this.edgeBeingEdited.to.id),this.edgeBeingEdited.controlNodes.from.unselect()),1==this.edgeBeingEdited.controlNodes.to.selected&&(this.edgeBeingEdited._restoreControlNodes(),this._editEdge(this.edgeBeingEdited.from.id,e.id),this.edgeBeingEdited.controlNodes.to.unselect())):this.edgeBeingEdited._restoreControlNodes(),this.freezeSimulation=!1,this._redraw()},e._handleConnect=function(t){if(0==this._getSelectedNodeCount()){var e=this._getNodeAt(t);if(null!=e)if(e.clusterSize>1)alert(this.constants.locales[this.constants.locale].createEdgeError);else{this._selectObject(e,!1);var i=this.sectors.support.nodes;i.targetNode=new o({id:"targetNode"},{},{},this.constants);var s=i.targetNode;s.x=e.x,s.y=e.y,this.edges.connectionEdge=new n({id:"connectionEdge",from:e.id,to:s.id},this,this.constants);var r=this.edges.connectionEdge;r.from=e,r.connected=!0,r.options.smoothCurves={enabled:!0,dynamic:!1,type:"continuous",roundness:.5},r.selected=!0,r.to=s,this.cachedFunctions._handleOnDrag=this._handleOnDrag,this._handleOnDrag=function(t){var e=this._getPointer(t.center),i=this.edges.connectionEdge;i.to.x=this._XconvertDOMtoCanvas(e.x),i.to.y=this._YconvertDOMtoCanvas(e.y)},this.moving=!0,this.start()}}},e._finishConnect=function(t){if(1==this._getSelectedNodeCount()){var e=this._getPointer(t.center);this._handleOnDrag=this.cachedFunctions._handleOnDrag,delete this.cachedFunctions._handleOnDrag;var i=this.edges.connectionEdge.fromId;delete this.edges.connectionEdge,delete this.sectors.support.nodes.targetNode,delete this.sectors.support.nodes.targetViaNode;var s=this._getNodeAt(e);null!=s&&(s.clusterSize>1?alert(this.constants.locales[this.constants.locale].createEdgeError):(this._createEdge(i,s.id),this._createManipulatorBar())),this._unselectAll()}},e._addNode=function(){if(this._selectionIsEmpty()&&1==this.editMode){var t=this._pointerToPositionObject(this.pointerPosition),e={id:s.randomUUID(),x:t.left,y:t.top,label:"new",allowedToMoveX:!0,allowedToMoveY:!0};if(this.triggerFunctions.add){if(2!=this.triggerFunctions.add.length)throw new Error("The function for add does not support two arguments (data,callback)");var i=this;this.triggerFunctions.add(e,function(t){i.nodesData.add(t),i._createManipulatorBar(),i.moving=!0,i.start()})}else this.nodesData.add(e),this._createManipulatorBar(),this.moving=!0,this.start()}},e._createEdge=function(t,e){if(1==this.editMode){var i={from:t,to:e};if(this.triggerFunctions.connect){if(2!=this.triggerFunctions.connect.length)throw new Error("The function for connect does not support two arguments (data,callback)");var s=this;this.triggerFunctions.connect(i,function(t){s.edgesData.add(t),s.moving=!0,s.start()})}else this.edgesData.add(i),this.moving=!0,this.start()}},e._editEdge=function(t,e){if(1==this.editMode){var i={id:this.edgeBeingEdited.id,from:t,to:e};if(this.triggerFunctions.editEdge){if(2!=this.triggerFunctions.editEdge.length)throw new Error("The function for edit does not support two arguments (data, callback)");var s=this;this.triggerFunctions.editEdge(i,function(t){s.edgesData.update(t),s.moving=!0,s.start()})}else this.edgesData.update(i),this.moving=!0,this.start()}},e._editNode=function(){if(!this.triggerFunctions.edit||1!=this.editMode)throw new Error("No edit function has been bound to this button");var t=this._getSelectedNode(),e={id:t.id,label:t.label,group:t.options.group,shape:t.options.shape,color:{background:t.options.color.background,border:t.options.color.border,highlight:{background:t.options.color.highlight.background,border:t.options.color.highlight.border}}};if(2!=this.triggerFunctions.edit.length)throw new Error("The function for edit does not support two arguments (data, callback)");var i=this;this.triggerFunctions.edit(e,function(t){i.nodesData.update(t),i._createManipulatorBar(),i.moving=!0,i.start()})},e._deleteSelected=function(){if(!this._selectionIsEmpty()&&1==this.editMode)if(this._clusterInSelection())alert(this.constants.locales[this.constants.locale].deleteClusterError);else{var t=this.getSelectedNodes(),e=this.getSelectedEdges();if(this.triggerFunctions.del){var i=this,s={nodes:t,edges:e};if(2!=this.triggerFunctions.del.length)throw new Error("The function for delete does not support two arguments (data, callback)");this.triggerFunctions.del(s,function(t){i.edgesData.remove(t.edges),i.nodesData.remove(t.nodes),i._unselectAll(),i.moving=!0,i.start()})}else this.edgesData.remove(e),this.nodesData.remove(t),this._unselectAll(),this.moving=!0,this.start()}}},function(t,e,i){var s=(i(1),i(47)),o=i(45);e._cleanNavigation=function(){if(0!=this.navigationHammers.existing.length){for(var t=0;t0){var t,e,i=0,s=!1,o=!1;for(e in this.nodes)this.nodes.hasOwnProperty(e)&&(t=this.nodes[e],-1!=t.level?s=!0:o=!0,is&&(n.xFixed=!1,n.x=i[n.level].minPos,r=!0):n.yFixed&&n.level>s&&(n.yFixed=!1,n.y=i[n.level].minPos,r=!0),1==r&&(i[n.level].minPos+=i[n.level].nodeSpacing,n.edges.length>1&&this._placeBranchNodes(n.edges,n.id,i,n.level))}},e._setLevel=function(t,e,i){for(var s=0;st)&&(o.level=t,o.edges.length>1&&this._setLevel(t+1,o.edges,o.id))}},e._setLevelDirected=function(t,e,i){this.nodes[i].hierarchyEnumerated=!0;for(var s,o,n=0;n1&&s.hierarchyEnumerated===!1&&this._setLevelDirected(s.level,s.edges,s.id)},e._restoreNodes=function(){for(var t in this.nodes)this.nodes.hasOwnProperty(t)&&(this.nodes[t].xFixed=!1,this.nodes[t].yFixed=!1)}},function(t,e,i){function s(){this.constants.smoothCurves.enabled=!this.constants.smoothCurves.enabled;var t=document.getElementById("graph_toggleSmooth");t.style.background=1==this.constants.smoothCurves.enabled?"#A4FF56":"#FF8532",this._configureSmoothCurves(!1)}function o(){for(var t in this.calculationNodes)this.calculationNodes.hasOwnProperty(t)&&(this.calculationNodes[t].vx=0,this.calculationNodes[t].vy=0,this.calculationNodes[t].fx=0,this.calculationNodes[t].fy=0);1==this.constants.hierarchicalLayout.enabled?(this._setupHierarchicalLayout(),a.call(this,"graph_H_nd",1,"physics_hierarchicalRepulsion_nodeDistance"),a.call(this,"graph_H_cg",1,"physics_centralGravity"),a.call(this,"graph_H_sc",1,"physics_springConstant"),a.call(this,"graph_H_sl",1,"physics_springLength"),a.call(this,"graph_H_damp",1,"physics_damping")):this.repositionNodes(),this.moving=!0,this.start()}function n(){var t="No options are required, default values used.",e=[],i=document.getElementById("graph_physicsMethod1"),s=document.getElementById("graph_physicsMethod2");if(1==i.checked){if(this.constants.physics.barnesHut.gravitationalConstant!=this.backupConstants.physics.barnesHut.gravitationalConstant&&e.push("gravitationalConstant: "+this.constants.physics.barnesHut.gravitationalConstant),this.constants.physics.centralGravity!=this.backupConstants.physics.barnesHut.centralGravity&&e.push("centralGravity: "+this.constants.physics.centralGravity),this.constants.physics.springLength!=this.backupConstants.physics.barnesHut.springLength&&e.push("springLength: "+this.constants.physics.springLength),this.constants.physics.springConstant!=this.backupConstants.physics.barnesHut.springConstant&&e.push("springConstant: "+this.constants.physics.springConstant),this.constants.physics.damping!=this.backupConstants.physics.barnesHut.damping&&e.push("damping: "+this.constants.physics.damping),0!=e.length){t="var options = {",t+="physics: {barnesHut: {";for(var o=0;othis.constants.clustering.clusterThreshold&&1==this.constants.clustering.enabled&&this.clusterToFit(this.constants.clustering.reduceToNodes,!1),this._calculateForces())},e._calculateForces=function(){this._calculateGravitationalForces(),this._calculateNodeForces(),this.constants.physics.springConstant>0&&(1==this.constants.smoothCurves.enabled&&1==this.constants.smoothCurves.dynamic?this._calculateSpringForcesWithSupport():1==this.constants.physics.hierarchicalRepulsion.enabled?this._calculateHierarchicalSpringForces():this._calculateSpringForces())},e._updateCalculationNodes=function(){if(1==this.constants.smoothCurves.enabled&&1==this.constants.smoothCurves.dynamic){this.calculationNodes={},this.calculationNodeIndices=[];for(var t in this.nodes)this.nodes.hasOwnProperty(t)&&(this.calculationNodes[t]=this.nodes[t]);var e=this.sectors.support.nodes;for(var i in e)e.hasOwnProperty(i)&&(this.edges.hasOwnProperty(e[i].parentEdgeId)?this.calculationNodes[i]=e[i]:e[i]._setForce(0,0));for(var s in this.calculationNodes)this.calculationNodes.hasOwnProperty(s)&&this.calculationNodeIndices.push(s)}else this.calculationNodes=this.nodes,this.calculationNodeIndices=this.nodeIndices},e._calculateGravitationalForces=function(){var t,e,i,s,o,n=this.calculationNodes,r=this.constants.physics.centralGravity,a=0;for(o=0;oSimulation Mode:Barnes HutRepulsionHierarchical
Options:
',this.containerElement.parentElement.insertBefore(this.physicsConfiguration,this.containerElement),this.optionsDiv=document.createElement("div"),this.optionsDiv.style.fontSize="14px",this.optionsDiv.style.fontFamily="verdana",this.containerElement.parentElement.insertBefore(this.optionsDiv,this.containerElement); +var e;e=document.getElementById("graph_BH_gc"),e.onchange=a.bind(this,"graph_BH_gc",-1,"physics_barnesHut_gravitationalConstant"),e=document.getElementById("graph_BH_cg"),e.onchange=a.bind(this,"graph_BH_cg",1,"physics_centralGravity"),e=document.getElementById("graph_BH_sc"),e.onchange=a.bind(this,"graph_BH_sc",1,"physics_springConstant"),e=document.getElementById("graph_BH_sl"),e.onchange=a.bind(this,"graph_BH_sl",1,"physics_springLength"),e=document.getElementById("graph_BH_damp"),e.onchange=a.bind(this,"graph_BH_damp",1,"physics_damping"),e=document.getElementById("graph_R_nd"),e.onchange=a.bind(this,"graph_R_nd",1,"physics_repulsion_nodeDistance"),e=document.getElementById("graph_R_cg"),e.onchange=a.bind(this,"graph_R_cg",1,"physics_centralGravity"),e=document.getElementById("graph_R_sc"),e.onchange=a.bind(this,"graph_R_sc",1,"physics_springConstant"),e=document.getElementById("graph_R_sl"),e.onchange=a.bind(this,"graph_R_sl",1,"physics_springLength"),e=document.getElementById("graph_R_damp"),e.onchange=a.bind(this,"graph_R_damp",1,"physics_damping"),e=document.getElementById("graph_H_nd"),e.onchange=a.bind(this,"graph_H_nd",1,"physics_hierarchicalRepulsion_nodeDistance"),e=document.getElementById("graph_H_cg"),e.onchange=a.bind(this,"graph_H_cg",1,"physics_centralGravity"),e=document.getElementById("graph_H_sc"),e.onchange=a.bind(this,"graph_H_sc",1,"physics_springConstant"),e=document.getElementById("graph_H_sl"),e.onchange=a.bind(this,"graph_H_sl",1,"physics_springLength"),e=document.getElementById("graph_H_damp"),e.onchange=a.bind(this,"graph_H_damp",1,"physics_damping"),e=document.getElementById("graph_H_direction"),e.onchange=a.bind(this,"graph_H_direction",t,"hierarchicalLayout_direction"),e=document.getElementById("graph_H_levsep"),e.onchange=a.bind(this,"graph_H_levsep",1,"hierarchicalLayout_levelSeparation"),e=document.getElementById("graph_H_nspac"),e.onchange=a.bind(this,"graph_H_nspac",1,"hierarchicalLayout_nodeSpacing");var i=document.getElementById("graph_physicsMethod1"),d=document.getElementById("graph_physicsMethod2"),l=document.getElementById("graph_physicsMethod3");d.checked=!0,this.constants.physics.barnesHut.enabled&&(i.checked=!0),this.constants.hierarchicalLayout.enabled&&(l.checked=!0);var c=document.getElementById("graph_toggleSmooth"),p=document.getElementById("graph_repositionNodes"),u=document.getElementById("graph_generateOptions");c.onclick=s.bind(this),p.onclick=o.bind(this),u.onclick=n.bind(this),c.style.background=1==this.constants.smoothCurves&&0==this.constants.dynamicSmoothCurves?"#A4FF56":"#FF8532",r.apply(this),i.onchange=r.bind(this),d.onchange=r.bind(this),l.onchange=r.bind(this)}},e._overWriteGraphConstants=function(t,e){var i=t.split("_");1==i.length?this.constants[i[0]]=e:2==i.length?this.constants[i[0]][i[1]]=e:3==i.length&&(this.constants[i[0]][i[1]][i[2]]=e)}},function(t){function e(t){throw new Error("Cannot find module '"+t+"'.")}e.keys=function(){return[]},e.resolve=e,t.exports=e,e.id=68},function(t,e){e._calculateNodeForces=function(){var t,e,i,s,o,n,r,a,h,d,l,c=this.calculationNodes,p=this.calculationNodeIndices,u=-2/3,m=4/3,f=this.constants.physics.repulsion.nodeDistance,g=f;for(d=0;di&&(r=.5*g>i?1:v*i+m,r*=0==n?1:1+n*this.constants.clustering.forceAmplification,r/=Math.max(i,.01*g),s=t*r,o=e*r,a.fx-=s,a.fy-=o,h.fx+=s,h.fy+=o)}}},function(t,e){e._calculateNodeForces=function(){var t,e,i,s,o,n,r,a,h,d,l=this.calculationNodes,c=this.calculationNodeIndices,p=this.constants.physics.hierarchicalRepulsion.nodeDistance;for(h=0;hi?-Math.pow(u*i,2)+Math.pow(u*p,2):0,0==i?i=.01:n/=i,s=t*n,o=e*n,r.fx-=s,r.fy-=o,a.fx+=s,a.fy+=o}},e._calculateHierarchicalSpringForces=function(){for(var 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a/core/src/main/scala/org/apache/spark/Aggregator.scala +++ b/core/src/main/scala/org/apache/spark/Aggregator.scala @@ -88,10 +88,7 @@ case class Aggregator[K, V, C] ( combiners.iterator } else { val combiners = new ExternalAppendOnlyMap[K, C, C](identity, mergeCombiners, mergeCombiners) - while (iter.hasNext) { - val pair = iter.next() - combiners.insert(pair._1, pair._2) - } + combiners.insertAll(iter) // Update task metrics if context is not null // TODO: Make context non-optional in a future release Option(context).foreach { c => diff --git a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala index b986fa87dc2f4..228d9149df2a2 100644 --- a/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala +++ b/core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala @@ -27,13 +27,20 @@ import org.apache.spark.util.{ThreadUtils, Clock, SystemClock, Utils} /** * An agent that dynamically allocates and removes executors based on the workload. * - * The add policy depends on whether there are backlogged tasks waiting to be scheduled. If - * the scheduler queue is not drained in N seconds, then new executors are added. If the queue - * persists for another M seconds, then more executors are added and so on. The number added - * in each round increases exponentially from the previous round until an upper bound on the - * number of executors has been reached. The upper bound is based both on a configured property - * and on the number of tasks pending: the policy will never increase the number of executor - * requests past the number needed to handle all pending tasks. + * The ExecutorAllocationManager maintains a moving target number of executors which is periodically + * synced to the cluster manager. The target starts at a configured initial value and changes with + * the number of pending and running tasks. + * + * Decreasing the target number of executors happens when the current target is more than needed to + * handle the current load. The target number of executors is always truncated to the number of + * executors that could run all current running and pending tasks at once. + * + * Increasing the target number of executors happens in response to backlogged tasks waiting to be + * scheduled. If the scheduler queue is not drained in N seconds, then new executors are added. If + * the queue persists for another M seconds, then more executors are added and so on. The number + * added in each round increases exponentially from the previous round until an upper bound has been + * reached. The upper bound is based both on a configured property and on the current number of + * running and pending tasks, as described above. * * The rationale for the exponential increase is twofold: (1) Executors should be added slowly * in the beginning in case the number of extra executors needed turns out to be small. Otherwise, @@ -105,8 +112,10 @@ private[spark] class ExecutorAllocationManager( // Number of executors to add in the next round private var numExecutorsToAdd = 1 - // Number of executors that have been requested but have not registered yet - private var numExecutorsPending = 0 + // The desired number of executors at this moment in time. If all our executors were to die, this + // is the number of executors we would immediately want from the cluster manager. + private var numExecutorsTarget = + conf.getInt("spark.dynamicAllocation.initialExecutors", minNumExecutors) // Executors that have been requested to be removed but have not been killed yet private val executorsPendingToRemove = new mutable.HashSet[String] @@ -199,13 +208,6 @@ private[spark] class ExecutorAllocationManager( executor.awaitTermination(10, TimeUnit.SECONDS) } - /** - * The number of executors we would have if the cluster manager were to fulfill all our existing - * requests. - */ - private def targetNumExecutors(): Int = - numExecutorsPending + executorIds.size - executorsPendingToRemove.size - /** * The maximum number of executors we would need under the current load to satisfy all running * and pending tasks, rounded up. @@ -227,7 +229,7 @@ private[spark] class ExecutorAllocationManager( private def schedule(): Unit = synchronized { val now = clock.getTimeMillis - addOrCancelExecutorRequests(now) + updateAndSyncNumExecutorsTarget(now) removeTimes.retain { case (executorId, expireTime) => val expired = now >= expireTime @@ -239,26 +241,28 @@ private[spark] class ExecutorAllocationManager( } /** + * Updates our target number of executors and syncs the result with the cluster manager. + * * Check to see whether our existing allocation and the requests we've made previously exceed our - * current needs. If so, let the cluster manager know so that it can cancel pending requests that - * are unneeded. + * current needs. If so, truncate our target and let the cluster manager know so that it can + * cancel pending requests that are unneeded. * * If not, and the add time has expired, see if we can request new executors and refresh the add * time. * * @return the delta in the target number of executors. */ - private def addOrCancelExecutorRequests(now: Long): Int = synchronized { - val currentTarget = targetNumExecutors + private def updateAndSyncNumExecutorsTarget(now: Long): Int = synchronized { val maxNeeded = maxNumExecutorsNeeded - if (maxNeeded < currentTarget) { + if (maxNeeded < numExecutorsTarget) { // The target number exceeds the number we actually need, so stop adding new - // executors and inform the cluster manager to cancel the extra pending requests. - val newTotalExecutors = math.max(maxNeeded, minNumExecutors) - client.requestTotalExecutors(newTotalExecutors) + // executors and inform the cluster manager to cancel the extra pending requests + val oldNumExecutorsTarget = numExecutorsTarget + numExecutorsTarget = math.max(maxNeeded, minNumExecutors) + client.requestTotalExecutors(numExecutorsTarget) numExecutorsToAdd = 1 - updateNumExecutorsPending(newTotalExecutors) + numExecutorsTarget - oldNumExecutorsTarget } else if (addTime != NOT_SET && now >= addTime) { val delta = addExecutors(maxNeeded) logDebug(s"Starting timer to add more executors (to " + @@ -281,21 +285,30 @@ private[spark] class ExecutorAllocationManager( */ private def addExecutors(maxNumExecutorsNeeded: Int): Int = { // Do not request more executors if it would put our target over the upper bound - val currentTarget = targetNumExecutors - if (currentTarget >= maxNumExecutors) { - logDebug(s"Not adding executors because there are already ${executorIds.size} " + - s"registered and $numExecutorsPending pending executor(s) (limit $maxNumExecutors)") + if (numExecutorsTarget >= maxNumExecutors) { + val numExecutorsPending = numExecutorsTarget - executorIds.size + logDebug(s"Not adding executors because there are already ${executorIds.size} registered " + + s"and ${numExecutorsPending} pending executor(s) (limit $maxNumExecutors)") numExecutorsToAdd = 1 return 0 } - val actualMaxNumExecutors = math.min(maxNumExecutors, maxNumExecutorsNeeded) - val newTotalExecutors = math.min(currentTarget + numExecutorsToAdd, actualMaxNumExecutors) - val addRequestAcknowledged = testing || client.requestTotalExecutors(newTotalExecutors) + val oldNumExecutorsTarget = numExecutorsTarget + // There's no point in wasting time ramping up to the number of executors we already have, so + // make sure our target is at least as much as our current allocation: + numExecutorsTarget = math.max(numExecutorsTarget, executorIds.size) + // Boost our target with the number to add for this round: + numExecutorsTarget += numExecutorsToAdd + // Ensure that our target doesn't exceed what we need at the present moment: + numExecutorsTarget = math.min(numExecutorsTarget, maxNumExecutorsNeeded) + // Ensure that our target fits within configured bounds: + numExecutorsTarget = math.max(math.min(numExecutorsTarget, maxNumExecutors), minNumExecutors) + + val addRequestAcknowledged = testing || client.requestTotalExecutors(numExecutorsTarget) if (addRequestAcknowledged) { - val delta = updateNumExecutorsPending(newTotalExecutors) + val delta = numExecutorsTarget - oldNumExecutorsTarget logInfo(s"Requesting $delta new executor(s) because tasks are backlogged" + - s" (new desired total will be $newTotalExecutors)") + s" (new desired total will be $numExecutorsTarget)") numExecutorsToAdd = if (delta == numExecutorsToAdd) { numExecutorsToAdd * 2 } else { @@ -304,23 +317,11 @@ private[spark] class ExecutorAllocationManager( delta } else { logWarning( - s"Unable to reach the cluster manager to request $newTotalExecutors total executors!") + s"Unable to reach the cluster manager to request $numExecutorsTarget total executors!") 0 } } - /** - * Given the new target number of executors, update the number of pending executor requests, - * and return the delta from the old number of pending requests. - */ - private def updateNumExecutorsPending(newTotalExecutors: Int): Int = { - val newNumExecutorsPending = - newTotalExecutors - executorIds.size + executorsPendingToRemove.size - val delta = newNumExecutorsPending - numExecutorsPending - numExecutorsPending = newNumExecutorsPending - delta - } - /** * Request the cluster manager to remove the given executor. * Return whether the request is received. @@ -372,10 +373,6 @@ private[spark] class ExecutorAllocationManager( // as idle again so as not to forget that it is a candidate for removal. (see SPARK-4951) executorIds.filter(listener.isExecutorIdle).foreach(onExecutorIdle) logInfo(s"New executor $executorId has registered (new total is ${executorIds.size})") - if (numExecutorsPending > 0) { - numExecutorsPending -= 1 - logDebug(s"Decremented number of pending executors ($numExecutorsPending left)") - } } else { logWarning(s"Duplicate executor $executorId has registered") } diff --git a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala index d65c94e410662..16072283edbe9 100644 --- a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala +++ b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala @@ -106,7 +106,7 @@ private[spark] abstract class MapOutputTracker(conf: SparkConf) extends Logging */ protected def askTracker[T: ClassTag](message: Any): T = { try { - trackerEndpoint.askWithReply[T](message) + trackerEndpoint.askWithRetry[T](message) } catch { case e: Exception => logError("Error communicating with MapOutputTracker", e) diff --git a/core/src/main/scala/org/apache/spark/SecurityManager.scala b/core/src/main/scala/org/apache/spark/SecurityManager.scala index 3653f724ba192..8aed1e20e0686 100644 --- a/core/src/main/scala/org/apache/spark/SecurityManager.scala +++ b/core/src/main/scala/org/apache/spark/SecurityManager.scala @@ -150,8 +150,13 @@ import org.apache.spark.util.Utils * authorization. If not filter is in place the user is generally null and no authorization * can take place. * - * Connection encryption (SSL) configuration is organized hierarchically. The user can configure - * the default SSL settings which will be used for all the supported communication protocols unless + * When authentication is being used, encryption can also be enabled by setting the option + * spark.authenticate.enableSaslEncryption to true. This is only supported by communication + * channels that use the network-common library, and can be used as an alternative to SSL in those + * cases. + * + * SSL can be used for encryption for certain communication channels. The user can configure the + * default SSL settings which will be used for all the supported communication protocols unless * they are overwritten by protocol specific settings. This way the user can easily provide the * common settings for all the protocols without disabling the ability to configure each one * individually. @@ -412,6 +417,14 @@ private[spark] class SecurityManager(sparkConf: SparkConf) */ def isAuthenticationEnabled(): Boolean = authOn + /** + * Checks whether SASL encryption should be enabled. + * @return Whether to enable SASL encryption when connecting to services that support it. + */ + def isSaslEncryptionEnabled(): Boolean = { + sparkConf.getBoolean("spark.authenticate.enableSaslEncryption", false) + } + /** * Gets the user used for authenticating HTTP connections. * For now use a single hardcoded user. diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index ecf9b4260c206..714bfb5c216de 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -217,6 +217,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli private var _heartbeatReceiver: RpcEndpointRef = _ @volatile private var _dagScheduler: DAGScheduler = _ private var _applicationId: String = _ + private var _applicationAttemptId: Option[String] = None private var _eventLogger: Option[EventLoggingListener] = None private var _executorAllocationManager: Option[ExecutorAllocationManager] = None private var _cleaner: Option[ContextCleaner] = None @@ -247,9 +248,11 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli private[spark] def eventLogDir: Option[URI] = _eventLogDir private[spark] def eventLogCodec: Option[String] = _eventLogCodec - // Generate the random name for a temp folder in Tachyon + // Generate the random name for a temp folder in external block store. // Add a timestamp as the suffix here to make it more safe - val tachyonFolderName = "spark-" + randomUUID.toString() + val externalBlockStoreFolderName = "spark-" + randomUUID.toString() + @deprecated("Use externalBlockStoreFolderName instead.", "1.4.0") + val tachyonFolderName = externalBlockStoreFolderName def isLocal: Boolean = (master == "local" || master.startsWith("local[")) @@ -313,6 +316,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli } def applicationId: String = _applicationId + def applicationAttemptId: Option[String] = _applicationAttemptId def metricsSystem: MetricsSystem = if (_env != null) _env.metricsSystem else null @@ -343,6 +347,19 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli value } + /** Control our logLevel. This overrides any user-defined log settings. + * @param logLevel The desired log level as a string. + * Valid log levels include: ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, WARN + */ + def setLogLevel(logLevel: String) { + val validLevels = Seq("ALL", "DEBUG", "ERROR", "FATAL", "INFO", "OFF", "TRACE", "WARN") + if (!validLevels.contains(logLevel)) { + throw new IllegalArgumentException( + s"Supplied level $logLevel did not match one of: ${validLevels.mkString(",")}") + } + Utils.setLogLevel(org.apache.log4j.Level.toLevel(logLevel)) + } + try { _conf = config.clone() _conf.validateSettings() @@ -386,7 +403,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli } } - _conf.set("spark.tachyonStore.folderName", tachyonFolderName) + _conf.set("spark.externalBlockStore.folderName", externalBlockStoreFolderName) if (master == "yarn-client") System.setProperty("SPARK_YARN_MODE", "true") @@ -470,6 +487,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli _taskScheduler.start() _applicationId = _taskScheduler.applicationId() + _applicationAttemptId = taskScheduler.applicationAttemptId() _conf.set("spark.app.id", _applicationId) _env.blockManager.initialize(_applicationId) @@ -482,7 +500,8 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli _eventLogger = if (isEventLogEnabled) { val logger = - new EventLoggingListener(_applicationId, _eventLogDir.get, _conf, _hadoopConfiguration) + new EventLoggingListener(_applicationId, _applicationAttemptId, _eventLogDir.get, + _conf, _hadoopConfiguration) logger.start() listenerBus.addListener(logger) Some(logger) @@ -555,7 +574,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli SparkEnv.executorActorSystemName, RpcAddress(host, port), ExecutorEndpoint.EXECUTOR_ENDPOINT_NAME) - Some(endpointRef.askWithReply[Array[ThreadStackTrace]](TriggerThreadDump)) + Some(endpointRef.askWithRetry[Array[ThreadStackTrace]](TriggerThreadDump)) } } catch { case e: Exception => @@ -728,7 +747,9 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli minPartitions: Int = defaultMinPartitions): RDD[(String, String)] = withRDDScope { assertNotStopped() val job = new NewHadoopJob(hadoopConfiguration) - NewFileInputFormat.addInputPath(job, new Path(path)) + // Use setInputPaths so that wholeTextFiles aligns with hadoopFile/textFile in taking + // comma separated files as input. (see SPARK-7155) + NewFileInputFormat.setInputPaths(job, path) val updateConf = job.getConfiguration new WholeTextFileRDD( this, @@ -775,7 +796,9 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli minPartitions: Int = defaultMinPartitions): RDD[(String, PortableDataStream)] = withRDDScope { assertNotStopped() val job = new NewHadoopJob(hadoopConfiguration) - NewFileInputFormat.addInputPath(job, new Path(path)) + // Use setInputPaths so that binaryFiles aligns with hadoopFile/textFile in taking + // comma separated files as input. (see SPARK-7155) + NewFileInputFormat.setInputPaths(job, path) val updateConf = job.getConfiguration new BinaryFileRDD( this, @@ -952,7 +975,9 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli // The call to new NewHadoopJob automatically adds security credentials to conf, // so we don't need to explicitly add them ourselves val job = new NewHadoopJob(conf) - NewFileInputFormat.addInputPath(job, new Path(path)) + // Use setInputPaths so that newAPIHadoopFile aligns with hadoopFile/textFile in taking + // comma separated files as input. (see SPARK-7155) + NewFileInputFormat.setInputPaths(job, path) val updatedConf = job.getConfiguration new NewHadoopRDD(this, fClass, kClass, vClass, updatedConf).setName(path) } @@ -1879,7 +1904,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli // Note: this code assumes that the task scheduler has been initialized and has contacted // the cluster manager to get an application ID (in case the cluster manager provides one). listenerBus.post(SparkListenerApplicationStart(appName, Some(applicationId), - startTime, sparkUser)) + startTime, sparkUser, applicationAttemptId)) } /** Post the application end event */ diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala index 959aefabd8de4..0c4d28f786edd 100644 --- a/core/src/main/scala/org/apache/spark/SparkEnv.scala +++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala @@ -40,6 +40,7 @@ import org.apache.spark.scheduler.OutputCommitCoordinator.OutputCommitCoordinato import org.apache.spark.serializer.Serializer import org.apache.spark.shuffle.{ShuffleMemoryManager, ShuffleManager} import org.apache.spark.storage._ +import org.apache.spark.unsafe.memory.{ExecutorMemoryManager, MemoryAllocator} import org.apache.spark.util.{RpcUtils, Utils} /** @@ -69,6 +70,7 @@ class SparkEnv ( val sparkFilesDir: String, val metricsSystem: MetricsSystem, val shuffleMemoryManager: ShuffleMemoryManager, + val executorMemoryManager: ExecutorMemoryManager, val outputCommitCoordinator: OutputCommitCoordinator, val conf: SparkConf) extends Logging { @@ -382,6 +384,15 @@ object SparkEnv extends Logging { new OutputCommitCoordinatorEndpoint(rpcEnv, outputCommitCoordinator)) outputCommitCoordinator.coordinatorRef = Some(outputCommitCoordinatorRef) + val executorMemoryManager: ExecutorMemoryManager = { + val allocator = if (conf.getBoolean("spark.unsafe.offHeap", false)) { + MemoryAllocator.UNSAFE + } else { + MemoryAllocator.HEAP + } + new ExecutorMemoryManager(allocator) + } + val envInstance = new SparkEnv( executorId, rpcEnv, @@ -398,6 +409,7 @@ object SparkEnv extends Logging { sparkFilesDir, metricsSystem, shuffleMemoryManager, + executorMemoryManager, outputCommitCoordinator, conf) diff --git a/core/src/main/scala/org/apache/spark/TaskContext.scala b/core/src/main/scala/org/apache/spark/TaskContext.scala index 7d7fe1a446313..d09e17dea0911 100644 --- a/core/src/main/scala/org/apache/spark/TaskContext.scala +++ b/core/src/main/scala/org/apache/spark/TaskContext.scala @@ -21,6 +21,7 @@ import java.io.Serializable import org.apache.spark.annotation.DeveloperApi import org.apache.spark.executor.TaskMetrics +import org.apache.spark.unsafe.memory.TaskMemoryManager import org.apache.spark.util.TaskCompletionListener @@ -133,4 +134,9 @@ abstract class TaskContext extends Serializable { /** ::DeveloperApi:: */ @DeveloperApi def taskMetrics(): TaskMetrics + + /** + * Returns the manager for this task's managed memory. + */ + private[spark] def taskMemoryManager(): TaskMemoryManager } diff --git a/core/src/main/scala/org/apache/spark/TaskContextImpl.scala b/core/src/main/scala/org/apache/spark/TaskContextImpl.scala index 337c8e4ebebcd..b4d572cb52313 100644 --- a/core/src/main/scala/org/apache/spark/TaskContextImpl.scala +++ b/core/src/main/scala/org/apache/spark/TaskContextImpl.scala @@ -18,6 +18,7 @@ package org.apache.spark import org.apache.spark.executor.TaskMetrics +import org.apache.spark.unsafe.memory.TaskMemoryManager import org.apache.spark.util.{TaskCompletionListener, TaskCompletionListenerException} import scala.collection.mutable.ArrayBuffer @@ -27,6 +28,7 @@ private[spark] class TaskContextImpl( val partitionId: Int, override val taskAttemptId: Long, override val attemptNumber: Int, + override val taskMemoryManager: TaskMemoryManager, val runningLocally: Boolean = false, val taskMetrics: TaskMetrics = TaskMetrics.empty) extends TaskContext diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala index 3be6783bba49d..02e49a853c5f7 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala @@ -755,6 +755,14 @@ class JavaSparkContext(val sc: SparkContext) */ def getLocalProperty(key: String): String = sc.getLocalProperty(key) + /** Control our logLevel. This overrides any user-defined log settings. + * @param logLevel The desired log level as a string. + * Valid log levels include: ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, WARN + */ + def setLogLevel(logLevel: String) { + sc.setLogLevel(logLevel) + } + /** * Assigns a group ID to all the jobs started by this thread until the group ID is set to a * different value or cleared. diff --git a/core/src/main/scala/org/apache/spark/deploy/Client.scala b/core/src/main/scala/org/apache/spark/deploy/Client.scala index c2c3e9a9e4827..848b62f9de71b 100644 --- a/core/src/main/scala/org/apache/spark/deploy/Client.scala +++ b/core/src/main/scala/org/apache/spark/deploy/Client.scala @@ -17,6 +17,7 @@ package org.apache.spark.deploy +import scala.collection.mutable.HashSet import scala.concurrent._ import akka.actor._ @@ -31,21 +32,24 @@ import org.apache.spark.util.{ActorLogReceive, AkkaUtils, RpcUtils, Utils} /** * Proxy that relays messages to the driver. + * + * We currently don't support retry if submission fails. In HA mode, client will submit request to + * all masters and see which one could handle it. */ private class ClientActor(driverArgs: ClientArguments, conf: SparkConf) extends Actor with ActorLogReceive with Logging { - var masterActor: ActorSelection = _ + private val masterActors = driverArgs.masters.map { m => + context.actorSelection(Master.toAkkaUrl(m, AkkaUtils.protocol(context.system))) + } + private val lostMasters = new HashSet[Address] + private var activeMasterActor: ActorSelection = null + val timeout = RpcUtils.askTimeout(conf) override def preStart(): Unit = { - masterActor = context.actorSelection( - Master.toAkkaUrl(driverArgs.master, AkkaUtils.protocol(context.system))) - context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent]) - println(s"Sending ${driverArgs.cmd} command to ${driverArgs.master}") - driverArgs.cmd match { case "launch" => // TODO: We could add an env variable here and intercept it in `sc.addJar` that would @@ -79,11 +83,17 @@ private class ClientActor(driverArgs: ClientArguments, conf: SparkConf) driverArgs.supervise, command) - masterActor ! RequestSubmitDriver(driverDescription) + // This assumes only one Master is active at a time + for (masterActor <- masterActors) { + masterActor ! RequestSubmitDriver(driverDescription) + } case "kill" => val driverId = driverArgs.driverId - masterActor ! RequestKillDriver(driverId) + // This assumes only one Master is active at a time + for (masterActor <- masterActors) { + masterActor ! RequestKillDriver(driverId) + } } } @@ -92,10 +102,9 @@ private class ClientActor(driverArgs: ClientArguments, conf: SparkConf) println("... waiting before polling master for driver state") Thread.sleep(5000) println("... polling master for driver state") - val statusFuture = (masterActor ? RequestDriverStatus(driverId))(timeout) + val statusFuture = (activeMasterActor ? RequestDriverStatus(driverId))(timeout) .mapTo[DriverStatusResponse] val statusResponse = Await.result(statusFuture, timeout) - statusResponse.found match { case false => println(s"ERROR: Cluster master did not recognize $driverId") @@ -122,20 +131,46 @@ private class ClientActor(driverArgs: ClientArguments, conf: SparkConf) case SubmitDriverResponse(success, driverId, message) => println(message) - if (success) pollAndReportStatus(driverId.get) else System.exit(-1) + if (success) { + activeMasterActor = context.actorSelection(sender.path) + pollAndReportStatus(driverId.get) + } else if (!Utils.responseFromBackup(message)) { + System.exit(-1) + } + case KillDriverResponse(driverId, success, message) => println(message) - if (success) pollAndReportStatus(driverId) else System.exit(-1) + if (success) { + activeMasterActor = context.actorSelection(sender.path) + pollAndReportStatus(driverId) + } else if (!Utils.responseFromBackup(message)) { + System.exit(-1) + } case DisassociatedEvent(_, remoteAddress, _) => - println(s"Error connecting to master ${driverArgs.master} ($remoteAddress), exiting.") - System.exit(-1) + if (!lostMasters.contains(remoteAddress)) { + println(s"Error connecting to master $remoteAddress.") + lostMasters += remoteAddress + // Note that this heuristic does not account for the fact that a Master can recover within + // the lifetime of this client. Thus, once a Master is lost it is lost to us forever. This + // is not currently a concern, however, because this client does not retry submissions. + if (lostMasters.size >= masterActors.size) { + println("No master is available, exiting.") + System.exit(-1) + } + } case AssociationErrorEvent(cause, _, remoteAddress, _, _) => - println(s"Error connecting to master ${driverArgs.master} ($remoteAddress), exiting.") - println(s"Cause was: $cause") - System.exit(-1) + if (!lostMasters.contains(remoteAddress)) { + println(s"Error connecting to master ($remoteAddress).") + println(s"Cause was: $cause") + lostMasters += remoteAddress + if (lostMasters.size >= masterActors.size) { + println("No master is available, exiting.") + System.exit(-1) + } + } } } @@ -163,7 +198,9 @@ object Client { "driverClient", Utils.localHostName(), 0, conf, new SecurityManager(conf)) // Verify driverArgs.master is a valid url so that we can use it in ClientActor safely - Master.toAkkaUrl(driverArgs.master, AkkaUtils.protocol(actorSystem)) + for (m <- driverArgs.masters) { + Master.toAkkaUrl(m, AkkaUtils.protocol(actorSystem)) + } actorSystem.actorOf(Props(classOf[ClientActor], driverArgs, conf)) actorSystem.awaitTermination() diff --git a/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala b/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala index 5cbac787dceeb..316e2d59f01b8 100644 --- a/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/ClientArguments.scala @@ -22,8 +22,7 @@ import java.net.{URI, URISyntaxException} import scala.collection.mutable.ListBuffer import org.apache.log4j.Level - -import org.apache.spark.util.{IntParam, MemoryParam} +import org.apache.spark.util.{IntParam, MemoryParam, Utils} /** * Command-line parser for the driver client. @@ -35,7 +34,7 @@ private[deploy] class ClientArguments(args: Array[String]) { var logLevel = Level.WARN // launch parameters - var master: String = "" + var masters: Array[String] = null var jarUrl: String = "" var mainClass: String = "" var supervise: Boolean = DEFAULT_SUPERVISE @@ -80,13 +79,13 @@ private[deploy] class ClientArguments(args: Array[String]) { } jarUrl = _jarUrl - master = _master + masters = Utils.parseStandaloneMasterUrls(_master) mainClass = _mainClass _driverOptions ++= tail case "kill" :: _master :: _driverId :: tail => cmd = "kill" - master = _master + masters = Utils.parseStandaloneMasterUrls(_master) driverId = _driverId case _ => diff --git a/core/src/main/scala/org/apache/spark/deploy/ExternalShuffleService.scala b/core/src/main/scala/org/apache/spark/deploy/ExternalShuffleService.scala index cd16f992a3c0a..09973a0a2c998 100644 --- a/core/src/main/scala/org/apache/spark/deploy/ExternalShuffleService.scala +++ b/core/src/main/scala/org/apache/spark/deploy/ExternalShuffleService.scala @@ -19,10 +19,12 @@ package org.apache.spark.deploy import java.util.concurrent.CountDownLatch +import scala.collection.JavaConversions._ + import org.apache.spark.{Logging, SparkConf, SecurityManager} import org.apache.spark.network.TransportContext import org.apache.spark.network.netty.SparkTransportConf -import org.apache.spark.network.sasl.SaslRpcHandler +import org.apache.spark.network.sasl.SaslServerBootstrap import org.apache.spark.network.server.TransportServer import org.apache.spark.network.shuffle.ExternalShuffleBlockHandler import org.apache.spark.util.Utils @@ -44,10 +46,7 @@ class ExternalShuffleService(sparkConf: SparkConf, securityManager: SecurityMana private val transportConf = SparkTransportConf.fromSparkConf(sparkConf, numUsableCores = 0) private val blockHandler = new ExternalShuffleBlockHandler(transportConf) - private val transportContext: TransportContext = { - val handler = if (useSasl) new SaslRpcHandler(blockHandler, securityManager) else blockHandler - new TransportContext(transportConf, handler) - } + private val transportContext: TransportContext = new TransportContext(transportConf, blockHandler) private var server: TransportServer = _ @@ -62,7 +61,13 @@ class ExternalShuffleService(sparkConf: SparkConf, securityManager: SecurityMana def start() { require(server == null, "Shuffle server already started") logInfo(s"Starting shuffle service on port $port with useSasl = $useSasl") - server = transportContext.createServer(port) + val bootstraps = + if (useSasl) { + Seq(new SaslServerBootstrap(transportConf, securityManager)) + } else { + Nil + } + server = transportContext.createServer(port, bootstraps) } def stop() { diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala index cfaebf9ea5050..b563034457a91 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala @@ -17,12 +17,16 @@ package org.apache.spark.deploy +import java.io.{ByteArrayInputStream, DataInputStream} import java.lang.reflect.Method import java.security.PrivilegedExceptionAction +import java.util.{Arrays, Comparator} +import com.google.common.primitives.Longs import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FileStatus, FileSystem, Path} +import org.apache.hadoop.fs.{FileStatus, FileSystem, Path, PathFilter} import org.apache.hadoop.fs.FileSystem.Statistics +import org.apache.hadoop.hdfs.security.token.delegation.DelegationTokenIdentifier import org.apache.hadoop.mapred.JobConf import org.apache.hadoop.mapreduce.JobContext import org.apache.hadoop.security.{Credentials, UserGroupInformation} @@ -32,6 +36,8 @@ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.util.Utils import scala.collection.JavaConversions._ +import scala.concurrent.duration._ +import scala.language.postfixOps /** * :: DeveloperApi :: @@ -39,7 +45,8 @@ import scala.collection.JavaConversions._ */ @DeveloperApi class SparkHadoopUtil extends Logging { - val conf: Configuration = newConfiguration(new SparkConf()) + private val sparkConf = new SparkConf() + val conf: Configuration = newConfiguration(sparkConf) UserGroupInformation.setConfiguration(conf) /** @@ -201,6 +208,61 @@ class SparkHadoopUtil extends Logging { if (baseStatus.isDir) recurse(basePath) else Array(baseStatus) } + /** + * Lists all the files in a directory with the specified prefix, and does not end with the + * given suffix. The returned {{FileStatus}} instances are sorted by the modification times of + * the respective files. + */ + def listFilesSorted( + remoteFs: FileSystem, + dir: Path, + prefix: String, + exclusionSuffix: String): Array[FileStatus] = { + val fileStatuses = remoteFs.listStatus(dir, + new PathFilter { + override def accept(path: Path): Boolean = { + val name = path.getName + name.startsWith(prefix) && !name.endsWith(exclusionSuffix) + } + }) + Arrays.sort(fileStatuses, new Comparator[FileStatus] { + override def compare(o1: FileStatus, o2: FileStatus): Int = { + Longs.compare(o1.getModificationTime, o2.getModificationTime) + } + }) + fileStatuses + } + + /** + * How much time is remaining (in millis) from now to (fraction * renewal time for the token that + * is valid the latest)? + * This will return -ve (or 0) value if the fraction of validity has already expired. + */ + def getTimeFromNowToRenewal( + sparkConf: SparkConf, + fraction: Double, + credentials: Credentials): Long = { + val now = System.currentTimeMillis() + + val renewalInterval = + sparkConf.getLong("spark.yarn.token.renewal.interval", (24 hours).toMillis) + + credentials.getAllTokens.filter(_.getKind == DelegationTokenIdentifier.HDFS_DELEGATION_KIND) + .map { t => + val identifier = new DelegationTokenIdentifier() + identifier.readFields(new DataInputStream(new ByteArrayInputStream(t.getIdentifier))) + (identifier.getIssueDate + fraction * renewalInterval).toLong - now + }.foldLeft(0L)(math.max) + } + + + private[spark] def getSuffixForCredentialsPath(credentialsPath: Path): Int = { + val fileName = credentialsPath.getName + fileName.substring( + fileName.lastIndexOf(SparkHadoopUtil.SPARK_YARN_CREDS_COUNTER_DELIM) + 1).toInt + } + + private val HADOOP_CONF_PATTERN = "(\\$\\{hadoopconf-[^\\}\\$\\s]+\\})".r.unanchored /** @@ -231,6 +293,17 @@ class SparkHadoopUtil extends Logging { } } } + + /** + * Start a thread to periodically update the current user's credentials with new delegation + * tokens so that writes to HDFS do not fail. + */ + private[spark] def startExecutorDelegationTokenRenewer(conf: SparkConf) {} + + /** + * Stop the thread that does the delegation token updates. + */ + private[spark] def stopExecutorDelegationTokenRenewer() {} } object SparkHadoopUtil { @@ -251,6 +324,10 @@ object SparkHadoopUtil { } } + val SPARK_YARN_CREDS_TEMP_EXTENSION = ".tmp" + + val SPARK_YARN_CREDS_COUNTER_DELIM = "-" + def get: SparkHadoopUtil = { hadoop } diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala index f4f572e1e256e..42b5d41b7b526 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala @@ -118,8 +118,8 @@ object SparkSubmit { * Kill an existing submission using the REST protocol. Standalone and Mesos cluster mode only. */ private def kill(args: SparkSubmitArguments): Unit = { - new RestSubmissionClient() - .killSubmission(args.master, args.submissionToKill) + new RestSubmissionClient(args.master) + .killSubmission(args.submissionToKill) } /** @@ -127,8 +127,8 @@ object SparkSubmit { * Standalone and Mesos cluster mode only. */ private def requestStatus(args: SparkSubmitArguments): Unit = { - new RestSubmissionClient() - .requestSubmissionStatus(args.master, args.submissionToRequestStatusFor) + new RestSubmissionClient(args.master) + .requestSubmissionStatus(args.submissionToRequestStatusFor) } /** @@ -400,6 +400,10 @@ object SparkSubmit { OptionAssigner(args.archives, YARN, CLUSTER, clOption = "--archives"), OptionAssigner(args.jars, YARN, CLUSTER, clOption = "--addJars"), + // Yarn client or cluster + OptionAssigner(args.principal, YARN, ALL_DEPLOY_MODES, clOption = "--principal"), + OptionAssigner(args.keytab, YARN, ALL_DEPLOY_MODES, clOption = "--keytab"), + // Other options OptionAssigner(args.executorCores, STANDALONE, ALL_DEPLOY_MODES, sysProp = "spark.executor.cores"), @@ -734,13 +738,31 @@ private[deploy] object SparkSubmitUtils { /** * Extracts maven coordinates from a comma-delimited string * @param remoteRepos Comma-delimited string of remote repositories + * @param ivySettings The Ivy settings for this session * @return A ChainResolver used by Ivy to search for and resolve dependencies. */ - def createRepoResolvers(remoteRepos: Option[String]): ChainResolver = { + def createRepoResolvers(remoteRepos: Option[String], ivySettings: IvySettings): ChainResolver = { // We need a chain resolver if we want to check multiple repositories val cr = new ChainResolver cr.setName("list") + val localM2 = new IBiblioResolver + localM2.setM2compatible(true) + val m2Path = ".m2" + File.separator + "repository" + File.separator + localM2.setRoot(new File(System.getProperty("user.home"), m2Path).toURI.toString) + localM2.setUsepoms(true) + localM2.setName("local-m2-cache") + cr.add(localM2) + + val localIvy = new IBiblioResolver + localIvy.setRoot(new File(ivySettings.getDefaultIvyUserDir, + "local" + File.separator).toURI.toString) + val ivyPattern = Seq("[organisation]", "[module]", "[revision]", "[type]s", + "[artifact](-[classifier]).[ext]").mkString(File.separator) + localIvy.setPattern(ivyPattern) + localIvy.setName("local-ivy-cache") + cr.add(localIvy) + // the biblio resolver resolves POM declared dependencies val br: IBiblioResolver = new IBiblioResolver br.setM2compatible(true) @@ -773,8 +795,7 @@ private[deploy] object SparkSubmitUtils { /** * Output a comma-delimited list of paths for the downloaded jars to be added to the classpath - * (will append to jars in SparkSubmit). The name of the jar is given - * after a '!' by Ivy. It also sometimes contains '(bundle)' after '.jar'. Remove that as well. + * (will append to jars in SparkSubmit). * @param artifacts Sequence of dependencies that were resolved and retrieved * @param cacheDirectory directory where jars are cached * @return a comma-delimited list of paths for the dependencies @@ -783,10 +804,9 @@ private[deploy] object SparkSubmitUtils { artifacts: Array[AnyRef], cacheDirectory: File): String = { artifacts.map { artifactInfo => - val artifactString = artifactInfo.toString - val jarName = artifactString.drop(artifactString.lastIndexOf("!") + 1) + val artifact = artifactInfo.asInstanceOf[Artifact].getModuleRevisionId cacheDirectory.getAbsolutePath + File.separator + - jarName.substring(0, jarName.lastIndexOf(".jar") + 4) + s"${artifact.getOrganisation}_${artifact.getName}-${artifact.getRevision}.jar" }.mkString(",") } @@ -868,6 +888,7 @@ private[deploy] object SparkSubmitUtils { if (alternateIvyCache.trim.isEmpty) { new File(ivySettings.getDefaultIvyUserDir, "jars") } else { + ivySettings.setDefaultIvyUserDir(new File(alternateIvyCache)) ivySettings.setDefaultCache(new File(alternateIvyCache, "cache")) new File(alternateIvyCache, "jars") } @@ -877,7 +898,7 @@ private[deploy] object SparkSubmitUtils { // create a pattern matcher ivySettings.addMatcher(new GlobPatternMatcher) // create the dependency resolvers - val repoResolver = createRepoResolvers(remoteRepos) + val repoResolver = createRepoResolvers(remoteRepos, ivySettings) ivySettings.addResolver(repoResolver) ivySettings.setDefaultResolver(repoResolver.getName) @@ -911,7 +932,8 @@ private[deploy] object SparkSubmitUtils { } // retrieve all resolved dependencies ivy.retrieve(rr.getModuleDescriptor.getModuleRevisionId, - packagesDirectory.getAbsolutePath + File.separator + "[artifact](-[classifier]).[ext]", + packagesDirectory.getAbsolutePath + File.separator + + "[organization]_[artifact]-[revision].[ext]", retrieveOptions.setConfs(Array(ivyConfName))) System.setOut(sysOut) resolveDependencyPaths(rr.getArtifacts.toArray, packagesDirectory) diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala index c621b8fc86f94..c0e4c771908b3 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -63,6 +63,8 @@ private[deploy] class SparkSubmitArguments(args: Seq[String], env: Map[String, S var action: SparkSubmitAction = null val sparkProperties: HashMap[String, String] = new HashMap[String, String]() var proxyUser: String = null + var principal: String = null + var keytab: String = null // Standalone cluster mode only var supervise: Boolean = false @@ -393,6 +395,12 @@ private[deploy] class SparkSubmitArguments(args: Seq[String], env: Map[String, S case PROXY_USER => proxyUser = value + case PRINCIPAL => + principal = value + + case KEYTAB => + keytab = value + case HELP => printUsageAndExit(0) @@ -506,6 +514,13 @@ private[deploy] class SparkSubmitArguments(args: Seq[String], env: Map[String, S | --num-executors NUM Number of executors to launch (Default: 2). | --archives ARCHIVES Comma separated list of archives to be extracted into the | working directory of each executor. + | --principal PRINCIPAL Principal to be used to login to KDC, while running on + | secure HDFS. + | --keytab KEYTAB The full path to the file that contains the keytab for the + | principal specified above. This keytab will be copied to + | the node running the Application Master via the Secure + | Distributed Cache, for renewing the login tickets and the + | delegation tokens periodically. """.stripMargin ) SparkSubmit.exitFn() diff --git a/core/src/main/scala/org/apache/spark/deploy/history/ApplicationHistoryProvider.scala b/core/src/main/scala/org/apache/spark/deploy/history/ApplicationHistoryProvider.scala index ea6c85ee511d5..6a5011af17458 100644 --- a/core/src/main/scala/org/apache/spark/deploy/history/ApplicationHistoryProvider.scala +++ b/core/src/main/scala/org/apache/spark/deploy/history/ApplicationHistoryProvider.scala @@ -19,15 +19,19 @@ package org.apache.spark.deploy.history import org.apache.spark.ui.SparkUI -private[history] case class ApplicationHistoryInfo( - id: String, - name: String, +private[history] case class ApplicationAttemptInfo( + attemptId: Option[String], startTime: Long, endTime: Long, lastUpdated: Long, sparkUser: String, completed: Boolean = false) +private[history] case class ApplicationHistoryInfo( + id: String, + name: String, + attempts: List[ApplicationAttemptInfo]) + private[history] abstract class ApplicationHistoryProvider { /** @@ -41,9 +45,10 @@ private[history] abstract class ApplicationHistoryProvider { * Returns the Spark UI for a specific application. * * @param appId The application ID. + * @param attemptId The application attempt ID (or None if there is no attempt ID). * @return The application's UI, or None if application is not found. */ - def getAppUI(appId: String): Option[SparkUI] + def getAppUI(appId: String, attemptId: Option[String]): Option[SparkUI] /** * Called when the server is shutting down. diff --git a/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala b/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala index fb2cbbcccc54b..993763f3aa092 100644 --- a/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala +++ b/core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala @@ -32,7 +32,7 @@ import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.io.CompressionCodec import org.apache.spark.scheduler._ import org.apache.spark.ui.SparkUI -import org.apache.spark.util.{ThreadUtils, Utils} +import org.apache.spark.util.{Clock, SystemClock, ThreadUtils, Utils} import org.apache.spark.{Logging, SecurityManager, SparkConf} /** @@ -40,8 +40,12 @@ import org.apache.spark.{Logging, SecurityManager, SparkConf} * This provider checks for new finished applications in the background periodically and * renders the history application UI by parsing the associated event logs. */ -private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHistoryProvider - with Logging { +private[history] class FsHistoryProvider(conf: SparkConf, clock: Clock) + extends ApplicationHistoryProvider with Logging { + + def this(conf: SparkConf) = { + this(conf, new SystemClock()) + } import FsHistoryProvider._ @@ -75,8 +79,8 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis @volatile private var applications: mutable.LinkedHashMap[String, FsApplicationHistoryInfo] = new mutable.LinkedHashMap() - // List of applications to be deleted by event log cleaner. - private var appsToClean = new mutable.ListBuffer[FsApplicationHistoryInfo] + // List of application logs to be deleted by event log cleaner. + private var attemptsToClean = new mutable.ListBuffer[FsApplicationAttemptInfo] // Constants used to parse Spark 1.0.0 log directories. private[history] val LOG_PREFIX = "EVENT_LOG_" @@ -138,31 +142,33 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis override def getListing(): Iterable[FsApplicationHistoryInfo] = applications.values - override def getAppUI(appId: String): Option[SparkUI] = { + override def getAppUI(appId: String, attemptId: Option[String]): Option[SparkUI] = { try { - applications.get(appId).map { info => - val replayBus = new ReplayListenerBus() - val ui = { - val conf = this.conf.clone() - val appSecManager = new SecurityManager(conf) - SparkUI.createHistoryUI(conf, replayBus, appSecManager, appId, - s"${HistoryServer.UI_PATH_PREFIX}/$appId") - // Do not call ui.bind() to avoid creating a new server for each application - } + applications.get(appId).flatMap { appInfo => + appInfo.attempts.find(_.attemptId == attemptId).map { attempt => + val replayBus = new ReplayListenerBus() + val ui = { + val conf = this.conf.clone() + val appSecManager = new SecurityManager(conf) + SparkUI.createHistoryUI(conf, replayBus, appSecManager, appId, + HistoryServer.getAttemptURI(appId, attempt.attemptId)) + // Do not call ui.bind() to avoid creating a new server for each application + } - val appListener = new ApplicationEventListener() - replayBus.addListener(appListener) - val appInfo = replay(fs.getFileStatus(new Path(logDir, info.logPath)), replayBus) + val appListener = new ApplicationEventListener() + replayBus.addListener(appListener) + val appInfo = replay(fs.getFileStatus(new Path(logDir, attempt.logPath)), replayBus) - ui.setAppName(s"${appInfo.name} ($appId)") + ui.setAppName(s"${appInfo.name} ($appId)") - val uiAclsEnabled = conf.getBoolean("spark.history.ui.acls.enable", false) - ui.getSecurityManager.setAcls(uiAclsEnabled) - // make sure to set admin acls before view acls so they are properly picked up - ui.getSecurityManager.setAdminAcls(appListener.adminAcls.getOrElse("")) - ui.getSecurityManager.setViewAcls(appInfo.sparkUser, - appListener.viewAcls.getOrElse("")) - ui + val uiAclsEnabled = conf.getBoolean("spark.history.ui.acls.enable", false) + ui.getSecurityManager.setAcls(uiAclsEnabled) + // make sure to set admin acls before view acls so they are properly picked up + ui.getSecurityManager.setAdminAcls(appListener.adminAcls.getOrElse("")) + ui.getSecurityManager.setViewAcls(attempt.sparkUser, + appListener.viewAcls.getOrElse("")) + ui + } } } catch { case e: FileNotFoundException => None @@ -220,7 +226,7 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis */ private def mergeApplicationListing(logs: Seq[FileStatus]): Unit = { val bus = new ReplayListenerBus() - val newApps = logs.flatMap { fileStatus => + val newAttempts = logs.flatMap { fileStatus => try { val res = replay(fileStatus, bus) logInfo(s"Application log ${res.logPath} loaded successfully.") @@ -232,76 +238,104 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis e) None } - }.toSeq.sortWith(compareAppInfo) - - // When there are new logs, merge the new list with the existing one, maintaining - // the expected ordering (descending end time). Maintaining the order is important - // to avoid having to sort the list every time there is a request for the log list. - if (newApps.nonEmpty) { - val mergedApps = new mutable.LinkedHashMap[String, FsApplicationHistoryInfo]() - def addIfAbsent(info: FsApplicationHistoryInfo): Unit = { - if (!mergedApps.contains(info.id) || - mergedApps(info.id).logPath.endsWith(EventLoggingListener.IN_PROGRESS) && - !info.logPath.endsWith(EventLoggingListener.IN_PROGRESS)) { - mergedApps += (info.id -> info) - } - } + } - val newIterator = newApps.iterator.buffered - val oldIterator = applications.values.iterator.buffered - while (newIterator.hasNext && oldIterator.hasNext) { - if (compareAppInfo(newIterator.head, oldIterator.head)) { - addIfAbsent(newIterator.next()) - } else { - addIfAbsent(oldIterator.next()) + if (newAttempts.isEmpty) { + return + } + + // Build a map containing all apps that contain new attempts. The app information in this map + // contains both the new app attempt, and those that were already loaded in the existing apps + // map. If an attempt has been updated, it replaces the old attempt in the list. + val newAppMap = new mutable.HashMap[String, FsApplicationHistoryInfo]() + newAttempts.foreach { attempt => + val appInfo = newAppMap.get(attempt.appId) + .orElse(applications.get(attempt.appId)) + .map { app => + val attempts = + app.attempts.filter(_.attemptId != attempt.attemptId).toList ++ List(attempt) + new FsApplicationHistoryInfo(attempt.appId, attempt.name, + attempts.sortWith(compareAttemptInfo)) } + .getOrElse(new FsApplicationHistoryInfo(attempt.appId, attempt.name, List(attempt))) + newAppMap(attempt.appId) = appInfo + } + + // Merge the new app list with the existing one, maintaining the expected ordering (descending + // end time). Maintaining the order is important to avoid having to sort the list every time + // there is a request for the log list. + val newApps = newAppMap.values.toSeq.sortWith(compareAppInfo) + val mergedApps = new mutable.LinkedHashMap[String, FsApplicationHistoryInfo]() + def addIfAbsent(info: FsApplicationHistoryInfo): Unit = { + if (!mergedApps.contains(info.id)) { + mergedApps += (info.id -> info) } - newIterator.foreach(addIfAbsent) - oldIterator.foreach(addIfAbsent) + } - applications = mergedApps + val newIterator = newApps.iterator.buffered + val oldIterator = applications.values.iterator.buffered + while (newIterator.hasNext && oldIterator.hasNext) { + if (newAppMap.contains(oldIterator.head.id)) { + oldIterator.next() + } else if (compareAppInfo(newIterator.head, oldIterator.head)) { + addIfAbsent(newIterator.next()) + } else { + addIfAbsent(oldIterator.next()) + } } + newIterator.foreach(addIfAbsent) + oldIterator.foreach(addIfAbsent) + + applications = mergedApps } /** * Delete event logs from the log directory according to the clean policy defined by the user. */ - private def cleanLogs(): Unit = { + private[history] def cleanLogs(): Unit = { try { val maxAge = conf.getTimeAsSeconds("spark.history.fs.cleaner.maxAge", "7d") * 1000 - val now = System.currentTimeMillis() + val now = clock.getTimeMillis() val appsToRetain = new mutable.LinkedHashMap[String, FsApplicationHistoryInfo]() + def shouldClean(attempt: FsApplicationAttemptInfo): Boolean = { + now - attempt.lastUpdated > maxAge && attempt.completed + } + // Scan all logs from the log directory. // Only completed applications older than the specified max age will be deleted. - applications.values.foreach { info => - if (now - info.lastUpdated <= maxAge || !info.completed) { - appsToRetain += (info.id -> info) - } else { - appsToClean += info + applications.values.foreach { app => + val (toClean, toRetain) = app.attempts.partition(shouldClean) + attemptsToClean ++= toClean + + if (toClean.isEmpty) { + appsToRetain += (app.id -> app) + } else if (toRetain.nonEmpty) { + appsToRetain += (app.id -> + new FsApplicationHistoryInfo(app.id, app.name, toRetain.toList)) } } applications = appsToRetain - val leftToClean = new mutable.ListBuffer[FsApplicationHistoryInfo] - appsToClean.foreach { info => + val leftToClean = new mutable.ListBuffer[FsApplicationAttemptInfo] + attemptsToClean.foreach { attempt => try { - val path = new Path(logDir, info.logPath) + val path = new Path(logDir, attempt.logPath) if (fs.exists(path)) { fs.delete(path, true) } } catch { case e: AccessControlException => - logInfo(s"No permission to delete ${info.logPath}, ignoring.") + logInfo(s"No permission to delete ${attempt.logPath}, ignoring.") case t: IOException => - logError(s"IOException in cleaning logs of ${info.logPath}", t) - leftToClean += info + logError(s"IOException in cleaning ${attempt.logPath}", t) + leftToClean += attempt } } - appsToClean = leftToClean + attemptsToClean = leftToClean } catch { case t: Exception => logError("Exception in cleaning logs", t) } @@ -315,14 +349,36 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis private def compareAppInfo( i1: FsApplicationHistoryInfo, i2: FsApplicationHistoryInfo): Boolean = { - if (i1.endTime != i2.endTime) i1.endTime >= i2.endTime else i1.startTime >= i2.startTime + val a1 = i1.attempts.head + val a2 = i2.attempts.head + if (a1.endTime != a2.endTime) a1.endTime >= a2.endTime else a1.startTime >= a2.startTime + } + + /** + * Comparison function that defines the sort order for application attempts within the same + * application. Order is: running attempts before complete attempts, running attempts sorted + * by start time, completed attempts sorted by end time. + * + * Normally applications should have a single running attempt; but failure to call sc.stop() + * may cause multiple running attempts to show up. + * + * @return Whether `a1` should precede `a2`. + */ + private def compareAttemptInfo( + a1: FsApplicationAttemptInfo, + a2: FsApplicationAttemptInfo): Boolean = { + if (a1.completed == a2.completed) { + if (a1.completed) a1.endTime >= a2.endTime else a1.startTime >= a2.startTime + } else { + !a1.completed + } } /** * Replays the events in the specified log file and returns information about the associated * application. */ - private def replay(eventLog: FileStatus, bus: ReplayListenerBus): FsApplicationHistoryInfo = { + private def replay(eventLog: FileStatus, bus: ReplayListenerBus): FsApplicationAttemptInfo = { val logPath = eventLog.getPath() logInfo(s"Replaying log path: $logPath") val logInput = @@ -336,10 +392,11 @@ private[history] class FsHistoryProvider(conf: SparkConf) extends ApplicationHis val appCompleted = isApplicationCompleted(eventLog) bus.addListener(appListener) bus.replay(logInput, logPath.toString, !appCompleted) - new FsApplicationHistoryInfo( + new FsApplicationAttemptInfo( logPath.getName(), - appListener.appId.getOrElse(logPath.getName()), appListener.appName.getOrElse(NOT_STARTED), + appListener.appId.getOrElse(logPath.getName()), + appListener.appAttemptId, appListener.startTime.getOrElse(-1L), appListener.endTime.getOrElse(-1L), getModificationTime(eventLog).get, @@ -425,13 +482,21 @@ private object FsHistoryProvider { val DEFAULT_LOG_DIR = "file:/tmp/spark-events" } -private class FsApplicationHistoryInfo( +private class FsApplicationAttemptInfo( val logPath: String, - id: String, - name: String, + val name: String, + val appId: String, + attemptId: Option[String], startTime: Long, endTime: Long, lastUpdated: Long, sparkUser: String, completed: Boolean = true) - extends ApplicationHistoryInfo(id, name, startTime, endTime, lastUpdated, sparkUser, completed) + extends ApplicationAttemptInfo( + attemptId, startTime, endTime, lastUpdated, sparkUser, completed) + +private class FsApplicationHistoryInfo( + id: String, + override val name: String, + override val attempts: List[FsApplicationAttemptInfo]) + extends ApplicationHistoryInfo(id, name, attempts) diff --git a/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala b/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala index 3781b4e8c12bd..0830cc1ba1245 100644 --- a/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala +++ b/core/src/main/scala/org/apache/spark/deploy/history/HistoryPage.scala @@ -34,18 +34,28 @@ private[history] class HistoryPage(parent: HistoryServer) extends WebUIPage("") val requestedIncomplete = Option(request.getParameter("showIncomplete")).getOrElse("false").toBoolean - val allApps = parent.getApplicationList().filter(_.completed != requestedIncomplete) - val actualFirst = if (requestedFirst < allApps.size) requestedFirst else 0 - val apps = allApps.slice(actualFirst, Math.min(actualFirst + pageSize, allApps.size)) + val allApps = parent.getApplicationList() + .filter(_.attempts.head.completed != requestedIncomplete) + val allAppsSize = allApps.size + + val actualFirst = if (requestedFirst < allAppsSize) requestedFirst else 0 + val appsToShow = allApps.slice(actualFirst, actualFirst + pageSize) val actualPage = (actualFirst / pageSize) + 1 - val last = Math.min(actualFirst + pageSize, allApps.size) - 1 - val pageCount = allApps.size / pageSize + (if (allApps.size % pageSize > 0) 1 else 0) + val last = Math.min(actualFirst + pageSize, allAppsSize) - 1 + val pageCount = allAppsSize / pageSize + (if (allAppsSize % pageSize > 0) 1 else 0) val secondPageFromLeft = 2 val secondPageFromRight = pageCount - 1 - val appTable = UIUtils.listingTable(appHeader, appRow, apps) + val hasMultipleAttempts = appsToShow.exists(_.attempts.size > 1) + val appTable = + if (hasMultipleAttempts) { + UIUtils.listingTable(appWithAttemptHeader, appWithAttemptRow, appsToShow) + } else { + UIUtils.listingTable(appHeader, appRow, appsToShow) + } + val providerConfig = parent.getProviderConfig() val content =
@@ -59,7 +69,7 @@ private[history] class HistoryPage(parent: HistoryServer) extends WebUIPage("") // to the first and last page. If the current page +/- `plusOrMinus` is greater // than the 2nd page from the first page or less than the 2nd page from the last // page, `...` will be displayed. - if (allApps.size > 0) { + if (allAppsSize > 0) { val leftSideIndices = rangeIndices(actualPage - plusOrMinus until actualPage, 1 < _, requestedIncomplete) val rightSideIndices = @@ -67,7 +77,7 @@ private[history] class HistoryPage(parent: HistoryServer) extends WebUIPage("") requestedIncomplete)

- Showing {actualFirst + 1}-{last + 1} of {allApps.size} + Showing {actualFirst + 1}-{last + 1} of {allAppsSize} {if (requestedIncomplete) "(Incomplete applications)"} { @@ -125,30 +135,85 @@ private[history] class HistoryPage(parent: HistoryServer) extends WebUIPage("") "Spark User", "Last Updated") - private def rangeIndices(range: Seq[Int], condition: Int => Boolean, showIncomplete: Boolean): - Seq[Node] = { + private val appWithAttemptHeader = Seq( + "App ID", + "App Name", + "Attempt ID", + "Started", + "Completed", + "Duration", + "Spark User", + "Last Updated") + + private def rangeIndices( + range: Seq[Int], + condition: Int => Boolean, + showIncomplete: Boolean): Seq[Node] = { range.filter(condition).map(nextPage => {nextPage} ) } - private def appRow(info: ApplicationHistoryInfo): Seq[Node] = { - val uiAddress = HistoryServer.UI_PATH_PREFIX + s"/${info.id}" - val startTime = UIUtils.formatDate(info.startTime) - val endTime = if (info.endTime > 0) UIUtils.formatDate(info.endTime) else "-" + private def attemptRow( + renderAttemptIdColumn: Boolean, + info: ApplicationHistoryInfo, + attempt: ApplicationAttemptInfo, + isFirst: Boolean): Seq[Node] = { + val uiAddress = HistoryServer.getAttemptURI(info.id, attempt.attemptId) + val startTime = UIUtils.formatDate(attempt.startTime) + val endTime = if (attempt.endTime > 0) UIUtils.formatDate(attempt.endTime) else "-" val duration = - if (info.endTime > 0) UIUtils.formatDuration(info.endTime - info.startTime) else "-" - val lastUpdated = UIUtils.formatDate(info.lastUpdated) + if (attempt.endTime > 0) { + UIUtils.formatDuration(attempt.endTime - attempt.startTime) + } else { + "-" + } + val lastUpdated = UIUtils.formatDate(attempt.lastUpdated) - {info.id} - {info.name} - {startTime} - {endTime} - {duration} - {info.sparkUser} - {lastUpdated} + { + if (isFirst) { + if (info.attempts.size > 1 || renderAttemptIdColumn) { + + {info.id} + + {info.name} + } else { + {info.id} + {info.name} + } + } else { + Nil + } + } + { + if (renderAttemptIdColumn) { + if (info.attempts.size > 1 && attempt.attemptId.isDefined) { + + {attempt.attemptId.get} + } else { +   + } + } else { + Nil + } + } + {startTime} + {endTime} + + {duration} + {attempt.sparkUser} + {lastUpdated} } + private def appRow(info: ApplicationHistoryInfo): Seq[Node] = { + attemptRow(false, info, info.attempts.head, true) + } + + private def appWithAttemptRow(info: ApplicationHistoryInfo): Seq[Node] = { + attemptRow(true, info, info.attempts.head, true) ++ + info.attempts.drop(1).flatMap(attemptRow(true, info, _, false)) + } + private def makePageLink(linkPage: Int, showIncomplete: Boolean): String = { "/?" + Array( "page=" + linkPage, diff --git a/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala b/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala index 56bef57e55392..754c8e9b6668b 100644 --- a/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala +++ b/core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala @@ -52,7 +52,11 @@ class HistoryServer( private val appLoader = new CacheLoader[String, SparkUI] { override def load(key: String): SparkUI = { - val ui = provider.getAppUI(key).getOrElse(throw new NoSuchElementException()) + val parts = key.split("/") + require(parts.length == 1 || parts.length == 2, s"Invalid app key $key") + val ui = provider + .getAppUI(parts(0), if (parts.length > 1) Some(parts(1)) else None) + .getOrElse(throw new NoSuchElementException()) attachSparkUI(ui) ui } @@ -69,6 +73,8 @@ class HistoryServer( private val loaderServlet = new HttpServlet { protected override def doGet(req: HttpServletRequest, res: HttpServletResponse): Unit = { + // Parse the URI created by getAttemptURI(). It contains an app ID and an optional + // attempt ID (separated by a slash). val parts = Option(req.getPathInfo()).getOrElse("").split("/") if (parts.length < 2) { res.sendError(HttpServletResponse.SC_BAD_REQUEST, @@ -76,18 +82,23 @@ class HistoryServer( return } - val appId = parts(1) + val appKey = + if (parts.length == 3) { + s"${parts(1)}/${parts(2)}" + } else { + parts(1) + } // Note we don't use the UI retrieved from the cache; the cache loader above will register // the app's UI, and all we need to do is redirect the user to the same URI that was // requested, and the proper data should be served at that point. try { - appCache.get(appId) + appCache.get(appKey) res.sendRedirect(res.encodeRedirectURL(req.getRequestURI())) } catch { case e: Exception => e.getCause() match { case nsee: NoSuchElementException => - val msg =
Application {appId} not found.
+ val msg =
Application {appKey} not found.
res.setStatus(HttpServletResponse.SC_NOT_FOUND) UIUtils.basicSparkPage(msg, "Not Found").foreach( n => res.getWriter().write(n.toString)) @@ -213,4 +224,9 @@ object HistoryServer extends Logging { } } + private[history] def getAttemptURI(appId: String, attemptId: Option[String]): String = { + val attemptSuffix = attemptId.map { id => s"/$id" }.getOrElse("") + s"${HistoryServer.UI_PATH_PREFIX}/${appId}${attemptSuffix}" + } + } diff --git a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala index 1c21c179562ac..0fac3cdcf55e7 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/Master.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/Master.scala @@ -62,7 +62,7 @@ private[master] class Master( private val hadoopConf = SparkHadoopUtil.get.newConfiguration(conf) private def createDateFormat = new SimpleDateFormat("yyyyMMddHHmmss") // For application IDs - + private val WORKER_TIMEOUT = conf.getLong("spark.worker.timeout", 60) * 1000 private val RETAINED_APPLICATIONS = conf.getInt("spark.deploy.retainedApplications", 200) private val RETAINED_DRIVERS = conf.getInt("spark.deploy.retainedDrivers", 200) @@ -86,7 +86,7 @@ private[master] class Master( private val drivers = new HashSet[DriverInfo] private val completedDrivers = new ArrayBuffer[DriverInfo] // Drivers currently spooled for scheduling - private val waitingDrivers = new ArrayBuffer[DriverInfo] + private val waitingDrivers = new ArrayBuffer[DriverInfo] private var nextDriverNumber = 0 Utils.checkHost(host, "Expected hostname") @@ -254,7 +254,8 @@ private[master] class Master( case RequestSubmitDriver(description) => { if (state != RecoveryState.ALIVE) { - val msg = s"Can only accept driver submissions in ALIVE state. Current state: $state." + val msg = s"${Utils.BACKUP_STANDALONE_MASTER_PREFIX}: $state. " + + "Can only accept driver submissions in ALIVE state." sender ! SubmitDriverResponse(false, None, msg) } else { logInfo("Driver submitted " + description.command.mainClass) @@ -274,7 +275,8 @@ private[master] class Master( case RequestKillDriver(driverId) => { if (state != RecoveryState.ALIVE) { - val msg = s"Can only kill drivers in ALIVE state. Current state: $state." + val msg = s"${Utils.BACKUP_STANDALONE_MASTER_PREFIX}: $state. " + + s"Can only kill drivers in ALIVE state." sender ! KillDriverResponse(driverId, success = false, msg) } else { logInfo("Asked to kill driver " + driverId) @@ -305,12 +307,18 @@ private[master] class Master( } case RequestDriverStatus(driverId) => { - (drivers ++ completedDrivers).find(_.id == driverId) match { - case Some(driver) => - sender ! DriverStatusResponse(found = true, Some(driver.state), - driver.worker.map(_.id), driver.worker.map(_.hostPort), driver.exception) - case None => - sender ! DriverStatusResponse(found = false, None, None, None, None) + if (state != RecoveryState.ALIVE) { + val msg = s"${Utils.BACKUP_STANDALONE_MASTER_PREFIX}: $state. " + + "Can only request driver status in ALIVE state." + sender ! DriverStatusResponse(found = false, None, None, None, Some(new Exception(msg))) + } else { + (drivers ++ completedDrivers).find(_.id == driverId) match { + case Some(driver) => + sender ! DriverStatusResponse(found = true, Some(driver.state), + driver.worker.map(_.id), driver.worker.map(_.hostPort), driver.exception) + case None => + sender ! DriverStatusResponse(found = false, None, None, None, None) + } } } @@ -758,24 +766,24 @@ private[master] class Master( app.desc.appUiUrl = notFoundBasePath return false } - + val eventLogFilePrefix = EventLoggingListener.getLogPath( - eventLogDir, app.id, app.desc.eventLogCodec) + eventLogDir, app.id, None, app.desc.eventLogCodec) val fs = Utils.getHadoopFileSystem(eventLogDir, hadoopConf) - val inProgressExists = fs.exists(new Path(eventLogFilePrefix + + val inProgressExists = fs.exists(new Path(eventLogFilePrefix + EventLoggingListener.IN_PROGRESS)) - + if (inProgressExists) { // Event logging is enabled for this application, but the application is still in progress logWarning(s"Application $appName is still in progress, it may be terminated abnormally.") } - + val (eventLogFile, status) = if (inProgressExists) { (eventLogFilePrefix + EventLoggingListener.IN_PROGRESS, " (in progress)") } else { (eventLogFilePrefix, " (completed)") } - + val logInput = EventLoggingListener.openEventLog(new Path(eventLogFile), fs) val replayBus = new ReplayListenerBus() val ui = SparkUI.createHistoryUI(new SparkConf, replayBus, new SecurityManager(conf), @@ -859,8 +867,8 @@ private[master] class Master( } private def removeDriver( - driverId: String, - finalState: DriverState, + driverId: String, + finalState: DriverState, exception: Option[Exception]) { drivers.find(d => d.id == driverId) match { case Some(driver) => diff --git a/core/src/main/scala/org/apache/spark/deploy/master/PersistenceEngine.scala b/core/src/main/scala/org/apache/spark/deploy/master/PersistenceEngine.scala index da5060778edeb..a03d460509e03 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/PersistenceEngine.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/PersistenceEngine.scala @@ -33,7 +33,7 @@ import scala.reflect.ClassTag * The implementation of this trait defines how name-object pairs are stored or retrieved. */ @DeveloperApi -trait PersistenceEngine { +abstract class PersistenceEngine { /** * Defines how the object is serialized and persisted. Implementation will diff --git a/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala b/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala index aad9c87bdb987..dea0a65eeeaa6 100644 --- a/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala +++ b/core/src/main/scala/org/apache/spark/deploy/master/ui/MasterWebUI.scala @@ -44,9 +44,9 @@ class MasterWebUI(val master: Master, requestedPort: Int) attachPage(masterPage) attachHandler(createStaticHandler(MasterWebUI.STATIC_RESOURCE_DIR, "/static")) attachHandler(createRedirectHandler( - "/app/kill", "/", masterPage.handleAppKillRequest, httpMethod = "POST")) + "/app/kill", "/", masterPage.handleAppKillRequest, httpMethods = Set("POST"))) attachHandler(createRedirectHandler( - "/driver/kill", "/", masterPage.handleDriverKillRequest, httpMethod = "POST")) + "/driver/kill", "/", masterPage.handleDriverKillRequest, httpMethods = Set("POST"))) } /** Attach a reconstructed UI to this Master UI. Only valid after bind(). */ diff --git a/core/src/main/scala/org/apache/spark/deploy/mesos/ui/DriverPage.scala b/core/src/main/scala/org/apache/spark/deploy/mesos/ui/DriverPage.scala new file mode 100644 index 0000000000000..be8560d10fc62 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/mesos/ui/DriverPage.scala @@ -0,0 +1,180 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.deploy.mesos.ui + +import javax.servlet.http.HttpServletRequest + +import scala.xml.Node + +import org.apache.spark.deploy.Command +import org.apache.spark.deploy.mesos.MesosDriverDescription +import org.apache.spark.scheduler.cluster.mesos.{MesosClusterSubmissionState, MesosClusterRetryState} +import org.apache.spark.ui.{UIUtils, WebUIPage} + + +private[ui] class DriverPage(parent: MesosClusterUI) extends WebUIPage("driver") { + + override def render(request: HttpServletRequest): Seq[Node] = { + val driverId = request.getParameter("id") + require(driverId != null && driverId.nonEmpty, "Missing id parameter") + + val state = parent.scheduler.getDriverState(driverId) + if (state.isEmpty) { + val content = +
+

Cannot find driver {driverId}

+
+ return UIUtils.basicSparkPage(content, s"Details for Job $driverId") + } + val driverState = state.get + val driverHeaders = Seq("Driver property", "Value") + val schedulerHeaders = Seq("Scheduler property", "Value") + val commandEnvHeaders = Seq("Command environment variable", "Value") + val launchedHeaders = Seq("Launched property", "Value") + val commandHeaders = Seq("Comamnd property", "Value") + val retryHeaders = Seq("Last failed status", "Next retry time", "Retry count") + val driverDescription = Iterable.apply(driverState.description) + val submissionState = Iterable.apply(driverState.submissionState) + val command = Iterable.apply(driverState.description.command) + val schedulerProperties = Iterable.apply(driverState.description.schedulerProperties) + val commandEnv = Iterable.apply(driverState.description.command.environment) + val driverTable = + UIUtils.listingTable(driverHeaders, driverRow, driverDescription) + val commandTable = + UIUtils.listingTable(commandHeaders, commandRow, command) + val commandEnvTable = + UIUtils.listingTable(commandEnvHeaders, propertiesRow, commandEnv) + val schedulerTable = + UIUtils.listingTable(schedulerHeaders, propertiesRow, schedulerProperties) + val launchedTable = + UIUtils.listingTable(launchedHeaders, launchedRow, submissionState) + val retryTable = + UIUtils.listingTable( + retryHeaders, retryRow, Iterable.apply(driverState.description.retryState)) + val content = +

Driver state information for driver id {driverId}

+ Back to Drivers +
+
+

Driver state: {driverState.state}

+

Driver properties

+ {driverTable} +

Driver command

+ {commandTable} +

Driver command environment

+ {commandEnvTable} +

Scheduler properties

+ {schedulerTable} +

Launched state

+ {launchedTable} +

Retry state

+ {retryTable} +
+
; + + UIUtils.basicSparkPage(content, s"Details for Job $driverId") + } + + private def launchedRow(submissionState: Option[MesosClusterSubmissionState]): Seq[Node] = { + submissionState.map { state => + + Mesos Slave ID + {state.slaveId.getValue} + + + Mesos Task ID + {state.taskId.getValue} + + + Launch Time + {state.startDate} + + + Finish Time + {state.finishDate.map(_.toString).getOrElse("")} + + + Last Task Status + {state.mesosTaskStatus.map(_.toString).getOrElse("")} + + }.getOrElse(Seq[Node]()) + } + + private def propertiesRow(properties: collection.Map[String, String]): Seq[Node] = { + properties.map { case (k, v) => + + {k}{v} + + }.toSeq + } + + private def commandRow(command: Command): Seq[Node] = { + + Main class{command.mainClass} + + + Arguments{command.arguments.mkString(" ")} + + + Class path entries{command.classPathEntries.mkString(" ")} + + + Java options{command.javaOpts.mkString((" "))} + + + Library path entries{command.libraryPathEntries.mkString((" "))} + + } + + private def driverRow(driver: MesosDriverDescription): Seq[Node] = { + + Name{driver.name} + + + Id{driver.submissionId} + + + Cores{driver.cores} + + + Memory{driver.mem} + + + Submitted{driver.submissionDate} + + + Supervise{driver.supervise} + + } + + private def retryRow(retryState: Option[MesosClusterRetryState]): Seq[Node] = { + retryState.map { state => + + + {state.lastFailureStatus} + + + {state.nextRetry} + + + {state.retries} + + + }.getOrElse(Seq[Node]()) + } +} diff --git a/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterPage.scala b/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterPage.scala index 7b2005e0f1237..7419fa9699648 100644 --- a/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterPage.scala +++ b/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterPage.scala @@ -56,8 +56,9 @@ private[mesos] class MesosClusterPage(parent: MesosClusterUI) extends WebUIPage( } private def queuedRow(submission: MesosDriverDescription): Seq[Node] = { + val id = submission.submissionId - {submission.submissionId} + {id} {submission.submissionDate} {submission.command.mainClass} cpus: {submission.cores}, mem: {submission.mem} @@ -65,8 +66,9 @@ private[mesos] class MesosClusterPage(parent: MesosClusterUI) extends WebUIPage( } private def driverRow(state: MesosClusterSubmissionState): Seq[Node] = { + val id = state.driverDescription.submissionId - {state.driverDescription.submissionId} + {id} {state.driverDescription.submissionDate} {state.driverDescription.command.mainClass} cpus: {state.driverDescription.cores}, mem: {state.driverDescription.mem} @@ -77,8 +79,9 @@ private[mesos] class MesosClusterPage(parent: MesosClusterUI) extends WebUIPage( } private def retryRow(submission: MesosDriverDescription): Seq[Node] = { + val id = submission.submissionId - {submission.submissionId} + {id} {submission.submissionDate} {submission.command.mainClass} {submission.retryState.get.lastFailureStatus} diff --git a/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterUI.scala b/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterUI.scala index 4865d46dbc4ab..3f693545a0349 100644 --- a/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterUI.scala +++ b/core/src/main/scala/org/apache/spark/deploy/mesos/ui/MesosClusterUI.scala @@ -39,6 +39,7 @@ private[spark] class MesosClusterUI( override def initialize() { attachPage(new MesosClusterPage(this)) + attachPage(new DriverPage(this)) attachHandler(createStaticHandler(MesosClusterUI.STATIC_RESOURCE_DIR, "/static")) } } diff --git a/core/src/main/scala/org/apache/spark/deploy/rest/RestSubmissionClient.scala b/core/src/main/scala/org/apache/spark/deploy/rest/RestSubmissionClient.scala index 307cebfb4bd09..6078f50518ba4 100644 --- a/core/src/main/scala/org/apache/spark/deploy/rest/RestSubmissionClient.scala +++ b/core/src/main/scala/org/apache/spark/deploy/rest/RestSubmissionClient.scala @@ -18,9 +18,10 @@ package org.apache.spark.deploy.rest import java.io.{DataOutputStream, FileNotFoundException} -import java.net.{HttpURLConnection, SocketException, URL} +import java.net.{ConnectException, HttpURLConnection, SocketException, URL} import javax.servlet.http.HttpServletResponse +import scala.collection.mutable import scala.io.Source import com.fasterxml.jackson.core.JsonProcessingException @@ -51,57 +52,109 @@ import org.apache.spark.util.Utils * implementation of this client can use that information to retry using the version specified * by the server. */ -private[spark] class RestSubmissionClient extends Logging { +private[spark] class RestSubmissionClient(master: String) extends Logging { import RestSubmissionClient._ private val supportedMasterPrefixes = Seq("spark://", "mesos://") + private val masters: Array[String] = Utils.parseStandaloneMasterUrls(master) + + // Set of masters that lost contact with us, used to keep track of + // whether there are masters still alive for us to communicate with + private val lostMasters = new mutable.HashSet[String] + /** * Submit an application specified by the parameters in the provided request. * * If the submission was successful, poll the status of the submission and report * it to the user. Otherwise, report the error message provided by the server. */ - def createSubmission( - master: String, - request: CreateSubmissionRequest): SubmitRestProtocolResponse = { + def createSubmission(request: CreateSubmissionRequest): SubmitRestProtocolResponse = { logInfo(s"Submitting a request to launch an application in $master.") - validateMaster(master) - val url = getSubmitUrl(master) - val response = postJson(url, request.toJson) - response match { - case s: CreateSubmissionResponse => - reportSubmissionStatus(master, s) - handleRestResponse(s) - case unexpected => - handleUnexpectedRestResponse(unexpected) + var handled: Boolean = false + var response: SubmitRestProtocolResponse = null + for (m <- masters if !handled) { + validateMaster(m) + val url = getSubmitUrl(m) + try { + response = postJson(url, request.toJson) + response match { + case s: CreateSubmissionResponse => + if (s.success) { + reportSubmissionStatus(s) + handleRestResponse(s) + handled = true + } + case unexpected => + handleUnexpectedRestResponse(unexpected) + } + } catch { + case e: SubmitRestConnectionException => + if (handleConnectionException(m)) { + throw new SubmitRestConnectionException("Unable to connect to server", e) + } + } } response } /** Request that the server kill the specified submission. */ - def killSubmission(master: String, submissionId: String): SubmitRestProtocolResponse = { + def killSubmission(submissionId: String): SubmitRestProtocolResponse = { logInfo(s"Submitting a request to kill submission $submissionId in $master.") - validateMaster(master) - val response = post(getKillUrl(master, submissionId)) - response match { - case k: KillSubmissionResponse => handleRestResponse(k) - case unexpected => handleUnexpectedRestResponse(unexpected) + var handled: Boolean = false + var response: SubmitRestProtocolResponse = null + for (m <- masters if !handled) { + validateMaster(m) + val url = getKillUrl(m, submissionId) + try { + response = post(url) + response match { + case k: KillSubmissionResponse => + if (!Utils.responseFromBackup(k.message)) { + handleRestResponse(k) + handled = true + } + case unexpected => + handleUnexpectedRestResponse(unexpected) + } + } catch { + case e: SubmitRestConnectionException => + if (handleConnectionException(m)) { + throw new SubmitRestConnectionException("Unable to connect to server", e) + } + } } response } /** Request the status of a submission from the server. */ def requestSubmissionStatus( - master: String, submissionId: String, quiet: Boolean = false): SubmitRestProtocolResponse = { logInfo(s"Submitting a request for the status of submission $submissionId in $master.") - validateMaster(master) - val response = get(getStatusUrl(master, submissionId)) - response match { - case s: SubmissionStatusResponse => if (!quiet) { handleRestResponse(s) } - case unexpected => handleUnexpectedRestResponse(unexpected) + + var handled: Boolean = false + var response: SubmitRestProtocolResponse = null + for (m <- masters if !handled) { + validateMaster(m) + val url = getStatusUrl(m, submissionId) + try { + response = get(url) + response match { + case s: SubmissionStatusResponse if s.success => + if (!quiet) { + handleRestResponse(s) + } + handled = true + case unexpected => + handleUnexpectedRestResponse(unexpected) + } + } catch { + case e: SubmitRestConnectionException => + if (handleConnectionException(m)) { + throw new SubmitRestConnectionException("Unable to connect to server", e) + } + } } response } @@ -148,11 +201,16 @@ private[spark] class RestSubmissionClient extends Logging { conn.setRequestProperty("Content-Type", "application/json") conn.setRequestProperty("charset", "utf-8") conn.setDoOutput(true) - val out = new DataOutputStream(conn.getOutputStream) - Utils.tryWithSafeFinally { - out.write(json.getBytes(Charsets.UTF_8)) - } { - out.close() + try { + val out = new DataOutputStream(conn.getOutputStream) + Utils.tryWithSafeFinally { + out.write(json.getBytes(Charsets.UTF_8)) + } { + out.close() + } + } catch { + case e: ConnectException => + throw new SubmitRestConnectionException("Connect Exception when connect to server", e) } readResponse(conn) } @@ -191,11 +249,9 @@ private[spark] class RestSubmissionClient extends Logging { } } catch { case unreachable @ (_: FileNotFoundException | _: SocketException) => - throw new SubmitRestConnectionException( - s"Unable to connect to server ${connection.getURL}", unreachable) + throw new SubmitRestConnectionException("Unable to connect to server", unreachable) case malformed @ (_: JsonProcessingException | _: SubmitRestProtocolException) => - throw new SubmitRestProtocolException( - "Malformed response received from server", malformed) + throw new SubmitRestProtocolException("Malformed response received from server", malformed) } } @@ -241,13 +297,12 @@ private[spark] class RestSubmissionClient extends Logging { /** Report the status of a newly created submission. */ private def reportSubmissionStatus( - master: String, submitResponse: CreateSubmissionResponse): Unit = { if (submitResponse.success) { val submissionId = submitResponse.submissionId if (submissionId != null) { logInfo(s"Submission successfully created as $submissionId. Polling submission state...") - pollSubmissionStatus(master, submissionId) + pollSubmissionStatus(submissionId) } else { // should never happen logError("Application successfully submitted, but submission ID was not provided!") @@ -262,9 +317,9 @@ private[spark] class RestSubmissionClient extends Logging { * Poll the status of the specified submission and log it. * This retries up to a fixed number of times before giving up. */ - private def pollSubmissionStatus(master: String, submissionId: String): Unit = { + private def pollSubmissionStatus(submissionId: String): Unit = { (1 to REPORT_DRIVER_STATUS_MAX_TRIES).foreach { _ => - val response = requestSubmissionStatus(master, submissionId, quiet = true) + val response = requestSubmissionStatus(submissionId, quiet = true) val statusResponse = response match { case s: SubmissionStatusResponse => s case _ => return // unexpected type, let upstream caller handle it @@ -302,6 +357,21 @@ private[spark] class RestSubmissionClient extends Logging { private def handleUnexpectedRestResponse(unexpected: SubmitRestProtocolResponse): Unit = { logError(s"Error: Server responded with message of unexpected type ${unexpected.messageType}.") } + + /** + * When a connection exception is caught, return true if all masters are lost. + * Note that the heuristic used here does not take into account that masters + * can recover during the lifetime of this client. This assumption should be + * harmless because this client currently does not support retrying submission + * on failure yet (SPARK-6443). + */ + private def handleConnectionException(masterUrl: String): Boolean = { + if (!lostMasters.contains(masterUrl)) { + logWarning(s"Unable to connect to server ${masterUrl}.") + lostMasters += masterUrl + } + lostMasters.size >= masters.size + } } private[spark] object RestSubmissionClient { @@ -324,10 +394,10 @@ private[spark] object RestSubmissionClient { } val sparkProperties = conf.getAll.toMap val environmentVariables = env.filter { case (k, _) => k.startsWith("SPARK_") } - val client = new RestSubmissionClient + val client = new RestSubmissionClient(master) val submitRequest = client.constructSubmitRequest( appResource, mainClass, appArgs, sparkProperties, environmentVariables) - client.createSubmission(master, submitRequest) + client.createSubmission(submitRequest) } def main(args: Array[String]): Unit = { diff --git a/core/src/main/scala/org/apache/spark/deploy/rest/mesos/MesosRestServer.scala b/core/src/main/scala/org/apache/spark/deploy/rest/mesos/MesosRestServer.scala index fd17a980c9319..8198296eeb341 100644 --- a/core/src/main/scala/org/apache/spark/deploy/rest/mesos/MesosRestServer.scala +++ b/core/src/main/scala/org/apache/spark/deploy/rest/mesos/MesosRestServer.scala @@ -53,7 +53,7 @@ private[spark] class MesosRestServer( new MesosStatusRequestServlet(scheduler, masterConf) } -private[deploy] class MesosSubmitRequestServlet( +private[mesos] class MesosSubmitRequestServlet( scheduler: MesosClusterScheduler, conf: SparkConf) extends SubmitRequestServlet { @@ -139,7 +139,7 @@ private[deploy] class MesosSubmitRequestServlet( } } -private[deploy] class MesosKillRequestServlet(scheduler: MesosClusterScheduler, conf: SparkConf) +private[mesos] class MesosKillRequestServlet(scheduler: MesosClusterScheduler, conf: SparkConf) extends KillRequestServlet { protected override def handleKill(submissionId: String): KillSubmissionResponse = { val k = scheduler.killDriver(submissionId) @@ -148,7 +148,7 @@ private[deploy] class MesosKillRequestServlet(scheduler: MesosClusterScheduler, } } -private[deploy] class MesosStatusRequestServlet(scheduler: MesosClusterScheduler, conf: SparkConf) +private[mesos] class MesosStatusRequestServlet(scheduler: MesosClusterScheduler, conf: SparkConf) extends StatusRequestServlet { protected override def handleStatus(submissionId: String): SubmissionStatusResponse = { val d = scheduler.getDriverStatus(submissionId) diff --git a/core/src/main/scala/org/apache/spark/deploy/worker/WorkerArguments.scala b/core/src/main/scala/org/apache/spark/deploy/worker/WorkerArguments.scala index 88f9d880ac209..9678631da9f6f 100644 --- a/core/src/main/scala/org/apache/spark/deploy/worker/WorkerArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/worker/WorkerArguments.scala @@ -105,7 +105,7 @@ private[worker] class WorkerArguments(args: Array[String], conf: SparkConf) { if (masters != null) { // Two positional arguments were given printUsageAndExit(1) } - masters = value.stripPrefix("spark://").split(",").map("spark://" + _) + masters = Utils.parseStandaloneMasterUrls(value) parse(tail) case Nil => diff --git a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala index 8af46f3327adb..ed159dec4f998 100644 --- a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala @@ -20,6 +20,8 @@ package org.apache.spark.executor import java.net.URL import java.nio.ByteBuffer +import org.apache.hadoop.conf.Configuration + import scala.collection.mutable import scala.util.{Failure, Success} @@ -57,7 +59,7 @@ private[spark] class CoarseGrainedExecutorBackend( logInfo("Connecting to driver: " + driverUrl) rpcEnv.asyncSetupEndpointRefByURI(driverUrl).flatMap { ref => driver = Some(ref) - ref.sendWithReply[RegisteredExecutor.type]( + ref.ask[RegisteredExecutor.type]( RegisterExecutor(executorId, self, hostPort, cores, extractLogUrls)) } onComplete { case Success(msg) => Utils.tryLogNonFatalError { @@ -154,7 +156,7 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { executorConf, new SecurityManager(executorConf)) val driver = fetcher.setupEndpointRefByURI(driverUrl) - val props = driver.askWithReply[Seq[(String, String)]](RetrieveSparkProps) ++ + val props = driver.askWithRetry[Seq[(String, String)]](RetrieveSparkProps) ++ Seq[(String, String)](("spark.app.id", appId)) fetcher.shutdown() @@ -168,6 +170,12 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { driverConf.set(key, value) } } + if (driverConf.contains("spark.yarn.credentials.file")) { + logInfo("Will periodically update credentials from: " + + driverConf.get("spark.yarn.credentials.file")) + SparkHadoopUtil.get.startExecutorDelegationTokenRenewer(driverConf) + } + val env = SparkEnv.createExecutorEnv( driverConf, executorId, hostname, port, cores, isLocal = false) @@ -183,6 +191,7 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { env.rpcEnv.setupEndpoint("WorkerWatcher", new WorkerWatcher(env.rpcEnv, url)) } env.rpcEnv.awaitTermination() + SparkHadoopUtil.get.stopExecutorDelegationTokenRenewer() } } diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala b/core/src/main/scala/org/apache/spark/executor/Executor.scala index f57e215c3f2ed..8f916e0502ecb 100644 --- a/core/src/main/scala/org/apache/spark/executor/Executor.scala +++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala @@ -32,6 +32,7 @@ import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.scheduler.{DirectTaskResult, IndirectTaskResult, Task} import org.apache.spark.shuffle.FetchFailedException import org.apache.spark.storage.{StorageLevel, TaskResultBlockId} +import org.apache.spark.unsafe.memory.TaskMemoryManager import org.apache.spark.util._ /** @@ -178,6 +179,7 @@ private[spark] class Executor( } override def run(): Unit = { + val taskMemoryManager = new TaskMemoryManager(env.executorMemoryManager) val deserializeStartTime = System.currentTimeMillis() Thread.currentThread.setContextClassLoader(replClassLoader) val ser = env.closureSerializer.newInstance() @@ -190,6 +192,7 @@ private[spark] class Executor( val (taskFiles, taskJars, taskBytes) = Task.deserializeWithDependencies(serializedTask) updateDependencies(taskFiles, taskJars) task = ser.deserialize[Task[Any]](taskBytes, Thread.currentThread.getContextClassLoader) + task.setTaskMemoryManager(taskMemoryManager) // If this task has been killed before we deserialized it, let's quit now. Otherwise, // continue executing the task. @@ -206,7 +209,21 @@ private[spark] class Executor( // Run the actual task and measure its runtime. taskStart = System.currentTimeMillis() - val value = task.run(taskAttemptId = taskId, attemptNumber = attemptNumber) + val value = try { + task.run(taskAttemptId = taskId, attemptNumber = attemptNumber) + } finally { + // Note: this memory freeing logic is duplicated in DAGScheduler.runLocallyWithinThread; + // when changing this, make sure to update both copies. + val freedMemory = taskMemoryManager.cleanUpAllAllocatedMemory() + if (freedMemory > 0) { + val errMsg = s"Managed memory leak detected; size = $freedMemory bytes, TID = $taskId" + if (conf.getBoolean("spark.unsafe.exceptionOnMemoryLeak", false)) { + throw new SparkException(errMsg) + } else { + logError(errMsg) + } + } + } val taskFinish = System.currentTimeMillis() // If the task has been killed, let's fail it. @@ -424,7 +441,7 @@ private[spark] class Executor( val message = Heartbeat(executorId, tasksMetrics.toArray, env.blockManager.blockManagerId) try { - val response = heartbeatReceiverRef.askWithReply[HeartbeatResponse](message) + val response = heartbeatReceiverRef.askWithRetry[HeartbeatResponse](message) if (response.reregisterBlockManager) { logWarning("Told to re-register on heartbeat") env.blockManager.reregister() diff --git a/core/src/main/scala/org/apache/spark/executor/ExecutorExitCode.scala b/core/src/main/scala/org/apache/spark/executor/ExecutorExitCode.scala index 52862ae0ca5e4..ea36fb60bd540 100644 --- a/core/src/main/scala/org/apache/spark/executor/ExecutorExitCode.scala +++ b/core/src/main/scala/org/apache/spark/executor/ExecutorExitCode.scala @@ -33,11 +33,11 @@ object ExecutorExitCode { /** DiskStore failed to create a local temporary directory after many attempts. */ val DISK_STORE_FAILED_TO_CREATE_DIR = 53 - /** TachyonStore failed to initialize after many attempts. */ - val TACHYON_STORE_FAILED_TO_INITIALIZE = 54 + /** ExternalBlockStore failed to initialize after many attempts. */ + val EXTERNAL_BLOCK_STORE_FAILED_TO_INITIALIZE = 54 - /** TachyonStore failed to create a local temporary directory after many attempts. */ - val TACHYON_STORE_FAILED_TO_CREATE_DIR = 55 + /** ExternalBlockStore failed to create a local temporary directory after many attempts. */ + val EXTERNAL_BLOCK_STORE_FAILED_TO_CREATE_DIR = 55 def explainExitCode(exitCode: Int): String = { exitCode match { @@ -46,9 +46,11 @@ object ExecutorExitCode { case OOM => "OutOfMemoryError" case DISK_STORE_FAILED_TO_CREATE_DIR => "Failed to create local directory (bad spark.local.dir?)" - case TACHYON_STORE_FAILED_TO_INITIALIZE => "TachyonStore failed to initialize." - case TACHYON_STORE_FAILED_TO_CREATE_DIR => - "TachyonStore failed to create a local temporary directory." + // TODO: replace external block store with concrete implementation name + case EXTERNAL_BLOCK_STORE_FAILED_TO_INITIALIZE => "ExternalBlockStore failed to initialize." + // TODO: replace external block store with concrete implementation name + case EXTERNAL_BLOCK_STORE_FAILED_TO_CREATE_DIR => + "ExternalBlockStore failed to create a local temporary directory." case _ => "Unknown executor exit code (" + exitCode + ")" + ( if (exitCode > 128) { diff --git a/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala b/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala index 3f0950dae1f24..6181c0ee9fa2b 100644 --- a/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala +++ b/core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala @@ -24,7 +24,7 @@ import org.apache.spark.{SecurityManager, SparkConf} import org.apache.spark.network._ import org.apache.spark.network.buffer.ManagedBuffer import org.apache.spark.network.client.{TransportClientBootstrap, RpcResponseCallback, TransportClientFactory} -import org.apache.spark.network.sasl.{SaslRpcHandler, SaslClientBootstrap} +import org.apache.spark.network.sasl.{SaslClientBootstrap, SaslServerBootstrap} import org.apache.spark.network.server._ import org.apache.spark.network.shuffle.{RetryingBlockFetcher, BlockFetchingListener, OneForOneBlockFetcher} import org.apache.spark.network.shuffle.protocol.UploadBlock @@ -49,18 +49,18 @@ class NettyBlockTransferService(conf: SparkConf, securityManager: SecurityManage private[this] var appId: String = _ override def init(blockDataManager: BlockDataManager): Unit = { - val (rpcHandler: RpcHandler, bootstrap: Option[TransportClientBootstrap]) = { - val nettyRpcHandler = new NettyBlockRpcServer(serializer, blockDataManager) - if (!authEnabled) { - (nettyRpcHandler, None) - } else { - (new SaslRpcHandler(nettyRpcHandler, securityManager), - Some(new SaslClientBootstrap(transportConf, conf.getAppId, securityManager))) - } + val rpcHandler = new NettyBlockRpcServer(serializer, blockDataManager) + var serverBootstrap: Option[TransportServerBootstrap] = None + var clientBootstrap: Option[TransportClientBootstrap] = None + if (authEnabled) { + serverBootstrap = Some(new SaslServerBootstrap(transportConf, securityManager)) + clientBootstrap = Some(new SaslClientBootstrap(transportConf, conf.getAppId, securityManager, + securityManager.isSaslEncryptionEnabled())) } transportContext = new TransportContext(transportConf, rpcHandler) - clientFactory = transportContext.createClientFactory(bootstrap.toList) - server = transportContext.createServer(conf.getInt("spark.blockManager.port", 0)) + clientFactory = transportContext.createClientFactory(clientBootstrap.toList) + server = transportContext.createServer(conf.getInt("spark.blockManager.port", 0), + serverBootstrap.toList) appId = conf.getAppId logInfo("Server created on " + server.getPort) } diff --git a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala index 16e905982cf64..497871ed6d5e5 100644 --- a/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala +++ b/core/src/main/scala/org/apache/spark/network/nio/ConnectionManager.scala @@ -656,7 +656,7 @@ private[nio] class ConnectionManager( connection.synchronized { if (connection.sparkSaslServer == null) { logDebug("Creating sasl Server") - connection.sparkSaslServer = new SparkSaslServer(conf.getAppId, securityManager) + connection.sparkSaslServer = new SparkSaslServer(conf.getAppId, securityManager, false) } } replyToken = connection.sparkSaslServer.response(securityMsg.getToken) @@ -800,7 +800,7 @@ private[nio] class ConnectionManager( if (!conn.isSaslComplete()) { conn.synchronized { if (conn.sparkSaslClient == null) { - conn.sparkSaslClient = new SparkSaslClient(conf.getAppId, securityManager) + conn.sparkSaslClient = new SparkSaslClient(conf.getAppId, securityManager, false) var firstResponse: Array[Byte] = null try { firstResponse = conn.sparkSaslClient.firstToken() diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index 95fc938420d62..dec6872233143 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -421,11 +421,26 @@ abstract class RDD[T: ClassTag]( val sum = weights.sum val normalizedCumWeights = weights.map(_ / sum).scanLeft(0.0d)(_ + _) normalizedCumWeights.sliding(2).map { x => - new PartitionwiseSampledRDD[T, T]( - this, new BernoulliCellSampler[T](x(0), x(1)), true, seed) + randomSampleWithRange(x(0), x(1), seed) }.toArray } + /** + * Internal method exposed for Random Splits in DataFrames. Samples an RDD given a probability + * range. + * @param lb lower bound to use for the Bernoulli sampler + * @param ub upper bound to use for the Bernoulli sampler + * @param seed the seed for the Random number generator + * @return A random sub-sample of the RDD without replacement. + */ + private[spark] def randomSampleWithRange(lb: Double, ub: Double, seed: Long): RDD[T] = { + this.mapPartitionsWithIndex { case (index, partition) => + val sampler = new BernoulliCellSampler[T](lb, ub) + sampler.setSeed(seed + index) + sampler.sample(partition) + } + } + /** * Return a fixed-size sampled subset of this RDD in an array * @@ -1526,9 +1541,9 @@ abstract class RDD[T: ClassTag]( val persistence = if (storageLevel != StorageLevel.NONE) storageLevel.description else "" val storageInfo = rdd.context.getRDDStorageInfo.filter(_.id == rdd.id).map(info => - " CachedPartitions: %d; MemorySize: %s; TachyonSize: %s; DiskSize: %s".format( + " CachedPartitions: %d; MemorySize: %s; ExternalBlockStoreSize: %s; DiskSize: %s".format( info.numCachedPartitions, bytesToString(info.memSize), - bytesToString(info.tachyonSize), bytesToString(info.diskSize))) + bytesToString(info.externalBlockStoreSize), bytesToString(info.diskSize))) s"$rdd [$persistence]" +: storageInfo } diff --git a/core/src/main/scala/org/apache/spark/rpc/RpcCallContext.scala b/core/src/main/scala/org/apache/spark/rpc/RpcCallContext.scala new file mode 100644 index 0000000000000..3e5b64265e919 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rpc/RpcCallContext.scala @@ -0,0 +1,41 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rpc + +/** + * A callback that [[RpcEndpoint]] can use it to send back a message or failure. It's thread-safe + * and can be called in any thread. + */ +private[spark] trait RpcCallContext { + + /** + * Reply a message to the sender. If the sender is [[RpcEndpoint]], its [[RpcEndpoint.receive]] + * will be called. + */ + def reply(response: Any): Unit + + /** + * Report a failure to the sender. + */ + def sendFailure(e: Throwable): Unit + + /** + * The sender of this message. + */ + def sender: RpcEndpointRef +} diff --git a/core/src/main/scala/org/apache/spark/rpc/RpcEndpoint.scala b/core/src/main/scala/org/apache/spark/rpc/RpcEndpoint.scala new file mode 100644 index 0000000000000..d2b2baef1d8c4 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rpc/RpcEndpoint.scala @@ -0,0 +1,148 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rpc + +import org.apache.spark.SparkException + +/** + * A factory class to create the [[RpcEnv]]. It must have an empty constructor so that it can be + * created using Reflection. + */ +private[spark] trait RpcEnvFactory { + + def create(config: RpcEnvConfig): RpcEnv +} + +/** + * A trait that requires RpcEnv thread-safely sending messages to it. + * + * Thread-safety means processing of one message happens before processing of the next message by + * the same [[ThreadSafeRpcEndpoint]]. In the other words, changes to internal fields of a + * [[ThreadSafeRpcEndpoint]] are visible when processing the next message, and fields in the + * [[ThreadSafeRpcEndpoint]] need not be volatile or equivalent. + * + * However, there is no guarantee that the same thread will be executing the same + * [[ThreadSafeRpcEndpoint]] for different messages. + */ +private[spark] trait ThreadSafeRpcEndpoint extends RpcEndpoint + + +/** + * An end point for the RPC that defines what functions to trigger given a message. + * + * It is guaranteed that `onStart`, `receive` and `onStop` will be called in sequence. + * + * The lift-cycle will be: + * + * constructor onStart receive* onStop + * + * Note: `receive` can be called concurrently. If you want `receive` is thread-safe, please use + * [[ThreadSafeRpcEndpoint]] + * + * If any error is thrown from one of [[RpcEndpoint]] methods except `onError`, `onError` will be + * invoked with the cause. If `onError` throws an error, [[RpcEnv]] will ignore it. + */ +private[spark] trait RpcEndpoint { + + /** + * The [[RpcEnv]] that this [[RpcEndpoint]] is registered to. + */ + val rpcEnv: RpcEnv + + /** + * The [[RpcEndpointRef]] of this [[RpcEndpoint]]. `self` will become valid when `onStart` is + * called. And `self` will become `null` when `onStop` is called. + * + * Note: Because before `onStart`, [[RpcEndpoint]] has not yet been registered and there is not + * valid [[RpcEndpointRef]] for it. So don't call `self` before `onStart` is called. + */ + final def self: RpcEndpointRef = { + require(rpcEnv != null, "rpcEnv has not been initialized") + rpcEnv.endpointRef(this) + } + + /** + * Process messages from [[RpcEndpointRef.send]] or [[RpcCallContext.reply)]]. If receiving a + * unmatched message, [[SparkException]] will be thrown and sent to `onError`. + */ + def receive: PartialFunction[Any, Unit] = { + case _ => throw new SparkException(self + " does not implement 'receive'") + } + + /** + * Process messages from [[RpcEndpointRef.ask]]. If receiving a unmatched message, + * [[SparkException]] will be thrown and sent to `onError`. + */ + def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = { + case _ => context.sendFailure(new SparkException(self + " won't reply anything")) + } + + /** + * Invoked when any exception is thrown during handling messages. + */ + def onError(cause: Throwable): Unit = { + // By default, throw e and let RpcEnv handle it + throw cause + } + + /** + * Invoked before [[RpcEndpoint]] starts to handle any message. + */ + def onStart(): Unit = { + // By default, do nothing. + } + + /** + * Invoked when [[RpcEndpoint]] is stopping. + */ + def onStop(): Unit = { + // By default, do nothing. + } + + /** + * Invoked when `remoteAddress` is connected to the current node. + */ + def onConnected(remoteAddress: RpcAddress): Unit = { + // By default, do nothing. + } + + /** + * Invoked when `remoteAddress` is lost. + */ + def onDisconnected(remoteAddress: RpcAddress): Unit = { + // By default, do nothing. + } + + /** + * Invoked when some network error happens in the connection between the current node and + * `remoteAddress`. + */ + def onNetworkError(cause: Throwable, remoteAddress: RpcAddress): Unit = { + // By default, do nothing. + } + + /** + * A convenient method to stop [[RpcEndpoint]]. + */ + final def stop(): Unit = { + val _self = self + if (_self != null) { + rpcEnv.stop(_self) + } + } +} diff --git a/core/src/main/scala/org/apache/spark/rpc/RpcEndpointRef.scala b/core/src/main/scala/org/apache/spark/rpc/RpcEndpointRef.scala new file mode 100644 index 0000000000000..69181edb9ad44 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/rpc/RpcEndpointRef.scala @@ -0,0 +1,119 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.rpc + +import scala.concurrent.{Await, Future} +import scala.concurrent.duration.FiniteDuration +import scala.reflect.ClassTag + +import org.apache.spark.util.RpcUtils +import org.apache.spark.{SparkException, Logging, SparkConf} + +/** + * A reference for a remote [[RpcEndpoint]]. [[RpcEndpointRef]] is thread-safe. + */ +private[spark] abstract class RpcEndpointRef(@transient conf: SparkConf) + extends Serializable with Logging { + + private[this] val maxRetries = RpcUtils.numRetries(conf) + private[this] val retryWaitMs = RpcUtils.retryWaitMs(conf) + private[this] val defaultAskTimeout = RpcUtils.askTimeout(conf) + + /** + * return the address for the [[RpcEndpointRef]] + */ + def address: RpcAddress + + def name: String + + /** + * Sends a one-way asynchronous message. Fire-and-forget semantics. + */ + def send(message: Any): Unit + + /** + * Send a message to the corresponding [[RpcEndpoint.receiveAndReply)]] and return a [[Future]] to + * receive the reply within the specified timeout. + * + * This method only sends the message once and never retries. + */ + def ask[T: ClassTag](message: Any, timeout: FiniteDuration): Future[T] + + /** + * Send a message to the corresponding [[RpcEndpoint.receiveAndReply)]] and return a [[Future]] to + * receive the reply within a default timeout. + * + * This method only sends the message once and never retries. + */ + def ask[T: ClassTag](message: Any): Future[T] = ask(message, defaultAskTimeout) + + /** + * Send a message to the corresponding [[RpcEndpoint]] and get its result within a default + * timeout, or throw a SparkException if this fails even after the default number of retries. + * The default `timeout` will be used in every trial of calling `sendWithReply`. Because this + * method retries, the message handling in the receiver side should be idempotent. + * + * Note: this is a blocking action which may cost a lot of time, so don't call it in an message + * loop of [[RpcEndpoint]]. + * + * @param message the message to send + * @tparam T type of the reply message + * @return the reply message from the corresponding [[RpcEndpoint]] + */ + def askWithRetry[T: ClassTag](message: Any): T = askWithRetry(message, defaultAskTimeout) + + /** + * Send a message to the corresponding [[RpcEndpoint.receive]] and get its result within a + * specified timeout, throw a SparkException if this fails even after the specified number of + * retries. `timeout` will be used in every trial of calling `sendWithReply`. Because this method + * retries, the message handling in the receiver side should be idempotent. + * + * Note: this is a blocking action which may cost a lot of time, so don't call it in an message + * loop of [[RpcEndpoint]]. + * + * @param message the message to send + * @param timeout the timeout duration + * @tparam T type of the reply message + * @return the reply message from the corresponding [[RpcEndpoint]] + */ + def askWithRetry[T: ClassTag](message: Any, timeout: FiniteDuration): T = { + // TODO: Consider removing multiple attempts + var attempts = 0 + var lastException: Exception = null + while (attempts < maxRetries) { + attempts += 1 + try { + val future = ask[T](message, timeout) + val result = Await.result(future, timeout) + if (result == null) { + throw new SparkException("Actor returned null") + } + return result + } catch { + case ie: InterruptedException => throw ie + case e: Exception => + lastException = e + logWarning(s"Error sending message [message = $message] in $attempts attempts", e) + } + Thread.sleep(retryWaitMs) + } + + throw new SparkException( + s"Error sending message [message = $message]", lastException) + } +} diff --git a/core/src/main/scala/org/apache/spark/rpc/RpcEnv.scala b/core/src/main/scala/org/apache/spark/rpc/RpcEnv.scala index a5336b7563802..12b6b28d4d7ec 100644 --- a/core/src/main/scala/org/apache/spark/rpc/RpcEnv.scala +++ b/core/src/main/scala/org/apache/spark/rpc/RpcEnv.scala @@ -20,13 +20,41 @@ package org.apache.spark.rpc import java.net.URI import scala.concurrent.{Await, Future} -import scala.concurrent.duration._ import scala.language.postfixOps -import scala.reflect.ClassTag -import org.apache.spark.{Logging, SparkException, SecurityManager, SparkConf} +import org.apache.spark.{SecurityManager, SparkConf} import org.apache.spark.util.{RpcUtils, Utils} + +/** + * A RpcEnv implementation must have a [[RpcEnvFactory]] implementation with an empty constructor + * so that it can be created via Reflection. + */ +private[spark] object RpcEnv { + + private def getRpcEnvFactory(conf: SparkConf): RpcEnvFactory = { + // Add more RpcEnv implementations here + val rpcEnvNames = Map("akka" -> "org.apache.spark.rpc.akka.AkkaRpcEnvFactory") + val rpcEnvName = conf.get("spark.rpc", "akka") + val rpcEnvFactoryClassName = rpcEnvNames.getOrElse(rpcEnvName.toLowerCase, rpcEnvName) + Class.forName(rpcEnvFactoryClassName, true, Utils.getContextOrSparkClassLoader). + newInstance().asInstanceOf[RpcEnvFactory] + } + + def create( + name: String, + host: String, + port: Int, + conf: SparkConf, + securityManager: SecurityManager): RpcEnv = { + // Using Reflection to create the RpcEnv to avoid to depend on Akka directly + val config = RpcEnvConfig(conf, name, host, port, securityManager) + getRpcEnvFactory(conf).create(config) + } + +} + + /** * An RPC environment. [[RpcEndpoint]]s need to register itself with a name to [[RpcEnv]] to * receives messages. Then [[RpcEnv]] will process messages sent from [[RpcEndpointRef]] or remote @@ -112,6 +140,7 @@ private[spark] abstract class RpcEnv(conf: SparkConf) { def uriOf(systemName: String, address: RpcAddress, endpointName: String): String } + private[spark] case class RpcEnvConfig( conf: SparkConf, name: String, @@ -119,261 +148,9 @@ private[spark] case class RpcEnvConfig( port: Int, securityManager: SecurityManager) -/** - * A RpcEnv implementation must have a [[RpcEnvFactory]] implementation with an empty constructor - * so that it can be created via Reflection. - */ -private[spark] object RpcEnv { - - private def getRpcEnvFactory(conf: SparkConf): RpcEnvFactory = { - // Add more RpcEnv implementations here - val rpcEnvNames = Map("akka" -> "org.apache.spark.rpc.akka.AkkaRpcEnvFactory") - val rpcEnvName = conf.get("spark.rpc", "akka") - val rpcEnvFactoryClassName = rpcEnvNames.getOrElse(rpcEnvName.toLowerCase, rpcEnvName) - Class.forName(rpcEnvFactoryClassName, true, Utils.getContextOrSparkClassLoader). - newInstance().asInstanceOf[RpcEnvFactory] - } - - def create( - name: String, - host: String, - port: Int, - conf: SparkConf, - securityManager: SecurityManager): RpcEnv = { - // Using Reflection to create the RpcEnv to avoid to depend on Akka directly - val config = RpcEnvConfig(conf, name, host, port, securityManager) - getRpcEnvFactory(conf).create(config) - } - -} - -/** - * A factory class to create the [[RpcEnv]]. It must have an empty constructor so that it can be - * created using Reflection. - */ -private[spark] trait RpcEnvFactory { - - def create(config: RpcEnvConfig): RpcEnv -} /** - * An end point for the RPC that defines what functions to trigger given a message. - * - * It is guaranteed that `onStart`, `receive` and `onStop` will be called in sequence. - * - * The lift-cycle will be: - * - * constructor onStart receive* onStop - * - * Note: `receive` can be called concurrently. If you want `receive` is thread-safe, please use - * [[ThreadSafeRpcEndpoint]] - * - * If any error is thrown from one of [[RpcEndpoint]] methods except `onError`, `onError` will be - * invoked with the cause. If `onError` throws an error, [[RpcEnv]] will ignore it. - */ -private[spark] trait RpcEndpoint { - - /** - * The [[RpcEnv]] that this [[RpcEndpoint]] is registered to. - */ - val rpcEnv: RpcEnv - - /** - * The [[RpcEndpointRef]] of this [[RpcEndpoint]]. `self` will become valid when `onStart` is - * called. And `self` will become `null` when `onStop` is called. - * - * Note: Because before `onStart`, [[RpcEndpoint]] has not yet been registered and there is not - * valid [[RpcEndpointRef]] for it. So don't call `self` before `onStart` is called. - */ - final def self: RpcEndpointRef = { - require(rpcEnv != null, "rpcEnv has not been initialized") - rpcEnv.endpointRef(this) - } - - /** - * Process messages from [[RpcEndpointRef.send]] or [[RpcCallContext.reply)]]. If receiving a - * unmatched message, [[SparkException]] will be thrown and sent to `onError`. - */ - def receive: PartialFunction[Any, Unit] = { - case _ => throw new SparkException(self + " does not implement 'receive'") - } - - /** - * Process messages from [[RpcEndpointRef.sendWithReply]]. If receiving a unmatched message, - * [[SparkException]] will be thrown and sent to `onError`. - */ - def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = { - case _ => context.sendFailure(new SparkException(self + " won't reply anything")) - } - - /** - * Call onError when any exception is thrown during handling messages. - * - * @param cause - */ - def onError(cause: Throwable): Unit = { - // By default, throw e and let RpcEnv handle it - throw cause - } - - /** - * Invoked before [[RpcEndpoint]] starts to handle any message. - */ - def onStart(): Unit = { - // By default, do nothing. - } - - /** - * Invoked when [[RpcEndpoint]] is stopping. - */ - def onStop(): Unit = { - // By default, do nothing. - } - - /** - * Invoked when `remoteAddress` is connected to the current node. - */ - def onConnected(remoteAddress: RpcAddress): Unit = { - // By default, do nothing. - } - - /** - * Invoked when `remoteAddress` is lost. - */ - def onDisconnected(remoteAddress: RpcAddress): Unit = { - // By default, do nothing. - } - - /** - * Invoked when some network error happens in the connection between the current node and - * `remoteAddress`. - */ - def onNetworkError(cause: Throwable, remoteAddress: RpcAddress): Unit = { - // By default, do nothing. - } - - /** - * A convenient method to stop [[RpcEndpoint]]. - */ - final def stop(): Unit = { - val _self = self - if (_self != null) { - rpcEnv.stop(_self) - } - } -} - -/** - * A trait that requires RpcEnv thread-safely sending messages to it. - * - * Thread-safety means processing of one message happens before processing of the next message by - * the same [[ThreadSafeRpcEndpoint]]. In the other words, changes to internal fields of a - * [[ThreadSafeRpcEndpoint]] are visible when processing the next message, and fields in the - * [[ThreadSafeRpcEndpoint]] need not be volatile or equivalent. - * - * However, there is no guarantee that the same thread will be executing the same - * [[ThreadSafeRpcEndpoint]] for different messages. - */ -trait ThreadSafeRpcEndpoint extends RpcEndpoint - -/** - * A reference for a remote [[RpcEndpoint]]. [[RpcEndpointRef]] is thread-safe. - */ -private[spark] abstract class RpcEndpointRef(@transient conf: SparkConf) - extends Serializable with Logging { - - private[this] val maxRetries = RpcUtils.numRetries(conf) - private[this] val retryWaitMs = RpcUtils.retryWaitMs(conf) - private[this] val defaultAskTimeout = RpcUtils.askTimeout(conf) - - /** - * return the address for the [[RpcEndpointRef]] - */ - def address: RpcAddress - - def name: String - - /** - * Sends a one-way asynchronous message. Fire-and-forget semantics. - */ - def send(message: Any): Unit - - /** - * Send a message to the corresponding [[RpcEndpoint.receiveAndReply)]] and return a `Future` to - * receive the reply within a default timeout. - * - * This method only sends the message once and never retries. - */ - def sendWithReply[T: ClassTag](message: Any): Future[T] = - sendWithReply(message, defaultAskTimeout) - - /** - * Send a message to the corresponding [[RpcEndpoint.receiveAndReply)]] and return a `Future` to - * receive the reply within the specified timeout. - * - * This method only sends the message once and never retries. - */ - def sendWithReply[T: ClassTag](message: Any, timeout: FiniteDuration): Future[T] - - /** - * Send a message to the corresponding [[RpcEndpoint]] and get its result within a default - * timeout, or throw a SparkException if this fails even after the default number of retries. - * The default `timeout` will be used in every trial of calling `sendWithReply`. Because this - * method retries, the message handling in the receiver side should be idempotent. - * - * Note: this is a blocking action which may cost a lot of time, so don't call it in an message - * loop of [[RpcEndpoint]]. - * - * @param message the message to send - * @tparam T type of the reply message - * @return the reply message from the corresponding [[RpcEndpoint]] - */ - def askWithReply[T: ClassTag](message: Any): T = askWithReply(message, defaultAskTimeout) - - /** - * Send a message to the corresponding [[RpcEndpoint.receive]] and get its result within a - * specified timeout, throw a SparkException if this fails even after the specified number of - * retries. `timeout` will be used in every trial of calling `sendWithReply`. Because this method - * retries, the message handling in the receiver side should be idempotent. - * - * Note: this is a blocking action which may cost a lot of time, so don't call it in an message - * loop of [[RpcEndpoint]]. - * - * @param message the message to send - * @param timeout the timeout duration - * @tparam T type of the reply message - * @return the reply message from the corresponding [[RpcEndpoint]] - */ - def askWithReply[T: ClassTag](message: Any, timeout: FiniteDuration): T = { - // TODO: Consider removing multiple attempts - var attempts = 0 - var lastException: Exception = null - while (attempts < maxRetries) { - attempts += 1 - try { - val future = sendWithReply[T](message, timeout) - val result = Await.result(future, timeout) - if (result == null) { - throw new SparkException("Actor returned null") - } - return result - } catch { - case ie: InterruptedException => throw ie - case e: Exception => - lastException = e - logWarning(s"Error sending message [message = $message] in $attempts attempts", e) - } - Thread.sleep(retryWaitMs) - } - - throw new SparkException( - s"Error sending message [message = $message]", lastException) - } - -} - -/** - * Represent a host with a port + * Represents a host and port. */ private[spark] case class RpcAddress(host: String, port: Int) { // TODO do we need to add the type of RpcEnv in the address? @@ -383,6 +160,7 @@ private[spark] case class RpcAddress(host: String, port: Int) { override val toString: String = hostPort } + private[spark] object RpcAddress { /** @@ -404,26 +182,3 @@ private[spark] object RpcAddress { RpcAddress(host, port) } } - -/** - * A callback that [[RpcEndpoint]] can use it to send back a message or failure. It's thread-safe - * and can be called in any thread. - */ -private[spark] trait RpcCallContext { - - /** - * Reply a message to the sender. If the sender is [[RpcEndpoint]], its [[RpcEndpoint.receive]] - * will be called. - */ - def reply(response: Any): Unit - - /** - * Report a failure to the sender. - */ - def sendFailure(e: Throwable): Unit - - /** - * The sender of this message. - */ - def sender: RpcEndpointRef -} diff --git a/core/src/main/scala/org/apache/spark/rpc/akka/AkkaRpcEnv.scala b/core/src/main/scala/org/apache/spark/rpc/akka/AkkaRpcEnv.scala index 652e52f2b2e73..ba0d468f111ef 100644 --- a/core/src/main/scala/org/apache/spark/rpc/akka/AkkaRpcEnv.scala +++ b/core/src/main/scala/org/apache/spark/rpc/akka/AkkaRpcEnv.scala @@ -293,7 +293,7 @@ private[akka] class AkkaRpcEndpointRef( actorRef ! AkkaMessage(message, false) } - override def sendWithReply[T: ClassTag](message: Any, timeout: FiniteDuration): Future[T] = { + override def ask[T: ClassTag](message: Any, timeout: FiniteDuration): Future[T] = { import scala.concurrent.ExecutionContext.Implicits.global actorRef.ask(AkkaMessage(message, true))(timeout).flatMap { case msg @ AkkaMessage(message, reply) => diff --git a/core/src/main/scala/org/apache/spark/scheduler/ApplicationEventListener.scala b/core/src/main/scala/org/apache/spark/scheduler/ApplicationEventListener.scala index 6d39a5e3fa64c..9f218c64cac2d 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/ApplicationEventListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/ApplicationEventListener.scala @@ -26,6 +26,7 @@ package org.apache.spark.scheduler private[spark] class ApplicationEventListener extends SparkListener { var appName: Option[String] = None var appId: Option[String] = None + var appAttemptId: Option[String] = None var sparkUser: Option[String] = None var startTime: Option[Long] = None var endTime: Option[Long] = None @@ -35,6 +36,7 @@ private[spark] class ApplicationEventListener extends SparkListener { override def onApplicationStart(applicationStart: SparkListenerApplicationStart) { appName = Some(applicationStart.appName) appId = applicationStart.appId + appAttemptId = applicationStart.appAttemptId startTime = Some(applicationStart.time) sparkUser = Some(applicationStart.sparkUser) } diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala index 8c4bff4e83afc..5d812918a13d1 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala @@ -28,12 +28,15 @@ import scala.language.existentials import scala.language.postfixOps import scala.util.control.NonFatal +import org.apache.commons.lang3.SerializationUtils + import org.apache.spark._ import org.apache.spark.broadcast.Broadcast import org.apache.spark.executor.TaskMetrics import org.apache.spark.partial.{ApproximateActionListener, ApproximateEvaluator, PartialResult} import org.apache.spark.rdd.RDD import org.apache.spark.storage._ +import org.apache.spark.unsafe.memory.TaskMemoryManager import org.apache.spark.util._ import org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat @@ -166,7 +169,7 @@ class DAGScheduler( taskMetrics: Array[(Long, Int, Int, TaskMetrics)], // (taskId, stageId, stateAttempt, metrics) blockManagerId: BlockManagerId): Boolean = { listenerBus.post(SparkListenerExecutorMetricsUpdate(execId, taskMetrics)) - blockManagerMaster.driverEndpoint.askWithReply[Boolean]( + blockManagerMaster.driverEndpoint.askWithRetry[Boolean]( BlockManagerHeartbeat(blockManagerId), 600 seconds) } @@ -509,7 +512,8 @@ class DAGScheduler( val func2 = func.asInstanceOf[(TaskContext, Iterator[_]) => _] val waiter = new JobWaiter(this, jobId, partitions.size, resultHandler) eventProcessLoop.post(JobSubmitted( - jobId, rdd, func2, partitions.toArray, allowLocal, callSite, waiter, properties)) + jobId, rdd, func2, partitions.toArray, allowLocal, callSite, waiter, + SerializationUtils.clone(properties))) waiter } @@ -546,7 +550,8 @@ class DAGScheduler( val partitions = (0 until rdd.partitions.size).toArray val jobId = nextJobId.getAndIncrement() eventProcessLoop.post(JobSubmitted( - jobId, rdd, func2, partitions, allowLocal = false, callSite, listener, properties)) + jobId, rdd, func2, partitions, allowLocal = false, callSite, listener, + SerializationUtils.clone(properties))) listener.awaitResult() // Will throw an exception if the job fails } @@ -643,8 +648,15 @@ class DAGScheduler( try { val rdd = job.finalStage.rdd val split = rdd.partitions(job.partitions(0)) - val taskContext = new TaskContextImpl(job.finalStage.id, job.partitions(0), taskAttemptId = 0, - attemptNumber = 0, runningLocally = true) + val taskMemoryManager = new TaskMemoryManager(env.executorMemoryManager) + val taskContext = + new TaskContextImpl( + job.finalStage.id, + job.partitions(0), + taskAttemptId = 0, + attemptNumber = 0, + taskMemoryManager = taskMemoryManager, + runningLocally = true) TaskContext.setTaskContext(taskContext) try { val result = job.func(taskContext, rdd.iterator(split, taskContext)) @@ -652,6 +664,16 @@ class DAGScheduler( } finally { taskContext.markTaskCompleted() TaskContext.unset() + // Note: this memory freeing logic is duplicated in Executor.run(); when changing this, + // make sure to update both copies. + val freedMemory = taskMemoryManager.cleanUpAllAllocatedMemory() + if (freedMemory > 0) { + if (sc.getConf.getBoolean("spark.unsafe.exceptionOnMemoryLeak", false)) { + throw new SparkException(s"Managed memory leak detected; size = $freedMemory bytes") + } else { + logError(s"Managed memory leak detected; size = $freedMemory bytes") + } + } } } catch { case e: Exception => @@ -686,8 +708,11 @@ class DAGScheduler( private[scheduler] def handleJobGroupCancelled(groupId: String) { // Cancel all jobs belonging to this job group. // First finds all active jobs with this group id, and then kill stages for them. - val activeInGroup = activeJobs.filter(activeJob => - Option(activeJob.properties).exists(_.get(SparkContext.SPARK_JOB_GROUP_ID) == groupId)) + val activeInGroup = activeJobs.filter { activeJob => + Option(activeJob.properties).exists { + _.getProperty(SparkContext.SPARK_JOB_GROUP_ID) == groupId + } + } val jobIds = activeInGroup.map(_.jobId) jobIds.foreach(handleJobCancellation(_, "part of cancelled job group %s".format(groupId))) submitWaitingStages() @@ -1374,6 +1399,7 @@ class DAGScheduler( def stop() { logInfo("Stopping DAGScheduler") + messageScheduler.shutdownNow() eventProcessLoop.stop() taskScheduler.stop() } diff --git a/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala b/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala index 08e7727db2fde..529a5b2bf1a0d 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/EventLoggingListener.scala @@ -47,6 +47,7 @@ import org.apache.spark.util.{JsonProtocol, Utils} */ private[spark] class EventLoggingListener( appId: String, + appAttemptId : Option[String], logBaseDir: URI, sparkConf: SparkConf, hadoopConf: Configuration) @@ -54,8 +55,9 @@ private[spark] class EventLoggingListener( import EventLoggingListener._ - def this(appId: String, logBaseDir: URI, sparkConf: SparkConf) = - this(appId, logBaseDir, sparkConf, SparkHadoopUtil.get.newConfiguration(sparkConf)) + def this(appId: String, appAttemptId : Option[String], logBaseDir: URI, sparkConf: SparkConf) = + this(appId, appAttemptId, logBaseDir, sparkConf, + SparkHadoopUtil.get.newConfiguration(sparkConf)) private val shouldCompress = sparkConf.getBoolean("spark.eventLog.compress", false) private val shouldOverwrite = sparkConf.getBoolean("spark.eventLog.overwrite", false) @@ -89,7 +91,7 @@ private[spark] class EventLoggingListener( private[scheduler] val loggedEvents = new ArrayBuffer[JValue] // Visible for tests only. - private[scheduler] val logPath = getLogPath(logBaseDir, appId, compressionCodecName) + private[scheduler] val logPath = getLogPath(logBaseDir, appId, appAttemptId, compressionCodecName) /** * Creates the log file in the configured log directory. @@ -252,8 +254,12 @@ private[spark] object EventLoggingListener extends Logging { * we won't know which codec to use to decompress the metadata needed to open the file in * the first place. * + * The log file name will identify the compression codec used for the contents, if any. + * For example, app_123 for an uncompressed log, app_123.lzf for an LZF-compressed log. + * * @param logBaseDir Directory where the log file will be written. * @param appId A unique app ID. + * @param appAttemptId A unique attempt id of appId. May be the empty string. * @param compressionCodecName Name to identify the codec used to compress the contents * of the log, or None if compression is not enabled. * @return A path which consists of file-system-safe characters. @@ -261,11 +267,19 @@ private[spark] object EventLoggingListener extends Logging { def getLogPath( logBaseDir: URI, appId: String, + appAttemptId: Option[String], compressionCodecName: Option[String] = None): String = { - val sanitizedAppId = appId.replaceAll("[ :/]", "-").replaceAll("[.${}'\"]", "_").toLowerCase - // e.g. app_123, app_123.lzf - val logName = sanitizedAppId + compressionCodecName.map { "." + _ }.getOrElse("") - logBaseDir.toString.stripSuffix("/") + "/" + logName + val base = logBaseDir.toString.stripSuffix("/") + "/" + sanitize(appId) + val codec = compressionCodecName.map("." + _).getOrElse("") + if (appAttemptId.isDefined) { + base + "_" + sanitize(appAttemptId.get) + codec + } else { + base + codec + } + } + + private def sanitize(str: String): String = { + str.replaceAll("[ :/]", "-").replaceAll("[.${}'\"]", "_").toLowerCase } /** diff --git a/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala b/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala index 7c184b1dcb308..0b1d47cff3746 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala @@ -85,7 +85,7 @@ private[spark] class OutputCommitCoordinator(conf: SparkConf) extends Logging { val msg = AskPermissionToCommitOutput(stage, partition, attempt) coordinatorRef match { case Some(endpointRef) => - endpointRef.askWithReply[Boolean](msg) + endpointRef.askWithRetry[Boolean](msg) case None => logError( "canCommit called after coordinator was stopped (is SparkEnv shutdown in progress)?") diff --git a/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala index 992c477493d8e..646820520ea1b 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SchedulerBackend.scala @@ -41,4 +41,12 @@ private[spark] trait SchedulerBackend { */ def applicationId(): String = appId + /** + * Get the attempt ID for this run, if the cluster manager supports multiple + * attempts. Applications run in client mode will not have attempt IDs. + * + * @return The application attempt id, if available. + */ + def applicationAttemptId(): Option[String] = None + } diff --git a/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala index b711ff209af94..169d4fd3a94f0 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala @@ -110,8 +110,8 @@ case class SparkListenerExecutorMetricsUpdate( extends SparkListenerEvent @DeveloperApi -case class SparkListenerApplicationStart(appName: String, appId: Option[String], time: Long, - sparkUser: String) extends SparkListenerEvent +case class SparkListenerApplicationStart(appName: String, appId: Option[String], + time: Long, sparkUser: String, appAttemptId: Option[String]) extends SparkListenerEvent @DeveloperApi case class SparkListenerApplicationEnd(time: Long) extends SparkListenerEvent diff --git a/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala b/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala index 869f1d602bbcd..e439d2a7e1229 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala @@ -48,6 +48,18 @@ class StageInfo( failureReason = Some(reason) completionTime = Some(System.currentTimeMillis) } + + private[spark] def getStatusString: String = { + if (completionTime.isDefined) { + if (failureReason.isDefined) { + "failed" + } else { + "succeeded" + } + } else { + "running" + } + } } private[spark] object StageInfo { diff --git a/core/src/main/scala/org/apache/spark/scheduler/Task.scala b/core/src/main/scala/org/apache/spark/scheduler/Task.scala index b09b19e2ac9e7..586d1e06204c1 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/Task.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/Task.scala @@ -25,6 +25,7 @@ import scala.collection.mutable.HashMap import org.apache.spark.{TaskContextImpl, TaskContext} import org.apache.spark.executor.TaskMetrics import org.apache.spark.serializer.SerializerInstance +import org.apache.spark.unsafe.memory.TaskMemoryManager import org.apache.spark.util.ByteBufferInputStream import org.apache.spark.util.Utils @@ -52,8 +53,13 @@ private[spark] abstract class Task[T](val stageId: Int, var partitionId: Int) ex * @return the result of the task */ final def run(taskAttemptId: Long, attemptNumber: Int): T = { - context = new TaskContextImpl(stageId = stageId, partitionId = partitionId, - taskAttemptId = taskAttemptId, attemptNumber = attemptNumber, runningLocally = false) + context = new TaskContextImpl( + stageId = stageId, + partitionId = partitionId, + taskAttemptId = taskAttemptId, + attemptNumber = attemptNumber, + taskMemoryManager = taskMemoryManager, + runningLocally = false) TaskContext.setTaskContext(context) context.taskMetrics.setHostname(Utils.localHostName()) taskThread = Thread.currentThread() @@ -68,6 +74,12 @@ private[spark] abstract class Task[T](val stageId: Int, var partitionId: Int) ex } } + private var taskMemoryManager: TaskMemoryManager = _ + + def setTaskMemoryManager(taskMemoryManager: TaskMemoryManager): Unit = { + this.taskMemoryManager = taskMemoryManager + } + def runTask(context: TaskContext): T def preferredLocations: Seq[TaskLocation] = Nil diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskScheduler.scala index ed3418676e077..f25f3ed0d9037 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskScheduler.scala @@ -73,9 +73,17 @@ private[spark] trait TaskScheduler { * @return An application ID */ def applicationId(): String = appId - + /** * Process a lost executor */ def executorLost(executorId: String, reason: ExecutorLossReason): Unit + + /** + * Get an application's attempt ID associated with the job. + * + * @return An application's Attempt ID + */ + def applicationAttemptId(): Option[String] + } diff --git a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala index 13a52d836f32f..b4b8a630694bb 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala @@ -513,6 +513,8 @@ private[spark] class TaskSchedulerImpl( override def applicationId(): String = backend.applicationId() + override def applicationAttemptId(): Option[String] = backend.applicationAttemptId() + } diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala index 9656fb76858ea..f107148f3b8c6 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala @@ -68,6 +68,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp class DriverEndpoint(override val rpcEnv: RpcEnv, sparkProperties: Seq[(String, String)]) extends ThreadSafeRpcEndpoint with Logging { + override protected def log = CoarseGrainedSchedulerBackend.this.log private val addressToExecutorId = new HashMap[RpcAddress, String] @@ -112,6 +113,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp // Ignoring the task kill since the executor is not registered. logWarning(s"Attempted to kill task $taskId for unknown executor $executorId.") } + } override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = { @@ -122,7 +124,6 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp } else { logInfo("Registered executor: " + executorRef + " with ID " + executorId) context.reply(RegisteredExecutor) - addressToExecutorId(executorRef.address) = executorId totalCoreCount.addAndGet(cores) totalRegisteredExecutors.addAndGet(1) @@ -243,6 +244,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp properties += ((key, value)) } } + // TODO (prashant) send conf instead of properties driverEndpoint = rpcEnv.setupEndpoint( CoarseGrainedSchedulerBackend.ENDPOINT_NAME, new DriverEndpoint(rpcEnv, properties)) @@ -252,7 +254,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp try { if (driverEndpoint != null) { logInfo("Shutting down all executors") - driverEndpoint.askWithReply[Boolean](StopExecutors) + driverEndpoint.askWithRetry[Boolean](StopExecutors) } } catch { case e: Exception => @@ -264,7 +266,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp stopExecutors() try { if (driverEndpoint != null) { - driverEndpoint.askWithReply[Boolean](StopDriver) + driverEndpoint.askWithRetry[Boolean](StopDriver) } } catch { case e: Exception => @@ -287,7 +289,7 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp // Called by subclasses when notified of a lost worker def removeExecutor(executorId: String, reason: String) { try { - driverEndpoint.askWithReply[Boolean](RemoveExecutor(executorId, reason)) + driverEndpoint.askWithRetry[Boolean](RemoveExecutor(executorId, reason)) } catch { case e: Exception => throw new SparkException("Error notifying standalone scheduler's driver endpoint", e) diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala index d987c7d563579..2a3a5d925d06f 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/YarnSchedulerBackend.scala @@ -53,14 +53,14 @@ private[spark] abstract class YarnSchedulerBackend( * This includes executors already pending or running. */ override def doRequestTotalExecutors(requestedTotal: Int): Boolean = { - yarnSchedulerEndpoint.askWithReply[Boolean](RequestExecutors(requestedTotal)) + yarnSchedulerEndpoint.askWithRetry[Boolean](RequestExecutors(requestedTotal)) } /** * Request that the ApplicationMaster kill the specified executors. */ override def doKillExecutors(executorIds: Seq[String]): Boolean = { - yarnSchedulerEndpoint.askWithReply[Boolean](KillExecutors(executorIds)) + yarnSchedulerEndpoint.askWithRetry[Boolean](KillExecutors(executorIds)) } override def sufficientResourcesRegistered(): Boolean = { @@ -115,7 +115,7 @@ private[spark] abstract class YarnSchedulerBackend( amEndpoint match { case Some(am) => Future { - context.reply(am.askWithReply[Boolean](r)) + context.reply(am.askWithRetry[Boolean](r)) } onFailure { case NonFatal(e) => logError(s"Sending $r to AM was unsuccessful", e) @@ -130,7 +130,7 @@ private[spark] abstract class YarnSchedulerBackend( amEndpoint match { case Some(am) => Future { - context.reply(am.askWithReply[Boolean](k)) + context.reply(am.askWithRetry[Boolean](k)) } onFailure { case NonFatal(e) => logError(s"Sending $k to AM was unsuccessful", e) diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala index 3412301e64fd7..dc59545b43314 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala @@ -196,9 +196,14 @@ private[spark] class CoarseMesosSchedulerBackend( .addResources(createResource("cpus", cpusToUse)) .addResources(createResource("mem", MemoryUtils.calculateTotalMemory(sc))) - .build() + + sc.conf.getOption("spark.mesos.executor.docker.image").foreach { image => + MesosSchedulerBackendUtil + .setupContainerBuilderDockerInfo(image, sc.conf, task.getContainerBuilder()) + } + d.launchTasks( - Collections.singleton(offer.getId), Collections.singletonList(task), filters) + Collections.singleton(offer.getId), Collections.singletonList(task.build()), filters) } else { // Filter it out d.launchTasks( diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosClusterScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosClusterScheduler.scala index 0396e62be5309..06f0e2881c344 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosClusterScheduler.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosClusterScheduler.scala @@ -50,12 +50,13 @@ private[spark] class MesosClusterSubmissionState( val taskId: TaskID, val slaveId: SlaveID, var mesosTaskStatus: Option[TaskStatus], - var startDate: Date) + var startDate: Date, + var finishDate: Option[Date]) extends Serializable { def copy(): MesosClusterSubmissionState = { new MesosClusterSubmissionState( - driverDescription, taskId, slaveId, mesosTaskStatus, startDate) + driverDescription, taskId, slaveId, mesosTaskStatus, startDate, finishDate) } } @@ -95,6 +96,14 @@ private[spark] class MesosClusterSchedulerState( val finishedDrivers: Iterable[MesosClusterSubmissionState], val pendingRetryDrivers: Iterable[MesosDriverDescription]) +/** + * The full state of a Mesos driver, that is being used to display driver information on the UI. + */ +private[spark] class MesosDriverState( + val state: String, + val description: MesosDriverDescription, + val submissionState: Option[MesosClusterSubmissionState] = None) + /** * A Mesos scheduler that is responsible for launching submitted Spark drivers in cluster mode * as Mesos tasks in a Mesos cluster. @@ -233,6 +242,22 @@ private[spark] class MesosClusterScheduler( s } + /** + * Gets the driver state to be displayed on the Web UI. + */ + def getDriverState(submissionId: String): Option[MesosDriverState] = { + stateLock.synchronized { + queuedDrivers.find(_.submissionId.equals(submissionId)) + .map(d => new MesosDriverState("QUEUED", d)) + .orElse(launchedDrivers.get(submissionId) + .map(d => new MesosDriverState("RUNNING", d.driverDescription, Some(d)))) + .orElse(finishedDrivers.find(_.driverDescription.submissionId.equals(submissionId)) + .map(d => new MesosDriverState("FINISHED", d.driverDescription, Some(d)))) + .orElse(pendingRetryDrivers.find(_.submissionId.equals(submissionId)) + .map(d => new MesosDriverState("RETRYING", d))) + } + } + private def isQueueFull(): Boolean = launchedDrivers.size >= queuedCapacity /** @@ -439,7 +464,7 @@ private[spark] class MesosClusterScheduler( logTrace(s"Using offer ${offer.offer.getId.getValue} to launch driver " + submission.submissionId) val newState = new MesosClusterSubmissionState(submission, taskId, offer.offer.getSlaveId, - None, new Date()) + None, new Date(), None) launchedDrivers(submission.submissionId) = newState launchedDriversState.persist(submission.submissionId, newState) afterLaunchCallback(submission.submissionId) @@ -534,6 +559,7 @@ private[spark] class MesosClusterScheduler( // Check if the driver is supervise enabled and can be relaunched. if (state.driverDescription.supervise && shouldRelaunch(status.getState)) { removeFromLaunchedDrivers(taskId) + state.finishDate = Some(new Date()) val retryState: Option[MesosClusterRetryState] = state.driverDescription.retryState val (retries, waitTimeSec) = retryState .map { rs => (rs.retries + 1, Math.min(maxRetryWaitTime, rs.waitTime * 2)) } @@ -546,6 +572,7 @@ private[spark] class MesosClusterScheduler( pendingRetryDriversState.persist(taskId, newDriverDescription) } else if (TaskState.isFinished(TaskState.fromMesos(status.getState))) { removeFromLaunchedDrivers(taskId) + state.finishDate = Some(new Date()) if (finishedDrivers.size >= retainedDrivers) { val toRemove = math.max(retainedDrivers / 10, 1) finishedDrivers.trimStart(toRemove) diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala index 8346a2407489f..db0a080b3b0c0 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala @@ -23,7 +23,7 @@ import java.util.{ArrayList => JArrayList, Collections, List => JList} import scala.collection.JavaConversions._ import scala.collection.mutable.{HashMap, HashSet} -import org.apache.mesos.Protos.{ExecutorInfo => MesosExecutorInfo, TaskInfo => MesosTaskInfo, TaskState => MesosTaskState, _} +import org.apache.mesos.Protos.{ExecutorInfo => MesosExecutorInfo, TaskInfo => MesosTaskInfo, _} import org.apache.mesos.protobuf.ByteString import org.apache.mesos.{Scheduler => MScheduler, _} import org.apache.spark.executor.MesosExecutorBackend @@ -56,7 +56,7 @@ private[spark] class MesosSchedulerBackend( // The listener bus to publish executor added/removed events. val listenerBus = sc.listenerBus - + private[mesos] val mesosExecutorCores = sc.conf.getDouble("spark.mesos.mesosExecutor.cores", 1) @volatile var appId: String = _ @@ -124,13 +124,19 @@ private[spark] class MesosSchedulerBackend( Value.Scalar.newBuilder() .setValue(MemoryUtils.calculateTotalMemory(sc)).build()) .build() - MesosExecutorInfo.newBuilder() + val executorInfo = MesosExecutorInfo.newBuilder() .setExecutorId(ExecutorID.newBuilder().setValue(execId).build()) .setCommand(command) .setData(ByteString.copyFrom(createExecArg())) .addResources(cpus) .addResources(memory) - .build() + + sc.conf.getOption("spark.mesos.executor.docker.image").foreach { image => + MesosSchedulerBackendUtil + .setupContainerBuilderDockerInfo(image, sc.conf, executorInfo.getContainerBuilder()) + } + + executorInfo.build() } /** diff --git a/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendUtil.scala b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendUtil.scala new file mode 100644 index 0000000000000..928c5cfed417a --- /dev/null +++ b/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendUtil.scala @@ -0,0 +1,142 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.scheduler.cluster.mesos + +import org.apache.mesos.Protos.{ContainerInfo, Volume} +import org.apache.mesos.Protos.ContainerInfo.DockerInfo + +import org.apache.spark.{Logging, SparkConf} + +/** + * A collection of utility functions which can be used by both the + * MesosSchedulerBackend and the CoarseMesosSchedulerBackend. + */ +private[mesos] object MesosSchedulerBackendUtil extends Logging { + /** + * Parse a comma-delimited list of volume specs, each of which + * takes the form [host-dir:]container-dir[:rw|:ro]. + */ + def parseVolumesSpec(volumes: String): List[Volume] = { + volumes.split(",").map(_.split(":")).flatMap { spec => + val vol: Volume.Builder = Volume + .newBuilder() + .setMode(Volume.Mode.RW) + spec match { + case Array(container_path) => + Some(vol.setContainerPath(container_path)) + case Array(container_path, "rw") => + Some(vol.setContainerPath(container_path)) + case Array(container_path, "ro") => + Some(vol.setContainerPath(container_path) + .setMode(Volume.Mode.RO)) + case Array(host_path, container_path) => + Some(vol.setContainerPath(container_path) + .setHostPath(host_path)) + case Array(host_path, container_path, "rw") => + Some(vol.setContainerPath(container_path) + .setHostPath(host_path)) + case Array(host_path, container_path, "ro") => + Some(vol.setContainerPath(container_path) + .setHostPath(host_path) + .setMode(Volume.Mode.RO)) + case spec => { + logWarning(s"Unable to parse volume specs: $volumes. " + + "Expected form: \"[host-dir:]container-dir[:rw|:ro](, ...)\"") + None + } + } + } + .map { _.build() } + .toList + } + + /** + * Parse a comma-delimited list of port mapping specs, each of which + * takes the form host_port:container_port[:udp|:tcp] + * + * Note: + * the docker form is [ip:]host_port:container_port, but the DockerInfo + * message has no field for 'ip', and instead has a 'protocol' field. + * Docker itself only appears to support TCP, so this alternative form + * anticipates the expansion of the docker form to allow for a protocol + * and leaves open the chance for mesos to begin to accept an 'ip' field + */ + def parsePortMappingsSpec(portmaps: String): List[DockerInfo.PortMapping] = { + portmaps.split(",").map(_.split(":")).flatMap { spec: Array[String] => + val portmap: DockerInfo.PortMapping.Builder = DockerInfo.PortMapping + .newBuilder() + .setProtocol("tcp") + spec match { + case Array(host_port, container_port) => + Some(portmap.setHostPort(host_port.toInt) + .setContainerPort(container_port.toInt)) + case Array(host_port, container_port, protocol) => + Some(portmap.setHostPort(host_port.toInt) + .setContainerPort(container_port.toInt) + .setProtocol(protocol)) + case spec => { + logWarning(s"Unable to parse port mapping specs: $portmaps. " + + "Expected form: \"host_port:container_port[:udp|:tcp](, ...)\"") + None + } + } + } + .map { _.build() } + .toList + } + + /** + * Construct a DockerInfo structure and insert it into a ContainerInfo + */ + def addDockerInfo( + container: ContainerInfo.Builder, + image: String, + volumes: Option[List[Volume]] = None, + network: Option[ContainerInfo.DockerInfo.Network] = None, + portmaps: Option[List[ContainerInfo.DockerInfo.PortMapping]] = None):Unit = { + + val docker = ContainerInfo.DockerInfo.newBuilder().setImage(image) + + network.foreach(docker.setNetwork) + portmaps.foreach(_.foreach(docker.addPortMappings)) + container.setType(ContainerInfo.Type.DOCKER) + container.setDocker(docker.build()) + volumes.foreach(_.foreach(container.addVolumes)) + } + + /** + * Setup a docker containerizer + */ + def setupContainerBuilderDockerInfo( + imageName: String, + conf: SparkConf, + builder: ContainerInfo.Builder): Unit = { + val volumes = conf + .getOption("spark.mesos.executor.docker.volumes") + .map(parseVolumesSpec) + val portmaps = conf + .getOption("spark.mesos.executor.docker.portmaps") + .map(parsePortMappingsSpec) + addDockerInfo( + builder, + imageName, + volumes = volumes, + portmaps = portmaps) + logDebug("setupContainerDockerInfo: using docker image: " + imageName) + } +} diff --git a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala index ac5b524517818..e64d06c4d3cfc 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/local/LocalBackend.scala @@ -123,7 +123,7 @@ private[spark] class LocalBackend( } override def stop() { - localEndpoint.sendWithReply(StopExecutor) + localEndpoint.ask(StopExecutor) } override def reviveOffers() { diff --git a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala index 754832b8a4ca7..b7bc087855b9f 100644 --- a/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/KryoSerializer.scala @@ -200,6 +200,16 @@ private[spark] class KryoSerializerInstance(ks: KryoSerializer) extends Serializ override def deserializeStream(s: InputStream): DeserializationStream = { new KryoDeserializationStream(kryo, s) } + + /** + * Returns true if auto-reset is on. The only reason this would be false is if the user-supplied + * registrator explicitly turns auto-reset off. + */ + def getAutoReset(): Boolean = { + val field = classOf[Kryo].getDeclaredField("autoReset") + field.setAccessible(true) + field.get(kryo).asInstanceOf[Boolean] + } } /** diff --git a/core/src/main/scala/org/apache/spark/serializer/Serializer.scala b/core/src/main/scala/org/apache/spark/serializer/Serializer.scala index ca6e971d227fb..c381672a4f588 100644 --- a/core/src/main/scala/org/apache/spark/serializer/Serializer.scala +++ b/core/src/main/scala/org/apache/spark/serializer/Serializer.scala @@ -101,7 +101,12 @@ abstract class SerializerInstance { */ @DeveloperApi abstract class SerializationStream { + /** The most general-purpose method to write an object. */ def writeObject[T: ClassTag](t: T): SerializationStream + /** Writes the object representing the key of a key-value pair. */ + def writeKey[T: ClassTag](key: T): SerializationStream = writeObject(key) + /** Writes the object representing the value of a key-value pair. */ + def writeValue[T: ClassTag](value: T): SerializationStream = writeObject(value) def flush(): Unit def close(): Unit @@ -120,7 +125,12 @@ abstract class SerializationStream { */ @DeveloperApi abstract class DeserializationStream { + /** The most general-purpose method to read an object. */ def readObject[T: ClassTag](): T + /** Reads the object representing the key of a key-value pair. */ + def readKey[T: ClassTag](): T = readObject[T]() + /** Reads the object representing the value of a key-value pair. */ + def readValue[T: ClassTag](): T = readObject[T]() def close(): Unit /** @@ -141,4 +151,25 @@ abstract class DeserializationStream { DeserializationStream.this.close() } } + + /** + * Read the elements of this stream through an iterator over key-value pairs. This can only be + * called once, as reading each element will consume data from the input source. + */ + def asKeyValueIterator: Iterator[(Any, Any)] = new NextIterator[(Any, Any)] { + override protected def getNext() = { + try { + (readKey[Any](), readValue[Any]()) + } catch { + case eof: EOFException => { + finished = true + null + } + } + } + + override protected def close() { + DeserializationStream.this.close() + } + } } diff --git a/core/src/main/scala/org/apache/spark/shuffle/ShuffleHandle.scala b/core/src/main/scala/org/apache/spark/shuffle/ShuffleHandle.scala index 13c7115f88afa..e04c97fe61894 100644 --- a/core/src/main/scala/org/apache/spark/shuffle/ShuffleHandle.scala +++ b/core/src/main/scala/org/apache/spark/shuffle/ShuffleHandle.scala @@ -17,9 +17,12 @@ package org.apache.spark.shuffle +import org.apache.spark.annotation.DeveloperApi + /** * An opaque handle to a shuffle, used by a ShuffleManager to pass information about it to tasks. * * @param shuffleId ID of the shuffle */ -private[spark] abstract class ShuffleHandle(val shuffleId: Int) extends Serializable {} +@DeveloperApi +abstract class ShuffleHandle(val shuffleId: Int) extends Serializable {} diff --git a/core/src/main/scala/org/apache/spark/shuffle/hash/HashShuffleWriter.scala b/core/src/main/scala/org/apache/spark/shuffle/hash/HashShuffleWriter.scala index 755f17d6aa15a..cd27c9e07a3cd 100644 --- a/core/src/main/scala/org/apache/spark/shuffle/hash/HashShuffleWriter.scala +++ b/core/src/main/scala/org/apache/spark/shuffle/hash/HashShuffleWriter.scala @@ -63,7 +63,7 @@ private[spark] class HashShuffleWriter[K, V]( for (elem <- iter) { val bucketId = dep.partitioner.getPartition(elem._1) - shuffle.writers(bucketId).write(elem) + shuffle.writers(bucketId).write(elem._1, elem._2) } } diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala index 55718e584c195..a46fecd2274ef 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala @@ -78,19 +78,11 @@ private[spark] class BlockManager( private val blockInfo = new TimeStampedHashMap[BlockId, BlockInfo] // Actual storage of where blocks are kept - private var tachyonInitialized = false + private var externalBlockStoreInitialized = false private[spark] val memoryStore = new MemoryStore(this, maxMemory) private[spark] val diskStore = new DiskStore(this, diskBlockManager) - private[spark] lazy val tachyonStore: TachyonStore = { - val storeDir = conf.get("spark.tachyonStore.baseDir", "/tmp_spark_tachyon") - val appFolderName = conf.get("spark.tachyonStore.folderName") - val tachyonStorePath = s"$storeDir/$appFolderName/${this.executorId}" - val tachyonMaster = conf.get("spark.tachyonStore.url", "tachyon://localhost:19998") - val tachyonBlockManager = - new TachyonBlockManager(this, tachyonStorePath, tachyonMaster) - tachyonInitialized = true - new TachyonStore(this, tachyonBlockManager) - } + private[spark] lazy val externalBlockStore: ExternalBlockStore = + new ExternalBlockStore(this, executorId) private[spark] val externalShuffleServiceEnabled = conf.getBoolean("spark.shuffle.service.enabled", false) @@ -119,7 +111,8 @@ private[spark] class BlockManager( // standard BlockTransferService to directly connect to other Executors. private[spark] val shuffleClient = if (externalShuffleServiceEnabled) { val transConf = SparkTransportConf.fromSparkConf(conf, numUsableCores) - new ExternalShuffleClient(transConf, securityManager, securityManager.isAuthenticationEnabled()) + new ExternalShuffleClient(transConf, securityManager, securityManager.isAuthenticationEnabled(), + securityManager.isSaslEncryptionEnabled()) } else { blockTransferService } @@ -320,13 +313,13 @@ private[spark] class BlockManager( /** * Get the BlockStatus for the block identified by the given ID, if it exists. - * NOTE: This is mainly for testing, and it doesn't fetch information from Tachyon. + * NOTE: This is mainly for testing, and it doesn't fetch information from external block store. */ def getStatus(blockId: BlockId): Option[BlockStatus] = { blockInfo.get(blockId).map { info => val memSize = if (memoryStore.contains(blockId)) memoryStore.getSize(blockId) else 0L val diskSize = if (diskStore.contains(blockId)) diskStore.getSize(blockId) else 0L - // Assume that block is not in Tachyon + // Assume that block is not in external block store BlockStatus(info.level, memSize, diskSize, 0L) } } @@ -376,10 +369,10 @@ private[spark] class BlockManager( if (info.tellMaster) { val storageLevel = status.storageLevel val inMemSize = Math.max(status.memSize, droppedMemorySize) - val inTachyonSize = status.tachyonSize + val inExternalBlockStoreSize = status.externalBlockStoreSize val onDiskSize = status.diskSize master.updateBlockInfo( - blockManagerId, blockId, storageLevel, inMemSize, onDiskSize, inTachyonSize) + blockManagerId, blockId, storageLevel, inMemSize, onDiskSize, inExternalBlockStoreSize) } else { true } @@ -397,15 +390,17 @@ private[spark] class BlockManager( BlockStatus(StorageLevel.NONE, 0L, 0L, 0L) case level => val inMem = level.useMemory && memoryStore.contains(blockId) - val inTachyon = level.useOffHeap && tachyonStore.contains(blockId) + val inExternalBlockStore = level.useOffHeap && externalBlockStore.contains(blockId) val onDisk = level.useDisk && diskStore.contains(blockId) val deserialized = if (inMem) level.deserialized else false - val replication = if (inMem || inTachyon || onDisk) level.replication else 1 - val storageLevel = StorageLevel(onDisk, inMem, inTachyon, deserialized, replication) + val replication = if (inMem || inExternalBlockStore || onDisk) level.replication else 1 + val storageLevel = + StorageLevel(onDisk, inMem, inExternalBlockStore, deserialized, replication) val memSize = if (inMem) memoryStore.getSize(blockId) else 0L - val tachyonSize = if (inTachyon) tachyonStore.getSize(blockId) else 0L + val externalBlockStoreSize = + if (inExternalBlockStore) externalBlockStore.getSize(blockId) else 0L val diskSize = if (onDisk) diskStore.getSize(blockId) else 0L - BlockStatus(storageLevel, memSize, diskSize, tachyonSize) + BlockStatus(storageLevel, memSize, diskSize, externalBlockStoreSize) } } } @@ -485,11 +480,11 @@ private[spark] class BlockManager( } } - // Look for the block in Tachyon + // Look for the block in external block store if (level.useOffHeap) { - logDebug(s"Getting block $blockId from tachyon") - if (tachyonStore.contains(blockId)) { - tachyonStore.getBytes(blockId) match { + logDebug(s"Getting block $blockId from ExternalBlockStore") + if (externalBlockStore.contains(blockId)) { + externalBlockStore.getBytes(blockId) match { case Some(bytes) => if (!asBlockResult) { return Some(bytes) @@ -498,7 +493,7 @@ private[spark] class BlockManager( dataDeserialize(blockId, bytes), DataReadMethod.Memory, info.size)) } case None => - logDebug(s"Block $blockId not found in tachyon") + logDebug(s"Block $blockId not found in externalBlockStore") } } } @@ -766,8 +761,8 @@ private[spark] class BlockManager( // We will drop it to disk later if the memory store can't hold it. (true, memoryStore) } else if (putLevel.useOffHeap) { - // Use tachyon for off-heap storage - (false, tachyonStore) + // Use external block store + (false, externalBlockStore) } else if (putLevel.useDisk) { // Don't get back the bytes from put unless we replicate them (putLevel.replication > 1, diskStore) @@ -802,7 +797,7 @@ private[spark] class BlockManager( val putBlockStatus = getCurrentBlockStatus(blockId, putBlockInfo) if (putBlockStatus.storageLevel != StorageLevel.NONE) { - // Now that the block is in either the memory, tachyon, or disk store, + // Now that the block is in either the memory, externalBlockStore, or disk store, // let other threads read it, and tell the master about it. marked = true putBlockInfo.markReady(size) @@ -1099,10 +1094,11 @@ private[spark] class BlockManager( // Removals are idempotent in disk store and memory store. At worst, we get a warning. val removedFromMemory = memoryStore.remove(blockId) val removedFromDisk = diskStore.remove(blockId) - val removedFromTachyon = if (tachyonInitialized) tachyonStore.remove(blockId) else false - if (!removedFromMemory && !removedFromDisk && !removedFromTachyon) { + val removedFromExternalBlockStore = + if (externalBlockStoreInitialized) externalBlockStore.remove(blockId) else false + if (!removedFromMemory && !removedFromDisk && !removedFromExternalBlockStore) { logWarning(s"Block $blockId could not be removed as it was not found in either " + - "the disk, memory, or tachyon store") + "the disk, memory, or external block store") } blockInfo.remove(blockId) if (tellMaster && info.tellMaster) { @@ -1136,7 +1132,7 @@ private[spark] class BlockManager( val level = info.level if (level.useMemory) { memoryStore.remove(id) } if (level.useDisk) { diskStore.remove(id) } - if (level.useOffHeap) { tachyonStore.remove(id) } + if (level.useOffHeap) { externalBlockStore.remove(id) } iterator.remove() logInfo(s"Dropped block $id") } @@ -1216,8 +1212,8 @@ private[spark] class BlockManager( blockInfo.clear() memoryStore.clear() diskStore.clear() - if (tachyonInitialized) { - tachyonStore.clear() + if (externalBlockStoreInitialized) { + externalBlockStore.clear() } metadataCleaner.cancel() broadcastCleaner.cancel() diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala index c798843bd5d8a..a85e1c7632973 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala @@ -54,21 +54,22 @@ class BlockManagerMaster( storageLevel: StorageLevel, memSize: Long, diskSize: Long, - tachyonSize: Long): Boolean = { - val res = driverEndpoint.askWithReply[Boolean]( - UpdateBlockInfo(blockManagerId, blockId, storageLevel, memSize, diskSize, tachyonSize)) + externalBlockStoreSize: Long): Boolean = { + val res = driverEndpoint.askWithRetry[Boolean]( + UpdateBlockInfo(blockManagerId, blockId, storageLevel, + memSize, diskSize, externalBlockStoreSize)) logDebug(s"Updated info of block $blockId") res } /** Get locations of the blockId from the driver */ def getLocations(blockId: BlockId): Seq[BlockManagerId] = { - driverEndpoint.askWithReply[Seq[BlockManagerId]](GetLocations(blockId)) + driverEndpoint.askWithRetry[Seq[BlockManagerId]](GetLocations(blockId)) } /** Get locations of multiple blockIds from the driver */ def getLocations(blockIds: Array[BlockId]): Seq[Seq[BlockManagerId]] = { - driverEndpoint.askWithReply[Seq[Seq[BlockManagerId]]](GetLocationsMultipleBlockIds(blockIds)) + driverEndpoint.askWithRetry[Seq[Seq[BlockManagerId]]](GetLocationsMultipleBlockIds(blockIds)) } /** @@ -81,11 +82,11 @@ class BlockManagerMaster( /** Get ids of other nodes in the cluster from the driver */ def getPeers(blockManagerId: BlockManagerId): Seq[BlockManagerId] = { - driverEndpoint.askWithReply[Seq[BlockManagerId]](GetPeers(blockManagerId)) + driverEndpoint.askWithRetry[Seq[BlockManagerId]](GetPeers(blockManagerId)) } def getRpcHostPortForExecutor(executorId: String): Option[(String, Int)] = { - driverEndpoint.askWithReply[Option[(String, Int)]](GetRpcHostPortForExecutor(executorId)) + driverEndpoint.askWithRetry[Option[(String, Int)]](GetRpcHostPortForExecutor(executorId)) } /** @@ -93,12 +94,12 @@ class BlockManagerMaster( * blocks that the driver knows about. */ def removeBlock(blockId: BlockId) { - driverEndpoint.askWithReply[Boolean](RemoveBlock(blockId)) + driverEndpoint.askWithRetry[Boolean](RemoveBlock(blockId)) } /** Remove all blocks belonging to the given RDD. */ def removeRdd(rddId: Int, blocking: Boolean) { - val future = driverEndpoint.askWithReply[Future[Seq[Int]]](RemoveRdd(rddId)) + val future = driverEndpoint.askWithRetry[Future[Seq[Int]]](RemoveRdd(rddId)) future.onFailure { case e: Exception => logWarning(s"Failed to remove RDD $rddId - ${e.getMessage}}") @@ -110,7 +111,7 @@ class BlockManagerMaster( /** Remove all blocks belonging to the given shuffle. */ def removeShuffle(shuffleId: Int, blocking: Boolean) { - val future = driverEndpoint.askWithReply[Future[Seq[Boolean]]](RemoveShuffle(shuffleId)) + val future = driverEndpoint.askWithRetry[Future[Seq[Boolean]]](RemoveShuffle(shuffleId)) future.onFailure { case e: Exception => logWarning(s"Failed to remove shuffle $shuffleId - ${e.getMessage}}") @@ -122,7 +123,7 @@ class BlockManagerMaster( /** Remove all blocks belonging to the given broadcast. */ def removeBroadcast(broadcastId: Long, removeFromMaster: Boolean, blocking: Boolean) { - val future = driverEndpoint.askWithReply[Future[Seq[Int]]]( + val future = driverEndpoint.askWithRetry[Future[Seq[Int]]]( RemoveBroadcast(broadcastId, removeFromMaster)) future.onFailure { case e: Exception => @@ -141,11 +142,11 @@ class BlockManagerMaster( * amount of remaining memory. */ def getMemoryStatus: Map[BlockManagerId, (Long, Long)] = { - driverEndpoint.askWithReply[Map[BlockManagerId, (Long, Long)]](GetMemoryStatus) + driverEndpoint.askWithRetry[Map[BlockManagerId, (Long, Long)]](GetMemoryStatus) } def getStorageStatus: Array[StorageStatus] = { - driverEndpoint.askWithReply[Array[StorageStatus]](GetStorageStatus) + driverEndpoint.askWithRetry[Array[StorageStatus]](GetStorageStatus) } /** @@ -166,7 +167,7 @@ class BlockManagerMaster( * master endpoint for a response to a prior message. */ val response = driverEndpoint. - askWithReply[Map[BlockManagerId, Future[Option[BlockStatus]]]](msg) + askWithRetry[Map[BlockManagerId, Future[Option[BlockStatus]]]](msg) val (blockManagerIds, futures) = response.unzip val result = Await.result(Future.sequence(futures), timeout) if (result == null) { @@ -190,7 +191,7 @@ class BlockManagerMaster( filter: BlockId => Boolean, askSlaves: Boolean): Seq[BlockId] = { val msg = GetMatchingBlockIds(filter, askSlaves) - val future = driverEndpoint.askWithReply[Future[Seq[BlockId]]](msg) + val future = driverEndpoint.askWithRetry[Future[Seq[BlockId]]](msg) Await.result(future, timeout) } @@ -205,7 +206,7 @@ class BlockManagerMaster( /** Send a one-way message to the master endpoint, to which we expect it to reply with true. */ private def tell(message: Any) { - if (!driverEndpoint.askWithReply[Boolean](message)) { + if (!driverEndpoint.askWithRetry[Boolean](message)) { throw new SparkException("BlockManagerMasterEndpoint returned false, expected true.") } } diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterEndpoint.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterEndpoint.scala index 4682167912ff0..3afb4c3c02e2d 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterEndpoint.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMasterEndpoint.scala @@ -60,9 +60,9 @@ class BlockManagerMasterEndpoint( context.reply(true) case UpdateBlockInfo( - blockManagerId, blockId, storageLevel, deserializedSize, size, tachyonSize) => + blockManagerId, blockId, storageLevel, deserializedSize, size, externalBlockStoreSize) => context.reply(updateBlockInfo( - blockManagerId, blockId, storageLevel, deserializedSize, size, tachyonSize)) + blockManagerId, blockId, storageLevel, deserializedSize, size, externalBlockStoreSize)) case GetLocations(blockId) => context.reply(getLocations(blockId)) @@ -132,7 +132,7 @@ class BlockManagerMasterEndpoint( val removeMsg = RemoveRdd(rddId) Future.sequence( blockManagerInfo.values.map { bm => - bm.slaveEndpoint.sendWithReply[Int](removeMsg) + bm.slaveEndpoint.ask[Int](removeMsg) }.toSeq ) } @@ -142,7 +142,7 @@ class BlockManagerMasterEndpoint( val removeMsg = RemoveShuffle(shuffleId) Future.sequence( blockManagerInfo.values.map { bm => - bm.slaveEndpoint.sendWithReply[Boolean](removeMsg) + bm.slaveEndpoint.ask[Boolean](removeMsg) }.toSeq ) } @@ -159,7 +159,7 @@ class BlockManagerMasterEndpoint( } Future.sequence( requiredBlockManagers.map { bm => - bm.slaveEndpoint.sendWithReply[Int](removeMsg) + bm.slaveEndpoint.ask[Int](removeMsg) }.toSeq ) } @@ -214,7 +214,7 @@ class BlockManagerMasterEndpoint( // Remove the block from the slave's BlockManager. // Doesn't actually wait for a confirmation and the message might get lost. // If message loss becomes frequent, we should add retry logic here. - blockManager.get.slaveEndpoint.sendWithReply[Boolean](RemoveBlock(blockId)) + blockManager.get.slaveEndpoint.ask[Boolean](RemoveBlock(blockId)) } } } @@ -253,7 +253,7 @@ class BlockManagerMasterEndpoint( blockManagerInfo.values.map { info => val blockStatusFuture = if (askSlaves) { - info.slaveEndpoint.sendWithReply[Option[BlockStatus]](getBlockStatus) + info.slaveEndpoint.ask[Option[BlockStatus]](getBlockStatus) } else { Future { info.getStatus(blockId) } } @@ -277,7 +277,7 @@ class BlockManagerMasterEndpoint( blockManagerInfo.values.map { info => val future = if (askSlaves) { - info.slaveEndpoint.sendWithReply[Seq[BlockId]](getMatchingBlockIds) + info.slaveEndpoint.ask[Seq[BlockId]](getMatchingBlockIds) } else { Future { info.blocks.keys.filter(filter).toSeq } } @@ -314,7 +314,7 @@ class BlockManagerMasterEndpoint( storageLevel: StorageLevel, memSize: Long, diskSize: Long, - tachyonSize: Long): Boolean = { + externalBlockStoreSize: Long): Boolean = { if (!blockManagerInfo.contains(blockManagerId)) { if (blockManagerId.isDriver && !isLocal) { @@ -332,7 +332,7 @@ class BlockManagerMasterEndpoint( } blockManagerInfo(blockManagerId).updateBlockInfo( - blockId, storageLevel, memSize, diskSize, tachyonSize) + blockId, storageLevel, memSize, diskSize, externalBlockStoreSize) var locations: mutable.HashSet[BlockManagerId] = null if (blockLocations.containsKey(blockId)) { @@ -396,8 +396,8 @@ case class BlockStatus( storageLevel: StorageLevel, memSize: Long, diskSize: Long, - tachyonSize: Long) { - def isCached: Boolean = memSize + diskSize + tachyonSize > 0 + externalBlockStoreSize: Long) { + def isCached: Boolean = memSize + diskSize + externalBlockStoreSize > 0 } @DeveloperApi @@ -429,7 +429,7 @@ private[spark] class BlockManagerInfo( storageLevel: StorageLevel, memSize: Long, diskSize: Long, - tachyonSize: Long) { + externalBlockStoreSize: Long) { updateLastSeenMs() @@ -445,9 +445,9 @@ private[spark] class BlockManagerInfo( } if (storageLevel.isValid) { - /* isValid means it is either stored in-memory, on-disk or on-Tachyon. + /* isValid means it is either stored in-memory, on-disk or on-externalBlockStore. * The memSize here indicates the data size in or dropped from memory, - * tachyonSize here indicates the data size in or dropped from Tachyon, + * externalBlockStoreSize here indicates the data size in or dropped from externalBlockStore, * and the diskSize here indicates the data size in or dropped to disk. * They can be both larger than 0, when a block is dropped from memory to disk. * Therefore, a safe way to set BlockStatus is to set its info in accurate modes. */ @@ -464,9 +464,9 @@ private[spark] class BlockManagerInfo( blockId, blockManagerId.hostPort, Utils.bytesToString(diskSize))) } if (storageLevel.useOffHeap) { - _blocks.put(blockId, BlockStatus(storageLevel, 0, 0, tachyonSize)) - logInfo("Added %s on tachyon on %s (size: %s)".format( - blockId, blockManagerId.hostPort, Utils.bytesToString(tachyonSize))) + _blocks.put(blockId, BlockStatus(storageLevel, 0, 0, externalBlockStoreSize)) + logInfo("Added %s on ExternalBlockStore on %s (size: %s)".format( + blockId, blockManagerId.hostPort, Utils.bytesToString(externalBlockStoreSize))) } } else if (_blocks.containsKey(blockId)) { // If isValid is not true, drop the block. @@ -482,8 +482,9 @@ private[spark] class BlockManagerInfo( blockId, blockManagerId.hostPort, Utils.bytesToString(blockStatus.diskSize))) } if (blockStatus.storageLevel.useOffHeap) { - logInfo("Removed %s on %s on tachyon (size: %s)".format( - blockId, blockManagerId.hostPort, Utils.bytesToString(blockStatus.tachyonSize))) + logInfo("Removed %s on %s on externalBlockStore (size: %s)".format( + blockId, blockManagerId.hostPort, + Utils.bytesToString(blockStatus.externalBlockStoreSize))) } } } diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerMessages.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerMessages.scala index f89d8d7493f7c..1683576067fe8 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMessages.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMessages.scala @@ -60,7 +60,7 @@ private[spark] object BlockManagerMessages { var storageLevel: StorageLevel, var memSize: Long, var diskSize: Long, - var tachyonSize: Long) + var externalBlockStoreSize: Long) extends ToBlockManagerMaster with Externalizable { @@ -72,7 +72,7 @@ private[spark] object BlockManagerMessages { storageLevel.writeExternal(out) out.writeLong(memSize) out.writeLong(diskSize) - out.writeLong(tachyonSize) + out.writeLong(externalBlockStoreSize) } override def readExternal(in: ObjectInput): Unit = Utils.tryOrIOException { @@ -81,7 +81,7 @@ private[spark] object BlockManagerMessages { storageLevel = StorageLevel(in) memSize = in.readLong() diskSize = in.readLong() - tachyonSize = in.readLong() + externalBlockStoreSize = in.readLong() } } diff --git a/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala b/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala index 14833791f7a4d..499dd97c0656a 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala @@ -33,7 +33,7 @@ import org.apache.spark.util.Utils * This interface does not support concurrent writes. Also, once the writer has * been opened, it cannot be reopened again. */ -private[spark] abstract class BlockObjectWriter(val blockId: BlockId) { +private[spark] abstract class BlockObjectWriter(val blockId: BlockId) extends OutputStream { def open(): BlockObjectWriter @@ -54,9 +54,14 @@ private[spark] abstract class BlockObjectWriter(val blockId: BlockId) { def revertPartialWritesAndClose() /** - * Writes an object. + * Writes a key-value pair. */ - def write(value: Any) + def write(key: Any, value: Any) + + /** + * Notify the writer that a record worth of bytes has been written with writeBytes. + */ + def recordWritten() /** * Returns the file segment of committed data that this Writer has written. @@ -203,12 +208,32 @@ private[spark] class DiskBlockObjectWriter( } } - override def write(value: Any) { + override def write(key: Any, value: Any) { + if (!initialized) { + open() + } + + objOut.writeKey(key) + objOut.writeValue(value) + numRecordsWritten += 1 + writeMetrics.incShuffleRecordsWritten(1) + + if (numRecordsWritten % 32 == 0) { + updateBytesWritten() + } + } + + override def write(b: Int): Unit = throw new UnsupportedOperationException() + + override def write(kvBytes: Array[Byte], offs: Int, len: Int): Unit = { if (!initialized) { open() } - objOut.writeObject(value) + bs.write(kvBytes, offs, len) + } + + override def recordWritten(): Unit = { numRecordsWritten += 1 writeMetrics.incShuffleRecordsWritten(1) @@ -238,7 +263,7 @@ private[spark] class DiskBlockObjectWriter( } // For testing - private[spark] def flush() { + private[spark] override def flush() { objOut.flush() bs.flush() } diff --git a/core/src/main/scala/org/apache/spark/storage/ExternalBlockManager.scala b/core/src/main/scala/org/apache/spark/storage/ExternalBlockManager.scala new file mode 100644 index 0000000000000..8964762df6af3 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/ExternalBlockManager.scala @@ -0,0 +1,102 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +import java.nio.ByteBuffer + +/** + * An abstract class that the concrete external block manager has to inherit. + * The class has to have a no-argument constructor, and will be initialized by init, + * which is invoked by ExternalBlockStore. The main input parameter is blockId for all + * the methods, which is the unique identifier for Block in one Spark application. + * + * The underlying external block manager should avoid any name space conflicts among multiple + * Spark applications. For example, creating different directory for different applications + * by randomUUID + * + */ +private[spark] abstract class ExternalBlockManager { + + override def toString: String = {"External Block Store"} + + /** + * Initialize a concrete block manager implementation. Subclass should initialize its internal + * data structure, e.g, file system, in this function, which is invoked by ExternalBlockStore + * right after the class is constructed. The function should throw IOException on failure + * + * @throws java.io.IOException if there is any file system failure during the initialization. + */ + def init(blockManager: BlockManager, executorId: String): Unit + + /** + * Drop the block from underlying external block store, if it exists.. + * @return true on successfully removing the block + * false if the block could not be removed as it was not found + * + * @throws java.io.IOException if there is any file system failure in removing the block. + */ + def removeBlock(blockId: BlockId): Boolean + + /** + * Used by BlockManager to check the existence of the block in the underlying external + * block store. + * @return true if the block exists. + * false if the block does not exists. + * + * @throws java.io.IOException if there is any file system failure in checking + * the block existence. + */ + def blockExists(blockId: BlockId): Boolean + + /** + * Put the given block to the underlying external block store. Note that in normal case, + * putting a block should never fail unless something wrong happens to the underlying + * external block store, e.g., file system failure, etc. In this case, IOException + * should be thrown. + * + * @throws java.io.IOException if there is any file system failure in putting the block. + */ + def putBytes(blockId: BlockId, bytes: ByteBuffer): Unit + + /** + * Retrieve the block bytes. + * @return Some(ByteBuffer) if the block bytes is successfully retrieved + * None if the block does not exist in the external block store. + * + * @throws java.io.IOException if there is any file system failure in getting the block. + */ + def getBytes(blockId: BlockId): Option[ByteBuffer] + + /** + * Get the size of the block saved in the underlying external block store, + * which is saved before by putBytes. + * @return size of the block + * 0 if the block does not exist + * + * @throws java.io.IOException if there is any file system failure in getting the block size. + */ + def getSize(blockId: BlockId): Long + + /** + * Clean up any information persisted in the underlying external block store, + * e.g., the directory, files, etc,which is invoked by the shutdown hook of ExternalBlockStore + * during system shutdown. + * + */ + def shutdown() +} diff --git a/core/src/main/scala/org/apache/spark/storage/ExternalBlockStore.scala b/core/src/main/scala/org/apache/spark/storage/ExternalBlockStore.scala new file mode 100644 index 0000000000000..0bf770306ae9b --- /dev/null +++ b/core/src/main/scala/org/apache/spark/storage/ExternalBlockStore.scala @@ -0,0 +1,181 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.storage + +import java.nio.ByteBuffer +import org.apache.spark.Logging +import org.apache.spark.util.Utils +import scala.util.control.NonFatal + + +/** + * Stores BlockManager blocks on ExternalBlockStore. + * We capture any potential exception from underlying implementation + * and return with the expected failure value + */ +private[spark] class ExternalBlockStore(blockManager: BlockManager, executorId: String) + extends BlockStore(blockManager: BlockManager) with Logging { + + lazy val externalBlockManager: Option[ExternalBlockManager] = createBlkManager() + + logInfo("ExternalBlockStore started") + + override def getSize(blockId: BlockId): Long = { + try { + externalBlockManager.map(_.getSize(blockId)).getOrElse(0) + } catch { + case NonFatal(t) => + logError(s"error in getSize from $blockId", t) + 0L + } + } + + override def putBytes(blockId: BlockId, bytes: ByteBuffer, level: StorageLevel): PutResult = { + putIntoExternalBlockStore(blockId, bytes, returnValues = true) + } + + override def putArray( + blockId: BlockId, + values: Array[Any], + level: StorageLevel, + returnValues: Boolean): PutResult = { + putIterator(blockId, values.toIterator, level, returnValues) + } + + override def putIterator( + blockId: BlockId, + values: Iterator[Any], + level: StorageLevel, + returnValues: Boolean): PutResult = { + logDebug(s"Attempting to write values for block $blockId") + val bytes = blockManager.dataSerialize(blockId, values) + putIntoExternalBlockStore(blockId, bytes, returnValues) + } + + private def putIntoExternalBlockStore( + blockId: BlockId, + bytes: ByteBuffer, + returnValues: Boolean): PutResult = { + // So that we do not modify the input offsets ! + // duplicate does not copy buffer, so inexpensive + val byteBuffer = bytes.duplicate() + byteBuffer.rewind() + logDebug(s"Attempting to put block $blockId into ExtBlk store") + // we should never hit here if externalBlockManager is None. Handle it anyway for safety. + try { + val startTime = System.currentTimeMillis + if (externalBlockManager.isDefined) { + externalBlockManager.get.putBytes(blockId, bytes) + val finishTime = System.currentTimeMillis + logDebug("Block %s stored as %s file in ExternalBlockStore in %d ms".format( + blockId, Utils.bytesToString(byteBuffer.limit), finishTime - startTime)) + + if (returnValues) { + PutResult(bytes.limit(), Right(bytes.duplicate())) + } else { + PutResult(bytes.limit(), null) + } + } else { + logError(s"error in putBytes $blockId") + PutResult(bytes.limit(), null, Seq((blockId, BlockStatus.empty))) + } + } catch { + case NonFatal(t) => + logError(s"error in putBytes $blockId", t) + PutResult(bytes.limit(), null, Seq((blockId, BlockStatus.empty))) + } + } + + // We assume the block is removed even if exception thrown + override def remove(blockId: BlockId): Boolean = { + try { + externalBlockManager.map(_.removeBlock(blockId)).getOrElse(true) + } catch { + case NonFatal(t) => + logError(s"error in removing $blockId", t) + true + } + } + + override def getValues(blockId: BlockId): Option[Iterator[Any]] = { + getBytes(blockId).map(buffer => blockManager.dataDeserialize(blockId, buffer)) + } + + override def getBytes(blockId: BlockId): Option[ByteBuffer] = { + try { + externalBlockManager.flatMap(_.getBytes(blockId)) + } catch { + case NonFatal(t) => + logError(s"error in getBytes from $blockId", t) + None + } + } + + override def contains(blockId: BlockId): Boolean = { + try { + val ret = externalBlockManager.map(_.blockExists(blockId)).getOrElse(false) + if (!ret) { + logInfo(s"remove block $blockId") + blockManager.removeBlock(blockId, true) + } + ret + } catch { + case NonFatal(t) => + logError(s"error in getBytes from $blockId", t) + false + } + } + + private def addShutdownHook() { + Runtime.getRuntime.addShutdownHook(new Thread("ExternalBlockStore shutdown hook") { + override def run(): Unit = Utils.logUncaughtExceptions { + logDebug("Shutdown hook called") + externalBlockManager.map(_.shutdown()) + } + }) + } + + // Create concrete block manager and fall back to Tachyon by default for backward compatibility. + private def createBlkManager(): Option[ExternalBlockManager] = { + val clsName = blockManager.conf.getOption(ExternalBlockStore.BLOCK_MANAGER_NAME) + .getOrElse(ExternalBlockStore.DEFAULT_BLOCK_MANAGER_NAME) + + try { + val instance = Class.forName(clsName) + .newInstance() + .asInstanceOf[ExternalBlockManager] + instance.init(blockManager, executorId) + addShutdownHook(); + Some(instance) + } catch { + case NonFatal(t) => + logError("Cannot initialize external block store", t) + None + } + } +} + +private[spark] object ExternalBlockStore extends Logging { + val MAX_DIR_CREATION_ATTEMPTS = 10 + val SUB_DIRS_PER_DIR = "64" + val BASE_DIR = "spark.externalBlockStore.baseDir" + val FOLD_NAME = "spark.externalBlockStore.folderName" + val MASTER_URL = "spark.externalBlockStore.url" + val BLOCK_MANAGER_NAME = "spark.externalBlockStore.blockManager" + val DEFAULT_BLOCK_MANAGER_NAME = "org.apache.spark.storage.TachyonBlockManager" +} diff --git a/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala b/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala index 11fe336c9c3ec..99e3d13c46003 100644 --- a/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala +++ b/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala @@ -34,17 +34,19 @@ class RDDInfo( var numCachedPartitions = 0 var memSize = 0L var diskSize = 0L - var tachyonSize = 0L + var externalBlockStoreSize = 0L - def isCached: Boolean = (memSize + diskSize + tachyonSize > 0) && numCachedPartitions > 0 + def isCached: Boolean = + (memSize + diskSize + externalBlockStoreSize > 0) && numCachedPartitions > 0 override def toString: String = { import Utils.bytesToString val _scope = Option(scope).getOrElse("--") ("RDD \"%s\" (%d) StorageLevel: %s; CachedPartitions: %d; TotalPartitions: %d; " + - "MemorySize: %s; TachyonSize: %s; DiskSize: %s [scope: %s]").format( + "MemorySize: %s; ExternalBlockStoreSize: %s; DiskSize: %s [scope: %s]").format( name, id, storageLevel.toString, numCachedPartitions, numPartitions, - bytesToString(memSize), bytesToString(tachyonSize), bytesToString(diskSize), _scope) + bytesToString(memSize), bytesToString(externalBlockStoreSize), bytesToString(diskSize), + _scope) } override def compare(that: RDDInfo): Int = { diff --git a/core/src/main/scala/org/apache/spark/storage/ShuffleBlockFetcherIterator.scala b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockFetcherIterator.scala index f3379521d55e2..d0faab62c9e9e 100644 --- a/core/src/main/scala/org/apache/spark/storage/ShuffleBlockFetcherIterator.scala +++ b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockFetcherIterator.scala @@ -17,14 +17,12 @@ package org.apache.spark.storage -import java.io.{InputStream, IOException} import java.util.concurrent.LinkedBlockingQueue import scala.collection.mutable.{ArrayBuffer, HashSet, Queue} -import scala.util.{Failure, Success, Try} +import scala.util.{Failure, Try} import org.apache.spark.{Logging, TaskContext} -import org.apache.spark.network.BlockTransferService import org.apache.spark.network.shuffle.{BlockFetchingListener, ShuffleClient} import org.apache.spark.network.buffer.ManagedBuffer import org.apache.spark.serializer.{SerializerInstance, Serializer} @@ -301,7 +299,7 @@ final class ShuffleBlockFetcherIterator( // the scheduler gets a FetchFailedException. Try(buf.createInputStream()).map { is0 => val is = blockManager.wrapForCompression(blockId, is0) - val iter = serializerInstance.deserializeStream(is).asIterator + val iter = serializerInstance.deserializeStream(is).asKeyValueIterator CompletionIterator[Any, Iterator[Any]](iter, { // Once the iterator is exhausted, release the buffer and set currentResult to null // so we don't release it again in cleanup. diff --git a/core/src/main/scala/org/apache/spark/storage/StorageLevel.scala b/core/src/main/scala/org/apache/spark/storage/StorageLevel.scala index 134abea866218..703bce3e6b85b 100644 --- a/core/src/main/scala/org/apache/spark/storage/StorageLevel.scala +++ b/core/src/main/scala/org/apache/spark/storage/StorageLevel.scala @@ -26,9 +26,9 @@ import org.apache.spark.util.Utils /** * :: DeveloperApi :: * Flags for controlling the storage of an RDD. Each StorageLevel records whether to use memory, - * or Tachyon, whether to drop the RDD to disk if it falls out of memory or Tachyon , whether to - * keep the data in memory in a serialized format, and whether to replicate the RDD partitions on - * multiple nodes. + * or ExternalBlockStore, whether to drop the RDD to disk if it falls out of memory or + * ExternalBlockStore, whether to keep the data in memory in a serialized format, and whether + * to replicate the RDD partitions on multiple nodes. * * The [[org.apache.spark.storage.StorageLevel$]] singleton object contains some static constants * for commonly useful storage levels. To create your own storage level object, use the @@ -126,7 +126,7 @@ class StorageLevel private( var result = "" result += (if (useDisk) "Disk " else "") result += (if (useMemory) "Memory " else "") - result += (if (useOffHeap) "Tachyon " else "") + result += (if (useOffHeap) "ExternalBlockStore " else "") result += (if (deserialized) "Deserialized " else "Serialized ") result += s"${replication}x Replicated" result diff --git a/core/src/main/scala/org/apache/spark/storage/StorageUtils.scala b/core/src/main/scala/org/apache/spark/storage/StorageUtils.scala index 2bd6b749be261..c4ac30092f807 100644 --- a/core/src/main/scala/org/apache/spark/storage/StorageUtils.scala +++ b/core/src/main/scala/org/apache/spark/storage/StorageUtils.scala @@ -199,33 +199,34 @@ class StorageStatus(val blockManagerId: BlockManagerId, val maxMem: Long) { val oldBlockStatus = getBlock(blockId).getOrElse(BlockStatus.empty) val changeInMem = newBlockStatus.memSize - oldBlockStatus.memSize val changeInDisk = newBlockStatus.diskSize - oldBlockStatus.diskSize - val changeInTachyon = newBlockStatus.tachyonSize - oldBlockStatus.tachyonSize + val changeInExternalBlockStore = + newBlockStatus.externalBlockStoreSize - oldBlockStatus.externalBlockStoreSize val level = newBlockStatus.storageLevel // Compute new info from old info - val (oldMem, oldDisk, oldTachyon) = blockId match { + val (oldMem, oldDisk, oldExternalBlockStore) = blockId match { case RDDBlockId(rddId, _) => _rddStorageInfo.get(rddId) - .map { case (mem, disk, tachyon, _) => (mem, disk, tachyon) } + .map { case (mem, disk, externalBlockStore, _) => (mem, disk, externalBlockStore) } .getOrElse((0L, 0L, 0L)) case _ => _nonRddStorageInfo } val newMem = math.max(oldMem + changeInMem, 0L) val newDisk = math.max(oldDisk + changeInDisk, 0L) - val newTachyon = math.max(oldTachyon + changeInTachyon, 0L) + val newExternalBlockStore = math.max(oldExternalBlockStore + changeInExternalBlockStore, 0L) // Set the correct info blockId match { case RDDBlockId(rddId, _) => // If this RDD is no longer persisted, remove it - if (newMem + newDisk + newTachyon == 0) { + if (newMem + newDisk + newExternalBlockStore == 0) { _rddStorageInfo.remove(rddId) } else { - _rddStorageInfo(rddId) = (newMem, newDisk, newTachyon, level) + _rddStorageInfo(rddId) = (newMem, newDisk, newExternalBlockStore, level) } case _ => - _nonRddStorageInfo = (newMem, newDisk, newTachyon) + _nonRddStorageInfo = (newMem, newDisk, newExternalBlockStore) } } @@ -247,13 +248,13 @@ private[spark] object StorageUtils { val numCachedPartitions = statuses.map(_.numRddBlocksById(rddId)).sum val memSize = statuses.map(_.memUsedByRdd(rddId)).sum val diskSize = statuses.map(_.diskUsedByRdd(rddId)).sum - val tachyonSize = statuses.map(_.offHeapUsedByRdd(rddId)).sum + val externalBlockStoreSize = statuses.map(_.offHeapUsedByRdd(rddId)).sum rddInfo.storageLevel = storageLevel rddInfo.numCachedPartitions = numCachedPartitions rddInfo.memSize = memSize rddInfo.diskSize = diskSize - rddInfo.tachyonSize = tachyonSize + rddInfo.externalBlockStoreSize = externalBlockStoreSize } } diff --git a/core/src/main/scala/org/apache/spark/storage/TachyonBlockManager.scala b/core/src/main/scala/org/apache/spark/storage/TachyonBlockManager.scala index 583f1fdf0475b..bdc6276e41915 100644 --- a/core/src/main/scala/org/apache/spark/storage/TachyonBlockManager.scala +++ b/core/src/main/scala/org/apache/spark/storage/TachyonBlockManager.scala @@ -17,13 +17,16 @@ package org.apache.spark.storage +import java.io.IOException +import java.nio.ByteBuffer import java.text.SimpleDateFormat import java.util.{Date, Random} +import com.google.common.io.ByteStreams +import tachyon.client.{ReadType, WriteType, TachyonFS, TachyonFile} import tachyon.TachyonURI -import tachyon.client.{TachyonFile, TachyonFS} -import org.apache.spark.Logging +import org.apache.spark.{SparkException, SparkConf, Logging} import org.apache.spark.executor.ExecutorExitCode import org.apache.spark.util.Utils @@ -32,32 +35,94 @@ import org.apache.spark.util.Utils * Creates and maintains the logical mapping between logical blocks and tachyon fs locations. By * default, one block is mapped to one file with a name given by its BlockId. * - * @param rootDirs The directories to use for storing block files. Data will be hashed among these. */ -private[spark] class TachyonBlockManager( - blockManager: BlockManager, - rootDirs: String, - val master: String) - extends Logging { +private[spark] class TachyonBlockManager() extends ExternalBlockManager with Logging { - val client = if (master != null && master != "") TachyonFS.get(new TachyonURI(master)) else null - - if (client == null) { - logError("Failed to connect to the Tachyon as the master address is not configured") - System.exit(ExecutorExitCode.TACHYON_STORE_FAILED_TO_INITIALIZE) - } - - private val MAX_DIR_CREATION_ATTEMPTS = 10 - private val subDirsPerTachyonDir = - blockManager.conf.get("spark.tachyonStore.subDirectories", "64").toInt + var blockManager: BlockManager =_ + var rootDirs: String = _ + var master: String = _ + var client: tachyon.client.TachyonFS = _ + private var subDirsPerTachyonDir: Int = _ // Create one Tachyon directory for each path mentioned in spark.tachyonStore.folderName; // then, inside this directory, create multiple subdirectories that we will hash files into, // in order to avoid having really large inodes at the top level in Tachyon. - private val tachyonDirs: Array[TachyonFile] = createTachyonDirs() - private val subDirs = Array.fill(tachyonDirs.length)(new Array[TachyonFile](subDirsPerTachyonDir)) + private var tachyonDirs: Array[TachyonFile] = _ + private var subDirs: Array[Array[tachyon.client.TachyonFile]] = _ + + + override def init(blockManager: BlockManager, executorId: String): Unit = { + this.blockManager = blockManager + val storeDir = blockManager.conf.get(ExternalBlockStore.BASE_DIR, "/tmp_spark_tachyon") + val appFolderName = blockManager.conf.get(ExternalBlockStore.FOLD_NAME) + + rootDirs = s"$storeDir/$appFolderName/$executorId" + master = blockManager.conf.get(ExternalBlockStore.MASTER_URL, "tachyon://localhost:19998") + client = if (master != null && master != "") TachyonFS.get(new TachyonURI(master)) else null + // original implementation call System.exit, we change it to run without extblkstore support + if (client == null) { + logError("Failed to connect to the Tachyon as the master address is not configured") + throw new IOException("Failed to connect to the Tachyon as the master " + + "address is not configured") + } + subDirsPerTachyonDir = blockManager.conf.get("spark.externalBlockStore.subDirectories", + ExternalBlockStore.SUB_DIRS_PER_DIR).toInt + + // Create one Tachyon directory for each path mentioned in spark.tachyonStore.folderName; + // then, inside this directory, create multiple subdirectories that we will hash files into, + // in order to avoid having really large inodes at the top level in Tachyon. + tachyonDirs = createTachyonDirs() + subDirs = Array.fill(tachyonDirs.length)(new Array[TachyonFile](subDirsPerTachyonDir)) + tachyonDirs.foreach(tachyonDir => Utils.registerShutdownDeleteDir(tachyonDir)) + } + + override def toString: String = {"ExternalBlockStore-Tachyon"} + + override def removeBlock(blockId: BlockId): Boolean = { + val file = getFile(blockId) + if (fileExists(file)) { + removeFile(file) + } else { + false + } + } + + override def blockExists(blockId: BlockId): Boolean = { + val file = getFile(blockId) + fileExists(file) + } - addShutdownHook() + override def putBytes(blockId: BlockId, bytes: ByteBuffer): Unit = { + val file = getFile(blockId) + val os = file.getOutStream(WriteType.TRY_CACHE) + os.write(bytes.array()) + os.close() + } + + override def getBytes(blockId: BlockId): Option[ByteBuffer] = { + val file = getFile(blockId) + if (file == null || file.getLocationHosts.size == 0) { + return None + } + val is = file.getInStream(ReadType.CACHE) + assert (is != null) + try { + val size = file.length + val bs = new Array[Byte](size.asInstanceOf[Int]) + ByteStreams.readFully(is, bs) + Some(ByteBuffer.wrap(bs)) + } catch { + case ioe: IOException => + logWarning(s"Failed to fetch the block $blockId from Tachyon", ioe) + None + } finally { + is.close() + } + } + + override def getSize(blockId: BlockId): Long = { + getFile(blockId.name).length + } def removeFile(file: TachyonFile): Boolean = { client.delete(new TachyonURI(file.getPath()), false) @@ -109,7 +174,7 @@ private[spark] class TachyonBlockManager( var tachyonDirId: String = null var tries = 0 val rand = new Random() - while (!foundLocalDir && tries < MAX_DIR_CREATION_ATTEMPTS) { + while (!foundLocalDir && tries < ExternalBlockStore.MAX_DIR_CREATION_ATTEMPTS) { tries += 1 try { tachyonDirId = "%s-%04x".format(dateFormat.format(new Date), rand.nextInt(65536)) @@ -124,30 +189,27 @@ private[spark] class TachyonBlockManager( } } if (!foundLocalDir) { - logError("Failed " + MAX_DIR_CREATION_ATTEMPTS + " attempts to create tachyon dir in " + - rootDir) - System.exit(ExecutorExitCode.TACHYON_STORE_FAILED_TO_CREATE_DIR) + logError("Failed " + ExternalBlockStore.MAX_DIR_CREATION_ATTEMPTS + + " attempts to create tachyon dir in " + rootDir) + System.exit(ExecutorExitCode.EXTERNAL_BLOCK_STORE_FAILED_TO_CREATE_DIR) } logInfo("Created tachyon directory at " + tachyonDir) tachyonDir } } - private def addShutdownHook() { - tachyonDirs.foreach(tachyonDir => Utils.registerShutdownDeleteDir(tachyonDir)) - Utils.addShutdownHook { () => - logDebug("Shutdown hook called") - tachyonDirs.foreach { tachyonDir => - try { - if (!Utils.hasRootAsShutdownDeleteDir(tachyonDir)) { - Utils.deleteRecursively(tachyonDir, client) - } - } catch { - case e: Exception => - logError("Exception while deleting tachyon spark dir: " + tachyonDir, e) + override def shutdown() { + logDebug("Shutdown hook called") + tachyonDirs.foreach { tachyonDir => + try { + if (!Utils.hasRootAsShutdownDeleteDir(tachyonDir)) { + Utils.deleteRecursively(tachyonDir, client) } + } catch { + case e: Exception => + logError("Exception while deleting tachyon spark dir: " + tachyonDir, e) } - client.close() } + client.close() } } diff --git a/core/src/main/scala/org/apache/spark/storage/TachyonStore.scala b/core/src/main/scala/org/apache/spark/storage/TachyonStore.scala deleted file mode 100644 index 233d1e2b7c616..0000000000000 --- a/core/src/main/scala/org/apache/spark/storage/TachyonStore.scala +++ /dev/null @@ -1,128 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.storage - -import java.io.IOException -import java.nio.ByteBuffer - -import com.google.common.io.ByteStreams -import tachyon.client.{ReadType, WriteType} - -import org.apache.spark.Logging -import org.apache.spark.util.Utils - -/** - * Stores BlockManager blocks on Tachyon. - */ -private[spark] class TachyonStore( - blockManager: BlockManager, - tachyonManager: TachyonBlockManager) - extends BlockStore(blockManager: BlockManager) with Logging { - - logInfo("TachyonStore started") - - override def getSize(blockId: BlockId): Long = { - tachyonManager.getFile(blockId.name).length - } - - override def putBytes(blockId: BlockId, bytes: ByteBuffer, level: StorageLevel): PutResult = { - putIntoTachyonStore(blockId, bytes, returnValues = true) - } - - override def putArray( - blockId: BlockId, - values: Array[Any], - level: StorageLevel, - returnValues: Boolean): PutResult = { - putIterator(blockId, values.toIterator, level, returnValues) - } - - override def putIterator( - blockId: BlockId, - values: Iterator[Any], - level: StorageLevel, - returnValues: Boolean): PutResult = { - logDebug(s"Attempting to write values for block $blockId") - val bytes = blockManager.dataSerialize(blockId, values) - putIntoTachyonStore(blockId, bytes, returnValues) - } - - private def putIntoTachyonStore( - blockId: BlockId, - bytes: ByteBuffer, - returnValues: Boolean): PutResult = { - // So that we do not modify the input offsets ! - // duplicate does not copy buffer, so inexpensive - val byteBuffer = bytes.duplicate() - byteBuffer.rewind() - logDebug(s"Attempting to put block $blockId into Tachyon") - val startTime = System.currentTimeMillis - val file = tachyonManager.getFile(blockId) - val os = file.getOutStream(WriteType.TRY_CACHE) - os.write(byteBuffer.array()) - os.close() - val finishTime = System.currentTimeMillis - logDebug("Block %s stored as %s file in Tachyon in %d ms".format( - blockId, Utils.bytesToString(byteBuffer.limit), finishTime - startTime)) - - if (returnValues) { - PutResult(bytes.limit(), Right(bytes.duplicate())) - } else { - PutResult(bytes.limit(), null) - } - } - - override def remove(blockId: BlockId): Boolean = { - val file = tachyonManager.getFile(blockId) - if (tachyonManager.fileExists(file)) { - tachyonManager.removeFile(file) - } else { - false - } - } - - override def getValues(blockId: BlockId): Option[Iterator[Any]] = { - getBytes(blockId).map(buffer => blockManager.dataDeserialize(blockId, buffer)) - } - - override def getBytes(blockId: BlockId): Option[ByteBuffer] = { - val file = tachyonManager.getFile(blockId) - if (file == null || file.getLocationHosts.size == 0) { - return None - } - val is = file.getInStream(ReadType.CACHE) - assert (is != null) - try { - val size = file.length - val bs = new Array[Byte](size.asInstanceOf[Int]) - ByteStreams.readFully(is, bs) - Some(ByteBuffer.wrap(bs)) - } catch { - case ioe: IOException => - logWarning(s"Failed to fetch the block $blockId from Tachyon", ioe) - None - } finally { - is.close() - } - } - - override def contains(blockId: BlockId): Boolean = { - val file = tachyonManager.getFile(blockId) - tachyonManager.fileExists(file) - } -} diff --git a/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala b/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala index a091ca650c60c..dfd6fdb5e9993 100644 --- a/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala +++ b/core/src/main/scala/org/apache/spark/ui/JettyUtils.scala @@ -115,19 +115,21 @@ private[spark] object JettyUtils extends Logging { destPath: String, beforeRedirect: HttpServletRequest => Unit = x => (), basePath: String = "", - httpMethod: String = "GET"): ServletContextHandler = { + httpMethods: Set[String] = Set("GET")): ServletContextHandler = { val prefixedDestPath = attachPrefix(basePath, destPath) val servlet = new HttpServlet { override def doGet(request: HttpServletRequest, response: HttpServletResponse): Unit = { - httpMethod match { - case "GET" => doRequest(request, response) - case _ => response.sendError(HttpServletResponse.SC_METHOD_NOT_ALLOWED) + if (httpMethods.contains("GET")) { + doRequest(request, response) + } else { + response.sendError(HttpServletResponse.SC_METHOD_NOT_ALLOWED) } } override def doPost(request: HttpServletRequest, response: HttpServletResponse): Unit = { - httpMethod match { - case "POST" => doRequest(request, response) - case _ => response.sendError(HttpServletResponse.SC_METHOD_NOT_ALLOWED) + if (httpMethods.contains("POST")) { + doRequest(request, response) + } else { + response.sendError(HttpServletResponse.SC_METHOD_NOT_ALLOWED) } } private def doRequest(request: HttpServletRequest, response: HttpServletResponse): Unit = { diff --git a/core/src/main/scala/org/apache/spark/ui/SparkUI.scala b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala index caac58abb0af4..dabfb5900ea0d 100644 --- a/core/src/main/scala/org/apache/spark/ui/SparkUI.scala +++ b/core/src/main/scala/org/apache/spark/ui/SparkUI.scala @@ -57,8 +57,10 @@ private[spark] class SparkUI private ( attachTab(new ExecutorsTab(this)) attachHandler(createStaticHandler(SparkUI.STATIC_RESOURCE_DIR, "/static")) attachHandler(createRedirectHandler("/", "/jobs", basePath = basePath)) + // This should be POST only, but, the YARN AM proxy won't proxy POSTs attachHandler(createRedirectHandler( - "/stages/stage/kill", "/stages", stagesTab.handleKillRequest, httpMethod = "POST")) + "/stages/stage/kill", "/stages", stagesTab.handleKillRequest, + httpMethods = Set("GET", "POST"))) } initialize() diff --git a/core/src/main/scala/org/apache/spark/ui/UIUtils.scala b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala index 8836e09f0e182..80e93977b6e15 100644 --- a/core/src/main/scala/org/apache/spark/ui/UIUtils.scala +++ b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala @@ -159,12 +159,17 @@ private[spark] object UIUtils extends Logging { type="text/css" /> + + + + } def vizHeaderNodes: Seq[Node] = { diff --git a/core/src/main/scala/org/apache/spark/ui/exec/ExecutorsTab.scala b/core/src/main/scala/org/apache/spark/ui/exec/ExecutorsTab.scala index 69053fe44d7e4..0a08b000e2d03 100644 --- a/core/src/main/scala/org/apache/spark/ui/exec/ExecutorsTab.scala +++ b/core/src/main/scala/org/apache/spark/ui/exec/ExecutorsTab.scala @@ -24,6 +24,7 @@ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.scheduler._ import org.apache.spark.storage.{StorageStatus, StorageStatusListener} import org.apache.spark.ui.{SparkUI, SparkUITab} +import org.apache.spark.ui.jobs.UIData.ExecutorUIData private[ui] class ExecutorsTab(parent: SparkUI) extends SparkUITab(parent, "executors") { val listener = parent.executorsListener @@ -54,12 +55,22 @@ class ExecutorsListener(storageStatusListener: StorageStatusListener) extends Sp val executorToShuffleRead = HashMap[String, Long]() val executorToShuffleWrite = HashMap[String, Long]() val executorToLogUrls = HashMap[String, Map[String, String]]() + val executorIdToData = HashMap[String, ExecutorUIData]() def storageStatusList: Seq[StorageStatus] = storageStatusListener.storageStatusList override def onExecutorAdded(executorAdded: SparkListenerExecutorAdded): Unit = synchronized { val eid = executorAdded.executorId executorToLogUrls(eid) = executorAdded.executorInfo.logUrlMap + executorIdToData(eid) = ExecutorUIData(executorAdded.time) + } + + override def onExecutorRemoved( + executorRemoved: SparkListenerExecutorRemoved): Unit = synchronized { + val eid = executorRemoved.executorId + val uiData = executorIdToData(eid) + uiData.finishTime = Some(executorRemoved.time) + uiData.finishReason = Some(executorRemoved.reason) } override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = synchronized { diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala index bd923d78a86ce..a7ea12b1655fe 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala @@ -17,17 +17,183 @@ package org.apache.spark.ui.jobs -import scala.xml.{Node, NodeSeq} +import scala.collection.mutable.{HashMap, ListBuffer} +import scala.xml.{Node, NodeSeq, Unparsed} +import java.util.Date import javax.servlet.http.HttpServletRequest -import org.apache.spark.ui.{WebUIPage, UIUtils} -import org.apache.spark.ui.jobs.UIData.JobUIData +import org.apache.spark.ui.{UIUtils, WebUIPage} +import org.apache.spark.ui.jobs.UIData.{ExecutorUIData, JobUIData} +import org.apache.spark.JobExecutionStatus /** Page showing list of all ongoing and recently finished jobs */ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { - private val startTime: Option[Long] = parent.sc.map(_.startTime) - private val listener = parent.listener + private val JOBS_LEGEND = +
+ + Succeeded + + Failed + + Running +
.toString.filter(_ != '\n') + + private val EXECUTORS_LEGEND = +
+ + Added + + Removed +
.toString.filter(_ != '\n') + + private def getLastStageNameAndDescription(job: JobUIData): (String, String) = { + val lastStageInfo = Option(job.stageIds) + .filter(_.nonEmpty) + .flatMap { ids => parent.jobProgresslistener.stageIdToInfo.get(ids.max)} + val lastStageData = lastStageInfo.flatMap { s => + parent.jobProgresslistener.stageIdToData.get((s.stageId, s.attemptId)) + } + val name = lastStageInfo.map(_.name).getOrElse("(Unknown Stage Name)") + val description = lastStageData.flatMap(_.description).getOrElse("") + (name, description) + } + + private def makeJobEvent(jobUIDatas: Seq[JobUIData]): Seq[String] = { + jobUIDatas.filter { jobUIData => + jobUIData.status != JobExecutionStatus.UNKNOWN && jobUIData.submissionTime.isDefined + }.map { jobUIData => + val jobId = jobUIData.jobId + val status = jobUIData.status + val (jobName, jobDescription) = getLastStageNameAndDescription(jobUIData) + val displayJobDescription = if (jobDescription.isEmpty) jobName else jobDescription + val submissionTime = jobUIData.submissionTime.get + val completionTimeOpt = jobUIData.completionTime + val completionTime = completionTimeOpt.getOrElse(System.currentTimeMillis()) + val classNameByStatus = status match { + case JobExecutionStatus.SUCCEEDED => "succeeded" + case JobExecutionStatus.FAILED => "failed" + case JobExecutionStatus.RUNNING => "running" + } + + val jobEventJsonAsStr = + s""" + |{ + | 'className': 'job application-timeline-object ${classNameByStatus}', + | 'group': 'jobs', + | 'start': new Date(${submissionTime}), + | 'end': new Date(${completionTime}), + | 'content': '
Completion Time: ${UIUtils.formatDate(new Date(completionTime))}""" + } else { + "" + } + }">' + + | '${displayJobDescription} (Job ${jobId})
' + |} + """.stripMargin + jobEventJsonAsStr + } + } + + private def makeExecutorEvent(executorUIDatas: HashMap[String, ExecutorUIData]): Seq[String] = { + val events = ListBuffer[String]() + executorUIDatas.foreach { + case (executorId, event) => + val addedEvent = + s""" + |{ + | 'className': 'executor added', + | 'group': 'executors', + | 'start': new Date(${event.startTime}), + | 'content': '
Executor ${executorId} added
' + |} + """.stripMargin + events += addedEvent + + if (event.finishTime.isDefined) { + val removedEvent = + s""" + |{ + | 'className': 'executor removed', + | 'group': 'executors', + | 'start': new Date(${event.finishTime.get}), + | 'content': '
Reason: ${event.finishReason.get}""" + } else { + "" + } + }"' + + | 'data-html="true">Executor ${executorId} removed
' + |} + """.stripMargin + events += removedEvent + } + } + events.toSeq + } + + private def makeTimeline( + jobs: Seq[JobUIData], + executors: HashMap[String, ExecutorUIData], + startTime: Long): Seq[Node] = { + + val jobEventJsonAsStrSeq = makeJobEvent(jobs) + val executorEventJsonAsStrSeq = makeExecutorEvent(executors) + + val groupJsonArrayAsStr = + s""" + |[ + | { + | 'id': 'executors', + | 'content': '
Executors
${EXECUTORS_LEGEND}', + | }, + | { + | 'id': 'jobs', + | 'content': '
Jobs
${JOBS_LEGEND}', + | } + |] + """.stripMargin + + val eventArrayAsStr = + (jobEventJsonAsStrSeq ++ executorEventJsonAsStrSeq).mkString("[", ",", "]") + + + + Event Timeline + ++ + ++ + + } private def jobsTable(jobs: Seq[JobUIData]): Seq[Node] = { val someJobHasJobGroup = jobs.exists(_.jobGroup.isDefined) @@ -42,15 +208,7 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { } def makeRow(job: JobUIData): Seq[Node] = { - val lastStageInfo = Option(job.stageIds) - .filter(_.nonEmpty) - .flatMap { ids => listener.stageIdToInfo.get(ids.max) } - val lastStageData = lastStageInfo.flatMap { s => - listener.stageIdToData.get((s.stageId, s.attemptId)) - } - - val lastStageName = lastStageInfo.map(_.name).getOrElse("(Unknown Stage Name)") - val lastStageDescription = lastStageData.flatMap(_.description).getOrElse("") + val (lastStageName, lastStageDescription) = getLastStageNameAndDescription(job) val duration: Option[Long] = { job.submissionTime.map { start => val end = job.completionTime.getOrElse(System.currentTimeMillis()) @@ -61,7 +219,7 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { val formattedSubmissionTime = job.submissionTime.map(UIUtils.formatDate).getOrElse("Unknown") val detailUrl = "%s/jobs/job?id=%s".format(UIUtils.prependBaseUri(parent.basePath), job.jobId) - + {job.jobId} {job.jobGroup.map(id => s"($id)").getOrElse("")} @@ -95,11 +253,12 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { } def render(request: HttpServletRequest): Seq[Node] = { + val listener = parent.jobProgresslistener listener.synchronized { + val startTime = listener.startTime val activeJobs = listener.activeJobs.values.toSeq val completedJobs = listener.completedJobs.reverse.toSeq val failedJobs = listener.failedJobs.reverse.toSeq - val now = System.currentTimeMillis val activeJobsTable = jobsTable(activeJobs.sortBy(_.submissionTime.getOrElse(-1L)).reverse) @@ -115,11 +274,11 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { val summary: NodeSeq =
    - {if (startTime.isDefined) { + {if (parent.sc.isDefined) { // Total duration is not meaningful unless the UI is live
  • Total Duration: - {UIUtils.formatDuration(now - startTime.get)} + {UIUtils.formatDuration(System.currentTimeMillis() - startTime)}
    • }}
  • @@ -154,6 +313,10 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") {
var content = summary + val executorListener = parent.executorListener + content ++= makeTimeline(activeJobs ++ completedJobs ++ failedJobs, + executorListener.executorIdToData, startTime) + if (shouldShowActiveJobs) { content ++=

Active Jobs ({activeJobs.size})

++ activeJobsTable @@ -166,6 +329,7 @@ private[ui] class AllJobsPage(parent: JobsTab) extends WebUIPage("") { content ++=

Failed Jobs ({failedJobs.size})

++ failedJobsTable } + val helpText = """A job is triggered by an action, like "count()" or "saveAsTextFile()".""" + " Click on a job's title to see information about the stages of tasks associated with" + " the job." diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/JobPage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/JobPage.scala index 5a370d0363882..f3a515901d7ce 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/JobPage.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/JobPage.scala @@ -17,21 +17,168 @@ package org.apache.spark.ui.jobs -import scala.collection.mutable -import scala.xml.{NodeSeq, Node} +import java.util.Date + +import scala.collection.mutable.{Buffer, HashMap, ListBuffer} +import scala.xml.{NodeSeq, Node, Unparsed} import javax.servlet.http.HttpServletRequest import org.apache.spark.JobExecutionStatus import org.apache.spark.scheduler.StageInfo import org.apache.spark.ui.{UIUtils, WebUIPage} +import org.apache.spark.ui.jobs.UIData.ExecutorUIData /** Page showing statistics and stage list for a given job */ private[ui] class JobPage(parent: JobsTab) extends WebUIPage("job") { - private val listener = parent.listener - private val vizListener = parent.vizListener + + private val STAGES_LEGEND = +
+ + Completed + + Failed + + Active +
.toString.filter(_ != '\n') + + private val EXECUTORS_LEGEND = +
+ + Added + + Removed +
.toString.filter(_ != '\n') + + private def makeStageEvent(stageInfos: Seq[StageInfo]): Seq[String] = { + stageInfos.map { stage => + val stageId = stage.stageId + val attemptId = stage.attemptId + val name = stage.name + val status = stage.getStatusString + val submissionTime = stage.submissionTime.get + val completionTime = stage.completionTime.getOrElse(System.currentTimeMillis()) + + s""" + |{ + | 'className': 'stage job-timeline-object ${status}', + | 'group': 'stages', + | 'start': new Date(${submissionTime}), + | 'end': new Date(${completionTime}), + | 'content': '
Completion Time: ${UIUtils.formatDate(new Date(completionTime))}""" + } else { + "" + } + }">' + + | '${name} (Stage ${stageId}.${attemptId})
', + |} + """.stripMargin + } + } + + def makeExecutorEvent(executorUIDatas: HashMap[String, ExecutorUIData]): Seq[String] = { + val events = ListBuffer[String]() + executorUIDatas.foreach { + case (executorId, event) => + val addedEvent = + s""" + |{ + | 'className': 'executor added', + | 'group': 'executors', + | 'start': new Date(${event.startTime}), + | 'content': '
Executor ${executorId} added
' + |} + """.stripMargin + events += addedEvent + + if (event.finishTime.isDefined) { + val removedEvent = + s""" + |{ + | 'className': 'executor removed', + | 'group': 'executors', + | 'start': new Date(${event.finishTime.get}), + | 'content': '
Reason: ${event.finishReason.get}""" + } else { + "" + } + }"' + + | 'data-html="true">Executor ${executorId} removed
' + |} + """.stripMargin + events += removedEvent + } + } + events.toSeq + } + + private def makeTimeline( + stages: Seq[StageInfo], + executors: HashMap[String, ExecutorUIData], + appStartTime: Long): Seq[Node] = { + + val stageEventJsonAsStrSeq = makeStageEvent(stages) + val executorsJsonAsStrSeq = makeExecutorEvent(executors) + + val groupJsonArrayAsStr = + s""" + |[ + | { + | 'id': 'executors', + | 'content': '
Executors
${EXECUTORS_LEGEND}', + | }, + | { + | 'id': 'stages', + | 'content': '
Stages
${STAGES_LEGEND}', + | } + |] + """.stripMargin + + val eventArrayAsStr = + (stageEventJsonAsStrSeq ++ executorsJsonAsStrSeq).mkString("[", ",", "]") + + + + Event Timeline + ++ + ++ + + } def render(request: HttpServletRequest): Seq[Node] = { + val listener = parent.jobProgresslistener + listener.synchronized { val parameterId = request.getParameter("id") require(parameterId != null && parameterId.nonEmpty, "Missing id parameter") @@ -55,11 +202,11 @@ private[ui] class JobPage(parent: JobsTab) extends WebUIPage("job") { new StageInfo(stageId, 0, "Unknown", 0, Seq.empty, Seq.empty, "Unknown")) } - val activeStages = mutable.Buffer[StageInfo]() - val completedStages = mutable.Buffer[StageInfo]() + val activeStages = Buffer[StageInfo]() + val completedStages = Buffer[StageInfo]() // If the job is completed, then any pending stages are displayed as "skipped": - val pendingOrSkippedStages = mutable.Buffer[StageInfo]() - val failedStages = mutable.Buffer[StageInfo]() + val pendingOrSkippedStages = Buffer[StageInfo]() + val failedStages = Buffer[StageInfo]() for (stage <- stages) { if (stage.submissionTime.isEmpty) { pendingOrSkippedStages += stage @@ -76,18 +223,18 @@ private[ui] class JobPage(parent: JobsTab) extends WebUIPage("job") { val activeStagesTable = new StageTableBase(activeStages.sortBy(_.submissionTime).reverse, - parent.basePath, parent.listener, isFairScheduler = parent.isFairScheduler, + parent.basePath, parent.jobProgresslistener, isFairScheduler = parent.isFairScheduler, killEnabled = parent.killEnabled) val pendingOrSkippedStagesTable = new StageTableBase(pendingOrSkippedStages.sortBy(_.stageId).reverse, - parent.basePath, parent.listener, isFairScheduler = parent.isFairScheduler, + parent.basePath, parent.jobProgresslistener, isFairScheduler = parent.isFairScheduler, killEnabled = false) val completedStagesTable = new StageTableBase(completedStages.sortBy(_.submissionTime).reverse, parent.basePath, - parent.listener, isFairScheduler = parent.isFairScheduler, killEnabled = false) + parent.jobProgresslistener, isFairScheduler = parent.isFairScheduler, killEnabled = false) val failedStagesTable = new FailedStageTable(failedStages.sortBy(_.submissionTime).reverse, parent.basePath, - parent.listener, isFairScheduler = parent.isFairScheduler) + parent.jobProgresslistener, isFairScheduler = parent.isFairScheduler) val shouldShowActiveStages = activeStages.nonEmpty val shouldShowPendingStages = !isComplete && pendingOrSkippedStages.nonEmpty @@ -155,7 +302,15 @@ private[ui] class JobPage(parent: JobsTab) extends WebUIPage("job") {

var content = summary + val appStartTime = listener.startTime + val executorListener = parent.executorListener + val vizListener = parent.vizListener + + content ++= makeTimeline(activeStages ++ completedStages ++ failedStages, + executorListener.executorIdToData, appStartTime) + content ++= vizListener.showVizElementForJob(jobId) + if (shouldShowActiveStages) { content ++=

Active Stages ({activeStages.size})

++ activeStagesTable.toNodeSeq diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala index 33e9baffb7910..8f9aa9fdec819 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/JobProgressListener.scala @@ -49,6 +49,9 @@ class JobProgressListener(conf: SparkConf) extends SparkListener with Logging { type PoolName = String type ExecutorId = String + // Applicatin: + @volatile var startTime = -1L + // Jobs: val activeJobs = new HashMap[JobId, JobUIData] val completedJobs = ListBuffer[JobUIData]() @@ -74,6 +77,7 @@ class JobProgressListener(conf: SparkConf) extends SparkListener with Logging { // Misc: val executorIdToBlockManagerId = HashMap[ExecutorId, BlockManagerId]() + def blockManagerIds: Seq[BlockManagerId] = executorIdToBlockManagerId.values.toSeq var schedulingMode: Option[SchedulingMode] = None @@ -515,4 +519,7 @@ class JobProgressListener(conf: SparkConf) extends SparkListener with Logging { } } + override def onApplicationStart(appStarted: SparkListenerApplicationStart) { + startTime = appStarted.time + } } diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/JobsTab.scala b/core/src/main/scala/org/apache/spark/ui/jobs/JobsTab.scala index db76497ddcae8..4288a7bad55c8 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/JobsTab.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/JobsTab.scala @@ -24,11 +24,13 @@ import org.apache.spark.ui.{SparkUI, SparkUITab} private[ui] class JobsTab(parent: SparkUI) extends SparkUITab(parent, "jobs") { val sc = parent.sc val killEnabled = parent.killEnabled - def isFairScheduler: Boolean = listener.schedulingMode.exists(_ == SchedulingMode.FAIR) - // TODO: rename this listener - val listener = parent.jobProgressListener + val jobProgresslistener = parent.jobProgressListener + val executorListener = parent.executorsListener val vizListener = parent.visualizationListener + def isFairScheduler: Boolean = + jobProgresslistener.schedulingMode.exists(_ == SchedulingMode.FAIR) + attachPage(new AllJobsPage(this)) attachPage(new JobPage(this)) } diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/StageTable.scala b/core/src/main/scala/org/apache/spark/ui/jobs/StageTable.scala index cb72890a0fd20..a33243d4252bf 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/StageTable.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/StageTable.scala @@ -76,15 +76,20 @@ private[ui] class StageTableBase( val basePathUri = UIUtils.prependBaseUri(basePath) val killLink = if (killEnabled) { - val killLinkUri = s"$basePathUri/stages/stage/kill/" val confirm = s"if (window.confirm('Are you sure you want to kill stage ${s.stageId} ?')) " + "{ this.parentNode.submit(); return true; } else { return false; }" + // SPARK-6846 this should be POST-only but YARN AM won't proxy POST + /* + val killLinkUri = s"$basePathUri/stages/stage/kill/"
(kill)
+ */ + val killLinkUri = s"$basePathUri/stages/stage/kill/?id=${s.stageId}&terminate=true" + (kill) } val nameLinkUri = s"$basePathUri/stages/stage?id=${s.stageId}&attempt=${s.attemptId}" @@ -174,7 +179,8 @@ private[ui] class StageTableBase( } /** Render an HTML row that represents a stage */ - private def renderStageRow(s: StageInfo): Seq[Node] = {stageRow(s)} + private def renderStageRow(s: StageInfo): Seq[Node] = + {stageRow(s)} } private[ui] class FailedStageTable( diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala b/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala index 711a3697bda15..3d96113aa5fe9 100644 --- a/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala +++ b/core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala @@ -24,7 +24,7 @@ import org.apache.spark.util.collection.OpenHashSet import scala.collection.mutable.HashMap -private[jobs] object UIData { +private[spark] object UIData { class ExecutorSummary { var taskTime : Long = 0 @@ -108,4 +108,9 @@ private[jobs] object UIData { var taskInfo: TaskInfo, var taskMetrics: Option[TaskMetrics] = None, var errorMessage: Option[String] = None) + + case class ExecutorUIData( + val startTime: Long, + var finishTime: Option[Long] = None, + var finishReason: Option[String] = None) } diff --git a/core/src/main/scala/org/apache/spark/ui/storage/StoragePage.scala b/core/src/main/scala/org/apache/spark/ui/storage/StoragePage.scala index 6ced6052d2b18..59dc6b547c1d8 100644 --- a/core/src/main/scala/org/apache/spark/ui/storage/StoragePage.scala +++ b/core/src/main/scala/org/apache/spark/ui/storage/StoragePage.scala @@ -42,7 +42,7 @@ private[ui] class StoragePage(parent: StorageTab) extends WebUIPage("") { "Cached Partitions", "Fraction Cached", "Size in Memory", - "Size in Tachyon", + "Size in ExternalBlockStore", "Size on Disk") /** Render an HTML row representing an RDD */ @@ -59,7 +59,7 @@ private[ui] class StoragePage(parent: StorageTab) extends WebUIPage("") { {rdd.numCachedPartitions} {"%.0f%%".format(rdd.numCachedPartitions * 100.0 / rdd.numPartitions)} {Utils.bytesToString(rdd.memSize)} - {Utils.bytesToString(rdd.tachyonSize)} + {Utils.bytesToString(rdd.externalBlockStoreSize)} {Utils.bytesToString(rdd.diskSize)} // scalastyle:on diff --git a/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala b/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala index e3f52f6ff1e63..4ac0382d80815 100644 --- a/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala +++ b/core/src/main/scala/org/apache/spark/util/ClosureCleaner.scala @@ -19,17 +19,20 @@ package org.apache.spark.util import java.io.{ByteArrayInputStream, ByteArrayOutputStream} -import scala.collection.mutable.Map -import scala.collection.mutable.Set +import scala.collection.mutable.{Map, Set} import com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.{ClassReader, ClassVisitor, MethodVisitor, Type} import com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.Opcodes._ import org.apache.spark.{Logging, SparkEnv, SparkException} +/** + * A cleaner that renders closures serializable if they can be done so safely. + */ private[spark] object ClosureCleaner extends Logging { + // Get an ASM class reader for a given class from the JAR that loaded it - private def getClassReader(cls: Class[_]): ClassReader = { + private[util] def getClassReader(cls: Class[_]): ClassReader = { // Copy data over, before delegating to ClassReader - else we can run out of open file handles. val className = cls.getName.replaceFirst("^.*\\.", "") + ".class" val resourceStream = cls.getResourceAsStream(className) @@ -55,10 +58,14 @@ private[spark] object ClosureCleaner extends Logging { private def getOuterClasses(obj: AnyRef): List[Class[_]] = { for (f <- obj.getClass.getDeclaredFields if f.getName == "$outer") { f.setAccessible(true) - if (isClosure(f.getType)) { - return f.getType :: getOuterClasses(f.get(obj)) - } else { - return f.getType :: Nil // Stop at the first $outer that is not a closure + val outer = f.get(obj) + // The outer pointer may be null if we have cleaned this closure before + if (outer != null) { + if (isClosure(f.getType)) { + return f.getType :: getOuterClasses(outer) + } else { + return f.getType :: Nil // Stop at the first $outer that is not a closure + } } } Nil @@ -68,16 +75,23 @@ private[spark] object ClosureCleaner extends Logging { private def getOuterObjects(obj: AnyRef): List[AnyRef] = { for (f <- obj.getClass.getDeclaredFields if f.getName == "$outer") { f.setAccessible(true) - if (isClosure(f.getType)) { - return f.get(obj) :: getOuterObjects(f.get(obj)) - } else { - return f.get(obj) :: Nil // Stop at the first $outer that is not a closure + val outer = f.get(obj) + // The outer pointer may be null if we have cleaned this closure before + if (outer != null) { + if (isClosure(f.getType)) { + return outer :: getOuterObjects(outer) + } else { + return outer :: Nil // Stop at the first $outer that is not a closure + } } } Nil } - private def getInnerClasses(obj: AnyRef): List[Class[_]] = { + /** + * Return a list of classes that represent closures enclosed in the given closure object. + */ + private def getInnerClosureClasses(obj: AnyRef): List[Class[_]] = { val seen = Set[Class[_]](obj.getClass) var stack = List[Class[_]](obj.getClass) while (!stack.isEmpty) { @@ -90,7 +104,7 @@ private[spark] object ClosureCleaner extends Logging { stack = cls :: stack } } - return (seen - obj.getClass).toList + (seen - obj.getClass).toList } private def createNullValue(cls: Class[_]): AnyRef = { @@ -101,21 +115,124 @@ private[spark] object ClosureCleaner extends Logging { } } - def clean(func: AnyRef, checkSerializable: Boolean = true) { + /** + * Clean the given closure in place. + * + * More specifically, this renders the given closure serializable as long as it does not + * explicitly reference unserializable objects. + * + * @param closure the closure to clean + * @param checkSerializable whether to verify that the closure is serializable after cleaning + * @param cleanTransitively whether to clean enclosing closures transitively + */ + def clean( + closure: AnyRef, + checkSerializable: Boolean = true, + cleanTransitively: Boolean = true): Unit = { + clean(closure, checkSerializable, cleanTransitively, Map.empty) + } + + /** + * Helper method to clean the given closure in place. + * + * The mechanism is to traverse the hierarchy of enclosing closures and null out any + * references along the way that are not actually used by the starting closure, but are + * nevertheless included in the compiled anonymous classes. Note that it is unsafe to + * simply mutate the enclosing closures in place, as other code paths may depend on them. + * Instead, we clone each enclosing closure and set the parent pointers accordingly. + * + * By default, closures are cleaned transitively. This means we detect whether enclosing + * objects are actually referenced by the starting one, either directly or transitively, + * and, if not, sever these closures from the hierarchy. In other words, in addition to + * nulling out unused field references, we also null out any parent pointers that refer + * to enclosing objects not actually needed by the starting closure. We determine + * transitivity by tracing through the tree of all methods ultimately invoked by the + * inner closure and record all the fields referenced in the process. + * + * For instance, transitive cleaning is necessary in the following scenario: + * + * class SomethingNotSerializable { + * def someValue = 1 + * def scope(name: String)(body: => Unit) = body + * def someMethod(): Unit = scope("one") { + * def x = someValue + * def y = 2 + * scope("two") { println(y + 1) } + * } + * } + * + * In this example, scope "two" is not serializable because it references scope "one", which + * references SomethingNotSerializable. Note that, however, the body of scope "two" does not + * actually depend on SomethingNotSerializable. This means we can safely null out the parent + * pointer of a cloned scope "one" and set it the parent of scope "two", such that scope "two" + * no longer references SomethingNotSerializable transitively. + * + * @param func the starting closure to clean + * @param checkSerializable whether to verify that the closure is serializable after cleaning + * @param cleanTransitively whether to clean enclosing closures transitively + * @param accessedFields a map from a class to a set of its fields that are accessed by + * the starting closure + */ + private def clean( + func: AnyRef, + checkSerializable: Boolean, + cleanTransitively: Boolean, + accessedFields: Map[Class[_], Set[String]]): Unit = { + + // TODO: clean all inner closures first. This requires us to find the inner objects. // TODO: cache outerClasses / innerClasses / accessedFields + + if (func == null) { + return + } + + logDebug(s"+++ Cleaning closure $func (${func.getClass.getName}}) +++") + + // A list of classes that represents closures enclosed in the given one + val innerClasses = getInnerClosureClasses(func) + + // A list of enclosing objects and their respective classes, from innermost to outermost + // An outer object at a given index is of type outer class at the same index val outerClasses = getOuterClasses(func) - val innerClasses = getInnerClasses(func) val outerObjects = getOuterObjects(func) - val accessedFields = Map[Class[_], Set[String]]() - + // For logging purposes only + val declaredFields = func.getClass.getDeclaredFields + val declaredMethods = func.getClass.getDeclaredMethods + + logDebug(" + declared fields: " + declaredFields.size) + declaredFields.foreach { f => logDebug(" " + f) } + logDebug(" + declared methods: " + declaredMethods.size) + declaredMethods.foreach { m => logDebug(" " + m) } + logDebug(" + inner classes: " + innerClasses.size) + innerClasses.foreach { c => logDebug(" " + c.getName) } + logDebug(" + outer classes: " + outerClasses.size) + outerClasses.foreach { c => logDebug(" " + c.getName) } + logDebug(" + outer objects: " + outerObjects.size) + outerObjects.foreach { o => logDebug(" " + o) } + + // Fail fast if we detect return statements in closures getClassReader(func.getClass).accept(new ReturnStatementFinder(), 0) - - for (cls <- outerClasses) - accessedFields(cls) = Set[String]() - for (cls <- func.getClass :: innerClasses) - getClassReader(cls).accept(new FieldAccessFinder(accessedFields), 0) - // logInfo("accessedFields: " + accessedFields) + + // If accessed fields is not populated yet, we assume that + // the closure we are trying to clean is the starting one + if (accessedFields.isEmpty) { + logDebug(s" + populating accessed fields because this is the starting closure") + // Initialize accessed fields with the outer classes first + // This step is needed to associate the fields to the correct classes later + for (cls <- outerClasses) { + accessedFields(cls) = Set[String]() + } + // Populate accessed fields by visiting all fields and methods accessed by this and + // all of its inner closures. If transitive cleaning is enabled, this may recursively + // visits methods that belong to other classes in search of transitively referenced fields. + for (cls <- func.getClass :: innerClasses) { + getClassReader(cls).accept(new FieldAccessFinder(accessedFields, cleanTransitively), 0) + } + } + + logDebug(s" + fields accessed by starting closure: " + accessedFields.size) + accessedFields.foreach { f => logDebug(" " + f) } val inInterpreter = { try { @@ -126,34 +243,68 @@ private[spark] object ClosureCleaner extends Logging { } } + // List of outer (class, object) pairs, ordered from outermost to innermost + // Note that all outer objects but the outermost one (first one in this list) must be closures var outerPairs: List[(Class[_], AnyRef)] = (outerClasses zip outerObjects).reverse - var outer: AnyRef = null + var parent: AnyRef = null if (outerPairs.size > 0 && !isClosure(outerPairs.head._1)) { // The closure is ultimately nested inside a class; keep the object of that // class without cloning it since we don't want to clone the user's objects. - outer = outerPairs.head._2 + // Note that we still need to keep around the outermost object itself because + // we need it to clone its child closure later (see below). + logDebug(s" + outermost object is not a closure, so do not clone it: ${outerPairs.head}") + parent = outerPairs.head._2 // e.g. SparkContext outerPairs = outerPairs.tail + } else if (outerPairs.size > 0) { + logDebug(s" + outermost object is a closure, so we just keep it: ${outerPairs.head}") + } else { + logDebug(" + there are no enclosing objects!") } + // Clone the closure objects themselves, nulling out any fields that are not // used in the closure we're working on or any of its inner closures. for ((cls, obj) <- outerPairs) { - outer = instantiateClass(cls, outer, inInterpreter) + logDebug(s" + cloning the object $obj of class ${cls.getName}") + // We null out these unused references by cloning each object and then filling in all + // required fields from the original object. We need the parent here because the Java + // language specification requires the first constructor parameter of any closure to be + // its enclosing object. + val clone = instantiateClass(cls, parent, inInterpreter) for (fieldName <- accessedFields(cls)) { val field = cls.getDeclaredField(fieldName) field.setAccessible(true) val value = field.get(obj) - // logInfo("1: Setting " + fieldName + " on " + cls + " to " + value); - field.set(outer, value) + field.set(clone, value) + } + // If transitive cleaning is enabled, we recursively clean any enclosing closure using + // the already populated accessed fields map of the starting closure + if (cleanTransitively && isClosure(clone.getClass)) { + logDebug(s" + cleaning cloned closure $clone recursively (${cls.getName})") + // No need to check serializable here for the outer closures because we're + // only interested in the serializability of the starting closure + clean(clone, checkSerializable = false, cleanTransitively, accessedFields) } + parent = clone } - if (outer != null) { - // logInfo("2: Setting $outer on " + func.getClass + " to " + outer); + // Update the parent pointer ($outer) of this closure + if (parent != null) { val field = func.getClass.getDeclaredField("$outer") field.setAccessible(true) - field.set(func, outer) + // If the starting closure doesn't actually need our enclosing object, then just null it out + if (accessedFields.contains(func.getClass) && + !accessedFields(func.getClass).contains("$outer")) { + logDebug(s" + the starting closure doesn't actually need $parent, so we null it out") + field.set(func, null) + } else { + // Update this closure's parent pointer to point to our enclosing object, + // which could either be a cloned closure or the original user object + field.set(func, parent) + } } - + + logDebug(s" +++ closure $func (${func.getClass.getName}) is now cleaned +++") + if (checkSerializable) { ensureSerializable(func) } @@ -167,15 +318,17 @@ private[spark] object ClosureCleaner extends Logging { } } - private def instantiateClass(cls: Class[_], outer: AnyRef, inInterpreter: Boolean): AnyRef = { - // logInfo("Creating a " + cls + " with outer = " + outer) + private def instantiateClass( + cls: Class[_], + enclosingObject: AnyRef, + inInterpreter: Boolean): AnyRef = { if (!inInterpreter) { // This is a bona fide closure class, whose constructor has no effects // other than to set its fields, so use its constructor val cons = cls.getConstructors()(0) val params = cons.getParameterTypes.map(createNullValue).toArray - if (outer != null) { - params(0) = outer // First param is always outer object + if (enclosingObject != null) { + params(0) = enclosingObject // First param is always enclosing object } return cons.newInstance(params: _*).asInstanceOf[AnyRef] } else { @@ -184,19 +337,17 @@ private[spark] object ClosureCleaner extends Logging { val parentCtor = classOf[java.lang.Object].getDeclaredConstructor() val newCtor = rf.newConstructorForSerialization(cls, parentCtor) val obj = newCtor.newInstance().asInstanceOf[AnyRef] - if (outer != null) { - // logInfo("3: Setting $outer on " + cls + " to " + outer); + if (enclosingObject != null) { val field = cls.getDeclaredField("$outer") field.setAccessible(true) - field.set(obj, outer) + field.set(obj, enclosingObject) } obj } } } -private[spark] -class ReturnStatementFinder extends ClassVisitor(ASM4) { +private class ReturnStatementFinder extends ClassVisitor(ASM4) { override def visitMethod(access: Int, name: String, desc: String, sig: String, exceptions: Array[String]): MethodVisitor = { if (name.contains("apply")) { @@ -213,26 +364,65 @@ class ReturnStatementFinder extends ClassVisitor(ASM4) { } } -private[spark] -class FieldAccessFinder(output: Map[Class[_], Set[String]]) extends ClassVisitor(ASM4) { - override def visitMethod(access: Int, name: String, desc: String, - sig: String, exceptions: Array[String]): MethodVisitor = { +/** Helper class to identify a method. */ +private case class MethodIdentifier[T](cls: Class[T], name: String, desc: String) + +/** + * Find the fields accessed by a given class. + * + * The resulting fields are stored in the mutable map passed in through the constructor. + * This map is assumed to have its keys already populated with the classes of interest. + * + * @param fields the mutable map that stores the fields to return + * @param findTransitively if true, find fields indirectly referenced through method calls + * @param specificMethod if not empty, visit only this specific method + * @param visitedMethods a set of visited methods to avoid cycles + */ +private[util] class FieldAccessFinder( + fields: Map[Class[_], Set[String]], + findTransitively: Boolean, + specificMethod: Option[MethodIdentifier[_]] = None, + visitedMethods: Set[MethodIdentifier[_]] = Set.empty) + extends ClassVisitor(ASM4) { + + override def visitMethod( + access: Int, + name: String, + desc: String, + sig: String, + exceptions: Array[String]): MethodVisitor = { + + // If we are told to visit only a certain method and this is not the one, ignore it + if (specificMethod.isDefined && + (specificMethod.get.name != name || specificMethod.get.desc != desc)) { + return null + } + new MethodVisitor(ASM4) { override def visitFieldInsn(op: Int, owner: String, name: String, desc: String) { if (op == GETFIELD) { - for (cl <- output.keys if cl.getName == owner.replace('/', '.')) { - output(cl) += name + for (cl <- fields.keys if cl.getName == owner.replace('/', '.')) { + fields(cl) += name } } } - override def visitMethodInsn(op: Int, owner: String, name: String, - desc: String) { - // Check for calls a getter method for a variable in an interpreter wrapper object. - // This means that the corresponding field will be accessed, so we should save it. - if (op == INVOKEVIRTUAL && owner.endsWith("$iwC") && !name.endsWith("$outer")) { - for (cl <- output.keys if cl.getName == owner.replace('/', '.')) { - output(cl) += name + override def visitMethodInsn(op: Int, owner: String, name: String, desc: String) { + for (cl <- fields.keys if cl.getName == owner.replace('/', '.')) { + // Check for calls a getter method for a variable in an interpreter wrapper object. + // This means that the corresponding field will be accessed, so we should save it. + if (op == INVOKEVIRTUAL && owner.endsWith("$iwC") && !name.endsWith("$outer")) { + fields(cl) += name + } + // Optionally visit other methods to find fields that are transitively referenced + if (findTransitively) { + val m = MethodIdentifier(cl, name, desc) + if (!visitedMethods.contains(m)) { + // Keep track of visited methods to avoid potential infinite cycles + visitedMethods += m + ClosureCleaner.getClassReader(cl).accept( + new FieldAccessFinder(fields, findTransitively, Some(m), visitedMethods), 0) + } } } } @@ -240,9 +430,14 @@ class FieldAccessFinder(output: Map[Class[_], Set[String]]) extends ClassVisitor } } -private[spark] class InnerClosureFinder(output: Set[Class[_]]) extends ClassVisitor(ASM4) { +private class InnerClosureFinder(output: Set[Class[_]]) extends ClassVisitor(ASM4) { var myName: String = null + // TODO: Recursively find inner closures that we indirectly reference, e.g. + // val closure1 = () = { () => 1 } + // val closure2 = () => { (1 to 5).map(closure1) } + // The second closure technically has two inner closures, but this finder only finds one + override def visit(version: Int, access: Int, name: String, sig: String, superName: String, interfaces: Array[String]) { myName = name diff --git a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala index b679dcc3d9cae..c8425039b9c6d 100644 --- a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala +++ b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala @@ -194,7 +194,8 @@ private[spark] object JsonProtocol { ("App Name" -> applicationStart.appName) ~ ("App ID" -> applicationStart.appId.map(JString(_)).getOrElse(JNothing)) ~ ("Timestamp" -> applicationStart.time) ~ - ("User" -> applicationStart.sparkUser) + ("User" -> applicationStart.sparkUser) ~ + ("App Attempt ID" -> applicationStart.appAttemptId.map(JString(_)).getOrElse(JNothing)) } def applicationEndToJson(applicationEnd: SparkListenerApplicationEnd): JValue = { @@ -378,14 +379,14 @@ private[spark] object JsonProtocol { ("Number of Partitions" -> rddInfo.numPartitions) ~ ("Number of Cached Partitions" -> rddInfo.numCachedPartitions) ~ ("Memory Size" -> rddInfo.memSize) ~ - ("Tachyon Size" -> rddInfo.tachyonSize) ~ + ("ExternalBlockStore Size" -> rddInfo.externalBlockStoreSize) ~ ("Disk Size" -> rddInfo.diskSize) } def storageLevelToJson(storageLevel: StorageLevel): JValue = { ("Use Disk" -> storageLevel.useDisk) ~ ("Use Memory" -> storageLevel.useMemory) ~ - ("Use Tachyon" -> storageLevel.useOffHeap) ~ + ("Use ExternalBlockStore" -> storageLevel.useOffHeap) ~ ("Deserialized" -> storageLevel.deserialized) ~ ("Replication" -> storageLevel.replication) } @@ -394,7 +395,7 @@ private[spark] object JsonProtocol { val storageLevel = storageLevelToJson(blockStatus.storageLevel) ("Storage Level" -> storageLevel) ~ ("Memory Size" -> blockStatus.memSize) ~ - ("Tachyon Size" -> blockStatus.tachyonSize) ~ + ("ExternalBlockStore Size" -> blockStatus.externalBlockStoreSize) ~ ("Disk Size" -> blockStatus.diskSize) } @@ -567,7 +568,8 @@ private[spark] object JsonProtocol { val appId = Utils.jsonOption(json \ "App ID").map(_.extract[String]) val time = (json \ "Timestamp").extract[Long] val sparkUser = (json \ "User").extract[String] - SparkListenerApplicationStart(appName, appId, time, sparkUser) + val appAttemptId = Utils.jsonOption(json \ "App Attempt ID").map(_.extract[String]) + SparkListenerApplicationStart(appName, appId, time, sparkUser, appAttemptId) } def applicationEndFromJson(json: JValue): SparkListenerApplicationEnd = { @@ -800,13 +802,15 @@ private[spark] object JsonProtocol { val numPartitions = (json \ "Number of Partitions").extract[Int] val numCachedPartitions = (json \ "Number of Cached Partitions").extract[Int] val memSize = (json \ "Memory Size").extract[Long] - val tachyonSize = (json \ "Tachyon Size").extract[Long] + // fallback to tachyon for backward compatability + val externalBlockStoreSize = (json \ "ExternalBlockStore Size").toSome + .getOrElse(json \ "Tachyon Size").extract[Long] val diskSize = (json \ "Disk Size").extract[Long] val rddInfo = new RDDInfo(rddId, name, numPartitions, storageLevel, scope, parentIds) rddInfo.numCachedPartitions = numCachedPartitions rddInfo.memSize = memSize - rddInfo.tachyonSize = tachyonSize + rddInfo.externalBlockStoreSize = externalBlockStoreSize rddInfo.diskSize = diskSize rddInfo } @@ -814,18 +818,22 @@ private[spark] object JsonProtocol { def storageLevelFromJson(json: JValue): StorageLevel = { val useDisk = (json \ "Use Disk").extract[Boolean] val useMemory = (json \ "Use Memory").extract[Boolean] - val useTachyon = (json \ "Use Tachyon").extract[Boolean] + // fallback to tachyon for backward compatability + val useExternalBlockStore = (json \ "Use ExternalBlockStore").toSome + .getOrElse(json \ "Use Tachyon").extract[Boolean] val deserialized = (json \ "Deserialized").extract[Boolean] val replication = (json \ "Replication").extract[Int] - StorageLevel(useDisk, useMemory, useTachyon, deserialized, replication) + StorageLevel(useDisk, useMemory, useExternalBlockStore, deserialized, replication) } def blockStatusFromJson(json: JValue): BlockStatus = { val storageLevel = storageLevelFromJson(json \ "Storage Level") val memorySize = (json \ "Memory Size").extract[Long] val diskSize = (json \ "Disk Size").extract[Long] - val tachyonSize = (json \ "Tachyon Size").extract[Long] - BlockStatus(storageLevel, memorySize, diskSize, tachyonSize) + // fallback to tachyon for backward compatability + val externalBlockStoreSize = (json \ "ExternalBlockStore Size").toSome + .getOrElse(json \ "Tachyon Size").extract[Long] + BlockStatus(storageLevel, memorySize, diskSize, externalBlockStoreSize) } def executorInfoFromJson(json: JValue): ExecutorInfo = { diff --git a/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala index 4dd7ab9e0767b..d91c3294ddb8b 100644 --- a/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala +++ b/core/src/main/scala/org/apache/spark/util/SizeEstimator.scala @@ -47,6 +47,11 @@ private[spark] object SizeEstimator extends Logging { private val FLOAT_SIZE = 4 private val DOUBLE_SIZE = 8 + // Fields can be primitive types, sizes are: 1, 2, 4, 8. Or fields can be pointers. The size of + // a pointer is 4 or 8 depending on the JVM (32-bit or 64-bit) and UseCompressedOops flag. + // The sizes should be in descending order, as we will use that information for fields placement. + private val fieldSizes = List(8, 4, 2, 1) + // Alignment boundary for objects // TODO: Is this arch dependent ? private val ALIGN_SIZE = 8 @@ -171,7 +176,7 @@ private[spark] object SizeEstimator extends Logging { // general all ClassLoaders and Classes will be shared between objects anyway. } else { val classInfo = getClassInfo(cls) - state.size += classInfo.shellSize + state.size += alignSize(classInfo.shellSize) for (field <- classInfo.pointerFields) { state.enqueue(field.get(obj)) } @@ -237,8 +242,8 @@ private[spark] object SizeEstimator extends Logging { } size } - - private def primitiveSize(cls: Class[_]): Long = { + + private def primitiveSize(cls: Class[_]): Int = { if (cls == classOf[Byte]) { BYTE_SIZE } else if (cls == classOf[Boolean]) { @@ -274,21 +279,50 @@ private[spark] object SizeEstimator extends Logging { val parent = getClassInfo(cls.getSuperclass) var shellSize = parent.shellSize var pointerFields = parent.pointerFields + val sizeCount = Array.fill(fieldSizes.max + 1)(0) + // iterate through the fields of this class and gather information. for (field <- cls.getDeclaredFields) { if (!Modifier.isStatic(field.getModifiers)) { val fieldClass = field.getType if (fieldClass.isPrimitive) { - shellSize += primitiveSize(fieldClass) + sizeCount(primitiveSize(fieldClass)) += 1 } else { field.setAccessible(true) // Enable future get()'s on this field - shellSize += pointerSize + sizeCount(pointerSize) += 1 pointerFields = field :: pointerFields } } } - shellSize = alignSize(shellSize) + // Based on the simulated field layout code in Aleksey Shipilev's report: + // http://cr.openjdk.java.net/~shade/papers/2013-shipilev-fieldlayout-latest.pdf + // The code is in Figure 9. + // The simplified idea of field layout consists of 4 parts (see more details in the report): + // + // 1. field alignment: HotSpot lays out the fields aligned by their size. + // 2. object alignment: HotSpot rounds instance size up to 8 bytes + // 3. consistent fields layouts throughout the hierarchy: This means we should layout + // superclass first. And we can use superclass's shellSize as a starting point to layout the + // other fields in this class. + // 4. class alignment: HotSpot rounds field blocks up to to HeapOopSize not 4 bytes, confirmed + // with Aleksey. see https://bugs.openjdk.java.net/browse/CODETOOLS-7901322 + // + // The real world field layout is much more complicated. There are three kinds of fields + // order in Java 8. And we don't consider the @contended annotation introduced by Java 8. + // see the HotSpot classloader code, layout_fields method for more details. + // hg.openjdk.java.net/jdk8/jdk8/hotspot/file/tip/src/share/vm/classfile/classFileParser.cpp + var alignedSize = shellSize + for (size <- fieldSizes if sizeCount(size) > 0) { + val count = sizeCount(size) + // If there are internal gaps, smaller field can fit in. + alignedSize = math.max(alignedSize, alignSizeUp(shellSize, size) + size * count) + shellSize += size * count + } + + // Should choose a larger size to be new shellSize and clearly alignedSize >= shellSize, and + // round up the instance filed blocks + shellSize = alignSizeUp(alignedSize, pointerSize) // Create and cache a new ClassInfo val newInfo = new ClassInfo(shellSize, pointerFields) @@ -296,8 +330,15 @@ private[spark] object SizeEstimator extends Logging { newInfo } - private def alignSize(size: Long): Long = { - val rem = size % ALIGN_SIZE - if (rem == 0) size else (size + ALIGN_SIZE - rem) - } + private def alignSize(size: Long): Long = alignSizeUp(size, ALIGN_SIZE) + + /** + * Compute aligned size. The alignSize must be 2^n, otherwise the result will be wrong. + * When alignSize = 2^n, alignSize - 1 = 2^n - 1. The binary representation of (alignSize - 1) + * will only have n trailing 1s(0b00...001..1). ~(alignSize - 1) will be 0b11..110..0. Hence, + * (size + alignSize - 1) & ~(alignSize - 1) will set the last n bits to zeros, which leads to + * multiple of alignSize. + */ + private def alignSizeUp(size: Long, alignSize: Int): Long = + (size + alignSize - 1) & ~(alignSize - 1) } diff --git a/core/src/main/scala/org/apache/spark/util/Utils.scala b/core/src/main/scala/org/apache/spark/util/Utils.scala index 4c028c06a5138..be4db02ab86d0 100644 --- a/core/src/main/scala/org/apache/spark/util/Utils.scala +++ b/core/src/main/scala/org/apache/spark/util/Utils.scala @@ -1299,16 +1299,18 @@ private[spark] object Utils extends Logging { } /** Default filtering function for finding call sites using `getCallSite`. */ - private def coreExclusionFunction(className: String): Boolean = { - // A regular expression to match classes of the "core" Spark API that we want to skip when - // finding the call site of a method. + private def sparkInternalExclusionFunction(className: String): Boolean = { + // A regular expression to match classes of the internal Spark API's + // that we want to skip when finding the call site of a method. val SPARK_CORE_CLASS_REGEX = """^org\.apache\.spark(\.api\.java)?(\.util)?(\.rdd)?(\.broadcast)?\.[A-Z]""".r + val SPARK_SQL_CLASS_REGEX = """^org\.apache\.spark\.sql.*""".r val SCALA_CORE_CLASS_PREFIX = "scala" - val isSparkCoreClass = SPARK_CORE_CLASS_REGEX.findFirstIn(className).isDefined + val isSparkClass = SPARK_CORE_CLASS_REGEX.findFirstIn(className).isDefined || + SPARK_SQL_CLASS_REGEX.findFirstIn(className).isDefined val isScalaClass = className.startsWith(SCALA_CORE_CLASS_PREFIX) // If the class is a Spark internal class or a Scala class, then exclude. - isSparkCoreClass || isScalaClass + isSparkClass || isScalaClass } /** @@ -1318,7 +1320,7 @@ private[spark] object Utils extends Logging { * * @param skipClass Function that is used to exclude non-user-code classes. */ - def getCallSite(skipClass: String => Boolean = coreExclusionFunction): CallSite = { + def getCallSite(skipClass: String => Boolean = sparkInternalExclusionFunction): CallSite = { // Keep crawling up the stack trace until we find the first function not inside of the spark // package. We track the last (shallowest) contiguous Spark method. This might be an RDD // transformation, a SparkContext function (such as parallelize), or anything else that leads @@ -1357,9 +1359,17 @@ private[spark] object Utils extends Logging { } val callStackDepth = System.getProperty("spark.callstack.depth", "20").toInt - CallSite( - shortForm = s"$lastSparkMethod at $firstUserFile:$firstUserLine", - longForm = callStack.take(callStackDepth).mkString("\n")) + val shortForm = + if (firstUserFile == "HiveSessionImpl.java") { + // To be more user friendly, show a nicer string for queries submitted from the JDBC + // server. + "Spark JDBC Server Query" + } else { + s"$lastSparkMethod at $firstUserFile:$firstUserLine" + } + val longForm = callStack.take(callStackDepth).mkString("\n") + + CallSite(shortForm, longForm) } /** Return a string containing part of a file from byte 'start' to 'end'. */ @@ -2012,6 +2022,13 @@ private[spark] object Utils extends Logging { } } + /** + * configure a new log4j level + */ + def setLogLevel(l: org.apache.log4j.Level) { + org.apache.log4j.Logger.getRootLogger().setLevel(l) + } + /** * config a log4j properties used for testsuite */ @@ -2142,6 +2159,22 @@ private[spark] object Utils extends Logging { .getOrElse(UserGroupInformation.getCurrentUser().getShortUserName()) } + /** + * Split the comma delimited string of master URLs into a list. + * For instance, "spark://abc,def" becomes [spark://abc, spark://def]. + */ + def parseStandaloneMasterUrls(masterUrls: String): Array[String] = { + masterUrls.stripPrefix("spark://").split(",").map("spark://" + _) + } + + /** An identifier that backup masters use in their responses. */ + val BACKUP_STANDALONE_MASTER_PREFIX = "Current state is not alive" + + /** Return true if the response message is sent from a backup Master on standby. */ + def responseFromBackup(msg: String): Boolean = { + msg.startsWith(BACKUP_STANDALONE_MASTER_PREFIX) + } + /** * Adds a shutdown hook with default priority. * diff --git a/core/src/main/scala/org/apache/spark/util/collection/ChainedBuffer.scala b/core/src/main/scala/org/apache/spark/util/collection/ChainedBuffer.scala new file mode 100644 index 0000000000000..a60bffe611f14 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/collection/ChainedBuffer.scala @@ -0,0 +1,144 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util.collection + +import java.io.OutputStream + +import scala.collection.mutable.ArrayBuffer + +/** + * A logical byte buffer that wraps a list of byte arrays. All the byte arrays have equal size. The + * advantage of this over a standard ArrayBuffer is that it can grow without claiming large amounts + * of memory and needing to copy the full contents. The disadvantage is that the contents don't + * occupy a contiguous segment of memory. + */ +private[spark] class ChainedBuffer(chunkSize: Int) { + private val chunkSizeLog2 = (math.log(chunkSize) / math.log(2)).toInt + assert(math.pow(2, chunkSizeLog2).toInt == chunkSize, + s"ChainedBuffer chunk size $chunkSize must be a power of two") + private val chunks: ArrayBuffer[Array[Byte]] = new ArrayBuffer[Array[Byte]]() + private var _size: Int = _ + + /** + * Feed bytes from this buffer into a BlockObjectWriter. + * + * @param pos Offset in the buffer to read from. + * @param os OutputStream to read into. + * @param len Number of bytes to read. + */ + def read(pos: Int, os: OutputStream, len: Int): Unit = { + if (pos + len > _size) { + throw new IndexOutOfBoundsException( + s"Read of $len bytes at position $pos would go past size ${_size} of buffer") + } + var chunkIndex = pos >> chunkSizeLog2 + var posInChunk = pos - (chunkIndex << chunkSizeLog2) + var written = 0 + while (written < len) { + val toRead = math.min(len - written, chunkSize - posInChunk) + os.write(chunks(chunkIndex), posInChunk, toRead) + written += toRead + chunkIndex += 1 + posInChunk = 0 + } + } + + /** + * Read bytes from this buffer into a byte array. + * + * @param pos Offset in the buffer to read from. + * @param bytes Byte array to read into. + * @param offs Offset in the byte array to read to. + * @param len Number of bytes to read. + */ + def read(pos: Int, bytes: Array[Byte], offs: Int, len: Int): Unit = { + if (pos + len > _size) { + throw new IndexOutOfBoundsException( + s"Read of $len bytes at position $pos would go past size of buffer") + } + var chunkIndex = pos >> chunkSizeLog2 + var posInChunk = pos - (chunkIndex << chunkSizeLog2) + var written = 0 + while (written < len) { + val toRead = math.min(len - written, chunkSize - posInChunk) + System.arraycopy(chunks(chunkIndex), posInChunk, bytes, offs + written, toRead) + written += toRead + chunkIndex += 1 + posInChunk = 0 + } + } + + /** + * Write bytes from a byte array into this buffer. + * + * @param pos Offset in the buffer to write to. + * @param bytes Byte array to write from. + * @param offs Offset in the byte array to write from. + * @param len Number of bytes to write. + */ + def write(pos: Int, bytes: Array[Byte], offs: Int, len: Int): Unit = { + if (pos > _size) { + throw new IndexOutOfBoundsException( + s"Write at position $pos starts after end of buffer ${_size}") + } + // Grow if needed + val endChunkIndex = (pos + len - 1) >> chunkSizeLog2 + while (endChunkIndex >= chunks.length) { + chunks += new Array[Byte](chunkSize) + } + + var chunkIndex = pos >> chunkSizeLog2 + var posInChunk = pos - (chunkIndex << chunkSizeLog2) + var written = 0 + while (written < len) { + val toWrite = math.min(len - written, chunkSize - posInChunk) + System.arraycopy(bytes, offs + written, chunks(chunkIndex), posInChunk, toWrite) + written += toWrite + chunkIndex += 1 + posInChunk = 0 + } + + _size = math.max(_size, pos + len) + } + + /** + * Total size of buffer that can be written to without allocating additional memory. + */ + def capacity: Int = chunks.size * chunkSize + + /** + * Size of the logical buffer. + */ + def size: Int = _size +} + +/** + * Output stream that writes to a ChainedBuffer. + */ +private[spark] class ChainedBufferOutputStream(chainedBuffer: ChainedBuffer) extends OutputStream { + private var pos = 0 + + override def write(b: Int): Unit = { + throw new UnsupportedOperationException() + } + + override def write(bytes: Array[Byte], offs: Int, len: Int): Unit = { + chainedBuffer.write(pos, bytes, offs, len) + pos += len + } +} diff --git a/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala b/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala index f912049563906..b850973145077 100644 --- a/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala +++ b/core/src/main/scala/org/apache/spark/util/collection/ExternalAppendOnlyMap.scala @@ -174,7 +174,7 @@ class ExternalAppendOnlyMap[K, V, C]( val it = currentMap.destructiveSortedIterator(keyComparator) while (it.hasNext) { val kv = it.next() - writer.write(kv) + writer.write(kv._1, kv._2) objectsWritten += 1 if (objectsWritten == serializerBatchSize) { @@ -435,7 +435,9 @@ class ExternalAppendOnlyMap[K, V, C]( */ private def readNextItem(): (K, C) = { try { - val item = deserializeStream.readObject().asInstanceOf[(K, C)] + val k = deserializeStream.readKey().asInstanceOf[K] + val c = deserializeStream.readValue().asInstanceOf[C] + val item = (k, c) objectsRead += 1 if (objectsRead == serializerBatchSize) { objectsRead = 0 diff --git a/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala b/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala index ef3cac622505e..b7306cd551918 100644 --- a/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala +++ b/core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala @@ -26,7 +26,7 @@ import scala.collection.mutable import com.google.common.io.ByteStreams import org.apache.spark._ -import org.apache.spark.serializer.{DeserializationStream, Serializer} +import org.apache.spark.serializer._ import org.apache.spark.executor.ShuffleWriteMetrics import org.apache.spark.storage.{BlockObjectWriter, BlockId} @@ -66,10 +66,11 @@ import org.apache.spark.storage.{BlockObjectWriter, BlockId} * * At a high level, this class works internally as follows: * - * - We repeatedly fill up buffers of in-memory data, using either a SizeTrackingAppendOnlyMap if - * we want to combine by key, or an simple SizeTrackingBuffer if we don't. Inside these buffers, - * we sort elements of type ((Int, K), C) where the Int is the partition ID. This is done to - * avoid calling the partitioner multiple times on the same key (e.g. for RangePartitioner). + * - We repeatedly fill up buffers of in-memory data, using either a PartitionedAppendOnlyMap if + * we want to combine by key, or a PartitionedSerializedPairBuffer or PartitionedPairBuffer if we + * don't. Inside these buffers, we sort elements by partition ID and then possibly also by key. + * To avoid calling the partitioner multiple times with each key, we store the partition ID + * alongside each record. * * - When each buffer reaches our memory limit, we spill it to a file. This file is sorted first * by partition ID and possibly second by key or by hash code of the key, if we want to do @@ -96,7 +97,7 @@ private[spark] class ExternalSorter[K, V, C]( partitioner: Option[Partitioner] = None, ordering: Option[Ordering[K]] = None, serializer: Option[Serializer] = None) - extends Logging with Spillable[SizeTrackingPairCollection[(Int, K), C]] { + extends Logging with Spillable[WritablePartitionedPairCollection[K, C]] { private val numPartitions = partitioner.map(_.numPartitions).getOrElse(1) private val shouldPartition = numPartitions > 1 @@ -126,11 +127,22 @@ private[spark] class ExternalSorter[K, V, C]( if (shouldPartition) partitioner.get.getPartition(key) else 0 } + private val metaInitialRecords = 256 + private val kvChunkSize = conf.getInt("spark.shuffle.sort.kvChunkSize", 1 << 22) // 4 MB + private val useSerializedPairBuffer = + !ordering.isDefined && conf.getBoolean("spark.shuffle.sort.serializeMapOutputs", true) && + ser.isInstanceOf[KryoSerializer] && + serInstance.asInstanceOf[KryoSerializerInstance].getAutoReset + // Data structures to store in-memory objects before we spill. Depending on whether we have an // Aggregator set, we either put objects into an AppendOnlyMap where we combine them, or we // store them in an array buffer. - private var map = new SizeTrackingAppendOnlyMap[(Int, K), C] - private var buffer = new SizeTrackingPairBuffer[(Int, K), C] + private var map = new PartitionedAppendOnlyMap[K, C] + private var buffer = if (useSerializedPairBuffer) { + new PartitionedSerializedPairBuffer[K, C](metaInitialRecords, kvChunkSize, serInstance) + } else { + new PartitionedPairBuffer[K, C] + } // Total spilling statistics private var _diskBytesSpilled = 0L @@ -163,33 +175,6 @@ private[spark] class ExternalSorter[K, V, C]( } }) - // A comparator for (Int, K) pairs that orders them by only their partition ID - private val partitionComparator: Comparator[(Int, K)] = new Comparator[(Int, K)] { - override def compare(a: (Int, K), b: (Int, K)): Int = { - a._1 - b._1 - } - } - - // A comparator that orders (Int, K) pairs by partition ID and then possibly by key - private val partitionKeyComparator: Comparator[(Int, K)] = { - if (ordering.isDefined || aggregator.isDefined) { - // Sort by partition ID then key comparator - new Comparator[(Int, K)] { - override def compare(a: (Int, K), b: (Int, K)): Int = { - val partitionDiff = a._1 - b._1 - if (partitionDiff != 0) { - partitionDiff - } else { - keyComparator.compare(a._2, b._2) - } - } - } - } else { - // Just sort it by partition ID - partitionComparator - } - } - // Information about a spilled file. Includes sizes in bytes of "batches" written by the // serializer as we periodically reset its stream, as well as number of elements in each // partition, used to efficiently keep track of partitions when merging. @@ -221,16 +206,18 @@ private[spark] class ExternalSorter[K, V, C]( } else if (bypassMergeSort) { // SPARK-4479: Also bypass buffering if merge sort is bypassed to avoid defensive copies if (records.hasNext) { - spillToPartitionFiles(records.map { kv => - ((getPartition(kv._1), kv._1), kv._2.asInstanceOf[C]) - }) + spillToPartitionFiles( + WritablePartitionedIterator.fromIterator(records.map { kv => + ((getPartition(kv._1), kv._1), kv._2.asInstanceOf[C]) + }) + ) } } else { // Stick values into our buffer while (records.hasNext) { addElementsRead() val kv = records.next() - buffer.insert((getPartition(kv._1), kv._1), kv._2.asInstanceOf[C]) + buffer.insert(getPartition(kv._1), kv._1, kv._2.asInstanceOf[C]) maybeSpillCollection(usingMap = false) } } @@ -248,11 +235,15 @@ private[spark] class ExternalSorter[K, V, C]( if (usingMap) { if (maybeSpill(map, map.estimateSize())) { - map = new SizeTrackingAppendOnlyMap[(Int, K), C] + map = new PartitionedAppendOnlyMap[K, C] } } else { if (maybeSpill(buffer, buffer.estimateSize())) { - buffer = new SizeTrackingPairBuffer[(Int, K), C] + buffer = if (useSerializedPairBuffer) { + new PartitionedSerializedPairBuffer[K, C](metaInitialRecords, kvChunkSize, serInstance) + } else { + new PartitionedPairBuffer[K, C] + } } } } @@ -260,7 +251,7 @@ private[spark] class ExternalSorter[K, V, C]( /** * Spill the current in-memory collection to disk, adding a new file to spills, and clear it. */ - override protected[this] def spill(collection: SizeTrackingPairCollection[(Int, K), C]): Unit = { + override protected[this] def spill(collection: WritablePartitionedPairCollection[K, C]): Unit = { if (bypassMergeSort) { spillToPartitionFiles(collection) } else { @@ -277,7 +268,7 @@ private[spark] class ExternalSorter[K, V, C]( * * @param collection whichever collection we're using (map or buffer) */ - private def spillToMergeableFile(collection: SizeTrackingPairCollection[(Int, K), C]): Unit = { + private def spillToMergeableFile(collection: WritablePartitionedPairCollection[K, C]): Unit = { assert(!bypassMergeSort) // Because these files may be read during shuffle, their compression must be controlled by @@ -308,14 +299,10 @@ private[spark] class ExternalSorter[K, V, C]( var success = false try { - val it = collection.destructiveSortedIterator(partitionKeyComparator) + val it = collection.destructiveSortedWritablePartitionedIterator(comparator) while (it.hasNext) { - val elem = it.next() - val partitionId = elem._1._1 - val key = elem._1._2 - val value = elem._2 - writer.write(key) - writer.write(value) + val partitionId = it.nextPartition() + it.writeNext(writer) elementsPerPartition(partitionId) += 1 objectsWritten += 1 @@ -357,11 +344,11 @@ private[spark] class ExternalSorter[K, V, C]( * * @param collection whichever collection we're using (map or buffer) */ - private def spillToPartitionFiles(collection: SizeTrackingPairCollection[(Int, K), C]): Unit = { - spillToPartitionFiles(collection.iterator) + private def spillToPartitionFiles(collection: WritablePartitionedPairCollection[K, C]): Unit = { + spillToPartitionFiles(collection.writablePartitionedIterator()) } - private def spillToPartitionFiles(iterator: Iterator[((Int, K), C)]): Unit = { + private def spillToPartitionFiles(iterator: WritablePartitionedIterator): Unit = { assert(bypassMergeSort) // Create our file writers if we haven't done so yet @@ -385,11 +372,8 @@ private[spark] class ExternalSorter[K, V, C]( // No need to sort stuff, just write each element out while (iterator.hasNext) { - val elem = iterator.next() - val partitionId = elem._1._1 - val key = elem._1._2 - val value = elem._2 - partitionWriters(partitionId).write((key, value)) + val partitionId = iterator.nextPartition() + iterator.writeNext(partitionWriters(partitionId)) } } @@ -527,7 +511,8 @@ private[spark] class ExternalSorter[K, V, C]( val k = elem._1 var c = elem._2 while (sorted.hasNext && sorted.head._1 == k) { - c = mergeCombiners(c, sorted.head._2) + val pair = sorted.next() + c = mergeCombiners(c, pair._2) } (k, c) } @@ -617,8 +602,8 @@ private[spark] class ExternalSorter[K, V, C]( if (finished || deserializeStream == null) { return null } - val k = deserializeStream.readObject().asInstanceOf[K] - val c = deserializeStream.readObject().asInstanceOf[C] + val k = deserializeStream.readKey().asInstanceOf[K] + val c = deserializeStream.readValue().asInstanceOf[C] lastPartitionId = partitionId // Start reading the next batch if we're done with this one indexInBatch += 1 @@ -694,27 +679,27 @@ private[spark] class ExternalSorter[K, V, C]( */ def partitionedIterator: Iterator[(Int, Iterator[Product2[K, C]])] = { val usingMap = aggregator.isDefined - val collection: SizeTrackingPairCollection[(Int, K), C] = if (usingMap) map else buffer + val collection: WritablePartitionedPairCollection[K, C] = if (usingMap) map else buffer if (spills.isEmpty && partitionWriters == null) { // Special case: if we have only in-memory data, we don't need to merge streams, and perhaps // we don't even need to sort by anything other than partition ID if (!ordering.isDefined) { // The user hasn't requested sorted keys, so only sort by partition ID, not key - groupByPartition(collection.destructiveSortedIterator(partitionComparator)) + groupByPartition(collection.partitionedDestructiveSortedIterator(None)) } else { // We do need to sort by both partition ID and key - groupByPartition(collection.destructiveSortedIterator(partitionKeyComparator)) + groupByPartition(collection.partitionedDestructiveSortedIterator(Some(keyComparator))) } } else if (bypassMergeSort) { // Read data from each partition file and merge it together with the data in memory; // note that there's no ordering or aggregator in this case -- we just partition objects - val collIter = groupByPartition(collection.destructiveSortedIterator(partitionComparator)) + val collIter = groupByPartition(collection.partitionedDestructiveSortedIterator(None)) collIter.map { case (partitionId, values) => (partitionId, values ++ readPartitionFile(partitionWriters(partitionId))) } } else { // Merge spilled and in-memory data - merge(spills, collection.destructiveSortedIterator(partitionKeyComparator)) + merge(spills, collection.partitionedDestructiveSortedIterator(comparator)) } } @@ -761,15 +746,29 @@ private[spark] class ExternalSorter[K, V, C]( context.taskMetrics.shuffleWriteMetrics.foreach( _.incShuffleWriteTime(System.nanoTime - writeStartTime)) } + } else if (spills.isEmpty && partitionWriters == null) { + // Case where we only have in-memory data + val collection = if (aggregator.isDefined) map else buffer + val it = collection.destructiveSortedWritablePartitionedIterator(comparator) + while (it.hasNext) { + val writer = blockManager.getDiskWriter(blockId, outputFile, serInstance, fileBufferSize, + context.taskMetrics.shuffleWriteMetrics.get) + val partitionId = it.nextPartition() + while (it.hasNext && it.nextPartition() == partitionId) { + it.writeNext(writer) + } + writer.commitAndClose() + val segment = writer.fileSegment() + lengths(partitionId) = segment.length + } } else { - // Either we're not bypassing merge-sort or we have only in-memory data; get an iterator by - // partition and just write everything directly. + // Not bypassing merge-sort; get an iterator by partition and just write everything directly. for ((id, elements) <- this.partitionedIterator) { if (elements.hasNext) { val writer = blockManager.getDiskWriter(blockId, outputFile, serInstance, fileBufferSize, context.taskMetrics.shuffleWriteMetrics.get) for (elem <- elements) { - writer.write(elem) + writer.write(elem._1, elem._2) } writer.commitAndClose() val segment = writer.fileSegment() @@ -798,7 +797,7 @@ private[spark] class ExternalSorter[K, V, C]( if (writer.isOpen) { writer.commitAndClose() } - blockManager.diskStore.getValues(writer.blockId, ser).get.asInstanceOf[Iterator[Product2[K, C]]] + new PairIterator[K, C](blockManager.diskStore.getValues(writer.blockId, ser).get) } def stop(): Unit = { @@ -828,6 +827,14 @@ private[spark] class ExternalSorter[K, V, C]( (0 until numPartitions).iterator.map(p => (p, new IteratorForPartition(p, buffered))) } + private def comparator: Option[Comparator[K]] = { + if (ordering.isDefined || aggregator.isDefined) { + Some(keyComparator) + } else { + None + } + } + /** * An iterator that reads only the elements for a given partition ID from an underlying buffered * stream, assuming this partition is the next one to be read. Used to make it easier to return diff --git a/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingPairCollection.scala b/core/src/main/scala/org/apache/spark/util/collection/PairIterator.scala similarity index 55% rename from core/src/main/scala/org/apache/spark/util/collection/SizeTrackingPairCollection.scala rename to core/src/main/scala/org/apache/spark/util/collection/PairIterator.scala index faa4e2b12ddb6..d75959f480756 100644 --- a/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingPairCollection.scala +++ b/core/src/main/scala/org/apache/spark/util/collection/PairIterator.scala @@ -17,18 +17,8 @@ package org.apache.spark.util.collection -import java.util.Comparator +private[spark] class PairIterator[K, V](iter: Iterator[Any]) extends Iterator[(K, V)] { + def hasNext: Boolean = iter.hasNext -/** - * A common interface for our size-tracking collections of key-value pairs, which are used in - * external operations. These all support estimating the size and obtaining a memory-efficient - * sorted iterator. - */ -// TODO: should extend Iterable[Product2[K, V]] instead of (K, V) -private[spark] trait SizeTrackingPairCollection[K, V] extends Iterable[(K, V)] { - /** Estimate the collection's current memory usage in bytes. */ - def estimateSize(): Long - - /** Iterate through the data in a given key order. This may destroy the underlying collection. */ - def destructiveSortedIterator(keyComparator: Comparator[K]): Iterator[(K, V)] + def next(): (K, V) = (iter.next().asInstanceOf[K], iter.next().asInstanceOf[V]) } diff --git a/core/src/main/scala/org/apache/spark/util/collection/PartitionedAppendOnlyMap.scala b/core/src/main/scala/org/apache/spark/util/collection/PartitionedAppendOnlyMap.scala new file mode 100644 index 0000000000000..e2e2f1faae9d1 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/collection/PartitionedAppendOnlyMap.scala @@ -0,0 +1,44 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util.collection + +import java.util.Comparator + +import org.apache.spark.util.collection.WritablePartitionedPairCollection._ + +/** + * Implementation of WritablePartitionedPairCollection that wraps a map in which the keys are tuples + * of (partition ID, K) + */ +private[spark] class PartitionedAppendOnlyMap[K, V] + extends SizeTrackingAppendOnlyMap[(Int, K), V] with WritablePartitionedPairCollection[K, V] { + + def partitionedDestructiveSortedIterator(keyComparator: Option[Comparator[K]]) + : Iterator[((Int, K), V)] = { + val comparator = keyComparator.map(partitionKeyComparator).getOrElse(partitionComparator) + destructiveSortedIterator(comparator) + } + + def writablePartitionedIterator(): WritablePartitionedIterator = { + WritablePartitionedIterator.fromIterator(super.iterator) + } + + def insert(partition: Int, key: K, value: V): Unit = { + update((partition, key), value) + } +} diff --git a/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingPairBuffer.scala b/core/src/main/scala/org/apache/spark/util/collection/PartitionedPairBuffer.scala similarity index 66% rename from core/src/main/scala/org/apache/spark/util/collection/SizeTrackingPairBuffer.scala rename to core/src/main/scala/org/apache/spark/util/collection/PartitionedPairBuffer.scala index 9e9c16c5a2962..e8332e1a87eac 100644 --- a/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingPairBuffer.scala +++ b/core/src/main/scala/org/apache/spark/util/collection/PartitionedPairBuffer.scala @@ -19,11 +19,15 @@ package org.apache.spark.util.collection import java.util.Comparator +import org.apache.spark.storage.BlockObjectWriter +import org.apache.spark.util.collection.WritablePartitionedPairCollection._ + /** - * Append-only buffer of key-value pairs that keeps track of its estimated size in bytes. + * Append-only buffer of key-value pairs, each with a corresponding partition ID, that keeps track + * of its estimated size in bytes. */ -private[spark] class SizeTrackingPairBuffer[K, V](initialCapacity: Int = 64) - extends SizeTracker with SizeTrackingPairCollection[K, V] +private[spark] class PartitionedPairBuffer[K, V](initialCapacity: Int = 64) + extends WritablePartitionedPairCollection[K, V] with SizeTracker { require(initialCapacity <= (1 << 29), "Can't make capacity bigger than 2^29 elements") require(initialCapacity >= 1, "Invalid initial capacity") @@ -35,35 +39,16 @@ private[spark] class SizeTrackingPairBuffer[K, V](initialCapacity: Int = 64) private var data = new Array[AnyRef](2 * initialCapacity) /** Add an element into the buffer */ - def insert(key: K, value: V): Unit = { + def insert(partition: Int, key: K, value: V): Unit = { if (curSize == capacity) { growArray() } - data(2 * curSize) = key.asInstanceOf[AnyRef] + data(2 * curSize) = (partition, key.asInstanceOf[AnyRef]) data(2 * curSize + 1) = value.asInstanceOf[AnyRef] curSize += 1 afterUpdate() } - /** Total number of elements in buffer */ - override def size: Int = curSize - - /** Iterate over the elements of the buffer */ - override def iterator: Iterator[(K, V)] = new Iterator[(K, V)] { - var pos = 0 - - override def hasNext: Boolean = pos < curSize - - override def next(): (K, V) = { - if (!hasNext) { - throw new NoSuchElementException - } - val pair = (data(2 * pos).asInstanceOf[K], data(2 * pos + 1).asInstanceOf[V]) - pos += 1 - pair - } - } - /** Double the size of the array because we've reached capacity */ private def growArray(): Unit = { if (capacity == (1 << 29)) { @@ -79,8 +64,29 @@ private[spark] class SizeTrackingPairBuffer[K, V](initialCapacity: Int = 64) } /** Iterate through the data in a given order. For this class this is not really destructive. */ - override def destructiveSortedIterator(keyComparator: Comparator[K]): Iterator[(K, V)] = { - new Sorter(new KVArraySortDataFormat[K, AnyRef]).sort(data, 0, curSize, keyComparator) + override def partitionedDestructiveSortedIterator(keyComparator: Option[Comparator[K]]) + : Iterator[((Int, K), V)] = { + val comparator = keyComparator.map(partitionKeyComparator).getOrElse(partitionComparator) + new Sorter(new KVArraySortDataFormat[(Int, K), AnyRef]).sort(data, 0, curSize, comparator) iterator } + + override def writablePartitionedIterator(): WritablePartitionedIterator = { + WritablePartitionedIterator.fromIterator(iterator) + } + + private def iterator(): Iterator[((Int, K), V)] = new Iterator[((Int, K), V)] { + var pos = 0 + + override def hasNext: Boolean = pos < curSize + + override def next(): ((Int, K), V) = { + if (!hasNext) { + throw new NoSuchElementException + } + val pair = (data(2 * pos).asInstanceOf[(Int, K)], data(2 * pos + 1).asInstanceOf[V]) + pos += 1 + pair + } + } } diff --git a/core/src/main/scala/org/apache/spark/util/collection/PartitionedSerializedPairBuffer.scala b/core/src/main/scala/org/apache/spark/util/collection/PartitionedSerializedPairBuffer.scala new file mode 100644 index 0000000000000..b5ca0c62a04f2 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/collection/PartitionedSerializedPairBuffer.scala @@ -0,0 +1,254 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util.collection + +import java.io.InputStream +import java.nio.IntBuffer +import java.util.Comparator + +import org.apache.spark.SparkEnv +import org.apache.spark.serializer.{JavaSerializerInstance, SerializerInstance} +import org.apache.spark.storage.BlockObjectWriter +import org.apache.spark.util.collection.PartitionedSerializedPairBuffer._ + +/** + * Append-only buffer of key-value pairs, each with a corresponding partition ID, that serializes + * its records upon insert and stores them as raw bytes. + * + * We use two data-structures to store the contents. The serialized records are stored in a + * ChainedBuffer that can expand gracefully as records are added. This buffer is accompanied by a + * metadata buffer that stores pointers into the data buffer as well as the partition ID of each + * record. Each entry in the metadata buffer takes up a fixed amount of space. + * + * Sorting the collection means swapping entries in the metadata buffer - the record buffer need not + * be modified at all. Storing the partition IDs in the metadata buffer means that comparisons can + * happen without following any pointers, which should minimize cache misses. + * + * Currently, only sorting by partition is supported. + * + * @param metaInitialRecords The initial number of entries in the metadata buffer. + * @param kvBlockSize The size of each byte buffer in the ChainedBuffer used to store the records. + * @param serializerInstance the serializer used for serializing inserted records. + */ +private[spark] class PartitionedSerializedPairBuffer[K, V]( + metaInitialRecords: Int, + kvBlockSize: Int, + serializerInstance: SerializerInstance) + extends WritablePartitionedPairCollection[K, V] with SizeTracker { + + if (serializerInstance.isInstanceOf[JavaSerializerInstance]) { + throw new IllegalArgumentException("PartitionedSerializedPairBuffer does not support" + + " Java-serialized objects.") + } + + private var metaBuffer = IntBuffer.allocate(metaInitialRecords * RECORD_SIZE) + + private val kvBuffer: ChainedBuffer = new ChainedBuffer(kvBlockSize) + private val kvOutputStream = new ChainedBufferOutputStream(kvBuffer) + private val kvSerializationStream = serializerInstance.serializeStream(kvOutputStream) + + def insert(partition: Int, key: K, value: V): Unit = { + if (metaBuffer.position == metaBuffer.capacity) { + growMetaBuffer() + } + + val keyStart = kvBuffer.size + if (keyStart < 0) { + throw new Exception(s"Can't grow buffer beyond ${1 << 31} bytes") + } + kvSerializationStream.writeObject[Any](key) + kvSerializationStream.flush() + val valueStart = kvBuffer.size + kvSerializationStream.writeObject[Any](value) + kvSerializationStream.flush() + val valueEnd = kvBuffer.size + + metaBuffer.put(keyStart) + metaBuffer.put(valueStart) + metaBuffer.put(valueEnd) + metaBuffer.put(partition) + } + + /** Double the size of the array because we've reached capacity */ + private def growMetaBuffer(): Unit = { + if (metaBuffer.capacity.toLong * 2 > Int.MaxValue) { + // Doubling the capacity would create an array bigger than Int.MaxValue, so don't + throw new Exception(s"Can't grow buffer beyond ${Int.MaxValue} bytes") + } + val newMetaBuffer = IntBuffer.allocate(metaBuffer.capacity * 2) + newMetaBuffer.put(metaBuffer.array) + metaBuffer = newMetaBuffer + } + + /** Iterate through the data in a given order. For this class this is not really destructive. */ + override def partitionedDestructiveSortedIterator(keyComparator: Option[Comparator[K]]) + : Iterator[((Int, K), V)] = { + sort(keyComparator) + val is = orderedInputStream + val deserStream = serializerInstance.deserializeStream(is) + new Iterator[((Int, K), V)] { + var metaBufferPos = 0 + def hasNext: Boolean = metaBufferPos < metaBuffer.position + def next(): ((Int, K), V) = { + val key = deserStream.readKey[Any]().asInstanceOf[K] + val value = deserStream.readValue[Any]().asInstanceOf[V] + val partition = metaBuffer.get(metaBufferPos + PARTITION) + metaBufferPos += RECORD_SIZE + ((partition, key), value) + } + } + } + + override def estimateSize: Long = metaBuffer.capacity * 4 + kvBuffer.capacity + + override def destructiveSortedWritablePartitionedIterator(keyComparator: Option[Comparator[K]]) + : WritablePartitionedIterator = { + sort(keyComparator) + writablePartitionedIterator + } + + override def writablePartitionedIterator(): WritablePartitionedIterator = { + new WritablePartitionedIterator { + // current position in the meta buffer in ints + var pos = 0 + + def writeNext(writer: BlockObjectWriter): Unit = { + val keyStart = metaBuffer.get(pos + KEY_START) + val valueEnd = metaBuffer.get(pos + VAL_END) + pos += RECORD_SIZE + kvBuffer.read(keyStart, writer, valueEnd - keyStart) + writer.recordWritten() + } + def nextPartition(): Int = metaBuffer.get(pos + PARTITION) + def hasNext(): Boolean = pos < metaBuffer.position + } + } + + // Visible for testing + def orderedInputStream: OrderedInputStream = { + new OrderedInputStream(metaBuffer, kvBuffer) + } + + private def sort(keyComparator: Option[Comparator[K]]): Unit = { + val comparator = if (keyComparator.isEmpty) { + new Comparator[Int]() { + def compare(partition1: Int, partition2: Int): Int = { + partition1 - partition2 + } + } + } else { + throw new UnsupportedOperationException() + } + + val sorter = new Sorter(new SerializedSortDataFormat) + sorter.sort(metaBuffer, 0, metaBuffer.position / RECORD_SIZE, comparator) + } +} + +private[spark] class OrderedInputStream(metaBuffer: IntBuffer, kvBuffer: ChainedBuffer) + extends InputStream { + + private var metaBufferPos = 0 + private var kvBufferPos = + if (metaBuffer.position > 0) metaBuffer.get(metaBufferPos + KEY_START) else 0 + + override def read(bytes: Array[Byte]): Int = read(bytes, 0, bytes.length) + + override def read(bytes: Array[Byte], offs: Int, len: Int): Int = { + if (metaBufferPos >= metaBuffer.position) { + return -1 + } + val bytesRemainingInRecord = metaBuffer.get(metaBufferPos + VAL_END) - kvBufferPos + val toRead = math.min(bytesRemainingInRecord, len) + kvBuffer.read(kvBufferPos, bytes, offs, toRead) + if (toRead == bytesRemainingInRecord) { + metaBufferPos += RECORD_SIZE + if (metaBufferPos < metaBuffer.position) { + kvBufferPos = metaBuffer.get(metaBufferPos + KEY_START) + } + } else { + kvBufferPos += toRead + } + toRead + } + + override def read(): Int = { + throw new UnsupportedOperationException() + } +} + +private[spark] class SerializedSortDataFormat extends SortDataFormat[Int, IntBuffer] { + + private val META_BUFFER_TMP = new Array[Int](RECORD_SIZE) + + /** Return the sort key for the element at the given index. */ + override protected def getKey(metaBuffer: IntBuffer, pos: Int): Int = { + metaBuffer.get(pos * RECORD_SIZE + PARTITION) + } + + /** Swap two elements. */ + override def swap(metaBuffer: IntBuffer, pos0: Int, pos1: Int): Unit = { + val iOff = pos0 * RECORD_SIZE + val jOff = pos1 * RECORD_SIZE + System.arraycopy(metaBuffer.array, iOff, META_BUFFER_TMP, 0, RECORD_SIZE) + System.arraycopy(metaBuffer.array, jOff, metaBuffer.array, iOff, RECORD_SIZE) + System.arraycopy(META_BUFFER_TMP, 0, metaBuffer.array, jOff, RECORD_SIZE) + } + + /** Copy a single element from src(srcPos) to dst(dstPos). */ + override def copyElement( + src: IntBuffer, + srcPos: Int, + dst: IntBuffer, + dstPos: Int): Unit = { + val srcOff = srcPos * RECORD_SIZE + val dstOff = dstPos * RECORD_SIZE + System.arraycopy(src.array, srcOff, dst.array, dstOff, RECORD_SIZE) + } + + /** + * Copy a range of elements starting at src(srcPos) to dst, starting at dstPos. + * Overlapping ranges are allowed. + */ + override def copyRange( + src: IntBuffer, + srcPos: Int, + dst: IntBuffer, + dstPos: Int, + length: Int): Unit = { + val srcOff = srcPos * RECORD_SIZE + val dstOff = dstPos * RECORD_SIZE + System.arraycopy(src.array, srcOff, dst.array, dstOff, RECORD_SIZE * length) + } + + /** + * Allocates a Buffer that can hold up to 'length' elements. + * All elements of the buffer should be considered invalid until data is explicitly copied in. + */ + override def allocate(length: Int): IntBuffer = { + IntBuffer.allocate(length * RECORD_SIZE) + } +} + +private[spark] object PartitionedSerializedPairBuffer { + val KEY_START = 0 + val VAL_START = 1 + val VAL_END = 2 + val PARTITION = 3 + val RECORD_SIZE = Seq(KEY_START, VAL_START, VAL_END, PARTITION).size // num ints of metadata +} diff --git a/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingAppendOnlyMap.scala b/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingAppendOnlyMap.scala index eb4de413867a0..722f78bd15986 100644 --- a/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingAppendOnlyMap.scala +++ b/core/src/main/scala/org/apache/spark/util/collection/SizeTrackingAppendOnlyMap.scala @@ -21,7 +21,7 @@ package org.apache.spark.util.collection * An append-only map that keeps track of its estimated size in bytes. */ private[spark] class SizeTrackingAppendOnlyMap[K, V] - extends AppendOnlyMap[K, V] with SizeTracker with SizeTrackingPairCollection[K, V] + extends AppendOnlyMap[K, V] with SizeTracker { override def update(key: K, value: V): Unit = { super.update(key, value) diff --git a/core/src/main/scala/org/apache/spark/util/collection/WritablePartitionedPairCollection.scala b/core/src/main/scala/org/apache/spark/util/collection/WritablePartitionedPairCollection.scala new file mode 100644 index 0000000000000..f26d1618c9200 --- /dev/null +++ b/core/src/main/scala/org/apache/spark/util/collection/WritablePartitionedPairCollection.scala @@ -0,0 +1,113 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util.collection + +import java.util.Comparator + +import org.apache.spark.storage.BlockObjectWriter + +/** + * A common interface for size-tracking collections of key-value pairs that + * - Have an associated partition for each key-value pair. + * - Support a memory-efficient sorted iterator + * - Support a WritablePartitionedIterator for writing the contents directly as bytes. + */ +private[spark] trait WritablePartitionedPairCollection[K, V] { + /** + * Insert a key-value pair with a partition into the collection + */ + def insert(partition: Int, key: K, value: V): Unit + + /** + * Iterate through the data in order of partition ID and then the given comparator. This may + * destroy the underlying collection. + */ + def partitionedDestructiveSortedIterator(keyComparator: Option[Comparator[K]]) + : Iterator[((Int, K), V)] + + /** + * Iterate through the data and write out the elements instead of returning them. Records are + * returned in order of their partition ID and then the given comparator. + * This may destroy the underlying collection. + */ + def destructiveSortedWritablePartitionedIterator(keyComparator: Option[Comparator[K]]) + : WritablePartitionedIterator = { + WritablePartitionedIterator.fromIterator(partitionedDestructiveSortedIterator(keyComparator)) + } + + /** + * Iterate through the data and write out the elements instead of returning them. + */ + def writablePartitionedIterator(): WritablePartitionedIterator +} + +private[spark] object WritablePartitionedPairCollection { + /** + * A comparator for (Int, K) pairs that orders them by only their partition ID. + */ + def partitionComparator[K]: Comparator[(Int, K)] = new Comparator[(Int, K)] { + override def compare(a: (Int, K), b: (Int, K)): Int = { + a._1 - b._1 + } + } + + /** + * A comparator for (Int, K) pairs that orders them both by their partition ID and a key ordering. + */ + def partitionKeyComparator[K](keyComparator: Comparator[K]): Comparator[(Int, K)] = { + new Comparator[(Int, K)] { + override def compare(a: (Int, K), b: (Int, K)): Int = { + val partitionDiff = a._1 - b._1 + if (partitionDiff != 0) { + partitionDiff + } else { + keyComparator.compare(a._2, b._2) + } + } + } + } +} + +/** + * Iterator that writes elements to a BlockObjectWriter instead of returning them. Each element + * has an associated partition. + */ +private[spark] trait WritablePartitionedIterator { + def writeNext(writer: BlockObjectWriter): Unit + + def hasNext(): Boolean + + def nextPartition(): Int +} + +private[spark] object WritablePartitionedIterator { + def fromIterator(it: Iterator[((Int, _), _)]): WritablePartitionedIterator = { + new WritablePartitionedIterator { + var cur = if (it.hasNext) it.next() else null + + def writeNext(writer: BlockObjectWriter): Unit = { + writer.write(cur._1._2, cur._2) + cur = if (it.hasNext) it.next() else null + } + + def hasNext(): Boolean = cur != null + + def nextPartition(): Int = cur._1._1 + } + } +} diff --git a/core/src/test/java/org/apache/spark/JavaAPISuite.java b/core/src/test/java/org/apache/spark/JavaAPISuite.java index 8a4f2a08fe701..c2089b0e56a1f 100644 --- a/core/src/test/java/org/apache/spark/JavaAPISuite.java +++ b/core/src/test/java/org/apache/spark/JavaAPISuite.java @@ -157,11 +157,11 @@ public void sample() { public void randomSplit() { List ints = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10); JavaRDD rdd = sc.parallelize(ints); - JavaRDD[] splits = rdd.randomSplit(new double[] { 0.4, 0.6, 1.0 }, 11); + JavaRDD[] splits = rdd.randomSplit(new double[] { 0.4, 0.6, 1.0 }, 31); Assert.assertEquals(3, splits.length); - Assert.assertEquals(2, splits[0].count()); - Assert.assertEquals(3, splits[1].count()); - Assert.assertEquals(5, splits[2].count()); + Assert.assertEquals(1, splits[0].count()); + Assert.assertEquals(2, splits[1].count()); + Assert.assertEquals(7, splits[2].count()); } @Test @@ -1009,7 +1009,7 @@ public void persist() { @Test public void iterator() { JavaRDD rdd = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5), 2); - TaskContext context = new TaskContextImpl(0, 0, 0L, 0, false, new TaskMetrics()); + TaskContext context = new TaskContextImpl(0, 0, 0L, 0, null, false, new TaskMetrics()); Assert.assertEquals(1, rdd.iterator(rdd.partitions().get(0), context).next().intValue()); } diff --git a/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala b/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala index 70529d9216591..668ddf9f5f0a9 100644 --- a/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/CacheManagerSuite.scala @@ -65,7 +65,7 @@ class CacheManagerSuite extends FunSuite with LocalSparkContext with BeforeAndAf // in blockManager.put is a losing battle. You have been warned. blockManager = sc.env.blockManager cacheManager = sc.env.cacheManager - val context = new TaskContextImpl(0, 0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0, null) val computeValue = cacheManager.getOrCompute(rdd, split, context, StorageLevel.MEMORY_ONLY) val getValue = blockManager.get(RDDBlockId(rdd.id, split.index)) assert(computeValue.toList === List(1, 2, 3, 4)) @@ -77,7 +77,7 @@ class CacheManagerSuite extends FunSuite with LocalSparkContext with BeforeAndAf val result = new BlockResult(Array(5, 6, 7).iterator, DataReadMethod.Memory, 12) when(blockManager.get(RDDBlockId(0, 0))).thenReturn(Some(result)) - val context = new TaskContextImpl(0, 0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0, null) val value = cacheManager.getOrCompute(rdd, split, context, StorageLevel.MEMORY_ONLY) assert(value.toList === List(5, 6, 7)) } @@ -86,14 +86,14 @@ class CacheManagerSuite extends FunSuite with LocalSparkContext with BeforeAndAf // Local computation should not persist the resulting value, so don't expect a put(). when(blockManager.get(RDDBlockId(0, 0))).thenReturn(None) - val context = new TaskContextImpl(0, 0, 0, 0, true) + val context = new TaskContextImpl(0, 0, 0, 0, null, true) val value = cacheManager.getOrCompute(rdd, split, context, StorageLevel.MEMORY_ONLY) assert(value.toList === List(1, 2, 3, 4)) } test("verify task metrics updated correctly") { cacheManager = sc.env.cacheManager - val context = new TaskContextImpl(0, 0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0, null) cacheManager.getOrCompute(rdd3, split, context, StorageLevel.MEMORY_ONLY) assert(context.taskMetrics.updatedBlocks.getOrElse(Seq()).size === 2) } diff --git a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala index 370c020530d72..84f787ee3715d 100644 --- a/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/ExecutorAllocationManagerSuite.scala @@ -78,7 +78,7 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit test("starting state") { sc = createSparkContext() val manager = sc.executorAllocationManager.get - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 1) assert(executorsPendingToRemove(manager).isEmpty) assert(executorIds(manager).isEmpty) assert(addTime(manager) === ExecutorAllocationManager.NOT_SET) @@ -91,108 +91,108 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit sc.listenerBus.postToAll(SparkListenerStageSubmitted(createStageInfo(0, 1000))) // Keep adding until the limit is reached - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 1) assert(numExecutorsToAdd(manager) === 1) assert(addExecutors(manager) === 1) - assert(numExecutorsPending(manager) === 1) + assert(numExecutorsTarget(manager) === 2) assert(numExecutorsToAdd(manager) === 2) assert(addExecutors(manager) === 2) - assert(numExecutorsPending(manager) === 3) + assert(numExecutorsTarget(manager) === 4) assert(numExecutorsToAdd(manager) === 4) assert(addExecutors(manager) === 4) - assert(numExecutorsPending(manager) === 7) + assert(numExecutorsTarget(manager) === 8) assert(numExecutorsToAdd(manager) === 8) - assert(addExecutors(manager) === 3) // reached the limit of 10 - assert(numExecutorsPending(manager) === 10) + assert(addExecutors(manager) === 2) // reached the limit of 10 + assert(numExecutorsTarget(manager) === 10) assert(numExecutorsToAdd(manager) === 1) assert(addExecutors(manager) === 0) - assert(numExecutorsPending(manager) === 10) + assert(numExecutorsTarget(manager) === 10) assert(numExecutorsToAdd(manager) === 1) // Register previously requested executors onExecutorAdded(manager, "first") - assert(numExecutorsPending(manager) === 9) + assert(numExecutorsTarget(manager) === 10) onExecutorAdded(manager, "second") onExecutorAdded(manager, "third") onExecutorAdded(manager, "fourth") - assert(numExecutorsPending(manager) === 6) + assert(numExecutorsTarget(manager) === 10) onExecutorAdded(manager, "first") // duplicates should not count onExecutorAdded(manager, "second") - assert(numExecutorsPending(manager) === 6) + assert(numExecutorsTarget(manager) === 10) // Try adding again // This should still fail because the number pending + running is still at the limit assert(addExecutors(manager) === 0) - assert(numExecutorsPending(manager) === 6) + assert(numExecutorsTarget(manager) === 10) assert(numExecutorsToAdd(manager) === 1) assert(addExecutors(manager) === 0) - assert(numExecutorsPending(manager) === 6) + assert(numExecutorsTarget(manager) === 10) assert(numExecutorsToAdd(manager) === 1) } test("add executors capped by num pending tasks") { - sc = createSparkContext(1, 10) + sc = createSparkContext(0, 10) val manager = sc.executorAllocationManager.get sc.listenerBus.postToAll(SparkListenerStageSubmitted(createStageInfo(0, 5))) // Verify that we're capped at number of tasks in the stage - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 0) assert(numExecutorsToAdd(manager) === 1) assert(addExecutors(manager) === 1) - assert(numExecutorsPending(manager) === 1) + assert(numExecutorsTarget(manager) === 1) assert(numExecutorsToAdd(manager) === 2) assert(addExecutors(manager) === 2) - assert(numExecutorsPending(manager) === 3) + assert(numExecutorsTarget(manager) === 3) assert(numExecutorsToAdd(manager) === 4) assert(addExecutors(manager) === 2) - assert(numExecutorsPending(manager) === 5) + assert(numExecutorsTarget(manager) === 5) assert(numExecutorsToAdd(manager) === 1) - // Verify that running a task reduces the cap + // Verify that running a task doesn't affect the target sc.listenerBus.postToAll(SparkListenerStageSubmitted(createStageInfo(1, 3))) sc.listenerBus.postToAll(SparkListenerExecutorAdded( 0L, "executor-1", new ExecutorInfo("host1", 1, Map.empty))) sc.listenerBus.postToAll(SparkListenerTaskStart(1, 0, createTaskInfo(0, 0, "executor-1"))) - assert(numExecutorsPending(manager) === 4) + assert(numExecutorsTarget(manager) === 5) assert(addExecutors(manager) === 1) - assert(numExecutorsPending(manager) === 5) + assert(numExecutorsTarget(manager) === 6) assert(numExecutorsToAdd(manager) === 2) assert(addExecutors(manager) === 2) - assert(numExecutorsPending(manager) === 7) + assert(numExecutorsTarget(manager) === 8) assert(numExecutorsToAdd(manager) === 4) assert(addExecutors(manager) === 0) - assert(numExecutorsPending(manager) === 7) + assert(numExecutorsTarget(manager) === 8) assert(numExecutorsToAdd(manager) === 1) - // Verify that re-running a task doesn't reduce the cap further + // Verify that re-running a task doesn't blow things up sc.listenerBus.postToAll(SparkListenerStageSubmitted(createStageInfo(2, 3))) sc.listenerBus.postToAll(SparkListenerTaskStart(2, 0, createTaskInfo(0, 0, "executor-1"))) sc.listenerBus.postToAll(SparkListenerTaskStart(2, 0, createTaskInfo(1, 0, "executor-1"))) assert(addExecutors(manager) === 1) - assert(numExecutorsPending(manager) === 8) + assert(numExecutorsTarget(manager) === 9) assert(numExecutorsToAdd(manager) === 2) assert(addExecutors(manager) === 1) - assert(numExecutorsPending(manager) === 9) + assert(numExecutorsTarget(manager) === 10) assert(numExecutorsToAdd(manager) === 1) // Verify that running a task once we're at our limit doesn't blow things up sc.listenerBus.postToAll(SparkListenerTaskStart(2, 0, createTaskInfo(0, 1, "executor-1"))) assert(addExecutors(manager) === 0) - assert(numExecutorsPending(manager) === 9) + assert(numExecutorsTarget(manager) === 10) } test("cancel pending executors when no longer needed") { - sc = createSparkContext(1, 10) + sc = createSparkContext(0, 10) val manager = sc.executorAllocationManager.get sc.listenerBus.postToAll(SparkListenerStageSubmitted(createStageInfo(2, 5))) - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 0) assert(numExecutorsToAdd(manager) === 1) assert(addExecutors(manager) === 1) - assert(numExecutorsPending(manager) === 1) + assert(numExecutorsTarget(manager) === 1) assert(numExecutorsToAdd(manager) === 2) assert(addExecutors(manager) === 2) - assert(numExecutorsPending(manager) === 3) + assert(numExecutorsTarget(manager) === 3) val task1Info = createTaskInfo(0, 0, "executor-1") sc.listenerBus.postToAll(SparkListenerTaskStart(2, 0, task1Info)) @@ -266,7 +266,6 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit // Add a few executors assert(addExecutors(manager) === 1) assert(addExecutors(manager) === 2) - assert(addExecutors(manager) === 4) onExecutorAdded(manager, "1") onExecutorAdded(manager, "2") onExecutorAdded(manager, "3") @@ -274,55 +273,57 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit onExecutorAdded(manager, "5") onExecutorAdded(manager, "6") onExecutorAdded(manager, "7") - assert(executorIds(manager).size === 7) + onExecutorAdded(manager, "8") + assert(executorIds(manager).size === 8) // Remove until limit assert(removeExecutor(manager, "1")) assert(removeExecutor(manager, "2")) - assert(!removeExecutor(manager, "3")) // lower limit reached - assert(!removeExecutor(manager, "4")) + assert(removeExecutor(manager, "3")) + assert(!removeExecutor(manager, "4")) // lower limit reached + assert(!removeExecutor(manager, "5")) onExecutorRemoved(manager, "1") onExecutorRemoved(manager, "2") + onExecutorRemoved(manager, "3") assert(executorIds(manager).size === 5) // Add until limit - assert(addExecutors(manager) === 5) // upper limit reached + assert(addExecutors(manager) === 2) // upper limit reached assert(addExecutors(manager) === 0) - assert(!removeExecutor(manager, "3")) // still at lower limit - assert(!removeExecutor(manager, "4")) - onExecutorAdded(manager, "8") + assert(!removeExecutor(manager, "4")) // still at lower limit + assert(!removeExecutor(manager, "5")) onExecutorAdded(manager, "9") onExecutorAdded(manager, "10") onExecutorAdded(manager, "11") onExecutorAdded(manager, "12") + onExecutorAdded(manager, "13") assert(executorIds(manager).size === 10) // Remove succeeds again, now that we are no longer at the lower limit - assert(removeExecutor(manager, "3")) assert(removeExecutor(manager, "4")) assert(removeExecutor(manager, "5")) assert(removeExecutor(manager, "6")) + assert(removeExecutor(manager, "7")) assert(executorIds(manager).size === 10) - assert(addExecutors(manager) === 1) - onExecutorRemoved(manager, "3") + assert(addExecutors(manager) === 0) onExecutorRemoved(manager, "4") + onExecutorRemoved(manager, "5") assert(executorIds(manager).size === 8) - // Add succeeds again, now that we are no longer at the upper limit - // Number of executors added restarts at 1 - assert(addExecutors(manager) === 2) - assert(addExecutors(manager) === 1) // upper limit reached + // Number of executors pending restarts at 1 + assert(numExecutorsToAdd(manager) === 1) assert(addExecutors(manager) === 0) assert(executorIds(manager).size === 8) - onExecutorRemoved(manager, "5") onExecutorRemoved(manager, "6") - onExecutorAdded(manager, "13") + onExecutorRemoved(manager, "7") onExecutorAdded(manager, "14") + onExecutorAdded(manager, "15") assert(executorIds(manager).size === 8) assert(addExecutors(manager) === 0) // still at upper limit - onExecutorAdded(manager, "15") onExecutorAdded(manager, "16") + onExecutorAdded(manager, "17") assert(executorIds(manager).size === 10) + assert(numExecutorsTarget(manager) === 10) } test("starting/canceling add timer") { @@ -405,33 +406,33 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit } test("mock polling loop with no events") { - sc = createSparkContext(1, 20) + sc = createSparkContext(0, 20) val manager = sc.executorAllocationManager.get val clock = new ManualClock(2020L) manager.setClock(clock) // No events - we should not be adding or removing - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 0) assert(executorsPendingToRemove(manager).isEmpty) schedule(manager) - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 0) assert(executorsPendingToRemove(manager).isEmpty) clock.advance(100L) schedule(manager) - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 0) assert(executorsPendingToRemove(manager).isEmpty) clock.advance(1000L) schedule(manager) - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 0) assert(executorsPendingToRemove(manager).isEmpty) clock.advance(10000L) schedule(manager) - assert(numExecutorsPending(manager) === 0) + assert(numExecutorsTarget(manager) === 0) assert(executorsPendingToRemove(manager).isEmpty) } test("mock polling loop add behavior") { - sc = createSparkContext(1, 20) + sc = createSparkContext(0, 20) val clock = new ManualClock(2020L) val manager = sc.executorAllocationManager.get manager.setClock(clock) @@ -441,43 +442,43 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit onSchedulerBacklogged(manager) clock.advance(schedulerBacklogTimeout * 1000 / 2) schedule(manager) - assert(numExecutorsPending(manager) === 0) // timer not exceeded yet + assert(numExecutorsTarget(manager) === 0) // timer not exceeded yet clock.advance(schedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 1) // first timer exceeded + assert(numExecutorsTarget(manager) === 1) // first timer exceeded clock.advance(sustainedSchedulerBacklogTimeout * 1000 / 2) schedule(manager) - assert(numExecutorsPending(manager) === 1) // second timer not exceeded yet + assert(numExecutorsTarget(manager) === 1) // second timer not exceeded yet clock.advance(sustainedSchedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 1 + 2) // second timer exceeded + assert(numExecutorsTarget(manager) === 1 + 2) // second timer exceeded clock.advance(sustainedSchedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 1 + 2 + 4) // third timer exceeded + assert(numExecutorsTarget(manager) === 1 + 2 + 4) // third timer exceeded // Scheduler queue drained onSchedulerQueueEmpty(manager) clock.advance(sustainedSchedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 7) // timer is canceled + assert(numExecutorsTarget(manager) === 7) // timer is canceled clock.advance(sustainedSchedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 7) + assert(numExecutorsTarget(manager) === 7) // Scheduler queue backlogged again onSchedulerBacklogged(manager) clock.advance(schedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 7 + 1) // timer restarted + assert(numExecutorsTarget(manager) === 7 + 1) // timer restarted clock.advance(sustainedSchedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 7 + 1 + 2) + assert(numExecutorsTarget(manager) === 7 + 1 + 2) clock.advance(sustainedSchedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 7 + 1 + 2 + 4) + assert(numExecutorsTarget(manager) === 7 + 1 + 2 + 4) clock.advance(sustainedSchedulerBacklogTimeout * 1000) schedule(manager) - assert(numExecutorsPending(manager) === 20) // limit reached + assert(numExecutorsTarget(manager) === 20) // limit reached } test("mock polling loop remove behavior") { @@ -671,6 +672,31 @@ class ExecutorAllocationManagerSuite extends FunSuite with LocalSparkContext wit assert(!removeTimes(manager).contains("executor-1")) } + test("avoid ramp up when target < running executors") { + sc = createSparkContext(0, 100000) + val manager = sc.executorAllocationManager.get + val stage1 = createStageInfo(0, 1000) + sc.listenerBus.postToAll(SparkListenerStageSubmitted(stage1)) + + assert(addExecutors(manager) === 1) + assert(addExecutors(manager) === 2) + assert(addExecutors(manager) === 4) + assert(addExecutors(manager) === 8) + assert(numExecutorsTarget(manager) === 15) + (0 until 15).foreach { i => + onExecutorAdded(manager, s"executor-$i") + } + assert(executorIds(manager).size === 15) + sc.listenerBus.postToAll(SparkListenerStageCompleted(stage1)) + + adjustRequestedExecutors(manager) + assert(numExecutorsTarget(manager) === 0) + + sc.listenerBus.postToAll(SparkListenerStageSubmitted(createStageInfo(1, 1000))) + addExecutors(manager) + assert(numExecutorsTarget(manager) === 16) + } + private def createSparkContext(minExecutors: Int = 1, maxExecutors: Int = 5): SparkContext = { val conf = new SparkConf() .setMaster("local") @@ -713,7 +739,7 @@ private object ExecutorAllocationManagerSuite extends PrivateMethodTester { * ------------------------------------------------------- */ private val _numExecutorsToAdd = PrivateMethod[Int]('numExecutorsToAdd) - private val _numExecutorsPending = PrivateMethod[Int]('numExecutorsPending) + private val _numExecutorsTarget = PrivateMethod[Int]('numExecutorsTarget) private val _maxNumExecutorsNeeded = PrivateMethod[Int]('maxNumExecutorsNeeded) private val _executorsPendingToRemove = PrivateMethod[collection.Set[String]]('executorsPendingToRemove) @@ -722,7 +748,8 @@ private object ExecutorAllocationManagerSuite extends PrivateMethodTester { private val _removeTimes = PrivateMethod[collection.Map[String, Long]]('removeTimes) private val _schedule = PrivateMethod[Unit]('schedule) private val _addExecutors = PrivateMethod[Int]('addExecutors) - private val _addOrCancelExecutorRequests = PrivateMethod[Int]('addOrCancelExecutorRequests) + private val _updateAndSyncNumExecutorsTarget = + PrivateMethod[Int]('updateAndSyncNumExecutorsTarget) private val _removeExecutor = PrivateMethod[Boolean]('removeExecutor) private val _onExecutorAdded = PrivateMethod[Unit]('onExecutorAdded) private val _onExecutorRemoved = PrivateMethod[Unit]('onExecutorRemoved) @@ -735,8 +762,8 @@ private object ExecutorAllocationManagerSuite extends PrivateMethodTester { manager invokePrivate _numExecutorsToAdd() } - private def numExecutorsPending(manager: ExecutorAllocationManager): Int = { - manager invokePrivate _numExecutorsPending() + private def numExecutorsTarget(manager: ExecutorAllocationManager): Int = { + manager invokePrivate _numExecutorsTarget() } private def executorsPendingToRemove( @@ -766,7 +793,7 @@ private object ExecutorAllocationManagerSuite extends PrivateMethodTester { } private def adjustRequestedExecutors(manager: ExecutorAllocationManager): Int = { - manager invokePrivate _addOrCancelExecutorRequests(0L) + manager invokePrivate _updateAndSyncNumExecutorsTarget(0L) } private def removeExecutor(manager: ExecutorAllocationManager, id: String): Boolean = { diff --git a/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala b/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala index 0fd570e5297d9..b789912e9ebef 100644 --- a/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala +++ b/core/src/test/scala/org/apache/spark/HeartbeatReceiverSuite.scala @@ -48,7 +48,7 @@ class HeartbeatReceiverSuite extends FunSuite with LocalSparkContext { val metrics = new TaskMetrics val blockManagerId = BlockManagerId("executor-1", "localhost", 12345) - val response = receiverRef.askWithReply[HeartbeatResponse]( + val response = receiverRef.askWithRetry[HeartbeatResponse]( Heartbeat("executor-1", Array(1L -> metrics), blockManagerId)) verify(scheduler).executorHeartbeatReceived( @@ -71,7 +71,7 @@ class HeartbeatReceiverSuite extends FunSuite with LocalSparkContext { val metrics = new TaskMetrics val blockManagerId = BlockManagerId("executor-1", "localhost", 12345) - val response = receiverRef.askWithReply[HeartbeatResponse]( + val response = receiverRef.askWithRetry[HeartbeatResponse]( Heartbeat("executor-1", Array(1L -> metrics), blockManagerId)) verify(scheduler).executorHeartbeatReceived( diff --git a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala index 4d3e09793faff..ae17fc60e4a43 100644 --- a/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala +++ b/core/src/test/scala/org/apache/spark/JobCancellationSuite.scala @@ -141,6 +141,41 @@ class JobCancellationSuite extends FunSuite with Matchers with BeforeAndAfter assert(jobB.get() === 100) } + test("inherited job group (SPARK-6629)") { + sc = new SparkContext("local[2]", "test") + + // Add a listener to release the semaphore once any tasks are launched. + val sem = new Semaphore(0) + sc.addSparkListener(new SparkListener { + override def onTaskStart(taskStart: SparkListenerTaskStart) { + sem.release() + } + }) + + sc.setJobGroup("jobA", "this is a job to be cancelled") + @volatile var exception: Exception = null + val jobA = new Thread() { + // The job group should be inherited by this thread + override def run(): Unit = { + exception = intercept[SparkException] { + sc.parallelize(1 to 10000, 2).map { i => Thread.sleep(10); i }.count() + } + } + } + jobA.start() + + // Block until both tasks of job A have started and cancel job A. + sem.acquire(2) + sc.cancelJobGroup("jobA") + jobA.join(10000) + assert(!jobA.isAlive) + assert(exception.getMessage contains "cancel") + + // Once A is cancelled, job B should finish fairly quickly. + val jobB = sc.parallelize(1 to 100, 2).countAsync() + assert(jobB.get() === 100) + } + test("job group with interruption") { sc = new SparkContext("local[2]", "test") diff --git a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala index 728558a424780..9049db7755358 100644 --- a/core/src/test/scala/org/apache/spark/SparkContextSuite.scala +++ b/core/src/test/scala/org/apache/spark/SparkContextSuite.scala @@ -25,7 +25,9 @@ import com.google.common.io.Files import org.scalatest.FunSuite -import org.apache.hadoop.io.BytesWritable +import org.apache.hadoop.io.{BytesWritable, LongWritable, Text} +import org.apache.hadoop.mapred.TextInputFormat +import org.apache.hadoop.mapreduce.lib.input.{TextInputFormat => NewTextInputFormat} import org.apache.spark.util.Utils import scala.concurrent.Await @@ -213,4 +215,63 @@ class SparkContextSuite extends FunSuite with LocalSparkContext { sc.stop() } } + + test("Comma separated paths for newAPIHadoopFile/wholeTextFiles/binaryFiles (SPARK-7155)") { + // Regression test for SPARK-7155 + // dir1 and dir2 are used for wholeTextFiles and binaryFiles + val dir1 = Utils.createTempDir() + val dir2 = Utils.createTempDir() + + val dirpath1=dir1.getAbsolutePath + val dirpath2=dir2.getAbsolutePath + + // file1 and file2 are placed inside dir1, they are also used for + // textFile, hadoopFile, and newAPIHadoopFile + // file3, file4 and file5 are placed inside dir2, they are used for + // textFile, hadoopFile, and newAPIHadoopFile as well + val file1 = new File(dir1, "part-00000") + val file2 = new File(dir1, "part-00001") + val file3 = new File(dir2, "part-00000") + val file4 = new File(dir2, "part-00001") + val file5 = new File(dir2, "part-00002") + + val filepath1=file1.getAbsolutePath + val filepath2=file2.getAbsolutePath + val filepath3=file3.getAbsolutePath + val filepath4=file4.getAbsolutePath + val filepath5=file5.getAbsolutePath + + + try { + // Create 5 text files. + Files.write("someline1 in file1\nsomeline2 in file1\nsomeline3 in file1", file1, UTF_8) + Files.write("someline1 in file2\nsomeline2 in file2", file2, UTF_8) + Files.write("someline1 in file3", file3, UTF_8) + Files.write("someline1 in file4\nsomeline2 in file4", file4, UTF_8) + Files.write("someline1 in file2\nsomeline2 in file5", file5, UTF_8) + + sc = new SparkContext(new SparkConf().setAppName("test").setMaster("local")) + + // Test textFile, hadoopFile, and newAPIHadoopFile for file1 and file2 + assert(sc.textFile(filepath1 + "," + filepath2).count() == 5L) + assert(sc.hadoopFile(filepath1 + "," + filepath2, + classOf[TextInputFormat], classOf[LongWritable], classOf[Text]).count() == 5L) + assert(sc.newAPIHadoopFile(filepath1 + "," + filepath2, + classOf[NewTextInputFormat], classOf[LongWritable], classOf[Text]).count() == 5L) + + // Test textFile, hadoopFile, and newAPIHadoopFile for file3, file4, and file5 + assert(sc.textFile(filepath3 + "," + filepath4 + "," + filepath5).count() == 5L) + assert(sc.hadoopFile(filepath3 + "," + filepath4 + "," + filepath5, + classOf[TextInputFormat], classOf[LongWritable], classOf[Text]).count() == 5L) + assert(sc.newAPIHadoopFile(filepath3 + "," + filepath4 + "," + filepath5, + classOf[NewTextInputFormat], classOf[LongWritable], classOf[Text]).count() == 5L) + + // Test wholeTextFiles, and binaryFiles for dir1 and dir2 + assert(sc.wholeTextFiles(dirpath1 + "," + dirpath2).count() == 5L) + assert(sc.binaryFiles(dirpath1 + "," + dirpath2).count() == 5L) + + } finally { + sc.stop() + } + } } diff --git a/core/src/test/scala/org/apache/spark/ThreadingSuite.scala b/core/src/test/scala/org/apache/spark/ThreadingSuite.scala index b5383d553add1..10917c866cc7d 100644 --- a/core/src/test/scala/org/apache/spark/ThreadingSuite.scala +++ b/core/src/test/scala/org/apache/spark/ThreadingSuite.scala @@ -17,10 +17,11 @@ package org.apache.spark -import java.util.concurrent.Semaphore +import java.util.concurrent.{TimeUnit, Semaphore} import java.util.concurrent.atomic.AtomicBoolean import java.util.concurrent.atomic.AtomicInteger +import org.apache.spark.scheduler._ import org.scalatest.FunSuite /** @@ -189,4 +190,47 @@ class ThreadingSuite extends FunSuite with LocalSparkContext { assert(sc.getLocalProperty("test") === "parent") assert(sc.getLocalProperty("Foo") === null) } + + test("mutations to local properties should not affect submitted jobs (SPARK-6629)") { + val jobStarted = new Semaphore(0) + val jobEnded = new Semaphore(0) + @volatile var jobResult: JobResult = null + + sc = new SparkContext("local", "test") + sc.setJobGroup("originalJobGroupId", "description") + sc.addSparkListener(new SparkListener { + override def onJobStart(jobStart: SparkListenerJobStart): Unit = { + jobStarted.release() + } + override def onJobEnd(jobEnd: SparkListenerJobEnd): Unit = { + jobResult = jobEnd.jobResult + jobEnded.release() + } + }) + + // Create a new thread which will inherit the current thread's properties + val thread = new Thread() { + override def run(): Unit = { + assert(sc.getLocalProperty(SparkContext.SPARK_JOB_GROUP_ID) === "originalJobGroupId") + // Sleeps for a total of 10 seconds, but allows cancellation to interrupt the task + try { + sc.parallelize(1 to 100).foreach { x => + Thread.sleep(100) + } + } catch { + case s: SparkException => // ignored so that we don't print noise in test logs + } + } + } + thread.start() + // Wait for the job to start, then mutate the original properties, which should have been + // inherited by the running job but hopefully defensively copied or snapshotted: + jobStarted.tryAcquire(10, TimeUnit.SECONDS) + sc.setJobGroup("modifiedJobGroupId", "description") + // Canceling the original job group should cancel the running job. In other words, the + // modification of the properties object should not affect the properties of running jobs + sc.cancelJobGroup("originalJobGroupId") + jobEnded.tryAcquire(10, TimeUnit.SECONDS) + assert(jobResult.isInstanceOf[JobFailed]) + } } diff --git a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala index c4e6f06146b0a..029a1156fda6b 100644 --- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala @@ -334,7 +334,7 @@ class SparkSubmitSuite extends FunSuite with Matchers with ResetSystemProperties runSparkSubmit(args) } - test("includes jars passed in through --packages") { + ignore("includes jars passed in through --packages") { val unusedJar = TestUtils.createJarWithClasses(Seq.empty) val packagesString = "com.databricks:spark-csv_2.10:0.1,com.databricks:spark-avro_2.10:0.1" val args = Seq( diff --git a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitUtilsSuite.scala b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitUtilsSuite.scala index 8bcca926097a1..2df2597e058cd 100644 --- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitUtilsSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitUtilsSuite.scala @@ -19,6 +19,8 @@ package org.apache.spark.deploy import java.io.{PrintStream, OutputStream, File} +import org.apache.ivy.core.settings.IvySettings + import scala.collection.mutable.ArrayBuffer import org.scalatest.{BeforeAndAfterAll, FunSuite} @@ -56,24 +58,23 @@ class SparkSubmitUtilsSuite extends FunSuite with BeforeAndAfterAll { } test("create repo resolvers") { - val resolver1 = SparkSubmitUtils.createRepoResolvers(None) + val settings = new IvySettings + val res1 = SparkSubmitUtils.createRepoResolvers(None, settings) // should have central and spark-packages by default - assert(resolver1.getResolvers.size() === 2) - assert(resolver1.getResolvers.get(0).asInstanceOf[IBiblioResolver].getName === "central") - assert(resolver1.getResolvers.get(1).asInstanceOf[IBiblioResolver].getName === "spark-packages") + assert(res1.getResolvers.size() === 4) + assert(res1.getResolvers.get(0).asInstanceOf[IBiblioResolver].getName === "local-m2-cache") + assert(res1.getResolvers.get(1).asInstanceOf[IBiblioResolver].getName === "local-ivy-cache") + assert(res1.getResolvers.get(2).asInstanceOf[IBiblioResolver].getName === "central") + assert(res1.getResolvers.get(3).asInstanceOf[IBiblioResolver].getName === "spark-packages") val repos = "a/1,b/2,c/3" - val resolver2 = SparkSubmitUtils.createRepoResolvers(Option(repos)) - assert(resolver2.getResolvers.size() === 5) + val resolver2 = SparkSubmitUtils.createRepoResolvers(Option(repos), settings) + assert(resolver2.getResolvers.size() === 7) val expected = repos.split(",").map(r => s"$r/") resolver2.getResolvers.toArray.zipWithIndex.foreach { case (resolver: IBiblioResolver, i) => - if (i == 0) { - assert(resolver.getName === "central") - } else if (i == 1) { - assert(resolver.getName === "spark-packages") - } else { - assert(resolver.getName === s"repo-${i - 1}") - assert(resolver.getRoot === expected(i - 2)) + if (i > 3) { + assert(resolver.getName === s"repo-${i - 3}") + assert(resolver.getRoot === expected(i - 4)) } } } @@ -116,7 +117,7 @@ class SparkSubmitUtilsSuite extends FunSuite with BeforeAndAfterAll { } } - test("neglects Spark and Spark's dependencies") { + ignore("neglects Spark and Spark's dependencies") { val components = Seq("bagel_", "catalyst_", "core_", "graphx_", "hive_", "mllib_", "repl_", "sql_", "streaming_", "yarn_", "network-common_", "network-shuffle_", "network-yarn_") diff --git a/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala b/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala index 9e367a0d9af0d..a0a0afa48833e 100644 --- a/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/history/FsHistoryProviderSuite.scala @@ -19,6 +19,7 @@ package org.apache.spark.deploy.history import java.io.{BufferedOutputStream, File, FileOutputStream, OutputStreamWriter} import java.net.URI +import java.util.concurrent.TimeUnit import scala.io.Source @@ -30,7 +31,7 @@ import org.scalatest.Matchers import org.apache.spark.{Logging, SparkConf} import org.apache.spark.io._ import org.apache.spark.scheduler._ -import org.apache.spark.util.{JsonProtocol, Utils} +import org.apache.spark.util.{JsonProtocol, ManualClock, Utils} class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers with Logging { @@ -47,10 +48,11 @@ class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers /** Create a fake log file using the new log format used in Spark 1.3+ */ private def newLogFile( appId: String, + appAttemptId: Option[String], inProgress: Boolean, codec: Option[String] = None): File = { val ip = if (inProgress) EventLoggingListener.IN_PROGRESS else "" - val logUri = EventLoggingListener.getLogPath(testDir.toURI, appId) + val logUri = EventLoggingListener.getLogPath(testDir.toURI, appId, appAttemptId) val logPath = new URI(logUri).getPath + ip new File(logPath) } @@ -59,22 +61,23 @@ class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers val provider = new FsHistoryProvider(createTestConf()) // Write a new-style application log. - val newAppComplete = newLogFile("new1", inProgress = false) + val newAppComplete = newLogFile("new1", None, inProgress = false) writeFile(newAppComplete, true, None, - SparkListenerApplicationStart("new-app-complete", None, 1L, "test"), + SparkListenerApplicationStart("new-app-complete", None, 1L, "test", None), SparkListenerApplicationEnd(5L) ) // Write a new-style application log. - val newAppCompressedComplete = newLogFile("new1compressed", inProgress = false, Some("lzf")) + val newAppCompressedComplete = newLogFile("new1compressed", None, inProgress = false, + Some("lzf")) writeFile(newAppCompressedComplete, true, None, - SparkListenerApplicationStart("new-app-compressed-complete", None, 1L, "test"), + SparkListenerApplicationStart("new-app-compressed-complete", None, 1L, "test", None), SparkListenerApplicationEnd(4L)) // Write an unfinished app, new-style. - val newAppIncomplete = newLogFile("new2", inProgress = true) + val newAppIncomplete = newLogFile("new2", None, inProgress = true) writeFile(newAppIncomplete, true, None, - SparkListenerApplicationStart("new-app-incomplete", None, 1L, "test") + SparkListenerApplicationStart("new-app-incomplete", None, 1L, "test", None) ) // Write an old-style application log. @@ -82,7 +85,7 @@ class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers oldAppComplete.mkdir() createEmptyFile(new File(oldAppComplete, provider.SPARK_VERSION_PREFIX + "1.0")) writeFile(new File(oldAppComplete, provider.LOG_PREFIX + "1"), false, None, - SparkListenerApplicationStart("old-app-complete", None, 2L, "test"), + SparkListenerApplicationStart("old-app-complete", None, 2L, "test", None), SparkListenerApplicationEnd(3L) ) createEmptyFile(new File(oldAppComplete, provider.APPLICATION_COMPLETE)) @@ -96,33 +99,45 @@ class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers oldAppIncomplete.mkdir() createEmptyFile(new File(oldAppIncomplete, provider.SPARK_VERSION_PREFIX + "1.0")) writeFile(new File(oldAppIncomplete, provider.LOG_PREFIX + "1"), false, None, - SparkListenerApplicationStart("old-app-incomplete", None, 2L, "test") + SparkListenerApplicationStart("old-app-incomplete", None, 2L, "test", None) ) // Force a reload of data from the log directory, and check that both logs are loaded. // Take the opportunity to check that the offset checks work as expected. - provider.checkForLogs() + updateAndCheck(provider) { list => + list.size should be (5) + list.count(_.attempts.head.completed) should be (3) + + def makeAppInfo( + id: String, + name: String, + start: Long, + end: Long, + lastMod: Long, + user: String, + completed: Boolean): ApplicationHistoryInfo = { + ApplicationHistoryInfo(id, name, + List(ApplicationAttemptInfo(None, start, end, lastMod, user, completed))) + } - val list = provider.getListing().toSeq - list should not be (null) - list.size should be (5) - list.count(_.completed) should be (3) - - list(0) should be (ApplicationHistoryInfo(newAppComplete.getName(), "new-app-complete", 1L, 5L, - newAppComplete.lastModified(), "test", true)) - list(1) should be (ApplicationHistoryInfo(newAppCompressedComplete.getName(), - "new-app-compressed-complete", 1L, 4L, newAppCompressedComplete.lastModified(), "test", true)) - list(2) should be (ApplicationHistoryInfo(oldAppComplete.getName(), "old-app-complete", 2L, 3L, - oldAppComplete.lastModified(), "test", true)) - list(3) should be (ApplicationHistoryInfo(oldAppIncomplete.getName(), "old-app-incomplete", 2L, - -1L, oldAppIncomplete.lastModified(), "test", false)) - list(4) should be (ApplicationHistoryInfo(newAppIncomplete.getName(), "new-app-incomplete", 1L, - -1L, newAppIncomplete.lastModified(), "test", false)) - - // Make sure the UI can be rendered. - list.foreach { case info => - val appUi = provider.getAppUI(info.id) - appUi should not be null + list(0) should be (makeAppInfo(newAppComplete.getName(), "new-app-complete", 1L, 5L, + newAppComplete.lastModified(), "test", true)) + list(1) should be (makeAppInfo(newAppCompressedComplete.getName(), + "new-app-compressed-complete", 1L, 4L, newAppCompressedComplete.lastModified(), "test", + true)) + list(2) should be (makeAppInfo(oldAppComplete.getName(), "old-app-complete", 2L, 3L, + oldAppComplete.lastModified(), "test", true)) + list(3) should be (makeAppInfo(oldAppIncomplete.getName(), "old-app-incomplete", 2L, -1L, + oldAppIncomplete.lastModified(), "test", false)) + list(4) should be (makeAppInfo(newAppIncomplete.getName(), "new-app-incomplete", 1L, -1L, + newAppIncomplete.lastModified(), "test", false)) + + // Make sure the UI can be rendered. + list.foreach { case info => + val appUi = provider.getAppUI(info.id, None) + appUi should not be null + appUi should not be None + } } } @@ -138,7 +153,7 @@ class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers logDir.mkdir() createEmptyFile(new File(logDir, provider.SPARK_VERSION_PREFIX + "1.0")) writeFile(new File(logDir, provider.LOG_PREFIX + "1"), false, Option(codec), - SparkListenerApplicationStart("app2", None, 2L, "test"), + SparkListenerApplicationStart("app2", None, 2L, "test", None), SparkListenerApplicationEnd(3L) ) createEmptyFile(new File(logDir, provider.COMPRESSION_CODEC_PREFIX + codecName)) @@ -159,52 +174,52 @@ class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers } test("SPARK-3697: ignore directories that cannot be read.") { - val logFile1 = newLogFile("new1", inProgress = false) + val logFile1 = newLogFile("new1", None, inProgress = false) writeFile(logFile1, true, None, - SparkListenerApplicationStart("app1-1", None, 1L, "test"), + SparkListenerApplicationStart("app1-1", None, 1L, "test", None), SparkListenerApplicationEnd(2L) ) - val logFile2 = newLogFile("new2", inProgress = false) + val logFile2 = newLogFile("new2", None, inProgress = false) writeFile(logFile2, true, None, - SparkListenerApplicationStart("app1-2", None, 1L, "test"), + SparkListenerApplicationStart("app1-2", None, 1L, "test", None), SparkListenerApplicationEnd(2L) ) logFile2.setReadable(false, false) val provider = new FsHistoryProvider(createTestConf()) - provider.checkForLogs() - - val list = provider.getListing().toSeq - list should not be (null) - list.size should be (1) + updateAndCheck(provider) { list => + list.size should be (1) + } } test("history file is renamed from inprogress to completed") { val provider = new FsHistoryProvider(createTestConf()) - val logFile1 = newLogFile("app1", inProgress = true) + val logFile1 = newLogFile("app1", None, inProgress = true) writeFile(logFile1, true, None, - SparkListenerApplicationStart("app1", Some("app1"), 1L, "test"), + SparkListenerApplicationStart("app1", Some("app1"), 1L, "test", None), SparkListenerApplicationEnd(2L) ) - provider.checkForLogs() - val appListBeforeRename = provider.getListing() - appListBeforeRename.size should be (1) - appListBeforeRename.head.logPath should endWith(EventLoggingListener.IN_PROGRESS) + updateAndCheck(provider) { list => + list.size should be (1) + list.head.attempts.head.asInstanceOf[FsApplicationAttemptInfo].logPath should + endWith(EventLoggingListener.IN_PROGRESS) + } - logFile1.renameTo(newLogFile("app1", inProgress = false)) - provider.checkForLogs() - val appListAfterRename = provider.getListing() - appListAfterRename.size should be (1) - appListAfterRename.head.logPath should not endWith(EventLoggingListener.IN_PROGRESS) + logFile1.renameTo(newLogFile("app1", None, inProgress = false)) + updateAndCheck(provider) { list => + list.size should be (1) + list.head.attempts.head.asInstanceOf[FsApplicationAttemptInfo].logPath should not + endWith(EventLoggingListener.IN_PROGRESS) + } } test("SPARK-5582: empty log directory") { val provider = new FsHistoryProvider(createTestConf()) - val logFile1 = newLogFile("app1", inProgress = true) + val logFile1 = newLogFile("app1", None, inProgress = true) writeFile(logFile1, true, None, - SparkListenerApplicationStart("app1", Some("app1"), 1L, "test"), + SparkListenerApplicationStart("app1", Some("app1"), 1L, "test", None), SparkListenerApplicationEnd(2L)) val oldLog = new File(testDir, "old1") @@ -215,6 +230,126 @@ class FsHistoryProviderSuite extends FunSuite with BeforeAndAfter with Matchers appListAfterRename.size should be (1) } + test("apps with multiple attempts") { + val provider = new FsHistoryProvider(createTestConf()) + + val attempt1 = newLogFile("app1", Some("attempt1"), inProgress = false) + writeFile(attempt1, true, None, + SparkListenerApplicationStart("app1", Some("app1"), 1L, "test", Some("attempt1")), + SparkListenerApplicationEnd(2L) + ) + + updateAndCheck(provider) { list => + list.size should be (1) + list.head.attempts.size should be (1) + } + + val attempt2 = newLogFile("app1", Some("attempt2"), inProgress = true) + writeFile(attempt2, true, None, + SparkListenerApplicationStart("app1", Some("app1"), 3L, "test", Some("attempt2")) + ) + + updateAndCheck(provider) { list => + list.size should be (1) + list.head.attempts.size should be (2) + list.head.attempts.head.attemptId should be (Some("attempt2")) + } + + val completedAttempt2 = newLogFile("app1", Some("attempt2"), inProgress = false) + attempt2.delete() + writeFile(attempt2, true, None, + SparkListenerApplicationStart("app1", Some("app1"), 3L, "test", Some("attempt2")), + SparkListenerApplicationEnd(4L) + ) + + updateAndCheck(provider) { list => + list should not be (null) + list.size should be (1) + list.head.attempts.size should be (2) + list.head.attempts.head.attemptId should be (Some("attempt2")) + } + + val app2Attempt1 = newLogFile("app2", Some("attempt1"), inProgress = false) + writeFile(attempt2, true, None, + SparkListenerApplicationStart("app2", Some("app2"), 5L, "test", Some("attempt1")), + SparkListenerApplicationEnd(6L) + ) + + updateAndCheck(provider) { list => + list.size should be (2) + list.head.attempts.size should be (1) + list.last.attempts.size should be (2) + list.head.attempts.head.attemptId should be (Some("attempt1")) + + list.foreach { case app => + app.attempts.foreach { attempt => + val appUi = provider.getAppUI(app.id, attempt.attemptId) + appUi should not be null + } + } + + } + } + + test("log cleaner") { + val maxAge = TimeUnit.SECONDS.toMillis(10) + val clock = new ManualClock(maxAge / 2) + val provider = new FsHistoryProvider( + createTestConf().set("spark.history.fs.cleaner.maxAge", s"${maxAge}ms"), clock) + + val log1 = newLogFile("app1", Some("attempt1"), inProgress = false) + writeFile(log1, true, None, + SparkListenerApplicationStart("app1", Some("app1"), 1L, "test", Some("attempt1")), + SparkListenerApplicationEnd(2L) + ) + log1.setLastModified(0L) + + val log2 = newLogFile("app1", Some("attempt2"), inProgress = false) + writeFile(log2, true, None, + SparkListenerApplicationStart("app1", Some("app1"), 3L, "test", Some("attempt2")), + SparkListenerApplicationEnd(4L) + ) + log2.setLastModified(clock.getTimeMillis()) + + updateAndCheck(provider) { list => + list.size should be (1) + list.head.attempts.size should be (2) + } + + // Move the clock forward so log1 exceeds the max age. + clock.advance(maxAge) + + updateAndCheck(provider) { list => + list.size should be (1) + list.head.attempts.size should be (1) + list.head.attempts.head.attemptId should be (Some("attempt2")) + } + assert(!log1.exists()) + + // Do the same for the other log. + clock.advance(maxAge) + + updateAndCheck(provider) { list => + list.size should be (0) + } + assert(!log2.exists()) + } + + /** + * Asks the provider to check for logs and calls a function to perform checks on the updated + * app list. Example: + * + * updateAndCheck(provider) { list => + * // asserts + * } + */ + private def updateAndCheck(provider: FsHistoryProvider) + (checkFn: Seq[ApplicationHistoryInfo] => Unit): Unit = { + provider.checkForLogs() + provider.cleanLogs() + checkFn(provider.getListing().toSeq) + } + private def writeFile(file: File, isNewFormat: Boolean, codec: Option[CompressionCodec], events: SparkListenerEvent*) = { val fstream = new FileOutputStream(file) diff --git a/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala b/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala index 20de46fdab909..71ba9c18257b8 100644 --- a/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/history/HistoryServerSuite.scala @@ -36,7 +36,8 @@ class HistoryServerSuite extends FunSuite with Matchers with MockitoSugar { val request = mock[HttpServletRequest] val ui = mock[SparkUI] val link = "/history/app1" - val info = new ApplicationHistoryInfo("app1", "app1", 0, 2, 1, "xxx", true) + val info = new ApplicationHistoryInfo("app1", "app1", + List(ApplicationAttemptInfo(None, 0, 2, 1, "xxx", true))) when(historyServer.getApplicationList()).thenReturn(Seq(info)) when(ui.basePath).thenReturn(link) when(historyServer.getProviderConfig()).thenReturn(Map[String, String]()) diff --git a/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala b/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala index 0a318a27ac212..f4d548d9e7720 100644 --- a/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/rest/StandaloneRestSubmitSuite.scala @@ -39,7 +39,6 @@ import org.apache.spark.deploy.master.DriverState._ * Tests for the REST application submission protocol used in standalone cluster mode. */ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { - private val client = new RestSubmissionClient private var actorSystem: Option[ActorSystem] = None private var server: Option[RestSubmissionServer] = None @@ -52,7 +51,7 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { val appArgs = Array("one", "two", "three") val sparkProperties = Map("spark.app.name" -> "pi") val environmentVariables = Map("SPARK_ONE" -> "UN", "SPARK_TWO" -> "DEUX") - val request = client.constructSubmitRequest( + val request = new RestSubmissionClient("spark://host:port").constructSubmitRequest( "my-app-resource", "my-main-class", appArgs, sparkProperties, environmentVariables) assert(request.action === Utils.getFormattedClassName(request)) assert(request.clientSparkVersion === SPARK_VERSION) @@ -71,7 +70,7 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { val request = constructSubmitRequest(masterUrl, appArgs) assert(request.appArgs === appArgs) assert(request.sparkProperties("spark.master") === masterUrl) - val response = client.createSubmission(masterUrl, request) + val response = new RestSubmissionClient(masterUrl).createSubmission(request) val submitResponse = getSubmitResponse(response) assert(submitResponse.action === Utils.getFormattedClassName(submitResponse)) assert(submitResponse.serverSparkVersion === SPARK_VERSION) @@ -102,7 +101,7 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { val submissionId = "my-lyft-driver" val killMessage = "your driver is killed" val masterUrl = startDummyServer(killMessage = killMessage) - val response = client.killSubmission(masterUrl, submissionId) + val response = new RestSubmissionClient(masterUrl).killSubmission(submissionId) val killResponse = getKillResponse(response) assert(killResponse.action === Utils.getFormattedClassName(killResponse)) assert(killResponse.serverSparkVersion === SPARK_VERSION) @@ -116,7 +115,7 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { val submissionState = KILLED val submissionException = new Exception("there was an irresponsible mix of alcohol and cars") val masterUrl = startDummyServer(state = submissionState, exception = Some(submissionException)) - val response = client.requestSubmissionStatus(masterUrl, submissionId) + val response = new RestSubmissionClient(masterUrl).requestSubmissionStatus(submissionId) val statusResponse = getStatusResponse(response) assert(statusResponse.action === Utils.getFormattedClassName(statusResponse)) assert(statusResponse.serverSparkVersion === SPARK_VERSION) @@ -129,13 +128,14 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { test("create then kill") { val masterUrl = startSmartServer() val request = constructSubmitRequest(masterUrl) - val response1 = client.createSubmission(masterUrl, request) + val client = new RestSubmissionClient(masterUrl) + val response1 = client.createSubmission(request) val submitResponse = getSubmitResponse(response1) assert(submitResponse.success) assert(submitResponse.submissionId != null) // kill submission that was just created val submissionId = submitResponse.submissionId - val response2 = client.killSubmission(masterUrl, submissionId) + val response2 = client.killSubmission(submissionId) val killResponse = getKillResponse(response2) assert(killResponse.success) assert(killResponse.submissionId === submissionId) @@ -144,13 +144,14 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { test("create then request status") { val masterUrl = startSmartServer() val request = constructSubmitRequest(masterUrl) - val response1 = client.createSubmission(masterUrl, request) + val client = new RestSubmissionClient(masterUrl) + val response1 = client.createSubmission(request) val submitResponse = getSubmitResponse(response1) assert(submitResponse.success) assert(submitResponse.submissionId != null) // request status of submission that was just created val submissionId = submitResponse.submissionId - val response2 = client.requestSubmissionStatus(masterUrl, submissionId) + val response2 = client.requestSubmissionStatus(submissionId) val statusResponse = getStatusResponse(response2) assert(statusResponse.success) assert(statusResponse.submissionId === submissionId) @@ -160,8 +161,9 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { test("create then kill then request status") { val masterUrl = startSmartServer() val request = constructSubmitRequest(masterUrl) - val response1 = client.createSubmission(masterUrl, request) - val response2 = client.createSubmission(masterUrl, request) + val client = new RestSubmissionClient(masterUrl) + val response1 = client.createSubmission(request) + val response2 = client.createSubmission(request) val submitResponse1 = getSubmitResponse(response1) val submitResponse2 = getSubmitResponse(response2) assert(submitResponse1.success) @@ -171,13 +173,13 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { val submissionId1 = submitResponse1.submissionId val submissionId2 = submitResponse2.submissionId // kill only submission 1, but not submission 2 - val response3 = client.killSubmission(masterUrl, submissionId1) + val response3 = client.killSubmission(submissionId1) val killResponse = getKillResponse(response3) assert(killResponse.success) assert(killResponse.submissionId === submissionId1) // request status for both submissions: 1 should be KILLED but 2 should be RUNNING still - val response4 = client.requestSubmissionStatus(masterUrl, submissionId1) - val response5 = client.requestSubmissionStatus(masterUrl, submissionId2) + val response4 = client.requestSubmissionStatus(submissionId1) + val response5 = client.requestSubmissionStatus(submissionId2) val statusResponse1 = getStatusResponse(response4) val statusResponse2 = getStatusResponse(response5) assert(statusResponse1.submissionId === submissionId1) @@ -189,13 +191,14 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { test("kill or request status before create") { val masterUrl = startSmartServer() val doesNotExist = "does-not-exist" + val client = new RestSubmissionClient(masterUrl) // kill a non-existent submission - val response1 = client.killSubmission(masterUrl, doesNotExist) + val response1 = client.killSubmission(doesNotExist) val killResponse = getKillResponse(response1) assert(!killResponse.success) assert(killResponse.submissionId === doesNotExist) // request status for a non-existent submission - val response2 = client.requestSubmissionStatus(masterUrl, doesNotExist) + val response2 = client.requestSubmissionStatus(doesNotExist) val statusResponse = getStatusResponse(response2) assert(!statusResponse.success) assert(statusResponse.submissionId === doesNotExist) @@ -339,6 +342,7 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { test("client handles faulty server") { val masterUrl = startFaultyServer() + val client = new RestSubmissionClient(masterUrl) val httpUrl = masterUrl.replace("spark://", "http://") val v = RestSubmissionServer.PROTOCOL_VERSION val submitRequestPath = s"$httpUrl/$v/submissions/create" @@ -425,7 +429,7 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { mainJar) ++ appArgs val args = new SparkSubmitArguments(commandLineArgs) val (_, _, sparkProperties, _) = SparkSubmit.prepareSubmitEnvironment(args) - client.constructSubmitRequest( + new RestSubmissionClient("spark://host:port").constructSubmitRequest( mainJar, mainClass, appArgs, sparkProperties.toMap, Map.empty) } @@ -492,7 +496,7 @@ class StandaloneRestSubmitSuite extends FunSuite with BeforeAndAfterEach { method: String, body: String = ""): (SubmitRestProtocolResponse, Int) = { val conn = sendHttpRequest(url, method, body) - (client.readResponse(conn), conn.getResponseCode) + (new RestSubmissionClient("spark://host:port").readResponse(conn), conn.getResponseCode) } } diff --git a/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala b/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala index aea76c1adcc09..85eb2a1d07ba4 100644 --- a/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala +++ b/core/src/test/scala/org/apache/spark/rdd/PipedRDDSuite.scala @@ -176,7 +176,7 @@ class PipedRDDSuite extends FunSuite with SharedSparkContext { } val hadoopPart1 = generateFakeHadoopPartition() val pipedRdd = new PipedRDD(nums, "printenv " + varName) - val tContext = new TaskContextImpl(0, 0, 0, 0) + val tContext = new TaskContextImpl(0, 0, 0, 0, null) val rddIter = pipedRdd.compute(hadoopPart1, tContext) val arr = rddIter.toArray assert(arr(0) == "/some/path") diff --git a/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala b/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala index 44c88b00c442a..ae3339d80f9c6 100644 --- a/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala +++ b/core/src/test/scala/org/apache/spark/rpc/RpcEnvSuite.scala @@ -100,8 +100,8 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { } val rpcEndpointRef = env.setupEndpoint("send-ref", endpoint) - val newRpcEndpointRef = rpcEndpointRef.askWithReply[RpcEndpointRef]("Hello") - val reply = newRpcEndpointRef.askWithReply[String]("Echo") + val newRpcEndpointRef = rpcEndpointRef.askWithRetry[RpcEndpointRef]("Hello") + val reply = newRpcEndpointRef.askWithRetry[String]("Echo") assert("Echo" === reply) } @@ -115,7 +115,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { } } }) - val reply = rpcEndpointRef.askWithReply[String]("hello") + val reply = rpcEndpointRef.askWithRetry[String]("hello") assert("hello" === reply) } @@ -134,7 +134,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { // Use anotherEnv to find out the RpcEndpointRef val rpcEndpointRef = anotherEnv.setupEndpointRef("local", env.address, "ask-remotely") try { - val reply = rpcEndpointRef.askWithReply[String]("hello") + val reply = rpcEndpointRef.askWithRetry[String]("hello") assert("hello" === reply) } finally { anotherEnv.shutdown() @@ -162,7 +162,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { val rpcEndpointRef = anotherEnv.setupEndpointRef("local", env.address, "ask-timeout") try { val e = intercept[Exception] { - rpcEndpointRef.askWithReply[String]("hello", 1 millis) + rpcEndpointRef.askWithRetry[String]("hello", 1 millis) } assert(e.isInstanceOf[TimeoutException] || e.getCause.isInstanceOf[TimeoutException]) } finally { @@ -399,7 +399,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { } }) - val f = endpointRef.sendWithReply[String]("Hi") + val f = endpointRef.ask[String]("Hi") val ack = Await.result(f, 5 seconds) assert("ack" === ack) @@ -419,7 +419,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { // Use anotherEnv to find out the RpcEndpointRef val rpcEndpointRef = anotherEnv.setupEndpointRef("local", env.address, "sendWithReply-remotely") try { - val f = rpcEndpointRef.sendWithReply[String]("hello") + val f = rpcEndpointRef.ask[String]("hello") val ack = Await.result(f, 5 seconds) assert("ack" === ack) } finally { @@ -437,7 +437,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { } }) - val f = endpointRef.sendWithReply[String]("Hi") + val f = endpointRef.ask[String]("Hi") val e = intercept[SparkException] { Await.result(f, 5 seconds) } @@ -460,7 +460,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { val rpcEndpointRef = anotherEnv.setupEndpointRef( "local", env.address, "sendWithReply-remotely-error") try { - val f = rpcEndpointRef.sendWithReply[String]("hello") + val f = rpcEndpointRef.ask[String]("hello") val e = intercept[SparkException] { Await.result(f, 5 seconds) } @@ -529,7 +529,7 @@ abstract class RpcEnvSuite extends FunSuite with BeforeAndAfterAll { val rpcEndpointRef = anotherEnv.setupEndpointRef( "local", env.address, "sendWithReply-unserializable-error") try { - val f = rpcEndpointRef.sendWithReply[String]("hello") + val f = rpcEndpointRef.ask[String]("hello") intercept[TimeoutException] { Await.result(f, 1 seconds) } diff --git a/core/src/test/scala/org/apache/spark/rpc/akka/AkkaRpcEnvSuite.scala b/core/src/test/scala/org/apache/spark/rpc/akka/AkkaRpcEnvSuite.scala index 58214c0637235..a33a83db7bc9e 100644 --- a/core/src/test/scala/org/apache/spark/rpc/akka/AkkaRpcEnvSuite.scala +++ b/core/src/test/scala/org/apache/spark/rpc/akka/AkkaRpcEnvSuite.scala @@ -40,7 +40,7 @@ class AkkaRpcEnvSuite extends RpcEnvSuite { RpcEnvConfig(conf, "test", "localhost", 12346, new SecurityManager(conf))) try { val newRef = newRpcEnv.setupEndpointRef("local", ref.address, "test_endpoint") - assert("akka.tcp://local@localhost:12345/user/test_endpoint" === + assert(s"akka.tcp://local@${env.address}/user/test_endpoint" === newRef.asInstanceOf[AkkaRpcEndpointRef].actorRef.path.toString) } finally { newRpcEnv.shutdown() diff --git a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala index 3c52a8c4460c6..2482603f420ee 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala @@ -95,6 +95,7 @@ class DAGSchedulerSuite override def setDAGScheduler(dagScheduler: DAGScheduler) = {} override def defaultParallelism() = 2 override def executorLost(executorId: String, reason: ExecutorLossReason): Unit = {} + override def applicationAttemptId(): Option[String] = None } /** Length of time to wait while draining listener events. */ @@ -404,6 +405,7 @@ class DAGSchedulerSuite taskMetrics: Array[(Long, TaskMetrics)], blockManagerId: BlockManagerId): Boolean = true override def executorLost(executorId: String, reason: ExecutorLossReason): Unit = {} + override def applicationAttemptId(): Option[String] = None } val noKillScheduler = new DAGScheduler( sc, diff --git a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala index 6d25edb7d20dc..b52a8d11d147d 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/EventLoggingListenerSuite.scala @@ -61,7 +61,7 @@ class EventLoggingListenerSuite extends FunSuite with LocalSparkContext with Bef test("Verify log file exist") { // Verify logging directory exists val conf = getLoggingConf(testDirPath) - val eventLogger = new EventLoggingListener("test", testDirPath.toUri(), conf) + val eventLogger = new EventLoggingListener("test", None, testDirPath.toUri(), conf) eventLogger.start() val logPath = new Path(eventLogger.logPath + EventLoggingListener.IN_PROGRESS) @@ -95,7 +95,7 @@ class EventLoggingListenerSuite extends FunSuite with LocalSparkContext with Bef } test("Log overwriting") { - val logUri = EventLoggingListener.getLogPath(testDir.toURI, "test") + val logUri = EventLoggingListener.getLogPath(testDir.toURI, "test", None) val logPath = new URI(logUri).getPath // Create file before writing the event log new FileOutputStream(new File(logPath)).close() @@ -108,18 +108,18 @@ class EventLoggingListenerSuite extends FunSuite with LocalSparkContext with Bef test("Event log name") { // without compression assert(s"file:/base-dir/app1" === EventLoggingListener.getLogPath( - Utils.resolveURI("/base-dir"), "app1")) + Utils.resolveURI("/base-dir"), "app1", None)) // with compression assert(s"file:/base-dir/app1.lzf" === - EventLoggingListener.getLogPath(Utils.resolveURI("/base-dir"), "app1", Some("lzf"))) + EventLoggingListener.getLogPath(Utils.resolveURI("/base-dir"), "app1", None, Some("lzf"))) // illegal characters in app ID assert(s"file:/base-dir/a-fine-mind_dollar_bills__1" === EventLoggingListener.getLogPath(Utils.resolveURI("/base-dir"), - "a fine:mind$dollar{bills}.1")) + "a fine:mind$dollar{bills}.1", None)) // illegal characters in app ID with compression assert(s"file:/base-dir/a-fine-mind_dollar_bills__1.lz4" === EventLoggingListener.getLogPath(Utils.resolveURI("/base-dir"), - "a fine:mind$dollar{bills}.1", Some("lz4"))) + "a fine:mind$dollar{bills}.1", None, Some("lz4"))) } /* ----------------- * @@ -140,10 +140,10 @@ class EventLoggingListenerSuite extends FunSuite with LocalSparkContext with Bef val conf = getLoggingConf(testDirPath, compressionCodec) extraConf.foreach { case (k, v) => conf.set(k, v) } val logName = compressionCodec.map("test-" + _).getOrElse("test") - val eventLogger = new EventLoggingListener(logName, testDirPath.toUri(), conf) + val eventLogger = new EventLoggingListener(logName, None, testDirPath.toUri(), conf) val listenerBus = new LiveListenerBus val applicationStart = SparkListenerApplicationStart("Greatest App (N)ever", None, - 125L, "Mickey") + 125L, "Mickey", None) val applicationEnd = SparkListenerApplicationEnd(1000L) // A comprehensive test on JSON de/serialization of all events is in JsonProtocolSuite @@ -186,7 +186,7 @@ class EventLoggingListenerSuite extends FunSuite with LocalSparkContext with Bef val eventLogPath = eventLogger.logPath val expectedLogDir = testDir.toURI() assert(eventLogPath === EventLoggingListener.getLogPath( - expectedLogDir, sc.applicationId, compressionCodec.map(CompressionCodec.getShortName))) + expectedLogDir, sc.applicationId, None, compressionCodec.map(CompressionCodec.getShortName))) // Begin listening for events that trigger asserts val eventExistenceListener = new EventExistenceListener(eventLogger) diff --git a/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala index 6de6d2fec622a..dabe4574b6456 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/ReplayListenerSuite.scala @@ -50,7 +50,7 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { val fstream = fileSystem.create(logFilePath) val writer = new PrintWriter(fstream) val applicationStart = SparkListenerApplicationStart("Greatest App (N)ever", None, - 125L, "Mickey") + 125L, "Mickey", None) val applicationEnd = SparkListenerApplicationEnd(1000L) writer.println(compact(render(JsonProtocol.sparkEventToJson(applicationStart)))) writer.println(compact(render(JsonProtocol.sparkEventToJson(applicationEnd)))) @@ -146,7 +146,7 @@ class ReplayListenerSuite extends FunSuite with BeforeAndAfter { * log the events. */ private class EventMonster(conf: SparkConf) - extends EventLoggingListener("test", new URI("testdir"), conf) { + extends EventLoggingListener("test", None, new URI("testdir"), conf) { override def start() { } diff --git a/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala index 057e226916027..83ae8701243e5 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/TaskContextSuite.scala @@ -51,7 +51,7 @@ class TaskContextSuite extends FunSuite with BeforeAndAfter with LocalSparkConte } test("all TaskCompletionListeners should be called even if some fail") { - val context = new TaskContextImpl(0, 0, 0, 0) + val context = new TaskContextImpl(0, 0, 0, 0, null) val listener = mock(classOf[TaskCompletionListener]) context.addTaskCompletionListener(_ => throw new Exception("blah")) context.addTaskCompletionListener(listener) diff --git a/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala index cdd7be0fbe5dd..ab863f3d8d672 100644 --- a/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala +++ b/core/src/test/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackendSuite.scala @@ -73,6 +73,52 @@ class MesosSchedulerBackendSuite extends FunSuite with LocalSparkContext with Mo s"cd test-app-1*; ./bin/spark-class ${classOf[MesosExecutorBackend].getName}") } + test("spark docker properties correctly populate the DockerInfo message") { + val taskScheduler = mock[TaskSchedulerImpl] + + val conf = new SparkConf() + .set("spark.mesos.executor.docker.image", "spark/mock") + .set("spark.mesos.executor.docker.volumes", "/a,/b:/b,/c:/c:rw,/d:ro,/e:/e:ro") + .set("spark.mesos.executor.docker.portmaps", "80:8080,53:53:tcp") + + val listenerBus = mock[LiveListenerBus] + listenerBus.post( + SparkListenerExecutorAdded(anyLong, "s1", new ExecutorInfo("host1", 2, Map.empty))) + + val sc = mock[SparkContext] + when(sc.executorMemory).thenReturn(100) + when(sc.getSparkHome()).thenReturn(Option("/spark-home")) + when(sc.executorEnvs).thenReturn(new mutable.HashMap[String, String]) + when(sc.conf).thenReturn(conf) + when(sc.listenerBus).thenReturn(listenerBus) + + val backend = new MesosSchedulerBackend(taskScheduler, sc, "master") + + val execInfo = backend.createExecutorInfo("mockExecutor") + assert(execInfo.getContainer.getDocker.getImage.equals("spark/mock")) + val portmaps = execInfo.getContainer.getDocker.getPortMappingsList + assert(portmaps.get(0).getHostPort.equals(80)) + assert(portmaps.get(0).getContainerPort.equals(8080)) + assert(portmaps.get(0).getProtocol.equals("tcp")) + assert(portmaps.get(1).getHostPort.equals(53)) + assert(portmaps.get(1).getContainerPort.equals(53)) + assert(portmaps.get(1).getProtocol.equals("tcp")) + val volumes = execInfo.getContainer.getVolumesList + assert(volumes.get(0).getContainerPath.equals("/a")) + assert(volumes.get(0).getMode.equals(Volume.Mode.RW)) + assert(volumes.get(1).getContainerPath.equals("/b")) + assert(volumes.get(1).getHostPath.equals("/b")) + assert(volumes.get(1).getMode.equals(Volume.Mode.RW)) + assert(volumes.get(2).getContainerPath.equals("/c")) + assert(volumes.get(2).getHostPath.equals("/c")) + assert(volumes.get(2).getMode.equals(Volume.Mode.RW)) + assert(volumes.get(3).getContainerPath.equals("/d")) + assert(volumes.get(3).getMode.equals(Volume.Mode.RO)) + assert(volumes.get(4).getContainerPath.equals("/e")) + assert(volumes.get(4).getHostPath.equals("/e")) + assert(volumes.get(4).getMode.equals(Volume.Mode.RO)) + } + test("mesos resource offers result in launching tasks") { def createOffer(id: Int, mem: Int, cpu: Int): Offer = { val builder = Offer.newBuilder() diff --git a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala index 1b13559e77cb8..778a7eee73b23 100644 --- a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala +++ b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala @@ -280,6 +280,15 @@ class KryoSerializerSuite extends FunSuite with SharedSparkContext { val thrown = intercept[SparkException](ser.serialize(largeObject)) assert(thrown.getMessage.contains(kryoBufferMaxProperty)) } + + test("getAutoReset") { + val ser = new KryoSerializer(new SparkConf).newInstance().asInstanceOf[KryoSerializerInstance] + assert(ser.getAutoReset) + val conf = new SparkConf().set("spark.kryo.registrator", + classOf[RegistratorWithoutAutoReset].getName) + val ser2 = new KryoSerializer(conf).newInstance().asInstanceOf[KryoSerializerInstance] + assert(!ser2.getAutoReset) + } } @@ -313,4 +322,10 @@ object KryoTest { k.register(classOf[java.util.HashMap[_, _]]) } } + + class RegistratorWithoutAutoReset extends KryoRegistrator { + override def registerClasses(k: Kryo) { + k.setAutoReset(false) + } + } } diff --git a/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala b/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala index 963264cef3a71..86fcf447287f7 100644 --- a/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala +++ b/core/src/test/scala/org/apache/spark/serializer/TestSerializer.scala @@ -24,7 +24,7 @@ import scala.reflect.ClassTag /** - * A serializer implementation that always return a single element in a deserialization stream. + * A serializer implementation that always returns two elements in a deserialization stream. */ class TestSerializer extends Serializer { override def newInstance(): TestSerializerInstance = new TestSerializerInstance @@ -51,7 +51,7 @@ class TestDeserializationStream extends DeserializationStream { override def readObject[T: ClassTag](): T = { count += 1 - if (count == 2) { + if (count == 3) { throw new EOFException } new Object().asInstanceOf[T] diff --git a/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala b/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala index 7d76435cd75e7..84384bb48999a 100644 --- a/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/shuffle/hash/HashShuffleManagerSuite.scala @@ -59,8 +59,8 @@ class HashShuffleManagerSuite extends FunSuite with LocalSparkContext { val shuffle1 = shuffleBlockManager.forMapTask(1, 1, 1, new JavaSerializer(conf), new ShuffleWriteMetrics) for (writer <- shuffle1.writers) { - writer.write("test1") - writer.write("test2") + writer.write("test1", "value") + writer.write("test2", "value") } for (writer <- shuffle1.writers) { writer.commitAndClose() @@ -73,8 +73,8 @@ class HashShuffleManagerSuite extends FunSuite with LocalSparkContext { new ShuffleWriteMetrics) for (writer <- shuffle2.writers) { - writer.write("test3") - writer.write("test4") + writer.write("test3", "value") + writer.write("test4", "vlue") } for (writer <- shuffle2.writers) { writer.commitAndClose() @@ -91,8 +91,8 @@ class HashShuffleManagerSuite extends FunSuite with LocalSparkContext { val shuffle3 = shuffleBlockManager.forMapTask(1, 3, 1, new JavaSerializer(testConf), new ShuffleWriteMetrics) for (writer <- shuffle3.writers) { - writer.write("test3") - writer.write("test4") + writer.write("test3", "value") + writer.write("test4", "value") } for (writer <- shuffle3.writers) { writer.commitAndClose() diff --git a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala index 6957bc72e9903..151955ef7f435 100644 --- a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala @@ -356,7 +356,7 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach master.removeExecutor(store.blockManagerId.executorId) assert(master.getLocations("a1").size == 0, "a1 was not removed from master") - val reregister = !master.driverEndpoint.askWithReply[Boolean]( + val reregister = !master.driverEndpoint.askWithRetry[Boolean]( BlockManagerHeartbeat(store.blockManagerId)) assert(reregister == true) } @@ -526,6 +526,7 @@ class BlockManagerSuite extends FunSuite with Matchers with BeforeAndAfterEach test("tachyon storage") { // TODO Make the spark.test.tachyon.enable true after using tachyon 0.5.0 testing jar. val tachyonUnitTestEnabled = conf.getBoolean("spark.test.tachyon.enable", false) + conf.set(ExternalBlockStore.BLOCK_MANAGER_NAME, ExternalBlockStore.DEFAULT_BLOCK_MANAGER_NAME) if (tachyonUnitTestEnabled) { store = makeBlockManager(1200) val a1 = new Array[Byte](400) diff --git a/core/src/test/scala/org/apache/spark/storage/BlockObjectWriterSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockObjectWriterSuite.scala index 003a728cb84a0..43ef469c1fd48 100644 --- a/core/src/test/scala/org/apache/spark/storage/BlockObjectWriterSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/BlockObjectWriterSuite.scala @@ -32,7 +32,7 @@ class BlockObjectWriterSuite extends FunSuite { val writer = new DiskBlockObjectWriter(new TestBlockId("0"), file, new JavaSerializer(new SparkConf()).newInstance(), 1024, os => os, true, writeMetrics) - writer.write(Long.box(20)) + writer.write(Long.box(20), Long.box(30)) // Record metrics update on every write assert(writeMetrics.shuffleRecordsWritten === 1) // Metrics don't update on every write @@ -40,7 +40,7 @@ class BlockObjectWriterSuite extends FunSuite { // After 32 writes, metrics should update for (i <- 0 until 32) { writer.flush() - writer.write(Long.box(i)) + writer.write(Long.box(i), Long.box(i)) } assert(writeMetrics.shuffleBytesWritten > 0) assert(writeMetrics.shuffleRecordsWritten === 33) @@ -54,7 +54,7 @@ class BlockObjectWriterSuite extends FunSuite { val writer = new DiskBlockObjectWriter(new TestBlockId("0"), file, new JavaSerializer(new SparkConf()).newInstance(), 1024, os => os, true, writeMetrics) - writer.write(Long.box(20)) + writer.write(Long.box(20), Long.box(30)) // Record metrics update on every write assert(writeMetrics.shuffleRecordsWritten === 1) // Metrics don't update on every write @@ -62,7 +62,7 @@ class BlockObjectWriterSuite extends FunSuite { // After 32 writes, metrics should update for (i <- 0 until 32) { writer.flush() - writer.write(Long.box(i)) + writer.write(Long.box(i), Long.box(i)) } assert(writeMetrics.shuffleBytesWritten > 0) assert(writeMetrics.shuffleRecordsWritten === 33) diff --git a/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala b/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala index 37b593b2c5f79..2080c432d77db 100644 --- a/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/ShuffleBlockFetcherIteratorSuite.scala @@ -89,7 +89,7 @@ class ShuffleBlockFetcherIteratorSuite extends FunSuite { ) val iterator = new ShuffleBlockFetcherIterator( - new TaskContextImpl(0, 0, 0, 0), + new TaskContextImpl(0, 0, 0, 0, null), transfer, blockManager, blocksByAddress, @@ -154,7 +154,7 @@ class ShuffleBlockFetcherIteratorSuite extends FunSuite { val blocksByAddress = Seq[(BlockManagerId, Seq[(BlockId, Long)])]( (remoteBmId, blocks.keys.map(blockId => (blockId, 1.asInstanceOf[Long])).toSeq)) - val taskContext = new TaskContextImpl(0, 0, 0, 0) + val taskContext = new TaskContextImpl(0, 0, 0, 0, null) val iterator = new ShuffleBlockFetcherIterator( taskContext, transfer, @@ -217,7 +217,7 @@ class ShuffleBlockFetcherIteratorSuite extends FunSuite { val blocksByAddress = Seq[(BlockManagerId, Seq[(BlockId, Long)])]( (remoteBmId, blocks.keys.map(blockId => (blockId, 1.asInstanceOf[Long])).toSeq)) - val taskContext = new TaskContextImpl(0, 0, 0, 0) + val taskContext = new TaskContextImpl(0, 0, 0, 0, null) val iterator = new ShuffleBlockFetcherIterator( taskContext, transfer, diff --git a/core/src/test/scala/org/apache/spark/storage/StorageSuite.scala b/core/src/test/scala/org/apache/spark/storage/StorageSuite.scala index 8f435114072a7..4c32d508ff813 100644 --- a/core/src/test/scala/org/apache/spark/storage/StorageSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/StorageSuite.scala @@ -240,11 +240,11 @@ class StorageSuite extends FunSuite { assert(status.rddBlocksById(1000).size === status.numRddBlocksById(1000)) } - test("storage status memUsed, diskUsed, tachyonUsed") { + test("storage status memUsed, diskUsed, externalBlockStoreUsed") { val status = storageStatus2 def actualMemUsed: Long = status.blocks.values.map(_.memSize).sum def actualDiskUsed: Long = status.blocks.values.map(_.diskSize).sum - def actualOffHeapUsed: Long = status.blocks.values.map(_.tachyonSize).sum + def actualOffHeapUsed: Long = status.blocks.values.map(_.externalBlockStoreSize).sum assert(status.memUsed === actualMemUsed) assert(status.diskUsed === actualDiskUsed) assert(status.offHeapUsed === actualOffHeapUsed) @@ -300,12 +300,12 @@ class StorageSuite extends FunSuite { assert(rddInfos(0).numCachedPartitions === 5) assert(rddInfos(0).memSize === 5L) assert(rddInfos(0).diskSize === 10L) - assert(rddInfos(0).tachyonSize === 0L) + assert(rddInfos(0).externalBlockStoreSize === 0L) assert(rddInfos(1).storageLevel === memAndDisk) assert(rddInfos(1).numCachedPartitions === 3) assert(rddInfos(1).memSize === 3L) assert(rddInfos(1).diskSize === 6L) - assert(rddInfos(1).tachyonSize === 0L) + assert(rddInfos(1).externalBlockStoreSize === 0L) } test("StorageUtils.getRddBlockLocations") { diff --git a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala index eb9db550fd74c..d53d7f3ba5ae7 100644 --- a/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala +++ b/core/src/test/scala/org/apache/spark/ui/UISeleniumSuite.scala @@ -350,7 +350,7 @@ class UISeleniumSuite extends FunSuite with WebBrowser with Matchers with Before } } - test("kill stage is POST only") { + test("kill stage POST/GET response is correct") { def getResponseCode(url: URL, method: String): Int = { val connection = url.openConnection().asInstanceOf[HttpURLConnection] connection.setRequestMethod(method) @@ -365,7 +365,8 @@ class UISeleniumSuite extends FunSuite with WebBrowser with Matchers with Before eventually(timeout(5 seconds), interval(50 milliseconds)) { val url = new URL( sc.ui.get.appUIAddress.stripSuffix("/") + "/stages/stage/kill/?id=0&terminate=true") - getResponseCode(url, "GET") should be (405) + // SPARK-6846: should be POST only but YARN AM doesn't proxy POST + getResponseCode(url, "GET") should be (200) getResponseCode(url, "POST") should be (200) } } diff --git a/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala b/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala index 8cd7b5972f62d..d35414674e52a 100644 --- a/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala +++ b/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala @@ -135,12 +135,12 @@ class StorageTabSuite extends FunSuite with BeforeAndAfter { bus.postToAll(SparkListenerTaskEnd(1, 0, "obliteration", Success, taskInfo, metrics1)) assert(storageListener._rddInfoMap(0).memSize === 800L) assert(storageListener._rddInfoMap(0).diskSize === 400L) - assert(storageListener._rddInfoMap(0).tachyonSize === 200L) + assert(storageListener._rddInfoMap(0).externalBlockStoreSize === 200L) assert(storageListener._rddInfoMap(0).numCachedPartitions === 3) assert(storageListener._rddInfoMap(0).isCached) assert(storageListener._rddInfoMap(1).memSize === 0L) assert(storageListener._rddInfoMap(1).diskSize === 240L) - assert(storageListener._rddInfoMap(1).tachyonSize === 0L) + assert(storageListener._rddInfoMap(1).externalBlockStoreSize === 0L) assert(storageListener._rddInfoMap(1).numCachedPartitions === 1) assert(storageListener._rddInfoMap(1).isCached) assert(!storageListener._rddInfoMap(2).isCached) @@ -157,7 +157,7 @@ class StorageTabSuite extends FunSuite with BeforeAndAfter { bus.postToAll(SparkListenerTaskEnd(2, 0, "obliteration", Success, taskInfo, metrics2)) assert(storageListener._rddInfoMap(0).memSize === 400L) assert(storageListener._rddInfoMap(0).diskSize === 400L) - assert(storageListener._rddInfoMap(0).tachyonSize === 200L) + assert(storageListener._rddInfoMap(0).externalBlockStoreSize === 200L) assert(storageListener._rddInfoMap(0).numCachedPartitions === 2) assert(storageListener._rddInfoMap(0).isCached) assert(!storageListener._rddInfoMap(1).isCached) diff --git a/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala index c47162779bbba..ff1bfe0774a2f 100644 --- a/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala @@ -50,7 +50,7 @@ class ClosureCleanerSuite extends FunSuite { val obj = new TestClassWithNesting(1) assert(obj.run() === 96) // 4 * (1+2+3+4) + 4 * (1+2+3+4) + 16 * 1 } - + test("toplevel return statements in closures are identified at cleaning time") { val ex = intercept[SparkException] { TestObjectWithBogusReturns.run() @@ -61,13 +61,20 @@ class ClosureCleanerSuite extends FunSuite { test("return statements from named functions nested in closures don't raise exceptions") { val result = TestObjectWithNestedReturns.run() - assert(result == 1) + assert(result === 1) } } // A non-serializable class we create in closures to make sure that we aren't // keeping references to unneeded variables from our outer closures. -class NonSerializable {} +class NonSerializable(val id: Int = -1) { + override def equals(other: Any): Boolean = { + other match { + case o: NonSerializable => id == o.id + case _ => false + } + } +} object TestObject { def run(): Int = { diff --git a/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite2.scala b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite2.scala new file mode 100644 index 0000000000000..59456790e89f0 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite2.scala @@ -0,0 +1,571 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util + +import java.io.NotSerializableException + +import scala.collection.mutable + +import org.scalatest.{BeforeAndAfterAll, FunSuite, PrivateMethodTester} + +import org.apache.spark.{SparkContext, SparkException} +import org.apache.spark.serializer.SerializerInstance + +/** + * Another test suite for the closure cleaner that is finer-grained. + * For tests involving end-to-end Spark jobs, see {{ClosureCleanerSuite}}. + */ +class ClosureCleanerSuite2 extends FunSuite with BeforeAndAfterAll with PrivateMethodTester { + + // Start a SparkContext so that the closure serializer is accessible + // We do not actually use this explicitly otherwise + private var sc: SparkContext = null + private var closureSerializer: SerializerInstance = null + + override def beforeAll(): Unit = { + sc = new SparkContext("local", "test") + closureSerializer = sc.env.closureSerializer.newInstance() + } + + override def afterAll(): Unit = { + sc.stop() + sc = null + closureSerializer = null + } + + // Some fields and methods to reference in inner closures later + private val someSerializableValue = 1 + private val someNonSerializableValue = new NonSerializable + private def someSerializableMethod() = 1 + private def someNonSerializableMethod() = new NonSerializable + + /** Assert that the given closure is serializable (or not). */ + private def assertSerializable(closure: AnyRef, serializable: Boolean): Unit = { + if (serializable) { + closureSerializer.serialize(closure) + } else { + intercept[NotSerializableException] { + closureSerializer.serialize(closure) + } + } + } + + /** + * Helper method for testing whether closure cleaning works as expected. + * This cleans the given closure twice, with and without transitive cleaning. + * + * @param closure closure to test cleaning with + * @param serializableBefore if true, verify that the closure is serializable + * before cleaning, otherwise assert that it is not + * @param serializableAfter if true, assert that the closure is serializable + * after cleaning otherwise assert that it is not + */ + private def verifyCleaning( + closure: AnyRef, + serializableBefore: Boolean, + serializableAfter: Boolean): Unit = { + verifyCleaning(closure, serializableBefore, serializableAfter, transitive = true) + verifyCleaning(closure, serializableBefore, serializableAfter, transitive = false) + } + + /** Helper method for testing whether closure cleaning works as expected. */ + private def verifyCleaning( + closure: AnyRef, + serializableBefore: Boolean, + serializableAfter: Boolean, + transitive: Boolean): Unit = { + assertSerializable(closure, serializableBefore) + // If the resulting closure is not serializable even after + // cleaning, we expect ClosureCleaner to throw a SparkException + if (serializableAfter) { + ClosureCleaner.clean(closure, checkSerializable = true, transitive) + } else { + intercept[SparkException] { + ClosureCleaner.clean(closure, checkSerializable = true, transitive) + } + } + assertSerializable(closure, serializableAfter) + } + + /** + * Return the fields accessed by the given closure by class. + * This also optionally finds the fields transitively referenced through methods invocations. + */ + private def findAccessedFields( + closure: AnyRef, + outerClasses: Seq[Class[_]], + findTransitively: Boolean): Map[Class[_], Set[String]] = { + val fields = new mutable.HashMap[Class[_], mutable.Set[String]] + outerClasses.foreach { c => fields(c) = new mutable.HashSet[String] } + ClosureCleaner.getClassReader(closure.getClass) + .accept(new FieldAccessFinder(fields, findTransitively), 0) + fields.mapValues(_.toSet).toMap + } + + // Accessors for private methods + private val _isClosure = PrivateMethod[Boolean]('isClosure) + private val _getInnerClosureClasses = PrivateMethod[List[Class[_]]]('getInnerClosureClasses) + private val _getOuterClasses = PrivateMethod[List[Class[_]]]('getOuterClasses) + private val _getOuterObjects = PrivateMethod[List[AnyRef]]('getOuterObjects) + + private def isClosure(obj: AnyRef): Boolean = { + ClosureCleaner invokePrivate _isClosure(obj) + } + + private def getInnerClosureClasses(closure: AnyRef): List[Class[_]] = { + ClosureCleaner invokePrivate _getInnerClosureClasses(closure) + } + + private def getOuterClasses(closure: AnyRef): List[Class[_]] = { + ClosureCleaner invokePrivate _getOuterClasses(closure) + } + + private def getOuterObjects(closure: AnyRef): List[AnyRef] = { + ClosureCleaner invokePrivate _getOuterObjects(closure) + } + + test("get inner closure classes") { + val closure1 = () => 1 + val closure2 = () => { () => 1 } + val closure3 = (i: Int) => { + (1 to i).map { x => x + 1 }.filter { x => x > 5 } + } + val closure4 = (j: Int) => { + (1 to j).flatMap { x => + (1 to x).flatMap { y => + (1 to y).map { z => z + 1 } + } + } + } + val inner1 = getInnerClosureClasses(closure1) + val inner2 = getInnerClosureClasses(closure2) + val inner3 = getInnerClosureClasses(closure3) + val inner4 = getInnerClosureClasses(closure4) + assert(inner1.isEmpty) + assert(inner2.size === 1) + assert(inner3.size === 2) + assert(inner4.size === 3) + assert(inner2.forall(isClosure)) + assert(inner3.forall(isClosure)) + assert(inner4.forall(isClosure)) + } + + test("get outer classes and objects") { + val localValue = someSerializableValue + val closure1 = () => 1 + val closure2 = () => localValue + val closure3 = () => someSerializableValue + val closure4 = () => someSerializableMethod() + val outerClasses1 = getOuterClasses(closure1) + val outerClasses2 = getOuterClasses(closure2) + val outerClasses3 = getOuterClasses(closure3) + val outerClasses4 = getOuterClasses(closure4) + val outerObjects1 = getOuterObjects(closure1) + val outerObjects2 = getOuterObjects(closure2) + val outerObjects3 = getOuterObjects(closure3) + val outerObjects4 = getOuterObjects(closure4) + + // The classes and objects should have the same size + assert(outerClasses1.size === outerObjects1.size) + assert(outerClasses2.size === outerObjects2.size) + assert(outerClasses3.size === outerObjects3.size) + assert(outerClasses4.size === outerObjects4.size) + + // These do not have $outer pointers because they reference only local variables + assert(outerClasses1.isEmpty) + assert(outerClasses2.isEmpty) + + // These closures do have $outer pointers because they ultimately reference `this` + // The first $outer pointer refers to the closure defines this test (see FunSuite#test) + // The second $outer pointer refers to ClosureCleanerSuite2 + assert(outerClasses3.size === 2) + assert(outerClasses4.size === 2) + assert(isClosure(outerClasses3(0))) + assert(isClosure(outerClasses4(0))) + assert(outerClasses3(0) === outerClasses4(0)) // part of the same "FunSuite#test" scope + assert(outerClasses3(1) === this.getClass) + assert(outerClasses4(1) === this.getClass) + assert(outerObjects3(1) === this) + assert(outerObjects4(1) === this) + } + + test("get outer classes and objects with nesting") { + val localValue = someSerializableValue + + val test1 = () => { + val x = 1 + val closure1 = () => 1 + val closure2 = () => x + val outerClasses1 = getOuterClasses(closure1) + val outerClasses2 = getOuterClasses(closure2) + val outerObjects1 = getOuterObjects(closure1) + val outerObjects2 = getOuterObjects(closure2) + assert(outerClasses1.size === outerObjects1.size) + assert(outerClasses2.size === outerObjects2.size) + // These inner closures only reference local variables, and so do not have $outer pointers + assert(outerClasses1.isEmpty) + assert(outerClasses2.isEmpty) + } + + val test2 = () => { + def y = 1 + val closure1 = () => 1 + val closure2 = () => y + val closure3 = () => localValue + val outerClasses1 = getOuterClasses(closure1) + val outerClasses2 = getOuterClasses(closure2) + val outerClasses3 = getOuterClasses(closure3) + val outerObjects1 = getOuterObjects(closure1) + val outerObjects2 = getOuterObjects(closure2) + val outerObjects3 = getOuterObjects(closure3) + assert(outerClasses1.size === outerObjects1.size) + assert(outerClasses2.size === outerObjects2.size) + assert(outerClasses3.size === outerObjects3.size) + // Same as above, this closure only references local variables + assert(outerClasses1.isEmpty) + // This closure references the "test2" scope because it needs to find the method `y` + // Scope hierarchy: "test2" < "FunSuite#test" < ClosureCleanerSuite2 + assert(outerClasses2.size === 3) + // This closure references the "test2" scope because it needs to find the `localValue` + // defined outside of this scope + assert(outerClasses3.size === 3) + assert(isClosure(outerClasses2(0))) + assert(isClosure(outerClasses3(0))) + assert(isClosure(outerClasses2(1))) + assert(isClosure(outerClasses3(1))) + assert(outerClasses2(0) === outerClasses3(0)) // part of the same "test2" scope + assert(outerClasses2(1) === outerClasses3(1)) // part of the same "FunSuite#test" scope + assert(outerClasses2(2) === this.getClass) + assert(outerClasses3(2) === this.getClass) + assert(outerObjects2(2) === this) + assert(outerObjects3(2) === this) + } + + test1() + test2() + } + + test("find accessed fields") { + val localValue = someSerializableValue + val closure1 = () => 1 + val closure2 = () => localValue + val closure3 = () => someSerializableValue + val outerClasses1 = getOuterClasses(closure1) + val outerClasses2 = getOuterClasses(closure2) + val outerClasses3 = getOuterClasses(closure3) + + val fields1 = findAccessedFields(closure1, outerClasses1, findTransitively = false) + val fields2 = findAccessedFields(closure2, outerClasses2, findTransitively = false) + val fields3 = findAccessedFields(closure3, outerClasses3, findTransitively = false) + assert(fields1.isEmpty) + assert(fields2.isEmpty) + assert(fields3.size === 2) + // This corresponds to the "FunSuite#test" closure. This is empty because the + // `someSerializableValue` belongs to its parent (i.e. ClosureCleanerSuite2). + assert(fields3(outerClasses3(0)).isEmpty) + // This corresponds to the ClosureCleanerSuite2. This is also empty, however, + // because accessing a `ClosureCleanerSuite2#someSerializableValue` actually involves a + // method call. Since we do not find fields transitively, we will not recursively trace + // through the fields referenced by this method. + assert(fields3(outerClasses3(1)).isEmpty) + + val fields1t = findAccessedFields(closure1, outerClasses1, findTransitively = true) + val fields2t = findAccessedFields(closure2, outerClasses2, findTransitively = true) + val fields3t = findAccessedFields(closure3, outerClasses3, findTransitively = true) + assert(fields1t.isEmpty) + assert(fields2t.isEmpty) + assert(fields3t.size === 2) + // Because we find fields transitively now, we are able to detect that we need the + // $outer pointer to get the field from the ClosureCleanerSuite2 + assert(fields3t(outerClasses3(0)).size === 1) + assert(fields3t(outerClasses3(0)).head === "$outer") + assert(fields3t(outerClasses3(1)).size === 1) + assert(fields3t(outerClasses3(1)).head.contains("someSerializableValue")) + } + + test("find accessed fields with nesting") { + val localValue = someSerializableValue + + val test1 = () => { + def a = localValue + 1 + val closure1 = () => 1 + val closure2 = () => a + val closure3 = () => localValue + val closure4 = () => someSerializableValue + val outerClasses1 = getOuterClasses(closure1) + val outerClasses2 = getOuterClasses(closure2) + val outerClasses3 = getOuterClasses(closure3) + val outerClasses4 = getOuterClasses(closure4) + + // First, find only fields accessed directly, not transitively, by these closures + val fields1 = findAccessedFields(closure1, outerClasses1, findTransitively = false) + val fields2 = findAccessedFields(closure2, outerClasses2, findTransitively = false) + val fields3 = findAccessedFields(closure3, outerClasses3, findTransitively = false) + val fields4 = findAccessedFields(closure4, outerClasses4, findTransitively = false) + assert(fields1.isEmpty) + // Note that the size here represents the number of outer classes, not the number of fields + // "test1" < parameter of "FunSuite#test" < ClosureCleanerSuite2 + assert(fields2.size === 3) + // Since we do not find fields transitively here, we do not look into what `def a` references + assert(fields2(outerClasses2(0)).isEmpty) // This corresponds to the "test1" scope + assert(fields2(outerClasses2(1)).isEmpty) // This corresponds to the "FunSuite#test" scope + assert(fields2(outerClasses2(2)).isEmpty) // This corresponds to the ClosureCleanerSuite2 + assert(fields3.size === 3) + // Note that `localValue` is a field of the "test1" scope because `def a` references it, + // but NOT a field of the "FunSuite#test" scope because it is only a local variable there + assert(fields3(outerClasses3(0)).size === 1) + assert(fields3(outerClasses3(0)).head.contains("localValue")) + assert(fields3(outerClasses3(1)).isEmpty) + assert(fields3(outerClasses3(2)).isEmpty) + assert(fields4.size === 3) + // Because `val someSerializableValue` is an instance variable, even an explicit reference + // here actually involves a method call to access the underlying value of the variable. + // Because we are not finding fields transitively here, we do not consider the fields + // accessed by this "method" (i.e. the val's accessor). + assert(fields4(outerClasses4(0)).isEmpty) + assert(fields4(outerClasses4(1)).isEmpty) + assert(fields4(outerClasses4(2)).isEmpty) + + // Now do the same, but find fields that the closures transitively reference + val fields1t = findAccessedFields(closure1, outerClasses1, findTransitively = true) + val fields2t = findAccessedFields(closure2, outerClasses2, findTransitively = true) + val fields3t = findAccessedFields(closure3, outerClasses3, findTransitively = true) + val fields4t = findAccessedFields(closure4, outerClasses4, findTransitively = true) + assert(fields1t.isEmpty) + assert(fields2t.size === 3) + assert(fields2t(outerClasses2(0)).size === 1) // `def a` references `localValue` + assert(fields2t(outerClasses2(0)).head.contains("localValue")) + assert(fields2t(outerClasses2(1)).isEmpty) + assert(fields2t(outerClasses2(2)).isEmpty) + assert(fields3t.size === 3) + assert(fields3t(outerClasses3(0)).size === 1) // as before + assert(fields3t(outerClasses3(0)).head.contains("localValue")) + assert(fields3t(outerClasses3(1)).isEmpty) + assert(fields3t(outerClasses3(2)).isEmpty) + assert(fields4t.size === 3) + // Through a series of method calls, we are able to detect that we ultimately access + // ClosureCleanerSuite2's field `someSerializableValue`. Along the way, we also accessed + // a few $outer parent pointers to get to the outermost object. + assert(fields4t(outerClasses4(0)) === Set("$outer")) + assert(fields4t(outerClasses4(1)) === Set("$outer")) + assert(fields4t(outerClasses4(2)).size === 1) + assert(fields4t(outerClasses4(2)).head.contains("someSerializableValue")) + } + + test1() + } + + test("clean basic serializable closures") { + val localValue = someSerializableValue + val closure1 = () => 1 + val closure2 = () => Array[String]("a", "b", "c") + val closure3 = (s: String, arr: Array[Long]) => s + arr.mkString(", ") + val closure4 = () => localValue + val closure5 = () => new NonSerializable(5) // we're just serializing the class information + val closure1r = closure1() + val closure2r = closure2() + val closure3r = closure3("g", Array(1, 5, 8)) + val closure4r = closure4() + val closure5r = closure5() + + verifyCleaning(closure1, serializableBefore = true, serializableAfter = true) + verifyCleaning(closure2, serializableBefore = true, serializableAfter = true) + verifyCleaning(closure3, serializableBefore = true, serializableAfter = true) + verifyCleaning(closure4, serializableBefore = true, serializableAfter = true) + verifyCleaning(closure5, serializableBefore = true, serializableAfter = true) + + // Verify that closures can still be invoked and the result still the same + assert(closure1() === closure1r) + assert(closure2() === closure2r) + assert(closure3("g", Array(1, 5, 8)) === closure3r) + assert(closure4() === closure4r) + assert(closure5() === closure5r) + } + + test("clean basic non-serializable closures") { + val closure1 = () => this // ClosureCleanerSuite2 is not serializable + val closure5 = () => someSerializableValue + val closure3 = () => someSerializableMethod() + val closure4 = () => someNonSerializableValue + val closure2 = () => someNonSerializableMethod() + + // These are not cleanable because they ultimately reference the ClosureCleanerSuite2 + verifyCleaning(closure1, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure2, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure3, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure4, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure5, serializableBefore = false, serializableAfter = false) + } + + test("clean basic nested serializable closures") { + val localValue = someSerializableValue + val closure1 = (i: Int) => { + (1 to i).map { x => x + localValue } // 1 level of nesting + } + val closure2 = (j: Int) => { + (1 to j).flatMap { x => + (1 to x).map { y => y + localValue } // 2 levels + } + } + val closure3 = (k: Int, l: Int, m: Int) => { + (1 to k).flatMap(closure2) ++ // 4 levels + (1 to l).flatMap(closure1) ++ // 3 levels + (1 to m).map { x => x + 1 } // 2 levels + } + val closure1r = closure1(1) + val closure2r = closure2(2) + val closure3r = closure3(3, 4, 5) + + verifyCleaning(closure1, serializableBefore = true, serializableAfter = true) + verifyCleaning(closure2, serializableBefore = true, serializableAfter = true) + verifyCleaning(closure3, serializableBefore = true, serializableAfter = true) + + // Verify that closures can still be invoked and the result still the same + assert(closure1(1) === closure1r) + assert(closure2(2) === closure2r) + assert(closure3(3, 4, 5) === closure3r) + } + + test("clean basic nested non-serializable closures") { + def localSerializableMethod(): Int = someSerializableValue + val localNonSerializableValue = someNonSerializableValue + // These closures ultimately reference the ClosureCleanerSuite2 + // Note that even accessing `val` that is an instance variable involves a method call + val closure1 = (i: Int) => { (1 to i).map { x => x + someSerializableValue } } + val closure2 = (j: Int) => { (1 to j).map { x => x + someSerializableMethod() } } + val closure4 = (k: Int) => { (1 to k).map { x => x + localSerializableMethod() } } + // This closure references a local non-serializable value + val closure3 = (l: Int) => { (1 to l).map { x => localNonSerializableValue } } + // This is non-serializable no matter how many levels we nest it + val closure5 = (m: Int) => { + (1 to m).foreach { x => + (1 to x).foreach { y => + (1 to y).foreach { z => + someSerializableValue + } + } + } + } + + verifyCleaning(closure1, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure2, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure3, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure4, serializableBefore = false, serializableAfter = false) + verifyCleaning(closure5, serializableBefore = false, serializableAfter = false) + } + + test("clean complicated nested serializable closures") { + val localValue = someSerializableValue + + // Here we assume that if the outer closure is serializable, + // then all inner closures must also be serializable + + // Reference local fields from all levels + val closure1 = (i: Int) => { + val a = 1 + (1 to i).flatMap { x => + val b = a + 1 + (1 to x).map { y => + y + a + b + localValue + } + } + } + + // Reference local fields and methods from all levels within the outermost closure + val closure2 = (i: Int) => { + val a1 = 1 + def a2 = 2 + (1 to i).flatMap { x => + val b1 = a1 + 1 + def b2 = a2 + 1 + (1 to x).map { y => + // If this references a method outside the outermost closure, then it will try to pull + // in the ClosureCleanerSuite2. This is why `localValue` here must be a local `val`. + y + a1 + a2 + b1 + b2 + localValue + } + } + } + + val closure1r = closure1(1) + val closure2r = closure2(2) + verifyCleaning(closure1, serializableBefore = true, serializableAfter = true) + verifyCleaning(closure2, serializableBefore = true, serializableAfter = true) + assert(closure1(1) == closure1r) + assert(closure2(2) == closure2r) + } + + test("clean complicated nested non-serializable closures") { + val localValue = someSerializableValue + + // Note that we are not interested in cleaning the outer closures here (they are not cleanable) + // The only reason why they exist is to nest the inner closures + + val test1 = () => { + val a = localValue + val b = sc + val inner1 = (x: Int) => x + a + b.hashCode() + val inner2 = (x: Int) => x + a + + // This closure explicitly references a non-serializable field + // There is no way to clean it + verifyCleaning(inner1, serializableBefore = false, serializableAfter = false) + + // This closure is serializable to begin with since it does not need a pointer to + // the outer closure (it only references local variables) + verifyCleaning(inner2, serializableBefore = true, serializableAfter = true) + } + + // Same as above, but the `val a` becomes `def a` + // The difference here is that all inner closures now have pointers to the outer closure + val test2 = () => { + def a = localValue + val b = sc + val inner1 = (x: Int) => x + a + b.hashCode() + val inner2 = (x: Int) => x + a + + // As before, this closure is neither serializable nor cleanable + verifyCleaning(inner1, serializableBefore = false, serializableAfter = false) + + // This closure is no longer serializable because it now has a pointer to the outer closure, + // which is itself not serializable because it has a pointer to the ClosureCleanerSuite2. + // If we do not clean transitively, we will not null out this indirect reference. + verifyCleaning( + inner2, serializableBefore = false, serializableAfter = false, transitive = false) + + // If we clean transitively, we will find that method `a` does not actually reference the + // outer closure's parent (i.e. the ClosureCleanerSuite), so we can additionally null out + // the outer closure's parent pointer. This will make `inner2` serializable. + verifyCleaning( + inner2, serializableBefore = false, serializableAfter = true, transitive = true) + } + + // Same as above, but with more levels of nesting + val test3 = () => { () => test1() } + val test4 = () => { () => test2() } + val test5 = () => { () => { () => test3() } } + val test6 = () => { () => { () => test4() } } + + test1() + test2() + test3()() + test4()() + test5()()() + test6()()() + } + +} diff --git a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala index 1bc0b3266c86d..20f28cae85ce3 100644 --- a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala @@ -74,7 +74,8 @@ class JsonProtocolSuite extends FunSuite { val blockManagerRemoved = SparkListenerBlockManagerRemoved(2L, BlockManagerId("Scarce", "to be counted...", 100)) val unpersistRdd = SparkListenerUnpersistRDD(12345) - val applicationStart = SparkListenerApplicationStart("The winner of all", None, 42L, "Garfield") + val applicationStart = SparkListenerApplicationStart("The winner of all", Some("appId"), + 42L, "Garfield", Some("appAttempt")) val applicationEnd = SparkListenerApplicationEnd(42L) val logUrlMap = Map("stderr" -> "mystderr", "stdout" -> "mystdout").toMap val executorAdded = SparkListenerExecutorAdded(executorAddedTime, "exec1", @@ -274,9 +275,11 @@ class JsonProtocolSuite extends FunSuite { test("SparkListenerApplicationStart backwards compatibility") { // SparkListenerApplicationStart in Spark 1.0.0 do not have an "appId" property. - val applicationStart = SparkListenerApplicationStart("test", None, 1L, "user") + // SparkListenerApplicationStart pre-Spark 1.4 does not have "appAttemptId". + val applicationStart = SparkListenerApplicationStart("test", None, 1L, "user", None) val oldEvent = JsonProtocol.applicationStartToJson(applicationStart) .removeField({ _._1 == "App ID" }) + .removeField({ _._1 == "App Attempt ID" }) assert(applicationStart === JsonProtocol.applicationStartFromJson(oldEvent)) } @@ -806,14 +809,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 201, | "Number of Cached Partitions": 301, | "Memory Size": 401, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 501 | } | ], @@ -991,12 +994,12 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": false, | "Replication": 2 | }, | "Memory Size": 0, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 0 | } | } @@ -1074,12 +1077,12 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": false, | "Replication": 2 | }, | "Memory Size": 0, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 0 | } | } @@ -1157,12 +1160,12 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": false, | "Replication": 2 | }, | "Memory Size": 0, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 0 | } | } @@ -1192,14 +1195,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 200, | "Number of Cached Partitions": 300, | "Memory Size": 400, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 500 | } | ], @@ -1234,14 +1237,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 400, | "Number of Cached Partitions": 600, | "Memory Size": 800, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 1000 | }, | { @@ -1252,14 +1255,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 401, | "Number of Cached Partitions": 601, | "Memory Size": 801, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 1001 | } | ], @@ -1294,14 +1297,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 600, | "Number of Cached Partitions": 900, | "Memory Size": 1200, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 1500 | }, | { @@ -1312,14 +1315,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 601, | "Number of Cached Partitions": 901, | "Memory Size": 1201, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 1501 | }, | { @@ -1330,14 +1333,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 602, | "Number of Cached Partitions": 902, | "Memory Size": 1202, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 1502 | } | ], @@ -1372,14 +1375,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 800, | "Number of Cached Partitions": 1200, | "Memory Size": 1600, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 2000 | }, | { @@ -1390,14 +1393,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 801, | "Number of Cached Partitions": 1201, | "Memory Size": 1601, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 2001 | }, | { @@ -1408,14 +1411,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 802, | "Number of Cached Partitions": 1202, | "Memory Size": 1602, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 2002 | }, | { @@ -1426,14 +1429,14 @@ class JsonProtocolSuite extends FunSuite { | "Storage Level": { | "Use Disk": true, | "Use Memory": true, - | "Use Tachyon": false, + | "Use ExternalBlockStore": false, | "Deserialized": true, | "Replication": 1 | }, | "Number of Partitions": 803, | "Number of Cached Partitions": 1203, | "Memory Size": 1603, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 2003 | } | ], @@ -1543,8 +1546,10 @@ class JsonProtocolSuite extends FunSuite { |{ | "Event": "SparkListenerApplicationStart", | "App Name": "The winner of all", + | "App ID": "appId", | "Timestamp": 42, - | "User": "Garfield" + | "User": "Garfield", + | "App Attempt ID": "appAttempt" |} """ diff --git a/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala index 28915bd53354e..133a76f28e000 100644 --- a/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/SizeEstimatorSuite.scala @@ -36,6 +36,15 @@ class DummyClass4(val d: DummyClass3) { val x: Int = 0 } +// dummy class to show class field blocks alignment. +class DummyClass5 extends DummyClass1 { + val x: Boolean = true +} + +class DummyClass6 extends DummyClass5 { + val y: Boolean = true +} + object DummyString { def apply(str: String) : DummyString = new DummyString(str.toArray) } @@ -50,6 +59,7 @@ class SizeEstimatorSuite override def beforeEach() { // Set the arch to 64-bit and compressedOops to true to get a deterministic test-case + super.beforeEach() System.setProperty("os.arch", "amd64") System.setProperty("spark.test.useCompressedOops", "true") } @@ -62,6 +72,22 @@ class SizeEstimatorSuite assertResult(48)(SizeEstimator.estimate(new DummyClass4(new DummyClass3))) } + test("primitive wrapper objects") { + assertResult(16)(SizeEstimator.estimate(new java.lang.Boolean(true))) + assertResult(16)(SizeEstimator.estimate(new java.lang.Byte("1"))) + assertResult(16)(SizeEstimator.estimate(new java.lang.Character('1'))) + assertResult(16)(SizeEstimator.estimate(new java.lang.Short("1"))) + assertResult(16)(SizeEstimator.estimate(new java.lang.Integer(1))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Long(1))) + assertResult(16)(SizeEstimator.estimate(new java.lang.Float(1.0))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Double(1.0d))) + } + + test("class field blocks rounding") { + assertResult(16)(SizeEstimator.estimate(new DummyClass5)) + assertResult(24)(SizeEstimator.estimate(new DummyClass6)) + } + // NOTE: The String class definition varies across JDK versions (1.6 vs. 1.7) and vendors // (Sun vs IBM). Use a DummyString class to make tests deterministic. test("strings") { @@ -102,18 +128,18 @@ class SizeEstimatorSuite val arr = new Array[Char](100000) assertResult(200016)(SizeEstimator.estimate(arr)) assertResult(480032)(SizeEstimator.estimate(Array.fill(10000)(new DummyString(arr)))) - + val buf = new ArrayBuffer[DummyString]() for (i <- 0 until 5000) { buf.append(new DummyString(new Array[Char](10))) } assertResult(340016)(SizeEstimator.estimate(buf.toArray)) - + for (i <- 0 until 5000) { buf.append(new DummyString(arr)) } assertResult(683912)(SizeEstimator.estimate(buf.toArray)) - + // If an array contains the *same* element many times, we should only count it once. val d1 = new DummyClass1 // 10 pointers plus 8-byte object @@ -155,5 +181,20 @@ class SizeEstimatorSuite assertResult(64)(SizeEstimator.estimate(DummyString("a"))) assertResult(64)(SizeEstimator.estimate(DummyString("ab"))) assertResult(72)(SizeEstimator.estimate(DummyString("abcdefgh"))) + + // primitive wrapper classes + assertResult(24)(SizeEstimator.estimate(new java.lang.Boolean(true))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Byte("1"))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Character('1'))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Short("1"))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Integer(1))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Long(1))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Float(1.0))) + assertResult(24)(SizeEstimator.estimate(new java.lang.Double(1.0d))) + } + + test("class field blocks rounding on 64-bit VM without useCompressedOops") { + assertResult(24)(SizeEstimator.estimate(new DummyClass5)) + assertResult(32)(SizeEstimator.estimate(new DummyClass6)) } } diff --git a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala index 62a3cbcdf69ea..651ead6ff1de2 100644 --- a/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/UtilsSuite.scala @@ -35,9 +35,10 @@ import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path import org.apache.spark.network.util.ByteUnit +import org.apache.spark.Logging import org.apache.spark.SparkConf -class UtilsSuite extends FunSuite with ResetSystemProperties { +class UtilsSuite extends FunSuite with ResetSystemProperties with Logging { test("timeConversion") { // Test -1 @@ -68,7 +69,7 @@ class UtilsSuite extends FunSuite with ResetSystemProperties { intercept[NumberFormatException] { Utils.timeStringAsMs("600l") } - + intercept[NumberFormatException] { Utils.timeStringAsMs("This breaks 600s") } @@ -99,7 +100,7 @@ class UtilsSuite extends FunSuite with ResetSystemProperties { assert(Utils.byteStringAsGb("1k") === 0) assert(Utils.byteStringAsGb("1t") === ByteUnit.TiB.toGiB(1)) assert(Utils.byteStringAsGb("1p") === ByteUnit.PiB.toGiB(1)) - + assert(Utils.byteStringAsMb("1") === 1) assert(Utils.byteStringAsMb("1m") === 1) assert(Utils.byteStringAsMb("1048575b") === 0) @@ -118,7 +119,7 @@ class UtilsSuite extends FunSuite with ResetSystemProperties { assert(Utils.byteStringAsKb("1g") === ByteUnit.GiB.toKiB(1)) assert(Utils.byteStringAsKb("1t") === ByteUnit.TiB.toKiB(1)) assert(Utils.byteStringAsKb("1p") === ByteUnit.PiB.toKiB(1)) - + assert(Utils.byteStringAsBytes("1") === 1) assert(Utils.byteStringAsBytes("1k") === ByteUnit.KiB.toBytes(1)) assert(Utils.byteStringAsBytes("1m") === ByteUnit.MiB.toBytes(1)) @@ -127,17 +128,17 @@ class UtilsSuite extends FunSuite with ResetSystemProperties { assert(Utils.byteStringAsBytes("1p") === ByteUnit.PiB.toBytes(1)) // Overflow handling, 1073741824p exceeds Long.MAX_VALUE if converted straight to Bytes - // This demonstrates that we can have e.g 1024^3 PB without overflowing. + // This demonstrates that we can have e.g 1024^3 PB without overflowing. assert(Utils.byteStringAsGb("1073741824p") === ByteUnit.PiB.toGiB(1073741824)) assert(Utils.byteStringAsMb("1073741824p") === ByteUnit.PiB.toMiB(1073741824)) - + // Run this to confirm it doesn't throw an exception - assert(Utils.byteStringAsBytes("9223372036854775807") === 9223372036854775807L) + assert(Utils.byteStringAsBytes("9223372036854775807") === 9223372036854775807L) assert(ByteUnit.PiB.toPiB(9223372036854775807L) === 9223372036854775807L) - + // Test overflow exception intercept[IllegalArgumentException] { - // This value exceeds Long.MAX when converted to bytes + // This value exceeds Long.MAX when converted to bytes Utils.byteStringAsBytes("9223372036854775808") } @@ -146,22 +147,22 @@ class UtilsSuite extends FunSuite with ResetSystemProperties { // This value exceeds Long.MAX when converted to TB ByteUnit.PiB.toTiB(9223372036854775807L) } - + // Test fractional string intercept[NumberFormatException] { Utils.byteStringAsMb("0.064") } - + // Test fractional string intercept[NumberFormatException] { Utils.byteStringAsMb("0.064m") } - + // Test invalid strings intercept[NumberFormatException] { Utils.byteStringAsBytes("500ub") } - + // Test invalid strings intercept[NumberFormatException] { Utils.byteStringAsBytes("This breaks 600b") @@ -174,12 +175,12 @@ class UtilsSuite extends FunSuite with ResetSystemProperties { intercept[NumberFormatException] { Utils.byteStringAsBytes("600gb This breaks") } - + intercept[NumberFormatException] { Utils.byteStringAsBytes("This 123mb breaks") } } - + test("bytesToString") { assert(Utils.bytesToString(10) === "10.0 B") assert(Utils.bytesToString(1500) === "1500.0 B") @@ -475,6 +476,15 @@ class UtilsSuite extends FunSuite with ResetSystemProperties { } } + // Test for using the util function to change our log levels. + test("log4j log level change") { + Utils.setLogLevel(org.apache.log4j.Level.ALL) + assert(log.isInfoEnabled()) + Utils.setLogLevel(org.apache.log4j.Level.ERROR) + assert(!log.isInfoEnabled()) + assert(log.isErrorEnabled()) + } + test("deleteRecursively") { val tempDir1 = Utils.createTempDir() assert(tempDir1.exists()) diff --git a/core/src/test/scala/org/apache/spark/util/collection/ChainedBufferSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/ChainedBufferSuite.scala new file mode 100644 index 0000000000000..c0c38cd4ac4ad --- /dev/null +++ b/core/src/test/scala/org/apache/spark/util/collection/ChainedBufferSuite.scala @@ -0,0 +1,143 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util.collection + +import java.nio.ByteBuffer + +import org.scalatest.FunSuite +import org.scalatest.Matchers._ + +class ChainedBufferSuite extends FunSuite { + test("write and read at start") { + // write from start of source array + val buffer = new ChainedBuffer(8) + buffer.capacity should be (0) + verifyWriteAndRead(buffer, 0, 0, 0, 4) + buffer.capacity should be (8) + + // write from middle of source array + verifyWriteAndRead(buffer, 0, 5, 0, 4) + buffer.capacity should be (8) + + // read to middle of target array + verifyWriteAndRead(buffer, 0, 0, 5, 4) + buffer.capacity should be (8) + + // write up to border + verifyWriteAndRead(buffer, 0, 0, 0, 8) + buffer.capacity should be (8) + + // expand into second buffer + verifyWriteAndRead(buffer, 0, 0, 0, 12) + buffer.capacity should be (16) + + // expand into multiple buffers + verifyWriteAndRead(buffer, 0, 0, 0, 28) + buffer.capacity should be (32) + } + + test("write and read at middle") { + val buffer = new ChainedBuffer(8) + + // fill to a middle point + verifyWriteAndRead(buffer, 0, 0, 0, 3) + + // write from start of source array + verifyWriteAndRead(buffer, 3, 0, 0, 4) + buffer.capacity should be (8) + + // write from middle of source array + verifyWriteAndRead(buffer, 3, 5, 0, 4) + buffer.capacity should be (8) + + // read to middle of target array + verifyWriteAndRead(buffer, 3, 0, 5, 4) + buffer.capacity should be (8) + + // write up to border + verifyWriteAndRead(buffer, 3, 0, 0, 5) + buffer.capacity should be (8) + + // expand into second buffer + verifyWriteAndRead(buffer, 3, 0, 0, 12) + buffer.capacity should be (16) + + // expand into multiple buffers + verifyWriteAndRead(buffer, 3, 0, 0, 28) + buffer.capacity should be (32) + } + + test("write and read at later buffer") { + val buffer = new ChainedBuffer(8) + + // fill to a middle point + verifyWriteAndRead(buffer, 0, 0, 0, 11) + + // write from start of source array + verifyWriteAndRead(buffer, 11, 0, 0, 4) + buffer.capacity should be (16) + + // write from middle of source array + verifyWriteAndRead(buffer, 11, 5, 0, 4) + buffer.capacity should be (16) + + // read to middle of target array + verifyWriteAndRead(buffer, 11, 0, 5, 4) + buffer.capacity should be (16) + + // write up to border + verifyWriteAndRead(buffer, 11, 0, 0, 5) + buffer.capacity should be (16) + + // expand into second buffer + verifyWriteAndRead(buffer, 11, 0, 0, 12) + buffer.capacity should be (24) + + // expand into multiple buffers + verifyWriteAndRead(buffer, 11, 0, 0, 28) + buffer.capacity should be (40) + } + + + // Used to make sure we're writing different bytes each time + var rangeStart = 0 + + /** + * @param buffer The buffer to write to and read from. + * @param offsetInBuffer The offset to write to in the buffer. + * @param offsetInSource The offset in the array that the bytes are written from. + * @param offsetInTarget The offset in the array to read the bytes into. + * @param length The number of bytes to read and write + */ + def verifyWriteAndRead( + buffer: ChainedBuffer, + offsetInBuffer: Int, + offsetInSource: Int, + offsetInTarget: Int, + length: Int): Unit = { + val source = new Array[Byte](offsetInSource + length) + (rangeStart until rangeStart + length).map(_.toByte).copyToArray(source, offsetInSource) + buffer.write(offsetInBuffer, source, offsetInSource, length) + val target = new Array[Byte](offsetInTarget + length) + buffer.read(offsetInBuffer, target, offsetInTarget, length) + ByteBuffer.wrap(source, offsetInSource, length) should be + (ByteBuffer.wrap(target, offsetInTarget, length)) + + rangeStart += 100 + } +} diff --git a/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala index 9ff067f86af44..7a98723bc6472 100644 --- a/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/collection/ExternalSorterSuite.scala @@ -19,19 +19,24 @@ package org.apache.spark.util.collection import scala.collection.mutable.ArrayBuffer -import org.scalatest.{PrivateMethodTester, FunSuite} - -import org.apache.spark._ +import org.scalatest.{FunSuite, PrivateMethodTester} import scala.util.Random +import org.apache.spark._ +import org.apache.spark.serializer.{JavaSerializer, KryoSerializer} + class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMethodTester { - private def createSparkConf(loadDefaults: Boolean): SparkConf = { + private def createSparkConf(loadDefaults: Boolean, kryo: Boolean): SparkConf = { val conf = new SparkConf(loadDefaults) - // Make the Java serializer write a reset instruction (TC_RESET) after each object to test - // for a bug we had with bytes written past the last object in a batch (SPARK-2792) - conf.set("spark.serializer.objectStreamReset", "1") - conf.set("spark.serializer", "org.apache.spark.serializer.JavaSerializer") + if (kryo) { + conf.set("spark.serializer", classOf[KryoSerializer].getName) + } else { + // Make the Java serializer write a reset instruction (TC_RESET) after each object to test + // for a bug we had with bytes written past the last object in a batch (SPARK-2792) + conf.set("spark.serializer.objectStreamReset", "1") + conf.set("spark.serializer", classOf[JavaSerializer].getName) + } // Ensure that we actually have multiple batches per spill file conf.set("spark.shuffle.spill.batchSize", "10") conf @@ -47,8 +52,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(!sorter.invokePrivate(bypassMergeSort()), "sorter bypassed merge-sort") } - test("empty data stream") { - val conf = new SparkConf(false) + test("empty data stream with kryo ser") { + emptyDataStream(createSparkConf(false, true)) + } + + test("empty data stream with java ser") { + emptyDataStream(createSparkConf(false, false)) + } + + def emptyDataStream(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -81,8 +93,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe sorter4.stop() } - test("few elements per partition") { - val conf = createSparkConf(false) + test("few elements per partition with kryo ser") { + fewElementsPerPartition(createSparkConf(false, true)) + } + + test("few elements per partition with java ser") { + fewElementsPerPartition(createSparkConf(false, false)) + } + + def fewElementsPerPartition(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -123,8 +142,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe sorter4.stop() } - test("empty partitions with spilling") { - val conf = createSparkConf(false) + test("empty partitions with spilling with kryo ser") { + emptyPartitionsWithSpilling(createSparkConf(false, true)) + } + + test("empty partitions with spilling with java ser") { + emptyPartitionsWithSpilling(createSparkConf(false, false)) + } + + def emptyPartitionsWithSpilling(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.spill.initialMemoryThreshold", "512") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") @@ -149,8 +175,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe sorter.stop() } - test("empty partitions with spilling, bypass merge-sort") { - val conf = createSparkConf(false) + test("empty partitions with spilling, bypass merge-sort with kryo ser") { + emptyPartitionerWithSpillingBypassMergeSort(createSparkConf(false, true)) + } + + test("empty partitions with spilling, bypass merge-sort with java ser") { + emptyPartitionerWithSpillingBypassMergeSort(createSparkConf(false, false)) + } + + def emptyPartitionerWithSpillingBypassMergeSort(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.spill.initialMemoryThreshold", "512") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") @@ -174,8 +207,17 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe sorter.stop() } - test("spilling in local cluster") { - val conf = createSparkConf(true) // Load defaults, otherwise SPARK_HOME is not found + test("spilling in local cluster with kryo ser") { + // Load defaults, otherwise SPARK_HOME is not found + testSpillingInLocalCluster(createSparkConf(true, true)) + } + + test("spilling in local cluster with java ser") { + // Load defaults, otherwise SPARK_HOME is not found + testSpillingInLocalCluster(createSparkConf(true, false)) + } + + def testSpillingInLocalCluster(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local-cluster[1,1,512]", "test", conf) @@ -245,8 +287,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(resultE === (0 until 100000).map(i => (i/4, i)).toSeq) } - test("spilling in local cluster with many reduce tasks") { - val conf = createSparkConf(true) // Load defaults, otherwise SPARK_HOME is not found + test("spilling in local cluster with many reduce tasks with kryo ser") { + spillingInLocalClusterWithManyReduceTasks(createSparkConf(true, true)) + } + + test("spilling in local cluster with many reduce tasks with java ser") { + spillingInLocalClusterWithManyReduceTasks(createSparkConf(true, false)) + } + + def spillingInLocalClusterWithManyReduceTasks(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local-cluster[2,1,512]", "test", conf) @@ -317,7 +366,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("cleanup of intermediate files in sorter") { - val conf = createSparkConf(true) // Load defaults, otherwise SPARK_HOME is not found + val conf = createSparkConf(true, false) // Load defaults, otherwise SPARK_HOME is not found conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -328,7 +377,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe val sorter = new ExternalSorter[Int, Int, Int]( None, Some(new HashPartitioner(3)), Some(ord), None) assertDidNotBypassMergeSort(sorter) - sorter.insertAll((0 until 100000).iterator.map(i => (i, i))) + sorter.insertAll((0 until 120000).iterator.map(i => (i, i))) assert(diskBlockManager.getAllFiles().length > 0) sorter.stop() assert(diskBlockManager.getAllBlocks().length === 0) @@ -336,15 +385,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe val sorter2 = new ExternalSorter[Int, Int, Int]( None, Some(new HashPartitioner(3)), Some(ord), None) assertDidNotBypassMergeSort(sorter2) - sorter2.insertAll((0 until 100000).iterator.map(i => (i, i))) + sorter2.insertAll((0 until 120000).iterator.map(i => (i, i))) assert(diskBlockManager.getAllFiles().length > 0) - assert(sorter2.iterator.toSet === (0 until 100000).map(i => (i, i)).toSet) + assert(sorter2.iterator.toSet === (0 until 120000).map(i => (i, i)).toSet) sorter2.stop() assert(diskBlockManager.getAllBlocks().length === 0) } test("cleanup of intermediate files in sorter, bypass merge-sort") { - val conf = createSparkConf(true) // Load defaults, otherwise SPARK_HOME is not found + val conf = createSparkConf(true, false) // Load defaults, otherwise SPARK_HOME is not found conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -367,7 +416,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("cleanup of intermediate files in sorter if there are errors") { - val conf = createSparkConf(true) // Load defaults, otherwise SPARK_HOME is not found + val conf = createSparkConf(true, false) // Load defaults, otherwise SPARK_HOME is not found conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -379,8 +428,8 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe None, Some(new HashPartitioner(3)), Some(ord), None) assertDidNotBypassMergeSort(sorter) intercept[SparkException] { - sorter.insertAll((0 until 100000).iterator.map(i => { - if (i == 99990) { + sorter.insertAll((0 until 120000).iterator.map(i => { + if (i == 119990) { throw new SparkException("Intentional failure") } (i, i) @@ -392,7 +441,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("cleanup of intermediate files in sorter if there are errors, bypass merge-sort") { - val conf = createSparkConf(true) // Load defaults, otherwise SPARK_HOME is not found + val conf = createSparkConf(true, false) // Load defaults, otherwise SPARK_HOME is not found conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -414,7 +463,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("cleanup of intermediate files in shuffle") { - val conf = createSparkConf(false) + val conf = createSparkConf(false, false) conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -429,7 +478,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("cleanup of intermediate files in shuffle with errors") { - val conf = createSparkConf(false) + val conf = createSparkConf(false, false) conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -450,8 +499,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(diskBlockManager.getAllFiles().length === 2) } - test("no partial aggregation or sorting") { - val conf = createSparkConf(false) + test("no partial aggregation or sorting with kryo ser") { + noPartialAggregationOrSorting(createSparkConf(false, true)) + } + + test("no partial aggregation or sorting with java ser") { + noPartialAggregationOrSorting(createSparkConf(false, false)) + } + + def noPartialAggregationOrSorting(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -465,8 +521,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(results === expected) } - test("partial aggregation without spill") { - val conf = createSparkConf(false) + test("partial aggregation without spill with kryo ser") { + partialAggregationWithoutSpill(createSparkConf(false, true)) + } + + test("partial aggregation without spill with java ser") { + partialAggregationWithoutSpill(createSparkConf(false, false)) + } + + def partialAggregationWithoutSpill(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -481,8 +544,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(results === expected) } - test("partial aggregation with spill, no ordering") { - val conf = createSparkConf(false) + test("partial aggregation with spill, no ordering with kryo ser") { + partialAggregationWIthSpillNoOrdering(createSparkConf(false, true)) + } + + test("partial aggregation with spill, no ordering with java ser") { + partialAggregationWIthSpillNoOrdering(createSparkConf(false, false)) + } + + def partialAggregationWIthSpillNoOrdering(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -497,8 +567,16 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(results === expected) } - test("partial aggregation with spill, with ordering") { - val conf = createSparkConf(false) + test("partial aggregation with spill, with ordering with kryo ser") { + partialAggregationWithSpillWithOrdering(createSparkConf(false, true)) + } + + + test("partial aggregation with spill, with ordering with java ser") { + partialAggregationWithSpillWithOrdering(createSparkConf(false, false)) + } + + def partialAggregationWithSpillWithOrdering(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -506,7 +584,10 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe val agg = new Aggregator[Int, Int, Int](i => i, (i, j) => i + j, (i, j) => i + j) val ord = implicitly[Ordering[Int]] val sorter = new ExternalSorter(Some(agg), Some(new HashPartitioner(3)), Some(ord), None) - sorter.insertAll((0 until 100000).iterator.map(i => (i / 2, i))) + + // avoid combine before spill + sorter.insertAll((0 until 50000).iterator.map(i => (i , 2 * i))) + sorter.insertAll((0 until 50000).iterator.map(i => (i, 2 * i + 1))) val results = sorter.partitionedIterator.map{case (p, vs) => (p, vs.toSet)}.toSet val expected = (0 until 3).map(p => { (p, (0 until 50000).map(i => (i, i * 4 + 1)).filter(_._1 % 3 == p).toSet) @@ -514,8 +595,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(results === expected) } - test("sorting without aggregation, no spill") { - val conf = createSparkConf(false) + test("sorting without aggregation, no spill with kryo ser") { + sortingWithoutAggregationNoSpill(createSparkConf(false, true)) + } + + test("sorting without aggregation, no spill with java ser") { + sortingWithoutAggregationNoSpill(createSparkConf(false, false)) + } + + def sortingWithoutAggregationNoSpill(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -531,8 +619,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assert(results === expected) } - test("sorting without aggregation, with spill") { - val conf = createSparkConf(false) + test("sorting without aggregation, with spill with kryo ser") { + sortingWithoutAggregationWithSpill(createSparkConf(false, true)) + } + + test("sorting without aggregation, with spill with java ser") { + sortingWithoutAggregationWithSpill(createSparkConf(false, false)) + } + + def sortingWithoutAggregationWithSpill(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -549,7 +644,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("spilling with hash collisions") { - val conf = createSparkConf(true) + val conf = createSparkConf(true, false) conf.set("spark.shuffle.memoryFraction", "0.001") sc = new SparkContext("local-cluster[1,1,512]", "test", conf) @@ -606,7 +701,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("spilling with many hash collisions") { - val conf = createSparkConf(true) + val conf = createSparkConf(true, false) conf.set("spark.shuffle.memoryFraction", "0.0001") sc = new SparkContext("local-cluster[1,1,512]", "test", conf) @@ -629,7 +724,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("spilling with hash collisions using the Int.MaxValue key") { - val conf = createSparkConf(true) + val conf = createSparkConf(true, false) conf.set("spark.shuffle.memoryFraction", "0.001") sc = new SparkContext("local-cluster[1,1,512]", "test", conf) @@ -653,7 +748,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("spilling with null keys and values") { - val conf = createSparkConf(true) + val conf = createSparkConf(true, false) conf.set("spark.shuffle.memoryFraction", "0.001") sc = new SparkContext("local-cluster[1,1,512]", "test", conf) @@ -682,7 +777,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } test("conditions for bypassing merge-sort") { - val conf = createSparkConf(false) + val conf = createSparkConf(false, false) conf.set("spark.shuffle.memoryFraction", "0.001") conf.set("spark.shuffle.manager", "org.apache.spark.shuffle.sort.SortShuffleManager") sc = new SparkContext("local", "test", conf) @@ -715,8 +810,15 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe assertDidNotBypassMergeSort(sorter4) } - test("sort without breaking sorting contracts") { - val conf = createSparkConf(true) + test("sort without breaking sorting contracts with kryo ser") { + sortWithoutBreakingSortingContracts(createSparkConf(true, true)) + } + + test("sort without breaking sorting contracts with java ser") { + sortWithoutBreakingSortingContracts(createSparkConf(true, false)) + } + + def sortWithoutBreakingSortingContracts(conf: SparkConf) { conf.set("spark.shuffle.memoryFraction", "0.01") conf.set("spark.shuffle.manager", "sort") sc = new SparkContext("local-cluster[1,1,512]", "test", conf) diff --git a/core/src/test/scala/org/apache/spark/util/collection/PartitionedSerializedPairBufferSuite.scala b/core/src/test/scala/org/apache/spark/util/collection/PartitionedSerializedPairBufferSuite.scala new file mode 100644 index 0000000000000..b5a2d9ef720c1 --- /dev/null +++ b/core/src/test/scala/org/apache/spark/util/collection/PartitionedSerializedPairBufferSuite.scala @@ -0,0 +1,149 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.util.collection + +import java.io.{ByteArrayInputStream, ByteArrayOutputStream, InputStream} + +import com.google.common.io.ByteStreams + +import org.scalatest.FunSuite +import org.scalatest.Matchers._ + +import org.apache.spark.SparkConf +import org.apache.spark.serializer.KryoSerializer +import org.apache.spark.storage.{FileSegment, BlockObjectWriter} + +class PartitionedSerializedPairBufferSuite extends FunSuite { + test("OrderedInputStream single record") { + val serializerInstance = new KryoSerializer(new SparkConf()).newInstance + + val buffer = new PartitionedSerializedPairBuffer[Int, SomeStruct](4, 32, serializerInstance) + val struct = SomeStruct("something", 5) + buffer.insert(4, 10, struct) + + val bytes = ByteStreams.toByteArray(buffer.orderedInputStream) + + val baos = new ByteArrayOutputStream() + val stream = serializerInstance.serializeStream(baos) + stream.writeObject(10) + stream.writeObject(struct) + stream.close() + + baos.toByteArray should be (bytes) + } + + test("insert single record") { + val serializerInstance = new KryoSerializer(new SparkConf()).newInstance + val buffer = new PartitionedSerializedPairBuffer[Int, SomeStruct](4, 32, serializerInstance) + val struct = SomeStruct("something", 5) + buffer.insert(4, 10, struct) + val elements = buffer.partitionedDestructiveSortedIterator(None).toArray + elements.size should be (1) + elements.head should be (((4, 10), struct)) + } + + test("insert multiple records") { + val serializerInstance = new KryoSerializer(new SparkConf()).newInstance + val buffer = new PartitionedSerializedPairBuffer[Int, SomeStruct](4, 32, serializerInstance) + val struct1 = SomeStruct("something1", 8) + buffer.insert(6, 1, struct1) + val struct2 = SomeStruct("something2", 9) + buffer.insert(4, 2, struct2) + val struct3 = SomeStruct("something3", 10) + buffer.insert(5, 3, struct3) + + val elements = buffer.partitionedDestructiveSortedIterator(None).toArray + elements.size should be (3) + elements(0) should be (((4, 2), struct2)) + elements(1) should be (((5, 3), struct3)) + elements(2) should be (((6, 1), struct1)) + } + + test("write single record") { + val serializerInstance = new KryoSerializer(new SparkConf()).newInstance + val buffer = new PartitionedSerializedPairBuffer[Int, SomeStruct](4, 32, serializerInstance) + val struct = SomeStruct("something", 5) + buffer.insert(4, 10, struct) + val it = buffer.destructiveSortedWritablePartitionedIterator(None) + val writer = new SimpleBlockObjectWriter + assert(it.hasNext) + it.nextPartition should be (4) + it.writeNext(writer) + assert(!it.hasNext) + + val stream = serializerInstance.deserializeStream(writer.getInputStream) + stream.readObject[AnyRef]() should be (10) + stream.readObject[AnyRef]() should be (struct) + } + + test("write multiple records") { + val serializerInstance = new KryoSerializer(new SparkConf()).newInstance + val buffer = new PartitionedSerializedPairBuffer[Int, SomeStruct](4, 32, serializerInstance) + val struct1 = SomeStruct("something1", 8) + buffer.insert(6, 1, struct1) + val struct2 = SomeStruct("something2", 9) + buffer.insert(4, 2, struct2) + val struct3 = SomeStruct("something3", 10) + buffer.insert(5, 3, struct3) + + val it = buffer.destructiveSortedWritablePartitionedIterator(None) + val writer = new SimpleBlockObjectWriter + assert(it.hasNext) + it.nextPartition should be (4) + it.writeNext(writer) + assert(it.hasNext) + it.nextPartition should be (5) + it.writeNext(writer) + assert(it.hasNext) + it.nextPartition should be (6) + it.writeNext(writer) + assert(!it.hasNext) + + val stream = serializerInstance.deserializeStream(writer.getInputStream) + val iter = stream.asIterator + iter.next() should be (2) + iter.next() should be (struct2) + iter.next() should be (3) + iter.next() should be (struct3) + iter.next() should be (1) + iter.next() should be (struct1) + assert(!iter.hasNext) + } +} + +case class SomeStruct(val str: String, val num: Int) + +class SimpleBlockObjectWriter extends BlockObjectWriter(null) { + val baos = new ByteArrayOutputStream() + + override def write(bytes: Array[Byte], offs: Int, len: Int): Unit = { + baos.write(bytes, offs, len) + } + + def getInputStream(): InputStream = new ByteArrayInputStream(baos.toByteArray) + + override def open(): BlockObjectWriter = this + override def close(): Unit = { } + override def isOpen: Boolean = true + override def commitAndClose(): Unit = { } + override def revertPartialWritesAndClose(): Unit = { } + override def fileSegment(): FileSegment = null + override def write(key: Any, value: Any): Unit = { } + override def recordWritten(): Unit = { } + override def write(b: Int): Unit = { } +} diff --git a/dev/run-tests-jenkins b/dev/run-tests-jenkins index 030f2cdddb350..f452ab66efcd8 100755 --- a/dev/run-tests-jenkins +++ b/dev/run-tests-jenkins @@ -62,7 +62,7 @@ TESTS_TIMEOUT="150m" # format: http://linux.die.net/man/1/timeout PR_TESTS=( "pr_merge_ability" "pr_public_classes" - "pr_new_dependencies" +# DISABLED (pwendell) "pr_new_dependencies" ) function post_message () { diff --git a/docker/spark-mesos/Dockerfile b/docker/spark-mesos/Dockerfile new file mode 100644 index 0000000000000..b90aef3655dee --- /dev/null +++ b/docker/spark-mesos/Dockerfile @@ -0,0 +1,30 @@ +# This is an example Dockerfile for creating a Spark image which can be +# references by the Spark property 'spark.mesos.executor.docker.image' +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +FROM mesosphere/mesos:0.20.1 + +# Update the base ubuntu image with dependencies needed for Spark +RUN apt-get update && \ + apt-get install -y python libnss3 openjdk-7-jre-headless curl + +RUN mkdir /opt/spark && \ + curl http://www.apache.org/dyn/closer.cgi/spark/spark-1.4.0/spark-1.4.0-bin-hadoop2.4.tgz \ + | tar -xzC /opt +ENV SPARK_HOME /opt/spark +ENV MESOS_NATIVE_JAVA_LIBRARY /usr/local/lib/libmesos.so diff --git a/docs/configuration.md b/docs/configuration.md index 72105feba4919..64066bc0d70cd 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -1,4 +1,4 @@ ---- +-- layout: global displayTitle: Spark Configuration title: Configuration @@ -843,19 +843,27 @@ Apart from these, the following properties are also available, and may be useful - spark.tachyonStore.baseDir + spark.externalBlockStore.blockManager + org.apache.spark.storage.TachyonBlockManager + + Implementation of external block manager (file system) that store RDDs. The file system's URL is set by + spark.externalBlockStore.url. + + + + spark.externalBlockStore.baseDir System.getProperty("java.io.tmpdir") - Directories of the Tachyon File System that store RDDs. The Tachyon file system's URL is set by - spark.tachyonStore.url. It can also be a comma-separated list of multiple + Directories of the external block store that store RDDs. The file system's URL is set by + spark.externalBlockStore.url It can also be a comma-separated list of multiple directories on Tachyon file system. - spark.tachyonStore.url - tachyon://localhost:19998 + spark.externalBlockStore.url + tachyon://localhost:19998 for Tachyon - The URL of the underlying Tachyon file system in the TachyonStore. + The URL of the underlying external blocker file system in the external block store. @@ -1456,6 +1464,16 @@ Apart from these, the following properties are also available, and may be useful for more details. + + spark.streaming.kafka.maxRetries + 1 + + Maximum number of consecutive retries the driver will make in order to find + the latest offsets on the leader of each partition (a default value of 1 + means that the driver will make a maximum of 2 attempts). Only applies to + the new Kafka direct stream API. + + #### Cluster Managers diff --git a/docs/mllib-collaborative-filtering.md b/docs/mllib-collaborative-filtering.md index 76140282a2dd0..7b397e30b2d90 100644 --- a/docs/mllib-collaborative-filtering.md +++ b/docs/mllib-collaborative-filtering.md @@ -216,7 +216,7 @@ model = ALS.train(ratings, rank, numIterations) testdata = ratings.map(lambda p: (p[0], p[1])) predictions = model.predictAll(testdata).map(lambda r: ((r[0], r[1]), r[2])) ratesAndPreds = ratings.map(lambda r: ((r[0], r[1]), r[2])).join(predictions) -MSE = ratesAndPreds.map(lambda r: (r[1][0] - r[1][1])**2).reduce(lambda x, y: x + y) / ratesAndPreds.count() +MSE = ratesAndPreds.map(lambda r: (r[1][0] - r[1][1])**2).mean() print("Mean Squared Error = " + str(MSE)) # Save and load model diff --git a/docs/running-on-mesos.md b/docs/running-on-mesos.md index 8f53d8201a089..5f1d6daeb27f0 100644 --- a/docs/running-on-mesos.md +++ b/docs/running-on-mesos.md @@ -184,6 +184,16 @@ acquire. By default, it will acquire *all* cores in the cluster (that get offere only makes sense if you run just one application at a time. You can cap the maximum number of cores using `conf.set("spark.cores.max", "10")` (for example). +# Mesos Docker Support + +Spark can make use of a Mesos Docker containerizer by setting the property `spark.mesos.executor.docker.image` +in your [SparkConf](configuration.html#spark-properties). + +The Docker image used must have an appropriate version of Spark already part of the image, or you can +have Mesos download Spark via the usual methods. + +Requires Mesos version 0.20.1 or later. + # Running Alongside Hadoop You can run Spark and Mesos alongside your existing Hadoop cluster by just launching them as a @@ -237,6 +247,38 @@ See the [configuration page](configuration.html) for information on Spark config The value can be a floating point number. + + spark.mesos.executor.docker.image + (none) + + Set the name of the docker image that the Spark executors will run in. The selected + image must have Spark installed, as well as a compatible version of the Mesos library. + The installed path of Spark in the image can be specified with spark.mesos.executor.home; + the installed path of the Mesos library can be specified with spark.executorEnv.MESOS_NATIVE_LIBRARY. + + + + spark.mesos.executor.docker.volumes + (none) + + Set the list of volumes which will be mounted into the Docker image, which was set using + spark.mesos.executor.docker.image. The format of this property is a comma-separated list of + mappings following the form passed to docker run -v. That is they take the form: + + 
[host_path:]container_path[:ro|:rw]
+ + + + spark.mesos.executor.docker.portmaps + (none) + + Set the list of incoming ports exposed by the Docker image, which was set using + spark.mesos.executor.docker.image. The format of this property is a comma-separated list of + mappings which take the form: + + 
host_port:container_port[:tcp|:udp]
+ + spark.mesos.executor.home driver side SPARK_HOME diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md index 0968fc5ad632b..b6701b64c2925 100644 --- a/docs/running-on-yarn.md +++ b/docs/running-on-yarn.md @@ -189,6 +189,13 @@ Most of the configs are the same for Spark on YARN as for other deployment modes In cluster mode, use spark.driver.extraJavaOptions instead. + + spark.yarn.am.extraLibraryPath + (none) + + Set a special library path to use when launching the application master in client mode. + + spark.yarn.maxAppAttempts yarn.resourcemanager.am.max-attempts in YARN diff --git a/docs/security.md b/docs/security.md index c034ba12ff1fc..d4ffa60e59a33 100644 --- a/docs/security.md +++ b/docs/security.md @@ -32,6 +32,8 @@ SSL must be configured on each node and configured for each component involved i ### YARN mode The key-store can be prepared on the client side and then distributed and used by the executors as the part of the application. It is possible because the user is able to deploy files before the application is started in YARN by using `spark.yarn.dist.files` or `spark.yarn.dist.archives` configuration settings. The responsibility for encryption of transferring these files is on YARN side and has nothing to do with Spark. +For long-running apps like Spark Streaming apps to be able to write to HDFS, it is possible to pass a principal and keytab to `spark-submit` via the `--principal` and `--keytab` parameters respectively. The keytab passed in will be copied over to the machine running the Application Master via the Hadoop Distributed Cache (securely - if YARN is configured with SSL and HDFS encryption is enabled). The Kerberos login will be periodically renewed using this principal and keytab and the delegation tokens required for HDFS will be generated periodically so the application can continue writing to HDFS. + ### Standalone mode The user needs to provide key-stores and configuration options for master and workers. They have to be set by attaching appropriate Java system properties in `SPARK_MASTER_OPTS` and in `SPARK_WORKER_OPTS` environment variables, or just in `SPARK_DAEMON_JAVA_OPTS`. In this mode, the user may allow the executors to use the SSL settings inherited from the worker which spawned that executor. It can be accomplished by setting `spark.ssl.useNodeLocalConf` to `true`. If that parameter is set, the settings provided by user on the client side, are not used by the executors. diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java index eaf00d09f550d..46377a99c4857 100644 --- a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java +++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java @@ -28,7 +28,6 @@ import org.apache.spark.ml.classification.ClassificationModel; import org.apache.spark.ml.param.IntParam; import org.apache.spark.ml.param.ParamMap; -import org.apache.spark.ml.param.Params; import org.apache.spark.ml.param.Params$; import org.apache.spark.mllib.linalg.BLAS; import org.apache.spark.mllib.linalg.Vector; @@ -100,11 +99,12 @@ public static void main(String[] args) throws Exception { /** * Example of defining a type of {@link Classifier}. * - * NOTE: This is private since it is an example. In practice, you may not want it to be private. + * Note: Some IDEs (e.g., IntelliJ) will complain that this will not compile due to + * {@link org.apache.spark.ml.param.Params#set} using incompatible return types. + * However, this should still compile and run successfully. */ class MyJavaLogisticRegression - extends Classifier - implements Params { + extends Classifier { /** * Param for max number of iterations @@ -145,10 +145,12 @@ public MyJavaLogisticRegressionModel train(DataFrame dataset, ParamMap paramMap) /** * Example of defining a type of {@link ClassificationModel}. * - * NOTE: This is private since it is an example. In practice, you may not want it to be private. + * Note: Some IDEs (e.g., IntelliJ) will complain that this will not compile due to + * {@link org.apache.spark.ml.param.Params#set} using incompatible return types. + * However, this should still compile and run successfully. */ class MyJavaLogisticRegressionModel - extends ClassificationModel implements Params { + extends ClassificationModel { private MyJavaLogisticRegression parent_; public MyJavaLogisticRegression parent() { return parent_; } diff --git a/external/kafka/pom.xml b/external/kafka/pom.xml index f695cff410a18..243ce6eaca658 100644 --- a/external/kafka/pom.xml +++ b/external/kafka/pom.xml @@ -44,7 +44,7 @@ org.apache.kafka kafka_${scala.binary.version} - 0.8.1.1 + 0.8.2.1 com.sun.jmx diff --git a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala index bd767031c1849..6cf254a7b69cb 100644 --- a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala +++ b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaCluster.scala @@ -20,9 +20,10 @@ package org.apache.spark.streaming.kafka import scala.util.control.NonFatal import scala.util.Random import scala.collection.mutable.ArrayBuffer +import scala.collection.JavaConverters._ import java.util.Properties import kafka.api._ -import kafka.common.{ErrorMapping, OffsetMetadataAndError, TopicAndPartition} +import kafka.common.{ErrorMapping, OffsetAndMetadata, OffsetMetadataAndError, TopicAndPartition} import kafka.consumer.{ConsumerConfig, SimpleConsumer} import org.apache.spark.SparkException @@ -220,12 +221,22 @@ class KafkaCluster(val kafkaParams: Map[String, String]) extends Serializable { // https://cwiki.apache.org/confluence/display/KAFKA/A+Guide+To+The+Kafka+Protocol#AGuideToTheKafkaProtocol-OffsetCommit/FetchAPI // scalastyle:on + // this 0 here indicates api version, in this case the original ZK backed api. + private def defaultConsumerApiVersion: Short = 0 + /** Requires Kafka >= 0.8.1.1 */ def getConsumerOffsets( groupId: String, topicAndPartitions: Set[TopicAndPartition] + ): Either[Err, Map[TopicAndPartition, Long]] = + getConsumerOffsets(groupId, topicAndPartitions, defaultConsumerApiVersion) + + def getConsumerOffsets( + groupId: String, + topicAndPartitions: Set[TopicAndPartition], + consumerApiVersion: Short ): Either[Err, Map[TopicAndPartition, Long]] = { - getConsumerOffsetMetadata(groupId, topicAndPartitions).right.map { r => + getConsumerOffsetMetadata(groupId, topicAndPartitions, consumerApiVersion).right.map { r => r.map { kv => kv._1 -> kv._2.offset } @@ -236,9 +247,16 @@ class KafkaCluster(val kafkaParams: Map[String, String]) extends Serializable { def getConsumerOffsetMetadata( groupId: String, topicAndPartitions: Set[TopicAndPartition] + ): Either[Err, Map[TopicAndPartition, OffsetMetadataAndError]] = + getConsumerOffsetMetadata(groupId, topicAndPartitions, defaultConsumerApiVersion) + + def getConsumerOffsetMetadata( + groupId: String, + topicAndPartitions: Set[TopicAndPartition], + consumerApiVersion: Short ): Either[Err, Map[TopicAndPartition, OffsetMetadataAndError]] = { var result = Map[TopicAndPartition, OffsetMetadataAndError]() - val req = OffsetFetchRequest(groupId, topicAndPartitions.toSeq) + val req = OffsetFetchRequest(groupId, topicAndPartitions.toSeq, consumerApiVersion) val errs = new Err withBrokers(Random.shuffle(config.seedBrokers), errs) { consumer => val resp = consumer.fetchOffsets(req) @@ -266,24 +284,39 @@ class KafkaCluster(val kafkaParams: Map[String, String]) extends Serializable { def setConsumerOffsets( groupId: String, offsets: Map[TopicAndPartition, Long] + ): Either[Err, Map[TopicAndPartition, Short]] = + setConsumerOffsets(groupId, offsets, defaultConsumerApiVersion) + + def setConsumerOffsets( + groupId: String, + offsets: Map[TopicAndPartition, Long], + consumerApiVersion: Short ): Either[Err, Map[TopicAndPartition, Short]] = { - setConsumerOffsetMetadata(groupId, offsets.map { kv => - kv._1 -> OffsetMetadataAndError(kv._2) - }) + val meta = offsets.map { kv => + kv._1 -> OffsetAndMetadata(kv._2) + } + setConsumerOffsetMetadata(groupId, meta, consumerApiVersion) } /** Requires Kafka >= 0.8.1.1 */ def setConsumerOffsetMetadata( groupId: String, - metadata: Map[TopicAndPartition, OffsetMetadataAndError] + metadata: Map[TopicAndPartition, OffsetAndMetadata] + ): Either[Err, Map[TopicAndPartition, Short]] = + setConsumerOffsetMetadata(groupId, metadata, defaultConsumerApiVersion) + + def setConsumerOffsetMetadata( + groupId: String, + metadata: Map[TopicAndPartition, OffsetAndMetadata], + consumerApiVersion: Short ): Either[Err, Map[TopicAndPartition, Short]] = { var result = Map[TopicAndPartition, Short]() - val req = OffsetCommitRequest(groupId, metadata) + val req = OffsetCommitRequest(groupId, metadata, consumerApiVersion) val errs = new Err val topicAndPartitions = metadata.keySet withBrokers(Random.shuffle(config.seedBrokers), errs) { consumer => val resp = consumer.commitOffsets(req) - val respMap = resp.requestInfo + val respMap = resp.commitStatus val needed = topicAndPartitions.diff(result.keySet) needed.foreach { tp: TopicAndPartition => respMap.get(tp).foreach { err: Short => diff --git a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala index 13e9475065979..6dc4e9517d5a4 100644 --- a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala +++ b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaTestUtils.scala @@ -29,10 +29,12 @@ import scala.language.postfixOps import scala.util.control.NonFatal import kafka.admin.AdminUtils +import kafka.api.Request +import kafka.common.TopicAndPartition import kafka.producer.{KeyedMessage, Producer, ProducerConfig} import kafka.serializer.StringEncoder import kafka.server.{KafkaConfig, KafkaServer} -import kafka.utils.ZKStringSerializer +import kafka.utils.{ZKStringSerializer, ZkUtils} import org.apache.zookeeper.server.{NIOServerCnxnFactory, ZooKeeperServer} import org.I0Itec.zkclient.ZkClient @@ -227,12 +229,35 @@ private class KafkaTestUtils extends Logging { tryAgain(1) } - private def waitUntilMetadataIsPropagated(topic: String, partition: Int): Unit = { + /** Wait until the leader offset for the given topic/partition equals the specified offset */ + def waitUntilLeaderOffset( + topic: String, + partition: Int, + offset: Long): Unit = { eventually(Time(10000), Time(100)) { + val kc = new KafkaCluster(Map("metadata.broker.list" -> brokerAddress)) + val tp = TopicAndPartition(topic, partition) + val llo = kc.getLatestLeaderOffsets(Set(tp)).right.get.apply(tp).offset assert( - server.apis.metadataCache.containsTopicAndPartition(topic, partition), - s"Partition [$topic, $partition] metadata not propagated after timeout" - ) + llo == offset, + s"$topic $partition $offset not reached after timeout") + } + } + + private def waitUntilMetadataIsPropagated(topic: String, partition: Int): Unit = { + def isPropagated = server.apis.metadataCache.getPartitionInfo(topic, partition) match { + case Some(partitionState) => + val leaderAndInSyncReplicas = partitionState.leaderIsrAndControllerEpoch.leaderAndIsr + + ZkUtils.getLeaderForPartition(zkClient, topic, partition).isDefined && + Request.isValidBrokerId(leaderAndInSyncReplicas.leader) && + leaderAndInSyncReplicas.isr.size >= 1 + + case _ => + false + } + eventually(Time(10000), Time(100)) { + assert(isPropagated, s"Partition [$topic, $partition] metadata not propagated after timeout") } } diff --git a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaUtils.scala b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaUtils.scala index 0721ddaf7055a..d7cf500577c2a 100644 --- a/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaUtils.scala +++ b/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/KafkaUtils.scala @@ -31,6 +31,7 @@ import kafka.message.MessageAndMetadata import kafka.serializer.{DefaultDecoder, Decoder, StringDecoder} import org.apache.spark.api.java.function.{Function => JFunction} +import org.apache.spark.streaming.util.WriteAheadLogUtils import org.apache.spark.{SparkContext, SparkException} import org.apache.spark.annotation.Experimental import org.apache.spark.rdd.RDD @@ -80,7 +81,7 @@ object KafkaUtils { topics: Map[String, Int], storageLevel: StorageLevel ): ReceiverInputDStream[(K, V)] = { - val walEnabled = ssc.conf.getBoolean("spark.streaming.receiver.writeAheadLog.enable", false) + val walEnabled = WriteAheadLogUtils.enableReceiverLog(ssc.conf) new KafkaInputDStream[K, V, U, T](ssc, kafkaParams, topics, walEnabled, storageLevel) } diff --git a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java index a9dc6e50613ca..5cf379635354f 100644 --- a/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java +++ b/external/kafka/src/test/java/org/apache/spark/streaming/kafka/JavaKafkaRDDSuite.java @@ -72,6 +72,9 @@ public void testKafkaRDD() throws InterruptedException { HashMap kafkaParams = new HashMap(); kafkaParams.put("metadata.broker.list", kafkaTestUtils.brokerAddress()); + kafkaTestUtils.waitUntilLeaderOffset(topic1, 0, topic1data.length); + kafkaTestUtils.waitUntilLeaderOffset(topic2, 0, topic2data.length); + OffsetRange[] offsetRanges = { OffsetRange.create(topic1, 0, 0, 1), OffsetRange.create(topic2, 0, 0, 1) diff --git a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala index 7d26ce50875b3..39c3fb448ff57 100644 --- a/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala +++ b/external/kafka/src/test/scala/org/apache/spark/streaming/kafka/KafkaRDDSuite.scala @@ -53,14 +53,15 @@ class KafkaRDDSuite extends FunSuite with BeforeAndAfterAll { } test("basic usage") { - val topic = "topicbasic" + val topic = s"topicbasic-${Random.nextInt}" kafkaTestUtils.createTopic(topic) val messages = Set("the", "quick", "brown", "fox") kafkaTestUtils.sendMessages(topic, messages.toArray) - val kafkaParams = Map("metadata.broker.list" -> kafkaTestUtils.brokerAddress, - "group.id" -> s"test-consumer-${Random.nextInt(10000)}") + "group.id" -> s"test-consumer-${Random.nextInt}") + + kafkaTestUtils.waitUntilLeaderOffset(topic, 0, messages.size) val offsetRanges = Array(OffsetRange(topic, 0, 0, messages.size)) @@ -73,27 +74,38 @@ class KafkaRDDSuite extends FunSuite with BeforeAndAfterAll { test("iterator boundary conditions") { // the idea is to find e.g. off-by-one errors between what kafka has available and the rdd - val topic = "topic1" + val topic = s"topicboundary-${Random.nextInt}" val sent = Map("a" -> 5, "b" -> 3, "c" -> 10) kafkaTestUtils.createTopic(topic) val kafkaParams = Map("metadata.broker.list" -> kafkaTestUtils.brokerAddress, - "group.id" -> s"test-consumer-${Random.nextInt(10000)}") + "group.id" -> s"test-consumer-${Random.nextInt}") val kc = new KafkaCluster(kafkaParams) // this is the "lots of messages" case kafkaTestUtils.sendMessages(topic, sent) + val sentCount = sent.values.sum + kafkaTestUtils.waitUntilLeaderOffset(topic, 0, sentCount) + // rdd defined from leaders after sending messages, should get the number sent val rdd = getRdd(kc, Set(topic)) assert(rdd.isDefined) - assert(rdd.get.count === sent.values.sum, "didn't get all sent messages") - val ranges = rdd.get.asInstanceOf[HasOffsetRanges] - .offsetRanges.map(o => TopicAndPartition(o.topic, o.partition) -> o.untilOffset).toMap + val ranges = rdd.get.asInstanceOf[HasOffsetRanges].offsetRanges + val rangeCount = ranges.map(o => o.untilOffset - o.fromOffset).sum - kc.setConsumerOffsets(kafkaParams("group.id"), ranges) + assert(rangeCount === sentCount, "offset range didn't include all sent messages") + assert(rdd.get.count === sentCount, "didn't get all sent messages") + + val rangesMap = ranges.map(o => TopicAndPartition(o.topic, o.partition) -> o.untilOffset).toMap + + // make sure consumer offsets are committed before the next getRdd call + kc.setConsumerOffsets(kafkaParams("group.id"), rangesMap).fold( + err => throw new Exception(err.mkString("\n")), + _ => () + ) // this is the "0 messages" case val rdd2 = getRdd(kc, Set(topic)) @@ -101,6 +113,8 @@ class KafkaRDDSuite extends FunSuite with BeforeAndAfterAll { val sentOnlyOne = Map("d" -> 1) kafkaTestUtils.sendMessages(topic, sentOnlyOne) + kafkaTestUtils.waitUntilLeaderOffset(topic, 0, sentCount + 1) + assert(rdd2.isDefined) assert(rdd2.get.count === 0, "got messages when there shouldn't be any") diff --git a/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala b/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala index 86f611d55aa8a..7edd627b20918 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/GraphOps.scala @@ -372,6 +372,31 @@ class GraphOps[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED]) extends Seriali PageRank.runUntilConvergence(graph, tol, resetProb) } + + /** + * Run personalized PageRank for a given vertex, such that all random walks + * are started relative to the source node. + * + * @see [[org.apache.spark.graphx.lib.PageRank$#runUntilConvergenceWithOptions]] + */ + def personalizedPageRank(src: VertexId, tol: Double, + resetProb: Double = 0.15) : Graph[Double, Double] = { + PageRank.runUntilConvergenceWithOptions(graph, tol, resetProb, Some(src)) + } + + /** + * Run Personalized PageRank for a fixed number of iterations with + * with all iterations originating at the source node + * returning a graph with vertex attributes + * containing the PageRank and edge attributes the normalized edge weight. + * + * @see [[org.apache.spark.graphx.lib.PageRank$#runWithOptions]] + */ + def staticPersonalizedPageRank(src: VertexId, numIter: Int, + resetProb: Double = 0.15) : Graph[Double, Double] = { + PageRank.runWithOptions(graph, numIter, resetProb, Some(src)) + } + /** * Run PageRank for a fixed number of iterations returning a graph with vertex attributes * containing the PageRank and edge attributes the normalized edge weight. diff --git a/graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala b/graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala index 042e366a29f58..bc974b2f04e70 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala @@ -18,6 +18,7 @@ package org.apache.spark.graphx.lib import scala.reflect.ClassTag +import scala.language.postfixOps import org.apache.spark.Logging import org.apache.spark.graphx._ @@ -60,6 +61,7 @@ import org.apache.spark.graphx._ */ object PageRank extends Logging { + /** * Run PageRank for a fixed number of iterations returning a graph * with vertex attributes containing the PageRank and edge @@ -74,10 +76,33 @@ object PageRank extends Logging { * * @return the graph containing with each vertex containing the PageRank and each edge * containing the normalized weight. + */ + def run[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED], numIter: Int, + resetProb: Double = 0.15): Graph[Double, Double] = + { + runWithOptions(graph, numIter, resetProb) + } + + /** + * Run PageRank for a fixed number of iterations returning a graph + * with vertex attributes containing the PageRank and edge + * attributes the normalized edge weight. + * + * @tparam VD the original vertex attribute (not used) + * @tparam ED the original edge attribute (not used) + * + * @param graph the graph on which to compute PageRank + * @param numIter the number of iterations of PageRank to run + * @param resetProb the random reset probability (alpha) + * @param srcId the source vertex for a Personalized Page Rank (optional) + * + * @return the graph containing with each vertex containing the PageRank and each edge + * containing the normalized weight. * */ - def run[VD: ClassTag, ED: ClassTag]( - graph: Graph[VD, ED], numIter: Int, resetProb: Double = 0.15): Graph[Double, Double] = + def runWithOptions[VD: ClassTag, ED: ClassTag]( + graph: Graph[VD, ED], numIter: Int, resetProb: Double = 0.15, + srcId: Option[VertexId] = None): Graph[Double, Double] = { // Initialize the PageRank graph with each edge attribute having // weight 1/outDegree and each vertex with attribute 1.0. @@ -89,6 +114,10 @@ object PageRank extends Logging { // Set the vertex attributes to the initial pagerank values .mapVertices( (id, attr) => resetProb ) + val personalized = srcId isDefined + val src: VertexId = srcId.getOrElse(-1L) + def delta(u: VertexId, v: VertexId):Double = { if (u == v) 1.0 else 0.0 } + var iteration = 0 var prevRankGraph: Graph[Double, Double] = null while (iteration < numIter) { @@ -103,8 +132,14 @@ object PageRank extends Logging { // that didn't receive a message. Requires a shuffle for broadcasting updated ranks to the // edge partitions. prevRankGraph = rankGraph + val rPrb = if (personalized) { + (src: VertexId ,id: VertexId) => resetProb * delta(src,id) + } else { + (src: VertexId, id: VertexId) => resetProb + } + rankGraph = rankGraph.joinVertices(rankUpdates) { - (id, oldRank, msgSum) => resetProb + (1.0 - resetProb) * msgSum + (id, oldRank, msgSum) => rPrb(src,id) + (1.0 - resetProb) * msgSum }.cache() rankGraph.edges.foreachPartition(x => {}) // also materializes rankGraph.vertices @@ -133,7 +168,29 @@ object PageRank extends Logging { * containing the normalized weight. */ def runUntilConvergence[VD: ClassTag, ED: ClassTag]( - graph: Graph[VD, ED], tol: Double, resetProb: Double = 0.15): Graph[Double, Double] = + graph: Graph[VD, ED], tol: Double, resetProb: Double = 0.15): Graph[Double, Double] = + { + runUntilConvergenceWithOptions(graph, tol, resetProb) + } + + /** + * Run a dynamic version of PageRank returning a graph with vertex attributes containing the + * PageRank and edge attributes containing the normalized edge weight. + * + * @tparam VD the original vertex attribute (not used) + * @tparam ED the original edge attribute (not used) + * + * @param graph the graph on which to compute PageRank + * @param tol the tolerance allowed at convergence (smaller => more accurate). + * @param resetProb the random reset probability (alpha) + * @param srcId the source vertex for a Personalized Page Rank (optional) + * + * @return the graph containing with each vertex containing the PageRank and each edge + * containing the normalized weight. + */ + def runUntilConvergenceWithOptions[VD: ClassTag, ED: ClassTag]( + graph: Graph[VD, ED], tol: Double, resetProb: Double = 0.15, + srcId: Option[VertexId] = None): Graph[Double, Double] = { // Initialize the pagerankGraph with each edge attribute // having weight 1/outDegree and each vertex with attribute 1.0. @@ -148,6 +205,10 @@ object PageRank extends Logging { .mapVertices( (id, attr) => (0.0, 0.0) ) .cache() + val personalized = srcId.isDefined + val src: VertexId = srcId.getOrElse(-1L) + + // Define the three functions needed to implement PageRank in the GraphX // version of Pregel def vertexProgram(id: VertexId, attr: (Double, Double), msgSum: Double): (Double, Double) = { @@ -156,7 +217,18 @@ object PageRank extends Logging { (newPR, newPR - oldPR) } - def sendMessage(edge: EdgeTriplet[(Double, Double), Double]): Iterator[(VertexId, Double)] = { + def personalizedVertexProgram(id: VertexId, attr: (Double, Double), + msgSum: Double): (Double, Double) = { + val (oldPR, lastDelta) = attr + var teleport = oldPR + val delta = if (src==id) 1.0 else 0.0 + teleport = oldPR*delta + + val newPR = teleport + (1.0 - resetProb) * msgSum + (newPR, newPR - oldPR) + } + + def sendMessage(edge: EdgeTriplet[(Double, Double), Double]) = { if (edge.srcAttr._2 > tol) { Iterator((edge.dstId, edge.srcAttr._2 * edge.attr)) } else { @@ -170,8 +242,17 @@ object PageRank extends Logging { val initialMessage = resetProb / (1.0 - resetProb) // Execute a dynamic version of Pregel. + val vp = if (personalized) { + (id: VertexId, attr: (Double, Double),msgSum: Double) => + personalizedVertexProgram(id, attr, msgSum) + } else { + (id: VertexId, attr: (Double, Double), msgSum: Double) => + vertexProgram(id, attr, msgSum) + } + Pregel(pagerankGraph, initialMessage, activeDirection = EdgeDirection.Out)( - vertexProgram, sendMessage, messageCombiner) + vp, sendMessage, messageCombiner) .mapVertices((vid, attr) => attr._1) } // end of deltaPageRank + } diff --git a/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala b/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala index 95804b07b1db0..3f3c9dfd7b3dd 100644 --- a/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala +++ b/graphx/src/test/scala/org/apache/spark/graphx/lib/PageRankSuite.scala @@ -92,6 +92,36 @@ class PageRankSuite extends FunSuite with LocalSparkContext { } } // end of test Star PageRank + test("Star PersonalPageRank") { + withSpark { sc => + val nVertices = 100 + val starGraph = GraphGenerators.starGraph(sc, nVertices).cache() + val resetProb = 0.15 + val errorTol = 1.0e-5 + + val staticRanks1 = starGraph.staticPersonalizedPageRank(0,numIter = 1, resetProb).vertices + val staticRanks2 = starGraph.staticPersonalizedPageRank(0,numIter = 2, resetProb) + .vertices.cache() + + // Static PageRank should only take 2 iterations to converge + val notMatching = staticRanks1.innerZipJoin(staticRanks2) { (vid, pr1, pr2) => + if (pr1 != pr2) 1 else 0 + }.map { case (vid, test) => test }.sum + assert(notMatching === 0) + + val staticErrors = staticRanks2.map { case (vid, pr) => + val correct = (vid > 0 && pr == resetProb) || + (vid == 0 && math.abs(pr - (resetProb + (1.0 - resetProb) * (resetProb * + (nVertices - 1)) )) < 1.0E-5) + if (!correct) 1 else 0 + } + assert(staticErrors.sum === 0) + + val dynamicRanks = starGraph.personalizedPageRank(0,0, resetProb).vertices.cache() + assert(compareRanks(staticRanks2, dynamicRanks) < errorTol) + } + } // end of test Star PageRank + test("Grid PageRank") { withSpark { sc => val rows = 10 @@ -128,4 +158,21 @@ class PageRankSuite extends FunSuite with LocalSparkContext { assert(compareRanks(staticRanks, dynamicRanks) < errorTol) } } + + test("Chain PersonalizedPageRank") { + withSpark { sc => + val chain1 = (0 until 9).map(x => (x, x + 1) ) + val rawEdges = sc.parallelize(chain1, 1).map { case (s,d) => (s.toLong, d.toLong) } + val chain = Graph.fromEdgeTuples(rawEdges, 1.0).cache() + val resetProb = 0.15 + val tol = 0.0001 + val numIter = 10 + val errorTol = 1.0e-1 + + val staticRanks = chain.staticPersonalizedPageRank(4, numIter, resetProb).vertices + val dynamicRanks = chain.personalizedPageRank(4, tol, resetProb).vertices + + assert(compareRanks(staticRanks, dynamicRanks) < errorTol) + } + } } diff --git a/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java index a73c9c87e3126..7d387d406edae 100644 --- a/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java +++ b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitCommandBuilder.java @@ -190,6 +190,10 @@ private List buildSparkSubmitCommand(Map env) throws IOE firstNonEmptyValue(SparkLauncher.DRIVER_EXTRA_CLASSPATH, conf, props) : null; List cmd = buildJavaCommand(extraClassPath); + // Take Thrift Server as daemon + if (isThriftServer(mainClass)) { + addOptionString(cmd, System.getenv("SPARK_DAEMON_JAVA_OPTS")); + } addOptionString(cmd, System.getenv("SPARK_SUBMIT_OPTS")); addOptionString(cmd, System.getenv("SPARK_JAVA_OPTS")); @@ -201,7 +205,11 @@ private List buildSparkSubmitCommand(Map env) throws IOE // - SPARK_DRIVER_MEMORY env variable // - SPARK_MEM env variable // - default value (512m) - String memory = firstNonEmpty(firstNonEmptyValue(SparkLauncher.DRIVER_MEMORY, conf, props), + // Take Thrift Server as daemon + String tsMemory = + isThriftServer(mainClass) ? System.getenv("SPARK_DAEMON_MEMORY") : null; + String memory = firstNonEmpty(tsMemory, + firstNonEmptyValue(SparkLauncher.DRIVER_MEMORY, conf, props), System.getenv("SPARK_DRIVER_MEMORY"), System.getenv("SPARK_MEM"), DEFAULT_MEM); cmd.add("-Xms" + memory); cmd.add("-Xmx" + memory); @@ -292,6 +300,15 @@ private boolean isClientMode(Properties userProps) { (!userMaster.equals("yarn-cluster") && deployMode == null); } + /** + * Return whether the given main class represents a thrift server. + */ + private boolean isThriftServer(String mainClass) { + return (mainClass != null && + mainClass.equals("org.apache.spark.sql.hive.thriftserver.HiveThriftServer2")); + } + + private class OptionParser extends SparkSubmitOptionParser { @Override diff --git a/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java index 8526d2e7cfa3f..229000087688f 100644 --- a/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java +++ b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java @@ -69,8 +69,10 @@ class SparkSubmitOptionParser { // YARN-only options. protected final String ARCHIVES = "--archives"; protected final String EXECUTOR_CORES = "--executor-cores"; - protected final String QUEUE = "--queue"; + protected final String KEYTAB = "--keytab"; protected final String NUM_EXECUTORS = "--num-executors"; + protected final String PRINCIPAL = "--principal"; + protected final String QUEUE = "--queue"; /** * This is the canonical list of spark-submit options. Each entry in the array contains the @@ -96,11 +98,13 @@ class SparkSubmitOptionParser { { EXECUTOR_MEMORY }, { FILES }, { JARS }, + { KEYTAB }, { KILL_SUBMISSION }, { MASTER }, { NAME }, { NUM_EXECUTORS }, { PACKAGES }, + { PRINCIPAL }, { PROPERTIES_FILE }, { PROXY_USER }, { PY_FILES }, diff --git a/make-distribution.sh b/make-distribution.sh index cb65932b4abc0..92177e19fe6be 100755 --- a/make-distribution.sh +++ b/make-distribution.sh @@ -26,6 +26,7 @@ set -o pipefail set -e +set -x # Figure out where the Spark framework is installed SPARK_HOME="$(cd "`dirname "$0"`"; pwd)" @@ -126,7 +127,7 @@ if [ ! $(command -v "$MVN") ] ; then exit -1; fi -VERSION=$("$MVN" help:evaluate -Dexpression=project.version 2>/dev/null | grep -v "INFO" | tail -n 1) +VERSION=$("$MVN" help:evaluate -Dexpression=project.version $@ 2>/dev/null | grep -v "INFO" | tail -n 1) SCALA_VERSION=$("$MVN" help:evaluate -Dexpression=scala.binary.version $@ 2>/dev/null\ | grep -v "INFO"\ | tail -n 1) diff --git a/mllib/pom.xml b/mllib/pom.xml index 5dfab36c76907..a3c57ae26000b 100644 --- a/mllib/pom.xml +++ b/mllib/pom.xml @@ -109,6 +109,21 @@ test-jar test + + org.jpmml + pmml-model + 1.1.15 + + + com.sun.xml.fastinfoset + FastInfoset + + + com.sun.istack + istack-commons-runtime + + + diff --git a/mllib/src/main/scala/org/apache/spark/ml/Evaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/Evaluator.scala index d2ca2e6871e6b..8b4b5fd8af986 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/Evaluator.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/Evaluator.scala @@ -19,6 +19,7 @@ package org.apache.spark.ml import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml.param.ParamMap +import org.apache.spark.ml.util.Identifiable import org.apache.spark.sql.DataFrame /** diff --git a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala index 8eddf79cdfe28..6bfeecd764d75 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/Pipeline.scala @@ -21,7 +21,7 @@ import scala.collection.mutable.ListBuffer import org.apache.spark.Logging import org.apache.spark.annotation.{AlphaComponent, DeveloperApi} -import org.apache.spark.ml.param.{Param, ParamMap} +import org.apache.spark.ml.param.{Params, Param, ParamMap} import org.apache.spark.sql.DataFrame import org.apache.spark.sql.types.StructType @@ -86,6 +86,14 @@ class Pipeline extends Estimator[PipelineModel] { def setStages(value: Array[PipelineStage]): this.type = { set(stages, value); this } def getStages: Array[PipelineStage] = getOrDefault(stages) + override def validate(paramMap: ParamMap): Unit = { + val map = extractParamMap(paramMap) + getStages.foreach { + case pStage: Params => pStage.validate(map) + case _ => + } + } + /** * Fits the pipeline to the input dataset with additional parameters. If a stage is an * [[Estimator]], its [[Estimator#fit]] method will be called on the input dataset to fit a model. @@ -140,7 +148,7 @@ class Pipeline extends Estimator[PipelineModel] { override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = { val map = extractParamMap(paramMap) val theStages = map(stages) - require(theStages.toSet.size == theStages.size, + require(theStages.toSet.size == theStages.length, "Cannot have duplicate components in a pipeline.") theStages.foldLeft(schema)((cur, stage) => stage.transformSchema(cur, paramMap)) } @@ -157,6 +165,11 @@ class PipelineModel private[ml] ( private[ml] val stages: Array[Transformer]) extends Model[PipelineModel] with Logging { + override def validate(paramMap: ParamMap): Unit = { + val map = fittingParamMap ++ extractParamMap(paramMap) + stages.foreach(_.validate(map)) + } + /** * Gets the model produced by the input estimator. Throws an NoSuchElementException is the input * estimator does not exist in the pipeline. @@ -168,7 +181,7 @@ class PipelineModel private[ml] ( } if (matched.isEmpty) { throw new NoSuchElementException(s"Cannot find stage $stage from the pipeline.") - } else if (matched.size > 1) { + } else if (matched.length > 1) { throw new IllegalStateException(s"Cannot have duplicate estimators in the sample pipeline.") } else { matched.head.asInstanceOf[M] diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala index d2e052fbbbf22..3d849867d4c47 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala @@ -103,21 +103,16 @@ final class GBTClassifier */ val lossType: Param[String] = new Param[String](this, "lossType", "Loss function which GBT" + " tries to minimize (case-insensitive). Supported options:" + - s" ${GBTClassifier.supportedLossTypes.mkString(", ")}") + s" ${GBTClassifier.supportedLossTypes.mkString(", ")}", + (value: String) => GBTClassifier.supportedLossTypes.contains(value.toLowerCase)) setDefault(lossType -> "logistic") /** @group setParam */ - def setLossType(value: String): this.type = { - val lossStr = value.toLowerCase - require(GBTClassifier.supportedLossTypes.contains(lossStr), "GBTClassifier was given bad loss" + - s" type: $value. Supported options: ${GBTClassifier.supportedLossTypes.mkString(", ")}") - set(lossType, lossStr) - this - } + def setLossType(value: String): this.type = set(lossType, value) /** @group getParam */ - def getLossType: String = getOrDefault(lossType) + def getLossType: String = getOrDefault(lossType).toLowerCase /** (private[ml]) Convert new loss to old loss. */ override private[ml] def getOldLossType: OldLoss = { diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala new file mode 100644 index 0000000000000..f3ce6dfca2c1c --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala @@ -0,0 +1,85 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.feature + +import org.apache.spark.annotation.AlphaComponent +import org.apache.spark.ml.Transformer +import org.apache.spark.ml.attribute.BinaryAttribute +import org.apache.spark.ml.param._ +import org.apache.spark.ml.param.shared.{HasInputCol, HasOutputCol} +import org.apache.spark.ml.util.SchemaUtils +import org.apache.spark.sql._ +import org.apache.spark.sql.functions._ +import org.apache.spark.sql.types.{DoubleType, StructType} + +/** + * :: AlphaComponent :: + * Binarize a column of continuous features given a threshold. + */ +@AlphaComponent +final class Binarizer extends Transformer with HasInputCol with HasOutputCol { + + /** + * Param for threshold used to binarize continuous features. + * The features greater than the threshold, will be binarized to 1.0. + * The features equal to or less than the threshold, will be binarized to 0.0. + * @group param + */ + val threshold: DoubleParam = + new DoubleParam(this, "threshold", "threshold used to binarize continuous features") + + /** @group getParam */ + def getThreshold: Double = getOrDefault(threshold) + + /** @group setParam */ + def setThreshold(value: Double): this.type = set(threshold, value) + + setDefault(threshold -> 0.0) + + /** @group setParam */ + def setInputCol(value: String): this.type = set(inputCol, value) + + /** @group setParam */ + def setOutputCol(value: String): this.type = set(outputCol, value) + + override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = { + transformSchema(dataset.schema, paramMap, logging = true) + val map = extractParamMap(paramMap) + val td = map(threshold) + val binarizer = udf { in: Double => if (in > td) 1.0 else 0.0 } + val outputColName = map(outputCol) + val metadata = BinaryAttribute.defaultAttr.withName(outputColName).toMetadata() + dataset.select(col("*"), + binarizer(col(map(inputCol))).as(outputColName, metadata)) + } + + override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = { + val map = extractParamMap(paramMap) + SchemaUtils.checkColumnType(schema, map(inputCol), DoubleType) + + val inputFields = schema.fields + val outputColName = map(outputCol) + + require(inputFields.forall(_.name != outputColName), + s"Output column $outputColName already exists.") + + val attr = BinaryAttribute.defaultAttr.withName(outputColName) + val outputFields = inputFields :+ attr.toStructField() + StructType(outputFields) + } +} diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala index b20f2fc49a8f6..0b3128f9ee8cd 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/HashingTF.scala @@ -19,7 +19,7 @@ package org.apache.spark.ml.feature import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml.UnaryTransformer -import org.apache.spark.ml.param.{IntParam, ParamMap} +import org.apache.spark.ml.param.{ParamValidators, IntParam, ParamMap} import org.apache.spark.mllib.feature import org.apache.spark.mllib.linalg.{VectorUDT, Vector} import org.apache.spark.sql.types.DataType @@ -32,10 +32,14 @@ import org.apache.spark.sql.types.DataType class HashingTF extends UnaryTransformer[Iterable[_], Vector, HashingTF] { /** - * number of features + * Number of features. Should be > 0. + * (default = 2^18^) * @group param */ - val numFeatures = new IntParam(this, "numFeatures", "number of features") + val numFeatures = new IntParam(this, "numFeatures", "number of features (> 0)", + ParamValidators.gt(0)) + + setDefault(numFeatures -> (1 << 18)) /** @group getParam */ def getNumFeatures: Int = getOrDefault(numFeatures) @@ -43,8 +47,6 @@ class HashingTF extends UnaryTransformer[Iterable[_], Vector, HashingTF] { /** @group setParam */ def setNumFeatures(value: Int): this.type = set(numFeatures, value) - setDefault(numFeatures -> (1 << 18)) - override protected def createTransformFunc(paramMap: ParamMap): Iterable[_] => Vector = { val hashingTF = new feature.HashingTF(paramMap(numFeatures)) hashingTF.transform diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala index decaeb0da6246..bd2b5f6067e2d 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Normalizer.scala @@ -19,7 +19,7 @@ package org.apache.spark.ml.feature import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml.UnaryTransformer -import org.apache.spark.ml.param.{DoubleParam, ParamMap} +import org.apache.spark.ml.param.{ParamValidators, DoubleParam, ParamMap} import org.apache.spark.mllib.feature import org.apache.spark.mllib.linalg.{VectorUDT, Vector} import org.apache.spark.sql.types.DataType @@ -32,10 +32,13 @@ import org.apache.spark.sql.types.DataType class Normalizer extends UnaryTransformer[Vector, Vector, Normalizer] { /** - * Normalization in L^p^ space, p = 2 by default. + * Normalization in L^p^ space. Must be >= 1. + * (default: p = 2) * @group param */ - val p = new DoubleParam(this, "p", "the p norm value") + val p = new DoubleParam(this, "p", "the p norm value", ParamValidators.gtEq(1)) + + setDefault(p -> 2.0) /** @group getParam */ def getP: Double = getOrDefault(p) @@ -43,8 +46,6 @@ class Normalizer extends UnaryTransformer[Vector, Vector, Normalizer] { /** @group setParam */ def setP(value: Double): this.type = set(p, value) - setDefault(p -> 2.0) - override protected def createTransformFunc(paramMap: ParamMap): Vector => Vector = { val normalizer = new feature.Normalizer(paramMap(p)) normalizer.transform diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala index d855f04799ae7..1b7c939c2dffe 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/PolynomialExpansion.scala @@ -21,7 +21,7 @@ import scala.collection.mutable import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml.UnaryTransformer -import org.apache.spark.ml.param.{IntParam, ParamMap} +import org.apache.spark.ml.param.{ParamValidators, IntParam, ParamMap} import org.apache.spark.mllib.linalg._ import org.apache.spark.sql.types.DataType @@ -37,10 +37,13 @@ import org.apache.spark.sql.types.DataType class PolynomialExpansion extends UnaryTransformer[Vector, Vector, PolynomialExpansion] { /** - * The polynomial degree to expand, which should be larger than 1. + * The polynomial degree to expand, which should be >= 1. A value of 1 means no expansion. + * Default: 2 * @group param */ - val degree = new IntParam(this, "degree", "the polynomial degree to expand") + val degree = new IntParam(this, "degree", "the polynomial degree to expand (>= 1)", + ParamValidators.gt(1)) + setDefault(degree -> 2) /** @group getParam */ diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala index 447851ec034d6..a0e9ed32e0e4c 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StandardScaler.scala @@ -31,17 +31,19 @@ import org.apache.spark.sql.types.{StructField, StructType} * Params for [[StandardScaler]] and [[StandardScalerModel]]. */ private[feature] trait StandardScalerParams extends Params with HasInputCol with HasOutputCol { - + /** - * False by default. Centers the data with mean before scaling. + * Centers the data with mean before scaling. * It will build a dense output, so this does not work on sparse input * and will raise an exception. + * Default: false * @group param */ val withMean: BooleanParam = new BooleanParam(this, "withMean", "Center data with mean") /** - * True by default. Scales the data to unit standard deviation. + * Scales the data to unit standard deviation. + * Default: true * @group param */ val withStd: BooleanParam = new BooleanParam(this, "withStd", "Scale to unit standard deviation") @@ -56,7 +58,7 @@ private[feature] trait StandardScalerParams extends Params with HasInputCol with class StandardScaler extends Estimator[StandardScalerModel] with StandardScalerParams { setDefault(withMean -> false, withStd -> true) - + /** @group setParam */ def setInputCol(value: String): this.type = set(inputCol, value) diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala index 23956c512c8a6..9db3b29e10d69 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala @@ -23,10 +23,9 @@ import org.apache.spark.ml.{Estimator, Model} import org.apache.spark.ml.attribute.NominalAttribute import org.apache.spark.ml.param._ import org.apache.spark.ml.param.shared._ -import org.apache.spark.ml.util.SchemaUtils import org.apache.spark.sql.DataFrame import org.apache.spark.sql.functions._ -import org.apache.spark.sql.types.{StringType, StructType} +import org.apache.spark.sql.types.{NumericType, StringType, StructType} import org.apache.spark.util.collection.OpenHashMap /** @@ -37,7 +36,11 @@ private[feature] trait StringIndexerBase extends Params with HasInputCol with Ha /** Validates and transforms the input schema. */ protected def validateAndTransformSchema(schema: StructType, paramMap: ParamMap): StructType = { val map = extractParamMap(paramMap) - SchemaUtils.checkColumnType(schema, map(inputCol), StringType) + val inputColName = map(inputCol) + val inputDataType = schema(inputColName).dataType + require(inputDataType == StringType || inputDataType.isInstanceOf[NumericType], + s"The input column $inputColName must be either string type or numeric type, " + + s"but got $inputDataType.") val inputFields = schema.fields val outputColName = map(outputCol) require(inputFields.forall(_.name != outputColName), @@ -51,6 +54,7 @@ private[feature] trait StringIndexerBase extends Params with HasInputCol with Ha /** * :: AlphaComponent :: * A label indexer that maps a string column of labels to an ML column of label indices. + * If the input column is numeric, we cast it to string and index the string values. * The indices are in [0, numLabels), ordered by label frequencies. * So the most frequent label gets index 0. */ @@ -67,7 +71,9 @@ class StringIndexer extends Estimator[StringIndexerModel] with StringIndexerBase override def fit(dataset: DataFrame, paramMap: ParamMap): StringIndexerModel = { val map = extractParamMap(paramMap) - val counts = dataset.select(map(inputCol)).map(_.getString(0)).countByValue() + val counts = dataset.select(col(map(inputCol)).cast(StringType)) + .map(_.getString(0)) + .countByValue() val labels = counts.toSeq.sortBy(-_._2).map(_._1).toArray val model = new StringIndexerModel(this, map, labels) Params.inheritValues(map, this, model) @@ -119,7 +125,8 @@ class StringIndexerModel private[ml] ( val outputColName = map(outputCol) val metadata = NominalAttribute.defaultAttr .withName(outputColName).withValues(labels).toMetadata() - dataset.select(col("*"), indexer(dataset(map(inputCol))).as(outputColName, metadata)) + dataset.select(col("*"), + indexer(dataset(map(inputCol)).cast(StringType)).as(outputColName, metadata)) } override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = { diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala index 376a004858b4c..01752ba482d0c 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Tokenizer.scala @@ -19,7 +19,7 @@ package org.apache.spark.ml.feature import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml.UnaryTransformer -import org.apache.spark.ml.param.{ParamMap, IntParam, BooleanParam, Param} +import org.apache.spark.ml.param._ import org.apache.spark.sql.types.{DataType, StringType, ArrayType} /** @@ -43,20 +43,20 @@ class Tokenizer extends UnaryTransformer[String, Seq[String], Tokenizer] { /** * :: AlphaComponent :: * A regex based tokenizer that extracts tokens either by repeatedly matching the regex(default) - * or using it to split the text (set matching to false). Optional parameters also allow to fold - * the text to lowercase prior to it being tokenized and to filer tokens using a minimal length. + * or using it to split the text (set matching to false). Optional parameters also allow filtering + * tokens using a minimal length. * It returns an array of strings that can be empty. - * The default parameters are regex = "\\p{L}+|[^\\p{L}\\s]+", matching = true, - * lowercase = false, minTokenLength = 1 */ @AlphaComponent class RegexTokenizer extends UnaryTransformer[String, Seq[String], RegexTokenizer] { /** - * param for minimum token length, default is one to avoid returning empty strings + * Minimum token length, >= 0. + * Default: 1, to avoid returning empty strings * @group param */ - val minTokenLength: IntParam = new IntParam(this, "minLength", "minimum token length") + val minTokenLength: IntParam = new IntParam(this, "minLength", "minimum token length (>= 0)", + ParamValidators.gtEq(0)) /** @group setParam */ def setMinTokenLength(value: Int): this.type = set(minTokenLength, value) @@ -65,7 +65,8 @@ class RegexTokenizer extends UnaryTransformer[String, Seq[String], RegexTokenize def getMinTokenLength: Int = getOrDefault(minTokenLength) /** - * param sets regex as splitting on gaps (true) or matching tokens (false) + * Indicates whether regex splits on gaps (true) or matching tokens (false). + * Default: false * @group param */ val gaps: BooleanParam = new BooleanParam(this, "gaps", "Set regex to match gaps or tokens") @@ -77,7 +78,8 @@ class RegexTokenizer extends UnaryTransformer[String, Seq[String], RegexTokenize def getGaps: Boolean = getOrDefault(gaps) /** - * param sets regex pattern used by tokenizer + * Regex pattern used by tokenizer. + * Default: `"\\p{L}+|[^\\p{L}\\s]+"` * @group param */ val pattern: Param[String] = new Param(this, "pattern", "regex pattern used for tokenizing") diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala index 7b2a451ca5ee5..5e781a326d98c 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala @@ -25,9 +25,7 @@ import org.apache.spark.ml.Transformer import org.apache.spark.ml.param.ParamMap import org.apache.spark.ml.param.shared._ import org.apache.spark.mllib.linalg.{Vector, VectorUDT, Vectors} -import org.apache.spark.sql.{Column, DataFrame, Row} -import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute -import org.apache.spark.sql.catalyst.expressions.{Alias, Cast, CreateStruct} +import org.apache.spark.sql.{DataFrame, Row} import org.apache.spark.sql.functions._ import org.apache.spark.sql.types._ @@ -53,13 +51,12 @@ class VectorAssembler extends Transformer with HasInputCols with HasOutputCol { val inputColNames = map(inputCols) val args = inputColNames.map { c => schema(c).dataType match { - case DoubleType => UnresolvedAttribute(c) - case t if t.isInstanceOf[VectorUDT] => UnresolvedAttribute(c) - case _: NumericType | BooleanType => - Alias(Cast(UnresolvedAttribute(c), DoubleType), s"${c}_double_$uid")() + case DoubleType => dataset(c) + case _: VectorUDT => dataset(c) + case _: NumericType | BooleanType => dataset(c).cast(DoubleType).as(s"${c}_double_$uid") } } - dataset.select(col("*"), assembleFunc(new Column(CreateStruct(args))).as(map(outputCol))) + dataset.select(col("*"), assembleFunc(struct(args : _*)).as(map(outputCol))) } override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = { diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala index 452faa06e2021..ed833c63c7ef1 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorIndexer.scala @@ -22,7 +22,7 @@ import org.apache.spark.ml.util.SchemaUtils import org.apache.spark.ml.{Estimator, Model} import org.apache.spark.ml.attribute.{BinaryAttribute, NumericAttribute, NominalAttribute, Attribute, AttributeGroup} -import org.apache.spark.ml.param.{IntParam, ParamMap, Params} +import org.apache.spark.ml.param.{ParamValidators, IntParam, ParamMap, Params} import org.apache.spark.ml.param.shared._ import org.apache.spark.mllib.linalg.{SparseVector, DenseVector, Vector, VectorUDT} import org.apache.spark.sql.{Row, DataFrame} @@ -37,17 +37,19 @@ private[ml] trait VectorIndexerParams extends Params with HasInputCol with HasOu /** * Threshold for the number of values a categorical feature can take. * If a feature is found to have > maxCategories values, then it is declared continuous. + * Must be >= 2. * * (default = 20) */ val maxCategories = new IntParam(this, "maxCategories", - "Threshold for the number of values a categorical feature can take." + - " If a feature is found to have > maxCategories values, then it is declared continuous.") + "Threshold for the number of values a categorical feature can take (>= 2)." + + " If a feature is found to have > maxCategories values, then it is declared continuous.", + ParamValidators.gtEq(2)) + + setDefault(maxCategories -> 20) /** @group getParam */ def getMaxCategories: Int = getOrDefault(maxCategories) - - setDefault(maxCategories -> 20) } /** @@ -90,11 +92,7 @@ private[ml] trait VectorIndexerParams extends Params with HasInputCol with HasOu class VectorIndexer extends Estimator[VectorIndexerModel] with VectorIndexerParams { /** @group setParam */ - def setMaxCategories(value: Int): this.type = { - require(value > 1, - s"DatasetIndexer given maxCategories = value, but requires maxCategories > 1.") - set(maxCategories, value) - } + def setMaxCategories(value: Int): this.type = set(maxCategories, value) /** @group setParam */ def setInputCol(value: String): this.type = set(inputCol, value) @@ -233,6 +231,7 @@ private object VectorIndexer { * - Continuous features (columns) are left unchanged. * This also appends metadata to the output column, marking features as Numeric (continuous), * Nominal (categorical), or Binary (either continuous or categorical). + * Non-ML metadata is not carried over from the input to the output column. * * This maintains vector sparsity. * @@ -283,34 +282,40 @@ class VectorIndexerModel private[ml] ( // TODO: Check more carefully about whether this whole class will be included in a closure. + /** Per-vector transform function */ private val transformFunc: Vector => Vector = { - val sortedCategoricalFeatureIndices = categoryMaps.keys.toArray.sorted + val sortedCatFeatureIndices = categoryMaps.keys.toArray.sorted val localVectorMap = categoryMaps - val f: Vector => Vector = { - case dv: DenseVector => - val tmpv = dv.copy - localVectorMap.foreach { case (featureIndex: Int, categoryMap: Map[Double, Int]) => - tmpv.values(featureIndex) = categoryMap(tmpv(featureIndex)) - } - tmpv - case sv: SparseVector => - // We use the fact that categorical value 0 is always mapped to index 0. - val tmpv = sv.copy - var catFeatureIdx = 0 // index into sortedCategoricalFeatureIndices - var k = 0 // index into non-zero elements of sparse vector - while (catFeatureIdx < sortedCategoricalFeatureIndices.length && k < tmpv.indices.length) { - val featureIndex = sortedCategoricalFeatureIndices(catFeatureIdx) - if (featureIndex < tmpv.indices(k)) { - catFeatureIdx += 1 - } else if (featureIndex > tmpv.indices(k)) { - k += 1 - } else { - tmpv.values(k) = localVectorMap(featureIndex)(tmpv.values(k)) - catFeatureIdx += 1 - k += 1 + val localNumFeatures = numFeatures + val f: Vector => Vector = { (v: Vector) => + assert(v.size == localNumFeatures, "VectorIndexerModel expected vector of length" + + s" $numFeatures but found length ${v.size}") + v match { + case dv: DenseVector => + val tmpv = dv.copy + localVectorMap.foreach { case (featureIndex: Int, categoryMap: Map[Double, Int]) => + tmpv.values(featureIndex) = categoryMap(tmpv(featureIndex)) } - } - tmpv + tmpv + case sv: SparseVector => + // We use the fact that categorical value 0 is always mapped to index 0. + val tmpv = sv.copy + var catFeatureIdx = 0 // index into sortedCatFeatureIndices + var k = 0 // index into non-zero elements of sparse vector + while (catFeatureIdx < sortedCatFeatureIndices.length && k < tmpv.indices.length) { + val featureIndex = sortedCatFeatureIndices(catFeatureIdx) + if (featureIndex < tmpv.indices(k)) { + catFeatureIdx += 1 + } else if (featureIndex > tmpv.indices(k)) { + k += 1 + } else { + tmpv.values(k) = localVectorMap(featureIndex)(tmpv.values(k)) + catFeatureIdx += 1 + k += 1 + } + } + tmpv + } } f } @@ -326,13 +331,6 @@ class VectorIndexerModel private[ml] ( val map = extractParamMap(paramMap) val newField = prepOutputField(dataset.schema, map) val newCol = callUDF(transformFunc, new VectorUDT, dataset(map(inputCol))) - // For now, just check the first row of inputCol for vector length. - val firstRow = dataset.select(map(inputCol)).take(1) - if (firstRow.length != 0) { - val actualNumFeatures = firstRow(0).getAs[Vector](0).size - require(numFeatures == actualNumFeatures, "VectorIndexerModel expected vector of length" + - s" $numFeatures but found length $actualNumFeatures") - } dataset.withColumn(map(outputCol), newCol.as(map(outputCol), newField.metadata)) } @@ -345,6 +343,7 @@ class VectorIndexerModel private[ml] ( s"VectorIndexerModel requires output column parameter: $outputCol") SchemaUtils.checkColumnType(schema, map(inputCol), dataType) + // If the input metadata specifies numFeatures, compare with expected numFeatures. val origAttrGroup = AttributeGroup.fromStructField(schema(map(inputCol))) val origNumFeatures: Option[Int] = if (origAttrGroup.attributes.nonEmpty) { Some(origAttrGroup.attributes.get.length) @@ -364,7 +363,7 @@ class VectorIndexerModel private[ml] ( * Prepare the output column field, including per-feature metadata. * @param schema Input schema * @param map Parameter map (with this class' embedded parameter map folded in) - * @return Output column field + * @return Output column field. This field does not contain non-ML metadata. */ private def prepOutputField(schema: StructType, map: ParamMap): StructField = { val origAttrGroup = AttributeGroup.fromStructField(schema(map(inputCol))) @@ -391,6 +390,6 @@ class VectorIndexerModel private[ml] ( partialFeatureAttributes } val newAttributeGroup = new AttributeGroup(map(outputCol), featureAttributes) - newAttributeGroup.toStructField(schema(map(inputCol)).metadata) + newAttributeGroup.toStructField() } } diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala b/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala new file mode 100644 index 0000000000000..0163fa8bd8a5b --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Word2Vec.scala @@ -0,0 +1,185 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.feature + +import org.apache.spark.annotation.AlphaComponent +import org.apache.spark.ml.param._ +import org.apache.spark.ml.param.shared._ +import org.apache.spark.ml.util.SchemaUtils +import org.apache.spark.ml.{Estimator, Model} +import org.apache.spark.mllib.feature +import org.apache.spark.mllib.linalg.BLAS._ +import org.apache.spark.mllib.linalg.{VectorUDT, Vectors} +import org.apache.spark.sql.functions._ +import org.apache.spark.sql.types._ +import org.apache.spark.sql.{DataFrame, Row} + +/** + * Params for [[Word2Vec]] and [[Word2VecModel]]. + */ +private[feature] trait Word2VecBase extends Params + with HasInputCol with HasOutputCol with HasMaxIter with HasStepSize with HasSeed { + + /** + * The dimension of the code that you want to transform from words. + */ + final val vectorSize = new IntParam( + this, "vectorSize", "the dimension of codes after transforming from words") + setDefault(vectorSize -> 100) + + /** @group getParam */ + def getVectorSize: Int = getOrDefault(vectorSize) + + /** + * Number of partitions for sentences of words. + */ + final val numPartitions = new IntParam( + this, "numPartitions", "number of partitions for sentences of words") + setDefault(numPartitions -> 1) + + /** @group getParam */ + def getNumPartitions: Int = getOrDefault(numPartitions) + + /** + * The minimum number of times a token must appear to be included in the word2vec model's + * vocabulary. + */ + final val minCount = new IntParam(this, "minCount", "the minimum number of times a token must " + + "appear to be included in the word2vec model's vocabulary") + setDefault(minCount -> 5) + + /** @group getParam */ + def getMinCount: Int = getOrDefault(minCount) + + setDefault(stepSize -> 0.025) + setDefault(maxIter -> 1) + setDefault(seed -> 42L) + + /** + * Validate and transform the input schema. + */ + protected def validateAndTransformSchema(schema: StructType, paramMap: ParamMap): StructType = { + val map = extractParamMap(paramMap) + SchemaUtils.checkColumnType(schema, map(inputCol), new ArrayType(StringType, true)) + SchemaUtils.appendColumn(schema, map(outputCol), new VectorUDT) + } +} + +/** + * :: AlphaComponent :: + * Word2Vec trains a model of `Map(String, Vector)`, i.e. transforms a word into a code for further + * natural language processing or machine learning process. + */ +@AlphaComponent +final class Word2Vec extends Estimator[Word2VecModel] with Word2VecBase { + + /** @group setParam */ + def setInputCol(value: String): this.type = set(inputCol, value) + + /** @group setParam */ + def setOutputCol(value: String): this.type = set(outputCol, value) + + /** @group setParam */ + def setVectorSize(value: Int): this.type = set(vectorSize, value) + + /** @group setParam */ + def setStepSize(value: Double): this.type = set(stepSize, value) + + /** @group setParam */ + def setNumPartitions(value: Int): this.type = set(numPartitions, value) + + /** @group setParam */ + def setMaxIter(value: Int): this.type = set(maxIter, value) + + /** @group setParam */ + def setSeed(value: Long): this.type = set(seed, value) + + /** @group setParam */ + def setMinCount(value: Int): this.type = set(minCount, value) + + override def fit(dataset: DataFrame, paramMap: ParamMap): Word2VecModel = { + transformSchema(dataset.schema, paramMap, logging = true) + val map = extractParamMap(paramMap) + val input = dataset.select(map(inputCol)).map { case Row(v: Seq[String]) => v } + val wordVectors = new feature.Word2Vec() + .setLearningRate(map(stepSize)) + .setMinCount(map(minCount)) + .setNumIterations(map(maxIter)) + .setNumPartitions(map(numPartitions)) + .setSeed(map(seed)) + .setVectorSize(map(vectorSize)) + .fit(input) + val model = new Word2VecModel(this, map, wordVectors) + Params.inheritValues(map, this, model) + model + } + + override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = { + validateAndTransformSchema(schema, paramMap) + } +} + +/** + * :: AlphaComponent :: + * Model fitted by [[Word2Vec]]. + */ +@AlphaComponent +class Word2VecModel private[ml] ( + override val parent: Word2Vec, + override val fittingParamMap: ParamMap, + wordVectors: feature.Word2VecModel) + extends Model[Word2VecModel] with Word2VecBase { + + /** @group setParam */ + def setInputCol(value: String): this.type = set(inputCol, value) + + /** @group setParam */ + def setOutputCol(value: String): this.type = set(outputCol, value) + + /** + * Transform a sentence column to a vector column to represent the whole sentence. The transform + * is performed by averaging all word vectors it contains. + */ + override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = { + transformSchema(dataset.schema, paramMap, logging = true) + val map = extractParamMap(paramMap) + val bWordVectors = dataset.sqlContext.sparkContext.broadcast(wordVectors) + val word2Vec = udf { sentence: Seq[String] => + if (sentence.size == 0) { + Vectors.sparse(map(vectorSize), Array.empty[Int], Array.empty[Double]) + } else { + val cum = Vectors.zeros(map(vectorSize)) + val model = bWordVectors.value.getVectors + for (word <- sentence) { + if (model.contains(word)) { + axpy(1.0, bWordVectors.value.transform(word), cum) + } else { + // pass words which not belong to model + } + } + scal(1.0 / sentence.size, cum) + cum + } + } + dataset.withColumn(map(outputCol), word2Vec(col(map(inputCol)))) + } + + override def transformSchema(schema: StructType, paramMap: ParamMap): StructType = { + validateAndTransformSchema(schema, paramMap) + } +} diff --git a/mllib/src/main/scala/org/apache/spark/ml/impl/tree/treeParams.scala b/mllib/src/main/scala/org/apache/spark/ml/impl/tree/treeParams.scala index ab6281b9b2e34..fb770622e71f0 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/impl/tree/treeParams.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/impl/tree/treeParams.scala @@ -38,14 +38,15 @@ import org.apache.spark.mllib.tree.loss.{Loss => OldLoss} private[ml] trait DecisionTreeParams extends PredictorParams { /** - * Maximum depth of the tree. + * Maximum depth of the tree (>= 0). * E.g., depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes. * (default = 5) * @group param */ final val maxDepth: IntParam = - new IntParam(this, "maxDepth", "Maximum depth of the tree." + - " E.g., depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes.") + new IntParam(this, "maxDepth", "Maximum depth of the tree. (>= 0)" + + " E.g., depth 0 means 1 leaf node; depth 1 means 1 internal node + 2 leaf nodes.", + ParamValidators.gtEq(0)) /** * Maximum number of bins used for discretizing continuous features and for choosing how to split @@ -56,7 +57,7 @@ private[ml] trait DecisionTreeParams extends PredictorParams { */ final val maxBins: IntParam = new IntParam(this, "maxBins", "Max number of bins for" + " discretizing continuous features. Must be >=2 and >= number of categories for any" + - " categorical feature.") + " categorical feature.", ParamValidators.gtEq(2)) /** * Minimum number of instances each child must have after split. @@ -69,7 +70,7 @@ private[ml] trait DecisionTreeParams extends PredictorParams { final val minInstancesPerNode: IntParam = new IntParam(this, "minInstancesPerNode", "Minimum" + " number of instances each child must have after split. If a split causes the left or right" + " child to have fewer than minInstancesPerNode, the split will be discarded as invalid." + - " Should be >= 1.") + " Should be >= 1.", ParamValidators.gtEq(1)) /** * Minimum information gain for a split to be considered at a tree node. @@ -85,7 +86,8 @@ private[ml] trait DecisionTreeParams extends PredictorParams { * @group expertParam */ final val maxMemoryInMB: IntParam = new IntParam(this, "maxMemoryInMB", - "Maximum memory in MB allocated to histogram aggregation.") + "Maximum memory in MB allocated to histogram aggregation.", + ParamValidators.gtEq(0)) /** * If false, the algorithm will pass trees to executors to match instances with nodes. @@ -111,34 +113,26 @@ private[ml] trait DecisionTreeParams extends PredictorParams { final val checkpointInterval: IntParam = new IntParam(this, "checkpointInterval", "Specifies" + " how often to checkpoint the cached node IDs. E.g. 10 means that the cache will get" + " checkpointed every 10 iterations. This is only used if cacheNodeIds is true and if the" + - " checkpoint directory is set in the SparkContext. Must be >= 1.") + " checkpoint directory is set in the SparkContext. Must be >= 1.", + ParamValidators.gtEq(1)) setDefault(maxDepth -> 5, maxBins -> 32, minInstancesPerNode -> 1, minInfoGain -> 0.0, maxMemoryInMB -> 256, cacheNodeIds -> false, checkpointInterval -> 10) /** @group setParam */ - def setMaxDepth(value: Int): this.type = { - require(value >= 0, s"maxDepth parameter must be >= 0. Given bad value: $value") - set(maxDepth, value) - } + def setMaxDepth(value: Int): this.type = set(maxDepth, value) /** @group getParam */ final def getMaxDepth: Int = getOrDefault(maxDepth) /** @group setParam */ - def setMaxBins(value: Int): this.type = { - require(value >= 2, s"maxBins parameter must be >= 2. Given bad value: $value") - set(maxBins, value) - } + def setMaxBins(value: Int): this.type = set(maxBins, value) /** @group getParam */ final def getMaxBins: Int = getOrDefault(maxBins) /** @group setParam */ - def setMinInstancesPerNode(value: Int): this.type = { - require(value >= 1, s"minInstancesPerNode parameter must be >= 1. Given bad value: $value") - set(minInstancesPerNode, value) - } + def setMinInstancesPerNode(value: Int): this.type = set(minInstancesPerNode, value) /** @group getParam */ final def getMinInstancesPerNode: Int = getOrDefault(minInstancesPerNode) @@ -150,10 +144,7 @@ private[ml] trait DecisionTreeParams extends PredictorParams { final def getMinInfoGain: Double = getOrDefault(minInfoGain) /** @group expertSetParam */ - def setMaxMemoryInMB(value: Int): this.type = { - require(value > 0, s"maxMemoryInMB parameter must be > 0. Given bad value: $value") - set(maxMemoryInMB, value) - } + def setMaxMemoryInMB(value: Int): this.type = set(maxMemoryInMB, value) /** @group expertGetParam */ final def getMaxMemoryInMB: Int = getOrDefault(maxMemoryInMB) @@ -165,10 +156,7 @@ private[ml] trait DecisionTreeParams extends PredictorParams { final def getCacheNodeIds: Boolean = getOrDefault(cacheNodeIds) /** @group expertSetParam */ - def setCheckpointInterval(value: Int): this.type = { - require(value >= 1, s"checkpointInterval parameter must be >= 1. Given bad value: $value") - set(checkpointInterval, value) - } + def setCheckpointInterval(value: Int): this.type = set(checkpointInterval, value) /** @group expertGetParam */ final def getCheckpointInterval: Int = getOrDefault(checkpointInterval) @@ -209,21 +197,16 @@ private[ml] trait TreeClassifierParams extends Params { */ final val impurity: Param[String] = new Param[String](this, "impurity", "Criterion used for" + " information gain calculation (case-insensitive). Supported options:" + - s" ${TreeClassifierParams.supportedImpurities.mkString(", ")}") + s" ${TreeClassifierParams.supportedImpurities.mkString(", ")}", + (value: String) => TreeClassifierParams.supportedImpurities.contains(value.toLowerCase)) setDefault(impurity -> "gini") /** @group setParam */ - def setImpurity(value: String): this.type = { - val impurityStr = value.toLowerCase - require(TreeClassifierParams.supportedImpurities.contains(impurityStr), - s"Tree-based classifier was given unrecognized impurity: $value." + - s" Supported options: ${TreeClassifierParams.supportedImpurities.mkString(", ")}") - set(impurity, impurityStr) - } + def setImpurity(value: String): this.type = set(impurity, value) /** @group getParam */ - final def getImpurity: String = getOrDefault(impurity) + final def getImpurity: String = getOrDefault(impurity).toLowerCase /** Convert new impurity to old impurity. */ private[ml] def getOldImpurity: OldImpurity = { @@ -256,21 +239,16 @@ private[ml] trait TreeRegressorParams extends Params { */ final val impurity: Param[String] = new Param[String](this, "impurity", "Criterion used for" + " information gain calculation (case-insensitive). Supported options:" + - s" ${TreeRegressorParams.supportedImpurities.mkString(", ")}") + s" ${TreeRegressorParams.supportedImpurities.mkString(", ")}", + (value: String) => TreeRegressorParams.supportedImpurities.contains(value.toLowerCase)) setDefault(impurity -> "variance") /** @group setParam */ - def setImpurity(value: String): this.type = { - val impurityStr = value.toLowerCase - require(TreeRegressorParams.supportedImpurities.contains(impurityStr), - s"Tree-based regressor was given unrecognized impurity: $value." + - s" Supported options: ${TreeRegressorParams.supportedImpurities.mkString(", ")}") - set(impurity, impurityStr) - } + def setImpurity(value: String): this.type = set(impurity, value) /** @group getParam */ - final def getImpurity: String = getOrDefault(impurity) + final def getImpurity: String = getOrDefault(impurity).toLowerCase /** Convert new impurity to old impurity. */ private[ml] def getOldImpurity: OldImpurity = { @@ -299,21 +277,18 @@ private[ml] object TreeRegressorParams { private[ml] trait TreeEnsembleParams extends DecisionTreeParams with HasSeed { /** - * Fraction of the training data used for learning each decision tree. + * Fraction of the training data used for learning each decision tree, in range (0, 1]. * (default = 1.0) * @group param */ final val subsamplingRate: DoubleParam = new DoubleParam(this, "subsamplingRate", - "Fraction of the training data used for learning each decision tree.") + "Fraction of the training data used for learning each decision tree, in range (0, 1].", + ParamValidators.inRange(0, 1, lowerInclusive = false, upperInclusive = true)) setDefault(subsamplingRate -> 1.0) /** @group setParam */ - def setSubsamplingRate(value: Double): this.type = { - require(value > 0.0 && value <= 1.0, - s"Subsampling rate must be in range (0,1]. Bad rate: $value") - set(subsamplingRate, value) - } + def setSubsamplingRate(value: Double): this.type = set(subsamplingRate, value) /** @group getParam */ final def getSubsamplingRate: Double = getOrDefault(subsamplingRate) @@ -350,7 +325,8 @@ private[ml] trait RandomForestParams extends TreeEnsembleParams { * (default = 20) * @group param */ - final val numTrees: IntParam = new IntParam(this, "numTrees", "Number of trees to train (>= 1)") + final val numTrees: IntParam = new IntParam(this, "numTrees", "Number of trees to train (>= 1)", + ParamValidators.gtEq(1)) /** * The number of features to consider for splits at each tree node. @@ -378,30 +354,23 @@ private[ml] trait RandomForestParams extends TreeEnsembleParams { */ final val featureSubsetStrategy: Param[String] = new Param[String](this, "featureSubsetStrategy", "The number of features to consider for splits at each tree node." + - s" Supported options: ${RandomForestParams.supportedFeatureSubsetStrategies.mkString(", ")}") + s" Supported options: ${RandomForestParams.supportedFeatureSubsetStrategies.mkString(", ")}", + (value: String) => + RandomForestParams.supportedFeatureSubsetStrategies.contains(value.toLowerCase)) setDefault(numTrees -> 20, featureSubsetStrategy -> "auto") /** @group setParam */ - def setNumTrees(value: Int): this.type = { - require(value >= 1, s"Random Forest numTrees parameter cannot be $value; it must be >= 1.") - set(numTrees, value) - } + def setNumTrees(value: Int): this.type = set(numTrees, value) /** @group getParam */ final def getNumTrees: Int = getOrDefault(numTrees) /** @group setParam */ - def setFeatureSubsetStrategy(value: String): this.type = { - val strategyStr = value.toLowerCase - require(RandomForestParams.supportedFeatureSubsetStrategies.contains(strategyStr), - s"RandomForestParams was given unrecognized featureSubsetStrategy: $value. Supported" + - s" options: ${RandomForestParams.supportedFeatureSubsetStrategies.mkString(", ")}") - set(featureSubsetStrategy, strategyStr) - } + def setFeatureSubsetStrategy(value: String): this.type = set(featureSubsetStrategy, value) /** @group getParam */ - final def getFeatureSubsetStrategy: String = getOrDefault(featureSubsetStrategy) + final def getFeatureSubsetStrategy: String = getOrDefault(featureSubsetStrategy).toLowerCase } private[ml] object RandomForestParams { @@ -426,7 +395,8 @@ private[ml] trait GBTParams extends TreeEnsembleParams with HasMaxIter { * @group param */ final val stepSize: DoubleParam = new DoubleParam(this, "stepSize", "Step size (a.k.a." + - " learning rate) in interval (0, 1] for shrinking the contribution of each estimator") + " learning rate) in interval (0, 1] for shrinking the contribution of each estimator", + ParamValidators.inRange(0, 1, lowerInclusive = false, upperInclusive = true)) /* TODO: Add this doc when we add this param. SPARK-7132 * Threshold for stopping early when runWithValidation is used. @@ -442,17 +412,10 @@ private[ml] trait GBTParams extends TreeEnsembleParams with HasMaxIter { setDefault(maxIter -> 20, stepSize -> 0.1) /** @group setParam */ - def setMaxIter(value: Int): this.type = { - require(value >= 1, s"Gradient Boosting maxIter parameter cannot be $value; it must be >= 1.") - set(maxIter, value) - } + def setMaxIter(value: Int): this.type = set(maxIter, value) /** @group setParam */ - def setStepSize(value: Double): this.type = { - require(value > 0.0 && value <= 1.0, - s"GBT given invalid step size ($value). Value should be in (0,1].") - set(stepSize, value) - } + def setStepSize(value: Double): this.type = set(stepSize, value) /** @group getParam */ final def getStepSize: Double = getOrDefault(stepSize) diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala index ddc5907e7facd..df6360dce6013 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/param/params.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/param/params.scala @@ -24,7 +24,7 @@ import scala.annotation.varargs import scala.collection.mutable import org.apache.spark.annotation.{AlphaComponent, DeveloperApi} -import org.apache.spark.ml.Identifiable +import org.apache.spark.ml.util.Identifiable /** * :: AlphaComponent :: @@ -34,10 +34,35 @@ import org.apache.spark.ml.Identifiable * @param parent parent object * @param name param name * @param doc documentation + * @param isValid optional validation method which indicates if a value is valid. + * See [[ParamValidators]] for factory methods for common validation functions. * @tparam T param value type */ @AlphaComponent -class Param[T] (val parent: Params, val name: String, val doc: String) extends Serializable { +class Param[T] (val parent: Params, val name: String, val doc: String, val isValid: T => Boolean) + extends Serializable { + + def this(parent: Params, name: String, doc: String) = + this(parent, name, doc, ParamValidators.alwaysTrue[T]) + + /** + * Assert that the given value is valid for this parameter. + * + * Note: Parameter checks involving interactions between multiple parameters should be + * implemented in [[Params.validate()]]. Checks for input/output columns should be + * implemented in [[org.apache.spark.ml.PipelineStage.transformSchema()]]. + * + * DEVELOPERS: This method is only called by [[ParamPair]], which means that all parameters + * should be specified via [[ParamPair]]. + * + * @throws IllegalArgumentException if the value is invalid + */ + private[param] def validate(value: T): Unit = { + if (!isValid(value)) { + throw new IllegalArgumentException(s"$parent parameter $name given invalid value $value." + + s" Parameter description: $toString") + } + } /** * Creates a param pair with the given value (for Java). @@ -65,38 +90,129 @@ class Param[T] (val parent: Params, val name: String, val doc: String) extends S } } +/** + * Factory methods for common validation functions for [[Param.isValid]]. + * The numerical methods only support Int, Long, Float, and Double. + */ +object ParamValidators { + + /** (private[param]) Default validation always return true */ + private[param] def alwaysTrue[T]: T => Boolean = (_: T) => true + + /** + * Private method for checking numerical types and converting to Double. + * This is mainly for the sake of compilation; type checks are really handled + * by [[Params]] setters and the [[ParamPair]] constructor. + */ + private def getDouble[T](value: T): Double = value match { + case x: Int => x.toDouble + case x: Long => x.toDouble + case x: Float => x.toDouble + case x: Double => x.toDouble + case _ => + // The type should be checked before this is ever called. + throw new IllegalArgumentException("Numerical Param validation failed because" + + s" of unexpected input type: ${value.getClass}") + } + + /** Check if value > lowerBound */ + def gt[T](lowerBound: Double): T => Boolean = { (value: T) => + getDouble(value) > lowerBound + } + + /** Check if value >= lowerBound */ + def gtEq[T](lowerBound: Double): T => Boolean = { (value: T) => + getDouble(value) >= lowerBound + } + + /** Check if value < upperBound */ + def lt[T](upperBound: Double): T => Boolean = { (value: T) => + getDouble(value) < upperBound + } + + /** Check if value <= upperBound */ + def ltEq[T](upperBound: Double): T => Boolean = { (value: T) => + getDouble(value) <= upperBound + } + + /** + * Check for value in range lowerBound to upperBound. + * @param lowerInclusive If true, check for value >= lowerBound. + * If false, check for value > lowerBound. + * @param upperInclusive If true, check for value <= upperBound. + * If false, check for value < upperBound. + */ + def inRange[T]( + lowerBound: Double, + upperBound: Double, + lowerInclusive: Boolean, + upperInclusive: Boolean): T => Boolean = { (value: T) => + val x: Double = getDouble(value) + val lowerValid = if (lowerInclusive) x >= lowerBound else x > lowerBound + val upperValid = if (upperInclusive) x <= upperBound else x < upperBound + lowerValid && upperValid + } + + /** Version of [[inRange()]] which uses inclusive be default: [lowerBound, upperBound] */ + def inRange[T](lowerBound: Double, upperBound: Double): T => Boolean = { + inRange[T](lowerBound, upperBound, lowerInclusive = true, upperInclusive = true) + } + + /** Check for value in an allowed set of values. */ + def inArray[T](allowed: Array[T]): T => Boolean = { (value: T) => + allowed.contains(value) + } + + /** Check for value in an allowed set of values. */ + def inArray[T](allowed: java.util.List[T]): T => Boolean = { (value: T) => + allowed.contains(value) + } +} + // specialize primitive-typed params because Java doesn't recognize scala.Double, scala.Int, ... /** Specialized version of [[Param[Double]]] for Java. */ -class DoubleParam(parent: Params, name: String, doc: String) - extends Param[Double](parent, name, doc) { +class DoubleParam(parent: Params, name: String, doc: String, isValid: Double => Boolean) + extends Param[Double](parent, name, doc, isValid) { + + def this(parent: Params, name: String, doc: String) = + this(parent, name, doc, ParamValidators.alwaysTrue) override def w(value: Double): ParamPair[Double] = super.w(value) } /** Specialized version of [[Param[Int]]] for Java. */ -class IntParam(parent: Params, name: String, doc: String) - extends Param[Int](parent, name, doc) { +class IntParam(parent: Params, name: String, doc: String, isValid: Int => Boolean) + extends Param[Int](parent, name, doc, isValid) { + + def this(parent: Params, name: String, doc: String) = + this(parent, name, doc, ParamValidators.alwaysTrue) override def w(value: Int): ParamPair[Int] = super.w(value) } /** Specialized version of [[Param[Float]]] for Java. */ -class FloatParam(parent: Params, name: String, doc: String) - extends Param[Float](parent, name, doc) { +class FloatParam(parent: Params, name: String, doc: String, isValid: Float => Boolean) + extends Param[Float](parent, name, doc, isValid) { + + def this(parent: Params, name: String, doc: String) = + this(parent, name, doc, ParamValidators.alwaysTrue) override def w(value: Float): ParamPair[Float] = super.w(value) } /** Specialized version of [[Param[Long]]] for Java. */ -class LongParam(parent: Params, name: String, doc: String) - extends Param[Long](parent, name, doc) { +class LongParam(parent: Params, name: String, doc: String, isValid: Long => Boolean) + extends Param[Long](parent, name, doc, isValid) { + + def this(parent: Params, name: String, doc: String) = + this(parent, name, doc, ParamValidators.alwaysTrue) override def w(value: Long): ParamPair[Long] = super.w(value) } /** Specialized version of [[Param[Boolean]]] for Java. */ -class BooleanParam(parent: Params, name: String, doc: String) +class BooleanParam(parent: Params, name: String, doc: String) // No need for isValid extends Param[Boolean](parent, name, doc) { override def w(value: Boolean): ParamPair[Boolean] = super.w(value) @@ -105,7 +221,11 @@ class BooleanParam(parent: Params, name: String, doc: String) /** * A param amd its value. */ -case class ParamPair[T](param: Param[T], value: T) +case class ParamPair[T](param: Param[T], value: T) { + // This is *the* place Param.validate is called. Whenever a parameter is specified, we should + // always construct a ParamPair so that validate is called. + param.validate(value) +} /** * :: AlphaComponent :: @@ -132,12 +252,22 @@ trait Params extends Identifiable with Serializable { /** * Validates parameter values stored internally plus the input parameter map. * Raises an exception if any parameter is invalid. + * + * This only needs to check for interactions between parameters. + * Parameter value checks which do not depend on other parameters are handled by + * [[Param.validate()]]. This method does not handle input/output column parameters; + * those are checked during schema validation. */ - def validate(paramMap: ParamMap): Unit = {} + def validate(paramMap: ParamMap): Unit = { } /** * Validates parameter values stored internally. * Raise an exception if any parameter value is invalid. + * + * This only needs to check for interactions between parameters. + * Parameter value checks which do not depend on other parameters are handled by + * [[Param.validate()]]. This method does not handle input/output column parameters; + * those are checked during schema validation. */ def validate(): Unit = validate(ParamMap.empty) @@ -221,6 +351,10 @@ trait Params extends Identifiable with Serializable { /** * Sets default values for a list of params. + * + * Note: Java developers should use the single-parameter [[setDefault()]]. + * Annotating this with varargs causes compilation failures. + * * @param paramPairs a list of param pairs that specify params and their default values to set * respectively. Make sure that the params are initialized before this method * gets called. @@ -305,6 +439,14 @@ private[spark] object Params { } } +/** + * Java-friendly wrapper for [[Params]]. + * Java developers who need to extend [[Params]] should use this class instead. + * If you need to extend a abstract class which already extends [[Params]], then that abstract + * class should be Java-friendly as well. + */ +abstract class JavaParams extends Params + /** * :: AlphaComponent :: * A param to value map. @@ -313,6 +455,12 @@ private[spark] object Params { final class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) extends Serializable { + /* DEVELOPERS: About validating parameter values + * This and ParamPair are the only two collections of parameters. + * This class should always create ParamPairs when + * specifying new parameter values. ParamPair will then call Param.validate(). + */ + /** * Creates an empty param map. */ @@ -321,10 +469,7 @@ final class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) /** * Puts a (param, value) pair (overwrites if the input param exists). */ - def put[T](param: Param[T], value: T): this.type = { - map(param.asInstanceOf[Param[Any]]) = value - this - } + def put[T](param: Param[T], value: T): this.type = put(ParamPair(param, value)) /** * Puts a list of param pairs (overwrites if the input params exists). @@ -332,7 +477,7 @@ final class ParamMap private[ml] (private val map: mutable.Map[Param[Any], Any]) @varargs def put(paramPairs: ParamPair[_]*): this.type = { paramPairs.foreach { p => - put(p.param.asInstanceOf[Param[Any]], p.value) + map(p.param.asInstanceOf[Param[Any]]) = p.value } this } diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala index 3f7e8f5a0b22c..7da4bb4b4bf25 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala @@ -21,6 +21,8 @@ import java.io.PrintWriter import scala.reflect.ClassTag +import org.apache.spark.ml.param.ParamValidators + /** * Code generator for shared params (sharedParams.scala). Run under the Spark folder with * {{{ @@ -31,8 +33,10 @@ private[shared] object SharedParamsCodeGen { def main(args: Array[String]): Unit = { val params = Seq( - ParamDesc[Double]("regParam", "regularization parameter"), - ParamDesc[Int]("maxIter", "max number of iterations"), + ParamDesc[Double]("regParam", "regularization parameter (>= 0)", + isValid = "ParamValidators.gtEq(0)"), + ParamDesc[Int]("maxIter", "max number of iterations (>= 0)", + isValid = "ParamValidators.gtEq(0)"), ParamDesc[String]("featuresCol", "features column name", Some("\"features\"")), ParamDesc[String]("labelCol", "label column name", Some("\"label\"")), ParamDesc[String]("predictionCol", "prediction column name", Some("\"prediction\"")), @@ -40,15 +44,21 @@ private[shared] object SharedParamsCodeGen { Some("\"rawPrediction\"")), ParamDesc[String]("probabilityCol", "column name for predicted class conditional probabilities", Some("\"probability\"")), - ParamDesc[Double]("threshold", "threshold in binary classification prediction"), + ParamDesc[Double]("threshold", + "threshold in binary classification prediction, in range [0, 1]", + isValid = "ParamValidators.inRange(0, 1)"), ParamDesc[String]("inputCol", "input column name"), ParamDesc[Array[String]]("inputCols", "input column names"), ParamDesc[String]("outputCol", "output column name"), - ParamDesc[Int]("checkpointInterval", "checkpoint interval"), + ParamDesc[Int]("checkpointInterval", "checkpoint interval (>= 1)", + isValid = "ParamValidators.gtEq(1)"), ParamDesc[Boolean]("fitIntercept", "whether to fit an intercept term", Some("true")), ParamDesc[Long]("seed", "random seed", Some("Utils.random.nextLong()")), - ParamDesc[Double]("elasticNetParam", "the ElasticNet mixing parameter"), - ParamDesc[Double]("tol", "the convergence tolerance for iterative algorithms")) + ParamDesc[Double]("elasticNetParam", "the ElasticNet mixing parameter, in range [0, 1]." + + " For alpha = 0, the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.", + isValid = "ParamValidators.inRange(0, 1)"), + ParamDesc[Double]("tol", "the convergence tolerance for iterative algorithms"), + ParamDesc[Double]("stepSize", "Step size to be used for each iteration of optimization.")) val code = genSharedParams(params) val file = "src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala" @@ -61,7 +71,8 @@ private[shared] object SharedParamsCodeGen { private case class ParamDesc[T: ClassTag]( name: String, doc: String, - defaultValueStr: Option[String] = None) { + defaultValueStr: Option[String] = None, + isValid: String = "") { require(name.matches("[a-z][a-zA-Z0-9]*"), s"Param name $name is invalid.") require(doc.nonEmpty) // TODO: more rigorous on doc @@ -112,20 +123,23 @@ private[shared] object SharedParamsCodeGen { | setDefault($name, $v) |""".stripMargin }.getOrElse("") + val isValid = if (param.isValid != "") { + ", " + param.isValid + } else { + "" + } s""" |/** - | * :: DeveloperApi :: - | * Trait for shared param $name$defaultValueDoc. + | * (private[ml]) Trait for shared param $name$defaultValueDoc. | */ - |@DeveloperApi - |trait Has$Name extends Params { + |private[ml] trait Has$Name extends Params { | | /** | * Param for $doc. | * @group param | */ - | final val $name: $Param = new $Param(this, "$name", "$doc") + | final val $name: $Param = new $Param(this, "$name", "$doc"$isValid) |$setDefault | /** @group getParam */ | final def get$Name: $T = getOrDefault($name) diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala index 7d2c76d6c62c8..e1549f46a68d4 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala @@ -26,45 +26,39 @@ import org.apache.spark.util.Utils // scalastyle:off /** - * :: DeveloperApi :: - * Trait for shared param regParam. + * (private[ml]) Trait for shared param regParam. */ -@DeveloperApi -trait HasRegParam extends Params { +private[ml] trait HasRegParam extends Params { /** - * Param for regularization parameter. + * Param for regularization parameter (>= 0). * @group param */ - final val regParam: DoubleParam = new DoubleParam(this, "regParam", "regularization parameter") + final val regParam: DoubleParam = new DoubleParam(this, "regParam", "regularization parameter (>= 0)", ParamValidators.gtEq(0)) /** @group getParam */ final def getRegParam: Double = getOrDefault(regParam) } /** - * :: DeveloperApi :: - * Trait for shared param maxIter. + * (private[ml]) Trait for shared param maxIter. */ -@DeveloperApi -trait HasMaxIter extends Params { +private[ml] trait HasMaxIter extends Params { /** - * Param for max number of iterations. + * Param for max number of iterations (>= 0). * @group param */ - final val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations") + final val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations (>= 0)", ParamValidators.gtEq(0)) /** @group getParam */ final def getMaxIter: Int = getOrDefault(maxIter) } /** - * :: DeveloperApi :: - * Trait for shared param featuresCol (default: "features"). + * (private[ml]) Trait for shared param featuresCol (default: "features"). */ -@DeveloperApi -trait HasFeaturesCol extends Params { +private[ml] trait HasFeaturesCol extends Params { /** * Param for features column name. @@ -79,11 +73,9 @@ trait HasFeaturesCol extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param labelCol (default: "label"). + * (private[ml]) Trait for shared param labelCol (default: "label"). */ -@DeveloperApi -trait HasLabelCol extends Params { +private[ml] trait HasLabelCol extends Params { /** * Param for label column name. @@ -98,11 +90,9 @@ trait HasLabelCol extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param predictionCol (default: "prediction"). + * (private[ml]) Trait for shared param predictionCol (default: "prediction"). */ -@DeveloperApi -trait HasPredictionCol extends Params { +private[ml] trait HasPredictionCol extends Params { /** * Param for prediction column name. @@ -117,11 +107,9 @@ trait HasPredictionCol extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param rawPredictionCol (default: "rawPrediction"). + * (private[ml]) Trait for shared param rawPredictionCol (default: "rawPrediction"). */ -@DeveloperApi -trait HasRawPredictionCol extends Params { +private[ml] trait HasRawPredictionCol extends Params { /** * Param for raw prediction (a.k.a. confidence) column name. @@ -136,11 +124,9 @@ trait HasRawPredictionCol extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param probabilityCol (default: "probability"). + * (private[ml]) Trait for shared param probabilityCol (default: "probability"). */ -@DeveloperApi -trait HasProbabilityCol extends Params { +private[ml] trait HasProbabilityCol extends Params { /** * Param for column name for predicted class conditional probabilities. @@ -155,28 +141,24 @@ trait HasProbabilityCol extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param threshold. + * (private[ml]) Trait for shared param threshold. */ -@DeveloperApi -trait HasThreshold extends Params { +private[ml] trait HasThreshold extends Params { /** - * Param for threshold in binary classification prediction. + * Param for threshold in binary classification prediction, in range [0, 1]. * @group param */ - final val threshold: DoubleParam = new DoubleParam(this, "threshold", "threshold in binary classification prediction") + final val threshold: DoubleParam = new DoubleParam(this, "threshold", "threshold in binary classification prediction, in range [0, 1]", ParamValidators.inRange(0, 1)) /** @group getParam */ final def getThreshold: Double = getOrDefault(threshold) } /** - * :: DeveloperApi :: - * Trait for shared param inputCol. + * (private[ml]) Trait for shared param inputCol. */ -@DeveloperApi -trait HasInputCol extends Params { +private[ml] trait HasInputCol extends Params { /** * Param for input column name. @@ -189,11 +171,9 @@ trait HasInputCol extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param inputCols. + * (private[ml]) Trait for shared param inputCols. */ -@DeveloperApi -trait HasInputCols extends Params { +private[ml] trait HasInputCols extends Params { /** * Param for input column names. @@ -206,11 +186,9 @@ trait HasInputCols extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param outputCol. + * (private[ml]) Trait for shared param outputCol. */ -@DeveloperApi -trait HasOutputCol extends Params { +private[ml] trait HasOutputCol extends Params { /** * Param for output column name. @@ -223,28 +201,24 @@ trait HasOutputCol extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param checkpointInterval. + * (private[ml]) Trait for shared param checkpointInterval. */ -@DeveloperApi -trait HasCheckpointInterval extends Params { +private[ml] trait HasCheckpointInterval extends Params { /** - * Param for checkpoint interval. + * Param for checkpoint interval (>= 1). * @group param */ - final val checkpointInterval: IntParam = new IntParam(this, "checkpointInterval", "checkpoint interval") + final val checkpointInterval: IntParam = new IntParam(this, "checkpointInterval", "checkpoint interval (>= 1)", ParamValidators.gtEq(1)) /** @group getParam */ final def getCheckpointInterval: Int = getOrDefault(checkpointInterval) } /** - * :: DeveloperApi :: - * Trait for shared param fitIntercept (default: true). + * (private[ml]) Trait for shared param fitIntercept (default: true). */ -@DeveloperApi -trait HasFitIntercept extends Params { +private[ml] trait HasFitIntercept extends Params { /** * Param for whether to fit an intercept term. @@ -259,11 +233,9 @@ trait HasFitIntercept extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param seed (default: Utils.random.nextLong()). + * (private[ml]) Trait for shared param seed (default: Utils.random.nextLong()). */ -@DeveloperApi -trait HasSeed extends Params { +private[ml] trait HasSeed extends Params { /** * Param for random seed. @@ -278,28 +250,24 @@ trait HasSeed extends Params { } /** - * :: DeveloperApi :: - * Trait for shared param elasticNetParam. + * (private[ml]) Trait for shared param elasticNetParam. */ -@DeveloperApi -trait HasElasticNetParam extends Params { +private[ml] trait HasElasticNetParam extends Params { /** - * Param for the ElasticNet mixing parameter. + * Param for the ElasticNet mixing parameter, in range [0, 1]. For alpha = 0, the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.. * @group param */ - final val elasticNetParam: DoubleParam = new DoubleParam(this, "elasticNetParam", "the ElasticNet mixing parameter") + final val elasticNetParam: DoubleParam = new DoubleParam(this, "elasticNetParam", "the ElasticNet mixing parameter, in range [0, 1]. For alpha = 0, the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.", ParamValidators.inRange(0, 1)) /** @group getParam */ final def getElasticNetParam: Double = getOrDefault(elasticNetParam) } /** - * :: DeveloperApi :: - * Trait for shared param tol. + * (private[ml]) Trait for shared param tol. */ -@DeveloperApi -trait HasTol extends Params { +private[ml] trait HasTol extends Params { /** * Param for the convergence tolerance for iterative algorithms. @@ -310,4 +278,19 @@ trait HasTol extends Params { /** @group getParam */ final def getTol: Double = getOrDefault(tol) } + +/** + * (private[ml]) Trait for shared param stepSize. + */ +private[ml] trait HasStepSize extends Params { + + /** + * Param for Step size to be used for each iteration of optimization.. + * @group param + */ + final val stepSize: DoubleParam = new DoubleParam(this, "stepSize", "Step size to be used for each iteration of optimization.") + + /** @group getParam */ + final def getStepSize: Double = getOrDefault(stepSize) +} // scalastyle:on diff --git a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala index bd793beba35b6..f9f2b2764ddb1 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala @@ -52,35 +52,40 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR with HasPredictionCol with HasCheckpointInterval { /** - * Param for rank of the matrix factorization. + * Param for rank of the matrix factorization (>= 1). + * Default: 10 * @group param */ - val rank = new IntParam(this, "rank", "rank of the factorization") + val rank = new IntParam(this, "rank", "rank of the factorization", ParamValidators.gtEq(1)) /** @group getParam */ def getRank: Int = getOrDefault(rank) /** - * Param for number of user blocks. + * Param for number of user blocks (>= 1). + * Default: 10 * @group param */ - val numUserBlocks = new IntParam(this, "numUserBlocks", "number of user blocks") + val numUserBlocks = new IntParam(this, "numUserBlocks", "number of user blocks", + ParamValidators.gtEq(1)) /** @group getParam */ def getNumUserBlocks: Int = getOrDefault(numUserBlocks) /** - * Param for number of item blocks. + * Param for number of item blocks (>= 1). + * Default: 10 * @group param */ - val numItemBlocks = - new IntParam(this, "numItemBlocks", "number of item blocks") + val numItemBlocks = new IntParam(this, "numItemBlocks", "number of item blocks", + ParamValidators.gtEq(1)) /** @group getParam */ def getNumItemBlocks: Int = getOrDefault(numItemBlocks) /** * Param to decide whether to use implicit preference. + * Default: false * @group param */ val implicitPrefs = new BooleanParam(this, "implicitPrefs", "whether to use implicit preference") @@ -89,16 +94,19 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR def getImplicitPrefs: Boolean = getOrDefault(implicitPrefs) /** - * Param for the alpha parameter in the implicit preference formulation. + * Param for the alpha parameter in the implicit preference formulation (>= 0). + * Default: 1.0 * @group param */ - val alpha = new DoubleParam(this, "alpha", "alpha for implicit preference") + val alpha = new DoubleParam(this, "alpha", "alpha for implicit preference", + ParamValidators.gtEq(0)) /** @group getParam */ def getAlpha: Double = getOrDefault(alpha) /** * Param for the column name for user ids. + * Default: "user" * @group param */ val userCol = new Param[String](this, "userCol", "column name for user ids") @@ -108,6 +116,7 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR /** * Param for the column name for item ids. + * Default: "item" * @group param */ val itemCol = new Param[String](this, "itemCol", "column name for item ids") @@ -117,6 +126,7 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR /** * Param for the column name for ratings. + * Default: "rating" * @group param */ val ratingCol = new Param[String](this, "ratingCol", "column name for ratings") @@ -126,6 +136,7 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR /** * Param for whether to apply nonnegativity constraints. + * Default: false * @group param */ val nonnegative = new BooleanParam( @@ -136,7 +147,7 @@ private[recommendation] trait ALSParams extends Params with HasMaxIter with HasR setDefault(rank -> 10, maxIter -> 10, regParam -> 0.1, numUserBlocks -> 10, numItemBlocks -> 10, implicitPrefs -> false, alpha -> 1.0, userCol -> "user", itemCol -> "item", - ratingCol -> "rating", nonnegative -> false) + ratingCol -> "rating", nonnegative -> false, checkpointInterval -> 10) /** * Validates and transforms the input schema. @@ -281,10 +292,6 @@ class ALS extends Estimator[ALSModel] with ALSParams { this } - setMaxIter(20) - setRegParam(1.0) - setCheckpointInterval(10) - override def fit(dataset: DataFrame, paramMap: ParamMap): ALSModel = { val map = extractParamMap(paramMap) val ratings = dataset diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala index c784cf39ed31a..76c98376930c5 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala @@ -102,21 +102,16 @@ final class GBTRegressor */ val lossType: Param[String] = new Param[String](this, "lossType", "Loss function which GBT" + " tries to minimize (case-insensitive). Supported options:" + - s" ${GBTRegressor.supportedLossTypes.mkString(", ")}") + s" ${GBTRegressor.supportedLossTypes.mkString(", ")}", + (value: String) => GBTRegressor.supportedLossTypes.contains(value.toLowerCase)) setDefault(lossType -> "squared") /** @group setParam */ - def setLossType(value: String): this.type = { - val lossStr = value.toLowerCase - require(GBTRegressor.supportedLossTypes.contains(lossStr), "GBTRegressor was given bad loss" + - s" type: $value. Supported options: ${GBTRegressor.supportedLossTypes.mkString(", ")}") - set(lossType, lossStr) - this - } + def setLossType(value: String): this.type = set(lossType, value) /** @group getParam */ - def getLossType: String = getOrDefault(lossType) + def getLossType: String = getOrDefault(lossType).toLowerCase /** (private[ml]) Convert new loss to old loss. */ override private[ml] def getOldLossType: OldLoss = { diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala index f92c6816eb54c..0b81c48466be9 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala @@ -25,7 +25,7 @@ import breeze.optimize.{CachedDiffFunction, DiffFunction} import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml.param.{Params, ParamMap} -import org.apache.spark.ml.param.shared.{HasElasticNetParam, HasMaxIter, HasRegParam, HasTol} +import org.apache.spark.ml.param.shared.{HasTol, HasElasticNetParam, HasMaxIter, HasRegParam} import org.apache.spark.mllib.stat.MultivariateOnlineSummarizer import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.linalg.BLAS._ @@ -34,6 +34,7 @@ import org.apache.spark.rdd.RDD import org.apache.spark.sql.DataFrame import org.apache.spark.storage.StorageLevel import org.apache.spark.util.StatCounter +import org.apache.spark.Logging /** * Params for linear regression. @@ -45,10 +46,20 @@ private[regression] trait LinearRegressionParams extends RegressorParams * :: AlphaComponent :: * * Linear regression. + * + * The learning objective is to minimize the squared error, with regularization. + * The specific squared error loss function used is: + * L = 1/2n ||A weights - y||^2^ + * + * This support multiple types of regularization: + * - none (a.k.a. ordinary least squares) + * - L2 (ridge regression) + * - L1 (Lasso) + * - L2 + L1 (elastic net) */ @AlphaComponent class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegressionModel] - with LinearRegressionParams { + with LinearRegressionParams with Logging { /** * Set the regularization parameter. @@ -91,9 +102,7 @@ class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegress case LabeledPoint(label: Double, features: Vector) => (label, features) } val handlePersistence = dataset.rdd.getStorageLevel == StorageLevel.NONE - if (handlePersistence) { - instances.persist(StorageLevel.MEMORY_AND_DISK) - } + if (handlePersistence) instances.persist(StorageLevel.MEMORY_AND_DISK) val (summarizer, statCounter) = instances.treeAggregate( (new MultivariateOnlineSummarizer, new StatCounter))( { @@ -110,6 +119,15 @@ class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegress val yMean = statCounter.mean val yStd = math.sqrt(statCounter.variance) + // If the yStd is zero, then the intercept is yMean with zero weights; + // as a result, training is not needed. + if (yStd == 0.0) { + logWarning(s"The standard deviation of the label is zero, so the weights will be zeros " + + s"and the intercept will be the mean of the label; as a result, training is not needed.") + if (handlePersistence) instances.unpersist() + return new LinearRegressionModel(this, paramMap, Vectors.sparse(numFeatures, Seq()), yMean) + } + val featuresMean = summarizer.mean.toArray val featuresStd = summarizer.variance.toArray.map(math.sqrt) @@ -141,7 +159,6 @@ class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegress } lossHistory += state.value - // TODO: Based on the sparsity of weights, we may convert the weights to the sparse vector. // The weights are trained in the scaled space; we're converting them back to // the original space. val weights = { @@ -158,11 +175,10 @@ class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegress // converged. See the following discussion for detail. // http://stats.stackexchange.com/questions/13617/how-is-the-intercept-computed-in-glmnet val intercept = yMean - dot(weights, Vectors.dense(featuresMean)) + if (handlePersistence) instances.unpersist() - if (handlePersistence) { - instances.unpersist() - } - new LinearRegressionModel(this, paramMap, weights, intercept) + // TODO: Converts to sparse format based on the storage, but may base on the scoring speed. + new LinearRegressionModel(this, paramMap, weights.compressed, intercept) } } @@ -198,15 +214,84 @@ class LinearRegressionModel private[ml] ( * Two LeastSquaresAggregator can be merged together to have a summary of loss and gradient of * the corresponding joint dataset. * - - * * Compute gradient and loss for a Least-squared loss function, as used in linear regression. - * This is correct for the averaged least squares loss function (mean squared error) - * L = 1/2n ||A weights-y||^2 - * See also the documentation for the precise formulation. + * For improving the convergence rate during the optimization process, and also preventing against + * features with very large variances exerting an overly large influence during model training, + * package like R's GLMNET performs the scaling to unit variance and removing the mean to reduce + * the condition number, and then trains the model in scaled space but returns the weights in + * the original scale. See page 9 in http://cran.r-project.org/web/packages/glmnet/glmnet.pdf + * + * However, we don't want to apply the `StandardScaler` on the training dataset, and then cache + * the standardized dataset since it will create a lot of overhead. As a result, we perform the + * scaling implicitly when we compute the objective function. The following is the mathematical + * derivation. + * + * Note that we don't deal with intercept by adding bias here, because the intercept + * can be computed using closed form after the coefficients are converged. + * See this discussion for detail. + * http://stats.stackexchange.com/questions/13617/how-is-the-intercept-computed-in-glmnet + * + * The objective function in the scaled space is given by + * {{{ + * L = 1/2n ||\sum_i w_i(x_i - \bar{x_i}) / \hat{x_i} - (y - \bar{y}) / \hat{y}||^2, + * }}} + * where \bar{x_i} is the mean of x_i, \hat{x_i} is the standard deviation of x_i, + * \bar{y} is the mean of label, and \hat{y} is the standard deviation of label. * - * @param weights weights/coefficients corresponding to features + * This can be rewritten as + * {{{ + * L = 1/2n ||\sum_i (w_i/\hat{x_i})x_i - \sum_i (w_i/\hat{x_i})\bar{x_i} - y / \hat{y} + * + \bar{y} / \hat{y}||^2 + * = 1/2n ||\sum_i w_i^\prime x_i - y / \hat{y} + offset||^2 = 1/2n diff^2 + * }}} + * where w_i^\prime is the effective weights defined by w_i/\hat{x_i}, offset is + * {{{ + * - \sum_i (w_i/\hat{x_i})\bar{x_i} + \bar{y} / \hat{y}. + * }}}, and diff is + * {{{ + * \sum_i w_i^\prime x_i - y / \hat{y} + offset + * }}} * - * @param updater Updater to be used to update weights after every iteration. + * Note that the effective weights and offset don't depend on training dataset, + * so they can be precomputed. + * + * Now, the first derivative of the objective function in scaled space is + * {{{ + * \frac{\partial L}{\partial\w_i} = diff/N (x_i - \bar{x_i}) / \hat{x_i} + * }}} + * However, ($x_i - \bar{x_i}$) will densify the computation, so it's not + * an ideal formula when the training dataset is sparse format. + * + * This can be addressed by adding the dense \bar{x_i} / \har{x_i} terms + * in the end by keeping the sum of diff. The first derivative of total + * objective function from all the samples is + * {{{ + * \frac{\partial L}{\partial\w_i} = + * 1/N \sum_j diff_j (x_{ij} - \bar{x_i}) / \hat{x_i} + * = 1/N ((\sum_j diff_j x_{ij} / \hat{x_i}) - diffSum \bar{x_i}) / \hat{x_i}) + * = 1/N ((\sum_j diff_j x_{ij} / \hat{x_i}) + correction_i) + * }}}, + * where correction_i = - diffSum \bar{x_i}) / \hat{x_i} + * + * A simple math can show that diffSum is actually zero, so we don't even + * need to add the correction terms in the end. From the definition of diff, + * {{{ + * diffSum = \sum_j (\sum_i w_i(x_{ij} - \bar{x_i}) / \hat{x_i} - (y_j - \bar{y}) / \hat{y}) + * = N * (\sum_i w_i(\bar{x_i} - \bar{x_i}) / \hat{x_i} - (\bar{y_j} - \bar{y}) / \hat{y}) + * = 0 + * }}} + * + * As a result, the first derivative of the total objective function only depends on + * the training dataset, which can be easily computed in distributed fashion, and is + * sparse format friendly. + * {{{ + * \frac{\partial L}{\partial\w_i} = 1/N ((\sum_j diff_j x_{ij} / \hat{x_i}) + * }}}, + * + * @param weights The weights/coefficients corresponding to the features. + * @param labelStd The standard deviation value of the label. + * @param labelMean The mean value of the label. + * @param featuresStd The standard deviation values of the features. + * @param featuresMean The mean values of the features. */ private class LeastSquaresAggregator( weights: Vector, @@ -215,9 +300,8 @@ private class LeastSquaresAggregator( featuresStd: Array[Double], featuresMean: Array[Double]) extends Serializable { - private var totalCnt: Long = 0 + private var totalCnt: Long = 0L private var lossSum = 0.0 - private var diffSum = 0.0 private val (effectiveWeightsArray: Array[Double], offset: Double, dim: Int) = { val weightsArray = weights.toArray.clone() @@ -234,9 +318,10 @@ private class LeastSquaresAggregator( } (weightsArray, -sum + labelMean / labelStd, weightsArray.length) } + private val effectiveWeightsVector = Vectors.dense(effectiveWeightsArray) - private val gradientSumArray: Array[Double] = Array.ofDim[Double](dim) + private val gradientSumArray = Array.ofDim[Double](dim) /** * Add a new training data to this LeastSquaresAggregator, and update the loss and gradient @@ -261,7 +346,6 @@ private class LeastSquaresAggregator( } } lossSum += diff * diff / 2.0 - diffSum += diff } totalCnt += 1 @@ -283,7 +367,6 @@ private class LeastSquaresAggregator( if (other.totalCnt != 0) { totalCnt += other.totalCnt lossSum += other.lossSum - diffSum += other.diffSum var i = 0 val localThisGradientSumArray = this.gradientSumArray @@ -302,18 +385,6 @@ private class LeastSquaresAggregator( def gradient: Vector = { val result = Vectors.dense(gradientSumArray.clone()) - - val correction = { - val temp = effectiveWeightsArray.clone() - var i = 0 - while (i < temp.length) { - temp(i) *= featuresMean(i) - i += 1 - } - Vectors.dense(temp) - } - - axpy(-diffSum, correction, result) scal(1.0 / totalCnt, result) result } diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala index 4bb4ed813c006..d1ad0893cd044 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala @@ -22,7 +22,7 @@ import com.github.fommil.netlib.F2jBLAS import org.apache.spark.Logging import org.apache.spark.annotation.AlphaComponent import org.apache.spark.ml._ -import org.apache.spark.ml.param.{IntParam, Param, ParamMap, Params} +import org.apache.spark.ml.param._ import org.apache.spark.mllib.util.MLUtils import org.apache.spark.sql.DataFrame import org.apache.spark.sql.types.StructType @@ -61,10 +61,12 @@ private[ml] trait CrossValidatorParams extends Params { def getEvaluator: Evaluator = getOrDefault(evaluator) /** - * param for number of folds for cross validation + * Param for number of folds for cross validation. Must be >= 2. + * Default: 3 * @group param */ - val numFolds: IntParam = new IntParam(this, "numFolds", "number of folds for cross validation") + val numFolds: IntParam = new IntParam(this, "numFolds", + "number of folds for cross validation (>= 2)", ParamValidators.gtEq(2)) /** @group getParam */ def getNumFolds: Int = getOrDefault(numFolds) @@ -93,6 +95,12 @@ class CrossValidator extends Estimator[CrossValidatorModel] with CrossValidatorP /** @group setParam */ def setNumFolds(value: Int): this.type = set(numFolds, value) + override def validate(paramMap: ParamMap): Unit = { + getEstimatorParamMaps.foreach { eMap => + getEstimator.validate(eMap ++ paramMap) + } + } + override def fit(dataset: DataFrame, paramMap: ParamMap): CrossValidatorModel = { val map = extractParamMap(paramMap) val schema = dataset.schema @@ -101,8 +109,8 @@ class CrossValidator extends Estimator[CrossValidatorModel] with CrossValidatorP val est = map(estimator) val eval = map(evaluator) val epm = map(estimatorParamMaps) - val numModels = epm.size - val metrics = new Array[Double](epm.size) + val numModels = epm.length + val metrics = new Array[Double](epm.length) val splits = MLUtils.kFold(dataset.rdd, map(numFolds), 0) splits.zipWithIndex.foreach { case ((training, validation), splitIndex) => val trainingDataset = sqlCtx.createDataFrame(training, schema).cache() @@ -148,6 +156,10 @@ class CrossValidatorModel private[ml] ( val bestModel: Model[_]) extends Model[CrossValidatorModel] with CrossValidatorParams { + override def validate(paramMap: ParamMap): Unit = { + bestModel.validate(paramMap) + } + override def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame = { bestModel.transform(dataset, paramMap) } diff --git a/mllib/src/main/scala/org/apache/spark/ml/Identifiable.scala b/mllib/src/main/scala/org/apache/spark/ml/util/Identifiable.scala similarity index 97% rename from mllib/src/main/scala/org/apache/spark/ml/Identifiable.scala rename to mllib/src/main/scala/org/apache/spark/ml/util/Identifiable.scala index a1d49095c24ac..8a56748ab0a02 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/Identifiable.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/util/Identifiable.scala @@ -15,7 +15,7 @@ * limitations under the License. */ -package org.apache.spark.ml +package org.apache.spark.ml.util import java.util.UUID diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala index 057b628c6a586..bd2e9079ce1ae 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala @@ -23,6 +23,7 @@ import org.apache.spark.mllib.classification.impl.GLMClassificationModel import org.apache.spark.mllib.linalg.BLAS.dot import org.apache.spark.mllib.linalg.{DenseVector, Vector} import org.apache.spark.mllib.optimization._ +import org.apache.spark.mllib.pmml.PMMLExportable import org.apache.spark.mllib.regression._ import org.apache.spark.mllib.util.{DataValidators, Saveable, Loader} import org.apache.spark.rdd.RDD @@ -46,7 +47,7 @@ class LogisticRegressionModel ( val numFeatures: Int, val numClasses: Int) extends GeneralizedLinearModel(weights, intercept) with ClassificationModel with Serializable - with Saveable { + with Saveable with PMMLExportable { if (numClasses == 2) { require(weights.size == numFeatures, diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala index 52fb62dcff1b4..33104cf06c6ea 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala @@ -22,6 +22,7 @@ import org.apache.spark.annotation.Experimental import org.apache.spark.mllib.classification.impl.GLMClassificationModel import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.optimization._ +import org.apache.spark.mllib.pmml.PMMLExportable import org.apache.spark.mllib.regression._ import org.apache.spark.mllib.util.{DataValidators, Loader, Saveable} import org.apache.spark.rdd.RDD @@ -36,7 +37,7 @@ class SVMModel ( override val weights: Vector, override val intercept: Double) extends GeneralizedLinearModel(weights, intercept) with ClassificationModel with Serializable - with Saveable { + with Saveable with PMMLExportable { private var threshold: Option[Double] = Some(0.0) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala index e4e411a3c8b42..ba228b11fcec3 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala @@ -25,6 +25,7 @@ import org.json4s.jackson.JsonMethods._ import org.apache.spark.api.java.JavaRDD import org.apache.spark.mllib.linalg.Vector +import org.apache.spark.mllib.pmml.PMMLExportable import org.apache.spark.mllib.util.{Loader, Saveable} import org.apache.spark.rdd.RDD import org.apache.spark.SparkContext @@ -34,7 +35,8 @@ import org.apache.spark.sql.Row /** * A clustering model for K-means. Each point belongs to the cluster with the closest center. */ -class KMeansModel (val clusterCenters: Array[Vector]) extends Saveable with Serializable { +class KMeansModel ( + val clusterCenters: Array[Vector]) extends Saveable with Serializable with PMMLExportable { /** A Java-friendly constructor that takes an Iterable of Vectors. */ def this(centers: java.lang.Iterable[Vector]) = this(centers.asScala.toArray) diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala index 34833e90d4af0..188d1e542b5b5 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala @@ -116,6 +116,40 @@ sealed trait Vector extends Serializable { * with type `Double`. */ private[spark] def foreachActive(f: (Int, Double) => Unit) + + /** + * Number of active entries. An "active entry" is an element which is explicitly stored, + * regardless of its value. Note that inactive entries have value 0. + */ + def numActives: Int + + /** + * Number of nonzero elements. This scans all active values and count nonzeros. + */ + def numNonzeros: Int + + /** + * Converts this vector to a sparse vector with all explicit zeros removed. + */ + def toSparse: SparseVector + + /** + * Converts this vector to a dense vector. + */ + def toDense: DenseVector = new DenseVector(this.toArray) + + /** + * Returns a vector in either dense or sparse format, whichever uses less storage. + */ + def compressed: Vector = { + val nnz = numNonzeros + // A dense vector needs 8 * size + 8 bytes, while a sparse vector needs 12 * nnz + 20 bytes. + if (1.5 * (nnz + 1.0) < size) { + toSparse + } else { + toDense + } + } } /** @@ -525,6 +559,34 @@ class DenseVector(val values: Array[Double]) extends Vector { } result } + + override def numActives: Int = size + + override def numNonzeros: Int = { + // same as values.count(_ != 0.0) but faster + var nnz = 0 + values.foreach { v => + if (v != 0.0) { + nnz += 1 + } + } + nnz + } + + override def toSparse: SparseVector = { + val nnz = numNonzeros + val ii = new Array[Int](nnz) + val vv = new Array[Double](nnz) + var k = 0 + foreachActive { (i, v) => + if (v != 0) { + ii(k) = i + vv(k) = v + k += 1 + } + } + new SparseVector(size, ii, vv) + } } object DenseVector { @@ -602,6 +664,37 @@ class SparseVector( } result } + + override def numActives: Int = values.length + + override def numNonzeros: Int = { + var nnz = 0 + values.foreach { v => + if (v != 0.0) { + nnz += 1 + } + } + nnz + } + + override def toSparse: SparseVector = { + val nnz = numNonzeros + if (nnz == numActives) { + this + } else { + val ii = new Array[Int](nnz) + val vv = new Array[Double](nnz) + var k = 0 + foreachActive { (i, v) => + if (v != 0.0) { + ii(k) = i + vv(k) = v + k += 1 + } + } + new SparseVector(size, ii, vv) + } + } } object SparseVector { diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala new file mode 100644 index 0000000000000..354e90f3eeaa6 --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala @@ -0,0 +1,74 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml + +import java.io.{File, OutputStream, StringWriter} +import javax.xml.transform.stream.StreamResult + +import org.jpmml.model.JAXBUtil + +import org.apache.spark.SparkContext +import org.apache.spark.mllib.pmml.export.PMMLModelExportFactory + +/** + * Export model to the PMML format + * Predictive Model Markup Language (PMML) is an XML-based file format + * developed by the Data Mining Group (www.dmg.org). + */ +trait PMMLExportable { + + /** + * Export the model to the stream result in PMML format + */ + private def toPMML(streamResult: StreamResult): Unit = { + val pmmlModelExport = PMMLModelExportFactory.createPMMLModelExport(this) + JAXBUtil.marshalPMML(pmmlModelExport.getPmml, streamResult) + } + + /** + * Export the model to a local file in PMML format + */ + def toPMML(localPath: String): Unit = { + toPMML(new StreamResult(new File(localPath))) + } + + /** + * Export the model to a directory on a distributed file system in PMML format + */ + def toPMML(sc: SparkContext, path: String): Unit = { + val pmml = toPMML() + sc.parallelize(Array(pmml), 1).saveAsTextFile(path) + } + + /** + * Export the model to the OutputStream in PMML format + */ + def toPMML(outputStream: OutputStream): Unit = { + toPMML(new StreamResult(outputStream)) + } + + /** + * Export the model to a String in PMML format + */ + def toPMML(): String = { + val writer = new StringWriter + toPMML(new StreamResult(writer)) + writer.toString + } + +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExport.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExport.scala new file mode 100644 index 0000000000000..34b447584e521 --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExport.scala @@ -0,0 +1,90 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import scala.{Array => SArray} + +import org.dmg.pmml._ + +import org.apache.spark.mllib.regression.GeneralizedLinearModel + +/** + * PMML Model Export for GeneralizedLinearModel class with binary ClassificationModel + */ +private[mllib] class BinaryClassificationPMMLModelExport( + model : GeneralizedLinearModel, + description : String, + normalizationMethod : RegressionNormalizationMethodType, + threshold: Double) + extends PMMLModelExport { + + populateBinaryClassificationPMML() + + /** + * Export the input LogisticRegressionModel or SVMModel to PMML format. + */ + private def populateBinaryClassificationPMML(): Unit = { + pmml.getHeader.setDescription(description) + + if (model.weights.size > 0) { + val fields = new SArray[FieldName](model.weights.size) + val dataDictionary = new DataDictionary + val miningSchema = new MiningSchema + val regressionTableYES = new RegressionTable(model.intercept).withTargetCategory("1") + var interceptNO = threshold + if (RegressionNormalizationMethodType.LOGIT == normalizationMethod) { + if (threshold <= 0) { + interceptNO = Double.MinValue + } else if (threshold >= 1) { + interceptNO = Double.MaxValue + } else { + interceptNO = -math.log(1 / threshold - 1) + } + } + val regressionTableNO = new RegressionTable(interceptNO).withTargetCategory("0") + val regressionModel = new RegressionModel() + .withFunctionName(MiningFunctionType.CLASSIFICATION) + .withMiningSchema(miningSchema) + .withModelName(description) + .withNormalizationMethod(normalizationMethod) + .withRegressionTables(regressionTableYES, regressionTableNO) + + for (i <- 0 until model.weights.size) { + fields(i) = FieldName.create("field_" + i) + dataDictionary.withDataFields(new DataField(fields(i), OpType.CONTINUOUS, DataType.DOUBLE)) + miningSchema + .withMiningFields(new MiningField(fields(i)) + .withUsageType(FieldUsageType.ACTIVE)) + regressionTableYES.withNumericPredictors(new NumericPredictor(fields(i), model.weights(i))) + } + + // add target field + val targetField = FieldName.create("target") + dataDictionary + .withDataFields(new DataField(targetField, OpType.CATEGORICAL, DataType.STRING)) + miningSchema + .withMiningFields(new MiningField(targetField) + .withUsageType(FieldUsageType.TARGET)) + + dataDictionary.withNumberOfFields(dataDictionary.getDataFields.size) + + pmml.setDataDictionary(dataDictionary) + pmml.withModels(regressionModel) + } + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExport.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExport.scala new file mode 100644 index 0000000000000..1874786af0002 --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExport.scala @@ -0,0 +1,75 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import scala.{Array => SArray} + +import org.dmg.pmml._ + +import org.apache.spark.mllib.regression.GeneralizedLinearModel + +/** + * PMML Model Export for GeneralizedLinearModel abstract class + */ +private[mllib] class GeneralizedLinearPMMLModelExport( + model: GeneralizedLinearModel, + description: String) + extends PMMLModelExport { + + populateGeneralizedLinearPMML(model) + + /** + * Export the input GeneralizedLinearModel model to PMML format. + */ + private def populateGeneralizedLinearPMML(model: GeneralizedLinearModel): Unit = { + pmml.getHeader.setDescription(description) + + if (model.weights.size > 0) { + val fields = new SArray[FieldName](model.weights.size) + val dataDictionary = new DataDictionary + val miningSchema = new MiningSchema + val regressionTable = new RegressionTable(model.intercept) + val regressionModel = new RegressionModel() + .withFunctionName(MiningFunctionType.REGRESSION) + .withMiningSchema(miningSchema) + .withModelName(description) + .withRegressionTables(regressionTable) + + for (i <- 0 until model.weights.size) { + fields(i) = FieldName.create("field_" + i) + dataDictionary.withDataFields(new DataField(fields(i), OpType.CONTINUOUS, DataType.DOUBLE)) + miningSchema + .withMiningFields(new MiningField(fields(i)) + .withUsageType(FieldUsageType.ACTIVE)) + regressionTable.withNumericPredictors(new NumericPredictor(fields(i), model.weights(i))) + } + + // for completeness add target field + val targetField = FieldName.create("target") + dataDictionary.withDataFields(new DataField(targetField, OpType.CONTINUOUS, DataType.DOUBLE)) + miningSchema + .withMiningFields(new MiningField(targetField) + .withUsageType(FieldUsageType.TARGET)) + + dataDictionary.withNumberOfFields(dataDictionary.getDataFields.size) + + pmml.setDataDictionary(dataDictionary) + pmml.withModels(regressionModel) + } + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExport.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExport.scala new file mode 100644 index 0000000000000..069e7afc9fca0 --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExport.scala @@ -0,0 +1,83 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import scala.{Array => SArray} + +import org.dmg.pmml._ + +import org.apache.spark.mllib.clustering.KMeansModel + +/** + * PMML Model Export for KMeansModel class + */ +private[mllib] class KMeansPMMLModelExport(model : KMeansModel) extends PMMLModelExport{ + + populateKMeansPMML(model) + + /** + * Export the input KMeansModel model to PMML format. + */ + private def populateKMeansPMML(model : KMeansModel): Unit = { + pmml.getHeader.setDescription("k-means clustering") + + if (model.clusterCenters.length > 0) { + val clusterCenter = model.clusterCenters(0) + val fields = new SArray[FieldName](clusterCenter.size) + val dataDictionary = new DataDictionary + val miningSchema = new MiningSchema + val comparisonMeasure = new ComparisonMeasure() + .withKind(ComparisonMeasure.Kind.DISTANCE) + .withMeasure(new SquaredEuclidean()) + val clusteringModel = new ClusteringModel() + .withModelName("k-means") + .withMiningSchema(miningSchema) + .withComparisonMeasure(comparisonMeasure) + .withFunctionName(MiningFunctionType.CLUSTERING) + .withModelClass(ClusteringModel.ModelClass.CENTER_BASED) + .withNumberOfClusters(model.clusterCenters.length) + + for (i <- 0 until clusterCenter.size) { + fields(i) = FieldName.create("field_" + i) + dataDictionary.withDataFields(new DataField(fields(i), OpType.CONTINUOUS, DataType.DOUBLE)) + miningSchema + .withMiningFields(new MiningField(fields(i)) + .withUsageType(FieldUsageType.ACTIVE)) + clusteringModel.withClusteringFields( + new ClusteringField(fields(i)).withCompareFunction(CompareFunctionType.ABS_DIFF)) + } + + dataDictionary.withNumberOfFields(dataDictionary.getDataFields.size) + + for (i <- 0 until model.clusterCenters.length) { + val cluster = new Cluster() + .withName("cluster_" + i) + .withArray(new org.dmg.pmml.Array() + .withType(Array.Type.REAL) + .withN(clusterCenter.size) + .withValue(model.clusterCenters(i).toArray.mkString(" "))) + // we don't have the size of the single cluster but only the centroids (withValue) + // .withSize(value) + clusteringModel.withClusters(cluster) + } + + pmml.setDataDictionary(dataDictionary) + pmml.withModels(clusteringModel) + } + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExport.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExport.scala new file mode 100644 index 0000000000000..ebdeae50bb32f --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExport.scala @@ -0,0 +1,47 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import java.text.SimpleDateFormat +import java.util.Date + +import scala.beans.BeanProperty + +import org.dmg.pmml.{Application, Header, PMML, Timestamp} + +private[mllib] trait PMMLModelExport { + + /** + * Holder of the exported model in PMML format + */ + @BeanProperty + val pmml: PMML = new PMML + + setHeader(pmml) + + private def setHeader(pmml: PMML): Unit = { + val version = getClass.getPackage.getImplementationVersion + val app = new Application().withName("Apache Spark MLlib").withVersion(version) + val timestamp = new Timestamp() + .withContent(new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss").format(new Date())) + val header = new Header() + .withApplication(app) + .withTimestamp(timestamp) + pmml.setHeader(header) + } +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactory.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactory.scala new file mode 100644 index 0000000000000..c16e83d6a067d --- /dev/null +++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactory.scala @@ -0,0 +1,64 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import org.dmg.pmml.RegressionNormalizationMethodType + +import org.apache.spark.mllib.classification.LogisticRegressionModel +import org.apache.spark.mllib.classification.SVMModel +import org.apache.spark.mllib.clustering.KMeansModel +import org.apache.spark.mllib.regression.LassoModel +import org.apache.spark.mllib.regression.LinearRegressionModel +import org.apache.spark.mllib.regression.RidgeRegressionModel + +private[mllib] object PMMLModelExportFactory { + + /** + * Factory object to help creating the necessary PMMLModelExport implementation + * taking as input the machine learning model (for example KMeansModel). + */ + def createPMMLModelExport(model: Any): PMMLModelExport = { + model match { + case kmeans: KMeansModel => + new KMeansPMMLModelExport(kmeans) + case linear: LinearRegressionModel => + new GeneralizedLinearPMMLModelExport(linear, "linear regression") + case ridge: RidgeRegressionModel => + new GeneralizedLinearPMMLModelExport(ridge, "ridge regression") + case lasso: LassoModel => + new GeneralizedLinearPMMLModelExport(lasso, "lasso regression") + case svm: SVMModel => + new BinaryClassificationPMMLModelExport( + svm, "linear SVM", RegressionNormalizationMethodType.NONE, + svm.getThreshold.getOrElse(0.0)) + case logistic: LogisticRegressionModel => + if (logistic.numClasses == 2) { + new BinaryClassificationPMMLModelExport( + logistic, "logistic regression", RegressionNormalizationMethodType.LOGIT, + logistic.getThreshold.getOrElse(0.5)) + } else { + throw new IllegalArgumentException( + "PMML Export not supported for Multinomial Logistic Regression") + } + case _ => + throw new IllegalArgumentException( + "PMML Export not supported for model: " + model.getClass.getName) + } + } + +} diff --git a/mllib/src/main/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctions.scala b/mllib/src/main/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctions.scala index 9213fd3f595c3..5af55aaf84802 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctions.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctions.scala @@ -42,13 +42,11 @@ class MLPairRDDFunctions[K: ClassTag, V: ClassTag](self: RDD[(K, V)]) extends Se self.aggregateByKey(new BoundedPriorityQueue[V](num)(ord))( seqOp = (queue, item) => { queue += item - queue }, combOp = (queue1, queue2) => { queue1 ++= queue2 - queue1 } - ).mapValues(_.toArray.sorted(ord.reverse)) + ).mapValues(_.toArray.reverse) // This is an min-heap, so we reverse the order. } } diff --git a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala index 36cbf060d9998..88c2148403313 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala @@ -20,14 +20,18 @@ package org.apache.spark.mllib.recommendation import java.io.IOException import java.lang.{Integer => JavaInteger} +import scala.collection.mutable + +import com.github.fommil.netlib.BLAS.{getInstance => blas} import org.apache.hadoop.fs.Path import org.json4s._ import org.json4s.JsonDSL._ import org.json4s.jackson.JsonMethods._ -import com.github.fommil.netlib.BLAS.{getInstance => blas} import org.apache.spark.{Logging, SparkContext} import org.apache.spark.api.java.{JavaPairRDD, JavaRDD} +import org.apache.spark.mllib.linalg._ +import org.apache.spark.mllib.rdd.MLPairRDDFunctions._ import org.apache.spark.mllib.util.{Loader, Saveable} import org.apache.spark.rdd.RDD import org.apache.spark.sql.{Row, SQLContext} @@ -57,7 +61,7 @@ class MatrixFactorizationModel( /** Validates factors and warns users if there are performance concerns. */ private def validateFeatures(name: String, features: RDD[(Int, Array[Double])]): Unit = { - require(features.first()._2.size == rank, + require(features.first()._2.length == rank, s"$name feature dimension does not match the rank $rank.") if (features.partitioner.isEmpty) { logWarning(s"$name factor does not have a partitioner. " @@ -72,19 +76,19 @@ class MatrixFactorizationModel( def predict(user: Int, product: Int): Double = { val userVector = userFeatures.lookup(user).head val productVector = productFeatures.lookup(product).head - blas.ddot(userVector.length, userVector, 1, productVector, 1) + blas.ddot(rank, userVector, 1, productVector, 1) } /** - * Predict the rating of many users for many products. - * The output RDD has an element per each element in the input RDD (including all duplicates) - * unless a user or product is missing in the training set. - * - * @param usersProducts RDD of (user, product) pairs. - * @return RDD of Ratings. - */ + * Predict the rating of many users for many products. + * The output RDD has an element per each element in the input RDD (including all duplicates) + * unless a user or product is missing in the training set. + * + * @param usersProducts RDD of (user, product) pairs. + * @return RDD of Ratings. + */ def predict(usersProducts: RDD[(Int, Int)]): RDD[Rating] = { - val users = userFeatures.join(usersProducts).map{ + val users = userFeatures.join(usersProducts).map { case (user, (uFeatures, product)) => (product, (user, uFeatures)) } users.join(productFeatures).map { @@ -112,7 +116,7 @@ class MatrixFactorizationModel( * recommended the product is. */ def recommendProducts(user: Int, num: Int): Array[Rating] = - recommend(userFeatures.lookup(user).head, productFeatures, num) + MatrixFactorizationModel.recommend(userFeatures.lookup(user).head, productFeatures, num) .map(t => Rating(user, t._1, t._2)) /** @@ -128,7 +132,7 @@ class MatrixFactorizationModel( * recommended the user is. */ def recommendUsers(product: Int, num: Int): Array[Rating] = - recommend(productFeatures.lookup(product).head, userFeatures, num) + MatrixFactorizationModel.recommend(productFeatures.lookup(product).head, userFeatures, num) .map(t => Rating(t._1, product, t._2)) protected override val formatVersion: String = "1.0" @@ -137,20 +141,113 @@ class MatrixFactorizationModel( MatrixFactorizationModel.SaveLoadV1_0.save(this, path) } + /** + * Recommends topK products for all users. + * + * @param num how many products to return for every user. + * @return [(Int, Array[Rating])] objects, where every tuple contains a userID and an array of + * rating objects which contains the same userId, recommended productID and a "score" in the + * rating field. Semantics of score is same as recommendProducts API + */ + def recommendProductsForUsers(num: Int): RDD[(Int, Array[Rating])] = { + MatrixFactorizationModel.recommendForAll(rank, userFeatures, productFeatures, num).map { + case (user, top) => + val ratings = top.map { case (product, rating) => Rating(user, product, rating) } + (user, ratings) + } + } + + + /** + * Recommends topK users for all products. + * + * @param num how many users to return for every product. + * @return [(Int, Array[Rating])] objects, where every tuple contains a productID and an array + * of rating objects which contains the recommended userId, same productID and a "score" in the + * rating field. Semantics of score is same as recommendUsers API + */ + def recommendUsersForProducts(num: Int): RDD[(Int, Array[Rating])] = { + MatrixFactorizationModel.recommendForAll(rank, productFeatures, userFeatures, num).map { + case (product, top) => + val ratings = top.map { case (user, rating) => Rating(user, product, rating) } + (product, ratings) + } + } +} + +object MatrixFactorizationModel extends Loader[MatrixFactorizationModel] { + + import org.apache.spark.mllib.util.Loader._ + + /** + * Makes recommendations for a single user (or product). + */ private def recommend( recommendToFeatures: Array[Double], recommendableFeatures: RDD[(Int, Array[Double])], num: Int): Array[(Int, Double)] = { - val scored = recommendableFeatures.map { case (id,features) => + val scored = recommendableFeatures.map { case (id, features) => (id, blas.ddot(features.length, recommendToFeatures, 1, features, 1)) } scored.top(num)(Ordering.by(_._2)) } -} -object MatrixFactorizationModel extends Loader[MatrixFactorizationModel] { + /** + * Makes recommendations for all users (or products). + * @param rank rank + * @param srcFeatures src features to receive recommendations + * @param dstFeatures dst features used to make recommendations + * @param num number of recommendations for each record + * @return an RDD of (srcId: Int, recommendations), where recommendations are stored as an array + * of (dstId, rating) pairs. + */ + private def recommendForAll( + rank: Int, + srcFeatures: RDD[(Int, Array[Double])], + dstFeatures: RDD[(Int, Array[Double])], + num: Int): RDD[(Int, Array[(Int, Double)])] = { + val srcBlocks = blockify(rank, srcFeatures) + val dstBlocks = blockify(rank, dstFeatures) + val ratings = srcBlocks.cartesian(dstBlocks).flatMap { + case ((srcIds, srcFactors), (dstIds, dstFactors)) => + val m = srcIds.length + val n = dstIds.length + val ratings = srcFactors.transpose.multiply(dstFactors) + val output = new Array[(Int, (Int, Double))](m * n) + var k = 0 + ratings.foreachActive { (i, j, r) => + output(k) = (srcIds(i), (dstIds(j), r)) + k += 1 + } + output.toSeq + } + ratings.topByKey(num)(Ordering.by(_._2)) + } - import org.apache.spark.mllib.util.Loader._ + /** + * Blockifies features to use Level-3 BLAS. + */ + private def blockify( + rank: Int, + features: RDD[(Int, Array[Double])]): RDD[(Array[Int], DenseMatrix)] = { + val blockSize = 4096 // TODO: tune the block size + val blockStorage = rank * blockSize + features.mapPartitions { iter => + iter.grouped(blockSize).map { grouped => + val ids = mutable.ArrayBuilder.make[Int] + ids.sizeHint(blockSize) + val factors = mutable.ArrayBuilder.make[Double] + factors.sizeHint(blockStorage) + var i = 0 + grouped.foreach { case (id, factor) => + ids += id + factors ++= factor + i += 1 + } + (ids.result(), new DenseMatrix(rank, i, factors.result())) + } + } + } override def load(sc: SparkContext, path: String): MatrixFactorizationModel = { val (loadedClassName, formatVersion, _) = loadMetadata(sc, path) @@ -214,4 +311,5 @@ object MatrixFactorizationModel extends Loader[MatrixFactorizationModel] { new Path(dataPath(path), "product").toUri.toString } } + } diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala index 9fd60ff7a0c79..26be30ff9d6fd 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala @@ -225,7 +225,7 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel] throw new SparkException("Input validation failed.") } - /* + /** * Scaling columns to unit variance as a heuristic to reduce the condition number: * * During the optimization process, the convergence (rate) depends on the condition number of diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala index e8b03816573cf..4f482384f0f38 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala @@ -20,6 +20,7 @@ package org.apache.spark.mllib.regression import org.apache.spark.SparkContext import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.optimization._ +import org.apache.spark.mllib.pmml.PMMLExportable import org.apache.spark.mllib.regression.impl.GLMRegressionModel import org.apache.spark.mllib.util.{Saveable, Loader} import org.apache.spark.rdd.RDD @@ -34,7 +35,7 @@ class LassoModel ( override val weights: Vector, override val intercept: Double) extends GeneralizedLinearModel(weights, intercept) - with RegressionModel with Serializable with Saveable { + with RegressionModel with Serializable with Saveable with PMMLExportable { override protected def predictPoint( dataMatrix: Vector, diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala index 6fa7ad52a5b33..9453c4f66c216 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala @@ -20,6 +20,7 @@ package org.apache.spark.mllib.regression import org.apache.spark.SparkContext import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.optimization._ +import org.apache.spark.mllib.pmml.PMMLExportable import org.apache.spark.mllib.regression.impl.GLMRegressionModel import org.apache.spark.mllib.util.{Saveable, Loader} import org.apache.spark.rdd.RDD @@ -34,7 +35,7 @@ class LinearRegressionModel ( override val weights: Vector, override val intercept: Double) extends GeneralizedLinearModel(weights, intercept) with RegressionModel with Serializable - with Saveable { + with Saveable with PMMLExportable { override protected def predictPoint( dataMatrix: Vector, diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala index 309f9af466457..e0c03d8180c7a 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala @@ -20,6 +20,7 @@ package org.apache.spark.mllib.regression import org.apache.spark.SparkContext import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.optimization._ +import org.apache.spark.mllib.pmml.PMMLExportable import org.apache.spark.mllib.regression.impl.GLMRegressionModel import org.apache.spark.mllib.util.{Loader, Saveable} import org.apache.spark.rdd.RDD @@ -35,7 +36,7 @@ class RidgeRegressionModel ( override val weights: Vector, override val intercept: Double) extends GeneralizedLinearModel(weights, intercept) - with RegressionModel with Serializable with Saveable { + with RegressionModel with Serializable with Saveable with PMMLExportable { override protected def predictPoint( dataMatrix: Vector, diff --git a/mllib/src/main/scala/org/apache/spark/mllib/stat/correlation/PearsonCorrelation.scala b/mllib/src/main/scala/org/apache/spark/mllib/stat/correlation/PearsonCorrelation.scala index 23b291eee070b..8a821d1b23bab 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/stat/correlation/PearsonCorrelation.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/stat/correlation/PearsonCorrelation.scala @@ -101,7 +101,7 @@ private[stat] object PearsonCorrelation extends Correlation with Logging { Matrices.fromBreeze(cov) } - private def closeToZero(value: Double, threshhold: Double = 1e-12): Boolean = { - math.abs(value) <= threshhold + private def closeToZero(value: Double, threshold: Double = 1e-12): Boolean = { + math.abs(value) <= threshold } } diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala index deac390130128..1f779584dcffd 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala @@ -180,7 +180,9 @@ object GradientBoostedTrees extends Logging { val persistedInput = if (input.getStorageLevel == StorageLevel.NONE) { input.persist(StorageLevel.MEMORY_AND_DISK) true - } else false + } else { + false + } timer.stop("init") diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala index d7bb943e84f53..b1a4517344970 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala @@ -75,8 +75,8 @@ object LinearDataGenerator { seed: Int, eps: Double = 0.1): Seq[LabeledPoint] = { generateLinearInput(intercept, weights, - Array.fill[Double](weights.size)(0.0), - Array.fill[Double](weights.size)(1.0 / 3.0), + Array.fill[Double](weights.length)(0.0), + Array.fill[Double](weights.length)(1.0 / 3.0), nPoints, seed, eps)} /** @@ -103,17 +103,15 @@ object LinearDataGenerator { val rnd = new Random(seed) val x = Array.fill[Array[Double]](nPoints)( - Array.fill[Double](weights.length)(rnd.nextDouble)) + Array.fill[Double](weights.length)(rnd.nextDouble())) - x.map(vector => { - // This doesn't work if `vector` is a sparse vector. - val vectorArray = vector.toArray + x.foreach { v => var i = 0 - while (i < vectorArray.size) { - vectorArray(i) = (vectorArray(i) - 0.5) * math.sqrt(12.0 * xVariance(i)) + xMean(i) + while (i < v.length) { + v(i) = (v(i) - 0.5) * math.sqrt(12.0 * xVariance(i)) + xMean(i) i += 1 } - }) + } val y = x.map { xi => blas.ddot(weights.length, xi, 1, weights, 1) + intercept + eps * rnd.nextGaussian() diff --git a/mllib/src/test/java/org/apache/spark/ml/param/JavaParamsSuite.java b/mllib/src/test/java/org/apache/spark/ml/param/JavaParamsSuite.java new file mode 100644 index 0000000000000..e7df10dfa63ac --- /dev/null +++ b/mllib/src/test/java/org/apache/spark/ml/param/JavaParamsSuite.java @@ -0,0 +1,66 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.param; + +import com.google.common.collect.Lists; +import org.junit.After; +import org.junit.Assert; +import org.junit.Before; +import org.junit.Test; + +import org.apache.spark.api.java.JavaSparkContext; + +/** + * Test Param and related classes in Java + */ +public class JavaParamsSuite { + + private transient JavaSparkContext jsc; + + @Before + public void setUp() { + jsc = new JavaSparkContext("local", "JavaParamsSuite"); + } + + @After + public void tearDown() { + jsc.stop(); + jsc = null; + } + + @Test + public void testParams() { + JavaTestParams testParams = new JavaTestParams(); + Assert.assertEquals(testParams.getMyIntParam(), 1); + testParams.setMyIntParam(2).setMyDoubleParam(0.4).setMyStringParam("a"); + Assert.assertEquals(testParams.getMyDoubleParam(), 0.4, 0.0); + Assert.assertEquals(testParams.getMyStringParam(), "a"); + } + + @Test + public void testParamValidate() { + ParamValidators.gt(1.0); + ParamValidators.gtEq(1.0); + ParamValidators.lt(1.0); + ParamValidators.ltEq(1.0); + ParamValidators.inRange(0, 1, true, false); + ParamValidators.inRange(0, 1); + ParamValidators.inArray(Lists.newArrayList(0, 1, 3)); + ParamValidators.inArray(Lists.newArrayList("a", "b")); + } +} diff --git a/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java b/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java new file mode 100644 index 0000000000000..8abe575610d19 --- /dev/null +++ b/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java @@ -0,0 +1,63 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.param; + +import java.util.List; + +import com.google.common.collect.Lists; + +/** + * A subclass of Params for testing. + */ +public class JavaTestParams extends JavaParams { + + public IntParam myIntParam; + + public int getMyIntParam() { return (Integer)getOrDefault(myIntParam); } + + public JavaTestParams setMyIntParam(int value) { + set(myIntParam, value); return this; + } + + public DoubleParam myDoubleParam; + + public double getMyDoubleParam() { return (Double)getOrDefault(myDoubleParam); } + + public JavaTestParams setMyDoubleParam(double value) { + set(myDoubleParam, value); return this; + } + + public Param myStringParam; + + public String getMyStringParam() { return (String)getOrDefault(myStringParam); } + + public JavaTestParams setMyStringParam(String value) { + set(myStringParam, value); return this; + } + + public JavaTestParams() { + myIntParam = new IntParam(this, "myIntParam", "this is an int param", ParamValidators.gt(0)); + myDoubleParam = new DoubleParam(this, "myDoubleParam", "this is a double param", + ParamValidators.inRange(0.0, 1.0)); + List validStrings = Lists.newArrayList("a", "b"); + myStringParam = new Param(this, "myStringParam", "this is a string param", + ParamValidators.inArray(validStrings)); + setDefault(myIntParam, 1); + setDefault(myDoubleParam, 0.5); + } +} diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala new file mode 100644 index 0000000000000..caf1b759593f3 --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala @@ -0,0 +1,69 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.feature + +import org.scalatest.FunSuite + +import org.apache.spark.mllib.util.MLlibTestSparkContext +import org.apache.spark.mllib.util.TestingUtils._ +import org.apache.spark.sql.{DataFrame, Row, SQLContext} + + +class BinarizerSuite extends FunSuite with MLlibTestSparkContext { + + @transient var data: Array[Double] = _ + @transient var sqlContext: SQLContext = _ + + override def beforeAll(): Unit = { + super.beforeAll() + sqlContext = new SQLContext(sc) + data = Array(0.1, -0.5, 0.2, -0.3, 0.8, 0.7, -0.1, -0.4) + } + + test("Binarize continuous features with default parameter") { + val defaultBinarized: Array[Double] = data.map(x => if (x > 0.0) 1.0 else 0.0) + val dataFrame: DataFrame = sqlContext.createDataFrame( + data.zip(defaultBinarized)).toDF("feature", "expected") + + val binarizer: Binarizer = new Binarizer() + .setInputCol("feature") + .setOutputCol("binarized_feature") + + binarizer.transform(dataFrame).select("binarized_feature", "expected").collect().foreach { + case Row(x: Double, y: Double) => + assert(x === y, "The feature value is not correct after binarization.") + } + } + + test("Binarize continuous features with setter") { + val threshold: Double = 0.2 + val thresholdBinarized: Array[Double] = data.map(x => if (x > threshold) 1.0 else 0.0) + val dataFrame: DataFrame = sqlContext.createDataFrame( + data.zip(thresholdBinarized)).toDF("feature", "expected") + + val binarizer: Binarizer = new Binarizer() + .setInputCol("feature") + .setOutputCol("binarized_feature") + .setThreshold(threshold) + + binarizer.transform(dataFrame).select("binarized_feature", "expected").collect().foreach { + case Row(x: Double, y: Double) => + assert(x === y, "The feature value is not correct after binarization.") + } + } +} diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala index 00b5d094d82f1..b6939e5870410 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala @@ -49,4 +49,23 @@ class StringIndexerSuite extends FunSuite with MLlibTestSparkContext { val expected = Set((0, 0.0), (1, 2.0), (2, 1.0), (3, 0.0), (4, 0.0), (5, 1.0)) assert(output === expected) } + + test("StringIndexer with a numeric input column") { + val data = sc.parallelize(Seq((0, 100), (1, 200), (2, 300), (3, 100), (4, 100), (5, 300)), 2) + val df = sqlContext.createDataFrame(data).toDF("id", "label") + val indexer = new StringIndexer() + .setInputCol("label") + .setOutputCol("labelIndex") + .fit(df) + val transformed = indexer.transform(df) + val attr = Attribute.fromStructField(transformed.schema("labelIndex")) + .asInstanceOf[NominalAttribute] + assert(attr.values.get === Array("100", "300", "200")) + val output = transformed.select("id", "labelIndex").map { r => + (r.getInt(0), r.getDouble(1)) + }.collect().toSet + // 100 -> 0, 200 -> 2, 300 -> 1 + val expected = Set((0, 0.0), (1, 2.0), (2, 1.0), (3, 0.0), (4, 0.0), (5, 1.0)) + assert(output === expected) + } } diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala index 1b261b2643854..38dc83b1241cf 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala @@ -23,7 +23,6 @@ import org.scalatest.FunSuite import org.apache.spark.SparkException import org.apache.spark.ml.attribute._ -import org.apache.spark.ml.util.TestingUtils import org.apache.spark.mllib.linalg.{SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.rdd.RDD @@ -111,8 +110,8 @@ class VectorIndexerSuite extends FunSuite with MLlibTestSparkContext { val model = vectorIndexer.fit(densePoints1) // vectors of length 3 model.transform(densePoints1) // should work model.transform(sparsePoints1) // should work - intercept[IllegalArgumentException] { - model.transform(densePoints2) + intercept[SparkException] { + model.transform(densePoints2).collect() println("Did not throw error when fit, transform were called on vectors of different lengths") } intercept[SparkException] { @@ -245,8 +244,6 @@ class VectorIndexerSuite extends FunSuite with MLlibTestSparkContext { // TODO: Once input features marked as categorical are handled correctly, check that here. } } - // Check that non-ML metadata are preserved. - TestingUtils.testPreserveMetadata(densePoints1WithMeta, model, "features", "indexed") } } diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala new file mode 100644 index 0000000000000..03ba86670d453 --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala @@ -0,0 +1,63 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.feature + +import org.scalatest.FunSuite + +import org.apache.spark.mllib.linalg.{Vector, Vectors} +import org.apache.spark.mllib.util.MLlibTestSparkContext +import org.apache.spark.mllib.util.TestingUtils._ +import org.apache.spark.sql.{Row, SQLContext} + +class Word2VecSuite extends FunSuite with MLlibTestSparkContext { + + test("Word2Vec") { + val sqlContext = new SQLContext(sc) + import sqlContext.implicits._ + + val sentence = "a b " * 100 + "a c " * 10 + val numOfWords = sentence.split(" ").size + val doc = sc.parallelize(Seq(sentence, sentence)).map(line => line.split(" ")) + + val codes = Map( + "a" -> Array(-0.2811822295188904,-0.6356269121170044,-0.3020961284637451), + "b" -> Array(1.0309048891067505,-1.29472815990448,0.22276712954044342), + "c" -> Array(-0.08456747233867645,0.5137411952018738,0.11731560528278351) + ) + + val expected = doc.map { sentence => + Vectors.dense(sentence.map(codes.apply).reduce((word1, word2) => + word1.zip(word2).map { case (v1, v2) => v1 + v2 } + ).map(_ / numOfWords)) + } + + val docDF = doc.zip(expected).toDF("text", "expected") + + val model = new Word2Vec() + .setVectorSize(3) + .setInputCol("text") + .setOutputCol("result") + .fit(docDF) + + model.transform(docDF).select("result", "expected").collect().foreach { + case Row(vector1: Vector, vector2: Vector) => + assert(vector1 ~== vector2 absTol 1E-5, "Transformed vector is different with expected.") + } + } +} + diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala index 88ea679eeaad5..f8852606abbf2 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala @@ -26,14 +26,22 @@ class ParamsSuite extends FunSuite { import solver.{maxIter, inputCol} assert(maxIter.name === "maxIter") - assert(maxIter.doc === "max number of iterations") + assert(maxIter.doc === "max number of iterations (>= 0)") assert(maxIter.parent.eq(solver)) - assert(maxIter.toString === "maxIter: max number of iterations (default: 10)") + assert(maxIter.toString === "maxIter: max number of iterations (>= 0) (default: 10)") + assert(!maxIter.isValid(-1)) + assert(maxIter.isValid(0)) + assert(maxIter.isValid(1)) solver.setMaxIter(5) - assert(maxIter.toString === "maxIter: max number of iterations (default: 10, current: 5)") + assert(maxIter.toString === + "maxIter: max number of iterations (>= 0) (default: 10, current: 5)") assert(inputCol.toString === "inputCol: input column name (undefined)") + + intercept[IllegalArgumentException] { + solver.setMaxIter(-1) + } } test("param pair") { @@ -47,6 +55,9 @@ class ParamsSuite extends FunSuite { assert(pair.param.eq(maxIter)) assert(pair.value === 5) } + intercept[IllegalArgumentException] { + val pair = maxIter -> -1 + } } test("param map") { @@ -59,6 +70,9 @@ class ParamsSuite extends FunSuite { map0.put(maxIter, 10) assert(map0.contains(maxIter)) assert(map0(maxIter) === 10) + intercept[IllegalArgumentException] { + map0.put(maxIter, -1) + } assert(!map0.contains(inputCol)) intercept[NoSuchElementException] { @@ -122,14 +136,57 @@ class ParamsSuite extends FunSuite { assert(solver.getInputCol === "input") solver.validate() intercept[IllegalArgumentException] { - solver.validate(ParamMap(maxIter -> -10)) + ParamMap(maxIter -> -10) } - solver.setMaxIter(-10) intercept[IllegalArgumentException] { - solver.validate() + solver.setMaxIter(-10) } solver.clearMaxIter() assert(!solver.isSet(maxIter)) } + + test("ParamValidate") { + val alwaysTrue = ParamValidators.alwaysTrue[Int] + assert(alwaysTrue(1)) + + val gt1Int = ParamValidators.gt[Int](1) + assert(!gt1Int(1) && gt1Int(2)) + val gt1Double = ParamValidators.gt[Double](1) + assert(!gt1Double(1.0) && gt1Double(1.1)) + + val gtEq1Int = ParamValidators.gtEq[Int](1) + assert(!gtEq1Int(0) && gtEq1Int(1)) + val gtEq1Double = ParamValidators.gtEq[Double](1) + assert(!gtEq1Double(0.9) && gtEq1Double(1.0)) + + val lt1Int = ParamValidators.lt[Int](1) + assert(lt1Int(0) && !lt1Int(1)) + val lt1Double = ParamValidators.lt[Double](1) + assert(lt1Double(0.9) && !lt1Double(1.0)) + + val ltEq1Int = ParamValidators.ltEq[Int](1) + assert(ltEq1Int(1) && !ltEq1Int(2)) + val ltEq1Double = ParamValidators.ltEq[Double](1) + assert(ltEq1Double(1.0) && !ltEq1Double(1.1)) + + val inRange02IntInclusive = ParamValidators.inRange[Int](0, 2) + assert(inRange02IntInclusive(0) && inRange02IntInclusive(1) && inRange02IntInclusive(2) && + !inRange02IntInclusive(-1) && !inRange02IntInclusive(3)) + val inRange02IntExclusive = + ParamValidators.inRange[Int](0, 2, lowerInclusive = false, upperInclusive = false) + assert(!inRange02IntExclusive(0) && inRange02IntExclusive(1) && !inRange02IntExclusive(2)) + + val inRange02DoubleInclusive = ParamValidators.inRange[Double](0, 2) + assert(inRange02DoubleInclusive(0) && inRange02DoubleInclusive(1) && + inRange02DoubleInclusive(2) && + !inRange02DoubleInclusive(-0.1) && !inRange02DoubleInclusive(2.1)) + val inRange02DoubleExclusive = + ParamValidators.inRange[Double](0, 2, lowerInclusive = false, upperInclusive = false) + assert(!inRange02DoubleExclusive(0) && inRange02DoubleExclusive(1) && + !inRange02DoubleExclusive(2)) + + val inArray = ParamValidators.inArray[Int](Array(1, 2)) + assert(inArray(1) && inArray(2) && !inArray(0)) + } } diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala index 641b64b42a5e7..6f9c9cb5166ae 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala @@ -29,7 +29,7 @@ class TestParams extends Params with HasMaxIter with HasInputCol { override def validate(paramMap: ParamMap): Unit = { val m = extractParamMap(paramMap) - require(m(maxIter) >= 0) + // Note: maxIter is validated when it is set. require(m.contains(inputCol)) } diff --git a/mllib/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala b/mllib/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala deleted file mode 100644 index c44cb61b34171..0000000000000 --- a/mllib/src/test/scala/org/apache/spark/ml/util/TestingUtils.scala +++ /dev/null @@ -1,60 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one or more - * contributor license agreements. See the NOTICE file distributed with - * this work for additional information regarding copyright ownership. - * The ASF licenses this file to You under the Apache License, Version 2.0 - * (the "License"); you may not use this file except in compliance with - * the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -package org.apache.spark.ml.util - -import org.apache.spark.ml.Transformer -import org.apache.spark.sql.DataFrame -import org.apache.spark.sql.types.MetadataBuilder -import org.scalatest.FunSuite - -private[ml] object TestingUtils extends FunSuite { - - /** - * Test whether unrelated metadata are preserved for this transformer. - * This attaches extra metadata to a column, transforms the column, and check to ensure the - * extra metadata have not changed. - * @param data Input dataset - * @param transformer Transformer to test - * @param inputCol Unique input column for Transformer. This must be the ONLY input column. - * @param outputCol Output column to test for metadata presence. - */ - def testPreserveMetadata( - data: DataFrame, - transformer: Transformer, - inputCol: String, - outputCol: String): Unit = { - // Create some fake metadata - val origMetadata = data.schema(inputCol).metadata - val metaKey = "__testPreserveMetadata__fake_key" - val metaValue = 12345 - assert(!origMetadata.contains(metaKey), - s"Unit test with testPreserveMetadata will fail since metadata key was present: $metaKey") - val newMetadata = - new MetadataBuilder().withMetadata(origMetadata).putLong(metaKey, metaValue).build() - // Add metadata to the inputCol - val withMetadata = data.select(data(inputCol).as(inputCol, newMetadata)) - // Transform, and ensure extra metadata was not affected - val transformed = transformer.transform(withMetadata) - val transMetadata = transformed.schema(outputCol).metadata - assert(transMetadata.contains(metaKey), - "Unit test with testPreserveMetadata failed; extra metadata key was not present.") - assert(transMetadata.getLong(metaKey) === metaValue, - "Unit test with testPreserveMetadata failed; extra metadata value was wrong." + - s" Expected $metaValue but found ${transMetadata.getLong(metaKey)}") - } -} diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala index 2839c4c289b2d..24755e9ff46fc 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala @@ -270,4 +270,48 @@ class VectorsSuite extends FunSuite { assert(Vectors.norm(sv, 3.7) ~== math.pow(sv.toArray.foldLeft(0.0)((a, v) => a + math.pow(math.abs(v), 3.7)), 1.0 / 3.7) relTol 1E-8) } + + test("Vector numActive and numNonzeros") { + val dv = Vectors.dense(0.0, 2.0, 3.0, 0.0) + assert(dv.numActives === 4) + assert(dv.numNonzeros === 2) + + val sv = Vectors.sparse(4, Array(0, 1, 2), Array(0.0, 2.0, 3.0)) + assert(sv.numActives === 3) + assert(sv.numNonzeros === 2) + } + + test("Vector toSparse and toDense") { + val dv0 = Vectors.dense(0.0, 2.0, 3.0, 0.0) + assert(dv0.toDense === dv0) + val dv0s = dv0.toSparse + assert(dv0s.numActives === 2) + assert(dv0s === dv0) + + val sv0 = Vectors.sparse(4, Array(0, 1, 2), Array(0.0, 2.0, 3.0)) + assert(sv0.toDense === sv0) + val sv0s = sv0.toSparse + assert(sv0s.numActives === 2) + assert(sv0s === sv0) + } + + test("Vector.compressed") { + val dv0 = Vectors.dense(1.0, 2.0, 3.0, 0.0) + val dv0c = dv0.compressed.asInstanceOf[DenseVector] + assert(dv0c === dv0) + + val dv1 = Vectors.dense(0.0, 2.0, 0.0, 0.0) + val dv1c = dv1.compressed.asInstanceOf[SparseVector] + assert(dv1 === dv1c) + assert(dv1c.numActives === 1) + + val sv0 = Vectors.sparse(4, Array(1, 2), Array(2.0, 0.0)) + val sv0c = sv0.compressed.asInstanceOf[SparseVector] + assert(sv0 === sv0c) + assert(sv0c.numActives === 1) + + val sv1 = Vectors.sparse(4, Array(0, 1, 2), Array(1.0, 2.0, 3.0)) + val sv1c = sv1.compressed.asInstanceOf[DenseVector] + assert(sv1 === sv1c) + } } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala new file mode 100644 index 0000000000000..0b646cf1ce6c4 --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala @@ -0,0 +1,84 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import org.dmg.pmml.RegressionModel +import org.dmg.pmml.RegressionNormalizationMethodType +import org.scalatest.FunSuite + +import org.apache.spark.mllib.classification.LogisticRegressionModel +import org.apache.spark.mllib.classification.SVMModel +import org.apache.spark.mllib.util.LinearDataGenerator + +class BinaryClassificationPMMLModelExportSuite extends FunSuite { + + test("logistic regression PMML export") { + val linearInput = LinearDataGenerator.generateLinearInput(3.0, Array(10.0, 10.0), 1, 17) + val logisticRegressionModel = + new LogisticRegressionModel(linearInput(0).features, linearInput(0).label) + + val logisticModelExport = PMMLModelExportFactory.createPMMLModelExport(logisticRegressionModel) + + // assert that the PMML format is as expected + assert(logisticModelExport.isInstanceOf[PMMLModelExport]) + val pmml = logisticModelExport.asInstanceOf[PMMLModelExport].getPmml + assert(pmml.getHeader.getDescription === "logistic regression") + // check that the number of fields match the weights size + assert(pmml.getDataDictionary.getNumberOfFields === logisticRegressionModel.weights.size + 1) + // This verify that there is a model attached to the pmml object and the model is a regression + // one. It also verifies that the pmml model has a regression table (for target category 1) + // with the same number of predictors of the model weights. + val pmmlRegressionModel = pmml.getModels.get(0).asInstanceOf[RegressionModel] + assert(pmmlRegressionModel.getRegressionTables.get(0).getTargetCategory === "1") + assert(pmmlRegressionModel.getRegressionTables.get(0).getNumericPredictors.size + === logisticRegressionModel.weights.size) + // verify if there is a second table with target category 0 and no predictors + assert(pmmlRegressionModel.getRegressionTables.get(1).getTargetCategory === "0") + assert(pmmlRegressionModel.getRegressionTables.get(1).getNumericPredictors.size === 0) + // ensure logistic regression has normalization method set to LOGIT + assert(pmmlRegressionModel.getNormalizationMethod() == RegressionNormalizationMethodType.LOGIT) + } + + test("linear SVM PMML export") { + val linearInput = LinearDataGenerator.generateLinearInput(3.0, Array(10.0, 10.0), 1, 17) + val svmModel = new SVMModel(linearInput(0).features, linearInput(0).label) + + val svmModelExport = PMMLModelExportFactory.createPMMLModelExport(svmModel) + + // assert that the PMML format is as expected + assert(svmModelExport.isInstanceOf[PMMLModelExport]) + val pmml = svmModelExport.getPmml + assert(pmml.getHeader.getDescription + === "linear SVM") + // check that the number of fields match the weights size + assert(pmml.getDataDictionary.getNumberOfFields === svmModel.weights.size + 1) + // This verify that there is a model attached to the pmml object and the model is a regression + // one. It also verifies that the pmml model has a regression table (for target category 1) + // with the same number of predictors of the model weights. + val pmmlRegressionModel = pmml.getModels.get(0).asInstanceOf[RegressionModel] + assert(pmmlRegressionModel.getRegressionTables.get(0).getTargetCategory === "1") + assert(pmmlRegressionModel.getRegressionTables.get(0).getNumericPredictors.size + === svmModel.weights.size) + // verify if there is a second table with target category 0 and no predictors + assert(pmmlRegressionModel.getRegressionTables.get(1).getTargetCategory === "0") + assert(pmmlRegressionModel.getRegressionTables.get(1).getNumericPredictors.size === 0) + // ensure linear SVM has normalization method set to NONE + assert(pmmlRegressionModel.getNormalizationMethod() == RegressionNormalizationMethodType.NONE) + } + +} diff --git a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala new file mode 100644 index 0000000000000..f9afbd888dfc5 --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala @@ -0,0 +1,84 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import org.dmg.pmml.RegressionModel +import org.scalatest.FunSuite + +import org.apache.spark.mllib.regression.{LassoModel, LinearRegressionModel, RidgeRegressionModel} +import org.apache.spark.mllib.util.LinearDataGenerator + +class GeneralizedLinearPMMLModelExportSuite extends FunSuite { + + test("linear regression PMML export") { + val linearInput = LinearDataGenerator.generateLinearInput(3.0, Array(10.0, 10.0), 1, 17) + val linearRegressionModel = + new LinearRegressionModel(linearInput(0).features, linearInput(0).label) + val linearModelExport = PMMLModelExportFactory.createPMMLModelExport(linearRegressionModel) + // assert that the PMML format is as expected + assert(linearModelExport.isInstanceOf[PMMLModelExport]) + val pmml = linearModelExport.getPmml + assert(pmml.getHeader.getDescription === "linear regression") + // check that the number of fields match the weights size + assert(pmml.getDataDictionary.getNumberOfFields === linearRegressionModel.weights.size + 1) + // This verifies that there is a model attached to the pmml object and the model is a regression + // one. It also verifies that the pmml model has a regression table with the same number of + // predictors of the model weights. + val pmmlRegressionModel = pmml.getModels.get(0).asInstanceOf[RegressionModel] + assert(pmmlRegressionModel.getRegressionTables.get(0).getNumericPredictors.size + === linearRegressionModel.weights.size) + } + + test("ridge regression PMML export") { + val linearInput = LinearDataGenerator.generateLinearInput(3.0, Array(10.0, 10.0), 1, 17) + val ridgeRegressionModel = + new RidgeRegressionModel(linearInput(0).features, linearInput(0).label) + val ridgeModelExport = PMMLModelExportFactory.createPMMLModelExport(ridgeRegressionModel) + // assert that the PMML format is as expected + assert(ridgeModelExport.isInstanceOf[PMMLModelExport]) + val pmml = ridgeModelExport.getPmml + assert(pmml.getHeader.getDescription === "ridge regression") + // check that the number of fields match the weights size + assert(pmml.getDataDictionary.getNumberOfFields === ridgeRegressionModel.weights.size + 1) + // This verify that there is a model attached to the pmml object and the model is a regression + // one. It also verifies that the pmml model has a regression table with the same number of + // predictors of the model weights. + val pmmlRegressionModel = pmml.getModels.get(0).asInstanceOf[RegressionModel] + assert(pmmlRegressionModel.getRegressionTables.get(0).getNumericPredictors.size + === ridgeRegressionModel.weights.size) + } + + test("lasso PMML export") { + val linearInput = LinearDataGenerator.generateLinearInput(3.0, Array(10.0, 10.0), 1, 17) + val lassoModel = new LassoModel(linearInput(0).features, linearInput(0).label) + val lassoModelExport = PMMLModelExportFactory.createPMMLModelExport(lassoModel) + // assert that the PMML format is as expected + assert(lassoModelExport.isInstanceOf[PMMLModelExport]) + val pmml = lassoModelExport.getPmml + assert(pmml.getHeader.getDescription === "lasso regression") + // check that the number of fields match the weights size + assert(pmml.getDataDictionary.getNumberOfFields === lassoModel.weights.size + 1) + // This verify that there is a model attached to the pmml object and the model is a regression + // one. It also verifies that the pmml model has a regression table with the same number of + // predictors of the model weights. + val pmmlRegressionModel = pmml.getModels.get(0).asInstanceOf[RegressionModel] + assert(pmmlRegressionModel.getRegressionTables.get(0).getNumericPredictors.size + === lassoModel.weights.size) + } + +} diff --git a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala new file mode 100644 index 0000000000000..b985d0446d7b0 --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala @@ -0,0 +1,49 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import org.dmg.pmml.ClusteringModel +import org.scalatest.FunSuite + +import org.apache.spark.mllib.clustering.KMeansModel +import org.apache.spark.mllib.linalg.Vectors + +class KMeansPMMLModelExportSuite extends FunSuite { + + test("KMeansPMMLModelExport generate PMML format") { + val clusterCenters = Array( + Vectors.dense(1.0, 2.0, 6.0), + Vectors.dense(1.0, 3.0, 0.0), + Vectors.dense(1.0, 4.0, 6.0)) + val kmeansModel = new KMeansModel(clusterCenters) + + val modelExport = PMMLModelExportFactory.createPMMLModelExport(kmeansModel) + + // assert that the PMML format is as expected + assert(modelExport.isInstanceOf[PMMLModelExport]) + val pmml = modelExport.asInstanceOf[PMMLModelExport].getPmml + assert(pmml.getHeader.getDescription === "k-means clustering") + // check that the number of fields match the single vector size + assert(pmml.getDataDictionary.getNumberOfFields === clusterCenters(0).size) + // This verify that there is a model attached to the pmml object and the model is a clustering + // one. It also verifies that the pmml model has the same number of clusters of the spark model. + val pmmlClusteringModel = pmml.getModels.get(0).asInstanceOf[ClusteringModel] + assert(pmmlClusteringModel.getNumberOfClusters === clusterCenters.length) + } + +} diff --git a/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactorySuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactorySuite.scala new file mode 100644 index 0000000000000..f28a4ac8ad01f --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactorySuite.scala @@ -0,0 +1,95 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.mllib.pmml.export + +import org.scalatest.FunSuite + +import org.apache.spark.mllib.classification.{LogisticRegressionModel, SVMModel} +import org.apache.spark.mllib.clustering.KMeansModel +import org.apache.spark.mllib.linalg.Vectors +import org.apache.spark.mllib.regression.{LassoModel, LinearRegressionModel, RidgeRegressionModel} +import org.apache.spark.mllib.util.LinearDataGenerator + +class PMMLModelExportFactorySuite extends FunSuite { + + test("PMMLModelExportFactory create KMeansPMMLModelExport when passing a KMeansModel") { + val clusterCenters = Array( + Vectors.dense(1.0, 2.0, 6.0), + Vectors.dense(1.0, 3.0, 0.0), + Vectors.dense(1.0, 4.0, 6.0)) + val kmeansModel = new KMeansModel(clusterCenters) + + val modelExport = PMMLModelExportFactory.createPMMLModelExport(kmeansModel) + + assert(modelExport.isInstanceOf[KMeansPMMLModelExport]) + } + + test("PMMLModelExportFactory create GeneralizedLinearPMMLModelExport when passing a " + + "LinearRegressionModel, RidgeRegressionModel or LassoModel") { + val linearInput = LinearDataGenerator.generateLinearInput(3.0, Array(10.0, 10.0), 1, 17) + + val linearRegressionModel = + new LinearRegressionModel(linearInput(0).features, linearInput(0).label) + val linearModelExport = PMMLModelExportFactory.createPMMLModelExport(linearRegressionModel) + assert(linearModelExport.isInstanceOf[GeneralizedLinearPMMLModelExport]) + + val ridgeRegressionModel = + new RidgeRegressionModel(linearInput(0).features, linearInput(0).label) + val ridgeModelExport = PMMLModelExportFactory.createPMMLModelExport(ridgeRegressionModel) + assert(ridgeModelExport.isInstanceOf[GeneralizedLinearPMMLModelExport]) + + val lassoModel = new LassoModel(linearInput(0).features, linearInput(0).label) + val lassoModelExport = PMMLModelExportFactory.createPMMLModelExport(lassoModel) + assert(lassoModelExport.isInstanceOf[GeneralizedLinearPMMLModelExport]) + } + + test("PMMLModelExportFactory create BinaryClassificationPMMLModelExport " + + "when passing a LogisticRegressionModel or SVMModel") { + val linearInput = LinearDataGenerator.generateLinearInput(3.0, Array(10.0, 10.0), 1, 17) + + val logisticRegressionModel = + new LogisticRegressionModel(linearInput(0).features, linearInput(0).label) + val logisticRegressionModelExport = + PMMLModelExportFactory.createPMMLModelExport(logisticRegressionModel) + assert(logisticRegressionModelExport.isInstanceOf[BinaryClassificationPMMLModelExport]) + + val svmModel = new SVMModel(linearInput(0).features, linearInput(0).label) + val svmModelExport = PMMLModelExportFactory.createPMMLModelExport(svmModel) + assert(svmModelExport.isInstanceOf[BinaryClassificationPMMLModelExport]) + } + + test("PMMLModelExportFactory throw IllegalArgumentException " + + "when passing a Multinomial Logistic Regression") { + /** 3 classes, 2 features */ + val multiclassLogisticRegressionModel = new LogisticRegressionModel( + weights = Vectors.dense(0.1, 0.2, 0.3, 0.4), intercept = 1.0, + numFeatures = 2, numClasses = 3) + + intercept[IllegalArgumentException] { + PMMLModelExportFactory.createPMMLModelExport(multiclassLogisticRegressionModel) + } + } + + test("PMMLModelExportFactory throw IllegalArgumentException when passing an unsupported model") { + val invalidModel = new Object + + intercept[IllegalArgumentException] { + PMMLModelExportFactory.createPMMLModelExport(invalidModel) + } + } +} diff --git a/mllib/src/test/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctionsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctionsSuite.scala index 1ac7c12c4e8e6..cb8fe4dba96f5 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctionsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/rdd/MLPairRDDFunctionsSuite.scala @@ -24,13 +24,13 @@ import org.apache.spark.mllib.rdd.MLPairRDDFunctions._ class MLPairRDDFunctionsSuite extends FunSuite with MLlibTestSparkContext { test("topByKey") { - val topMap = sc.parallelize(Array((1, 1), (1, 2), (3, 2), (3, 7), (3, 5), (5, 1), (5, 3)), 2) + val topMap = sc.parallelize(Array((1, 1), (1, 2), (3, 2), (3, 7), (5, 1), (3, 5)), 2) .topByKey(2) .collectAsMap() assert(topMap.size === 3) assert(topMap(1) === Array(2, 1)) assert(topMap(3) === Array(7, 5)) - assert(topMap(5) === Array(3, 1)) + assert(topMap(5) === Array(1)) } } diff --git a/mllib/src/test/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModelSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModelSuite.scala index 9801e87576744..2c92866f3893d 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModelSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModelSuite.scala @@ -72,4 +72,24 @@ class MatrixFactorizationModelSuite extends FunSuite with MLlibTestSparkContext Utils.deleteRecursively(tempDir) } } + + test("batch predict API recommendProductsForUsers") { + val model = new MatrixFactorizationModel(rank, userFeatures, prodFeatures) + val topK = 10 + val recommendations = model.recommendProductsForUsers(topK).collectAsMap() + + assert(recommendations(0)(0).rating ~== 17.0 relTol 1e-14) + assert(recommendations(1)(0).rating ~== 39.0 relTol 1e-14) + } + + test("batch predict API recommendUsersForProducts") { + val model = new MatrixFactorizationModel(rank, userFeatures, prodFeatures) + val topK = 10 + val recommendations = model.recommendUsersForProducts(topK).collectAsMap() + + assert(recommendations(2)(0).user == 1) + assert(recommendations(2)(0).rating ~== 39.0 relTol 1e-14) + assert(recommendations(2)(1).user == 0) + assert(recommendations(2)(1).rating ~== 17.0 relTol 1e-14) + } } diff --git a/network/common/src/main/java/org/apache/spark/network/TransportContext.java b/network/common/src/main/java/org/apache/spark/network/TransportContext.java index 3fe69b1bd8851..b8d073fa16b4b 100644 --- a/network/common/src/main/java/org/apache/spark/network/TransportContext.java +++ b/network/common/src/main/java/org/apache/spark/network/TransportContext.java @@ -36,6 +36,7 @@ import org.apache.spark.network.server.TransportChannelHandler; import org.apache.spark.network.server.TransportRequestHandler; import org.apache.spark.network.server.TransportServer; +import org.apache.spark.network.server.TransportServerBootstrap; import org.apache.spark.network.util.NettyUtils; import org.apache.spark.network.util.TransportConf; @@ -82,13 +83,21 @@ public TransportClientFactory createClientFactory() { } /** Create a server which will attempt to bind to a specific port. */ - public TransportServer createServer(int port) { - return new TransportServer(this, port); + public TransportServer createServer(int port, List bootstraps) { + return new TransportServer(this, port, rpcHandler, bootstraps); } /** Creates a new server, binding to any available ephemeral port. */ + public TransportServer createServer(List bootstraps) { + return createServer(0, bootstraps); + } + public TransportServer createServer() { - return new TransportServer(this, 0); + return createServer(0, Lists.newArrayList()); + } + + public TransportChannelHandler initializePipeline(SocketChannel channel) { + return initializePipeline(channel, rpcHandler); } /** @@ -96,13 +105,18 @@ public TransportServer createServer() { * has a {@link org.apache.spark.network.server.TransportChannelHandler} to handle request or * response messages. * + * @param channel The channel to initialize. + * @param channelRpcHandler The RPC handler to use for the channel. + * * @return Returns the created TransportChannelHandler, which includes a TransportClient that can * be used to communicate on this channel. The TransportClient is directly associated with a * ChannelHandler to ensure all users of the same channel get the same TransportClient object. */ - public TransportChannelHandler initializePipeline(SocketChannel channel) { + public TransportChannelHandler initializePipeline( + SocketChannel channel, + RpcHandler channelRpcHandler) { try { - TransportChannelHandler channelHandler = createChannelHandler(channel); + TransportChannelHandler channelHandler = createChannelHandler(channel, channelRpcHandler); channel.pipeline() .addLast("encoder", encoder) .addLast("frameDecoder", NettyUtils.createFrameDecoder()) @@ -123,7 +137,7 @@ public TransportChannelHandler initializePipeline(SocketChannel channel) { * ResponseMessages. The channel is expected to have been successfully created, though certain * properties (such as the remoteAddress()) may not be available yet. */ - private TransportChannelHandler createChannelHandler(Channel channel) { + private TransportChannelHandler createChannelHandler(Channel channel, RpcHandler rpcHandler) { TransportResponseHandler responseHandler = new TransportResponseHandler(channel); TransportClient client = new TransportClient(channel, responseHandler); TransportRequestHandler requestHandler = new TransportRequestHandler(channel, client, diff --git a/network/common/src/main/java/org/apache/spark/network/client/TransportClientBootstrap.java b/network/common/src/main/java/org/apache/spark/network/client/TransportClientBootstrap.java index 65e8020e34121..eaae2ee043c5a 100644 --- a/network/common/src/main/java/org/apache/spark/network/client/TransportClientBootstrap.java +++ b/network/common/src/main/java/org/apache/spark/network/client/TransportClientBootstrap.java @@ -17,6 +17,8 @@ package org.apache.spark.network.client; +import io.netty.channel.Channel; + /** * A bootstrap which is executed on a TransportClient before it is returned to the user. * This enables an initial exchange of information (e.g., SASL authentication tokens) on a once-per- @@ -28,5 +30,5 @@ */ public interface TransportClientBootstrap { /** Performs the bootstrapping operation, throwing an exception on failure. */ - public void doBootstrap(TransportClient client) throws RuntimeException; + void doBootstrap(TransportClient client, Channel channel) throws RuntimeException; } diff --git a/network/common/src/main/java/org/apache/spark/network/client/TransportClientFactory.java b/network/common/src/main/java/org/apache/spark/network/client/TransportClientFactory.java index d26b9b4d6055f..4952ffb44bb8b 100644 --- a/network/common/src/main/java/org/apache/spark/network/client/TransportClientFactory.java +++ b/network/common/src/main/java/org/apache/spark/network/client/TransportClientFactory.java @@ -172,12 +172,14 @@ private TransportClient createClient(InetSocketAddress address) throws IOExcepti .option(ChannelOption.ALLOCATOR, pooledAllocator); final AtomicReference clientRef = new AtomicReference(); + final AtomicReference channelRef = new AtomicReference(); bootstrap.handler(new ChannelInitializer() { @Override public void initChannel(SocketChannel ch) { TransportChannelHandler clientHandler = context.initializePipeline(ch); clientRef.set(clientHandler.getClient()); + channelRef.set(ch); } }); @@ -192,6 +194,7 @@ public void initChannel(SocketChannel ch) { } TransportClient client = clientRef.get(); + Channel channel = channelRef.get(); assert client != null : "Channel future completed successfully with null client"; // Execute any client bootstraps synchronously before marking the Client as successful. @@ -199,7 +202,7 @@ public void initChannel(SocketChannel ch) { logger.debug("Connection to {} successful, running bootstraps...", address); try { for (TransportClientBootstrap clientBootstrap : clientBootstraps) { - clientBootstrap.doBootstrap(client); + clientBootstrap.doBootstrap(client, channel); } } catch (Exception e) { // catch non-RuntimeExceptions too as bootstrap may be written in Scala long bootstrapTimeMs = (System.nanoTime() - preBootstrap) / 1000000; diff --git a/network/common/src/main/java/org/apache/spark/network/sasl/SaslClientBootstrap.java b/network/common/src/main/java/org/apache/spark/network/sasl/SaslClientBootstrap.java index 33aa1344345ff..185ba2ef3bb1f 100644 --- a/network/common/src/main/java/org/apache/spark/network/sasl/SaslClientBootstrap.java +++ b/network/common/src/main/java/org/apache/spark/network/sasl/SaslClientBootstrap.java @@ -17,8 +17,12 @@ package org.apache.spark.network.sasl; +import javax.security.sasl.Sasl; +import javax.security.sasl.SaslException; + import io.netty.buffer.ByteBuf; import io.netty.buffer.Unpooled; +import io.netty.channel.Channel; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -33,14 +37,24 @@ public class SaslClientBootstrap implements TransportClientBootstrap { private final Logger logger = LoggerFactory.getLogger(SaslClientBootstrap.class); + private final boolean encrypt; private final TransportConf conf; private final String appId; private final SecretKeyHolder secretKeyHolder; public SaslClientBootstrap(TransportConf conf, String appId, SecretKeyHolder secretKeyHolder) { + this(conf, appId, secretKeyHolder, false); + } + + public SaslClientBootstrap( + TransportConf conf, + String appId, + SecretKeyHolder secretKeyHolder, + boolean encrypt) { this.conf = conf; this.appId = appId; this.secretKeyHolder = secretKeyHolder; + this.encrypt = encrypt; } /** @@ -49,8 +63,8 @@ public SaslClientBootstrap(TransportConf conf, String appId, SecretKeyHolder sec * due to mismatch. */ @Override - public void doBootstrap(TransportClient client) { - SparkSaslClient saslClient = new SparkSaslClient(appId, secretKeyHolder); + public void doBootstrap(TransportClient client, Channel channel) { + SparkSaslClient saslClient = new SparkSaslClient(appId, secretKeyHolder, encrypt); try { byte[] payload = saslClient.firstToken(); @@ -62,13 +76,26 @@ public void doBootstrap(TransportClient client) { byte[] response = client.sendRpcSync(buf.array(), conf.saslRTTimeoutMs()); payload = saslClient.response(response); } + + if (encrypt) { + if (!SparkSaslServer.QOP_AUTH_CONF.equals(saslClient.getNegotiatedProperty(Sasl.QOP))) { + throw new RuntimeException( + new SaslException("Encryption requests by negotiated non-encrypted connection.")); + } + SaslEncryption.addToChannel(channel, saslClient, conf.maxSaslEncryptedBlockSize()); + saslClient = null; + logger.debug("Channel {} configured for SASL encryption.", client); + } } finally { - try { - // Once authentication is complete, the server will trust all remaining communication. - saslClient.dispose(); - } catch (RuntimeException e) { - logger.error("Error while disposing SASL client", e); + if (saslClient != null) { + try { + // Once authentication is complete, the server will trust all remaining communication. + saslClient.dispose(); + } catch (RuntimeException e) { + logger.error("Error while disposing SASL client", e); + } } } } + } diff --git a/network/common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java b/network/common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java new file mode 100644 index 0000000000000..127335e4d35fb --- /dev/null +++ b/network/common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java @@ -0,0 +1,291 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.sasl; + +import java.io.IOException; +import java.nio.ByteBuffer; +import java.nio.channels.WritableByteChannel; +import java.util.List; + +import com.google.common.annotations.VisibleForTesting; +import com.google.common.base.Preconditions; +import io.netty.buffer.ByteBuf; +import io.netty.buffer.Unpooled; +import io.netty.channel.Channel; +import io.netty.channel.ChannelHandlerContext; +import io.netty.channel.ChannelOutboundHandlerAdapter; +import io.netty.channel.ChannelPromise; +import io.netty.channel.FileRegion; +import io.netty.handler.codec.MessageToMessageDecoder; +import io.netty.util.AbstractReferenceCounted; +import io.netty.util.ReferenceCountUtil; + +import org.apache.spark.network.util.ByteArrayWritableChannel; +import org.apache.spark.network.util.NettyUtils; + +/** + * Provides SASL-based encription for transport channels. The single method exposed by this + * class installs the needed channel handlers on a connected channel. + */ +class SaslEncryption { + + @VisibleForTesting + static final String ENCRYPTION_HANDLER_NAME = "saslEncryption"; + + /** + * Adds channel handlers that perform encryption / decryption of data using SASL. + * + * @param channel The channel. + * @param backend The SASL backend. + * @param maxOutboundBlockSize Max size in bytes of outgoing encrypted blocks, to control + * memory usage. + */ + static void addToChannel( + Channel channel, + SaslEncryptionBackend backend, + int maxOutboundBlockSize) { + channel.pipeline() + .addFirst(ENCRYPTION_HANDLER_NAME, new EncryptionHandler(backend, maxOutboundBlockSize)) + .addFirst("saslDecryption", new DecryptionHandler(backend)) + .addFirst("saslFrameDecoder", NettyUtils.createFrameDecoder()); + } + + private static class EncryptionHandler extends ChannelOutboundHandlerAdapter { + + private final int maxOutboundBlockSize; + private final SaslEncryptionBackend backend; + + EncryptionHandler(SaslEncryptionBackend backend, int maxOutboundBlockSize) { + this.backend = backend; + this.maxOutboundBlockSize = maxOutboundBlockSize; + } + + /** + * Wrap the incoming message in an implementation that will perform encryption lazily. This is + * needed to guarantee ordering of the outgoing encrypted packets - they need to be decrypted in + * the same order, and netty doesn't have an atomic ChannelHandlerContext.write() API, so it + * does not guarantee any ordering. + */ + @Override + public void write(ChannelHandlerContext ctx, Object msg, ChannelPromise promise) + throws Exception { + + ctx.write(new EncryptedMessage(backend, msg, maxOutboundBlockSize), promise); + } + + @Override + public void handlerRemoved(ChannelHandlerContext ctx) throws Exception { + try { + backend.dispose(); + } finally { + super.handlerRemoved(ctx); + } + } + + } + + private static class DecryptionHandler extends MessageToMessageDecoder { + + private final SaslEncryptionBackend backend; + + DecryptionHandler(SaslEncryptionBackend backend) { + this.backend = backend; + } + + @Override + protected void decode(ChannelHandlerContext ctx, ByteBuf msg, List out) + throws Exception { + + byte[] data; + int offset; + int length = msg.readableBytes(); + if (msg.hasArray()) { + data = msg.array(); + offset = msg.arrayOffset(); + msg.skipBytes(length); + } else { + data = new byte[length]; + msg.readBytes(data); + offset = 0; + } + + out.add(Unpooled.wrappedBuffer(backend.unwrap(data, offset, length))); + } + + } + + @VisibleForTesting + static class EncryptedMessage extends AbstractReferenceCounted implements FileRegion { + + private final SaslEncryptionBackend backend; + private final boolean isByteBuf; + private final ByteBuf buf; + private final FileRegion region; + + /** + * A channel used to buffer input data for encryption. The channel has an upper size bound + * so that if the input is larger than the allowed buffer, it will be broken into multiple + * chunks. + */ + private final ByteArrayWritableChannel byteChannel; + + private ByteBuf currentHeader; + private ByteBuffer currentChunk; + private long currentChunkSize; + private long currentReportedBytes; + private long unencryptedChunkSize; + private long transferred; + + EncryptedMessage(SaslEncryptionBackend backend, Object msg, int maxOutboundBlockSize) { + Preconditions.checkArgument(msg instanceof ByteBuf || msg instanceof FileRegion, + "Unrecognized message type: %s", msg.getClass().getName()); + this.backend = backend; + this.isByteBuf = msg instanceof ByteBuf; + this.buf = isByteBuf ? (ByteBuf) msg : null; + this.region = isByteBuf ? null : (FileRegion) msg; + this.byteChannel = new ByteArrayWritableChannel(maxOutboundBlockSize); + } + + /** + * Returns the size of the original (unencrypted) message. + * + * This makes assumptions about how netty treats FileRegion instances, because there's no way + * to know beforehand what will be the size of the encrypted message. Namely, it assumes + * that netty will try to transfer data from this message while + * transfered() < count(). So these two methods return, technically, wrong data, + * but netty doesn't know better. + */ + @Override + public long count() { + return isByteBuf ? buf.readableBytes() : region.count(); + } + + @Override + public long position() { + return 0; + } + + /** + * Returns an approximation of the amount of data transferred. See {@link #count()}. + */ + @Override + public long transfered() { + return transferred; + } + + /** + * Transfers data from the original message to the channel, encrypting it in the process. + * + * This method also breaks down the original message into smaller chunks when needed. This + * is done to keep memory usage under control. This avoids having to copy the whole message + * data into memory at once, and can avoid ballooning memory usage when transferring large + * messages such as shuffle blocks. + * + * The {@link #transfered()} counter also behaves a little funny, in that it won't go forward + * until a whole chunk has been written. This is done because the code can't use the actual + * number of bytes written to the channel as the transferred count (see {@link #count()}). + * Instead, once an encrypted chunk is written to the output (including its header), the + * size of the original block will be added to the {@link #transfered()} amount. + */ + @Override + public long transferTo(final WritableByteChannel target, final long position) + throws IOException { + + Preconditions.checkArgument(position == transfered(), "Invalid position."); + + long reportedWritten = 0L; + long actuallyWritten = 0L; + do { + if (currentChunk == null) { + nextChunk(); + } + + if (currentHeader.readableBytes() > 0) { + int bytesWritten = target.write(currentHeader.nioBuffer()); + currentHeader.skipBytes(bytesWritten); + actuallyWritten += bytesWritten; + if (currentHeader.readableBytes() > 0) { + // Break out of loop if there are still header bytes left to write. + break; + } + } + + actuallyWritten += target.write(currentChunk); + if (!currentChunk.hasRemaining()) { + // Only update the count of written bytes once a full chunk has been written. + // See method javadoc. + long chunkBytesRemaining = unencryptedChunkSize - currentReportedBytes; + reportedWritten += chunkBytesRemaining; + transferred += chunkBytesRemaining; + currentHeader.release(); + currentHeader = null; + currentChunk = null; + currentChunkSize = 0; + currentReportedBytes = 0; + } + } while (currentChunk == null && transfered() + reportedWritten < count()); + + // Returning 0 triggers a backoff mechanism in netty which may harm performance. Instead, + // we return 1 until we can (i.e. until the reported count would actually match the size + // of the current chunk), at which point we resort to returning 0 so that the counts still + // match, at the cost of some performance. That situation should be rare, though. + if (reportedWritten != 0L) { + return reportedWritten; + } + + if (actuallyWritten > 0 && currentReportedBytes < currentChunkSize - 1) { + transferred += 1L; + currentReportedBytes += 1L; + return 1L; + } + + return 0L; + } + + private void nextChunk() throws IOException { + byteChannel.reset(); + if (isByteBuf) { + int copied = byteChannel.write(buf.nioBuffer()); + buf.skipBytes(copied); + } else { + region.transferTo(byteChannel, region.transfered()); + } + + byte[] encrypted = backend.wrap(byteChannel.getData(), 0, byteChannel.length()); + this.currentChunk = ByteBuffer.wrap(encrypted); + this.currentChunkSize = encrypted.length; + this.currentHeader = Unpooled.copyLong(8 + currentChunkSize); + this.unencryptedChunkSize = byteChannel.length(); + } + + @Override + protected void deallocate() { + if (currentHeader != null) { + currentHeader.release(); + } + if (buf != null) { + buf.release(); + } + if (region != null) { + region.release(); + } + } + + } + +} diff --git a/network/common/src/main/java/org/apache/spark/network/sasl/SaslEncryptionBackend.java b/network/common/src/main/java/org/apache/spark/network/sasl/SaslEncryptionBackend.java new file mode 100644 index 0000000000000..89b78bc7e1df1 --- /dev/null +++ b/network/common/src/main/java/org/apache/spark/network/sasl/SaslEncryptionBackend.java @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.sasl; + +import javax.security.sasl.SaslException; + +interface SaslEncryptionBackend { + + /** Disposes of resources used by the backend. */ + void dispose(); + + /** Encrypt data. */ + byte[] wrap(byte[] data, int offset, int len) throws SaslException; + + /** Decrypt data. */ + byte[] unwrap(byte[] data, int offset, int len) throws SaslException; + +} diff --git a/network/common/src/main/java/org/apache/spark/network/sasl/SaslRpcHandler.java b/network/common/src/main/java/org/apache/spark/network/sasl/SaslRpcHandler.java index 026cbd260d16c..be6165caf3c74 100644 --- a/network/common/src/main/java/org/apache/spark/network/sasl/SaslRpcHandler.java +++ b/network/common/src/main/java/org/apache/spark/network/sasl/SaslRpcHandler.java @@ -17,10 +17,10 @@ package org.apache.spark.network.sasl; -import java.util.concurrent.ConcurrentMap; +import javax.security.sasl.Sasl; -import com.google.common.collect.Maps; import io.netty.buffer.Unpooled; +import io.netty.channel.Channel; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -28,6 +28,7 @@ import org.apache.spark.network.client.TransportClient; import org.apache.spark.network.server.RpcHandler; import org.apache.spark.network.server.StreamManager; +import org.apache.spark.network.util.TransportConf; /** * RPC Handler which performs SASL authentication before delegating to a child RPC handler. @@ -37,8 +38,14 @@ * Note that the authentication process consists of multiple challenge-response pairs, each of * which are individual RPCs. */ -public class SaslRpcHandler extends RpcHandler { - private final Logger logger = LoggerFactory.getLogger(SaslRpcHandler.class); +class SaslRpcHandler extends RpcHandler { + private static final Logger logger = LoggerFactory.getLogger(SaslRpcHandler.class); + + /** Transport configuration. */ + private final TransportConf conf; + + /** The client channel. */ + private final Channel channel; /** RpcHandler we will delegate to for authenticated connections. */ private final RpcHandler delegate; @@ -46,19 +53,25 @@ public class SaslRpcHandler extends RpcHandler { /** Class which provides secret keys which are shared by server and client on a per-app basis. */ private final SecretKeyHolder secretKeyHolder; - /** Maps each channel to its SASL authentication state. */ - private final ConcurrentMap channelAuthenticationMap; + private SparkSaslServer saslServer; + private boolean isComplete; - public SaslRpcHandler(RpcHandler delegate, SecretKeyHolder secretKeyHolder) { + SaslRpcHandler( + TransportConf conf, + Channel channel, + RpcHandler delegate, + SecretKeyHolder secretKeyHolder) { + this.conf = conf; + this.channel = channel; this.delegate = delegate; this.secretKeyHolder = secretKeyHolder; - this.channelAuthenticationMap = Maps.newConcurrentMap(); + this.saslServer = null; + this.isComplete = false; } @Override public void receive(TransportClient client, byte[] message, RpcResponseCallback callback) { - SparkSaslServer saslServer = channelAuthenticationMap.get(client); - if (saslServer != null && saslServer.isComplete()) { + if (isComplete) { // Authentication complete, delegate to base handler. delegate.receive(client, message, callback); return; @@ -68,15 +81,30 @@ public void receive(TransportClient client, byte[] message, RpcResponseCallback if (saslServer == null) { // First message in the handshake, setup the necessary state. - saslServer = new SparkSaslServer(saslMessage.appId, secretKeyHolder); - channelAuthenticationMap.put(client, saslServer); + saslServer = new SparkSaslServer(saslMessage.appId, secretKeyHolder, + conf.saslServerAlwaysEncrypt()); } byte[] response = saslServer.response(saslMessage.payload); + callback.onSuccess(response); + + // Setup encryption after the SASL response is sent, otherwise the client can't parse the + // response. It's ok to change the channel pipeline here since we are processing an incoming + // message, so the pipeline is busy and no new incoming messages will be fed to it before this + // method returns. This assumes that the code ensures, through other means, that no outbound + // messages are being written to the channel while negotiation is still going on. if (saslServer.isComplete()) { logger.debug("SASL authentication successful for channel {}", client); + isComplete = true; + if (SparkSaslServer.QOP_AUTH_CONF.equals(saslServer.getNegotiatedProperty(Sasl.QOP))) { + logger.debug("Enabling encryption for channel {}", client); + SaslEncryption.addToChannel(channel, saslServer, conf.maxSaslEncryptedBlockSize()); + saslServer = null; + } else { + saslServer.dispose(); + saslServer = null; + } } - callback.onSuccess(response); } @Override @@ -86,9 +114,9 @@ public StreamManager getStreamManager() { @Override public void connectionTerminated(TransportClient client) { - SparkSaslServer saslServer = channelAuthenticationMap.remove(client); if (saslServer != null) { saslServer.dispose(); } } + } diff --git a/network/common/src/main/java/org/apache/spark/network/sasl/SaslServerBootstrap.java b/network/common/src/main/java/org/apache/spark/network/sasl/SaslServerBootstrap.java new file mode 100644 index 0000000000000..f2f983856f444 --- /dev/null +++ b/network/common/src/main/java/org/apache/spark/network/sasl/SaslServerBootstrap.java @@ -0,0 +1,49 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.sasl; + +import io.netty.channel.Channel; + +import org.apache.spark.network.server.RpcHandler; +import org.apache.spark.network.server.TransportServerBootstrap; +import org.apache.spark.network.util.TransportConf; + +/** + * A bootstrap which is executed on a TransportServer's client channel once a client connects + * to the server. This allows customizing the client channel to allow for things such as SASL + * authentication. + */ +public class SaslServerBootstrap implements TransportServerBootstrap { + + private final TransportConf conf; + private final SecretKeyHolder secretKeyHolder; + + public SaslServerBootstrap(TransportConf conf, SecretKeyHolder secretKeyHolder) { + this.conf = conf; + this.secretKeyHolder = secretKeyHolder; + } + + /** + * Wrap the given application handler in a SaslRpcHandler that will handle the initial SASL + * negotiation. + */ + public RpcHandler doBootstrap(Channel channel, RpcHandler rpcHandler) { + return new SaslRpcHandler(conf, channel, rpcHandler, secretKeyHolder); + } + +} diff --git a/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslClient.java b/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslClient.java index 9abad1f30a259..94685e91b862e 100644 --- a/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslClient.java +++ b/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslClient.java @@ -17,6 +17,8 @@ package org.apache.spark.network.sasl; +import java.io.IOException; +import java.util.Map; import javax.security.auth.callback.Callback; import javax.security.auth.callback.CallbackHandler; import javax.security.auth.callback.NameCallback; @@ -27,9 +29,9 @@ import javax.security.sasl.Sasl; import javax.security.sasl.SaslClient; import javax.security.sasl.SaslException; -import java.io.IOException; import com.google.common.base.Throwables; +import com.google.common.collect.ImmutableMap; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -40,19 +42,25 @@ * initial state to the "authenticated" state. This client initializes the protocol via a * firstToken, which is then followed by a set of challenges and responses. */ -public class SparkSaslClient { +public class SparkSaslClient implements SaslEncryptionBackend { private final Logger logger = LoggerFactory.getLogger(SparkSaslClient.class); private final String secretKeyId; private final SecretKeyHolder secretKeyHolder; + private final String expectedQop; private SaslClient saslClient; - public SparkSaslClient(String secretKeyId, SecretKeyHolder secretKeyHolder) { + public SparkSaslClient(String secretKeyId, SecretKeyHolder secretKeyHolder, boolean encrypt) { this.secretKeyId = secretKeyId; this.secretKeyHolder = secretKeyHolder; + this.expectedQop = encrypt ? QOP_AUTH_CONF : QOP_AUTH; + + Map saslProps = ImmutableMap.builder() + .put(Sasl.QOP, expectedQop) + .build(); try { this.saslClient = Sasl.createSaslClient(new String[] { DIGEST }, null, null, DEFAULT_REALM, - SASL_PROPS, new ClientCallbackHandler()); + saslProps, new ClientCallbackHandler()); } catch (SaslException e) { throw Throwables.propagate(e); } @@ -76,6 +84,11 @@ public synchronized boolean isComplete() { return saslClient != null && saslClient.isComplete(); } + /** Returns the value of a negotiated property. */ + public Object getNegotiatedProperty(String name) { + return saslClient.getNegotiatedProperty(name); + } + /** * Respond to server's SASL token. * @param token contains server's SASL token @@ -93,6 +106,7 @@ public synchronized byte[] response(byte[] token) { * Disposes of any system resources or security-sensitive information the * SaslClient might be using. */ + @Override public synchronized void dispose() { if (saslClient != null) { try { @@ -134,4 +148,15 @@ public void handle(Callback[] callbacks) throws IOException, UnsupportedCallback } } } + + @Override + public byte[] wrap(byte[] data, int offset, int len) throws SaslException { + return saslClient.wrap(data, offset, len); + } + + @Override + public byte[] unwrap(byte[] data, int offset, int len) throws SaslException { + return saslClient.unwrap(data, offset, len); + } + } diff --git a/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslServer.java b/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslServer.java index e87b17ead1e1a..431cb67a2ae0b 100644 --- a/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslServer.java +++ b/network/common/src/main/java/org/apache/spark/network/sasl/SparkSaslServer.java @@ -44,7 +44,7 @@ * initial state to the "authenticated" state. (It is not a server in the sense of accepting * connections on some socket.) */ -public class SparkSaslServer { +public class SparkSaslServer implements SaslEncryptionBackend { private final Logger logger = LoggerFactory.getLogger(SparkSaslServer.class); /** @@ -60,26 +60,37 @@ public class SparkSaslServer { static final String DIGEST = "DIGEST-MD5"; /** - * The quality of protection is just "auth". This means that we are doing - * authentication only, we are not supporting integrity or privacy protection of the - * communication channel after authentication. This could be changed to be configurable - * in the future. + * Quality of protection value that includes encryption. */ - static final Map SASL_PROPS = ImmutableMap.builder() - .put(Sasl.QOP, "auth") - .put(Sasl.SERVER_AUTH, "true") - .build(); + static final String QOP_AUTH_CONF = "auth-conf"; + + /** + * Quality of protection value that does not include encryption. + */ + static final String QOP_AUTH = "auth"; /** Identifier for a certain secret key within the secretKeyHolder. */ private final String secretKeyId; private final SecretKeyHolder secretKeyHolder; private SaslServer saslServer; - public SparkSaslServer(String secretKeyId, SecretKeyHolder secretKeyHolder) { + public SparkSaslServer( + String secretKeyId, + SecretKeyHolder secretKeyHolder, + boolean alwaysEncrypt) { this.secretKeyId = secretKeyId; this.secretKeyHolder = secretKeyHolder; + + // Sasl.QOP is a comma-separated list of supported values. The value that allows encryption + // is listed first since it's preferred over the non-encrypted one (if the client also + // lists both in the request). + String qop = alwaysEncrypt ? QOP_AUTH_CONF : String.format("%s,%s", QOP_AUTH_CONF, QOP_AUTH); + Map saslProps = ImmutableMap.builder() + .put(Sasl.SERVER_AUTH, "true") + .put(Sasl.QOP, qop) + .build(); try { - this.saslServer = Sasl.createSaslServer(DIGEST, null, DEFAULT_REALM, SASL_PROPS, + this.saslServer = Sasl.createSaslServer(DIGEST, null, DEFAULT_REALM, saslProps, new DigestCallbackHandler()); } catch (SaslException e) { throw Throwables.propagate(e); @@ -93,6 +104,11 @@ public synchronized boolean isComplete() { return saslServer != null && saslServer.isComplete(); } + /** Returns the value of a negotiated property. */ + public Object getNegotiatedProperty(String name) { + return saslServer.getNegotiatedProperty(name); + } + /** * Used to respond to server SASL tokens. * @param token Server's SASL token @@ -110,6 +126,7 @@ public synchronized byte[] response(byte[] token) { * Disposes of any system resources or security-sensitive information the * SaslServer might be using. */ + @Override public synchronized void dispose() { if (saslServer != null) { try { @@ -122,6 +139,16 @@ public synchronized void dispose() { } } + @Override + public byte[] wrap(byte[] data, int offset, int len) throws SaslException { + return saslServer.wrap(data, offset, len); + } + + @Override + public byte[] unwrap(byte[] data, int offset, int len) throws SaslException { + return saslServer.unwrap(data, offset, len); + } + /** * Implementation of javax.security.auth.callback.CallbackHandler for SASL DIGEST-MD5 mechanism. */ diff --git a/network/common/src/main/java/org/apache/spark/network/server/OneForOneStreamManager.java b/network/common/src/main/java/org/apache/spark/network/server/OneForOneStreamManager.java index a6d390e13f396..c95e64e8e2cda 100644 --- a/network/common/src/main/java/org/apache/spark/network/server/OneForOneStreamManager.java +++ b/network/common/src/main/java/org/apache/spark/network/server/OneForOneStreamManager.java @@ -20,14 +20,18 @@ import java.util.Iterator; import java.util.Map; import java.util.Random; +import java.util.Set; import java.util.concurrent.ConcurrentHashMap; import java.util.concurrent.atomic.AtomicLong; +import io.netty.channel.Channel; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.apache.spark.network.buffer.ManagedBuffer; +import com.google.common.base.Preconditions; + /** * StreamManager which allows registration of an Iterator<ManagedBuffer>, which are individually * fetched as chunks by the client. Each registered buffer is one chunk. @@ -36,18 +40,21 @@ public class OneForOneStreamManager extends StreamManager { private final Logger logger = LoggerFactory.getLogger(OneForOneStreamManager.class); private final AtomicLong nextStreamId; - private final Map streams; + private final ConcurrentHashMap streams; /** State of a single stream. */ private static class StreamState { final Iterator buffers; + // The channel associated to the stream + Channel associatedChannel = null; + // Used to keep track of the index of the buffer that the user has retrieved, just to ensure // that the caller only requests each chunk one at a time, in order. int curChunk = 0; StreamState(Iterator buffers) { - this.buffers = buffers; + this.buffers = Preconditions.checkNotNull(buffers); } } @@ -58,6 +65,13 @@ public OneForOneStreamManager() { streams = new ConcurrentHashMap(); } + @Override + public void registerChannel(Channel channel, long streamId) { + if (streams.containsKey(streamId)) { + streams.get(streamId).associatedChannel = channel; + } + } + @Override public ManagedBuffer getChunk(long streamId, int chunkIndex) { StreamState state = streams.get(streamId); @@ -80,12 +94,17 @@ public ManagedBuffer getChunk(long streamId, int chunkIndex) { } @Override - public void connectionTerminated(long streamId) { - // Release all remaining buffers. - StreamState state = streams.remove(streamId); - if (state != null && state.buffers != null) { - while (state.buffers.hasNext()) { - state.buffers.next().release(); + public void connectionTerminated(Channel channel) { + // Close all streams which have been associated with the channel. + for (Map.Entry entry: streams.entrySet()) { + StreamState state = entry.getValue(); + if (state.associatedChannel == channel) { + streams.remove(entry.getKey()); + + // Release all remaining buffers. + while (state.buffers.hasNext()) { + state.buffers.next().release(); + } } } } diff --git a/network/common/src/main/java/org/apache/spark/network/server/StreamManager.java b/network/common/src/main/java/org/apache/spark/network/server/StreamManager.java index 5a9a14a180c10..929f789bf9d24 100644 --- a/network/common/src/main/java/org/apache/spark/network/server/StreamManager.java +++ b/network/common/src/main/java/org/apache/spark/network/server/StreamManager.java @@ -17,6 +17,8 @@ package org.apache.spark.network.server; +import io.netty.channel.Channel; + import org.apache.spark.network.buffer.ManagedBuffer; /** @@ -44,9 +46,18 @@ public abstract class StreamManager { public abstract ManagedBuffer getChunk(long streamId, int chunkIndex); /** - * Indicates that the TCP connection that was tied to the given stream has been terminated. After - * this occurs, we are guaranteed not to read from the stream again, so any state can be cleaned - * up. + * Associates a stream with a single client connection, which is guaranteed to be the only reader + * of the stream. The getChunk() method will be called serially on this connection and once the + * connection is closed, the stream will never be used again, enabling cleanup. + * + * This must be called before the first getChunk() on the stream, but it may be invoked multiple + * times with the same channel and stream id. + */ + public void registerChannel(Channel channel, long streamId) { } + + /** + * Indicates that the given channel has been terminated. After this occurs, we are guaranteed not + * to read from the associated streams again, so any state can be cleaned up. */ - public void connectionTerminated(long streamId) { } + public void connectionTerminated(Channel channel) { } } diff --git a/network/common/src/main/java/org/apache/spark/network/server/TransportRequestHandler.java b/network/common/src/main/java/org/apache/spark/network/server/TransportRequestHandler.java index 1580180cc17e9..e5159ab56d0d4 100644 --- a/network/common/src/main/java/org/apache/spark/network/server/TransportRequestHandler.java +++ b/network/common/src/main/java/org/apache/spark/network/server/TransportRequestHandler.java @@ -17,10 +17,7 @@ package org.apache.spark.network.server; -import java.util.Set; - import com.google.common.base.Throwables; -import com.google.common.collect.Sets; import io.netty.channel.Channel; import io.netty.channel.ChannelFuture; import io.netty.channel.ChannelFutureListener; @@ -62,9 +59,6 @@ public class TransportRequestHandler extends MessageHandler { /** Returns each chunk part of a stream. */ private final StreamManager streamManager; - /** List of all stream ids that have been read on this handler, used for cleanup. */ - private final Set streamIds; - public TransportRequestHandler( Channel channel, TransportClient reverseClient, @@ -73,7 +67,6 @@ public TransportRequestHandler( this.reverseClient = reverseClient; this.rpcHandler = rpcHandler; this.streamManager = rpcHandler.getStreamManager(); - this.streamIds = Sets.newHashSet(); } @Override @@ -82,10 +75,7 @@ public void exceptionCaught(Throwable cause) { @Override public void channelUnregistered() { - // Inform the StreamManager that these streams will no longer be read from. - for (long streamId : streamIds) { - streamManager.connectionTerminated(streamId); - } + streamManager.connectionTerminated(channel); rpcHandler.connectionTerminated(reverseClient); } @@ -102,12 +92,12 @@ public void handle(RequestMessage request) { private void processFetchRequest(final ChunkFetchRequest req) { final String client = NettyUtils.getRemoteAddress(channel); - streamIds.add(req.streamChunkId.streamId); logger.trace("Received req from {} to fetch block {}", client, req.streamChunkId); ManagedBuffer buf; try { + streamManager.registerChannel(channel, req.streamChunkId.streamId); buf = streamManager.getChunk(req.streamChunkId.streamId, req.streamChunkId.chunkIndex); } catch (Exception e) { logger.error(String.format( diff --git a/network/common/src/main/java/org/apache/spark/network/server/TransportServer.java b/network/common/src/main/java/org/apache/spark/network/server/TransportServer.java index b7ce8541e565e..941ef95772e16 100644 --- a/network/common/src/main/java/org/apache/spark/network/server/TransportServer.java +++ b/network/common/src/main/java/org/apache/spark/network/server/TransportServer.java @@ -19,8 +19,11 @@ import java.io.Closeable; import java.net.InetSocketAddress; +import java.util.List; import java.util.concurrent.TimeUnit; +import com.google.common.base.Preconditions; +import com.google.common.collect.Lists; import io.netty.bootstrap.ServerBootstrap; import io.netty.buffer.PooledByteBufAllocator; import io.netty.channel.ChannelFuture; @@ -44,15 +47,23 @@ public class TransportServer implements Closeable { private final TransportContext context; private final TransportConf conf; + private final RpcHandler appRpcHandler; + private final List bootstraps; private ServerBootstrap bootstrap; private ChannelFuture channelFuture; private int port = -1; /** Creates a TransportServer that binds to the given port, or to any available if 0. */ - public TransportServer(TransportContext context, int portToBind) { + public TransportServer( + TransportContext context, + int portToBind, + RpcHandler appRpcHandler, + List bootstraps) { this.context = context; this.conf = context.getConf(); + this.appRpcHandler = appRpcHandler; + this.bootstraps = Lists.newArrayList(Preconditions.checkNotNull(bootstraps)); init(portToBind); } @@ -95,7 +106,11 @@ private void init(int portToBind) { bootstrap.childHandler(new ChannelInitializer() { @Override protected void initChannel(SocketChannel ch) throws Exception { - context.initializePipeline(ch); + RpcHandler rpcHandler = appRpcHandler; + for (TransportServerBootstrap bootstrap : bootstraps) { + rpcHandler = bootstrap.doBootstrap(ch, rpcHandler); + } + context.initializePipeline(ch, rpcHandler); } }); diff --git a/network/common/src/main/java/org/apache/spark/network/server/TransportServerBootstrap.java b/network/common/src/main/java/org/apache/spark/network/server/TransportServerBootstrap.java new file mode 100644 index 0000000000000..05803ab1bb059 --- /dev/null +++ b/network/common/src/main/java/org/apache/spark/network/server/TransportServerBootstrap.java @@ -0,0 +1,36 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.network.server; + +import io.netty.channel.Channel; + +/** + * A bootstrap which is executed on a TransportServer's client channel once a client connects + * to the server. This allows customizing the client channel to allow for things such as SASL + * authentication. + */ +public interface TransportServerBootstrap { + /** + * Customizes the channel to include new features, if needed. + * + * @param channel The connected channel opened by the client. + * @param rpcHandler The RPC handler for the server. + * @return The RPC handler to use for the channel. + */ + RpcHandler doBootstrap(Channel channel, RpcHandler rpcHandler); +} diff --git a/network/common/src/test/java/org/apache/spark/network/ByteArrayWritableChannel.java b/network/common/src/main/java/org/apache/spark/network/util/ByteArrayWritableChannel.java similarity index 70% rename from network/common/src/test/java/org/apache/spark/network/ByteArrayWritableChannel.java rename to network/common/src/main/java/org/apache/spark/network/util/ByteArrayWritableChannel.java index b525ed69fc9fb..b1415720045e2 100644 --- a/network/common/src/test/java/org/apache/spark/network/ByteArrayWritableChannel.java +++ b/network/common/src/main/java/org/apache/spark/network/util/ByteArrayWritableChannel.java @@ -15,11 +15,14 @@ * limitations under the License. */ -package org.apache.spark.network; +package org.apache.spark.network.util; import java.nio.ByteBuffer; import java.nio.channels.WritableByteChannel; +/** + * A writable channel that stores the written data in a byte array in memory. + */ public class ByteArrayWritableChannel implements WritableByteChannel { private final byte[] data; @@ -27,19 +30,30 @@ public class ByteArrayWritableChannel implements WritableByteChannel { public ByteArrayWritableChannel(int size) { this.data = new byte[size]; - this.offset = 0; } public byte[] getData() { return data; } + public int length() { + return offset; + } + + /** Resets the channel so that writing to it will overwrite the existing buffer. */ + public void reset() { + offset = 0; + } + + /** + * Reads from the given buffer into the internal byte array. + */ @Override public int write(ByteBuffer src) { - int available = src.remaining(); - src.get(data, offset, available); - offset += available; - return available; + int toTransfer = Math.min(src.remaining(), data.length - offset); + src.get(data, offset, toTransfer); + offset += toTransfer; + return toTransfer; } @Override diff --git a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java index 0aef7f1987315..3b2eff377955a 100644 --- a/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java +++ b/network/common/src/main/java/org/apache/spark/network/util/TransportConf.java @@ -17,6 +17,8 @@ package org.apache.spark.network.util; +import com.google.common.primitives.Ints; + /** * A central location that tracks all the settings we expose to users. */ @@ -112,4 +114,20 @@ public boolean lazyFileDescriptor() { public int portMaxRetries() { return conf.getInt("spark.port.maxRetries", 16); } + + /** + * Maximum number of bytes to be encrypted at a time when SASL encryption is enabled. + */ + public int maxSaslEncryptedBlockSize() { + return Ints.checkedCast(JavaUtils.byteStringAsBytes( + conf.get("spark.network.sasl.maxEncryptedBlockSize", "64k"))); + } + + /** + * Whether the server should enforce encryption on SASL-authenticated connections. + */ + public boolean saslServerAlwaysEncrypt() { + return conf.getBoolean("spark.network.sasl.serverAlwaysEncrypt", false); + } + } diff --git a/network/common/src/test/java/org/apache/spark/network/ProtocolSuite.java b/network/common/src/test/java/org/apache/spark/network/ProtocolSuite.java index 860dd6d9b3915..d500bc3c98a78 100644 --- a/network/common/src/test/java/org/apache/spark/network/ProtocolSuite.java +++ b/network/common/src/test/java/org/apache/spark/network/ProtocolSuite.java @@ -39,6 +39,7 @@ import org.apache.spark.network.protocol.RpcRequest; import org.apache.spark.network.protocol.RpcResponse; import org.apache.spark.network.protocol.StreamChunkId; +import org.apache.spark.network.util.ByteArrayWritableChannel; import org.apache.spark.network.util.NettyUtils; public class ProtocolSuite { diff --git a/network/common/src/test/java/org/apache/spark/network/protocol/MessageWithHeaderSuite.java b/network/common/src/test/java/org/apache/spark/network/protocol/MessageWithHeaderSuite.java index ff985096d72d5..6c98e733b462f 100644 --- a/network/common/src/test/java/org/apache/spark/network/protocol/MessageWithHeaderSuite.java +++ b/network/common/src/test/java/org/apache/spark/network/protocol/MessageWithHeaderSuite.java @@ -29,7 +29,7 @@ import static org.junit.Assert.*; -import org.apache.spark.network.ByteArrayWritableChannel; +import org.apache.spark.network.util.ByteArrayWritableChannel; public class MessageWithHeaderSuite { diff --git a/network/common/src/test/java/org/apache/spark/network/sasl/SparkSaslSuite.java b/network/common/src/test/java/org/apache/spark/network/sasl/SparkSaslSuite.java index 23b4e06f064e1..be6632bb8cf49 100644 --- a/network/common/src/test/java/org/apache/spark/network/sasl/SparkSaslSuite.java +++ b/network/common/src/test/java/org/apache/spark/network/sasl/SparkSaslSuite.java @@ -17,12 +17,47 @@ package org.apache.spark.network.sasl; -import static org.junit.Assert.assertFalse; -import static org.junit.Assert.assertTrue; -import static org.junit.Assert.fail; +import static com.google.common.base.Charsets.UTF_8; +import static org.junit.Assert.*; +import static org.mockito.Mockito.*; +import java.io.File; +import java.util.Arrays; +import java.util.List; +import java.util.Random; +import java.util.concurrent.TimeoutException; +import java.util.concurrent.TimeUnit; +import java.util.concurrent.atomic.AtomicReference; +import javax.security.sasl.SaslException; + +import com.google.common.collect.Lists; +import com.google.common.io.ByteStreams; +import com.google.common.io.Files; +import io.netty.buffer.ByteBuf; +import io.netty.buffer.Unpooled; +import io.netty.channel.Channel; +import io.netty.channel.ChannelHandlerContext; +import io.netty.channel.ChannelOutboundHandlerAdapter; +import io.netty.channel.ChannelPromise; import org.junit.Test; +import org.mockito.invocation.InvocationOnMock; +import org.mockito.stubbing.Answer; +import org.apache.spark.network.TestUtils; +import org.apache.spark.network.TransportContext; +import org.apache.spark.network.buffer.FileSegmentManagedBuffer; +import org.apache.spark.network.buffer.ManagedBuffer; +import org.apache.spark.network.client.ChunkReceivedCallback; +import org.apache.spark.network.client.RpcResponseCallback; +import org.apache.spark.network.client.TransportClient; +import org.apache.spark.network.client.TransportClientBootstrap; +import org.apache.spark.network.server.RpcHandler; +import org.apache.spark.network.server.StreamManager; +import org.apache.spark.network.server.TransportServer; +import org.apache.spark.network.server.TransportServerBootstrap; +import org.apache.spark.network.util.ByteArrayWritableChannel; +import org.apache.spark.network.util.SystemPropertyConfigProvider; +import org.apache.spark.network.util.TransportConf; /** * Jointly tests SparkSaslClient and SparkSaslServer, as both are black boxes. @@ -44,8 +79,8 @@ public String getSecretKey(String appId) { @Test public void testMatching() { - SparkSaslClient client = new SparkSaslClient("shared-secret", secretKeyHolder); - SparkSaslServer server = new SparkSaslServer("shared-secret", secretKeyHolder); + SparkSaslClient client = new SparkSaslClient("shared-secret", secretKeyHolder, false); + SparkSaslServer server = new SparkSaslServer("shared-secret", secretKeyHolder, false); assertFalse(client.isComplete()); assertFalse(server.isComplete()); @@ -64,11 +99,10 @@ public void testMatching() { assertFalse(client.isComplete()); } - @Test public void testNonMatching() { - SparkSaslClient client = new SparkSaslClient("my-secret", secretKeyHolder); - SparkSaslServer server = new SparkSaslServer("your-secret", secretKeyHolder); + SparkSaslClient client = new SparkSaslClient("my-secret", secretKeyHolder, false); + SparkSaslServer server = new SparkSaslServer("your-secret", secretKeyHolder, false); assertFalse(client.isComplete()); assertFalse(server.isComplete()); @@ -86,4 +120,312 @@ public void testNonMatching() { assertFalse(server.isComplete()); } } + + @Test + public void testSaslAuthentication() throws Exception { + testBasicSasl(false); + } + + @Test + public void testSaslEncryption() throws Exception { + testBasicSasl(true); + } + + private void testBasicSasl(boolean encrypt) throws Exception { + RpcHandler rpcHandler = mock(RpcHandler.class); + doAnswer(new Answer() { + @Override + public Void answer(InvocationOnMock invocation) { + byte[] message = (byte[]) invocation.getArguments()[1]; + RpcResponseCallback cb = (RpcResponseCallback) invocation.getArguments()[2]; + assertEquals("Ping", new String(message, UTF_8)); + cb.onSuccess("Pong".getBytes(UTF_8)); + return null; + } + }) + .when(rpcHandler) + .receive(any(TransportClient.class), any(byte[].class), any(RpcResponseCallback.class)); + + SaslTestCtx ctx = new SaslTestCtx(rpcHandler, encrypt, false); + try { + byte[] response = ctx.client.sendRpcSync("Ping".getBytes(UTF_8), TimeUnit.SECONDS.toMillis(10)); + assertEquals("Pong", new String(response, UTF_8)); + } finally { + ctx.close(); + } + } + + @Test + public void testEncryptedMessage() throws Exception { + SaslEncryptionBackend backend = mock(SaslEncryptionBackend.class); + byte[] data = new byte[1024]; + new Random().nextBytes(data); + when(backend.wrap(any(byte[].class), anyInt(), anyInt())).thenReturn(data); + + ByteBuf msg = Unpooled.buffer(); + try { + msg.writeBytes(data); + + // Create a channel with a really small buffer compared to the data. This means that on each + // call, the outbound data will not be fully written, so the write() method should return a + // dummy count to keep the channel alive when possible. + ByteArrayWritableChannel channel = new ByteArrayWritableChannel(32); + + SaslEncryption.EncryptedMessage emsg = + new SaslEncryption.EncryptedMessage(backend, msg, 1024); + long count = emsg.transferTo(channel, emsg.transfered()); + assertTrue(count < data.length); + assertTrue(count > 0); + + // Here, the output buffer is full so nothing should be transferred. + assertEquals(0, emsg.transferTo(channel, emsg.transfered())); + + // Now there's room in the buffer, but not enough to transfer all the remaining data, + // so the dummy count should be returned. + channel.reset(); + assertEquals(1, emsg.transferTo(channel, emsg.transfered())); + + // Eventually, the whole message should be transferred. + for (int i = 0; i < data.length / 32 - 2; i++) { + channel.reset(); + assertEquals(1, emsg.transferTo(channel, emsg.transfered())); + } + + channel.reset(); + count = emsg.transferTo(channel, emsg.transfered()); + assertTrue("Unexpected count: " + count, count > 1 && count < data.length); + assertEquals(data.length, emsg.transfered()); + } finally { + msg.release(); + } + } + + @Test + public void testEncryptedMessageChunking() throws Exception { + File file = File.createTempFile("sasltest", ".txt"); + try { + TransportConf conf = new TransportConf(new SystemPropertyConfigProvider()); + + byte[] data = new byte[8 * 1024]; + new Random().nextBytes(data); + Files.write(data, file); + + SaslEncryptionBackend backend = mock(SaslEncryptionBackend.class); + // It doesn't really matter what we return here, as long as it's not null. + when(backend.wrap(any(byte[].class), anyInt(), anyInt())).thenReturn(data); + + FileSegmentManagedBuffer msg = new FileSegmentManagedBuffer(conf, file, 0, file.length()); + SaslEncryption.EncryptedMessage emsg = + new SaslEncryption.EncryptedMessage(backend, msg.convertToNetty(), data.length / 8); + + ByteArrayWritableChannel channel = new ByteArrayWritableChannel(data.length); + while (emsg.transfered() < emsg.count()) { + channel.reset(); + emsg.transferTo(channel, emsg.transfered()); + } + + verify(backend, times(8)).wrap(any(byte[].class), anyInt(), anyInt()); + } finally { + file.delete(); + } + } + + @Test + public void testFileRegionEncryption() throws Exception { + final String blockSizeConf = "spark.network.sasl.maxEncryptedBlockSize"; + System.setProperty(blockSizeConf, "1k"); + + final AtomicReference response = new AtomicReference(); + final File file = File.createTempFile("sasltest", ".txt"); + SaslTestCtx ctx = null; + try { + final TransportConf conf = new TransportConf(new SystemPropertyConfigProvider()); + StreamManager sm = mock(StreamManager.class); + when(sm.getChunk(anyLong(), anyInt())).thenAnswer(new Answer() { + @Override + public ManagedBuffer answer(InvocationOnMock invocation) { + return new FileSegmentManagedBuffer(conf, file, 0, file.length()); + } + }); + + RpcHandler rpcHandler = mock(RpcHandler.class); + when(rpcHandler.getStreamManager()).thenReturn(sm); + + byte[] data = new byte[8 * 1024]; + new Random().nextBytes(data); + Files.write(data, file); + + ctx = new SaslTestCtx(rpcHandler, true, false); + + final Object lock = new Object(); + + ChunkReceivedCallback callback = mock(ChunkReceivedCallback.class); + doAnswer(new Answer() { + @Override + public Void answer(InvocationOnMock invocation) { + response.set((ManagedBuffer) invocation.getArguments()[1]); + response.get().retain(); + synchronized (lock) { + lock.notifyAll(); + } + return null; + } + }).when(callback).onSuccess(anyInt(), any(ManagedBuffer.class)); + + synchronized (lock) { + ctx.client.fetchChunk(0, 0, callback); + lock.wait(10 * 1000); + } + + verify(callback, times(1)).onSuccess(anyInt(), any(ManagedBuffer.class)); + verify(callback, never()).onFailure(anyInt(), any(Throwable.class)); + + byte[] received = ByteStreams.toByteArray(response.get().createInputStream()); + assertTrue(Arrays.equals(data, received)); + } finally { + file.delete(); + if (ctx != null) { + ctx.close(); + } + if (response.get() != null) { + response.get().release(); + } + System.clearProperty(blockSizeConf); + } + } + + @Test + public void testServerAlwaysEncrypt() throws Exception { + final String alwaysEncryptConfName = "spark.network.sasl.serverAlwaysEncrypt"; + System.setProperty(alwaysEncryptConfName, "true"); + + SaslTestCtx ctx = null; + try { + ctx = new SaslTestCtx(mock(RpcHandler.class), false, false); + fail("Should have failed to connect without encryption."); + } catch (Exception e) { + assertTrue(e.getCause() instanceof SaslException); + } finally { + if (ctx != null) { + ctx.close(); + } + System.clearProperty(alwaysEncryptConfName); + } + } + + @Test + public void testDataEncryptionIsActuallyEnabled() throws Exception { + // This test sets up an encrypted connection but then, using a client bootstrap, removes + // the encryption handler from the client side. This should cause the server to not be + // able to understand RPCs sent to it and thus close the connection. + SaslTestCtx ctx = null; + try { + ctx = new SaslTestCtx(mock(RpcHandler.class), true, true); + ctx.client.sendRpcSync("Ping".getBytes(UTF_8), TimeUnit.SECONDS.toMillis(10)); + fail("Should have failed to send RPC to server."); + } catch (Exception e) { + assertFalse(e.getCause() instanceof TimeoutException); + } finally { + if (ctx != null) { + ctx.close(); + } + } + } + + private static class SaslTestCtx { + + final TransportClient client; + final TransportServer server; + + private final boolean encrypt; + private final boolean disableClientEncryption; + private final EncryptionCheckerBootstrap checker; + + SaslTestCtx( + RpcHandler rpcHandler, + boolean encrypt, + boolean disableClientEncryption) + throws Exception { + + TransportConf conf = new TransportConf(new SystemPropertyConfigProvider()); + + SecretKeyHolder keyHolder = mock(SecretKeyHolder.class); + when(keyHolder.getSaslUser(anyString())).thenReturn("user"); + when(keyHolder.getSecretKey(anyString())).thenReturn("secret"); + + TransportContext ctx = new TransportContext(conf, rpcHandler); + + this.checker = new EncryptionCheckerBootstrap(); + this.server = ctx.createServer(Arrays.asList(new SaslServerBootstrap(conf, keyHolder), + checker)); + + try { + List clientBootstraps = Lists.newArrayList(); + clientBootstraps.add(new SaslClientBootstrap(conf, "user", keyHolder, encrypt)); + if (disableClientEncryption) { + clientBootstraps.add(new EncryptionDisablerBootstrap()); + } + + this.client = ctx.createClientFactory(clientBootstraps) + .createClient(TestUtils.getLocalHost(), server.getPort()); + } catch (Exception e) { + close(); + throw e; + } + + this.encrypt = encrypt; + this.disableClientEncryption = disableClientEncryption; + } + + void close() { + if (!disableClientEncryption) { + assertEquals(encrypt, checker.foundEncryptionHandler); + } + if (client != null) { + client.close(); + } + if (server != null) { + server.close(); + } + } + + } + + private static class EncryptionCheckerBootstrap extends ChannelOutboundHandlerAdapter + implements TransportServerBootstrap { + + boolean foundEncryptionHandler; + + @Override + public void write(ChannelHandlerContext ctx, Object msg, ChannelPromise promise) + throws Exception { + if (!foundEncryptionHandler) { + foundEncryptionHandler = + ctx.channel().pipeline().get(SaslEncryption.ENCRYPTION_HANDLER_NAME) != null; + } + ctx.write(msg, promise); + } + + @Override + public void handlerRemoved(ChannelHandlerContext ctx) throws Exception { + super.handlerRemoved(ctx); + } + + @Override + public RpcHandler doBootstrap(Channel channel, RpcHandler rpcHandler) { + channel.pipeline().addFirst("encryptionChecker", this); + return rpcHandler; + } + + } + + private static class EncryptionDisablerBootstrap implements TransportClientBootstrap { + + @Override + public void doBootstrap(TransportClient client, Channel channel) { + channel.pipeline().remove(SaslEncryption.ENCRYPTION_HANDLER_NAME); + } + + } + } diff --git a/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleClient.java b/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleClient.java index 6e8018b723dc6..612bce571a493 100644 --- a/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleClient.java +++ b/network/shuffle/src/main/java/org/apache/spark/network/shuffle/ExternalShuffleClient.java @@ -20,6 +20,7 @@ import java.io.IOException; import java.util.List; +import com.google.common.base.Preconditions; import com.google.common.collect.Lists; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -46,6 +47,7 @@ public class ExternalShuffleClient extends ShuffleClient { private final TransportConf conf; private final boolean saslEnabled; + private final boolean saslEncryptionEnabled; private final SecretKeyHolder secretKeyHolder; private TransportClientFactory clientFactory; @@ -58,10 +60,15 @@ public class ExternalShuffleClient extends ShuffleClient { public ExternalShuffleClient( TransportConf conf, SecretKeyHolder secretKeyHolder, - boolean saslEnabled) { + boolean saslEnabled, + boolean saslEncryptionEnabled) { + Preconditions.checkArgument( + !saslEncryptionEnabled || saslEnabled, + "SASL encryption can only be enabled if SASL is also enabled."); this.conf = conf; this.secretKeyHolder = secretKeyHolder; this.saslEnabled = saslEnabled; + this.saslEncryptionEnabled = saslEncryptionEnabled; } @Override @@ -70,7 +77,7 @@ public void init(String appId) { TransportContext context = new TransportContext(conf, new NoOpRpcHandler()); List bootstraps = Lists.newArrayList(); if (saslEnabled) { - bootstraps.add(new SaslClientBootstrap(conf, appId, secretKeyHolder)); + bootstraps.add(new SaslClientBootstrap(conf, appId, secretKeyHolder, saslEncryptionEnabled)); } clientFactory = context.createClientFactory(bootstraps); } diff --git a/network/shuffle/src/test/java/org/apache/spark/network/sasl/SaslIntegrationSuite.java b/network/shuffle/src/test/java/org/apache/spark/network/sasl/SaslIntegrationSuite.java index d25283e46ef96..382f613ecbb1b 100644 --- a/network/shuffle/src/test/java/org/apache/spark/network/sasl/SaslIntegrationSuite.java +++ b/network/shuffle/src/test/java/org/apache/spark/network/sasl/SaslIntegrationSuite.java @@ -18,6 +18,7 @@ package org.apache.spark.network.sasl; import java.io.IOException; +import java.util.Arrays; import com.google.common.collect.Lists; import org.junit.After; @@ -37,6 +38,7 @@ import org.apache.spark.network.server.RpcHandler; import org.apache.spark.network.server.StreamManager; import org.apache.spark.network.server.TransportServer; +import org.apache.spark.network.server.TransportServerBootstrap; import org.apache.spark.network.shuffle.ExternalShuffleBlockHandler; import org.apache.spark.network.util.SystemPropertyConfigProvider; import org.apache.spark.network.util.TransportConf; @@ -72,10 +74,11 @@ public String getSecretKey(String appId) { @BeforeClass public static void beforeAll() throws IOException { SecretKeyHolder secretKeyHolder = new TestSecretKeyHolder("good-key"); - SaslRpcHandler handler = new SaslRpcHandler(new TestRpcHandler(), secretKeyHolder); conf = new TransportConf(new SystemPropertyConfigProvider()); - context = new TransportContext(conf, handler); - server = context.createServer(); + context = new TransportContext(conf, new TestRpcHandler()); + + TransportServerBootstrap bootstrap = new SaslServerBootstrap(conf, secretKeyHolder); + server = context.createServer(Arrays.asList(bootstrap)); } diff --git a/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleIntegrationSuite.java b/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleIntegrationSuite.java index 02c10bcb7b261..39aa49911d9cb 100644 --- a/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleIntegrationSuite.java +++ b/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleIntegrationSuite.java @@ -136,7 +136,7 @@ private FetchResult fetchBlocks(String execId, String[] blockIds, int port) thro final Semaphore requestsRemaining = new Semaphore(0); - ExternalShuffleClient client = new ExternalShuffleClient(conf, null, false); + ExternalShuffleClient client = new ExternalShuffleClient(conf, null, false, false); client.init(APP_ID); client.fetchBlocks(TestUtils.getLocalHost(), port, execId, blockIds, new BlockFetchingListener() { @@ -274,7 +274,7 @@ public void testFetchNoServer() throws Exception { private void registerExecutor(String executorId, ExecutorShuffleInfo executorInfo) throws IOException { - ExternalShuffleClient client = new ExternalShuffleClient(conf, null, false); + ExternalShuffleClient client = new ExternalShuffleClient(conf, null, false, false); client.init(APP_ID); client.registerWithShuffleServer(TestUtils.getLocalHost(), server.getPort(), executorId, executorInfo); diff --git a/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleSecuritySuite.java b/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleSecuritySuite.java index 759a12910c94d..d4ec1956c1e29 100644 --- a/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleSecuritySuite.java +++ b/network/shuffle/src/test/java/org/apache/spark/network/shuffle/ExternalShuffleSecuritySuite.java @@ -18,6 +18,7 @@ package org.apache.spark.network.shuffle; import java.io.IOException; +import java.util.Arrays; import org.junit.After; import org.junit.Before; @@ -27,10 +28,11 @@ import org.apache.spark.network.TestUtils; import org.apache.spark.network.TransportContext; -import org.apache.spark.network.sasl.SaslRpcHandler; +import org.apache.spark.network.sasl.SaslServerBootstrap; import org.apache.spark.network.sasl.SecretKeyHolder; import org.apache.spark.network.server.RpcHandler; import org.apache.spark.network.server.TransportServer; +import org.apache.spark.network.server.TransportServerBootstrap; import org.apache.spark.network.shuffle.protocol.ExecutorShuffleInfo; import org.apache.spark.network.util.SystemPropertyConfigProvider; import org.apache.spark.network.util.TransportConf; @@ -42,10 +44,10 @@ public class ExternalShuffleSecuritySuite { @Before public void beforeEach() { - RpcHandler handler = new SaslRpcHandler(new ExternalShuffleBlockHandler(conf), - new TestSecretKeyHolder("my-app-id", "secret")); - TransportContext context = new TransportContext(conf, handler); - this.server = context.createServer(); + TransportContext context = new TransportContext(conf, new ExternalShuffleBlockHandler(conf)); + TransportServerBootstrap bootstrap = new SaslServerBootstrap(conf, + new TestSecretKeyHolder("my-app-id", "secret")); + this.server = context.createServer(Arrays.asList(bootstrap)); } @After @@ -58,13 +60,13 @@ public void afterEach() { @Test public void testValid() throws IOException { - validate("my-app-id", "secret"); + validate("my-app-id", "secret", false); } @Test public void testBadAppId() { try { - validate("wrong-app-id", "secret"); + validate("wrong-app-id", "secret", false); } catch (Exception e) { assertTrue(e.getMessage(), e.getMessage().contains("Wrong appId!")); } @@ -73,16 +75,21 @@ public void testBadAppId() { @Test public void testBadSecret() { try { - validate("my-app-id", "bad-secret"); + validate("my-app-id", "bad-secret", false); } catch (Exception e) { assertTrue(e.getMessage(), e.getMessage().contains("Mismatched response")); } } + @Test + public void testEncryption() throws IOException { + validate("my-app-id", "secret", true); + } + /** Creates an ExternalShuffleClient and attempts to register with the server. */ - private void validate(String appId, String secretKey) throws IOException { + private void validate(String appId, String secretKey, boolean encrypt) throws IOException { ExternalShuffleClient client = - new ExternalShuffleClient(conf, new TestSecretKeyHolder(appId, secretKey), true); + new ExternalShuffleClient(conf, new TestSecretKeyHolder(appId, secretKey), true, encrypt); client.init(appId); // Registration either succeeds or throws an exception. client.registerWithShuffleServer(TestUtils.getLocalHost(), server.getPort(), "exec0", diff --git a/network/yarn/src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java b/network/yarn/src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java index 63b21222e7b77..463f99ef3352d 100644 --- a/network/yarn/src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java +++ b/network/yarn/src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java @@ -17,9 +17,10 @@ package org.apache.spark.network.yarn; -import java.lang.Override; import java.nio.ByteBuffer; +import java.util.List; +import com.google.common.collect.Lists; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.yarn.api.records.ApplicationId; import org.apache.hadoop.yarn.api.records.ContainerId; @@ -32,10 +33,11 @@ import org.slf4j.LoggerFactory; import org.apache.spark.network.TransportContext; -import org.apache.spark.network.sasl.SaslRpcHandler; +import org.apache.spark.network.sasl.SaslServerBootstrap; import org.apache.spark.network.sasl.ShuffleSecretManager; import org.apache.spark.network.server.RpcHandler; import org.apache.spark.network.server.TransportServer; +import org.apache.spark.network.server.TransportServerBootstrap; import org.apache.spark.network.shuffle.ExternalShuffleBlockHandler; import org.apache.spark.network.util.TransportConf; import org.apache.spark.network.yarn.util.HadoopConfigProvider; @@ -103,16 +105,17 @@ protected void serviceInit(Configuration conf) { // special RPC handler that filters out unauthenticated fetch requests boolean authEnabled = conf.getBoolean(SPARK_AUTHENTICATE_KEY, DEFAULT_SPARK_AUTHENTICATE); blockHandler = new ExternalShuffleBlockHandler(transportConf); - RpcHandler rpcHandler = blockHandler; + + List bootstraps = Lists.newArrayList(); if (authEnabled) { secretManager = new ShuffleSecretManager(); - rpcHandler = new SaslRpcHandler(rpcHandler, secretManager); + bootstraps.add(new SaslServerBootstrap(transportConf, secretManager)); } int port = conf.getInt( SPARK_SHUFFLE_SERVICE_PORT_KEY, DEFAULT_SPARK_SHUFFLE_SERVICE_PORT); - TransportContext transportContext = new TransportContext(transportConf, rpcHandler); - shuffleServer = transportContext.createServer(port); + TransportContext transportContext = new TransportContext(transportConf, blockHandler); + shuffleServer = transportContext.createServer(port, bootstraps); String authEnabledString = authEnabled ? "enabled" : "not enabled"; logger.info("Started YARN shuffle service for Spark on port {}. " + "Authentication is {}.", port, authEnabledString); diff --git a/pom.xml b/pom.xml index 928f5d0f5efad..4313f940036c8 100644 --- a/pom.xml +++ b/pom.xml @@ -97,6 +97,7 @@ sql/catalyst sql/core sql/hive + unsafe assembly external/twitter external/flume @@ -116,7 +117,7 @@ 1.6 spark 2.0.1 - 0.21.0 + 0.21.1 shaded-protobuf 1.7.10 1.2.17 @@ -1215,6 +1216,7 @@ false false true + true false diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 967961c2bf5c3..bf343d4b7e40b 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -76,6 +76,34 @@ object MimaExcludes { // SPARK-7090 Introduce LDAOptimizer to LDA to further improve extensibility ProblemFilters.exclude[MissingClassProblem]( "org.apache.spark.mllib.clustering.LDA$EMOptimizer") + ) ++ Seq( + // SPARK-6756 add toSparse, toDense, numActives, numNonzeros, and compressed to Vector + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.mllib.linalg.Vector.compressed"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.mllib.linalg.Vector.toDense"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.mllib.linalg.Vector.numNonzeros"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.mllib.linalg.Vector.toSparse"), + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.mllib.linalg.Vector.numActives") + ) ++ Seq( + // This `protected[sql]` method was removed in 1.3.1 + ProblemFilters.exclude[MissingMethodProblem]( + "org.apache.spark.sql.SQLContext.checkAnalysis"), + // This `private[sql]` class was removed in 1.4.0: + ProblemFilters.exclude[MissingClassProblem]( + "org.apache.spark.sql.execution.AddExchange"), + ProblemFilters.exclude[MissingClassProblem]( + "org.apache.spark.sql.execution.AddExchange$"), + // These test support classes were moved out of src/main and into src/test: + ProblemFilters.exclude[MissingClassProblem]( + "org.apache.spark.sql.parquet.ParquetTestData"), + ProblemFilters.exclude[MissingClassProblem]( + "org.apache.spark.sql.parquet.ParquetTestData$"), + ProblemFilters.exclude[MissingClassProblem]( + "org.apache.spark.sql.parquet.TestGroupWriteSupport") ) case v if v.startsWith("1.3") => diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index 09b4976d10c26..b4431c7ee05b6 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -34,11 +34,11 @@ object BuildCommons { val allProjects@Seq(bagel, catalyst, core, graphx, hive, hiveThriftServer, mllib, repl, sql, networkCommon, networkShuffle, streaming, streamingFlumeSink, streamingFlume, streamingKafka, - streamingMqtt, streamingTwitter, streamingZeromq, launcher) = + streamingMqtt, streamingTwitter, streamingZeromq, launcher, unsafe) = Seq("bagel", "catalyst", "core", "graphx", "hive", "hive-thriftserver", "mllib", "repl", "sql", "network-common", "network-shuffle", "streaming", "streaming-flume-sink", "streaming-flume", "streaming-kafka", "streaming-mqtt", "streaming-twitter", - "streaming-zeromq", "launcher").map(ProjectRef(buildLocation, _)) + "streaming-zeromq", "launcher", "unsafe").map(ProjectRef(buildLocation, _)) val optionallyEnabledProjects@Seq(yarn, yarnStable, java8Tests, sparkGangliaLgpl, sparkKinesisAsl) = Seq("yarn", "yarn-stable", "java8-tests", "ganglia-lgpl", @@ -156,13 +156,15 @@ object SparkBuild extends PomBuild { /* Enable tests settings for all projects except examples, assembly and tools */ (allProjects ++ optionallyEnabledProjects).foreach(enable(TestSettings.settings)) - // TODO: Add Sql to mima checks - // TODO: remove launcher from this list after 1.3. - allProjects.filterNot(x => Seq(spark, sql, hive, hiveThriftServer, catalyst, repl, - networkCommon, networkShuffle, networkYarn, launcher).contains(x)).foreach { + // TODO: remove launcher from this list after 1.4.0 + allProjects.filterNot(x => Seq(spark, hive, hiveThriftServer, catalyst, repl, + networkCommon, networkShuffle, networkYarn, launcher, unsafe).contains(x)).foreach { x => enable(MimaBuild.mimaSettings(sparkHome, x))(x) } + /* Unsafe settings */ + enable(Unsafe.settings)(unsafe) + /* Enable Assembly for all assembly projects */ assemblyProjects.foreach(enable(Assembly.settings)) @@ -216,6 +218,13 @@ object SparkBuild extends PomBuild { } +object Unsafe { + lazy val settings = Seq( + // This option is needed to suppress warnings from sun.misc.Unsafe usage + javacOptions in Compile += "-XDignore.symbol.file" + ) +} + object Flume { lazy val settings = sbtavro.SbtAvro.avroSettings } @@ -424,6 +433,7 @@ object Unidoc { .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/network"))) .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/shuffle"))) .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/executor"))) + .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/unsafe"))) .map(_.filterNot(_.getCanonicalPath.contains("python"))) .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/util/collection"))) .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/sql/catalyst"))) @@ -467,7 +477,7 @@ object Unidoc { "mllib.evaluation", "mllib.feature", "mllib.random", "mllib.stat.correlation", "mllib.stat.test", "mllib.tree.impl", "mllib.tree.loss", "ml", "ml.attribute", "ml.classification", "ml.evaluation", "ml.feature", "ml.param", - "ml.tuning" + "ml.recommendation", "ml.regression", "ml.tuning" ), "-group", "Spark SQL", packageList("sql.api.java", "sql.api.java.types", "sql.hive.api.java"), "-noqualifier", "java.lang" @@ -496,6 +506,7 @@ object TestSettings { javaOptions in Test += "-Dspark.ui.enabled=false", javaOptions in Test += "-Dspark.ui.showConsoleProgress=false", javaOptions in Test += "-Dspark.driver.allowMultipleContexts=true", + javaOptions in Test += "-Dspark.unsafe.exceptionOnMemoryLeak=true", javaOptions in Test += "-Dsun.io.serialization.extendedDebugInfo=true", javaOptions in Test ++= System.getProperties.filter(_._1 startsWith "spark") .map { case (k,v) => s"-D$k=$v" }.toSeq, diff --git a/python/pyspark/context.py b/python/pyspark/context.py index b006120eb266d..31992795a9e45 100644 --- a/python/pyspark/context.py +++ b/python/pyspark/context.py @@ -267,6 +267,13 @@ def __exit__(self, type, value, trace): """ self.stop() + def setLogLevel(self, logLevel): + """ + Control our logLevel. This overrides any user-defined log settings. + Valid log levels include: ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, WARN + """ + self._jsc.setLogLevel(logLevel) + @classmethod def setSystemProperty(cls, key, value): """ diff --git a/python/pyspark/mllib/linalg.py b/python/pyspark/mllib/linalg.py index cc9a4cf8ba170..a57c0b3ae0d00 100644 --- a/python/pyspark/mllib/linalg.py +++ b/python/pyspark/mllib/linalg.py @@ -39,7 +39,8 @@ IntegerType, ByteType -__all__ = ['Vector', 'DenseVector', 'SparseVector', 'Vectors', 'DenseMatrix', 'Matrices'] +__all__ = ['Vector', 'DenseVector', 'SparseVector', 'Vectors', + 'Matrix', 'DenseMatrix', 'SparseMatrix', 'Matrices'] if sys.version_info[:2] == (2, 7): diff --git a/python/pyspark/mllib/recommendation.py b/python/pyspark/mllib/recommendation.py index 4b7d17d64e947..9c4647ddfdcfd 100644 --- a/python/pyspark/mllib/recommendation.py +++ b/python/pyspark/mllib/recommendation.py @@ -65,6 +65,13 @@ class MatrixFactorizationModel(JavaModelWrapper, JavaSaveable, JavaLoader): >>> model.userFeatures().collect() [(1, array('d', [...])), (2, array('d', [...]))] + >>> model.recommendUsers(1, 2) + [Rating(user=2, product=1, rating=1.9...), Rating(user=1, product=1, rating=1.0...)] + >>> model.recommendProducts(1, 2) + [Rating(user=1, product=2, rating=1.9...), Rating(user=1, product=1, rating=1.0...)] + >>> model.rank + 4 + >>> first_user = model.userFeatures().take(1)[0] >>> latents = first_user[1] >>> len(latents) == 4 @@ -105,9 +112,15 @@ class MatrixFactorizationModel(JavaModelWrapper, JavaSaveable, JavaLoader): ... pass """ def predict(self, user, product): + """ + Predicts rating for the given user and product. + """ return self._java_model.predict(int(user), int(product)) def predictAll(self, user_product): + """ + Returns a list of predicted ratings for input user and product pairs. + """ assert isinstance(user_product, RDD), "user_product should be RDD of (user, product)" first = user_product.first() assert len(first) == 2, "user_product should be RDD of (user, product)" @@ -115,11 +128,37 @@ def predictAll(self, user_product): return self.call("predict", user_product) def userFeatures(self): + """ + Returns a paired RDD, where the first element is the user and the + second is an array of features corresponding to that user. + """ return self.call("getUserFeatures").mapValues(lambda v: array.array('d', v)) def productFeatures(self): + """ + Returns a paired RDD, where the first element is the product and the + second is an array of features corresponding to that product. + """ return self.call("getProductFeatures").mapValues(lambda v: array.array('d', v)) + def recommendUsers(self, product, num): + """ + Recommends the top "num" number of users for a given product and returns a list + of Rating objects sorted by the predicted rating in descending order. + """ + return list(self.call("recommendUsers", product, num)) + + def recommendProducts(self, user, num): + """ + Recommends the top "num" number of products for a given user and returns a list + of Rating objects sorted by the predicted rating in descending order. + """ + return list(self.call("recommendProducts", user, num)) + + @property + def rank(self): + return self.call("rank") + @classmethod def load(cls, sc, path): model = cls._load_java(sc, path) diff --git a/python/pyspark/sql/__init__.py b/python/pyspark/sql/__init__.py index 6d54b9e49ed10..b60b991dd4d8b 100644 --- a/python/pyspark/sql/__init__.py +++ b/python/pyspark/sql/__init__.py @@ -54,7 +54,9 @@ from pyspark.sql.types import Row from pyspark.sql.context import SQLContext, HiveContext from pyspark.sql.dataframe import DataFrame, GroupedData, Column, SchemaRDD, DataFrameNaFunctions +from pyspark.sql.dataframe import DataFrameStatFunctions __all__ = [ - 'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row', 'DataFrameNaFunctions' + 'SQLContext', 'HiveContext', 'DataFrame', 'GroupedData', 'Column', 'Row', + 'DataFrameNaFunctions', 'DataFrameStatFunctions' ] diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py index 4759f5fe783ad..8ddcff8fcdf98 100644 --- a/python/pyspark/sql/dataframe.py +++ b/python/pyspark/sql/dataframe.py @@ -34,7 +34,8 @@ from pyspark.sql.types import _create_cls, _parse_datatype_json_string -__all__ = ["DataFrame", "GroupedData", "Column", "SchemaRDD", "DataFrameNaFunctions"] +__all__ = ["DataFrame", "GroupedData", "Column", "SchemaRDD", "DataFrameNaFunctions", + "DataFrameStatFunctions"] class DataFrame(object): @@ -93,6 +94,12 @@ def na(self): """ return DataFrameNaFunctions(self) + @property + def stat(self): + """Returns a :class:`DataFrameStatFunctions` for statistic functions. + """ + return DataFrameStatFunctions(self) + @ignore_unicode_prefix def toJSON(self, use_unicode=True): """Converts a :class:`DataFrame` into a :class:`RDD` of string. @@ -237,7 +244,8 @@ def explain(self, extended=False): :param extended: boolean, default ``False``. If ``False``, prints only the physical plan. >>> df.explain() - PhysicalRDD [age#0,name#1], MapPartitionsRDD[...] at mapPartitions at SQLContext.scala:... + PhysicalRDD [age#0,name#1], MapPartitionsRDD[...] at applySchemaToPythonRDD at\ + NativeMethodAccessorImpl.java:... >>> df.explain(True) == Parsed Logical Plan == @@ -425,7 +433,7 @@ def distinct(self): def sample(self, withReplacement, fraction, seed=None): """Returns a sampled subset of this :class:`DataFrame`. - >>> df.sample(False, 0.5, 97).count() + >>> df.sample(False, 0.5, 42).count() 1 """ assert fraction >= 0.0, "Negative fraction value: %s" % fraction @@ -433,6 +441,27 @@ def sample(self, withReplacement, fraction, seed=None): rdd = self._jdf.sample(withReplacement, fraction, long(seed)) return DataFrame(rdd, self.sql_ctx) + def randomSplit(self, weights, seed=None): + """Randomly splits this :class:`DataFrame` with the provided weights. + + :param weights: list of doubles as weights with which to split the DataFrame. Weights will + be normalized if they don't sum up to 1.0. + :param seed: The seed for sampling. + + >>> splits = df4.randomSplit([1.0, 2.0], 24) + >>> splits[0].count() + 1 + + >>> splits[1].count() + 3 + """ + for w in weights: + if w < 0.0: + raise ValueError("Weights must be positive. Found weight value: %s" % w) + seed = seed if seed is not None else random.randint(0, sys.maxsize) + rdd_array = self._jdf.randomSplit(_to_seq(self.sql_ctx._sc, weights), long(seed)) + return [DataFrame(rdd, self.sql_ctx) for rdd in rdd_array] + @property def dtypes(self): """Returns all column names and their data types as a list. @@ -632,7 +661,8 @@ def __getattr__(self, name): [Row(age=2), Row(age=5)] """ if name not in self.columns: - raise AttributeError("No such column: %s" % name) + raise AttributeError( + "'%s' object has no attribute '%s'" % (self.__class__.__name__, name)) jc = self._jdf.apply(name) return Column(jc) @@ -845,6 +875,40 @@ def fillna(self, value, subset=None): return DataFrame(self._jdf.na().fill(value, self._jseq(subset)), self.sql_ctx) + def cov(self, col1, col2): + """ + Calculate the sample covariance for the given columns, specified by their names, as a + double value. :func:`DataFrame.cov` and :func:`DataFrameStatFunctions.cov` are aliases. + + :param col1: The name of the first column + :param col2: The name of the second column + """ + if not isinstance(col1, str): + raise ValueError("col1 should be a string.") + if not isinstance(col2, str): + raise ValueError("col2 should be a string.") + return self._jdf.stat().cov(col1, col2) + + def freqItems(self, cols, support=None): + """ + Finding frequent items for columns, possibly with false positives. Using the + frequent element count algorithm described in + "http://dx.doi.org/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou". + :func:`DataFrame.freqItems` and :func:`DataFrameStatFunctions.freqItems` are aliases. + + :param cols: Names of the columns to calculate frequent items for as a list or tuple of + strings. + :param support: The frequency with which to consider an item 'frequent'. Default is 1%. + The support must be greater than 1e-4. + """ + if isinstance(cols, tuple): + cols = list(cols) + if not isinstance(cols, list): + raise ValueError("cols must be a list or tuple of column names as strings.") + if not support: + support = 0.01 + return DataFrame(self._jdf.stat().freqItems(_to_seq(self._sc, cols), support), self.sql_ctx) + @ignore_unicode_prefix def withColumn(self, colName, col): """Returns a new :class:`DataFrame` by adding a column. @@ -1288,6 +1352,24 @@ def fill(self, value, subset=None): fill.__doc__ = DataFrame.fillna.__doc__ +class DataFrameStatFunctions(object): + """Functionality for statistic functions with :class:`DataFrame`. + """ + + def __init__(self, df): + self.df = df + + def cov(self, col1, col2): + return self.df.cov(col1, col2) + + cov.__doc__ = DataFrame.cov.__doc__ + + def freqItems(self, cols, support=None): + return self.df.freqItems(cols, support) + + freqItems.__doc__ = DataFrame.freqItems.__doc__ + + def _test(): import doctest from pyspark.context import SparkContext diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py index 7b86655d9c82f..641220a264295 100644 --- a/python/pyspark/sql/functions.py +++ b/python/pyspark/sql/functions.py @@ -24,13 +24,20 @@ from itertools import imap as map from pyspark import SparkContext -from pyspark.rdd import _prepare_for_python_RDD +from pyspark.rdd import _prepare_for_python_RDD, ignore_unicode_prefix from pyspark.serializers import PickleSerializer, AutoBatchedSerializer from pyspark.sql.types import StringType from pyspark.sql.dataframe import Column, _to_java_column, _to_seq -__all__ = ['countDistinct', 'approxCountDistinct', 'udf'] +__all__ = [ + 'approxCountDistinct', + 'countDistinct', + 'monotonicallyIncreasingId', + 'rand', + 'randn', + 'sparkPartitionId', + 'udf'] def _create_function(name, doc=""): @@ -54,7 +61,7 @@ def _(col): 'upper': 'Converts a string expression to upper case.', 'lower': 'Converts a string expression to upper case.', 'sqrt': 'Computes the square root of the specified float value.', - 'abs': 'Computes the absolutle value.', + 'abs': 'Computes the absolute value.', 'max': 'Aggregate function: returns the maximum value of the expression in a group.', 'min': 'Aggregate function: returns the minimum value of the expression in a group.', @@ -67,7 +74,6 @@ def _(col): 'sumDistinct': 'Aggregate function: returns the sum of distinct values in the expression.', } - for _name, _doc in _functions.items(): globals()[_name] = _create_function(_name, _doc) del _name, _doc @@ -75,6 +81,24 @@ def _(col): __all__.sort() +def array(*cols): + """Creates a new array column. + + :param cols: list of column names (string) or list of :class:`Column` expressions that have + the same data type. + + >>> df.select(array('age', 'age').alias("arr")).collect() + [Row(arr=[2, 2]), Row(arr=[5, 5])] + >>> df.select(array([df.age, df.age]).alias("arr")).collect() + [Row(arr=[2, 2]), Row(arr=[5, 5])] + """ + sc = SparkContext._active_spark_context + if len(cols) == 1 and isinstance(cols[0], (list, set)): + cols = cols[0] + jc = sc._jvm.functions.array(_to_seq(sc, cols, _to_java_column)) + return Column(jc) + + def approxCountDistinct(col, rsd=None): """Returns a new :class:`Column` for approximate distinct count of ``col``. @@ -123,6 +147,28 @@ def monotonicallyIncreasingId(): return Column(sc._jvm.functions.monotonicallyIncreasingId()) +def rand(seed=None): + """Generates a random column with i.i.d. samples from U[0.0, 1.0]. + """ + sc = SparkContext._active_spark_context + if seed: + jc = sc._jvm.functions.rand(seed) + else: + jc = sc._jvm.functions.rand() + return Column(jc) + + +def randn(seed=None): + """Generates a column with i.i.d. samples from the standard normal distribution. + """ + sc = SparkContext._active_spark_context + if seed: + jc = sc._jvm.functions.randn(seed) + else: + jc = sc._jvm.functions.randn() + return Column(jc) + + def sparkPartitionId(): """A column for partition ID of the Spark task. @@ -135,6 +181,25 @@ def sparkPartitionId(): return Column(sc._jvm.functions.sparkPartitionId()) +@ignore_unicode_prefix +def struct(*cols): + """Creates a new struct column. + + :param cols: list of column names (string) or list of :class:`Column` expressions + that are named or aliased. + + >>> df.select(struct('age', 'name').alias("struct")).collect() + [Row(struct=Row(age=2, name=u'Alice')), Row(struct=Row(age=5, name=u'Bob'))] + >>> df.select(struct([df.age, df.name]).alias("struct")).collect() + [Row(struct=Row(age=2, name=u'Alice')), Row(struct=Row(age=5, name=u'Bob'))] + """ + sc = SparkContext._active_spark_context + if len(cols) == 1 and isinstance(cols[0], (list, set)): + cols = cols[0] + jc = sc._jvm.functions.struct(_to_seq(sc, cols, _to_java_column)) + return Column(jc) + + class UserDefinedFunction(object): """ User defined function in Python diff --git a/python/pyspark/sql/mathfunctions.py b/python/pyspark/sql/mathfunctions.py new file mode 100644 index 0000000000000..7dbcab8694293 --- /dev/null +++ b/python/pyspark/sql/mathfunctions.py @@ -0,0 +1,101 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +A collection of builtin math functions +""" + +from pyspark import SparkContext +from pyspark.sql.dataframe import Column + +__all__ = [] + + +def _create_unary_mathfunction(name, doc=""): + """ Create a unary mathfunction by name""" + def _(col): + sc = SparkContext._active_spark_context + jc = getattr(sc._jvm.mathfunctions, name)(col._jc if isinstance(col, Column) else col) + return Column(jc) + _.__name__ = name + _.__doc__ = doc + return _ + + +def _create_binary_mathfunction(name, doc=""): + """ Create a binary mathfunction by name""" + def _(col1, col2): + sc = SparkContext._active_spark_context + # users might write ints for simplicity. This would throw an error on the JVM side. + if type(col1) is int: + col1 = col1 * 1.0 + if type(col2) is int: + col2 = col2 * 1.0 + jc = getattr(sc._jvm.mathfunctions, name)(col1._jc if isinstance(col1, Column) else col1, + col2._jc if isinstance(col2, Column) else col2) + return Column(jc) + _.__name__ = name + _.__doc__ = doc + return _ + + +# math functions are found under another object therefore, they need to be handled separately +_mathfunctions = { + 'acos': 'Computes the cosine inverse of the given value; the returned angle is in the range' + + '0.0 through pi.', + 'asin': 'Computes the sine inverse of the given value; the returned angle is in the range' + + '-pi/2 through pi/2.', + 'atan': 'Computes the tangent inverse of the given value.', + 'cbrt': 'Computes the cube-root of the given value.', + 'ceil': 'Computes the ceiling of the given value.', + 'cos': 'Computes the cosine of the given value.', + 'cosh': 'Computes the hyperbolic cosine of the given value.', + 'exp': 'Computes the exponential of the given value.', + 'expm1': 'Computes the exponential of the given value minus one.', + 'floor': 'Computes the floor of the given value.', + 'log': 'Computes the natural logarithm of the given value.', + 'log10': 'Computes the logarithm of the given value in Base 10.', + 'log1p': 'Computes the natural logarithm of the given value plus one.', + 'rint': 'Returns the double value that is closest in value to the argument and' + + ' is equal to a mathematical integer.', + 'signum': 'Computes the signum of the given value.', + 'sin': 'Computes the sine of the given value.', + 'sinh': 'Computes the hyperbolic sine of the given value.', + 'tan': 'Computes the tangent of the given value.', + 'tanh': 'Computes the hyperbolic tangent of the given value.', + 'toDeg': 'Converts an angle measured in radians to an approximately equivalent angle ' + + 'measured in degrees.', + 'toRad': 'Converts an angle measured in degrees to an approximately equivalent angle ' + + 'measured in radians.' +} + +# math functions that take two arguments as input +_binary_mathfunctions = { + 'atan2': 'Returns the angle theta from the conversion of rectangular coordinates (x, y) to' + + 'polar coordinates (r, theta).', + 'hypot': 'Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow.', + 'pow': 'Returns the value of the first argument raised to the power of the second argument.' +} + +for _name, _doc in _mathfunctions.items(): + globals()[_name] = _create_unary_mathfunction(_name, _doc) +for _name, _doc in _binary_mathfunctions.items(): + globals()[_name] = _create_binary_mathfunction(_name, _doc) +del _name, _doc +__all__ += _mathfunctions.keys() +__all__ += _binary_mathfunctions.keys() +__all__.sort() diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py index fe43c374f1cb1..613efc0ac029d 100644 --- a/python/pyspark/sql/tests.py +++ b/python/pyspark/sql/tests.py @@ -375,6 +375,13 @@ def test_column_select(self): self.assertEqual(self.testData, df.select(df.key, df.value).collect()) self.assertEqual([Row(value='1')], df.where(df.key == 1).select(df.value).collect()) + def test_freqItems(self): + vals = [Row(a=1, b=-2.0) if i % 2 == 0 else Row(a=i, b=i * 1.0) for i in range(100)] + df = self.sc.parallelize(vals).toDF() + items = df.stat.freqItems(("a", "b"), 0.4).collect()[0] + self.assertTrue(1 in items[0]) + self.assertTrue(-2.0 in items[1]) + def test_aggregator(self): df = self.df g = df.groupBy() @@ -387,6 +394,50 @@ def test_aggregator(self): self.assertTrue(95 < g.agg(functions.approxCountDistinct(df.key)).first()[0]) self.assertEqual(100, g.agg(functions.countDistinct(df.value)).first()[0]) + def test_cov(self): + df = self.sc.parallelize([Row(a=i, b=2 * i) for i in range(10)]).toDF() + cov = df.stat.cov("a", "b") + self.assertTrue(abs(cov - 55.0 / 3) < 1e-6) + + def test_math_functions(self): + df = self.sc.parallelize([Row(a=i, b=2 * i) for i in range(10)]).toDF() + from pyspark.sql import mathfunctions as functions + import math + + def get_values(l): + return [j[0] for j in l] + + def assert_close(a, b): + c = get_values(b) + diff = [abs(v - c[k]) < 1e-6 for k, v in enumerate(a)] + return sum(diff) == len(a) + assert_close([math.cos(i) for i in range(10)], + df.select(functions.cos(df.a)).collect()) + assert_close([math.cos(i) for i in range(10)], + df.select(functions.cos("a")).collect()) + assert_close([math.sin(i) for i in range(10)], + df.select(functions.sin(df.a)).collect()) + assert_close([math.sin(i) for i in range(10)], + df.select(functions.sin(df['a'])).collect()) + assert_close([math.pow(i, 2 * i) for i in range(10)], + df.select(functions.pow(df.a, df.b)).collect()) + assert_close([math.pow(i, 2) for i in range(10)], + df.select(functions.pow(df.a, 2)).collect()) + assert_close([math.pow(i, 2) for i in range(10)], + df.select(functions.pow(df.a, 2.0)).collect()) + assert_close([math.hypot(i, 2 * i) for i in range(10)], + df.select(functions.hypot(df.a, df.b)).collect()) + + def test_rand_functions(self): + df = self.df + from pyspark.sql import functions + rnd = df.select('key', functions.rand()).collect() + for row in rnd: + assert row[1] >= 0.0 and row[1] <= 1.0, "got: %s" % row[1] + rndn = df.select('key', functions.randn(5)).collect() + for row in rndn: + assert row[1] >= -4.0 and row[1] <= 4.0, "got: %s" % row[1] + def test_save_and_load(self): df = self.df tmpPath = tempfile.mkdtemp() diff --git a/python/pyspark/streaming/tests.py b/python/pyspark/streaming/tests.py index 7c06c203455d9..33ea8c9293d74 100644 --- a/python/pyspark/streaming/tests.py +++ b/python/pyspark/streaming/tests.py @@ -606,7 +606,6 @@ def _validateRddResult(self, sendData, rdd): result = {} for i in rdd.map(lambda x: x[1]).collect(): result[i] = result.get(i, 0) + 1 - self.assertEqual(sendData, result) def test_kafka_stream(self): @@ -616,6 +615,7 @@ def test_kafka_stream(self): self._kafkaTestUtils.createTopic(topic) self._kafkaTestUtils.sendMessages(topic, sendData) + self._kafkaTestUtils.waitUntilLeaderOffset(topic, 0, sum(sendData.values())) stream = KafkaUtils.createStream(self.ssc, self._kafkaTestUtils.zkAddress(), "test-streaming-consumer", {topic: 1}, @@ -631,6 +631,7 @@ def test_kafka_direct_stream(self): self._kafkaTestUtils.createTopic(topic) self._kafkaTestUtils.sendMessages(topic, sendData) + self._kafkaTestUtils.waitUntilLeaderOffset(topic, 0, sum(sendData.values())) stream = KafkaUtils.createDirectStream(self.ssc, [topic], kafkaParams) self._validateStreamResult(sendData, stream) @@ -645,6 +646,7 @@ def test_kafka_direct_stream_from_offset(self): self._kafkaTestUtils.createTopic(topic) self._kafkaTestUtils.sendMessages(topic, sendData) + self._kafkaTestUtils.waitUntilLeaderOffset(topic, 0, sum(sendData.values())) stream = KafkaUtils.createDirectStream(self.ssc, [topic], kafkaParams, fromOffsets) self._validateStreamResult(sendData, stream) @@ -659,7 +661,7 @@ def test_kafka_rdd(self): self._kafkaTestUtils.createTopic(topic) self._kafkaTestUtils.sendMessages(topic, sendData) - + self._kafkaTestUtils.waitUntilLeaderOffset(topic, 0, sum(sendData.values())) rdd = KafkaUtils.createRDD(self.sc, kafkaParams, offsetRanges) self._validateRddResult(sendData, rdd) @@ -675,7 +677,7 @@ def test_kafka_rdd_with_leaders(self): self._kafkaTestUtils.createTopic(topic) self._kafkaTestUtils.sendMessages(topic, sendData) - + self._kafkaTestUtils.waitUntilLeaderOffset(topic, 0, sum(sendData.values())) rdd = KafkaUtils.createRDD(self.sc, kafkaParams, offsetRanges, leaders) self._validateRddResult(sendData, rdd) diff --git a/sql/catalyst/pom.xml b/sql/catalyst/pom.xml index 3dea2ee76542f..5c322d032d474 100644 --- a/sql/catalyst/pom.xml +++ b/sql/catalyst/pom.xml @@ -50,6 +50,11 @@ spark-core_${scala.binary.version} ${project.version} + + org.apache.spark + spark-unsafe_${scala.binary.version} + ${project.version} + org.scalacheck scalacheck_${scala.binary.version} diff --git a/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMap.java b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMap.java new file mode 100644 index 0000000000000..299ff3728a6d9 --- /dev/null +++ b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMap.java @@ -0,0 +1,259 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst.expressions; + +import java.util.Arrays; +import java.util.Iterator; + +import org.apache.spark.sql.Row; +import org.apache.spark.sql.types.StructField; +import org.apache.spark.sql.types.StructType; +import org.apache.spark.unsafe.PlatformDependent; +import org.apache.spark.unsafe.map.BytesToBytesMap; +import org.apache.spark.unsafe.memory.MemoryLocation; +import org.apache.spark.unsafe.memory.TaskMemoryManager; + +/** + * Unsafe-based HashMap for performing aggregations where the aggregated values are fixed-width. + * + * This map supports a maximum of 2 billion keys. + */ +public final class UnsafeFixedWidthAggregationMap { + + /** + * An empty aggregation buffer, encoded in UnsafeRow format. When inserting a new key into the + * map, we copy this buffer and use it as the value. + */ + private final long[] emptyAggregationBuffer; + + private final StructType aggregationBufferSchema; + + private final StructType groupingKeySchema; + + /** + * Encodes grouping keys as UnsafeRows. + */ + private final UnsafeRowConverter groupingKeyToUnsafeRowConverter; + + /** + * A hashmap which maps from opaque bytearray keys to bytearray values. + */ + private final BytesToBytesMap map; + + /** + * Re-used pointer to the current aggregation buffer + */ + private final UnsafeRow currentAggregationBuffer = new UnsafeRow(); + + /** + * Scratch space that is used when encoding grouping keys into UnsafeRow format. + * + * By default, this is a 1MB array, but it will grow as necessary in case larger keys are + * encountered. + */ + private long[] groupingKeyConversionScratchSpace = new long[1024 / 8]; + + private final boolean enablePerfMetrics; + + /** + * @return true if UnsafeFixedWidthAggregationMap supports grouping keys with the given schema, + * false otherwise. + */ + public static boolean supportsGroupKeySchema(StructType schema) { + for (StructField field: schema.fields()) { + if (!UnsafeRow.readableFieldTypes.contains(field.dataType())) { + return false; + } + } + return true; + } + + /** + * @return true if UnsafeFixedWidthAggregationMap supports aggregation buffers with the given + * schema, false otherwise. + */ + public static boolean supportsAggregationBufferSchema(StructType schema) { + for (StructField field: schema.fields()) { + if (!UnsafeRow.settableFieldTypes.contains(field.dataType())) { + return false; + } + } + return true; + } + + /** + * Create a new UnsafeFixedWidthAggregationMap. + * + * @param emptyAggregationBuffer the default value for new keys (a "zero" of the agg. function) + * @param aggregationBufferSchema the schema of the aggregation buffer, used for row conversion. + * @param groupingKeySchema the schema of the grouping key, used for row conversion. + * @param memoryManager the memory manager used to allocate our Unsafe memory structures. + * @param initialCapacity the initial capacity of the map (a sizing hint to avoid re-hashing). + * @param enablePerfMetrics if true, performance metrics will be recorded (has minor perf impact) + */ + public UnsafeFixedWidthAggregationMap( + Row emptyAggregationBuffer, + StructType aggregationBufferSchema, + StructType groupingKeySchema, + TaskMemoryManager memoryManager, + int initialCapacity, + boolean enablePerfMetrics) { + this.emptyAggregationBuffer = + convertToUnsafeRow(emptyAggregationBuffer, aggregationBufferSchema); + this.aggregationBufferSchema = aggregationBufferSchema; + this.groupingKeyToUnsafeRowConverter = new UnsafeRowConverter(groupingKeySchema); + this.groupingKeySchema = groupingKeySchema; + this.map = new BytesToBytesMap(memoryManager, initialCapacity, enablePerfMetrics); + this.enablePerfMetrics = enablePerfMetrics; + } + + /** + * Convert a Java object row into an UnsafeRow, allocating it into a new long array. + */ + private static long[] convertToUnsafeRow(Row javaRow, StructType schema) { + final UnsafeRowConverter converter = new UnsafeRowConverter(schema); + final long[] unsafeRow = new long[converter.getSizeRequirement(javaRow)]; + final long writtenLength = + converter.writeRow(javaRow, unsafeRow, PlatformDependent.LONG_ARRAY_OFFSET); + assert (writtenLength == unsafeRow.length): "Size requirement calculation was wrong!"; + return unsafeRow; + } + + /** + * Return the aggregation buffer for the current group. For efficiency, all calls to this method + * return the same object. + */ + public UnsafeRow getAggregationBuffer(Row groupingKey) { + final int groupingKeySize = groupingKeyToUnsafeRowConverter.getSizeRequirement(groupingKey); + // Make sure that the buffer is large enough to hold the key. If it's not, grow it: + if (groupingKeySize > groupingKeyConversionScratchSpace.length) { + // This new array will be initially zero, so there's no need to zero it out here + groupingKeyConversionScratchSpace = new long[groupingKeySize]; + } else { + // Zero out the buffer that's used to hold the current row. This is necessary in order + // to ensure that rows hash properly, since garbage data from the previous row could + // otherwise end up as padding in this row. As a performance optimization, we only zero out + // the portion of the buffer that we'll actually write to. + Arrays.fill(groupingKeyConversionScratchSpace, 0, groupingKeySize, 0); + } + final long actualGroupingKeySize = groupingKeyToUnsafeRowConverter.writeRow( + groupingKey, + groupingKeyConversionScratchSpace, + PlatformDependent.LONG_ARRAY_OFFSET); + assert (groupingKeySize == actualGroupingKeySize) : "Size requirement calculation was wrong!"; + + // Probe our map using the serialized key + final BytesToBytesMap.Location loc = map.lookup( + groupingKeyConversionScratchSpace, + PlatformDependent.LONG_ARRAY_OFFSET, + groupingKeySize); + if (!loc.isDefined()) { + // This is the first time that we've seen this grouping key, so we'll insert a copy of the + // empty aggregation buffer into the map: + loc.putNewKey( + groupingKeyConversionScratchSpace, + PlatformDependent.LONG_ARRAY_OFFSET, + groupingKeySize, + emptyAggregationBuffer, + PlatformDependent.LONG_ARRAY_OFFSET, + emptyAggregationBuffer.length + ); + } + + // Reset the pointer to point to the value that we just stored or looked up: + final MemoryLocation address = loc.getValueAddress(); + currentAggregationBuffer.pointTo( + address.getBaseObject(), + address.getBaseOffset(), + aggregationBufferSchema.length(), + aggregationBufferSchema + ); + return currentAggregationBuffer; + } + + /** + * Mutable pair object returned by {@link UnsafeFixedWidthAggregationMap#iterator()}. + */ + public static class MapEntry { + private MapEntry() { }; + public final UnsafeRow key = new UnsafeRow(); + public final UnsafeRow value = new UnsafeRow(); + } + + /** + * Returns an iterator over the keys and values in this map. + * + * For efficiency, each call returns the same object. + */ + public Iterator iterator() { + return new Iterator() { + + private final MapEntry entry = new MapEntry(); + private final Iterator mapLocationIterator = map.iterator(); + + @Override + public boolean hasNext() { + return mapLocationIterator.hasNext(); + } + + @Override + public MapEntry next() { + final BytesToBytesMap.Location loc = mapLocationIterator.next(); + final MemoryLocation keyAddress = loc.getKeyAddress(); + final MemoryLocation valueAddress = loc.getValueAddress(); + entry.key.pointTo( + keyAddress.getBaseObject(), + keyAddress.getBaseOffset(), + groupingKeySchema.length(), + groupingKeySchema + ); + entry.value.pointTo( + valueAddress.getBaseObject(), + valueAddress.getBaseOffset(), + aggregationBufferSchema.length(), + aggregationBufferSchema + ); + return entry; + } + + @Override + public void remove() { + throw new UnsupportedOperationException(); + } + }; + } + + /** + * Free the unsafe memory associated with this map. + */ + public void free() { + map.free(); + } + + @SuppressWarnings("UseOfSystemOutOrSystemErr") + public void printPerfMetrics() { + if (!enablePerfMetrics) { + throw new IllegalStateException("Perf metrics not enabled"); + } + System.out.println("Average probes per lookup: " + map.getAverageProbesPerLookup()); + System.out.println("Number of hash collisions: " + map.getNumHashCollisions()); + System.out.println("Time spent resizing (ns): " + map.getTimeSpentResizingNs()); + System.out.println("Total memory consumption (bytes): " + map.getTotalMemoryConsumption()); + } + +} diff --git a/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeRow.java b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeRow.java new file mode 100644 index 0000000000000..0a358ed408aa1 --- /dev/null +++ b/sql/catalyst/src/main/java/org/apache/spark/sql/catalyst/expressions/UnsafeRow.java @@ -0,0 +1,435 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst.expressions; + +import scala.collection.Map; +import scala.collection.Seq; +import scala.collection.mutable.ArraySeq; + +import javax.annotation.Nullable; +import java.math.BigDecimal; +import java.sql.Date; +import java.util.*; + +import org.apache.spark.sql.Row; +import org.apache.spark.sql.types.DataType; +import static org.apache.spark.sql.types.DataTypes.*; +import org.apache.spark.sql.types.StructType; +import org.apache.spark.sql.types.UTF8String; +import org.apache.spark.unsafe.PlatformDependent; +import org.apache.spark.unsafe.bitset.BitSetMethods; + +/** + * An Unsafe implementation of Row which is backed by raw memory instead of Java objects. + * + * Each tuple has three parts: [null bit set] [values] [variable length portion] + * + * The bit set is used for null tracking and is aligned to 8-byte word boundaries. It stores + * one bit per field. + * + * In the `values` region, we store one 8-byte word per field. For fields that hold fixed-length + * primitive types, such as long, double, or int, we store the value directly in the word. For + * fields with non-primitive or variable-length values, we store a relative offset (w.r.t. the + * base address of the row) that points to the beginning of the variable-length field. + * + * Instances of `UnsafeRow` act as pointers to row data stored in this format. + */ +public final class UnsafeRow implements MutableRow { + + private Object baseObject; + private long baseOffset; + + Object getBaseObject() { return baseObject; } + long getBaseOffset() { return baseOffset; } + + /** The number of fields in this row, used for calculating the bitset width (and in assertions) */ + private int numFields; + + /** The width of the null tracking bit set, in bytes */ + private int bitSetWidthInBytes; + /** + * This optional schema is required if you want to call generic get() and set() methods on + * this UnsafeRow, but is optional if callers will only use type-specific getTYPE() and setTYPE() + * methods. This should be removed after the planned InternalRow / Row split; right now, it's only + * needed by the generic get() method, which is only called internally by code that accesses + * UTF8String-typed columns. + */ + @Nullable + private StructType schema; + + private long getFieldOffset(int ordinal) { + return baseOffset + bitSetWidthInBytes + ordinal * 8L; + } + + public static int calculateBitSetWidthInBytes(int numFields) { + return ((numFields / 64) + (numFields % 64 == 0 ? 0 : 1)) * 8; + } + + /** + * Field types that can be updated in place in UnsafeRows (e.g. we support set() for these types) + */ + public static final Set settableFieldTypes; + + /** + * Fields types can be read(but not set (e.g. set() will throw UnsupportedOperationException). + */ + public static final Set readableFieldTypes; + + static { + settableFieldTypes = Collections.unmodifiableSet( + new HashSet( + Arrays.asList(new DataType[] { + NullType, + BooleanType, + ByteType, + ShortType, + IntegerType, + LongType, + FloatType, + DoubleType + }))); + + // We support get() on a superset of the types for which we support set(): + final Set _readableFieldTypes = new HashSet( + Arrays.asList(new DataType[]{ + StringType + })); + _readableFieldTypes.addAll(settableFieldTypes); + readableFieldTypes = Collections.unmodifiableSet(_readableFieldTypes); + } + + /** + * Construct a new UnsafeRow. The resulting row won't be usable until `pointTo()` has been called, + * since the value returned by this constructor is equivalent to a null pointer. + */ + public UnsafeRow() { } + + /** + * Update this UnsafeRow to point to different backing data. + * + * @param baseObject the base object + * @param baseOffset the offset within the base object + * @param numFields the number of fields in this row + * @param schema an optional schema; this is necessary if you want to call generic get() or set() + * methods on this row, but is optional if the caller will only use type-specific + * getTYPE() and setTYPE() methods. + */ + public void pointTo( + Object baseObject, + long baseOffset, + int numFields, + @Nullable StructType schema) { + assert numFields >= 0 : "numFields should >= 0"; + assert schema == null || schema.fields().length == numFields; + this.bitSetWidthInBytes = calculateBitSetWidthInBytes(numFields); + this.baseObject = baseObject; + this.baseOffset = baseOffset; + this.numFields = numFields; + this.schema = schema; + } + + private void assertIndexIsValid(int index) { + assert index >= 0 : "index (" + index + ") should >= 0"; + assert index < numFields : "index (" + index + ") should <= " + numFields; + } + + @Override + public void setNullAt(int i) { + assertIndexIsValid(i); + BitSetMethods.set(baseObject, baseOffset, i); + // To preserve row equality, zero out the value when setting the column to null. + // Since this row does does not currently support updates to variable-length values, we don't + // have to worry about zeroing out that data. + PlatformDependent.UNSAFE.putLong(baseObject, getFieldOffset(i), 0); + } + + private void setNotNullAt(int i) { + assertIndexIsValid(i); + BitSetMethods.unset(baseObject, baseOffset, i); + } + + @Override + public void update(int ordinal, Object value) { + throw new UnsupportedOperationException(); + } + + @Override + public void setInt(int ordinal, int value) { + assertIndexIsValid(ordinal); + setNotNullAt(ordinal); + PlatformDependent.UNSAFE.putInt(baseObject, getFieldOffset(ordinal), value); + } + + @Override + public void setLong(int ordinal, long value) { + assertIndexIsValid(ordinal); + setNotNullAt(ordinal); + PlatformDependent.UNSAFE.putLong(baseObject, getFieldOffset(ordinal), value); + } + + @Override + public void setDouble(int ordinal, double value) { + assertIndexIsValid(ordinal); + setNotNullAt(ordinal); + PlatformDependent.UNSAFE.putDouble(baseObject, getFieldOffset(ordinal), value); + } + + @Override + public void setBoolean(int ordinal, boolean value) { + assertIndexIsValid(ordinal); + setNotNullAt(ordinal); + PlatformDependent.UNSAFE.putBoolean(baseObject, getFieldOffset(ordinal), value); + } + + @Override + public void setShort(int ordinal, short value) { + assertIndexIsValid(ordinal); + setNotNullAt(ordinal); + PlatformDependent.UNSAFE.putShort(baseObject, getFieldOffset(ordinal), value); + } + + @Override + public void setByte(int ordinal, byte value) { + assertIndexIsValid(ordinal); + setNotNullAt(ordinal); + PlatformDependent.UNSAFE.putByte(baseObject, getFieldOffset(ordinal), value); + } + + @Override + public void setFloat(int ordinal, float value) { + assertIndexIsValid(ordinal); + setNotNullAt(ordinal); + PlatformDependent.UNSAFE.putFloat(baseObject, getFieldOffset(ordinal), value); + } + + @Override + public void setString(int ordinal, String value) { + throw new UnsupportedOperationException(); + } + + @Override + public int size() { + return numFields; + } + + @Override + public int length() { + return size(); + } + + @Override + public StructType schema() { + return schema; + } + + @Override + public Object apply(int i) { + return get(i); + } + + @Override + public Object get(int i) { + assertIndexIsValid(i); + assert (schema != null) : "Schema must be defined when calling generic get() method"; + final DataType dataType = schema.fields()[i].dataType(); + // UnsafeRow is only designed to be invoked by internal code, which only invokes this generic + // get() method when trying to access UTF8String-typed columns. If we refactor the codebase to + // separate the internal and external row interfaces, then internal code can fetch strings via + // a new getUTF8String() method and we'll be able to remove this method. + if (isNullAt(i)) { + return null; + } else if (dataType == StringType) { + return getUTF8String(i); + } else { + throw new UnsupportedOperationException(); + } + } + + @Override + public boolean isNullAt(int i) { + assertIndexIsValid(i); + return BitSetMethods.isSet(baseObject, baseOffset, i); + } + + @Override + public boolean getBoolean(int i) { + assertIndexIsValid(i); + return PlatformDependent.UNSAFE.getBoolean(baseObject, getFieldOffset(i)); + } + + @Override + public byte getByte(int i) { + assertIndexIsValid(i); + return PlatformDependent.UNSAFE.getByte(baseObject, getFieldOffset(i)); + } + + @Override + public short getShort(int i) { + assertIndexIsValid(i); + return PlatformDependent.UNSAFE.getShort(baseObject, getFieldOffset(i)); + } + + @Override + public int getInt(int i) { + assertIndexIsValid(i); + return PlatformDependent.UNSAFE.getInt(baseObject, getFieldOffset(i)); + } + + @Override + public long getLong(int i) { + assertIndexIsValid(i); + return PlatformDependent.UNSAFE.getLong(baseObject, getFieldOffset(i)); + } + + @Override + public float getFloat(int i) { + assertIndexIsValid(i); + if (isNullAt(i)) { + return Float.NaN; + } else { + return PlatformDependent.UNSAFE.getFloat(baseObject, getFieldOffset(i)); + } + } + + @Override + public double getDouble(int i) { + assertIndexIsValid(i); + if (isNullAt(i)) { + return Float.NaN; + } else { + return PlatformDependent.UNSAFE.getDouble(baseObject, getFieldOffset(i)); + } + } + + public UTF8String getUTF8String(int i) { + assertIndexIsValid(i); + final UTF8String str = new UTF8String(); + final long offsetToStringSize = getLong(i); + final int stringSizeInBytes = + (int) PlatformDependent.UNSAFE.getLong(baseObject, baseOffset + offsetToStringSize); + final byte[] strBytes = new byte[stringSizeInBytes]; + PlatformDependent.copyMemory( + baseObject, + baseOffset + offsetToStringSize + 8, // The `+ 8` is to skip past the size to get the data + strBytes, + PlatformDependent.BYTE_ARRAY_OFFSET, + stringSizeInBytes + ); + str.set(strBytes); + return str; + } + + @Override + public String getString(int i) { + return getUTF8String(i).toString(); + } + + @Override + public BigDecimal getDecimal(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public Date getDate(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public Seq getSeq(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public List getList(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public Map getMap(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public scala.collection.immutable.Map getValuesMap(Seq fieldNames) { + throw new UnsupportedOperationException(); + } + + @Override + public java.util.Map getJavaMap(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public Row getStruct(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public T getAs(int i) { + throw new UnsupportedOperationException(); + } + + @Override + public T getAs(String fieldName) { + throw new UnsupportedOperationException(); + } + + @Override + public int fieldIndex(String name) { + throw new UnsupportedOperationException(); + } + + @Override + public Row copy() { + throw new UnsupportedOperationException(); + } + + @Override + public boolean anyNull() { + return BitSetMethods.anySet(baseObject, baseOffset, bitSetWidthInBytes); + } + + @Override + public Seq toSeq() { + final ArraySeq values = new ArraySeq(numFields); + for (int fieldNumber = 0; fieldNumber < numFields; fieldNumber++) { + values.update(fieldNumber, get(fieldNumber)); + } + return values; + } + + @Override + public String toString() { + return mkString("[", ",", "]"); + } + + @Override + public String mkString() { + return toSeq().mkString(); + } + + @Override + public String mkString(String sep) { + return toSeq().mkString(sep); + } + + @Override + public String mkString(String start, String sep, String end) { + return toSeq().mkString(start, sep, end); + } +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/AbstractSparkSQLParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/AbstractSparkSQLParser.scala index 1f3c02478bd68..2eb3e167baad5 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/AbstractSparkSQLParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/AbstractSparkSQLParser.scala @@ -25,10 +25,6 @@ import scala.util.parsing.input.CharArrayReader.EofCh import org.apache.spark.sql.catalyst.plans.logical._ -private[sql] object KeywordNormalizer { - def apply(str: String): String = str.toLowerCase() -} - private[sql] abstract class AbstractSparkSQLParser extends StandardTokenParsers with PackratParsers { @@ -42,7 +38,7 @@ private[sql] abstract class AbstractSparkSQLParser } protected case class Keyword(str: String) { - def normalize: String = KeywordNormalizer(str) + def normalize: String = lexical.normalizeKeyword(str) def parser: Parser[String] = normalize } @@ -90,13 +86,16 @@ class SqlLexical extends StdLexical { reserved ++= keywords } + /* Normal the keyword string */ + def normalizeKeyword(str: String): String = str.toLowerCase + delimiters += ( "@", "*", "+", "-", "<", "=", "<>", "!=", "<=", ">=", ">", "/", "(", ")", ",", ";", "%", "{", "}", ":", "[", "]", ".", "&", "|", "^", "~", "<=>" ) protected override def processIdent(name: String) = { - val token = KeywordNormalizer(name) + val token = normalizeKeyword(name) if (reserved contains token) Keyword(token) else Identifier(name) } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/Dialect.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/Dialect.scala new file mode 100644 index 0000000000000..977003493d471 --- /dev/null +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/Dialect.scala @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst + +import org.apache.spark.annotation.DeveloperApi +import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan + +/** + * Root class of SQL Parser Dialect, and we don't guarantee the binary + * compatibility for the future release, let's keep it as the internal + * interface for advanced user. + * + */ +@DeveloperApi +abstract class Dialect { + // this is the main function that will be implemented by sql parser. + def parse(sqlText: String): LogicalPlan +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala index 0af969cc5cc67..1d3a2dc0d9bb0 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala @@ -365,6 +365,7 @@ class SqlParser extends AbstractSparkSQLParser with DataTypeParser { protected lazy val baseExpression: Parser[Expression] = ( "*" ^^^ UnresolvedStar(None) + | ident <~ "." ~ "*" ^^ { case tableName => UnresolvedStar(Option(tableName)) } | primary ) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala index 5d5aba9644ff7..fa6cc7a1a36cf 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala @@ -278,12 +278,6 @@ package object dsl { def sfilter[T1](arg1: Symbol)(udf: (T1) => Boolean): LogicalPlan = Filter(ScalaUdf(udf, BooleanType, Seq(UnresolvedAttribute(arg1.name))), logicalPlan) - def sample( - fraction: Double, - withReplacement: Boolean = true, - seed: Int = (math.random * 1000).toInt): LogicalPlan = - Sample(fraction, withReplacement, seed, logicalPlan) - // TODO specify the output column names def generate( generator: Generator, diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/errors/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/errors/package.scala index bdeb660b1ecb7..0fd4f9b374ee0 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/errors/package.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/errors/package.scala @@ -38,6 +38,8 @@ package object errors { } } + class DialectException(msg: String, cause: Throwable) extends Exception(msg, cause) + /** * Wraps any exceptions that are thrown while executing `f` in a * [[catalyst.errors.TreeNodeException TreeNodeException]], attaching the provided `tree`. diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala index 2225621dbaabd..c6217f07c452d 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala @@ -28,13 +28,21 @@ import org.apache.spark.sql.catalyst.trees * the layout of intermediate tuples, BindReferences should be run after all such transformations. */ case class BoundReference(ordinal: Int, dataType: DataType, nullable: Boolean) - extends Expression with trees.LeafNode[Expression] { + extends NamedExpression with trees.LeafNode[Expression] { type EvaluatedType = Any override def toString: String = s"input[$ordinal]" override def eval(input: Row): Any = input(ordinal) + + override def name: String = s"i[$ordinal]" + + override def toAttribute: Attribute = throw new UnsupportedOperationException + + override def qualifiers: Seq[String] = throw new UnsupportedOperationException + + override def exprId: ExprId = throw new UnsupportedOperationException } object BindReferences extends Logging { diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala index 3475ed05f4454..aa4099e4d7bf9 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/SpecificMutableRow.scala @@ -202,6 +202,7 @@ final class SpecificMutableRow(val values: Array[MutableValue]) extends MutableR case DoubleType => new MutableDouble case BooleanType => new MutableBoolean case LongType => new MutableLong + case DateType => new MutableInt // We use INT for DATE internally case _ => new MutableAny }.toArray) diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverter.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverter.scala new file mode 100644 index 0000000000000..5b2c8572784bd --- /dev/null +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverter.scala @@ -0,0 +1,223 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst.expressions + +import org.apache.spark.sql.types._ +import org.apache.spark.unsafe.PlatformDependent +import org.apache.spark.unsafe.array.ByteArrayMethods + +/** + * Converts Rows into UnsafeRow format. This class is NOT thread-safe. + * + * @param fieldTypes the data types of the row's columns. + */ +class UnsafeRowConverter(fieldTypes: Array[DataType]) { + + def this(schema: StructType) { + this(schema.fields.map(_.dataType)) + } + + /** Re-used pointer to the unsafe row being written */ + private[this] val unsafeRow = new UnsafeRow() + + /** Functions for encoding each column */ + private[this] val writers: Array[UnsafeColumnWriter] = { + fieldTypes.map(t => UnsafeColumnWriter.forType(t)) + } + + /** The size, in bytes, of the fixed-length portion of the row, including the null bitmap */ + private[this] val fixedLengthSize: Int = + (8 * fieldTypes.length) + UnsafeRow.calculateBitSetWidthInBytes(fieldTypes.length) + + /** + * Compute the amount of space, in bytes, required to encode the given row. + */ + def getSizeRequirement(row: Row): Int = { + var fieldNumber = 0 + var variableLengthFieldSize: Int = 0 + while (fieldNumber < writers.length) { + if (!row.isNullAt(fieldNumber)) { + variableLengthFieldSize += writers(fieldNumber).getSize(row, fieldNumber) + } + fieldNumber += 1 + } + fixedLengthSize + variableLengthFieldSize + } + + /** + * Convert the given row into UnsafeRow format. + * + * @param row the row to convert + * @param baseObject the base object of the destination address + * @param baseOffset the base offset of the destination address + * @return the number of bytes written. This should be equal to `getSizeRequirement(row)`. + */ + def writeRow(row: Row, baseObject: Object, baseOffset: Long): Long = { + unsafeRow.pointTo(baseObject, baseOffset, writers.length, null) + var fieldNumber = 0 + var appendCursor: Int = fixedLengthSize + while (fieldNumber < writers.length) { + if (row.isNullAt(fieldNumber)) { + unsafeRow.setNullAt(fieldNumber) + } else { + appendCursor += writers(fieldNumber).write(row, unsafeRow, fieldNumber, appendCursor) + } + fieldNumber += 1 + } + appendCursor + } + +} + +/** + * Function for writing a column into an UnsafeRow. + */ +private abstract class UnsafeColumnWriter { + /** + * Write a value into an UnsafeRow. + * + * @param source the row being converted + * @param target a pointer to the converted unsafe row + * @param column the column to write + * @param appendCursor the offset from the start of the unsafe row to the end of the row; + * used for calculating where variable-length data should be written + * @return the number of variable-length bytes written + */ + def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int + + /** + * Return the number of bytes that are needed to write this variable-length value. + */ + def getSize(source: Row, column: Int): Int +} + +private object UnsafeColumnWriter { + + def forType(dataType: DataType): UnsafeColumnWriter = { + dataType match { + case NullType => NullUnsafeColumnWriter + case BooleanType => BooleanUnsafeColumnWriter + case ByteType => ByteUnsafeColumnWriter + case ShortType => ShortUnsafeColumnWriter + case IntegerType => IntUnsafeColumnWriter + case LongType => LongUnsafeColumnWriter + case FloatType => FloatUnsafeColumnWriter + case DoubleType => DoubleUnsafeColumnWriter + case StringType => StringUnsafeColumnWriter + case t => + throw new UnsupportedOperationException(s"Do not know how to write columns of type $t") + } + } +} + +// ------------------------------------------------------------------------------------------------ + +private object NullUnsafeColumnWriter extends NullUnsafeColumnWriter +private object BooleanUnsafeColumnWriter extends BooleanUnsafeColumnWriter +private object ByteUnsafeColumnWriter extends ByteUnsafeColumnWriter +private object ShortUnsafeColumnWriter extends ShortUnsafeColumnWriter +private object IntUnsafeColumnWriter extends IntUnsafeColumnWriter +private object LongUnsafeColumnWriter extends LongUnsafeColumnWriter +private object FloatUnsafeColumnWriter extends FloatUnsafeColumnWriter +private object DoubleUnsafeColumnWriter extends DoubleUnsafeColumnWriter +private object StringUnsafeColumnWriter extends StringUnsafeColumnWriter + +private abstract class PrimitiveUnsafeColumnWriter extends UnsafeColumnWriter { + // Primitives don't write to the variable-length region: + def getSize(sourceRow: Row, column: Int): Int = 0 +} + +private class NullUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setNullAt(column) + 0 + } +} + +private class BooleanUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setBoolean(column, source.getBoolean(column)) + 0 + } +} + +private class ByteUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setByte(column, source.getByte(column)) + 0 + } +} + +private class ShortUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setShort(column, source.getShort(column)) + 0 + } +} + +private class IntUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setInt(column, source.getInt(column)) + 0 + } +} + +private class LongUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setLong(column, source.getLong(column)) + 0 + } +} + +private class FloatUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setFloat(column, source.getFloat(column)) + 0 + } +} + +private class DoubleUnsafeColumnWriter private() extends PrimitiveUnsafeColumnWriter { + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + target.setDouble(column, source.getDouble(column)) + 0 + } +} + +private class StringUnsafeColumnWriter private() extends UnsafeColumnWriter { + def getSize(source: Row, column: Int): Int = { + val numBytes = source.get(column).asInstanceOf[UTF8String].getBytes.length + 8 + ByteArrayMethods.roundNumberOfBytesToNearestWord(numBytes) + } + + override def write(source: Row, target: UnsafeRow, column: Int, appendCursor: Int): Int = { + val value = source.get(column).asInstanceOf[UTF8String] + val baseObject = target.getBaseObject + val baseOffset = target.getBaseOffset + val numBytes = value.getBytes.length + PlatformDependent.UNSAFE.putLong(baseObject, baseOffset + appendCursor, numBytes) + PlatformDependent.copyMemory( + value.getBytes, + PlatformDependent.BYTE_ARRAY_OFFSET, + baseObject, + baseOffset + appendCursor + 8, + numBytes + ) + target.setLong(column, appendCursor) + 8 + ByteArrayMethods.roundNumberOfBytesToNearestWord(numBytes) + } +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala index dbc92fb93e95e..d17af0e7ff87e 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala @@ -672,6 +672,7 @@ abstract class CodeGenerator[InType <: AnyRef, OutType <: AnyRef] extends Loggin case DoubleType => ru.Literal(Constant(-1.toDouble)) case DecimalType() => q"org.apache.spark.sql.types.Decimal(-1)" case IntegerType => ru.Literal(Constant(-1)) + case DateType => ru.Literal(Constant(-1)) case _ => ru.Literal(Constant(null)) } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/binary.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/binary.scala index 5b4d912a64f71..fcc06d3aa1036 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/binary.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/binary.scala @@ -65,12 +65,6 @@ abstract class BinaryMathExpression(f: (Double, Double) => Double, name: String) } } -case class Pow(left: Expression, right: Expression) extends BinaryMathExpression(math.pow, "POWER") - -case class Hypot( - left: Expression, - right: Expression) extends BinaryMathExpression(math.hypot, "HYPOT") - case class Atan2( left: Expression, right: Expression) extends BinaryMathExpression(math.atan2, "ATAN2") { @@ -91,3 +85,9 @@ case class Atan2( } } } + +case class Hypot( + left: Expression, + right: Expression) extends BinaryMathExpression(math.hypot, "HYPOT") + +case class Pow(left: Expression, right: Expression) extends BinaryMathExpression(math.pow, "POWER") diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/unary.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/unary.scala index 96cb77d487529..dc68469e060cb 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/unary.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/mathfuncs/unary.scala @@ -25,27 +25,16 @@ import org.apache.spark.sql.types._ * input format, therefore these functions extend `ExpectsInputTypes`. * @param name The short name of the function */ -abstract class MathematicalExpression(name: String) +abstract class MathematicalExpression(f: Double => Double, name: String) extends UnaryExpression with Serializable with ExpectsInputTypes { self: Product => type EvaluatedType = Any + override def expectedChildTypes: Seq[DataType] = Seq(DoubleType) override def dataType: DataType = DoubleType override def foldable: Boolean = child.foldable override def nullable: Boolean = true override def toString: String = s"$name($child)" -} - -/** - * A unary expression specifically for math functions that take a `Double` as input and return - * a `Double`. - * @param f The math function. - * @param name The short name of the function - */ -abstract class MathematicalExpressionForDouble(f: Double => Double, name: String) - extends MathematicalExpression(name) { self: Product => - - override def expectedChildTypes: Seq[DataType] = Seq(DoubleType) override def eval(input: Row): Any = { val evalE = child.eval(input) @@ -58,111 +47,46 @@ abstract class MathematicalExpressionForDouble(f: Double => Double, name: String } } -/** - * A unary expression specifically for math functions that take an `Int` as input and return - * an `Int`. - * @param f The math function. - * @param name The short name of the function - */ -abstract class MathematicalExpressionForInt(f: Int => Int, name: String) - extends MathematicalExpression(name) { self: Product => +case class Acos(child: Expression) extends MathematicalExpression(math.acos, "ACOS") - override def dataType: DataType = IntegerType - override def expectedChildTypes: Seq[DataType] = Seq(IntegerType) +case class Asin(child: Expression) extends MathematicalExpression(math.asin, "ASIN") - override def eval(input: Row): Any = { - val evalE = child.eval(input) - if (evalE == null) null else f(evalE.asInstanceOf[Int]) - } -} +case class Atan(child: Expression) extends MathematicalExpression(math.atan, "ATAN") -/** - * A unary expression specifically for math functions that take a `Float` as input and return - * a `Float`. - * @param f The math function. - * @param name The short name of the function - */ -abstract class MathematicalExpressionForFloat(f: Float => Float, name: String) - extends MathematicalExpression(name) { self: Product => +case class Cbrt(child: Expression) extends MathematicalExpression(math.cbrt, "CBRT") - override def dataType: DataType = FloatType - override def expectedChildTypes: Seq[DataType] = Seq(FloatType) +case class Ceil(child: Expression) extends MathematicalExpression(math.ceil, "CEIL") - override def eval(input: Row): Any = { - val evalE = child.eval(input) - if (evalE == null) { - null - } else { - val result = f(evalE.asInstanceOf[Float]) - if (result.isNaN) null else result - } - } -} - -/** - * A unary expression specifically for math functions that take a `Long` as input and return - * a `Long`. - * @param f The math function. - * @param name The short name of the function - */ -abstract class MathematicalExpressionForLong(f: Long => Long, name: String) - extends MathematicalExpression(name) { self: Product => - - override def dataType: DataType = LongType - override def expectedChildTypes: Seq[DataType] = Seq(LongType) - - override def eval(input: Row): Any = { - val evalE = child.eval(input) - if (evalE == null) null else f(evalE.asInstanceOf[Long]) - } -} - -case class Sin(child: Expression) extends MathematicalExpressionForDouble(math.sin, "SIN") - -case class Asin(child: Expression) extends MathematicalExpressionForDouble(math.asin, "ASIN") - -case class Sinh(child: Expression) extends MathematicalExpressionForDouble(math.sinh, "SINH") - -case class Cos(child: Expression) extends MathematicalExpressionForDouble(math.cos, "COS") +case class Cos(child: Expression) extends MathematicalExpression(math.cos, "COS") -case class Acos(child: Expression) extends MathematicalExpressionForDouble(math.acos, "ACOS") +case class Cosh(child: Expression) extends MathematicalExpression(math.cosh, "COSH") -case class Cosh(child: Expression) extends MathematicalExpressionForDouble(math.cosh, "COSH") +case class Exp(child: Expression) extends MathematicalExpression(math.exp, "EXP") -case class Tan(child: Expression) extends MathematicalExpressionForDouble(math.tan, "TAN") +case class Expm1(child: Expression) extends MathematicalExpression(math.expm1, "EXPM1") -case class Atan(child: Expression) extends MathematicalExpressionForDouble(math.atan, "ATAN") +case class Floor(child: Expression) extends MathematicalExpression(math.floor, "FLOOR") -case class Tanh(child: Expression) extends MathematicalExpressionForDouble(math.tanh, "TANH") +case class Log(child: Expression) extends MathematicalExpression(math.log, "LOG") -case class Ceil(child: Expression) extends MathematicalExpressionForDouble(math.ceil, "CEIL") +case class Log10(child: Expression) extends MathematicalExpression(math.log10, "LOG10") -case class Floor(child: Expression) extends MathematicalExpressionForDouble(math.floor, "FLOOR") +case class Log1p(child: Expression) extends MathematicalExpression(math.log1p, "LOG1P") -case class Rint(child: Expression) extends MathematicalExpressionForDouble(math.rint, "ROUND") +case class Rint(child: Expression) extends MathematicalExpression(math.rint, "ROUND") -case class Cbrt(child: Expression) extends MathematicalExpressionForDouble(math.cbrt, "CBRT") +case class Signum(child: Expression) extends MathematicalExpression(math.signum, "SIGNUM") -case class Signum(child: Expression) extends MathematicalExpressionForDouble(math.signum, "SIGNUM") +case class Sin(child: Expression) extends MathematicalExpression(math.sin, "SIN") -case class ISignum(child: Expression) extends MathematicalExpressionForInt(math.signum, "ISIGNUM") +case class Sinh(child: Expression) extends MathematicalExpression(math.sinh, "SINH") -case class FSignum(child: Expression) extends MathematicalExpressionForFloat(math.signum, "FSIGNUM") +case class Tan(child: Expression) extends MathematicalExpression(math.tan, "TAN") -case class LSignum(child: Expression) extends MathematicalExpressionForLong(math.signum, "LSIGNUM") +case class Tanh(child: Expression) extends MathematicalExpression(math.tanh, "TANH") case class ToDegrees(child: Expression) - extends MathematicalExpressionForDouble(math.toDegrees, "DEGREES") + extends MathematicalExpression(math.toDegrees, "DEGREES") case class ToRadians(child: Expression) - extends MathematicalExpressionForDouble(math.toRadians, "RADIANS") - -case class Log(child: Expression) extends MathematicalExpressionForDouble(math.log, "LOG") - -case class Log10(child: Expression) extends MathematicalExpressionForDouble(math.log10, "LOG10") - -case class Log1p(child: Expression) extends MathematicalExpressionForDouble(math.log1p, "LOG1P") - -case class Exp(child: Expression) extends MathematicalExpressionForDouble(math.exp, "EXP") - -case class Expm1(child: Expression) extends MathematicalExpressionForDouble(math.expm1, "EXPM1") + extends MathematicalExpression(math.toRadians, "RADIANS") diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala new file mode 100644 index 0000000000000..66d7c8b07cce8 --- /dev/null +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala @@ -0,0 +1,56 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst.expressions + +import org.apache.spark.TaskContext +import org.apache.spark.sql.types.{DataType, DoubleType} +import org.apache.spark.util.Utils +import org.apache.spark.util.random.XORShiftRandom + +/** + * A Random distribution generating expression. + * TODO: This can be made generic to generate any type of random distribution, or any type of + * StructType. + * + * Since this expression is stateful, it cannot be a case object. + */ +abstract class RDG(seed: Long) extends LeafExpression with Serializable { + self: Product => + + /** + * Record ID within each partition. By being transient, the Random Number Generator is + * reset every time we serialize and deserialize it. + */ + @transient protected lazy val rng = new XORShiftRandom(seed + TaskContext.get().partitionId()) + + override type EvaluatedType = Double + + override def nullable: Boolean = false + + override def dataType: DataType = DoubleType +} + +/** Generate a random column with i.i.d. uniformly distributed values in [0, 1). */ +case class Rand(seed: Long = Utils.random.nextLong()) extends RDG(seed) { + override def eval(input: Row): Double = rng.nextDouble() +} + +/** Generate a random column with i.i.d. gaussian random distribution. */ +case class Randn(seed: Long = Utils.random.nextLong()) extends RDG(seed) { + override def eval(input: Row): Double = rng.nextGaussian() +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala index 2d03fbfb0d311..709f7d672d931 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala @@ -36,7 +36,13 @@ object DefaultOptimizer extends Optimizer { // SubQueries are only needed for analysis and can be removed before execution. Batch("Remove SubQueries", FixedPoint(100), EliminateSubQueries) :: - Batch("Combine Limits", FixedPoint(100), + Batch("Operator Reordering", FixedPoint(100), + UnionPushdown, + CombineFilters, + PushPredicateThroughProject, + PushPredicateThroughJoin, + PushPredicateThroughGenerate, + ColumnPruning, CombineLimits) :: Batch("ConstantFolding", FixedPoint(100), NullPropagation, @@ -49,13 +55,6 @@ object DefaultOptimizer extends Optimizer { OptimizeIn) :: Batch("Decimal Optimizations", FixedPoint(100), DecimalAggregates) :: - Batch("Filter Pushdown", FixedPoint(100), - UnionPushdown, - CombineFilters, - PushPredicateThroughProject, - PushPredicateThroughJoin, - PushPredicateThroughGenerate, - ColumnPruning) :: Batch("LocalRelation", FixedPoint(100), ConvertToLocalRelation) :: Nil } @@ -171,6 +170,9 @@ object ColumnPruning extends Rule[LogicalPlan] { Project(substitutedProjection, child) + case Project(projectList, Limit(exp, child)) => + Limit(exp, Project(projectList, child)) + // Eliminate no-op Projects case Project(projectList, child) if child.output == projectList => child } @@ -569,7 +571,7 @@ object PushPredicateThroughJoin extends Rule[LogicalPlan] with PredicateHelper { split(joinCondition.map(splitConjunctivePredicates).getOrElse(Nil), left, right) joinType match { - case Inner => + case _ @ (Inner | LeftSemi) => // push down the single side only join filter for both sides sub queries val newLeft = leftJoinConditions. reduceLeftOption(And).map(Filter(_, left)).getOrElse(left) @@ -577,7 +579,7 @@ object PushPredicateThroughJoin extends Rule[LogicalPlan] with PredicateHelper { reduceLeftOption(And).map(Filter(_, right)).getOrElse(right) val newJoinCond = commonJoinCondition.reduceLeftOption(And) - Join(newLeft, newRight, Inner, newJoinCond) + Join(newLeft, newRight, joinType, newJoinCond) case RightOuter => // push down the left side only join filter for left side sub query val newLeft = leftJoinConditions. @@ -586,14 +588,14 @@ object PushPredicateThroughJoin extends Rule[LogicalPlan] with PredicateHelper { val newJoinCond = (rightJoinConditions ++ commonJoinCondition).reduceLeftOption(And) Join(newLeft, newRight, RightOuter, newJoinCond) - case _ @ (LeftOuter | LeftSemi) => + case LeftOuter => // push down the right side only join filter for right sub query val newLeft = left val newRight = rightJoinConditions. reduceLeftOption(And).map(Filter(_, right)).getOrElse(right) val newJoinCond = (leftJoinConditions ++ commonJoinCondition).reduceLeftOption(And) - Join(newLeft, newRight, joinType, newJoinCond) + Join(newLeft, newRight, LeftOuter, newJoinCond) case FullOuter => f } } diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala index bbc94a7ab3398..21208c8a5c281 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicOperators.scala @@ -300,8 +300,22 @@ case class Subquery(alias: String, child: LogicalPlan) extends UnaryNode { override def output: Seq[Attribute] = child.output.map(_.withQualifiers(alias :: Nil)) } -case class Sample(fraction: Double, withReplacement: Boolean, seed: Long, child: LogicalPlan) - extends UnaryNode { +/** + * Sample the dataset. + * + * @param lowerBound Lower-bound of the sampling probability (usually 0.0) + * @param upperBound Upper-bound of the sampling probability. The expected fraction sampled + * will be ub - lb. + * @param withReplacement Whether to sample with replacement. + * @param seed the random seed + * @param child the LogicalPlan + */ +case class Sample( + lowerBound: Double, + upperBound: Double, + withReplacement: Boolean, + seed: Long, + child: LogicalPlan) extends UnaryNode { override def output: Seq[Attribute] = child.output } @@ -310,6 +324,17 @@ case class Distinct(child: LogicalPlan) extends UnaryNode { override def output: Seq[Attribute] = child.output } +/** + * Return a new RDD that has exactly `numPartitions` partitions. Differs from + * [[RepartitionByExpression]] as this method is called directly by DataFrame's, because the user + * asked for `coalesce` or `repartition`. [[RepartitionByExpression]] is used when the consumer + * of the output requires some specific ordering or distribution of the data. + */ +case class Repartition(numPartitions: Int, shuffle: Boolean, child: LogicalPlan) + extends UnaryNode { + override def output: Seq[Attribute] = child.output +} + /** * A relation with one row. This is used in "SELECT ..." without a from clause. */ diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/partitioning.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/partitioning.scala index e737418d9c3bc..63df2c1ee72ff 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/partitioning.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/partitioning.scala @@ -32,5 +32,11 @@ abstract class RedistributeData extends UnaryNode { case class SortPartitions(sortExpressions: Seq[SortOrder], child: LogicalPlan) extends RedistributeData -case class Repartition(partitionExpressions: Seq[Expression], child: LogicalPlan) +/** + * This method repartitions data using [[Expression]]s, and receives information about the + * number of partitions during execution. Used when a specific ordering or distribution is + * expected by the consumer of the query result. Use [[Repartition]] for RDD-like + * `coalesce` and `repartition`. + */ +case class RepartitionByExpression(partitionExpressions: Seq[Expression], child: LogicalPlan) extends RedistributeData diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala index 5390ce43c6639..fa71001c9336e 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala @@ -1253,18 +1253,6 @@ class ExpressionEvaluationSuite extends ExpressionEvaluationBaseSuite { unaryMathFunctionEvaluation[Double](Signum, math.signum) } - test("isignum") { - unaryMathFunctionEvaluation[Int](ISignum, math.signum, (-5 to 5)) - } - - test("fsignum") { - unaryMathFunctionEvaluation[Float](FSignum, math.signum, (-5 to 5).map(_.toFloat)) - } - - test("lsignum") { - unaryMathFunctionEvaluation[Long](LSignum, math.signum, (5 to 5).map(_.toLong)) - } - test("log") { unaryMathFunctionEvaluation(Log, math.log, (0 to 20).map(_ * 0.1)) unaryMathFunctionEvaluation(Log, math.log, (-5 to -1).map(_ * 0.1), true) diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMapSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMapSuite.scala new file mode 100644 index 0000000000000..7a19e511eb8b5 --- /dev/null +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeFixedWidthAggregationMapSuite.scala @@ -0,0 +1,119 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst.expressions + +import scala.collection.JavaConverters._ +import scala.util.Random + +import org.apache.spark.unsafe.memory.{ExecutorMemoryManager, TaskMemoryManager, MemoryAllocator} +import org.scalatest.{BeforeAndAfterEach, FunSuite, Matchers} + +import org.apache.spark.sql.types._ + +class UnsafeFixedWidthAggregationMapSuite extends FunSuite with Matchers with BeforeAndAfterEach { + + import UnsafeFixedWidthAggregationMap._ + + private val groupKeySchema = StructType(StructField("product", StringType) :: Nil) + private val aggBufferSchema = StructType(StructField("salePrice", IntegerType) :: Nil) + private def emptyAggregationBuffer: Row = new GenericRow(Array[Any](0)) + + private var memoryManager: TaskMemoryManager = null + + override def beforeEach(): Unit = { + memoryManager = new TaskMemoryManager(new ExecutorMemoryManager(MemoryAllocator.HEAP)) + } + + override def afterEach(): Unit = { + if (memoryManager != null) { + memoryManager.cleanUpAllAllocatedMemory() + memoryManager = null + } + } + + test("supported schemas") { + assert(!supportsAggregationBufferSchema(StructType(StructField("x", StringType) :: Nil))) + assert(supportsGroupKeySchema(StructType(StructField("x", StringType) :: Nil))) + + assert( + !supportsAggregationBufferSchema(StructType(StructField("x", ArrayType(IntegerType)) :: Nil))) + assert( + !supportsGroupKeySchema(StructType(StructField("x", ArrayType(IntegerType)) :: Nil))) + } + + test("empty map") { + val map = new UnsafeFixedWidthAggregationMap( + emptyAggregationBuffer, + aggBufferSchema, + groupKeySchema, + memoryManager, + 1024, // initial capacity + false // disable perf metrics + ) + assert(!map.iterator().hasNext) + map.free() + } + + test("updating values for a single key") { + val map = new UnsafeFixedWidthAggregationMap( + emptyAggregationBuffer, + aggBufferSchema, + groupKeySchema, + memoryManager, + 1024, // initial capacity + false // disable perf metrics + ) + val groupKey = new GenericRow(Array[Any](UTF8String("cats"))) + + // Looking up a key stores a zero-entry in the map (like Python Counters or DefaultDicts) + map.getAggregationBuffer(groupKey) + val iter = map.iterator() + val entry = iter.next() + assert(!iter.hasNext) + entry.key.getString(0) should be ("cats") + entry.value.getInt(0) should be (0) + + // Modifications to rows retrieved from the map should update the values in the map + entry.value.setInt(0, 42) + map.getAggregationBuffer(groupKey).getInt(0) should be (42) + + map.free() + } + + test("inserting large random keys") { + val map = new UnsafeFixedWidthAggregationMap( + emptyAggregationBuffer, + aggBufferSchema, + groupKeySchema, + memoryManager, + 128, // initial capacity + false // disable perf metrics + ) + val rand = new Random(42) + val groupKeys: Set[String] = Seq.fill(512)(rand.nextString(1024)).toSet + groupKeys.foreach { keyString => + map.getAggregationBuffer(new GenericRow(Array[Any](UTF8String(keyString)))) + } + val seenKeys: Set[String] = map.iterator().asScala.map { entry => + entry.key.getString(0) + }.toSet + seenKeys.size should be (groupKeys.size) + seenKeys should be (groupKeys) + } + +} diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala new file mode 100644 index 0000000000000..3a60c7fd32675 --- /dev/null +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala @@ -0,0 +1,153 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.catalyst.expressions + +import java.util.Arrays + +import org.scalatest.{FunSuite, Matchers} + +import org.apache.spark.sql.types._ +import org.apache.spark.unsafe.PlatformDependent +import org.apache.spark.unsafe.array.ByteArrayMethods + +class UnsafeRowConverterSuite extends FunSuite with Matchers { + + test("basic conversion with only primitive types") { + val fieldTypes: Array[DataType] = Array(LongType, LongType, IntegerType) + val converter = new UnsafeRowConverter(fieldTypes) + + val row = new SpecificMutableRow(fieldTypes) + row.setLong(0, 0) + row.setLong(1, 1) + row.setInt(2, 2) + + val sizeRequired: Int = converter.getSizeRequirement(row) + sizeRequired should be (8 + (3 * 8)) + val buffer: Array[Long] = new Array[Long](sizeRequired / 8) + val numBytesWritten = converter.writeRow(row, buffer, PlatformDependent.LONG_ARRAY_OFFSET) + numBytesWritten should be (sizeRequired) + + val unsafeRow = new UnsafeRow() + unsafeRow.pointTo(buffer, PlatformDependent.LONG_ARRAY_OFFSET, fieldTypes.length, null) + unsafeRow.getLong(0) should be (0) + unsafeRow.getLong(1) should be (1) + unsafeRow.getInt(2) should be (2) + } + + test("basic conversion with primitive and string types") { + val fieldTypes: Array[DataType] = Array(LongType, StringType, StringType) + val converter = new UnsafeRowConverter(fieldTypes) + + val row = new SpecificMutableRow(fieldTypes) + row.setLong(0, 0) + row.setString(1, "Hello") + row.setString(2, "World") + + val sizeRequired: Int = converter.getSizeRequirement(row) + sizeRequired should be (8 + (8 * 3) + + ByteArrayMethods.roundNumberOfBytesToNearestWord("Hello".getBytes.length + 8) + + ByteArrayMethods.roundNumberOfBytesToNearestWord("World".getBytes.length + 8)) + val buffer: Array[Long] = new Array[Long](sizeRequired / 8) + val numBytesWritten = converter.writeRow(row, buffer, PlatformDependent.LONG_ARRAY_OFFSET) + numBytesWritten should be (sizeRequired) + + val unsafeRow = new UnsafeRow() + unsafeRow.pointTo(buffer, PlatformDependent.LONG_ARRAY_OFFSET, fieldTypes.length, null) + unsafeRow.getLong(0) should be (0) + unsafeRow.getString(1) should be ("Hello") + unsafeRow.getString(2) should be ("World") + } + + test("null handling") { + val fieldTypes: Array[DataType] = Array( + NullType, + BooleanType, + ByteType, + ShortType, + IntegerType, + LongType, + FloatType, + DoubleType) + val converter = new UnsafeRowConverter(fieldTypes) + + val rowWithAllNullColumns: Row = { + val r = new SpecificMutableRow(fieldTypes) + for (i <- 0 to fieldTypes.length - 1) { + r.setNullAt(i) + } + r + } + + val sizeRequired: Int = converter.getSizeRequirement(rowWithAllNullColumns) + val createdFromNullBuffer: Array[Long] = new Array[Long](sizeRequired / 8) + val numBytesWritten = converter.writeRow( + rowWithAllNullColumns, createdFromNullBuffer, PlatformDependent.LONG_ARRAY_OFFSET) + numBytesWritten should be (sizeRequired) + + val createdFromNull = new UnsafeRow() + createdFromNull.pointTo( + createdFromNullBuffer, PlatformDependent.LONG_ARRAY_OFFSET, fieldTypes.length, null) + for (i <- 0 to fieldTypes.length - 1) { + assert(createdFromNull.isNullAt(i)) + } + createdFromNull.getBoolean(1) should be (false) + createdFromNull.getByte(2) should be (0) + createdFromNull.getShort(3) should be (0) + createdFromNull.getInt(4) should be (0) + createdFromNull.getLong(5) should be (0) + assert(java.lang.Float.isNaN(createdFromNull.getFloat(6))) + assert(java.lang.Double.isNaN(createdFromNull.getFloat(7))) + + // If we have an UnsafeRow with columns that are initially non-null and we null out those + // columns, then the serialized row representation should be identical to what we would get by + // creating an entirely null row via the converter + val rowWithNoNullColumns: Row = { + val r = new SpecificMutableRow(fieldTypes) + r.setNullAt(0) + r.setBoolean(1, false) + r.setByte(2, 20) + r.setShort(3, 30) + r.setInt(4, 400) + r.setLong(5, 500) + r.setFloat(6, 600) + r.setDouble(7, 700) + r + } + val setToNullAfterCreationBuffer: Array[Long] = new Array[Long](sizeRequired / 8) + converter.writeRow( + rowWithNoNullColumns, setToNullAfterCreationBuffer, PlatformDependent.LONG_ARRAY_OFFSET) + val setToNullAfterCreation = new UnsafeRow() + setToNullAfterCreation.pointTo( + setToNullAfterCreationBuffer, PlatformDependent.LONG_ARRAY_OFFSET, fieldTypes.length, null) + + setToNullAfterCreation.isNullAt(0) should be (rowWithNoNullColumns.isNullAt(0)) + setToNullAfterCreation.getBoolean(1) should be (rowWithNoNullColumns.getBoolean(1)) + setToNullAfterCreation.getByte(2) should be (rowWithNoNullColumns.getByte(2)) + setToNullAfterCreation.getShort(3) should be (rowWithNoNullColumns.getShort(3)) + setToNullAfterCreation.getInt(4) should be (rowWithNoNullColumns.getInt(4)) + setToNullAfterCreation.getLong(5) should be (rowWithNoNullColumns.getLong(5)) + setToNullAfterCreation.getFloat(6) should be (rowWithNoNullColumns.getFloat(6)) + setToNullAfterCreation.getDouble(7) should be (rowWithNoNullColumns.getDouble(7)) + + for (i <- 0 to fieldTypes.length - 1) { + setToNullAfterCreation.setNullAt(i) + } + assert(Arrays.equals(createdFromNullBuffer, setToNullAfterCreationBuffer)) + } + +} diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/CombiningLimitsSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/CombiningLimitsSuite.scala index 2d16d668fd522..a30052b38fc11 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/CombiningLimitsSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/CombiningLimitsSuite.scala @@ -27,6 +27,8 @@ class CombiningLimitsSuite extends PlanTest { object Optimize extends RuleExecutor[LogicalPlan] { val batches = + Batch("Filter Pushdown", FixedPoint(100), + ColumnPruning) :: Batch("Combine Limit", FixedPoint(10), CombineLimits) :: Batch("Constant Folding", FixedPoint(10), @@ -69,4 +71,21 @@ class CombiningLimitsSuite extends PlanTest { comparePlans(optimized, correctAnswer) } + + test("limits: combines two limits after ColumnPruning") { + val originalQuery = + testRelation + .select('a) + .limit(2) + .select('a) + .limit(5) + + val optimized = Optimize.execute(originalQuery.analyze) + val correctAnswer = + testRelation + .select('a) + .limit(2).analyze + + comparePlans(optimized, correctAnswer) + } } diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala index 14b28e8402610..18f92150b0966 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ConstantFoldingSuite.scala @@ -160,7 +160,7 @@ class ConstantFoldingSuite extends PlanTest { val originalQuery = testRelation .select( - Rand + Literal(1) as Symbol("c1"), + Rand(5L) + Literal(1) as Symbol("c1"), Sum('a) as Symbol("c2")) val optimized = Optimize.execute(originalQuery.analyze) @@ -168,7 +168,7 @@ class ConstantFoldingSuite extends PlanTest { val correctAnswer = testRelation .select( - Rand + Literal(1.0) as Symbol("c1"), + Rand(5L) + Literal(1.0) as Symbol("c1"), Sum('a) as Symbol("c2")) .analyze diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala index aa9708b164efa..58d415d9011e1 100644 --- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala +++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala @@ -21,7 +21,7 @@ import org.apache.spark.sql.catalyst.analysis import org.apache.spark.sql.catalyst.analysis.EliminateSubQueries import org.apache.spark.sql.catalyst.expressions.{Count, Explode} import org.apache.spark.sql.catalyst.plans.logical._ -import org.apache.spark.sql.catalyst.plans.{PlanTest, LeftOuter, RightOuter} +import org.apache.spark.sql.catalyst.plans.{LeftSemi, PlanTest, LeftOuter, RightOuter} import org.apache.spark.sql.catalyst.rules._ import org.apache.spark.sql.catalyst.dsl.plans._ import org.apache.spark.sql.catalyst.dsl.expressions._ @@ -43,6 +43,8 @@ class FilterPushdownSuite extends PlanTest { val testRelation = LocalRelation('a.int, 'b.int, 'c.int) + val testRelation1 = LocalRelation('d.int) + // This test already passes. test("eliminate subqueries") { val originalQuery = @@ -90,7 +92,23 @@ class FilterPushdownSuite extends PlanTest { comparePlans(optimized, correctAnswer) } + + test("column pruning for Project(ne, Limit)") { + val originalQuery = + testRelation + .select('a,'b) + .limit(2) + .select('a) + val optimized = Optimize.execute(originalQuery.analyze) + val correctAnswer = + testRelation + .select('a) + .limit(2).analyze + + comparePlans(optimized, correctAnswer) + } + // After this line is unimplemented. test("simple push down") { val originalQuery = @@ -197,6 +215,23 @@ class FilterPushdownSuite extends PlanTest { comparePlans(optimized, correctAnswer) } + test("joins: push down left semi join") { + val x = testRelation.subquery('x) + val y = testRelation1.subquery('y) + + val originalQuery = { + x.join(y, LeftSemi, Option("x.a".attr === "y.d".attr && "x.b".attr >= 1 && "y.d".attr >= 2)) + } + + val optimized = Optimize.execute(originalQuery.analyze) + val left = testRelation.where('b >= 1) + val right = testRelation1.where('d >= 2) + val correctAnswer = + left.join(right, LeftSemi, Option("a".attr === "d".attr)).analyze + + comparePlans(optimized, correctAnswer) + } + test("joins: push down left outer join #1") { val x = testRelation.subquery('x) val y = testRelation.subquery('y) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala index ca6ae482eb2ab..c421006c8fd2d 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala @@ -330,6 +330,17 @@ class DataFrame private[sql]( */ def na: DataFrameNaFunctions = new DataFrameNaFunctions(this) + /** + * Returns a [[DataFrameStatFunctions]] for working statistic functions support. + * {{{ + * // Finding frequent items in column with name 'a'. + * df.stat.freqItems(Seq("a")) + * }}} + * + * @group dfops + */ + def stat: DataFrameStatFunctions = new DataFrameStatFunctions(this) + /** * Cartesian join with another [[DataFrame]]. * @@ -623,17 +634,12 @@ class DataFrame private[sql]( } /** - * (Scala-specific) Compute aggregates by specifying a map from column name to - * aggregate methods. The resulting [[DataFrame]] will also contain the grouping columns. - * - * The available aggregate methods are `avg`, `max`, `min`, `sum`, `count`. - * {{{ - * // Selects the age of the oldest employee and the aggregate expense for each department - * df.groupBy("department").agg( - * "age" -> "max", - * "expense" -> "sum" - * ) - * }}} + * (Scala-specific) Aggregates on the entire [[DataFrame]] without groups. + * {{ + * // df.agg(...) is a shorthand for df.groupBy().agg(...) + * df.agg("age" -> "max", "salary" -> "avg") + * df.groupBy().agg("age" -> "max", "salary" -> "avg") + * }} * @group dfops */ def agg(aggExpr: (String, String), aggExprs: (String, String)*): DataFrame = { @@ -711,7 +717,7 @@ class DataFrame private[sql]( * @group dfops */ def sample(withReplacement: Boolean, fraction: Double, seed: Long): DataFrame = { - Sample(fraction, withReplacement, seed, logicalPlan) + Sample(0.0, fraction, withReplacement, seed, logicalPlan) } /** @@ -725,6 +731,42 @@ class DataFrame private[sql]( sample(withReplacement, fraction, Utils.random.nextLong) } + /** + * Randomly splits this [[DataFrame]] with the provided weights. + * + * @param weights weights for splits, will be normalized if they don't sum to 1. + * @param seed Seed for sampling. + * @group dfops + */ + def randomSplit(weights: Array[Double], seed: Long): Array[DataFrame] = { + val sum = weights.sum + val normalizedCumWeights = weights.map(_ / sum).scanLeft(0.0d)(_ + _) + normalizedCumWeights.sliding(2).map { x => + new DataFrame(sqlContext, Sample(x(0), x(1), false, seed, logicalPlan)) + }.toArray + } + + /** + * Randomly splits this [[DataFrame]] with the provided weights. + * + * @param weights weights for splits, will be normalized if they don't sum to 1. + * @group dfops + */ + def randomSplit(weights: Array[Double]): Array[DataFrame] = { + randomSplit(weights, Utils.random.nextLong) + } + + /** + * Randomly splits this [[DataFrame]] with the provided weights. Provided for the Python Api. + * + * @param weights weights for splits, will be normalized if they don't sum to 1. + * @param seed Seed for sampling. + * @group dfops + */ + private[spark] def randomSplit(weights: List[Double], seed: Long): Array[DataFrame] = { + randomSplit(weights.toArray, seed) + } + /** * (Scala-specific) Returns a new [[DataFrame]] where each row has been expanded to zero or more * rows by the provided function. This is similar to a `LATERAL VIEW` in HiveQL. The columns of @@ -809,15 +851,40 @@ class DataFrame private[sql]( /** * Returns a new [[DataFrame]] with a column renamed. + * This is a no-op if schema doesn't contain existingName. * @group dfops */ def withColumnRenamed(existingName: String, newName: String): DataFrame = { val resolver = sqlContext.analyzer.resolver - val colNames = schema.map { field => - val name = field.name - if (resolver(name, existingName)) Column(name).as(newName) else Column(name) + val shouldRename = schema.exists(f => resolver(f.name, existingName)) + if (shouldRename) { + val colNames = schema.map { field => + val name = field.name + if (resolver(name, existingName)) Column(name).as(newName) else Column(name) + } + select(colNames : _*) + } else { + this + } + } + + /** + * Returns a new [[DataFrame]] with a column dropped. + * This is a no-op if schema doesn't contain column name. + * @group dfops + */ + def drop(colName: String): DataFrame = { + val resolver = sqlContext.analyzer.resolver + val shouldDrop = schema.exists(f => resolver(f.name, colName)) + if (shouldDrop) { + val colsAfterDrop = schema.filter { field => + val name = field.name + !resolver(name, colName) + }.map(f => Column(f.name)) + select(colsAfterDrop : _*) + } else { + this } - select(colNames :_*) } /** @@ -961,9 +1028,7 @@ class DataFrame private[sql]( * @group rdd */ override def repartition(numPartitions: Int): DataFrame = { - sqlContext.createDataFrame( - queryExecution.toRdd.map(_.copy()).repartition(numPartitions), - schema, needsConversion = false) + Repartition(numPartitions, shuffle = true, logicalPlan) } /** @@ -974,10 +1039,7 @@ class DataFrame private[sql]( * @group rdd */ override def coalesce(numPartitions: Int): DataFrame = { - sqlContext.createDataFrame( - queryExecution.toRdd.coalesce(numPartitions), - schema, - needsConversion = false) + Repartition(numPartitions, shuffle = false, logicalPlan) } /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala new file mode 100644 index 0000000000000..e8fa82947759b --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala @@ -0,0 +1,81 @@ +/* +* Licensed to the Apache Software Foundation (ASF) under one or more +* contributor license agreements. See the NOTICE file distributed with +* this work for additional information regarding copyright ownership. +* The ASF licenses this file to You under the Apache License, Version 2.0 +* (the "License"); you may not use this file except in compliance with +* the License. You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +package org.apache.spark.sql + +import org.apache.spark.annotation.Experimental +import org.apache.spark.sql.execution.stat._ + +/** + * :: Experimental :: + * Statistic functions for [[DataFrame]]s. + */ +@Experimental +final class DataFrameStatFunctions private[sql](df: DataFrame) { + + /** + * Finding frequent items for columns, possibly with false positives. Using the + * frequent element count algorithm described in + * [[http://dx.doi.org/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou]]. + * The `support` should be greater than 1e-4. + * + * @param cols the names of the columns to search frequent items in. + * @param support The minimum frequency for an item to be considered `frequent`. Should be greater + * than 1e-4. + * @return A Local DataFrame with the Array of frequent items for each column. + */ + def freqItems(cols: Array[String], support: Double): DataFrame = { + FrequentItems.singlePassFreqItems(df, cols, support) + } + + /** + * Finding frequent items for columns, possibly with false positives. Using the + * frequent element count algorithm described in + * [[http://dx.doi.org/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou]]. + * Uses a `default` support of 1%. + * + * @param cols the names of the columns to search frequent items in. + * @return A Local DataFrame with the Array of frequent items for each column. + */ + def freqItems(cols: Array[String]): DataFrame = { + FrequentItems.singlePassFreqItems(df, cols, 0.01) + } + + /** + * Python friendly implementation for `freqItems` + */ + def freqItems(cols: Seq[String], support: Double): DataFrame = { + FrequentItems.singlePassFreqItems(df, cols, support) + } + + /** + * Python friendly implementation for `freqItems` with a default `support` of 1%. + */ + def freqItems(cols: Seq[String]): DataFrame = { + FrequentItems.singlePassFreqItems(df, cols, 0.01) + } + + /** + * Calculate the sample covariance of two numerical columns of a DataFrame. + * @param col1 the name of the first column + * @param col2 the name of the second column + * @return the covariance of the two columns. + */ + def cov(col1: String, col2: String): Double = { + StatFunctions.calculateCov(df, Seq(col1, col2)) + } +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala index 4fc5de7e824fe..2fa602a6082dc 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLConf.scala @@ -30,6 +30,7 @@ private[spark] object SQLConf { val DEFAULT_SIZE_IN_BYTES = "spark.sql.defaultSizeInBytes" val SHUFFLE_PARTITIONS = "spark.sql.shuffle.partitions" val CODEGEN_ENABLED = "spark.sql.codegen" + val UNSAFE_ENABLED = "spark.sql.unsafe.enabled" val DIALECT = "spark.sql.dialect" val PARQUET_BINARY_AS_STRING = "spark.sql.parquet.binaryAsString" @@ -149,6 +150,14 @@ private[sql] class SQLConf extends Serializable { */ private[spark] def codegenEnabled: Boolean = getConf(CODEGEN_ENABLED, "false").toBoolean + /** + * When set to true, Spark SQL will use managed memory for certain operations. This option only + * takes effect if codegen is enabled. + * + * Defaults to false as this feature is currently experimental. + */ + private[spark] def unsafeEnabled: Boolean = getConf(UNSAFE_ENABLED, "false").toBoolean + private[spark] def useSqlSerializer2: Boolean = getConf(USE_SQL_SERIALIZER2, "true").toBoolean /** diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index a279b0f07c38a..7eabb93c1e3d6 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala @@ -24,6 +24,7 @@ import scala.collection.JavaConversions._ import scala.collection.immutable import scala.language.implicitConversions import scala.reflect.runtime.universe.TypeTag +import scala.util.control.NonFatal import com.google.common.reflect.TypeToken @@ -32,9 +33,11 @@ import org.apache.spark.api.java.{JavaRDD, JavaSparkContext} import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.analysis._ import org.apache.spark.sql.catalyst.expressions._ +import org.apache.spark.sql.catalyst.errors.DialectException import org.apache.spark.sql.catalyst.optimizer.{DefaultOptimizer, Optimizer} import org.apache.spark.sql.catalyst.plans.logical.{LocalRelation, LogicalPlan} import org.apache.spark.sql.catalyst.rules.RuleExecutor +import org.apache.spark.sql.catalyst.Dialect import org.apache.spark.sql.catalyst.{CatalystTypeConverters, ScalaReflection, expressions} import org.apache.spark.sql.execution.{Filter, _} import org.apache.spark.sql.jdbc.{JDBCPartition, JDBCPartitioningInfo, JDBCRelation} @@ -44,6 +47,42 @@ import org.apache.spark.sql.types._ import org.apache.spark.util.Utils import org.apache.spark.{Partition, SparkContext} +/** + * Currently we support the default dialect named "sql", associated with the class + * [[DefaultDialect]] + * + * And we can also provide custom SQL Dialect, for example in Spark SQL CLI: + * {{{ + *-- switch to "hiveql" dialect + * spark-sql>SET spark.sql.dialect=hiveql; + * spark-sql>SELECT * FROM src LIMIT 1; + * + *-- switch to "sql" dialect + * spark-sql>SET spark.sql.dialect=sql; + * spark-sql>SELECT * FROM src LIMIT 1; + * + *-- register the new SQL dialect + * spark-sql> SET spark.sql.dialect=com.xxx.xxx.SQL99Dialect; + * spark-sql> SELECT * FROM src LIMIT 1; + * + *-- register the non-exist SQL dialect + * spark-sql> SET spark.sql.dialect=NotExistedClass; + * spark-sql> SELECT * FROM src LIMIT 1; + * + *-- Exception will be thrown and switch to dialect + *-- "sql" (for SQLContext) or + *-- "hiveql" (for HiveContext) + * }}} + */ +private[spark] class DefaultDialect extends Dialect { + @transient + protected val sqlParser = new catalyst.SqlParser + + override def parse(sqlText: String): LogicalPlan = { + sqlParser.parse(sqlText) + } +} + /** * The entry point for working with structured data (rows and columns) in Spark. Allows the * creation of [[DataFrame]] objects as well as the execution of SQL queries. @@ -135,14 +174,27 @@ class SQLContext(@transient val sparkContext: SparkContext) protected[sql] val ddlParser = new DDLParser(sqlParser.parse(_)) @transient - protected[sql] val sqlParser = { - val fallback = new catalyst.SqlParser - new SparkSQLParser(fallback.parse(_)) + protected[sql] val sqlParser = new SparkSQLParser(getSQLDialect().parse(_)) + + protected[sql] def getSQLDialect(): Dialect = { + try { + val clazz = Utils.classForName(dialectClassName) + clazz.newInstance().asInstanceOf[Dialect] + } catch { + case NonFatal(e) => + // Since we didn't find the available SQL Dialect, it will fail even for SET command: + // SET spark.sql.dialect=sql; Let's reset as default dialect automatically. + val dialect = conf.dialect + // reset the sql dialect + conf.unsetConf(SQLConf.DIALECT) + // throw out the exception, and the default sql dialect will take effect for next query. + throw new DialectException( + s"""Instantiating dialect '$dialect' failed. + |Reverting to default dialect '${conf.dialect}'""".stripMargin, e) + } } - protected[sql] def parseSql(sql: String): LogicalPlan = { - ddlParser.parse(sql, false).getOrElse(sqlParser.parse(sql)) - } + protected[sql] def parseSql(sql: String): LogicalPlan = ddlParser.parse(sql, false) protected[sql] def executeSql(sql: String): this.QueryExecution = executePlan(parseSql(sql)) @@ -156,6 +208,12 @@ class SQLContext(@transient val sparkContext: SparkContext) @transient protected[sql] val defaultSession = createSession() + protected[sql] def dialectClassName = if (conf.dialect == "sql") { + classOf[DefaultDialect].getCanonicalName + } else { + conf.dialect + } + sparkContext.getConf.getAll.foreach { case (key, value) if key.startsWith("spark.sql") => setConf(key, value) case _ => @@ -428,20 +486,6 @@ class SQLContext(@transient val sparkContext: SparkContext) createDataFrame(rowRDD.rdd, schema) } - /** - * Creates a [[DataFrame]] from an [[JavaRDD]] containing [[Row]]s by applying - * a seq of names of columns to this RDD, the data type for each column will - * be inferred by the first row. - * - * @param rowRDD an JavaRDD of Row - * @param columns names for each column - * @return DataFrame - * @group dataframes - */ - def createDataFrame(rowRDD: JavaRDD[Row], columns: java.util.List[String]): DataFrame = { - createDataFrame(rowRDD.rdd, columns.toSeq) - } - /** * Applies a schema to an RDD of Java Beans. * @@ -945,11 +989,7 @@ class SQLContext(@transient val sparkContext: SparkContext) * @group basic */ def sql(sqlText: String): DataFrame = { - if (conf.dialect == "sql") { - DataFrame(this, parseSql(sqlText)) - } else { - sys.error(s"Unsupported SQL dialect: ${conf.dialect}") - } + DataFrame(this, parseSql(sqlText)) } /** @@ -1011,6 +1051,8 @@ class SQLContext(@transient val sparkContext: SparkContext) def codegenEnabled: Boolean = self.conf.codegenEnabled + def unsafeEnabled: Boolean = self.conf.unsafeEnabled + def numPartitions: Int = self.conf.numShufflePartitions def strategies: Seq[Strategy] = diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala index 1fd387eec7e57..57effbf7ec501 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/ExistingRDD.scala @@ -84,7 +84,7 @@ object RDDConversions { } /** Logical plan node for scanning data from an RDD. */ -case class LogicalRDD(output: Seq[Attribute], rdd: RDD[Row])(sqlContext: SQLContext) +private[sql] case class LogicalRDD(output: Seq[Attribute], rdd: RDD[Row])(sqlContext: SQLContext) extends LogicalPlan with MultiInstanceRelation { override def children: Seq[LogicalPlan] = Nil @@ -105,11 +105,12 @@ case class LogicalRDD(output: Seq[Attribute], rdd: RDD[Row])(sqlContext: SQLCont } /** Physical plan node for scanning data from an RDD. */ -case class PhysicalRDD(output: Seq[Attribute], rdd: RDD[Row]) extends LeafNode { +private[sql] case class PhysicalRDD(output: Seq[Attribute], rdd: RDD[Row]) extends LeafNode { override def execute(): RDD[Row] = rdd } /** Logical plan node for scanning data from a local collection. */ +private[sql] case class LogicalLocalTable(output: Seq[Attribute], rows: Seq[Row])(sqlContext: SQLContext) extends LogicalPlan with MultiInstanceRelation { diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala index b1ef6556de1e9..5d9f202681045 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GeneratedAggregate.scala @@ -17,6 +17,7 @@ package org.apache.spark.sql.execution +import org.apache.spark.TaskContext import org.apache.spark.annotation.DeveloperApi import org.apache.spark.rdd.RDD import org.apache.spark.sql.catalyst.trees._ @@ -40,6 +41,7 @@ case class AggregateEvaluation( * ensure all values where `groupingExpressions` are equal are present. * @param groupingExpressions expressions that are evaluated to determine grouping. * @param aggregateExpressions expressions that are computed for each group. + * @param unsafeEnabled whether to allow Unsafe-based aggregation buffers to be used. * @param child the input data source. */ @DeveloperApi @@ -47,6 +49,7 @@ case class GeneratedAggregate( partial: Boolean, groupingExpressions: Seq[Expression], aggregateExpressions: Seq[NamedExpression], + unsafeEnabled: Boolean, child: SparkPlan) extends UnaryNode { @@ -225,6 +228,21 @@ case class GeneratedAggregate( case e: Expression if groupMap.contains(e) => groupMap(e) }) + val aggregationBufferSchema: StructType = StructType.fromAttributes(computationSchema) + + val groupKeySchema: StructType = { + val fields = groupingExpressions.zipWithIndex.map { case (expr, idx) => + // This is a dummy field name + StructField(idx.toString, expr.dataType, expr.nullable) + } + StructType(fields) + } + + val schemaSupportsUnsafe: Boolean = { + UnsafeFixedWidthAggregationMap.supportsAggregationBufferSchema(aggregationBufferSchema) && + UnsafeFixedWidthAggregationMap.supportsGroupKeySchema(groupKeySchema) + } + child.execute().mapPartitions { iter => // Builds a new custom class for holding the results of aggregation for a group. val initialValues = computeFunctions.flatMap(_.initialValues) @@ -265,7 +283,49 @@ case class GeneratedAggregate( val resultProjection = resultProjectionBuilder() Iterator(resultProjection(buffer)) + } else if (unsafeEnabled && schemaSupportsUnsafe) { + log.info("Using Unsafe-based aggregator") + val aggregationMap = new UnsafeFixedWidthAggregationMap( + newAggregationBuffer(EmptyRow), + aggregationBufferSchema, + groupKeySchema, + TaskContext.get.taskMemoryManager(), + 1024 * 16, // initial capacity + false // disable tracking of performance metrics + ) + + while (iter.hasNext) { + val currentRow: Row = iter.next() + val groupKey: Row = groupProjection(currentRow) + val aggregationBuffer = aggregationMap.getAggregationBuffer(groupKey) + updateProjection.target(aggregationBuffer)(joinedRow(aggregationBuffer, currentRow)) + } + + new Iterator[Row] { + private[this] val mapIterator = aggregationMap.iterator() + private[this] val resultProjection = resultProjectionBuilder() + + def hasNext: Boolean = mapIterator.hasNext + + def next(): Row = { + val entry = mapIterator.next() + val result = resultProjection(joinedRow(entry.key, entry.value)) + if (hasNext) { + result + } else { + // This is the last element in the iterator, so let's free the buffer. Before we do, + // though, we need to make a defensive copy of the result so that we don't return an + // object that might contain dangling pointers to the freed memory + val resultCopy = result.copy() + aggregationMap.free() + resultCopy + } + } + } } else { + if (unsafeEnabled) { + log.info("Not using Unsafe-based aggregator because it is not supported for this schema") + } val buffers = new java.util.HashMap[Row, MutableRow]() var currentRow: Row = null diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala index 8a8c3a404323a..ace9af5f384c9 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/LocalTableScan.scala @@ -26,7 +26,7 @@ import org.apache.spark.sql.catalyst.expressions.Attribute /** * Physical plan node for scanning data from a local collection. */ -case class LocalTableScan(output: Seq[Attribute], rows: Seq[Row]) extends LeafNode { +private[sql] case class LocalTableScan(output: Seq[Attribute], rows: Seq[Row]) extends LeafNode { private lazy val rdd = sqlContext.sparkContext.parallelize(rows) diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer2.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer2.scala index cec97de2cd8e4..9552f41115866 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer2.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSqlSerializer2.scala @@ -50,10 +50,10 @@ private[sql] class Serializer2SerializationStream( extends SerializationStream with Logging { val rowOut = new DataOutputStream(out) - val writeKey = SparkSqlSerializer2.createSerializationFunction(keySchema, rowOut) - val writeValue = SparkSqlSerializer2.createSerializationFunction(valueSchema, rowOut) + val writeKeyFunc = SparkSqlSerializer2.createSerializationFunction(keySchema, rowOut) + val writeValueFunc = SparkSqlSerializer2.createSerializationFunction(valueSchema, rowOut) - def writeObject[T: ClassTag](t: T): SerializationStream = { + override def writeObject[T: ClassTag](t: T): SerializationStream = { val kv = t.asInstanceOf[Product2[Row, Row]] writeKey(kv._1) writeValue(kv._2) @@ -61,6 +61,16 @@ private[sql] class Serializer2SerializationStream( this } + override def writeKey[T: ClassTag](t: T): SerializationStream = { + writeKeyFunc(t.asInstanceOf[Row]) + this + } + + override def writeValue[T: ClassTag](t: T): SerializationStream = { + writeValueFunc(t.asInstanceOf[Row]) + this + } + def flush(): Unit = { rowOut.flush() } @@ -83,17 +93,27 @@ private[sql] class Serializer2DeserializationStream( val key = if (keySchema != null) new SpecificMutableRow(keySchema) else null val value = if (valueSchema != null) new SpecificMutableRow(valueSchema) else null - val readKey = SparkSqlSerializer2.createDeserializationFunction(keySchema, rowIn, key) - val readValue = SparkSqlSerializer2.createDeserializationFunction(valueSchema, rowIn, value) + val readKeyFunc = SparkSqlSerializer2.createDeserializationFunction(keySchema, rowIn, key) + val readValueFunc = SparkSqlSerializer2.createDeserializationFunction(valueSchema, rowIn, value) - def readObject[T: ClassTag](): T = { - readKey() - readValue() + override def readObject[T: ClassTag](): T = { + readKeyFunc() + readValueFunc() (key, value).asInstanceOf[T] } - def close(): Unit = { + override def readKey[T: ClassTag](): T = { + readKeyFunc() + key.asInstanceOf[T] + } + + override def readValue[T: ClassTag](): T = { + readValueFunc() + value.asInstanceOf[T] + } + + override def close(): Unit = { rowIn.close() } } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala index 030ef118f75d4..326e8ce4ca524 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala @@ -136,10 +136,12 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { partial = false, namedGroupingAttributes, rewrittenAggregateExpressions, + unsafeEnabled, execution.GeneratedAggregate( partial = true, groupingExpressions, partialComputation, + unsafeEnabled, planLater(child))) :: Nil // Cases where some aggregate can not be codegened @@ -283,7 +285,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { case logical.Distinct(child) => execution.Distinct(partial = false, execution.Distinct(partial = true, planLater(child))) :: Nil - + case logical.Repartition(numPartitions, shuffle, child) => + execution.Repartition(numPartitions, shuffle, planLater(child)) :: Nil case logical.SortPartitions(sortExprs, child) => // This sort only sorts tuples within a partition. Its requiredDistribution will be // an UnspecifiedDistribution. @@ -300,8 +303,8 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { execution.Expand(projections, output, planLater(child)) :: Nil case logical.Aggregate(group, agg, child) => execution.Aggregate(partial = false, group, agg, planLater(child)) :: Nil - case logical.Sample(fraction, withReplacement, seed, child) => - execution.Sample(fraction, withReplacement, seed, planLater(child)) :: Nil + case logical.Sample(lb, ub, withReplacement, seed, child) => + execution.Sample(lb, ub, withReplacement, seed, planLater(child)) :: Nil case logical.LocalRelation(output, data) => LocalTableScan(output, data) :: Nil case logical.Limit(IntegerLiteral(limit), child) => @@ -317,7 +320,7 @@ private[sql] abstract class SparkStrategies extends QueryPlanner[SparkPlan] { generator, join = join, outer = outer, g.output, planLater(child)) :: Nil case logical.OneRowRelation => execution.PhysicalRDD(Nil, singleRowRdd) :: Nil - case logical.Repartition(expressions, child) => + case logical.RepartitionByExpression(expressions, child) => execution.Exchange( HashPartitioning(expressions, numPartitions), Nil, planLater(child)) :: Nil case e @ EvaluatePython(udf, child, _) => diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala index d286fe81bee5f..5ca11e67a9434 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala @@ -63,16 +63,32 @@ case class Filter(condition: Expression, child: SparkPlan) extends UnaryNode { /** * :: DeveloperApi :: + * Sample the dataset. + * @param lowerBound Lower-bound of the sampling probability (usually 0.0) + * @param upperBound Upper-bound of the sampling probability. The expected fraction sampled + * will be ub - lb. + * @param withReplacement Whether to sample with replacement. + * @param seed the random seed + * @param child the QueryPlan */ @DeveloperApi -case class Sample(fraction: Double, withReplacement: Boolean, seed: Long, child: SparkPlan) +case class Sample( + lowerBound: Double, + upperBound: Double, + withReplacement: Boolean, + seed: Long, + child: SparkPlan) extends UnaryNode { override def output: Seq[Attribute] = child.output // TODO: How to pick seed? override def execute(): RDD[Row] = { - child.execute().map(_.copy()).sample(withReplacement, fraction, seed) + if (withReplacement) { + child.execute().map(_.copy()).sample(withReplacement, upperBound - lowerBound, seed) + } else { + child.execute().map(_.copy()).randomSampleWithRange(lowerBound, upperBound, seed) + } } } @@ -245,6 +261,20 @@ case class Distinct(partial: Boolean, child: SparkPlan) extends UnaryNode { } } +/** + * :: DeveloperApi :: + * Return a new RDD that has exactly `numPartitions` partitions. + */ +@DeveloperApi +case class Repartition(numPartitions: Int, shuffle: Boolean, child: SparkPlan) + extends UnaryNode { + override def output: Seq[Attribute] = child.output + + override def execute(): RDD[Row] = { + child.execute().map(_.copy()).coalesce(numPartitions, shuffle) + } +} + /** * :: DeveloperApi :: diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala index 99f24910fd61f..98df5bef34efa 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/commands.scala @@ -42,7 +42,7 @@ trait RunnableCommand extends logical.Command { * A physical operator that executes the run method of a `RunnableCommand` and * saves the result to prevent multiple executions. */ -case class ExecutedCommand(cmd: RunnableCommand) extends SparkPlan { +private[sql] case class ExecutedCommand(cmd: RunnableCommand) extends SparkPlan { /** * A concrete command should override this lazy field to wrap up any side effects caused by the * command or any other computation that should be evaluated exactly once. The value of this field diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala index 56200f6b8c8a9..6aaf35fb429e2 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNestedLoopJoin.scala @@ -59,10 +59,7 @@ case class BroadcastNestedLoopJoin( } @transient private lazy val boundCondition = - InterpretedPredicate.create( - condition - .map(c => BindReferences.bindReference(c, left.output ++ right.output)) - .getOrElse(Literal(true))) + newPredicate(condition.getOrElse(Literal(true)), left.output ++ right.output) override def execute(): RDD[Row] = { val broadcastedRelation = diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala index e06f63f94b78b..b03af410dca08 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala @@ -45,10 +45,7 @@ case class LeftSemiJoinBNL( override def right: SparkPlan = broadcast @transient private lazy val boundCondition = - InterpretedPredicate.create( - condition - .map(c => BindReferences.bindReference(c, left.output ++ right.output)) - .getOrElse(Literal(true))) + newPredicate(condition.getOrElse(Literal(true)), left.output ++ right.output) override def execute(): RDD[Row] = { val broadcastedRelation = diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala new file mode 100644 index 0000000000000..5ae7e107544f8 --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala @@ -0,0 +1,121 @@ +/* +* Licensed to the Apache Software Foundation (ASF) under one or more +* contributor license agreements. See the NOTICE file distributed with +* this work for additional information regarding copyright ownership. +* The ASF licenses this file to You under the Apache License, Version 2.0 +* (the "License"); you may not use this file except in compliance with +* the License. You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +package org.apache.spark.sql.execution.stat + +import scala.collection.mutable.{Map => MutableMap} + +import org.apache.spark.Logging +import org.apache.spark.sql.{Column, DataFrame, Row} +import org.apache.spark.sql.catalyst.plans.logical.LocalRelation +import org.apache.spark.sql.types.{ArrayType, StructField, StructType} + +private[sql] object FrequentItems extends Logging { + + /** A helper class wrapping `MutableMap[Any, Long]` for simplicity. */ + private class FreqItemCounter(size: Int) extends Serializable { + val baseMap: MutableMap[Any, Long] = MutableMap.empty[Any, Long] + + /** + * Add a new example to the counts if it exists, otherwise deduct the count + * from existing items. + */ + def add(key: Any, count: Long): this.type = { + if (baseMap.contains(key)) { + baseMap(key) += count + } else { + if (baseMap.size < size) { + baseMap += key -> count + } else { + // TODO: Make this more efficient... A flatMap? + baseMap.retain((k, v) => v > count) + baseMap.transform((k, v) => v - count) + } + } + this + } + + /** + * Merge two maps of counts. + * @param other The map containing the counts for that partition + */ + def merge(other: FreqItemCounter): this.type = { + other.baseMap.foreach { case (k, v) => + add(k, v) + } + this + } + } + + /** + * Finding frequent items for columns, possibly with false positives. Using the + * frequent element count algorithm described in + * [[http://dx.doi.org/10.1145/762471.762473, proposed by Karp, Schenker, and Papadimitriou]]. + * The `support` should be greater than 1e-4. + * For Internal use only. + * + * @param df The input DataFrame + * @param cols the names of the columns to search frequent items in + * @param support The minimum frequency for an item to be considered `frequent`. Should be greater + * than 1e-4. + * @return A Local DataFrame with the Array of frequent items for each column. + */ + private[sql] def singlePassFreqItems( + df: DataFrame, + cols: Seq[String], + support: Double): DataFrame = { + require(support >= 1e-4, s"support ($support) must be greater than 1e-4.") + val numCols = cols.length + // number of max items to keep counts for + val sizeOfMap = (1 / support).toInt + val countMaps = Seq.tabulate(numCols)(i => new FreqItemCounter(sizeOfMap)) + val originalSchema = df.schema + val colInfo = cols.map { name => + val index = originalSchema.fieldIndex(name) + (name, originalSchema.fields(index).dataType) + } + + val freqItems = df.select(cols.map(Column(_)):_*).rdd.aggregate(countMaps)( + seqOp = (counts, row) => { + var i = 0 + while (i < numCols) { + val thisMap = counts(i) + val key = row.get(i) + thisMap.add(key, 1L) + i += 1 + } + counts + }, + combOp = (baseCounts, counts) => { + var i = 0 + while (i < numCols) { + baseCounts(i).merge(counts(i)) + i += 1 + } + baseCounts + } + ) + val justItems = freqItems.map(m => m.baseMap.keys.toSeq) + val resultRow = Row(justItems:_*) + // append frequent Items to the column name for easy debugging + val outputCols = colInfo.map { v => + StructField(v._1 + "_freqItems", ArrayType(v._2, false)) + } + val schema = StructType(outputCols).toAttributes + new DataFrame(df.sqlContext, LocalRelation(schema, Seq(resultRow))) + } +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala new file mode 100644 index 0000000000000..d4a94c24d9866 --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala @@ -0,0 +1,80 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql.execution.stat + +import org.apache.spark.sql.catalyst.expressions.Cast +import org.apache.spark.sql.{Column, DataFrame} +import org.apache.spark.sql.types.{DoubleType, NumericType} + +private[sql] object StatFunctions { + + /** Helper class to simplify tracking and merging counts. */ + private class CovarianceCounter extends Serializable { + var xAvg = 0.0 + var yAvg = 0.0 + var Ck = 0.0 + var count = 0L + // add an example to the calculation + def add(x: Double, y: Double): this.type = { + val oldX = xAvg + count += 1 + xAvg += (x - xAvg) / count + yAvg += (y - yAvg) / count + Ck += (y - yAvg) * (x - oldX) + this + } + // merge counters from other partitions. Formula can be found at: + // http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Covariance + def merge(other: CovarianceCounter): this.type = { + val totalCount = count + other.count + Ck += other.Ck + + (xAvg - other.xAvg) * (yAvg - other.yAvg) * count / totalCount * other.count + xAvg = (xAvg * count + other.xAvg * other.count) / totalCount + yAvg = (yAvg * count + other.yAvg * other.count) / totalCount + count = totalCount + this + } + // return the sample covariance for the observed examples + def cov: Double = Ck / (count - 1) + } + + /** + * Calculate the covariance of two numerical columns of a DataFrame. + * @param df The DataFrame + * @param cols the column names + * @return the covariance of the two columns. + */ + private[sql] def calculateCov(df: DataFrame, cols: Seq[String]): Double = { + require(cols.length == 2, "Currently cov supports calculating the covariance " + + "between two columns.") + cols.map(name => (name, df.schema.fields.find(_.name == name))).foreach { case (name, data) => + require(data.nonEmpty, s"Couldn't find column with name $name") + require(data.get.dataType.isInstanceOf[NumericType], "Covariance calculation for columns " + + s"with dataType ${data.get.dataType} not supported.") + } + val columns = cols.map(n => Column(Cast(Column(n).expr, DoubleType))) + val counts = df.select(columns:_*).rdd.aggregate(new CovarianceCounter)( + seqOp = (counter, row) => { + counter.add(row.getDouble(0), row.getDouble(1)) + }, + combOp = (baseCounter, other) => { + baseCounter.merge(other) + }) + counts.cov + } +} diff --git a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala index aa31d04a0cbe4..7e283393d0563 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala @@ -22,10 +22,10 @@ import scala.reflect.runtime.universe.{TypeTag, typeTag} import org.apache.spark.annotation.Experimental import org.apache.spark.sql.catalyst.ScalaReflection -import org.apache.spark.sql.catalyst.analysis.{UnresolvedFunction, Star} +import org.apache.spark.sql.catalyst.analysis.{UnresolvedAttribute, UnresolvedFunction, Star} import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.types._ - +import org.apache.spark.util.Utils /** * :: Experimental :: @@ -283,6 +283,23 @@ object functions { */ def abs(e: Column): Column = Abs(e.expr) + /** + * Creates a new array column. The input columns must all have the same data type. + * + * @group normal_funcs + */ + @scala.annotation.varargs + def array(cols: Column*): Column = CreateArray(cols.map(_.expr)) + + /** + * Creates a new array column. The input columns must all have the same data type. + * + * @group normal_funcs + */ + def array(colName: String, colNames: String*): Column = { + array((colName +: colNames).map(col) : _*) + } + /** * Returns the first column that is not null. * {{{ @@ -346,6 +363,34 @@ object functions { */ def not(e: Column): Column = !e + /** + * Generate a random column with i.i.d. samples from U[0.0, 1.0]. + * + * @group normal_funcs + */ + def rand(seed: Long): Column = Rand(seed) + + /** + * Generate a random column with i.i.d. samples from U[0.0, 1.0]. + * + * @group normal_funcs + */ + def rand(): Column = rand(Utils.random.nextLong) + + /** + * Generate a column with i.i.d. samples from the standard normal distribution. + * + * @group normal_funcs + */ + def randn(seed: Long): Column = Randn(seed) + + /** + * Generate a column with i.i.d. samples from the standard normal distribution. + * + * @group normal_funcs + */ + def randn(): Column = randn(Utils.random.nextLong) + /** * Partition ID of the Spark task. * @@ -362,6 +407,28 @@ object functions { */ def sqrt(e: Column): Column = Sqrt(e.expr) + /** + * Creates a new struct column. The input column must be a column in a [[DataFrame]], or + * a derived column expression that is named (i.e. aliased). + * + * @group normal_funcs + */ + @scala.annotation.varargs + def struct(cols: Column*): Column = { + require(cols.forall(_.expr.isInstanceOf[NamedExpression]), + s"struct input columns must all be named or aliased ($cols)") + CreateStruct(cols.map(_.expr.asInstanceOf[NamedExpression])) + } + + /** + * Creates a new struct column that composes multiple input columns. + * + * @group normal_funcs + */ + def struct(colName: String, colNames: String*): Column = { + struct((colName +: colNames).map(col) : _*) + } + /** * Converts a string expression to upper case. * diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala index f3b5455574d1a..2f6ba48dbc3d9 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala @@ -37,7 +37,7 @@ private[sql] object JDBCRDD extends Logging { * @param sqlType - A field of java.sql.Types * @return The Catalyst type corresponding to sqlType. */ - private def getCatalystType(sqlType: Int): DataType = { + private def getCatalystType(sqlType: Int, precision: Int, scale: Int): DataType = { val answer = sqlType match { case java.sql.Types.ARRAY => null case java.sql.Types.BIGINT => LongType @@ -49,6 +49,8 @@ private[sql] object JDBCRDD extends Logging { case java.sql.Types.CLOB => StringType case java.sql.Types.DATALINK => null case java.sql.Types.DATE => DateType + case java.sql.Types.DECIMAL + if precision != 0 || scale != 0 => DecimalType(precision, scale) case java.sql.Types.DECIMAL => DecimalType.Unlimited case java.sql.Types.DISTINCT => null case java.sql.Types.DOUBLE => DoubleType @@ -61,6 +63,8 @@ private[sql] object JDBCRDD extends Logging { case java.sql.Types.NCHAR => StringType case java.sql.Types.NCLOB => StringType case java.sql.Types.NULL => null + case java.sql.Types.NUMERIC + if precision != 0 || scale != 0 => DecimalType(precision, scale) case java.sql.Types.NUMERIC => DecimalType.Unlimited case java.sql.Types.NVARCHAR => StringType case java.sql.Types.OTHER => null @@ -109,10 +113,11 @@ private[sql] object JDBCRDD extends Logging { val dataType = rsmd.getColumnType(i + 1) val typeName = rsmd.getColumnTypeName(i + 1) val fieldSize = rsmd.getPrecision(i + 1) + val fieldScale = rsmd.getScale(i + 1) val nullable = rsmd.isNullable(i + 1) != ResultSetMetaData.columnNoNulls val metadata = new MetadataBuilder().putString("name", columnName) var columnType = quirks.getCatalystType(dataType, typeName, fieldSize, metadata) - if (columnType == null) columnType = getCatalystType(dataType) + if (columnType == null) columnType = getCatalystType(dataType, fieldSize, fieldScale) fields(i) = StructField(columnName, columnType, nullable, metadata.build()) i = i + 1 } @@ -154,7 +159,7 @@ private[sql] object JDBCRDD extends Logging { def getConnector(driver: String, url: String, properties: Properties): () => Connection = { () => { try { - if (driver != null) Utils.getContextOrSparkClassLoader.loadClass(driver) + if (driver != null) DriverRegistry.register(driver) } catch { case e: ClassNotFoundException => { logWarning(s"Couldn't find class $driver", e); @@ -307,6 +312,7 @@ private[sql] class JDBCRDD( case BooleanType => BooleanConversion case DateType => DateConversion case DecimalType.Unlimited => DecimalConversion + case DecimalType.Fixed(d) => DecimalConversion case DoubleType => DoubleConversion case FloatType => FloatConversion case IntegerType => IntegerConversion diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala index 5f480083d5a49..d6b3fb3291a2e 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/JDBCRelation.scala @@ -100,7 +100,7 @@ private[sql] class DefaultSource extends RelationProvider { val upperBound = parameters.getOrElse("upperBound", null) val numPartitions = parameters.getOrElse("numPartitions", null) - if (driver != null) Utils.getContextOrSparkClassLoader.loadClass(driver) + if (driver != null) DriverRegistry.register(driver) if (partitionColumn != null && (lowerBound == null || upperBound == null || numPartitions == null)) { @@ -136,7 +136,7 @@ private[sql] case class JDBCRelation( override val schema: StructType = JDBCRDD.resolveTable(url, table, properties) override def buildScan(requiredColumns: Array[String], filters: Array[Filter]): RDD[Row] = { - val driver: String = DriverManager.getDriver(url).getClass.getCanonicalName + val driver: String = DriverRegistry.getDriverClassName(url) JDBCRDD.scanTable( sqlContext.sparkContext, schema, diff --git a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/jdbc.scala b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/jdbc.scala index d4e0abc040bc6..3a6c2c1e9101f 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/jdbc/jdbc.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/jdbc/jdbc.scala @@ -17,10 +17,14 @@ package org.apache.spark.sql -import java.sql.{Connection, DriverManager, PreparedStatement} +import java.sql.{Connection, Driver, DriverManager, DriverPropertyInfo, PreparedStatement, SQLFeatureNotSupportedException} +import java.util.Properties + +import scala.collection.mutable import org.apache.spark.Logging import org.apache.spark.sql.types._ +import org.apache.spark.util.Utils package object jdbc { private[sql] object JDBCWriteDetails extends Logging { @@ -179,4 +183,60 @@ package object jdbc { } } + + private [sql] class DriverWrapper(val wrapped: Driver) extends Driver { + override def acceptsURL(url: String): Boolean = wrapped.acceptsURL(url) + + override def jdbcCompliant(): Boolean = wrapped.jdbcCompliant() + + override def getPropertyInfo(url: String, info: Properties): Array[DriverPropertyInfo] = { + wrapped.getPropertyInfo(url, info) + } + + override def getMinorVersion: Int = wrapped.getMinorVersion + + def getParentLogger: java.util.logging.Logger = + throw new SQLFeatureNotSupportedException( + s"${this.getClass().getName}.getParentLogger is not yet implemented.") + + override def connect(url: String, info: Properties): Connection = wrapped.connect(url, info) + + override def getMajorVersion: Int = wrapped.getMajorVersion + } + + /** + * java.sql.DriverManager is always loaded by bootstrap classloader, + * so it can't load JDBC drivers accessible by Spark ClassLoader. + * + * To solve the problem, drivers from user-supplied jars are wrapped + * into thin wrapper. + */ + private [sql] object DriverRegistry extends Logging { + + private val wrapperMap: mutable.Map[String, DriverWrapper] = mutable.Map.empty + + def register(className: String): Unit = { + val cls = Utils.getContextOrSparkClassLoader.loadClass(className) + if (cls.getClassLoader == null) { + logTrace(s"$className has been loaded with bootstrap ClassLoader, wrapper is not required") + } else if (wrapperMap.get(className).isDefined) { + logTrace(s"Wrapper for $className already exists") + } else { + synchronized { + if (wrapperMap.get(className).isEmpty) { + val wrapper = new DriverWrapper(cls.newInstance().asInstanceOf[Driver]) + DriverManager.registerDriver(wrapper) + wrapperMap(className) = wrapper + logTrace(s"Wrapper for $className registered") + } + } + } + } + + def getDriverClassName(url: String): String = DriverManager.getDriver(url) match { + case wrapper: DriverWrapper => wrapper.wrapped.getClass.getCanonicalName + case driver => driver.getClass.getCanonicalName + } + } + } // package object jdbc diff --git a/sql/core/src/main/scala/org/apache/spark/sql/mathfunctions.scala b/sql/core/src/main/scala/org/apache/spark/sql/mathfunctions.scala index 84f62bf47f955..db47480c3864d 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/mathfunctions.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/mathfunctions.scala @@ -27,11 +27,6 @@ import org.apache.spark.sql.functions.lit /** * :: Experimental :: * Mathematical Functions available for [[DataFrame]]. - * - * @groupname double_funcs Functions that require DoubleType as an input - * @groupname int_funcs Functions that require IntegerType as an input - * @groupname float_funcs Functions that require FloatType as an input - * @groupname long_funcs Functions that require LongType as an input */ @Experimental // scalastyle:off @@ -41,522 +36,348 @@ object mathfunctions { private[this] implicit def toColumn(expr: Expression): Column = Column(expr) /** - * Computes the sine of the given value. - * - * @group double_funcs + * Computes the cosine inverse of the given value; the returned angle is in the range + * 0.0 through pi. */ - def sin(e: Column): Column = Sin(e.expr) + def acos(e: Column): Column = Acos(e.expr) /** - * Computes the sine of the given column. - * - * @group double_funcs + * Computes the cosine inverse of the given column; the returned angle is in the range + * 0.0 through pi. */ - def sin(columnName: String): Column = sin(Column(columnName)) + def acos(columnName: String): Column = acos(Column(columnName)) /** * Computes the sine inverse of the given value; the returned angle is in the range * -pi/2 through pi/2. - * - * @group double_funcs */ def asin(e: Column): Column = Asin(e.expr) /** * Computes the sine inverse of the given column; the returned angle is in the range * -pi/2 through pi/2. - * - * @group double_funcs */ def asin(columnName: String): Column = asin(Column(columnName)) /** - * Computes the hyperbolic sine of the given value. - * - * @group double_funcs - */ - def sinh(e: Column): Column = Sinh(e.expr) - - /** - * Computes the hyperbolic sine of the given column. - * - * @group double_funcs + * Computes the tangent inverse of the given value. */ - def sinh(columnName: String): Column = sinh(Column(columnName)) + def atan(e: Column): Column = Atan(e.expr) /** - * Computes the cosine of the given value. - * - * @group double_funcs + * Computes the tangent inverse of the given column. */ - def cos(e: Column): Column = Cos(e.expr) + def atan(columnName: String): Column = atan(Column(columnName)) /** - * Computes the cosine of the given column. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta). */ - def cos(columnName: String): Column = cos(Column(columnName)) + def atan2(l: Column, r: Column): Column = Atan2(l.expr, r.expr) /** - * Computes the cosine inverse of the given value; the returned angle is in the range - * 0.0 through pi. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta). */ - def acos(e: Column): Column = Acos(e.expr) + def atan2(l: Column, rightName: String): Column = atan2(l, Column(rightName)) /** - * Computes the cosine inverse of the given column; the returned angle is in the range - * 0.0 through pi. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta). */ - def acos(columnName: String): Column = acos(Column(columnName)) + def atan2(leftName: String, r: Column): Column = atan2(Column(leftName), r) /** - * Computes the hyperbolic cosine of the given value. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta). */ - def cosh(e: Column): Column = Cosh(e.expr) + def atan2(leftName: String, rightName: String): Column = + atan2(Column(leftName), Column(rightName)) /** - * Computes the hyperbolic cosine of the given column. - * - * @group double_funcs - */ - def cosh(columnName: String): Column = cosh(Column(columnName)) - - /** - * Computes the tangent of the given value. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta). */ - def tan(e: Column): Column = Tan(e.expr) + def atan2(l: Column, r: Double): Column = atan2(l, lit(r).expr) /** - * Computes the tangent of the given column. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta).= */ - def tan(columnName: String): Column = tan(Column(columnName)) + def atan2(leftName: String, r: Double): Column = atan2(Column(leftName), r) /** - * Computes the tangent inverse of the given value. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta). */ - def atan(e: Column): Column = Atan(e.expr) + def atan2(l: Double, r: Column): Column = atan2(lit(l).expr, r) /** - * Computes the tangent inverse of the given column. - * - * @group double_funcs + * Returns the angle theta from the conversion of rectangular coordinates (x, y) to + * polar coordinates (r, theta). */ - def atan(columnName: String): Column = atan(Column(columnName)) + def atan2(l: Double, rightName: String): Column = atan2(l, Column(rightName)) /** - * Computes the hyperbolic tangent of the given value. - * - * @group double_funcs + * Computes the cube-root of the given value. */ - def tanh(e: Column): Column = Tanh(e.expr) + def cbrt(e: Column): Column = Cbrt(e.expr) /** - * Computes the hyperbolic tangent of the given column. - * - * @group double_funcs + * Computes the cube-root of the given column. */ - def tanh(columnName: String): Column = tanh(Column(columnName)) + def cbrt(columnName: String): Column = cbrt(Column(columnName)) /** - * Converts an angle measured in radians to an approximately equivalent angle measured in degrees. - * - * @group double_funcs + * Computes the ceiling of the given value. */ - def toDeg(e: Column): Column = ToDegrees(e.expr) + def ceil(e: Column): Column = Ceil(e.expr) /** - * Converts an angle measured in radians to an approximately equivalent angle measured in degrees. - * - * @group double_funcs + * Computes the ceiling of the given column. */ - def toDeg(columnName: String): Column = toDeg(Column(columnName)) + def ceil(columnName: String): Column = ceil(Column(columnName)) /** - * Converts an angle measured in degrees to an approximately equivalent angle measured in radians. - * - * @group double_funcs + * Computes the cosine of the given value. */ - def toRad(e: Column): Column = ToRadians(e.expr) + def cos(e: Column): Column = Cos(e.expr) /** - * Converts an angle measured in degrees to an approximately equivalent angle measured in radians. - * - * @group double_funcs + * Computes the cosine of the given column. */ - def toRad(columnName: String): Column = toRad(Column(columnName)) + def cos(columnName: String): Column = cos(Column(columnName)) /** - * Computes the ceiling of the given value. - * - * @group double_funcs + * Computes the hyperbolic cosine of the given value. */ - def ceil(e: Column): Column = Ceil(e.expr) + def cosh(e: Column): Column = Cosh(e.expr) /** - * Computes the ceiling of the given column. - * - * @group double_funcs + * Computes the hyperbolic cosine of the given column. */ - def ceil(columnName: String): Column = ceil(Column(columnName)) + def cosh(columnName: String): Column = cosh(Column(columnName)) /** - * Computes the floor of the given value. - * - * @group double_funcs + * Computes the exponential of the given value. */ - def floor(e: Column): Column = Floor(e.expr) + def exp(e: Column): Column = Exp(e.expr) /** - * Computes the floor of the given column. - * - * @group double_funcs + * Computes the exponential of the given column. */ - def floor(columnName: String): Column = floor(Column(columnName)) + def exp(columnName: String): Column = exp(Column(columnName)) /** - * Returns the double value that is closest in value to the argument and - * is equal to a mathematical integer. - * - * @group double_funcs + * Computes the exponential of the given value minus one. */ - def rint(e: Column): Column = Rint(e.expr) + def expm1(e: Column): Column = Expm1(e.expr) /** - * Returns the double value that is closest in value to the argument and - * is equal to a mathematical integer. - * - * @group double_funcs + * Computes the exponential of the given column. */ - def rint(columnName: String): Column = rint(Column(columnName)) + def expm1(columnName: String): Column = expm1(Column(columnName)) /** - * Computes the cube-root of the given value. - * - * @group double_funcs + * Computes the floor of the given value. */ - def cbrt(e: Column): Column = Cbrt(e.expr) + def floor(e: Column): Column = Floor(e.expr) /** - * Computes the cube-root of the given column. - * - * @group double_funcs + * Computes the floor of the given column. */ - def cbrt(columnName: String): Column = cbrt(Column(columnName)) + def floor(columnName: String): Column = floor(Column(columnName)) /** - * Computes the signum of the given value. - * - * @group double_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def signum(e: Column): Column = Signum(e.expr) + def hypot(l: Column, r: Column): Column = Hypot(l.expr, r.expr) /** - * Computes the signum of the given column. - * - * @group double_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def signum(columnName: String): Column = signum(Column(columnName)) + def hypot(l: Column, rightName: String): Column = hypot(l, Column(rightName)) /** - * Computes the signum of the given value. For IntegerType. - * - * @group int_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def isignum(e: Column): Column = ISignum(e.expr) + def hypot(leftName: String, r: Column): Column = hypot(Column(leftName), r) /** - * Computes the signum of the given column. For IntegerType. - * - * @group int_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def isignum(columnName: String): Column = isignum(Column(columnName)) + def hypot(leftName: String, rightName: String): Column = + hypot(Column(leftName), Column(rightName)) /** - * Computes the signum of the given value. For FloatType. - * - * @group float_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def fsignum(e: Column): Column = FSignum(e.expr) + def hypot(l: Column, r: Double): Column = hypot(l, lit(r).expr) /** - * Computes the signum of the given column. For FloatType. - * - * @group float_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def fsignum(columnName: String): Column = fsignum(Column(columnName)) + def hypot(leftName: String, r: Double): Column = hypot(Column(leftName), r) /** - * Computes the signum of the given value. For LongType. - * - * @group long_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def lsignum(e: Column): Column = LSignum(e.expr) + def hypot(l: Double, r: Column): Column = hypot(lit(l).expr, r) /** - * Computes the signum of the given column. For FloatType. - * - * @group long_funcs + * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. */ - def lsignum(columnName: String): Column = lsignum(Column(columnName)) + def hypot(l: Double, rightName: String): Column = hypot(l, Column(rightName)) /** * Computes the natural logarithm of the given value. - * - * @group double_funcs */ def log(e: Column): Column = Log(e.expr) /** * Computes the natural logarithm of the given column. - * - * @group double_funcs */ def log(columnName: String): Column = log(Column(columnName)) /** * Computes the logarithm of the given value in Base 10. - * - * @group double_funcs */ def log10(e: Column): Column = Log10(e.expr) /** * Computes the logarithm of the given value in Base 10. - * - * @group double_funcs */ def log10(columnName: String): Column = log10(Column(columnName)) /** * Computes the natural logarithm of the given value plus one. - * - * @group double_funcs */ def log1p(e: Column): Column = Log1p(e.expr) /** * Computes the natural logarithm of the given column plus one. - * - * @group double_funcs */ def log1p(columnName: String): Column = log1p(Column(columnName)) - /** - * Computes the exponential of the given value. - * - * @group double_funcs - */ - def exp(e: Column): Column = Exp(e.expr) - - /** - * Computes the exponential of the given column. - * - * @group double_funcs - */ - def exp(columnName: String): Column = exp(Column(columnName)) - - /** - * Computes the exponential of the given value minus one. - * - * @group double_funcs - */ - def expm1(e: Column): Column = Expm1(e.expr) - - /** - * Computes the exponential of the given column. - * - * @group double_funcs - */ - def expm1(columnName: String): Column = expm1(Column(columnName)) - /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(l: Column, r: Column): Column = Pow(l.expr, r.expr) /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(l: Column, rightName: String): Column = pow(l, Column(rightName)) /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(leftName: String, r: Column): Column = pow(Column(leftName), r) /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(leftName: String, rightName: String): Column = pow(Column(leftName), Column(rightName)) /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(l: Column, r: Double): Column = pow(l, lit(r).expr) /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(leftName: String, r: Double): Column = pow(Column(leftName), r) /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(l: Double, r: Column): Column = pow(lit(l).expr, r) /** * Returns the value of the first argument raised to the power of the second argument. - * - * @group double_funcs */ def pow(l: Double, rightName: String): Column = pow(l, Column(rightName)) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Returns the double value that is closest in value to the argument and + * is equal to a mathematical integer. */ - def hypot(l: Column, r: Column): Column = Hypot(l.expr, r.expr) + def rint(e: Column): Column = Rint(e.expr) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Returns the double value that is closest in value to the argument and + * is equal to a mathematical integer. */ - def hypot(l: Column, rightName: String): Column = hypot(l, Column(rightName)) + def rint(columnName: String): Column = rint(Column(columnName)) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Computes the signum of the given value. */ - def hypot(leftName: String, r: Column): Column = hypot(Column(leftName), r) + def signum(e: Column): Column = Signum(e.expr) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Computes the signum of the given column. */ - def hypot(leftName: String, rightName: String): Column = - hypot(Column(leftName), Column(rightName)) + def signum(columnName: String): Column = signum(Column(columnName)) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Computes the sine of the given value. */ - def hypot(l: Column, r: Double): Column = hypot(l, lit(r).expr) + def sin(e: Column): Column = Sin(e.expr) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Computes the sine of the given column. */ - def hypot(leftName: String, r: Double): Column = hypot(Column(leftName), r) + def sin(columnName: String): Column = sin(Column(columnName)) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Computes the hyperbolic sine of the given value. */ - def hypot(l: Double, r: Column): Column = hypot(lit(l).expr, r) + def sinh(e: Column): Column = Sinh(e.expr) /** - * Computes `sqrt(a^2^ + b^2^)` without intermediate overflow or underflow. - * - * @group double_funcs + * Computes the hyperbolic sine of the given column. */ - def hypot(l: Double, rightName: String): Column = hypot(l, Column(rightName)) - + def sinh(columnName: String): Column = sinh(Column(columnName)) + /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Computes the tangent of the given value. */ - def atan2(l: Column, r: Column): Column = Atan2(l.expr, r.expr) + def tan(e: Column): Column = Tan(e.expr) /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Computes the tangent of the given column. */ - def atan2(l: Column, rightName: String): Column = atan2(l, Column(rightName)) - + def tan(columnName: String): Column = tan(Column(columnName)) + /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Computes the hyperbolic tangent of the given value. */ - def atan2(leftName: String, r: Column): Column = atan2(Column(leftName), r) + def tanh(e: Column): Column = Tanh(e.expr) /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Computes the hyperbolic tangent of the given column. */ - def atan2(leftName: String, rightName: String): Column = - atan2(Column(leftName), Column(rightName)) + def tanh(columnName: String): Column = tanh(Column(columnName)) /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Converts an angle measured in radians to an approximately equivalent angle measured in degrees. */ - def atan2(l: Column, r: Double): Column = atan2(l, lit(r).expr) + def toDeg(e: Column): Column = ToDegrees(e.expr) /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Converts an angle measured in radians to an approximately equivalent angle measured in degrees. */ - def atan2(leftName: String, r: Double): Column = atan2(Column(leftName), r) + def toDeg(columnName: String): Column = toDeg(Column(columnName)) /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Converts an angle measured in degrees to an approximately equivalent angle measured in radians. */ - def atan2(l: Double, r: Column): Column = atan2(lit(l).expr, r) + def toRad(e: Column): Column = ToRadians(e.expr) /** - * Returns the angle theta from the conversion of rectangular coordinates (x, y) to - * polar coordinates (r, theta). - * - * @group double_funcs + * Converts an angle measured in degrees to an approximately equivalent angle measured in radians. */ - def atan2(l: Double, rightName: String): Column = atan2(l, Column(rightName)) + def toRad(columnName: String): Column = toRad(Column(columnName)) } diff --git a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala index e7a0685e013d8..1abf3aa51cb25 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/sources/ddl.scala @@ -38,12 +38,12 @@ private[sql] class DDLParser( parseQuery: String => LogicalPlan) extends AbstractSparkSQLParser with DataTypeParser with Logging { - def parse(input: String, exceptionOnError: Boolean): Option[LogicalPlan] = { + def parse(input: String, exceptionOnError: Boolean): LogicalPlan = { try { - Some(parse(input)) + parse(input) } catch { case ddlException: DDLException => throw ddlException - case _ if !exceptionOnError => None + case _ if !exceptionOnError => parseQuery(input) case x: Throwable => throw x } } diff --git a/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java b/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java index e5c9504d21042..96fe66d0b84a6 100644 --- a/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java +++ b/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java @@ -22,10 +22,7 @@ import org.apache.spark.api.java.JavaRDD; import org.apache.spark.api.java.JavaSparkContext; -import org.apache.spark.sql.DataFrame; -import org.apache.spark.sql.Row; -import org.apache.spark.sql.SQLContext; -import org.apache.spark.sql.TestData$; +import org.apache.spark.sql.*; import org.apache.spark.sql.test.TestSQLContext; import org.apache.spark.sql.test.TestSQLContext$; import org.apache.spark.sql.types.*; @@ -107,6 +104,9 @@ public void testVarargMethods() { df2.select(pow("a", "a"), pow("b", 2.0)); df2.select(pow(col("a"), col("b")), exp("b")); df2.select(sin("a"), acos("b")); + + df2.select(rand(), acos("b")); + df2.select(col("*"), randn(5L)); } @Ignore @@ -178,5 +178,19 @@ public void testCreateDataFrameFromJavaBeans() { Assert.assertEquals(bean.getD().get(i), d.apply(i)); } } + + @Test + public void testFrequentItems() { + DataFrame df = context.table("testData2"); + String[] cols = new String[]{"a"}; + DataFrame results = df.stat().freqItems(cols, 0.2); + Assert.assertTrue(results.collect()[0].getSeq(0).contains(1)); + } + @Test + public void testCovariance() { + DataFrame df = context.table("testData2"); + Double result = df.stat().cov("a", "b"); + Assert.assertTrue(Math.abs(result) < 1e-6); + } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala index 2ba5fc21ff57c..6322faf4d9907 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/ColumnExpressionSuite.scala @@ -17,6 +17,8 @@ package org.apache.spark.sql +import org.scalatest.Matchers._ + import org.apache.spark.sql.functions._ import org.apache.spark.sql.test.TestSQLContext import org.apache.spark.sql.test.TestSQLContext.implicits._ @@ -349,4 +351,24 @@ class ColumnExpressionSuite extends QueryTest { assert(schema("value").metadata === Metadata.empty) assert(schema("abc").metadata === metadata) } + + test("rand") { + val randCol = testData.select('key, rand(5L).as("rand")) + randCol.columns.length should be (2) + val rows = randCol.collect() + rows.foreach { row => + assert(row.getDouble(1) <= 1.0) + assert(row.getDouble(1) >= 0.0) + } + } + + test("randn") { + val randCol = testData.select('key, randn(5L).as("rand")) + randCol.columns.length should be (2) + val rows = randCol.collect() + rows.foreach { row => + assert(row.getDouble(1) <= 4.0) + assert(row.getDouble(1) >= -4.0) + } + } } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala new file mode 100644 index 0000000000000..ca03713ef4658 --- /dev/null +++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala @@ -0,0 +1,84 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql + +import org.apache.spark.sql.functions._ +import org.apache.spark.sql.test.TestSQLContext.implicits._ +import org.apache.spark.sql.types._ + +/** + * Test suite for functions in [[org.apache.spark.sql.functions]]. + */ +class DataFrameFunctionsSuite extends QueryTest { + + test("array with column name") { + val df = Seq((0, 1)).toDF("a", "b") + val row = df.select(array("a", "b")).first() + + val expectedType = ArrayType(IntegerType, containsNull = false) + assert(row.schema(0).dataType === expectedType) + assert(row.getAs[Seq[Int]](0) === Seq(0, 1)) + } + + test("array with column expression") { + val df = Seq((0, 1)).toDF("a", "b") + val row = df.select(array(col("a"), col("b") + col("b"))).first() + + val expectedType = ArrayType(IntegerType, containsNull = false) + assert(row.schema(0).dataType === expectedType) + assert(row.getAs[Seq[Int]](0) === Seq(0, 2)) + } + + // Turn this on once we add a rule to the analyzer to throw a friendly exception + ignore("array: throw exception if putting columns of different types into an array") { + val df = Seq((0, "str")).toDF("a", "b") + intercept[AnalysisException] { + df.select(array("a", "b")) + } + } + + test("struct with column name") { + val df = Seq((1, "str")).toDF("a", "b") + val row = df.select(struct("a", "b")).first() + + val expectedType = StructType(Seq( + StructField("a", IntegerType, nullable = false), + StructField("b", StringType) + )) + assert(row.schema(0).dataType === expectedType) + assert(row.getAs[Row](0) === Row(1, "str")) + } + + test("struct with column expression") { + val df = Seq((1, "str")).toDF("a", "b") + val row = df.select(struct((col("a") * 2).as("c"), col("b"))).first() + + val expectedType = StructType(Seq( + StructField("c", IntegerType, nullable = false), + StructField("b", StringType) + )) + assert(row.schema(0).dataType === expectedType) + assert(row.getAs[Row](0) === Row(2, "str")) + } + + test("struct: must use named column expression") { + intercept[IllegalArgumentException] { + struct(col("a") * 2) + } + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala new file mode 100644 index 0000000000000..4f5a2ff696789 --- /dev/null +++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala @@ -0,0 +1,61 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.sql + +import org.scalatest.FunSuite +import org.scalatest.Matchers._ + +import org.apache.spark.sql.test.TestSQLContext +import org.apache.spark.sql.test.TestSQLContext.implicits._ + +class DataFrameStatSuite extends FunSuite { + + import TestData._ + val sqlCtx = TestSQLContext + def toLetter(i: Int): String = (i + 97).toChar.toString + + test("Frequent Items") { + val rows = Array.tabulate(1000) { i => + if (i % 3 == 0) (1, toLetter(1), -1.0) else (i, toLetter(i), i * -1.0) + } + val df = sqlCtx.sparkContext.parallelize(rows).toDF("numbers", "letters", "negDoubles") + + val results = df.stat.freqItems(Array("numbers", "letters"), 0.1) + val items = results.collect().head + items.getSeq[Int](0) should contain (1) + items.getSeq[String](1) should contain (toLetter(1)) + + val singleColResults = df.stat.freqItems(Array("negDoubles"), 0.1) + val items2 = singleColResults.collect().head + items2.getSeq[Double](0) should contain (-1.0) + + } + + test("covariance") { + val rows = Array.tabulate(10)(i => (i, 2.0 * i, toLetter(i))) + val df = sqlCtx.sparkContext.parallelize(rows).toDF("singles", "doubles", "letters") + + val results = df.stat.cov("singles", "doubles") + assert(math.abs(results - 55.0 / 3) < 1e-6) + intercept[IllegalArgumentException] { + df.stat.cov("singles", "letters") // doesn't accept non-numerical dataTypes + } + val decimalRes = decimalData.stat.cov("a", "b") + assert(math.abs(decimalRes) < 1e-6) + } +} diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala index 5ec06d448e50f..e286fef23caa4 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala @@ -499,6 +499,22 @@ class DataFrameSuite extends QueryTest { Row(2) :: Row(3) :: Row(4) :: Nil) } + test("drop column using drop") { + val df = testData.drop("key") + checkAnswer( + df, + testData.collect().map(x => Row(x.getString(1))).toSeq) + assert(df.schema.map(_.name) === Seq("value")) + } + + test("drop unknown column (no-op)") { + val df = testData.drop("random") + checkAnswer( + df, + testData.collect().toSeq) + assert(df.schema.map(_.name) === Seq("key","value")) + } + test("withColumnRenamed") { val df = testData.toDF().withColumn("newCol", col("key") + 1) .withColumnRenamed("value", "valueRenamed") @@ -510,6 +526,23 @@ class DataFrameSuite extends QueryTest { assert(df.schema.map(_.name).toSeq === Seq("key", "valueRenamed", "newCol")) } + test("randomSplit") { + val n = 600 + val data = TestSQLContext.sparkContext.parallelize(1 to n, 2).toDF("id") + for (seed <- 1 to 5) { + val splits = data.randomSplit(Array[Double](1, 2, 3), seed) + assert(splits.length == 3, "wrong number of splits") + + assert(splits.reduce((a, b) => a.unionAll(b)).sort("id").collect().toList == + data.collect().toList, "incomplete or wrong split") + + val s = splits.map(_.count()) + assert(math.abs(s(0) - 100) < 50) // std = 9.13 + assert(math.abs(s(1) - 200) < 50) // std = 11.55 + assert(math.abs(s(2) - 300) < 50) // std = 12.25 + } + } + test("describe") { val describeTestData = Seq( ("Bob", 16, 176), diff --git a/sql/core/src/test/scala/org/apache/spark/sql/MathExpressionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/MathExpressionsSuite.scala index 561553cc925cb..9e19bb7482e9b 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/MathExpressionsSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/MathExpressionsSuite.scala @@ -194,18 +194,6 @@ class MathExpressionsSuite extends QueryTest { testOneToOneMathFunction[Double](signum, math.signum) } - test("isignum") { - testOneToOneMathFunction[Int](isignum, math.signum) - } - - test("fsignum") { - testOneToOneMathFunction[Float](fsignum, math.signum) - } - - test("lsignum") { - testOneToOneMathFunction[Long](lsignum, math.signum) - } - test("pow") { testTwoToOneMathFunction(pow, pow, math.pow) } diff --git a/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala b/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala index 59f9508444f25..bbf9ab113ca43 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala @@ -132,11 +132,7 @@ object QueryTest { val errorMessage = s""" |Results do not match for query: - |${df.logicalPlan} - |== Analyzed Plan == - |${df.queryExecution.analyzed} - |== Physical Plan == - |${df.queryExecution.executedPlan} + |${df.queryExecution} |== Results == |${sideBySide( s"== Correct Answer - ${expectedAnswer.size} ==" +: diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index 9e02e69fda3f2..0ab8558c1db13 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala @@ -19,13 +19,18 @@ package org.apache.spark.sql import org.scalatest.BeforeAndAfterAll +import org.apache.spark.sql.catalyst.errors.DialectException import org.apache.spark.sql.execution.GeneratedAggregate import org.apache.spark.sql.functions._ import org.apache.spark.sql.TestData._ import org.apache.spark.sql.test.TestSQLContext import org.apache.spark.sql.test.TestSQLContext.{udf => _, _} + import org.apache.spark.sql.types._ +/** A SQL Dialect for testing purpose, and it can not be nested type */ +class MyDialect extends DefaultDialect + class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { // Make sure the tables are loaded. TestData @@ -46,6 +51,16 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { Row("1", 1) :: Row("2", 1) :: Row("3", 1) :: Nil) } + test("support table.star") { + checkAnswer( + sql( + """ + |SELECT r.* + |FROM testData l join testData2 r on (l.key = r.a) + """.stripMargin), + Row(1, 1) :: Row(1, 2) :: Row(2, 1) :: Row(2, 2) :: Row(3, 1) :: Row(3, 2) :: Nil) + } + test("self join with alias in agg") { Seq(1,2,3) .map(i => (i, i.toString)) @@ -64,6 +79,23 @@ class SQLQuerySuite extends QueryTest with BeforeAndAfterAll { Row("1", 1) :: Row("2", 1) :: Row("3", 1) :: Nil) } + test("SQL Dialect Switching to a new SQL parser") { + val newContext = new SQLContext(TestSQLContext.sparkContext) + newContext.setConf("spark.sql.dialect", classOf[MyDialect].getCanonicalName()) + assert(newContext.getSQLDialect().getClass === classOf[MyDialect]) + assert(newContext.sql("SELECT 1").collect() === Array(Row(1))) + } + + test("SQL Dialect Switch to an invalid parser with alias") { + val newContext = new SQLContext(TestSQLContext.sparkContext) + newContext.sql("SET spark.sql.dialect=MyTestClass") + intercept[DialectException] { + newContext.sql("SELECT 1") + } + // test if the dialect set back to DefaultSQLDialect + assert(newContext.getSQLDialect().getClass === classOf[DefaultDialect]) + } + test("SPARK-4625 support SORT BY in SimpleSQLParser & DSL") { checkAnswer( sql("SELECT a FROM testData2 SORT BY a"), diff --git a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala index db096af4535a9..b165ab2b1deb3 100644 --- a/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala +++ b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala @@ -22,6 +22,7 @@ import java.sql.DriverManager import java.util.{Calendar, GregorianCalendar, Properties} import org.apache.spark.sql.test._ +import org.apache.spark.sql.types._ import org.h2.jdbc.JdbcSQLException import org.scalatest.{FunSuite, BeforeAndAfter} import TestSQLContext._ @@ -256,12 +257,22 @@ class JDBCSuite extends FunSuite with BeforeAndAfter { assert(cachedRows(0).getAs[java.sql.Date](1) === java.sql.Date.valueOf("1996-01-01")) } + test("test DATE types in cache") { + val rows = TestSQLContext.jdbc(urlWithUserAndPass, "TEST.TIMETYPES").collect() + TestSQLContext + .jdbc(urlWithUserAndPass, "TEST.TIMETYPES").cache().registerTempTable("mycached_date") + val cachedRows = sql("select * from mycached_date").collect() + assert(rows(0).getAs[java.sql.Date](1) === java.sql.Date.valueOf("1996-01-01")) + assert(cachedRows(0).getAs[java.sql.Date](1) === java.sql.Date.valueOf("1996-01-01")) + } + test("H2 floating-point types") { val rows = sql("SELECT * FROM flttypes").collect() assert(rows(0).getDouble(0) === 1.00000000000000022) // Yes, I meant ==. assert(rows(0).getDouble(1) === 1.00000011920928955) // Yes, I meant ==. assert(rows(0).getAs[BigDecimal](2) .equals(new BigDecimal("123456789012345.54321543215432100000"))) + assert(rows(0).schema.fields(2).dataType === DecimalType(40, 20)) } test("SQL query as table name") { diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala index dd06b2620c5ee..1d8d0b5c322ad 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveContext.scala @@ -20,6 +20,9 @@ package org.apache.spark.sql.hive import java.io.{BufferedReader, InputStreamReader, PrintStream} import java.sql.Timestamp +import org.apache.hadoop.hive.ql.parse.VariableSubstitution +import org.apache.spark.sql.catalyst.Dialect + import scala.collection.JavaConversions._ import scala.language.implicitConversions @@ -42,6 +45,15 @@ import org.apache.spark.sql.hive.execution.{DescribeHiveTableCommand, HiveNative import org.apache.spark.sql.sources.{DDLParser, DataSourceStrategy} import org.apache.spark.sql.types._ +/** + * This is the HiveQL Dialect, this dialect is strongly bind with HiveContext + */ +private[hive] class HiveQLDialect extends Dialect { + override def parse(sqlText: String): LogicalPlan = { + HiveQl.parseSql(sqlText) + } +} + /** * An instance of the Spark SQL execution engine that integrates with data stored in Hive. * Configuration for Hive is read from hive-site.xml on the classpath. @@ -81,25 +93,16 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { protected[sql] def convertCTAS: Boolean = getConf("spark.sql.hive.convertCTAS", "false").toBoolean - override protected[sql] def executePlan(plan: LogicalPlan): this.QueryExecution = - new this.QueryExecution(plan) - @transient - protected[sql] val ddlParserWithHiveQL = new DDLParser(HiveQl.parseSql(_)) - - override def sql(sqlText: String): DataFrame = { - val substituted = new VariableSubstitution().substitute(hiveconf, sqlText) - // TODO: Create a framework for registering parsers instead of just hardcoding if statements. - if (conf.dialect == "sql") { - super.sql(substituted) - } else if (conf.dialect == "hiveql") { - val ddlPlan = ddlParserWithHiveQL.parse(sqlText, exceptionOnError = false) - DataFrame(this, ddlPlan.getOrElse(HiveQl.parseSql(substituted))) - } else { - sys.error(s"Unsupported SQL dialect: ${conf.dialect}. Try 'sql' or 'hiveql'") - } + protected[sql] lazy val substitutor = new VariableSubstitution() + + protected[sql] override def parseSql(sql: String): LogicalPlan = { + super.parseSql(substitutor.substitute(hiveconf, sql)) } + override protected[sql] def executePlan(plan: LogicalPlan): this.QueryExecution = + new this.QueryExecution(plan) + /** * Invalidate and refresh all the cached the metadata of the given table. For performance reasons, * Spark SQL or the external data source library it uses might cache certain metadata about a @@ -356,6 +359,12 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { } } + override protected[sql] def dialectClassName = if (conf.dialect == "hiveql") { + classOf[HiveQLDialect].getCanonicalName + } else { + super.dialectClassName + } + @transient private val hivePlanner = new SparkPlanner with HiveStrategies { val hiveContext = self diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala index 0ea6d57b816c6..63a8c05f775b8 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala @@ -19,13 +19,11 @@ package org.apache.spark.sql.hive import java.sql.Date - -import org.apache.hadoop.hive.ql.exec.{FunctionRegistry, FunctionInfo} - import scala.collection.mutable.ArrayBuffer import org.apache.hadoop.hive.conf.HiveConf import org.apache.hadoop.hive.ql.Context +import org.apache.hadoop.hive.ql.exec.{FunctionRegistry, FunctionInfo} import org.apache.hadoop.hive.ql.lib.Node import org.apache.hadoop.hive.ql.metadata.Table import org.apache.hadoop.hive.ql.parse._ @@ -783,13 +781,13 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C case (None, Some(perPartitionOrdering), None, None) => Sort(perPartitionOrdering.getChildren.map(nodeToSortOrder), false, withHaving) case (None, None, Some(partitionExprs), None) => - Repartition(partitionExprs.getChildren.map(nodeToExpr), withHaving) + RepartitionByExpression(partitionExprs.getChildren.map(nodeToExpr), withHaving) case (None, Some(perPartitionOrdering), Some(partitionExprs), None) => Sort(perPartitionOrdering.getChildren.map(nodeToSortOrder), false, - Repartition(partitionExprs.getChildren.map(nodeToExpr), withHaving)) + RepartitionByExpression(partitionExprs.getChildren.map(nodeToExpr), withHaving)) case (None, None, None, Some(clusterExprs)) => Sort(clusterExprs.getChildren.map(nodeToExpr).map(SortOrder(_, Ascending)), false, - Repartition(clusterExprs.getChildren.map(nodeToExpr), withHaving)) + RepartitionByExpression(clusterExprs.getChildren.map(nodeToExpr), withHaving)) case (None, None, None, None) => withHaving case _ => sys.error("Unsupported set of ordering / distribution clauses.") } @@ -887,13 +885,13 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C fraction.toDouble >= (0.0 - RandomSampler.roundingEpsilon) && fraction.toDouble <= (100.0 + RandomSampler.roundingEpsilon), s"Sampling fraction ($fraction) must be on interval [0, 100]") - Sample(fraction.toDouble / 100, withReplacement = false, (math.random * 1000).toInt, + Sample(0.0, fraction.toDouble / 100, withReplacement = false, (math.random * 1000).toInt, relation) case Token("TOK_TABLEBUCKETSAMPLE", Token(numerator, Nil) :: Token(denominator, Nil) :: Nil) => val fraction = numerator.toDouble / denominator.toDouble - Sample(fraction, withReplacement = false, (math.random * 1000).toInt, relation) + Sample(0.0, fraction, withReplacement = false, (math.random * 1000).toInt, relation) case a: ASTNode => throw new NotImplementedError( s"""No parse rules for sampling clause: ${a.getType}, text: ${a.getText} : @@ -1244,7 +1242,8 @@ https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C /* Other functions */ case Token("TOK_FUNCTION", Token(ARRAY(), Nil) :: children) => CreateArray(children.map(nodeToExpr)) - case Token("TOK_FUNCTION", Token(RAND(), Nil) :: Nil) => Rand + case Token("TOK_FUNCTION", Token(RAND(), Nil) :: Nil) => Rand() + case Token("TOK_FUNCTION", Token(RAND(), Nil) :: seed :: Nil) => Rand(seed.toString.toLong) case Token("TOK_FUNCTION", Token(SUBSTR(), Nil) :: string :: pos :: Nil) => Substring(nodeToExpr(string), nodeToExpr(pos), Literal.create(Integer.MAX_VALUE, IntegerType)) case Token("TOK_FUNCTION", Token(SUBSTR(), Nil) :: string :: pos :: length :: Nil) => diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala index 9f17bca083d13..edeab5158df62 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala @@ -107,7 +107,10 @@ class TestHiveContext(sc: SparkContext) extends HiveContext(sc) { /** Fewer partitions to speed up testing. */ protected[sql] override lazy val conf: SQLConf = new SQLConf { override def numShufflePartitions: Int = getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt - override def dialect: String = getConf(SQLConf.DIALECT, "hiveql") + + // TODO as in unit test, conf.clear() probably be called, all of the value will be cleared. + // The super.getConf(SQLConf.DIALECT) is "sql" by default, we need to set it as "hiveql" + override def dialect: String = super.getConf(SQLConf.DIALECT, "hiveql") } } diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala index a787fa5546e76..4990092df6a99 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/QueryPartitionSuite.scala @@ -28,7 +28,7 @@ import org.apache.spark.util.Utils class QueryPartitionSuite extends QueryTest { import org.apache.spark.sql.hive.test.TestHive.implicits._ - test("SPARK-5068: query data when path doesn't exists"){ + test("SPARK-5068: query data when path doesn't exist"){ val testData = TestHive.sparkContext.parallelize( (1 to 10).map(i => TestData(i, i.toString))).toDF() testData.registerTempTable("testData") @@ -52,8 +52,9 @@ class QueryPartitionSuite extends QueryTest { ++ testData.toSchemaRDD.collect ++ testData.toSchemaRDD.collect) // delete the path of one partition - val folders = tmpDir.listFiles.filter(_.isDirectory) - Utils.deleteRecursively(folders(0)) + tmpDir.listFiles + .find { f => f.isDirectory && f.getName().startsWith("ds=") } + .foreach { f => Utils.deleteRecursively(f) } // test for after delete the path checkAnswer(sql("select key,value from table_with_partition"), diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala index 4f8d0ac0e7656..630dec8fa05a0 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala @@ -18,14 +18,17 @@ package org.apache.spark.sql.hive.execution import org.apache.spark.sql.catalyst.analysis.EliminateSubQueries -import org.apache.spark.sql.hive.{MetastoreRelation, HiveShim} +import org.apache.spark.sql.catalyst.errors.DialectException +import org.apache.spark.sql.DefaultDialect +import org.apache.spark.sql.{AnalysisException, QueryTest, Row, SQLConf} +import org.apache.spark.sql.hive.MetastoreRelation import org.apache.spark.sql.hive.test.TestHive import org.apache.spark.sql.hive.test.TestHive._ import org.apache.spark.sql.hive.test.TestHive.implicits._ +import org.apache.spark.sql.hive.{HiveQLDialect, HiveShim} import org.apache.spark.sql.parquet.ParquetRelation2 import org.apache.spark.sql.sources.LogicalRelation import org.apache.spark.sql.types._ -import org.apache.spark.sql.{AnalysisException, QueryTest, Row, SQLConf} case class Nested1(f1: Nested2) case class Nested2(f2: Nested3) @@ -45,6 +48,9 @@ case class Order( state: String, month: Int) +/** A SQL Dialect for testing purpose, and it can not be nested type */ +class MyDialect extends DefaultDialect + /** * A collection of hive query tests where we generate the answers ourselves instead of depending on * Hive to generate them (in contrast to HiveQuerySuite). Often this is because the query is @@ -229,6 +235,35 @@ class SQLQuerySuite extends QueryTest { setConf("spark.sql.hive.convertCTAS", originalConf) } + test("SQL Dialect Switching") { + assert(getSQLDialect().getClass === classOf[HiveQLDialect]) + setConf("spark.sql.dialect", classOf[MyDialect].getCanonicalName()) + assert(getSQLDialect().getClass === classOf[MyDialect]) + assert(sql("SELECT 1").collect() === Array(Row(1))) + + // set the dialect back to the DefaultSQLDialect + sql("SET spark.sql.dialect=sql") + assert(getSQLDialect().getClass === classOf[DefaultDialect]) + sql("SET spark.sql.dialect=hiveql") + assert(getSQLDialect().getClass === classOf[HiveQLDialect]) + + // set invalid dialect + sql("SET spark.sql.dialect.abc=MyTestClass") + sql("SET spark.sql.dialect=abc") + intercept[Exception] { + sql("SELECT 1") + } + // test if the dialect set back to HiveQLDialect + getSQLDialect().getClass === classOf[HiveQLDialect] + + sql("SET spark.sql.dialect=MyTestClass") + intercept[DialectException] { + sql("SELECT 1") + } + // test if the dialect set back to HiveQLDialect + assert(getSQLDialect().getClass === classOf[HiveQLDialect]) + } + test("CTAS with serde") { sql("CREATE TABLE ctas1 AS SELECT key k, value FROM src ORDER BY k, value").collect() sql( diff --git a/streaming/src/main/java/org/apache/spark/streaming/util/WriteAheadLog.java b/streaming/src/main/java/org/apache/spark/streaming/util/WriteAheadLog.java new file mode 100644 index 0000000000000..8c0fdfa9c7478 --- /dev/null +++ b/streaming/src/main/java/org/apache/spark/streaming/util/WriteAheadLog.java @@ -0,0 +1,60 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streaming.util; + +import java.nio.ByteBuffer; +import java.util.Iterator; + +/** + * This abstract class represents a write ahead log (aka journal) that is used by Spark Streaming + * to save the received data (by receivers) and associated metadata to a reliable storage, so that + * they can be recovered after driver failures. See the Spark documentation for more information + * on how to plug in your own custom implementation of a write ahead log. + */ +@org.apache.spark.annotation.DeveloperApi +public abstract class WriteAheadLog { + /** + * Write the record to the log and return a record handle, which contains all the information + * necessary to read back the written record. The time is used to the index the record, + * such that it can be cleaned later. Note that implementations of this abstract class must + * ensure that the written data is durable and readable (using the record handle) by the + * time this function returns. + */ + abstract public WriteAheadLogRecordHandle write(ByteBuffer record, long time); + + /** + * Read a written record based on the given record handle. + */ + abstract public ByteBuffer read(WriteAheadLogRecordHandle handle); + + /** + * Read and return an iterator of all the records that have been written but not yet cleaned up. + */ + abstract public Iterator readAll(); + + /** + * Clean all the records that are older than the threshold time. It can wait for + * the completion of the deletion. + */ + abstract public void clean(long threshTime, boolean waitForCompletion); + + /** + * Close this log and release any resources. + */ + abstract public void close(); +} diff --git a/streaming/src/main/java/org/apache/spark/streaming/util/WriteAheadLogRecordHandle.java b/streaming/src/main/java/org/apache/spark/streaming/util/WriteAheadLogRecordHandle.java new file mode 100644 index 0000000000000..02324189b7822 --- /dev/null +++ b/streaming/src/main/java/org/apache/spark/streaming/util/WriteAheadLogRecordHandle.java @@ -0,0 +1,30 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streaming.util; + +/** + * This abstract class represents a handle that refers to a record written in a + * {@link org.apache.spark.streaming.util.WriteAheadLog WriteAheadLog}. + * It must contain all the information necessary for the record to be read and returned by + * an implemenation of the WriteAheadLog class. + * + * @see org.apache.spark.streaming.util.WriteAheadLog + */ +@org.apache.spark.annotation.DeveloperApi +public abstract class WriteAheadLogRecordHandle implements java.io.Serializable { +} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala b/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala index 0a50485118588..7bfae253c3a0c 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/Checkpoint.scala @@ -77,7 +77,8 @@ object Checkpoint extends Logging { } /** Get checkpoint files present in the give directory, ordered by oldest-first */ - def getCheckpointFiles(checkpointDir: String, fs: FileSystem): Seq[Path] = { + def getCheckpointFiles(checkpointDir: String, fsOption: Option[FileSystem] = None): Seq[Path] = { + def sortFunc(path1: Path, path2: Path): Boolean = { val (time1, bk1) = path1.getName match { case REGEX(x, y) => (x.toLong, !y.isEmpty) } val (time2, bk2) = path2.getName match { case REGEX(x, y) => (x.toLong, !y.isEmpty) } @@ -85,6 +86,7 @@ object Checkpoint extends Logging { } val path = new Path(checkpointDir) + val fs = fsOption.getOrElse(path.getFileSystem(new Configuration())) if (fs.exists(path)) { val statuses = fs.listStatus(path) if (statuses != null) { @@ -160,7 +162,7 @@ class CheckpointWriter( } // Delete old checkpoint files - val allCheckpointFiles = Checkpoint.getCheckpointFiles(checkpointDir, fs) + val allCheckpointFiles = Checkpoint.getCheckpointFiles(checkpointDir, Some(fs)) if (allCheckpointFiles.size > 10) { allCheckpointFiles.take(allCheckpointFiles.size - 10).foreach(file => { logInfo("Deleting " + file) @@ -234,15 +236,24 @@ class CheckpointWriter( private[streaming] object CheckpointReader extends Logging { - def read(checkpointDir: String, conf: SparkConf, hadoopConf: Configuration): Option[Checkpoint] = - { + /** + * Read checkpoint files present in the given checkpoint directory. If there are no checkpoint + * files, then return None, else try to return the latest valid checkpoint object. If no + * checkpoint files could be read correctly, then return None (if ignoreReadError = true), + * or throw exception (if ignoreReadError = false). + */ + def read( + checkpointDir: String, + conf: SparkConf, + hadoopConf: Configuration, + ignoreReadError: Boolean = false): Option[Checkpoint] = { val checkpointPath = new Path(checkpointDir) // TODO(rxin): Why is this a def?! def fs: FileSystem = checkpointPath.getFileSystem(hadoopConf) // Try to find the checkpoint files - val checkpointFiles = Checkpoint.getCheckpointFiles(checkpointDir, fs).reverse + val checkpointFiles = Checkpoint.getCheckpointFiles(checkpointDir, Some(fs)).reverse if (checkpointFiles.isEmpty) { return None } @@ -282,7 +293,10 @@ object CheckpointReader extends Logging { }) // If none of checkpoint files could be read, then throw exception - throw new SparkException("Failed to read checkpoint from directory " + checkpointPath) + if (!ignoreReadError) { + throw new SparkException(s"Failed to read checkpoint from directory $checkpointPath") + } + None } } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala index f57f295874645..117cb59fb61c9 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala @@ -107,6 +107,19 @@ class StreamingContext private[streaming] ( */ def this(path: String) = this(path, new Configuration) + /** + * Recreate a StreamingContext from a checkpoint file using an existing SparkContext. + * @param path Path to the directory that was specified as the checkpoint directory + * @param sparkContext Existing SparkContext + */ + def this(path: String, sparkContext: SparkContext) = { + this( + sparkContext, + CheckpointReader.read(path, sparkContext.conf, sparkContext.hadoopConfiguration).get, + null) + } + + if (sc_ == null && cp_ == null) { throw new Exception("Spark Streaming cannot be initialized with " + "both SparkContext and checkpoint as null") @@ -115,10 +128,12 @@ class StreamingContext private[streaming] ( private[streaming] val isCheckpointPresent = (cp_ != null) private[streaming] val sc: SparkContext = { - if (isCheckpointPresent) { + if (sc_ != null) { + sc_ + } else if (isCheckpointPresent) { new SparkContext(cp_.createSparkConf()) } else { - sc_ + throw new SparkException("Cannot create StreamingContext without a SparkContext") } } @@ -129,7 +144,7 @@ class StreamingContext private[streaming] ( private[streaming] val conf = sc.conf - private[streaming] val env = SparkEnv.get + private[streaming] val env = sc.env private[streaming] val graph: DStreamGraph = { if (isCheckpointPresent) { @@ -144,7 +159,7 @@ class StreamingContext private[streaming] ( } } - private val nextReceiverInputStreamId = new AtomicInteger(0) + private val nextInputStreamId = new AtomicInteger(0) private[streaming] var checkpointDir: String = { if (isCheckpointPresent) { @@ -174,7 +189,9 @@ class StreamingContext private[streaming] ( /** Register streaming source to metrics system */ private val streamingSource = new StreamingSource(this) - SparkEnv.get.metricsSystem.registerSource(streamingSource) + assert(env != null) + assert(env.metricsSystem != null) + env.metricsSystem.registerSource(streamingSource) /** Enumeration to identify current state of the StreamingContext */ private[streaming] object StreamingContextState extends Enumeration { @@ -224,7 +241,7 @@ class StreamingContext private[streaming] ( if (isCheckpointPresent) cp_ else null } - private[streaming] def getNewReceiverStreamId() = nextReceiverInputStreamId.getAndIncrement() + private[streaming] def getNewInputStreamId() = nextInputStreamId.getAndIncrement() /** * Create an input stream with any arbitrary user implemented receiver. @@ -621,19 +638,59 @@ object StreamingContext extends Logging { hadoopConf: Configuration = new Configuration(), createOnError: Boolean = false ): StreamingContext = { - val checkpointOption = try { - CheckpointReader.read(checkpointPath, new SparkConf(), hadoopConf) - } catch { - case e: Exception => - if (createOnError) { - None - } else { - throw e - } - } + val checkpointOption = CheckpointReader.read( + checkpointPath, new SparkConf(), hadoopConf, createOnError) checkpointOption.map(new StreamingContext(null, _, null)).getOrElse(creatingFunc()) } + + /** + * Either recreate a StreamingContext from checkpoint data or create a new StreamingContext. + * If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be + * recreated from the checkpoint data. If the data does not exist, then the StreamingContext + * will be created by called the provided `creatingFunc` on the provided `sparkContext`. Note + * that the SparkConf configuration in the checkpoint data will not be restored as the + * SparkContext has already been created. + * + * @param checkpointPath Checkpoint directory used in an earlier StreamingContext program + * @param creatingFunc Function to create a new StreamingContext using the given SparkContext + * @param sparkContext SparkContext using which the StreamingContext will be created + */ + def getOrCreate( + checkpointPath: String, + creatingFunc: SparkContext => StreamingContext, + sparkContext: SparkContext + ): StreamingContext = { + getOrCreate(checkpointPath, creatingFunc, sparkContext, createOnError = false) + } + + /** + * Either recreate a StreamingContext from checkpoint data or create a new StreamingContext. + * If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be + * recreated from the checkpoint data. If the data does not exist, then the StreamingContext + * will be created by called the provided `creatingFunc` on the provided `sparkContext`. Note + * that the SparkConf configuration in the checkpoint data will not be restored as the + * SparkContext has already been created. + * + * @param checkpointPath Checkpoint directory used in an earlier StreamingContext program + * @param creatingFunc Function to create a new StreamingContext using the given SparkContext + * @param sparkContext SparkContext using which the StreamingContext will be created + * @param createOnError Whether to create a new StreamingContext if there is an + * error in reading checkpoint data. By default, an exception will be + * thrown on error. + */ + def getOrCreate( + checkpointPath: String, + creatingFunc: SparkContext => StreamingContext, + sparkContext: SparkContext, + createOnError: Boolean + ): StreamingContext = { + val checkpointOption = CheckpointReader.read( + checkpointPath, sparkContext.conf, sparkContext.hadoopConfiguration, createOnError) + checkpointOption.map(new StreamingContext(sparkContext, _, null)) + .getOrElse(creatingFunc(sparkContext)) + } + /** * Find the JAR from which a given class was loaded, to make it easy for users to pass * their JARs to StreamingContext. diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala index 4095a7cc84946..572d7d8e8753d 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala @@ -32,13 +32,14 @@ import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.annotation.Experimental import org.apache.spark.api.java.{JavaPairRDD, JavaRDD, JavaSparkContext} import org.apache.spark.api.java.function.{Function => JFunction, Function2 => JFunction2} +import org.apache.spark.api.java.function.{Function0 => JFunction0} import org.apache.spark.rdd.RDD import org.apache.spark.storage.StorageLevel import org.apache.spark.streaming._ import org.apache.spark.streaming.scheduler.StreamingListener -import org.apache.hadoop.conf.Configuration -import org.apache.spark.streaming.dstream.{PluggableInputDStream, ReceiverInputDStream, DStream} +import org.apache.spark.streaming.dstream.DStream import org.apache.spark.streaming.receiver.Receiver +import org.apache.hadoop.conf.Configuration /** * A Java-friendly version of [[org.apache.spark.streaming.StreamingContext]] which is the main @@ -655,6 +656,7 @@ object JavaStreamingContext { * @param checkpointPath Checkpoint directory used in an earlier JavaStreamingContext program * @param factory JavaStreamingContextFactory object to create a new JavaStreamingContext */ + @deprecated("use getOrCreate without JavaStreamingContextFactor", "1.4.0") def getOrCreate( checkpointPath: String, factory: JavaStreamingContextFactory @@ -676,6 +678,7 @@ object JavaStreamingContext { * @param hadoopConf Hadoop configuration if necessary for reading from any HDFS compatible * file system */ + @deprecated("use getOrCreate without JavaStreamingContextFactory", "1.4.0") def getOrCreate( checkpointPath: String, hadoopConf: Configuration, @@ -700,6 +703,7 @@ object JavaStreamingContext { * @param createOnError Whether to create a new JavaStreamingContext if there is an * error in reading checkpoint data. */ + @deprecated("use getOrCreate without JavaStreamingContextFactory", "1.4.0") def getOrCreate( checkpointPath: String, hadoopConf: Configuration, @@ -712,6 +716,117 @@ object JavaStreamingContext { new JavaStreamingContext(ssc) } + /** + * Either recreate a StreamingContext from checkpoint data or create a new StreamingContext. + * If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be + * recreated from the checkpoint data. If the data does not exist, then the provided factory + * will be used to create a JavaStreamingContext. + * + * @param checkpointPath Checkpoint directory used in an earlier JavaStreamingContext program + * @param creatingFunc Function to create a new JavaStreamingContext + */ + def getOrCreate( + checkpointPath: String, + creatingFunc: JFunction0[JavaStreamingContext] + ): JavaStreamingContext = { + val ssc = StreamingContext.getOrCreate(checkpointPath, () => { + creatingFunc.call().ssc + }) + new JavaStreamingContext(ssc) + } + + /** + * Either recreate a StreamingContext from checkpoint data or create a new StreamingContext. + * If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be + * recreated from the checkpoint data. If the data does not exist, then the provided factory + * will be used to create a JavaStreamingContext. + * + * @param checkpointPath Checkpoint directory used in an earlier StreamingContext program + * @param creatingFunc Function to create a new JavaStreamingContext + * @param hadoopConf Hadoop configuration if necessary for reading from any HDFS compatible + * file system + */ + def getOrCreate( + checkpointPath: String, + creatingFunc: JFunction0[JavaStreamingContext], + hadoopConf: Configuration + ): JavaStreamingContext = { + val ssc = StreamingContext.getOrCreate(checkpointPath, () => { + creatingFunc.call().ssc + }, hadoopConf) + new JavaStreamingContext(ssc) + } + + /** + * Either recreate a StreamingContext from checkpoint data or create a new StreamingContext. + * If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be + * recreated from the checkpoint data. If the data does not exist, then the provided factory + * will be used to create a JavaStreamingContext. + * + * @param checkpointPath Checkpoint directory used in an earlier StreamingContext program + * @param creatingFunc Function to create a new JavaStreamingContext + * @param hadoopConf Hadoop configuration if necessary for reading from any HDFS compatible + * file system + * @param createOnError Whether to create a new JavaStreamingContext if there is an + * error in reading checkpoint data. + */ + def getOrCreate( + checkpointPath: String, + creatingFunc: JFunction0[JavaStreamingContext], + hadoopConf: Configuration, + createOnError: Boolean + ): JavaStreamingContext = { + val ssc = StreamingContext.getOrCreate(checkpointPath, () => { + creatingFunc.call().ssc + }, hadoopConf, createOnError) + new JavaStreamingContext(ssc) + } + + /** + * Either recreate a StreamingContext from checkpoint data or create a new StreamingContext. + * If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be + * recreated from the checkpoint data. If the data does not exist, then the provided factory + * will be used to create a JavaStreamingContext. + * + * @param checkpointPath Checkpoint directory used in an earlier StreamingContext program + * @param creatingFunc Function to create a new JavaStreamingContext + * @param sparkContext SparkContext using which the StreamingContext will be created + */ + def getOrCreate( + checkpointPath: String, + creatingFunc: JFunction[JavaSparkContext, JavaStreamingContext], + sparkContext: JavaSparkContext + ): JavaStreamingContext = { + val ssc = StreamingContext.getOrCreate(checkpointPath, (sparkContext: SparkContext) => { + creatingFunc.call(new JavaSparkContext(sparkContext)).ssc + }, sparkContext.sc) + new JavaStreamingContext(ssc) + } + + /** + * Either recreate a StreamingContext from checkpoint data or create a new StreamingContext. + * If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be + * recreated from the checkpoint data. If the data does not exist, then the provided factory + * will be used to create a JavaStreamingContext. + * + * @param checkpointPath Checkpoint directory used in an earlier StreamingContext program + * @param creatingFunc Function to create a new JavaStreamingContext + * @param sparkContext SparkContext using which the StreamingContext will be created + * @param createOnError Whether to create a new JavaStreamingContext if there is an + * error in reading checkpoint data. + */ + def getOrCreate( + checkpointPath: String, + creatingFunc: JFunction[JavaSparkContext, JavaStreamingContext], + sparkContext: JavaSparkContext, + createOnError: Boolean + ): JavaStreamingContext = { + val ssc = StreamingContext.getOrCreate(checkpointPath, (sparkContext: SparkContext) => { + creatingFunc.call(new JavaSparkContext(sparkContext)).ssc + }, sparkContext.sc, createOnError) + new JavaStreamingContext(ssc) + } + /** * Find the JAR from which a given class was loaded, to make it easy for users to pass * their JARs to StreamingContext. diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala index 24f99a2b929f5..83d41f5762444 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala @@ -626,7 +626,7 @@ abstract class DStream[T: ClassTag] ( println("Time: " + time) println("-------------------------------------------") firstNum.take(num).foreach(println) - if (firstNum.size > num) println("...") + if (firstNum.length > num) println("...") println() } } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/InputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/InputDStream.scala index e652702e213ef..e4ad4b509d8d8 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/InputDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/InputDStream.scala @@ -41,6 +41,9 @@ abstract class InputDStream[T: ClassTag] (@transient ssc_ : StreamingContext) ssc.graph.addInputStream(this) + /** This is an unique identifier for the input stream. */ + val id = ssc.getNewInputStreamId() + /** * Checks whether the 'time' is valid wrt slideDuration for generating RDD. * Additionally it also ensures valid times are in strictly increasing order. diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala index 8be04314c4285..ba88416ef4009 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/ReceiverInputDStream.scala @@ -24,7 +24,7 @@ import org.apache.spark.storage.{BlockId, StorageLevel} import org.apache.spark.streaming._ import org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD import org.apache.spark.streaming.receiver.{Receiver, WriteAheadLogBasedStoreResult} -import org.apache.spark.streaming.scheduler.ReceivedBlockInfo +import org.apache.spark.streaming.scheduler.{InputInfo, ReceivedBlockInfo} /** * Abstract class for defining any [[org.apache.spark.streaming.dstream.InputDStream]] @@ -39,9 +39,6 @@ import org.apache.spark.streaming.scheduler.ReceivedBlockInfo abstract class ReceiverInputDStream[T: ClassTag](@transient ssc_ : StreamingContext) extends InputDStream[T](ssc_) { - /** This is an unique identifier for the receiver input stream. */ - val id = ssc.getNewReceiverStreamId() - /** * Gets the receiver object that will be sent to the worker nodes * to receive data. This method needs to defined by any specific implementation @@ -72,6 +69,10 @@ abstract class ReceiverInputDStream[T: ClassTag](@transient ssc_ : StreamingCont val blockStoreResults = blockInfos.map { _.blockStoreResult } val blockIds = blockStoreResults.map { _.blockId.asInstanceOf[BlockId] }.toArray + // Register the input blocks information into InputInfoTracker + val inputInfo = InputInfo(id, blockInfos.map(_.numRecords).sum) + ssc.scheduler.inputInfoTracker.reportInfo(validTime, inputInfo) + // Check whether all the results are of the same type val resultTypes = blockStoreResults.map { _.getClass }.distinct if (resultTypes.size > 1) { @@ -82,7 +83,7 @@ abstract class ReceiverInputDStream[T: ClassTag](@transient ssc_ : StreamingCont // WriteAheadLogBackedBlockRDD else create simple BlockRDD. if (resultTypes.size == 1 && resultTypes.head == classOf[WriteAheadLogBasedStoreResult]) { val logSegments = blockStoreResults.map { - _.asInstanceOf[WriteAheadLogBasedStoreResult].segment + _.asInstanceOf[WriteAheadLogBasedStoreResult].walRecordHandle }.toArray // Since storeInBlockManager = false, the storage level does not matter. new WriteAheadLogBackedBlockRDD[T](ssc.sparkContext, diff --git a/streaming/src/main/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDD.scala b/streaming/src/main/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDD.scala index 93caa4ba35c7f..f4c8046e8a1a8 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDD.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDD.scala @@ -16,14 +16,17 @@ */ package org.apache.spark.streaming.rdd -import scala.reflect.ClassTag +import java.io.File +import java.nio.ByteBuffer +import java.util.UUID -import org.apache.hadoop.conf.Configuration +import scala.reflect.ClassTag +import scala.util.control.NonFatal import org.apache.spark._ import org.apache.spark.rdd.BlockRDD import org.apache.spark.storage.{BlockId, StorageLevel} -import org.apache.spark.streaming.util.{HdfsUtils, WriteAheadLogFileSegment, WriteAheadLogRandomReader} +import org.apache.spark.streaming.util._ /** * Partition class for [[org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD]]. @@ -31,26 +34,27 @@ import org.apache.spark.streaming.util.{HdfsUtils, WriteAheadLogFileSegment, Wri * the segment of the write ahead log that backs the partition. * @param index index of the partition * @param blockId id of the block having the partition data - * @param segment segment of the write ahead log having the partition data + * @param walRecordHandle Handle of the record in a write ahead log having the partition data */ private[streaming] class WriteAheadLogBackedBlockRDDPartition( val index: Int, val blockId: BlockId, - val segment: WriteAheadLogFileSegment) + val walRecordHandle: WriteAheadLogRecordHandle) extends Partition /** * This class represents a special case of the BlockRDD where the data blocks in - * the block manager are also backed by segments in write ahead logs. For reading + * the block manager are also backed by data in write ahead logs. For reading * the data, this RDD first looks up the blocks by their ids in the block manager. - * If it does not find them, it looks up the corresponding file segment. + * If it does not find them, it looks up the corresponding data in the write ahead log. * * @param sc SparkContext * @param blockIds Ids of the blocks that contains this RDD's data - * @param segments Segments in write ahead logs that contain this RDD's data - * @param storeInBlockManager Whether to store in the block manager after reading from the segment + * @param walRecordHandles Record handles in write ahead logs that contain this RDD's data + * @param storeInBlockManager Whether to store in the block manager after reading + * from the WAL record * @param storageLevel storage level to store when storing in block manager * (applicable when storeInBlockManager = true) */ @@ -58,15 +62,15 @@ private[streaming] class WriteAheadLogBackedBlockRDD[T: ClassTag]( @transient sc: SparkContext, @transient blockIds: Array[BlockId], - @transient segments: Array[WriteAheadLogFileSegment], + @transient walRecordHandles: Array[WriteAheadLogRecordHandle], storeInBlockManager: Boolean, storageLevel: StorageLevel) extends BlockRDD[T](sc, blockIds) { require( - blockIds.length == segments.length, + blockIds.length == walRecordHandles.length, s"Number of block ids (${blockIds.length}) must be " + - s"the same as number of segments (${segments.length}})!") + s"the same as number of WAL record handles (${walRecordHandles.length}})!") // Hadoop configuration is not serializable, so broadcast it as a serializable. @transient private val hadoopConfig = sc.hadoopConfiguration @@ -75,13 +79,13 @@ class WriteAheadLogBackedBlockRDD[T: ClassTag]( override def getPartitions: Array[Partition] = { assertValid() Array.tabulate(blockIds.size) { i => - new WriteAheadLogBackedBlockRDDPartition(i, blockIds(i), segments(i)) + new WriteAheadLogBackedBlockRDDPartition(i, blockIds(i), walRecordHandles(i)) } } /** * Gets the partition data by getting the corresponding block from the block manager. - * If the block does not exist, then the data is read from the corresponding segment + * If the block does not exist, then the data is read from the corresponding record * in write ahead log files. */ override def compute(split: Partition, context: TaskContext): Iterator[T] = { @@ -96,10 +100,39 @@ class WriteAheadLogBackedBlockRDD[T: ClassTag]( logDebug(s"Read partition data of $this from block manager, block $blockId") iterator case None => // Data not found in Block Manager, grab it from write ahead log file - val reader = new WriteAheadLogRandomReader(partition.segment.path, hadoopConf) - val dataRead = reader.read(partition.segment) - reader.close() - logInfo(s"Read partition data of $this from write ahead log, segment ${partition.segment}") + var dataRead: ByteBuffer = null + var writeAheadLog: WriteAheadLog = null + try { + // The WriteAheadLogUtils.createLog*** method needs a directory to create a + // WriteAheadLog object as the default FileBasedWriteAheadLog needs a directory for + // writing log data. However, the directory is not needed if data needs to be read, hence + // a dummy path is provided to satisfy the method parameter requirements. + // FileBasedWriteAheadLog will not create any file or directory at that path. + // FileBasedWriteAheadLog will not create any file or directory at that path. Also, + // this dummy directory should not already exist otherwise the WAL will try to recover + // past events from the directory and throw errors. + val nonExistentDirectory = new File( + System.getProperty("java.io.tmpdir"), UUID.randomUUID().toString).getAbsolutePath + writeAheadLog = WriteAheadLogUtils.createLogForReceiver( + SparkEnv.get.conf, nonExistentDirectory, hadoopConf) + dataRead = writeAheadLog.read(partition.walRecordHandle) + } catch { + case NonFatal(e) => + throw new SparkException( + s"Could not read data from write ahead log record ${partition.walRecordHandle}", e) + } finally { + if (writeAheadLog != null) { + writeAheadLog.close() + writeAheadLog = null + } + } + if (dataRead == null) { + throw new SparkException( + s"Could not read data from write ahead log record ${partition.walRecordHandle}, " + + s"read returned null") + } + logInfo(s"Read partition data of $this from write ahead log, record handle " + + partition.walRecordHandle) if (storeInBlockManager) { blockManager.putBytes(blockId, dataRead, storageLevel) logDebug(s"Stored partition data of $this into block manager with level $storageLevel") @@ -111,14 +144,20 @@ class WriteAheadLogBackedBlockRDD[T: ClassTag]( /** * Get the preferred location of the partition. This returns the locations of the block - * if it is present in the block manager, else it returns the location of the - * corresponding segment in HDFS. + * if it is present in the block manager, else if FileBasedWriteAheadLogSegment is used, + * it returns the location of the corresponding file segment in HDFS . */ override def getPreferredLocations(split: Partition): Seq[String] = { val partition = split.asInstanceOf[WriteAheadLogBackedBlockRDDPartition] val blockLocations = getBlockIdLocations().get(partition.blockId) - blockLocations.getOrElse( - HdfsUtils.getFileSegmentLocations( - partition.segment.path, partition.segment.offset, partition.segment.length, hadoopConfig)) + blockLocations.getOrElse { + partition.walRecordHandle match { + case fileSegment: FileBasedWriteAheadLogSegment => + HdfsUtils.getFileSegmentLocations( + fileSegment.path, fileSegment.offset, fileSegment.length, hadoopConfig) + case _ => + Seq.empty + } + } } } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala index f4963a78e1d18..4bebcc5aa7ca0 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/BlockGenerator.scala @@ -126,6 +126,20 @@ private[streaming] class BlockGenerator( listener.onAddData(data, metadata) } + /** + * Push multiple data items into the buffer. After buffering the data, the + * `BlockGeneratorListener.onAddData` callback will be called. All received data items + * will be periodically pushed into BlockManager. Note that all the data items is guaranteed + * to be present in a single block. + */ + def addMultipleDataWithCallback(dataIterator: Iterator[Any], metadata: Any): Unit = synchronized { + dataIterator.foreach { data => + waitToPush() + currentBuffer += data + } + listener.onAddData(dataIterator, metadata) + } + /** Change the buffer to which single records are added to. */ private def updateCurrentBuffer(time: Long): Unit = synchronized { try { diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala index 297bf04c0c25e..651b534ac1900 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala @@ -17,18 +17,18 @@ package org.apache.spark.streaming.receiver -import scala.concurrent.{Await, ExecutionContext, Future} import scala.concurrent.duration._ +import scala.concurrent.{Await, ExecutionContext, Future} import scala.language.{existentials, postfixOps} -import WriteAheadLogBasedBlockHandler._ import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path -import org.apache.spark.{Logging, SparkConf, SparkException} import org.apache.spark.storage._ -import org.apache.spark.streaming.util.{WriteAheadLogFileSegment, WriteAheadLogManager} -import org.apache.spark.util.{ThreadUtils, Clock, SystemClock} +import org.apache.spark.streaming.receiver.WriteAheadLogBasedBlockHandler._ +import org.apache.spark.streaming.util.{WriteAheadLogRecordHandle, WriteAheadLogUtils} +import org.apache.spark.util.{Clock, SystemClock, ThreadUtils} +import org.apache.spark.{Logging, SparkConf, SparkException} /** Trait that represents the metadata related to storage of blocks */ private[streaming] trait ReceivedBlockStoreResult { @@ -96,7 +96,7 @@ private[streaming] class BlockManagerBasedBlockHandler( */ private[streaming] case class WriteAheadLogBasedStoreResult( blockId: StreamBlockId, - segment: WriteAheadLogFileSegment + walRecordHandle: WriteAheadLogRecordHandle ) extends ReceivedBlockStoreResult @@ -116,10 +116,6 @@ private[streaming] class WriteAheadLogBasedBlockHandler( private val blockStoreTimeout = conf.getInt( "spark.streaming.receiver.blockStoreTimeout", 30).seconds - private val rollingInterval = conf.getInt( - "spark.streaming.receiver.writeAheadLog.rollingInterval", 60) - private val maxFailures = conf.getInt( - "spark.streaming.receiver.writeAheadLog.maxFailures", 3) private val effectiveStorageLevel = { if (storageLevel.deserialized) { @@ -139,13 +135,9 @@ private[streaming] class WriteAheadLogBasedBlockHandler( s"$effectiveStorageLevel when write ahead log is enabled") } - // Manages rolling log files - private val logManager = new WriteAheadLogManager( - checkpointDirToLogDir(checkpointDir, streamId), - hadoopConf, rollingInterval, maxFailures, - callerName = this.getClass.getSimpleName, - clock = clock - ) + // Write ahead log manages + private val writeAheadLog = WriteAheadLogUtils.createLogForReceiver( + conf, checkpointDirToLogDir(checkpointDir, streamId), hadoopConf) // For processing futures used in parallel block storing into block manager and write ahead log // # threads = 2, so that both writing to BM and WAL can proceed in parallel @@ -183,21 +175,22 @@ private[streaming] class WriteAheadLogBasedBlockHandler( // Store the block in write ahead log val storeInWriteAheadLogFuture = Future { - logManager.writeToLog(serializedBlock) + writeAheadLog.write(serializedBlock, clock.getTimeMillis()) } - // Combine the futures, wait for both to complete, and return the write ahead log segment + // Combine the futures, wait for both to complete, and return the write ahead log record handle val combinedFuture = storeInBlockManagerFuture.zip(storeInWriteAheadLogFuture).map(_._2) - val segment = Await.result(combinedFuture, blockStoreTimeout) - WriteAheadLogBasedStoreResult(blockId, segment) + val walRecordHandle = Await.result(combinedFuture, blockStoreTimeout) + WriteAheadLogBasedStoreResult(blockId, walRecordHandle) } def cleanupOldBlocks(threshTime: Long) { - logManager.cleanupOldLogs(threshTime, waitForCompletion = false) + writeAheadLog.clean(threshTime, false) } def stop() { - logManager.stop() + writeAheadLog.close() + executionContext.shutdown() } } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverSupervisorImpl.scala b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverSupervisorImpl.scala index 89af40330b9d9..93f047b91018f 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverSupervisorImpl.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceiverSupervisorImpl.scala @@ -25,12 +25,13 @@ import scala.collection.mutable.ArrayBuffer import com.google.common.base.Throwables import org.apache.hadoop.conf.Configuration -import org.apache.spark.{Logging, SparkEnv, SparkException} import org.apache.spark.rpc.{RpcEnv, ThreadSafeRpcEndpoint} import org.apache.spark.storage.StreamBlockId import org.apache.spark.streaming.Time import org.apache.spark.streaming.scheduler._ +import org.apache.spark.streaming.util.WriteAheadLogUtils import org.apache.spark.util.{RpcUtils, Utils} +import org.apache.spark.{Logging, SparkEnv, SparkException} /** * Concrete implementation of [[org.apache.spark.streaming.receiver.ReceiverSupervisor]] @@ -46,7 +47,7 @@ private[streaming] class ReceiverSupervisorImpl( ) extends ReceiverSupervisor(receiver, env.conf) with Logging { private val receivedBlockHandler: ReceivedBlockHandler = { - if (env.conf.getBoolean("spark.streaming.receiver.writeAheadLog.enable", false)) { + if (WriteAheadLogUtils.enableReceiverLog(env.conf)) { if (checkpointDirOption.isEmpty) { throw new SparkException( "Cannot enable receiver write-ahead log without checkpoint directory set. " + @@ -146,7 +147,7 @@ private[streaming] class ReceiverSupervisorImpl( logDebug(s"Pushed block $blockId in ${(System.currentTimeMillis - time)} ms") val blockInfo = ReceivedBlockInfo(streamId, numRecords, blockStoreResult) - trackerEndpoint.askWithReply[Boolean](AddBlock(blockInfo)) + trackerEndpoint.askWithRetry[Boolean](AddBlock(blockInfo)) logDebug(s"Reported block $blockId") } @@ -169,13 +170,13 @@ private[streaming] class ReceiverSupervisorImpl( override protected def onReceiverStart() { val msg = RegisterReceiver( streamId, receiver.getClass.getSimpleName, Utils.localHostName(), endpoint) - trackerEndpoint.askWithReply[Boolean](msg) + trackerEndpoint.askWithRetry[Boolean](msg) } override protected def onReceiverStop(message: String, error: Option[Throwable]) { logInfo("Deregistering receiver " + streamId) val errorString = error.map(Throwables.getStackTraceAsString).getOrElse("") - trackerEndpoint.askWithReply[Boolean](DeregisterReceiver(streamId, message, errorString)) + trackerEndpoint.askWithRetry[Boolean](DeregisterReceiver(streamId, message, errorString)) logInfo("Stopped receiver " + streamId) } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/BatchInfo.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/BatchInfo.scala index 92dc113f397ca..5b9bfbf9b01e3 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/BatchInfo.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/BatchInfo.scala @@ -24,6 +24,7 @@ import org.apache.spark.streaming.Time * :: DeveloperApi :: * Class having information on completed batches. * @param batchTime Time of the batch + * @param streamIdToNumRecords A map of input stream id to record number * @param submissionTime Clock time of when jobs of this batch was submitted to * the streaming scheduler queue * @param processingStartTime Clock time of when the first job of this batch started processing @@ -32,7 +33,7 @@ import org.apache.spark.streaming.Time @DeveloperApi case class BatchInfo( batchTime: Time, - receivedBlockInfo: Map[Int, Array[ReceivedBlockInfo]], + streamIdToNumRecords: Map[Int, Long], submissionTime: Long, processingStartTime: Option[Long], processingEndTime: Option[Long] @@ -58,4 +59,9 @@ case class BatchInfo( */ def totalDelay: Option[Long] = schedulingDelay.zip(processingDelay) .map(x => x._1 + x._2).headOption + + /** + * The number of recorders received by the receivers in this batch. + */ + def numRecords: Long = streamIdToNumRecords.values.sum } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/InputInfoTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/InputInfoTracker.scala new file mode 100644 index 0000000000000..a72efccf2f994 --- /dev/null +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/InputInfoTracker.scala @@ -0,0 +1,62 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streaming.scheduler + +import scala.collection.mutable + +import org.apache.spark.Logging +import org.apache.spark.streaming.{Time, StreamingContext} + +/** To track the information of input stream at specified batch time. */ +private[streaming] case class InputInfo(inputStreamId: Int, numRecords: Long) + +/** + * This class manages all the input streams as well as their input data statistics. The information + * will be exposed through StreamingListener for monitoring. + */ +private[streaming] class InputInfoTracker(ssc: StreamingContext) extends Logging { + + // Map to track all the InputInfo related to specific batch time and input stream. + private val batchTimeToInputInfos = new mutable.HashMap[Time, mutable.HashMap[Int, InputInfo]] + + /** Report the input information with batch time to the tracker */ + def reportInfo(batchTime: Time, inputInfo: InputInfo): Unit = synchronized { + val inputInfos = batchTimeToInputInfos.getOrElseUpdate(batchTime, + new mutable.HashMap[Int, InputInfo]()) + + if (inputInfos.contains(inputInfo.inputStreamId)) { + throw new IllegalStateException(s"Input stream ${inputInfo.inputStreamId}} for batch" + + s"$batchTime is already added into InputInfoTracker, this is a illegal state") + } + inputInfos += ((inputInfo.inputStreamId, inputInfo)) + } + + /** Get the all the input stream's information of specified batch time */ + def getInfo(batchTime: Time): Map[Int, InputInfo] = synchronized { + val inputInfos = batchTimeToInputInfos.get(batchTime) + // Convert mutable HashMap to immutable Map for the caller + inputInfos.map(_.toMap).getOrElse(Map[Int, InputInfo]()) + } + + /** Cleanup the tracked input information older than threshold batch time */ + def cleanup(batchThreshTime: Time): Unit = synchronized { + val timesToCleanup = batchTimeToInputInfos.keys.filter(_ < batchThreshTime) + logInfo(s"remove old batch metadata: ${timesToCleanup.mkString(" ")}") + batchTimeToInputInfos --= timesToCleanup + } +} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala index 30cf87f5b7dd1..3c481bf3491f9 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/Job.scala @@ -25,15 +25,49 @@ import scala.util.Try */ private[streaming] class Job(val time: Time, func: () => _) { - var id: String = _ - var result: Try[_] = null + private var _id: String = _ + private var _outputOpId: Int = _ + private var isSet = false + private var _result: Try[_] = null def run() { - result = Try(func()) + _result = Try(func()) } - def setId(number: Int) { - id = "streaming job " + time + "." + number + def result: Try[_] = { + if (_result == null) { + throw new IllegalStateException("Cannot access result before job finishes") + } + _result + } + + /** + * @return the global unique id of this Job. + */ + def id: String = { + if (!isSet) { + throw new IllegalStateException("Cannot access id before calling setId") + } + _id + } + + /** + * @return the output op id of this Job. Each Job has a unique output op id in the same JobSet. + */ + def outputOpId: Int = { + if (!isSet) { + throw new IllegalStateException("Cannot access number before calling setId") + } + _outputOpId + } + + def setOutputOpId(outputOpId: Int) { + if (isSet) { + throw new IllegalStateException("Cannot call setOutputOpId more than once") + } + isSet = true + _id = s"streaming job $time.$outputOpId" + _outputOpId = outputOpId } override def toString: String = id diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala index 2467d50839add..9f93d6cbc3c20 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobGenerator.scala @@ -243,9 +243,9 @@ class JobGenerator(jobScheduler: JobScheduler) extends Logging { graph.generateJobs(time) // generate jobs using allocated block } match { case Success(jobs) => - val receivedBlockInfos = - jobScheduler.receiverTracker.getBlocksOfBatch(time).mapValues { _.toArray } - jobScheduler.submitJobSet(JobSet(time, jobs, receivedBlockInfos)) + val streamIdToInputInfos = jobScheduler.inputInfoTracker.getInfo(time) + val streamIdToNumRecords = streamIdToInputInfos.mapValues(_.numRecords) + jobScheduler.submitJobSet(JobSet(time, jobs, streamIdToNumRecords)) case Failure(e) => jobScheduler.reportError("Error generating jobs for time " + time, e) } @@ -266,6 +266,7 @@ class JobGenerator(jobScheduler: JobScheduler) extends Logging { // checkpointing of this batch to complete. val maxRememberDuration = graph.getMaxInputStreamRememberDuration() jobScheduler.receiverTracker.cleanupOldBlocksAndBatches(time - maxRememberDuration) + jobScheduler.inputInfoTracker.cleanup(time - maxRememberDuration) markBatchFullyProcessed(time) } } @@ -278,6 +279,7 @@ class JobGenerator(jobScheduler: JobScheduler) extends Logging { // been saved to checkpoints, so its safe to delete block metadata and data WAL files val maxRememberDuration = graph.getMaxInputStreamRememberDuration() jobScheduler.receiverTracker.cleanupOldBlocksAndBatches(time - maxRememberDuration) + jobScheduler.inputInfoTracker.cleanup(time - maxRememberDuration) markBatchFullyProcessed(time) } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala index 508b89278dcba..1d1ddaaccf217 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala @@ -50,6 +50,9 @@ class JobScheduler(val ssc: StreamingContext) extends Logging { // These two are created only when scheduler starts. // eventLoop not being null means the scheduler has been started and not stopped var receiverTracker: ReceiverTracker = null + // A tracker to track all the input stream information as well as processed record number + var inputInfoTracker: InputInfoTracker = null + private var eventLoop: EventLoop[JobSchedulerEvent] = null def start(): Unit = synchronized { @@ -65,6 +68,7 @@ class JobScheduler(val ssc: StreamingContext) extends Logging { listenerBus.start(ssc.sparkContext) receiverTracker = new ReceiverTracker(ssc) + inputInfoTracker = new InputInfoTracker(ssc) receiverTracker.start() jobGenerator.start() logInfo("Started JobScheduler") @@ -172,16 +176,28 @@ class JobScheduler(val ssc: StreamingContext) extends Logging { ssc.waiter.notifyError(e) } - private class JobHandler(job: Job) extends Runnable { + private class JobHandler(job: Job) extends Runnable with Logging { def run() { - eventLoop.post(JobStarted(job)) - // Disable checks for existing output directories in jobs launched by the streaming scheduler, - // since we may need to write output to an existing directory during checkpoint recovery; - // see SPARK-4835 for more details. - PairRDDFunctions.disableOutputSpecValidation.withValue(true) { - job.run() + ssc.sc.setLocalProperty(JobScheduler.BATCH_TIME_PROPERTY_KEY, job.time.milliseconds.toString) + ssc.sc.setLocalProperty(JobScheduler.OUTPUT_OP_ID_PROPERTY_KEY, job.outputOpId.toString) + try { + eventLoop.post(JobStarted(job)) + // Disable checks for existing output directories in jobs launched by the streaming + // scheduler, since we may need to write output to an existing directory during checkpoint + // recovery; see SPARK-4835 for more details. + PairRDDFunctions.disableOutputSpecValidation.withValue(true) { + job.run() + } + eventLoop.post(JobCompleted(job)) + } finally { + ssc.sc.setLocalProperty(JobScheduler.BATCH_TIME_PROPERTY_KEY, null) + ssc.sc.setLocalProperty(JobScheduler.OUTPUT_OP_ID_PROPERTY_KEY, null) } - eventLoop.post(JobCompleted(job)) } } } + +private[streaming] object JobScheduler { + val BATCH_TIME_PROPERTY_KEY = "spark.streaming.internal.batchTime" + val OUTPUT_OP_ID_PROPERTY_KEY = "spark.streaming.internal.outputOpId" +} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobSet.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobSet.scala index 5b134877d0b2d..e6be63b2ddbdc 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobSet.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobSet.scala @@ -28,14 +28,14 @@ private[streaming] case class JobSet( time: Time, jobs: Seq[Job], - receivedBlockInfo: Map[Int, Array[ReceivedBlockInfo]] = Map.empty) { + streamIdToNumRecords: Map[Int, Long] = Map.empty) { private val incompleteJobs = new HashSet[Job]() private val submissionTime = System.currentTimeMillis() // when this jobset was submitted private var processingStartTime = -1L // when the first job of this jobset started processing private var processingEndTime = -1L // when the last job of this jobset finished processing - jobs.zipWithIndex.foreach { case (job, i) => job.setId(i) } + jobs.zipWithIndex.foreach { case (job, i) => job.setOutputOpId(i) } incompleteJobs ++= jobs def handleJobStart(job: Job) { @@ -64,7 +64,7 @@ case class JobSet( def toBatchInfo: BatchInfo = { new BatchInfo( time, - receivedBlockInfo, + streamIdToNumRecords, submissionTime, if (processingStartTime >= 0 ) Some(processingStartTime) else None, if (processingEndTime >= 0 ) Some(processingEndTime) else None diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala index 200cf4ef4b0f1..14e769a281f51 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala @@ -25,10 +25,10 @@ import scala.language.implicitConversions import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path -import org.apache.spark.{SparkException, Logging, SparkConf} import org.apache.spark.streaming.Time -import org.apache.spark.streaming.util.WriteAheadLogManager +import org.apache.spark.streaming.util.{WriteAheadLog, WriteAheadLogUtils} import org.apache.spark.util.{Clock, Utils} +import org.apache.spark.{Logging, SparkConf, SparkException} /** Trait representing any event in the ReceivedBlockTracker that updates its state. */ private[streaming] sealed trait ReceivedBlockTrackerLogEvent @@ -70,7 +70,7 @@ private[streaming] class ReceivedBlockTracker( private val streamIdToUnallocatedBlockQueues = new mutable.HashMap[Int, ReceivedBlockQueue] private val timeToAllocatedBlocks = new mutable.HashMap[Time, AllocatedBlocks] - private val logManagerOption = createLogManager() + private val writeAheadLogOption = createWriteAheadLog() private var lastAllocatedBatchTime: Time = null @@ -155,12 +155,12 @@ private[streaming] class ReceivedBlockTracker( logInfo("Deleting batches " + timesToCleanup) writeToLog(BatchCleanupEvent(timesToCleanup)) timeToAllocatedBlocks --= timesToCleanup - logManagerOption.foreach(_.cleanupOldLogs(cleanupThreshTime.milliseconds, waitForCompletion)) + writeAheadLogOption.foreach(_.clean(cleanupThreshTime.milliseconds, waitForCompletion)) } /** Stop the block tracker. */ def stop() { - logManagerOption.foreach { _.stop() } + writeAheadLogOption.foreach { _.close() } } /** @@ -190,9 +190,10 @@ private[streaming] class ReceivedBlockTracker( timeToAllocatedBlocks --= batchTimes } - logManagerOption.foreach { logManager => + writeAheadLogOption.foreach { writeAheadLog => logInfo(s"Recovering from write ahead logs in ${checkpointDirOption.get}") - logManager.readFromLog().foreach { byteBuffer => + import scala.collection.JavaConversions._ + writeAheadLog.readAll().foreach { byteBuffer => logTrace("Recovering record " + byteBuffer) Utils.deserialize[ReceivedBlockTrackerLogEvent](byteBuffer.array) match { case BlockAdditionEvent(receivedBlockInfo) => @@ -208,10 +209,10 @@ private[streaming] class ReceivedBlockTracker( /** Write an update to the tracker to the write ahead log */ private def writeToLog(record: ReceivedBlockTrackerLogEvent) { - if (isLogManagerEnabled) { + if (isWriteAheadLogEnabled) { logDebug(s"Writing to log $record") - logManagerOption.foreach { logManager => - logManager.writeToLog(ByteBuffer.wrap(Utils.serialize(record))) + writeAheadLogOption.foreach { logManager => + logManager.write(ByteBuffer.wrap(Utils.serialize(record)), clock.getTimeMillis()) } } } @@ -222,8 +223,8 @@ private[streaming] class ReceivedBlockTracker( } /** Optionally create the write ahead log manager only if the feature is enabled */ - private def createLogManager(): Option[WriteAheadLogManager] = { - if (conf.getBoolean("spark.streaming.receiver.writeAheadLog.enable", false)) { + private def createWriteAheadLog(): Option[WriteAheadLog] = { + if (WriteAheadLogUtils.enableReceiverLog(conf)) { if (checkpointDirOption.isEmpty) { throw new SparkException( "Cannot enable receiver write-ahead log without checkpoint directory set. " + @@ -231,19 +232,16 @@ private[streaming] class ReceivedBlockTracker( "See documentation for more details.") } val logDir = ReceivedBlockTracker.checkpointDirToLogDir(checkpointDirOption.get) - val rollingIntervalSecs = conf.getInt( - "spark.streaming.receivedBlockTracker.writeAheadLog.rotationIntervalSecs", 60) - val logManager = new WriteAheadLogManager(logDir, hadoopConf, - rollingIntervalSecs = rollingIntervalSecs, clock = clock, - callerName = "ReceivedBlockHandlerMaster") - Some(logManager) + + val log = WriteAheadLogUtils.createLogForDriver(conf, logDir, hadoopConf) + Some(log) } else { None } } - /** Check if the log manager is enabled. This is only used for testing purposes. */ - private[streaming] def isLogManagerEnabled: Boolean = logManagerOption.nonEmpty + /** Check if the write ahead log is enabled. This is only used for testing purposes. */ + private[streaming] def isWriteAheadLogEnabled: Boolean = writeAheadLogOption.nonEmpty } private[streaming] object ReceivedBlockTracker { diff --git a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala index c4ead6f30a63d..1af65716d3003 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverTracker.scala @@ -20,6 +20,7 @@ package org.apache.spark.streaming.scheduler import scala.collection.mutable.{HashMap, SynchronizedMap} import scala.language.existentials +import org.apache.spark.streaming.util.WriteAheadLogUtils import org.apache.spark.{Logging, SerializableWritable, SparkEnv, SparkException} import org.apache.spark.rpc._ import org.apache.spark.streaming.{StreamingContext, Time} @@ -125,7 +126,7 @@ class ReceiverTracker(ssc: StreamingContext, skipReceiverLaunch: Boolean = false receivedBlockTracker.cleanupOldBatches(cleanupThreshTime, waitForCompletion = false) // Signal the receivers to delete old block data - if (ssc.conf.getBoolean("spark.streaming.receiver.writeAheadLog.enable", false)) { + if (WriteAheadLogUtils.enableReceiverLog(ssc.conf)) { logInfo(s"Cleanup old received batch data: $cleanupThreshTime") receiverInfo.values.flatMap { info => Option(info.endpoint) } .foreach { _.send(CleanupOldBlocks(cleanupThreshTime)) } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/AllBatchesTable.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/AllBatchesTable.scala index df1c0a10704c3..e219e27785533 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/ui/AllBatchesTable.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/AllBatchesTable.scala @@ -19,7 +19,6 @@ package org.apache.spark.streaming.ui import scala.xml.Node -import org.apache.spark.streaming.scheduler.BatchInfo import org.apache.spark.ui.UIUtils private[ui] abstract class BatchTableBase(tableId: String) { @@ -31,18 +30,20 @@ private[ui] abstract class BatchTableBase(tableId: String) { Processing Time } - protected def baseRow(batch: BatchInfo): Seq[Node] = { + protected def baseRow(batch: BatchUIData): Seq[Node] = { val batchTime = batch.batchTime.milliseconds val formattedBatchTime = UIUtils.formatDate(batch.batchTime.milliseconds) - val eventCount = batch.receivedBlockInfo.values.map { - receivers => receivers.map(_.numRecords).sum - }.sum + val eventCount = batch.numRecords val schedulingDelay = batch.schedulingDelay val formattedSchedulingDelay = schedulingDelay.map(UIUtils.formatDuration).getOrElse("-") val processingTime = batch.processingDelay val formattedProcessingTime = processingTime.map(UIUtils.formatDuration).getOrElse("-") - {formattedBatchTime} + + + {formattedBatchTime} + + {eventCount.toString} events {formattedSchedulingDelay} @@ -73,8 +74,9 @@ private[ui] abstract class BatchTableBase(tableId: String) { protected def renderRows: Seq[Node] } -private[ui] class ActiveBatchTable(runningBatches: Seq[BatchInfo], waitingBatches: Seq[BatchInfo]) - extends BatchTableBase("active-batches-table") { +private[ui] class ActiveBatchTable( + runningBatches: Seq[BatchUIData], + waitingBatches: Seq[BatchUIData]) extends BatchTableBase("active-batches-table") { override protected def columns: Seq[Node] = super.columns ++ Status @@ -85,16 +87,16 @@ private[ui] class ActiveBatchTable(runningBatches: Seq[BatchInfo], waitingBatche runningBatches.flatMap(batch => {runningBatchRow(batch)}) } - private def runningBatchRow(batch: BatchInfo): Seq[Node] = { + private def runningBatchRow(batch: BatchUIData): Seq[Node] = { baseRow(batch) ++ processing } - private def waitingBatchRow(batch: BatchInfo): Seq[Node] = { + private def waitingBatchRow(batch: BatchUIData): Seq[Node] = { baseRow(batch) ++ queued } } -private[ui] class CompletedBatchTable(batches: Seq[BatchInfo]) +private[ui] class CompletedBatchTable(batches: Seq[BatchUIData]) extends BatchTableBase("completed-batches-table") { override protected def columns: Seq[Node] = super.columns ++ Total Delay @@ -103,7 +105,7 @@ private[ui] class CompletedBatchTable(batches: Seq[BatchInfo]) batches.flatMap(batch => {completedBatchRow(batch)}) } - private def completedBatchRow(batch: BatchInfo): Seq[Node] = { + private def completedBatchRow(batch: BatchUIData): Seq[Node] = { val totalDelay = batch.totalDelay val formattedTotalDelay = totalDelay.map(UIUtils.formatDuration).getOrElse("-") baseRow(batch) ++ diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/BatchPage.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/BatchPage.scala new file mode 100644 index 0000000000000..2da9a29e2529e --- /dev/null +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/BatchPage.scala @@ -0,0 +1,264 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streaming.ui + +import javax.servlet.http.HttpServletRequest + +import scala.xml.{NodeSeq, Node} + +import org.apache.commons.lang3.StringEscapeUtils + +import org.apache.spark.streaming.Time +import org.apache.spark.ui.{UIUtils, WebUIPage} +import org.apache.spark.streaming.ui.StreamingJobProgressListener.{SparkJobId, OutputOpId} +import org.apache.spark.ui.jobs.UIData.JobUIData + + +private[ui] class BatchPage(parent: StreamingTab) extends WebUIPage("batch") { + private val streamingListener = parent.listener + private val sparkListener = parent.ssc.sc.jobProgressListener + + private def columns: Seq[Node] = { + Output Op Id + Description + Duration + Job Id + Duration + Stages: Succeeded/Total + Tasks (for all stages): Succeeded/Total + Error + } + + /** + * Generate a row for a Spark Job. Because duplicated output op infos needs to be collapsed into + * one cell, we use "rowspan" for the first row of a output op. + */ + def generateJobRow( + outputOpId: OutputOpId, + formattedOutputOpDuration: String, + numSparkJobRowsInOutputOp: Int, + isFirstRow: Boolean, + sparkJob: JobUIData): Seq[Node] = { + val lastStageInfo = Option(sparkJob.stageIds) + .filter(_.nonEmpty) + .flatMap { ids => sparkListener.stageIdToInfo.get(ids.max) } + val lastStageData = lastStageInfo.flatMap { s => + sparkListener.stageIdToData.get((s.stageId, s.attemptId)) + } + + val lastStageName = lastStageInfo.map(_.name).getOrElse("(Unknown Stage Name)") + val lastStageDescription = lastStageData.flatMap(_.description).getOrElse("") + val duration: Option[Long] = { + sparkJob.submissionTime.map { start => + val end = sparkJob.completionTime.getOrElse(System.currentTimeMillis()) + end - start + } + } + val lastFailureReason = + sparkJob.stageIds.sorted.reverse.flatMap(sparkListener.stageIdToInfo.get). + dropWhile(_.failureReason == None).take(1). // get the first info that contains failure + flatMap(info => info.failureReason).headOption.getOrElse("") + val formattedDuration = duration.map(d => UIUtils.formatDuration(d)).getOrElse("-") + val detailUrl = s"${UIUtils.prependBaseUri(parent.basePath)}/jobs/job?id=${sparkJob.jobId}" + + // In the first row, output op id and its information needs to be shown. In other rows, these + // cells will be taken up due to "rowspan". + // scalastyle:off + val prefixCells = + if (isFirstRow) { + {outputOpId.toString} + + + {lastStageDescription} + {lastStageName} + + {formattedOutputOpDuration} + } else { + Nil + } + // scalastyle:on + + + {prefixCells} + + + {sparkJob.jobId}{sparkJob.jobGroup.map(id => s"($id)").getOrElse("")} + + + + {formattedDuration} + + + {sparkJob.completedStageIndices.size}/{sparkJob.stageIds.size - sparkJob.numSkippedStages} + {if (sparkJob.numFailedStages > 0) s"(${sparkJob.numFailedStages} failed)"} + {if (sparkJob.numSkippedStages > 0) s"(${sparkJob.numSkippedStages} skipped)"} + + + { + UIUtils.makeProgressBar( + started = sparkJob.numActiveTasks, + completed = sparkJob.numCompletedTasks, + failed = sparkJob.numFailedTasks, + skipped = sparkJob.numSkippedTasks, + total = sparkJob.numTasks - sparkJob.numSkippedTasks) + } + + {failureReasonCell(lastFailureReason)} + + } + + private def generateOutputOpIdRow( + outputOpId: OutputOpId, sparkJobs: Seq[JobUIData]): Seq[Node] = { + val sparkjobDurations = sparkJobs.map(sparkJob => { + sparkJob.submissionTime.map { start => + val end = sparkJob.completionTime.getOrElse(System.currentTimeMillis()) + end - start + } + }) + val formattedOutputOpDuration = + if (sparkjobDurations.exists(_ == None)) { + // If any job does not finish, set "formattedOutputOpDuration" to "-" + "-" + } else { + UIUtils.formatDuration(sparkjobDurations.flatMap(x => x).sum) + } + generateJobRow(outputOpId, formattedOutputOpDuration, sparkJobs.size, true, sparkJobs.head) ++ + sparkJobs.tail.map { sparkJob => + generateJobRow(outputOpId, formattedOutputOpDuration, sparkJobs.size, false, sparkJob) + }.flatMap(x => x) + } + + private def failureReasonCell(failureReason: String): Seq[Node] = { + val isMultiline = failureReason.indexOf('\n') >= 0 + // Display the first line by default + val failureReasonSummary = StringEscapeUtils.escapeHtml4( + if (isMultiline) { + failureReason.substring(0, failureReason.indexOf('\n')) + } else { + failureReason + }) + val details = if (isMultiline) { + // scalastyle:off + + +details + ++ + + // scalastyle:on + } else { + "" + } + {failureReasonSummary}{details} + } + + private def getJobData(sparkJobId: SparkJobId): Option[JobUIData] = { + sparkListener.activeJobs.get(sparkJobId).orElse { + sparkListener.completedJobs.find(_.jobId == sparkJobId).orElse { + sparkListener.failedJobs.find(_.jobId == sparkJobId) + } + } + } + + /** + * Generate the job table for the batch. + */ + private def generateJobTable(batchUIData: BatchUIData): Seq[Node] = { + val outputOpIdToSparkJobIds = batchUIData.outputOpIdSparkJobIdPairs.groupBy(_.outputOpId).toSeq. + sortBy(_._1). // sorted by OutputOpId + map { case (outputOpId, outputOpIdAndSparkJobIds) => + // sort SparkJobIds for each OutputOpId + (outputOpId, outputOpIdAndSparkJobIds.map(_.sparkJobId).sorted) + } + sparkListener.synchronized { + val outputOpIdWithJobs: Seq[(OutputOpId, Seq[JobUIData])] = + outputOpIdToSparkJobIds.map { case (outputOpId, sparkJobIds) => + // Filter out spark Job ids that don't exist in sparkListener + (outputOpId, sparkJobIds.flatMap(getJobData)) + } + + + + {columns} + + + { + outputOpIdWithJobs.map { + case (outputOpId, jobs) => generateOutputOpIdRow(outputOpId, jobs) + } + } + +
+ } + } + + def render(request: HttpServletRequest): Seq[Node] = { + val batchTime = Option(request.getParameter("id")).map(id => Time(id.toLong)).getOrElse { + throw new IllegalArgumentException(s"Missing id parameter") + } + val formattedBatchTime = UIUtils.formatDate(batchTime.milliseconds) + + val batchUIData = streamingListener.getBatchUIData(batchTime).getOrElse { + throw new IllegalArgumentException(s"Batch $formattedBatchTime does not exist") + } + + val formattedSchedulingDelay = + batchUIData.schedulingDelay.map(UIUtils.formatDuration).getOrElse("-") + val formattedProcessingTime = + batchUIData.processingDelay.map(UIUtils.formatDuration).getOrElse("-") + val formattedTotalDelay = batchUIData.totalDelay.map(UIUtils.formatDuration).getOrElse("-") + + val summary: NodeSeq = +
+
    +
  • + Batch Duration: + {UIUtils.formatDuration(streamingListener.batchDuration)} +
    • +
  • + Input data size: + {batchUIData.numRecords} records +
    • +
  • + Scheduling delay: + {formattedSchedulingDelay} +
    • +
  • + Processing time: + {formattedProcessingTime} +
    • +
  • + Total delay: + {formattedTotalDelay} +
    • +
+
+ + val jobTable = + if (batchUIData.outputOpIdSparkJobIdPairs.isEmpty) { +
Cannot find any job for Batch {formattedBatchTime}.
+ } else { + generateJobTable(batchUIData) + } + + val content = summary ++ jobTable + + UIUtils.headerSparkPage(s"Details of batch at $formattedBatchTime", content, parent) + } +} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/BatchUIData.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/BatchUIData.scala new file mode 100644 index 0000000000000..99e10d2b0be12 --- /dev/null +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/BatchUIData.scala @@ -0,0 +1,75 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + + +package org.apache.spark.streaming.ui + +import org.apache.spark.streaming.Time +import org.apache.spark.streaming.scheduler.BatchInfo +import org.apache.spark.streaming.ui.StreamingJobProgressListener._ + +private[ui] case class OutputOpIdAndSparkJobId(outputOpId: OutputOpId, sparkJobId: SparkJobId) + +private[ui] case class BatchUIData( + val batchTime: Time, + val receiverNumRecords: Map[Int, Long], + val submissionTime: Long, + val processingStartTime: Option[Long], + val processingEndTime: Option[Long], + var outputOpIdSparkJobIdPairs: Seq[OutputOpIdAndSparkJobId] = Seq.empty) { + + /** + * Time taken for the first job of this batch to start processing from the time this batch + * was submitted to the streaming scheduler. Essentially, it is + * `processingStartTime` - `submissionTime`. + */ + def schedulingDelay: Option[Long] = processingStartTime.map(_ - submissionTime) + + /** + * Time taken for the all jobs of this batch to finish processing from the time they started + * processing. Essentially, it is `processingEndTime` - `processingStartTime`. + */ + def processingDelay: Option[Long] = { + for (start <- processingStartTime; + end <- processingEndTime) + yield end - start + } + + /** + * Time taken for all the jobs of this batch to finish processing from the time they + * were submitted. Essentially, it is `processingDelay` + `schedulingDelay`. + */ + def totalDelay: Option[Long] = processingEndTime.map(_ - submissionTime) + + /** + * The number of recorders received by the receivers in this batch. + */ + def numRecords: Long = receiverNumRecords.map(_._2).sum +} + +private[ui] object BatchUIData { + + def apply(batchInfo: BatchInfo): BatchUIData = { + new BatchUIData( + batchInfo.batchTime, + batchInfo.streamIdToNumRecords, + batchInfo.submissionTime, + batchInfo.processingStartTime, + batchInfo.processingEndTime + ) + } +} diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala index be1e8686cf9fa..d2729fa70d6d2 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingJobProgressListener.scala @@ -17,29 +17,58 @@ package org.apache.spark.streaming.ui -import scala.collection.mutable.{Queue, HashMap} +import java.util.LinkedHashMap +import java.util.{Map => JMap} +import java.util.Properties +import scala.collection.mutable.{ArrayBuffer, Queue, HashMap, SynchronizedBuffer} + +import org.apache.spark.scheduler._ import org.apache.spark.streaming.{Time, StreamingContext} import org.apache.spark.streaming.scheduler._ import org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted import org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted -import org.apache.spark.streaming.scheduler.BatchInfo import org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted import org.apache.spark.util.Distribution private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) - extends StreamingListener { + extends StreamingListener with SparkListener { - private val waitingBatchInfos = new HashMap[Time, BatchInfo] - private val runningBatchInfos = new HashMap[Time, BatchInfo] - private val completedBatchInfos = new Queue[BatchInfo] - private val batchInfoLimit = ssc.conf.getInt("spark.streaming.ui.retainedBatches", 100) + private val waitingBatchUIData = new HashMap[Time, BatchUIData] + private val runningBatchUIData = new HashMap[Time, BatchUIData] + private val completedBatchUIData = new Queue[BatchUIData] + private val batchUIDataLimit = ssc.conf.getInt("spark.streaming.ui.retainedBatches", 100) private var totalCompletedBatches = 0L private var totalReceivedRecords = 0L private var totalProcessedRecords = 0L private val receiverInfos = new HashMap[Int, ReceiverInfo] + // Because onJobStart and onBatchXXX messages are processed in different threads, + // we may not be able to get the corresponding BatchUIData when receiving onJobStart. So here we + // cannot use a map of (Time, BatchUIData). + private[ui] val batchTimeToOutputOpIdSparkJobIdPair = + new LinkedHashMap[Time, SynchronizedBuffer[OutputOpIdAndSparkJobId]] { + override def removeEldestEntry( + p1: JMap.Entry[Time, SynchronizedBuffer[OutputOpIdAndSparkJobId]]): Boolean = { + // If a lot of "onBatchCompleted"s happen before "onJobStart" (image if + // SparkContext.listenerBus is very slow), "batchTimeToOutputOpIdToSparkJobIds" + // may add some information for a removed batch when processing "onJobStart". It will be a + // memory leak. + // + // To avoid the memory leak, we control the size of "batchTimeToOutputOpIdToSparkJobIds" and + // evict the eldest one. + // + // Note: if "onJobStart" happens before "onBatchSubmitted", the size of + // "batchTimeToOutputOpIdToSparkJobIds" may be greater than the number of the retained + // batches temporarily, so here we use "10" to handle such case. This is not a perfect + // solution, but at least it can handle most of cases. + size() > + waitingBatchUIData.size + runningBatchUIData.size + completedBatchUIData.size + 10 + } + } + + val batchDuration = ssc.graph.batchDuration.milliseconds override def onReceiverStarted(receiverStarted: StreamingListenerReceiverStarted) { @@ -62,37 +91,62 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) override def onBatchSubmitted(batchSubmitted: StreamingListenerBatchSubmitted): Unit = { synchronized { - waitingBatchInfos(batchSubmitted.batchInfo.batchTime) = batchSubmitted.batchInfo + waitingBatchUIData(batchSubmitted.batchInfo.batchTime) = + BatchUIData(batchSubmitted.batchInfo) } } override def onBatchStarted(batchStarted: StreamingListenerBatchStarted): Unit = synchronized { - runningBatchInfos(batchStarted.batchInfo.batchTime) = batchStarted.batchInfo - waitingBatchInfos.remove(batchStarted.batchInfo.batchTime) + val batchUIData = BatchUIData(batchStarted.batchInfo) + runningBatchUIData(batchStarted.batchInfo.batchTime) = BatchUIData(batchStarted.batchInfo) + waitingBatchUIData.remove(batchStarted.batchInfo.batchTime) - batchStarted.batchInfo.receivedBlockInfo.foreach { case (_, infos) => - totalReceivedRecords += infos.map(_.numRecords).sum - } + totalReceivedRecords += batchUIData.numRecords } override def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted): Unit = { synchronized { - waitingBatchInfos.remove(batchCompleted.batchInfo.batchTime) - runningBatchInfos.remove(batchCompleted.batchInfo.batchTime) - completedBatchInfos.enqueue(batchCompleted.batchInfo) - if (completedBatchInfos.size > batchInfoLimit) completedBatchInfos.dequeue() + waitingBatchUIData.remove(batchCompleted.batchInfo.batchTime) + runningBatchUIData.remove(batchCompleted.batchInfo.batchTime) + val batchUIData = BatchUIData(batchCompleted.batchInfo) + completedBatchUIData.enqueue(batchUIData) + if (completedBatchUIData.size > batchUIDataLimit) { + val removedBatch = completedBatchUIData.dequeue() + batchTimeToOutputOpIdSparkJobIdPair.remove(removedBatch.batchTime) + } totalCompletedBatches += 1L - batchCompleted.batchInfo.receivedBlockInfo.foreach { case (_, infos) => - totalProcessedRecords += infos.map(_.numRecords).sum + totalProcessedRecords += batchUIData.numRecords + } + } + + override def onJobStart(jobStart: SparkListenerJobStart): Unit = synchronized { + getBatchTimeAndOutputOpId(jobStart.properties).foreach { case (batchTime, outputOpId) => + var outputOpIdToSparkJobIds = batchTimeToOutputOpIdSparkJobIdPair.get(batchTime) + if (outputOpIdToSparkJobIds == null) { + outputOpIdToSparkJobIds = + new ArrayBuffer[OutputOpIdAndSparkJobId]() + with SynchronizedBuffer[OutputOpIdAndSparkJobId] + batchTimeToOutputOpIdSparkJobIdPair.put(batchTime, outputOpIdToSparkJobIds) } + outputOpIdToSparkJobIds += OutputOpIdAndSparkJobId(outputOpId, jobStart.jobId) } } - def numReceivers: Int = synchronized { - ssc.graph.getReceiverInputStreams().size + private def getBatchTimeAndOutputOpId(properties: Properties): Option[(Time, Int)] = { + val batchTime = properties.getProperty(JobScheduler.BATCH_TIME_PROPERTY_KEY) + if (batchTime == null) { + // Not submitted from JobScheduler + None + } else { + val outputOpId = properties.getProperty(JobScheduler.OUTPUT_OP_ID_PROPERTY_KEY) + assert(outputOpId != null) + Some(Time(batchTime.toLong) -> outputOpId.toInt) + } } + def numReceivers: Int = ssc.graph.getReceiverInputStreams().size + def numTotalCompletedBatches: Long = synchronized { totalCompletedBatches } @@ -106,19 +160,19 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) } def numUnprocessedBatches: Long = synchronized { - waitingBatchInfos.size + runningBatchInfos.size + waitingBatchUIData.size + runningBatchUIData.size } - def waitingBatches: Seq[BatchInfo] = synchronized { - waitingBatchInfos.values.toSeq + def waitingBatches: Seq[BatchUIData] = synchronized { + waitingBatchUIData.values.toSeq } - def runningBatches: Seq[BatchInfo] = synchronized { - runningBatchInfos.values.toSeq + def runningBatches: Seq[BatchUIData] = synchronized { + runningBatchUIData.values.toSeq } - def retainedCompletedBatches: Seq[BatchInfo] = synchronized { - completedBatchInfos.toSeq + def retainedCompletedBatches: Seq[BatchUIData] = synchronized { + completedBatchUIData.toSeq } def processingDelayDistribution: Option[Distribution] = synchronized { @@ -134,29 +188,26 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) } def receivedRecordsDistributions: Map[Int, Option[Distribution]] = synchronized { - val latestBatchInfos = retainedBatches.reverse.take(batchInfoLimit) - val latestBlockInfos = latestBatchInfos.map(_.receivedBlockInfo) - (0 until numReceivers).map { receiverId => - val blockInfoOfParticularReceiver = latestBlockInfos.map { batchInfo => - batchInfo.get(receiverId).getOrElse(Array.empty) - } - val recordsOfParticularReceiver = blockInfoOfParticularReceiver.map { blockInfo => - // calculate records per second for each batch - blockInfo.map(_.numRecords).sum.toDouble * 1000 / batchDuration - } - val distributionOption = Distribution(recordsOfParticularReceiver) - (receiverId, distributionOption) + val latestBatchInfos = retainedBatches.reverse.take(batchUIDataLimit) + val latestReceiverNumRecords = latestBatchInfos.map(_.receiverNumRecords) + val streamIds = ssc.graph.getInputStreams().map(_.id) + streamIds.map { id => + val recordsOfParticularReceiver = + latestReceiverNumRecords.map(v => v.getOrElse(id, 0L).toDouble * 1000 / batchDuration) + val distribution = Distribution(recordsOfParticularReceiver) + (id, distribution) }.toMap } def lastReceivedBatchRecords: Map[Int, Long] = synchronized { - val lastReceivedBlockInfoOption = lastReceivedBatch.map(_.receivedBlockInfo) - lastReceivedBlockInfoOption.map { lastReceivedBlockInfo => - (0 until numReceivers).map { receiverId => - (receiverId, lastReceivedBlockInfo(receiverId).map(_.numRecords).sum) + val lastReceiverNumRecords = lastReceivedBatch.map(_.receiverNumRecords) + val streamIds = ssc.graph.getInputStreams().map(_.id) + lastReceiverNumRecords.map { receiverNumRecords => + streamIds.map { id => + (id, receiverNumRecords.getOrElse(id, 0L)) }.toMap }.getOrElse { - (0 until numReceivers).map(receiverId => (receiverId, 0L)).toMap + streamIds.map(id => (id, 0L)).toMap } } @@ -164,20 +215,43 @@ private[streaming] class StreamingJobProgressListener(ssc: StreamingContext) receiverInfos.get(receiverId) } - def lastCompletedBatch: Option[BatchInfo] = synchronized { - completedBatchInfos.sortBy(_.batchTime)(Time.ordering).lastOption + def receiverIds(): Iterable[Int] = synchronized { + receiverInfos.keys + } + + def lastCompletedBatch: Option[BatchUIData] = synchronized { + completedBatchUIData.sortBy(_.batchTime)(Time.ordering).lastOption } - def lastReceivedBatch: Option[BatchInfo] = synchronized { + def lastReceivedBatch: Option[BatchUIData] = synchronized { retainedBatches.lastOption } - private def retainedBatches: Seq[BatchInfo] = { - (waitingBatchInfos.values.toSeq ++ - runningBatchInfos.values.toSeq ++ completedBatchInfos).sortBy(_.batchTime)(Time.ordering) + private def retainedBatches: Seq[BatchUIData] = { + (waitingBatchUIData.values.toSeq ++ + runningBatchUIData.values.toSeq ++ completedBatchUIData).sortBy(_.batchTime)(Time.ordering) } - private def extractDistribution(getMetric: BatchInfo => Option[Long]): Option[Distribution] = { - Distribution(completedBatchInfos.flatMap(getMetric(_)).map(_.toDouble)) + private def extractDistribution(getMetric: BatchUIData => Option[Long]): Option[Distribution] = { + Distribution(completedBatchUIData.flatMap(getMetric(_)).map(_.toDouble)) } + + def getBatchUIData(batchTime: Time): Option[BatchUIData] = synchronized { + val batchUIData = waitingBatchUIData.get(batchTime).orElse { + runningBatchUIData.get(batchTime).orElse { + completedBatchUIData.find(batch => batch.batchTime == batchTime) + } + } + batchUIData.foreach { _batchUIData => + val outputOpIdToSparkJobIds = + Option(batchTimeToOutputOpIdSparkJobIdPair.get(batchTime)).getOrElse(Seq.empty) + _batchUIData.outputOpIdSparkJobIdPairs = outputOpIdToSparkJobIds + } + batchUIData + } +} + +private[streaming] object StreamingJobProgressListener { + type SparkJobId = Int + type OutputOpId = Int } diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala index 07fa285642eec..db37ae815bdf5 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingPage.scala @@ -95,7 +95,7 @@ private[ui] class StreamingPage(parent: StreamingTab) "Maximum rate\n[events/sec]", "Last Error" ) - val dataRows = (0 until listener.numReceivers).map { receiverId => + val dataRows = listener.receiverIds().map { receiverId => val receiverInfo = listener.receiverInfo(receiverId) val receiverName = receiverInfo.map(_.name).getOrElse(s"Receiver-$receiverId") val receiverActive = receiverInfo.map { info => @@ -114,7 +114,7 @@ private[ui] class StreamingPage(parent: StreamingTab) }.getOrElse(emptyCell) Seq(receiverName, receiverActive, receiverLocation, receiverLastBatchRecords) ++ receivedRecordStats ++ Seq(receiverLastError) - } + }.toSeq Some(listingTable(headerRow, dataRows)) } else { None diff --git a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingTab.scala b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingTab.scala index 9a860ea4a6c68..e4039639adbad 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingTab.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/ui/StreamingTab.scala @@ -27,14 +27,16 @@ import StreamingTab._ * Spark Web UI tab that shows statistics of a streaming job. * This assumes the given SparkContext has enabled its SparkUI. */ -private[spark] class StreamingTab(ssc: StreamingContext) +private[spark] class StreamingTab(val ssc: StreamingContext) extends SparkUITab(getSparkUI(ssc), "streaming") with Logging { val parent = getSparkUI(ssc) val listener = ssc.progressListener ssc.addStreamingListener(listener) + ssc.sc.addSparkListener(listener) attachPage(new StreamingPage(this)) + attachPage(new BatchPage(this)) parent.attachTab(this) def detach() { diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogManager.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala similarity index 79% rename from streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogManager.scala rename to streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala index 38a93cc3c9a1f..9985fedc35141 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogManager.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLog.scala @@ -17,6 +17,7 @@ package org.apache.spark.streaming.util import java.nio.ByteBuffer +import java.util.{Iterator => JIterator} import scala.collection.mutable.ArrayBuffer import scala.concurrent.{Await, ExecutionContext, Future} @@ -24,9 +25,9 @@ import scala.language.postfixOps import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path -import org.apache.spark.Logging -import org.apache.spark.util.{ThreadUtils, Clock, SystemClock} -import WriteAheadLogManager._ + +import org.apache.spark.util.ThreadUtils +import org.apache.spark.{Logging, SparkConf} /** * This class manages write ahead log files. @@ -34,37 +35,32 @@ import WriteAheadLogManager._ * - Recovers the log files and the reads the recovered records upon failures. * - Cleans up old log files. * - * Uses [[org.apache.spark.streaming.util.WriteAheadLogWriter]] to write - * and [[org.apache.spark.streaming.util.WriteAheadLogReader]] to read. + * Uses [[org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter]] to write + * and [[org.apache.spark.streaming.util.FileBasedWriteAheadLogReader]] to read. * * @param logDirectory Directory when rotating log files will be created. * @param hadoopConf Hadoop configuration for reading/writing log files. - * @param rollingIntervalSecs The interval in seconds with which logs will be rolled over. - * Default is one minute. - * @param maxFailures Max number of failures that is tolerated for every attempt to write to log. - * Default is three. - * @param callerName Optional name of the class who is using this manager. - * @param clock Optional clock that is used to check for rotation interval. */ -private[streaming] class WriteAheadLogManager( +private[streaming] class FileBasedWriteAheadLog( + conf: SparkConf, logDirectory: String, hadoopConf: Configuration, - rollingIntervalSecs: Int = 60, - maxFailures: Int = 3, - callerName: String = "", - clock: Clock = new SystemClock - ) extends Logging { + rollingIntervalSecs: Int, + maxFailures: Int + ) extends WriteAheadLog with Logging { + + import FileBasedWriteAheadLog._ private val pastLogs = new ArrayBuffer[LogInfo] - private val callerNameTag = - if (callerName.nonEmpty) s" for $callerName" else "" + private val callerNameTag = getCallerName.map(c => s" for $c").getOrElse("") + private val threadpoolName = s"WriteAheadLogManager $callerNameTag" implicit private val executionContext = ExecutionContext.fromExecutorService( ThreadUtils.newDaemonSingleThreadExecutor(threadpoolName)) override protected val logName = s"WriteAheadLogManager $callerNameTag" private var currentLogPath: Option[String] = None - private var currentLogWriter: WriteAheadLogWriter = null + private var currentLogWriter: FileBasedWriteAheadLogWriter = null private var currentLogWriterStartTime: Long = -1L private var currentLogWriterStopTime: Long = -1L @@ -75,14 +71,14 @@ private[streaming] class WriteAheadLogManager( * ByteBuffer to HDFS. When this method returns, the data is guaranteed to have been flushed * to HDFS, and will be available for readers to read. */ - def writeToLog(byteBuffer: ByteBuffer): WriteAheadLogFileSegment = synchronized { - var fileSegment: WriteAheadLogFileSegment = null + def write(byteBuffer: ByteBuffer, time: Long): FileBasedWriteAheadLogSegment = synchronized { + var fileSegment: FileBasedWriteAheadLogSegment = null var failures = 0 var lastException: Exception = null var succeeded = false while (!succeeded && failures < maxFailures) { try { - fileSegment = getLogWriter(clock.getTimeMillis()).write(byteBuffer) + fileSegment = getLogWriter(time).write(byteBuffer) succeeded = true } catch { case ex: Exception => @@ -99,6 +95,19 @@ private[streaming] class WriteAheadLogManager( fileSegment } + def read(segment: WriteAheadLogRecordHandle): ByteBuffer = { + val fileSegment = segment.asInstanceOf[FileBasedWriteAheadLogSegment] + var reader: FileBasedWriteAheadLogRandomReader = null + var byteBuffer: ByteBuffer = null + try { + reader = new FileBasedWriteAheadLogRandomReader(fileSegment.path, hadoopConf) + byteBuffer = reader.read(fileSegment) + } finally { + reader.close() + } + byteBuffer + } + /** * Read all the existing logs from the log directory. * @@ -108,12 +117,14 @@ private[streaming] class WriteAheadLogManager( * the latest the records. This does not deal with currently active log files, and * hence the implementation is kept simple. */ - def readFromLog(): Iterator[ByteBuffer] = synchronized { + def readAll(): JIterator[ByteBuffer] = synchronized { + import scala.collection.JavaConversions._ val logFilesToRead = pastLogs.map{ _.path} ++ currentLogPath logInfo("Reading from the logs: " + logFilesToRead.mkString("\n")) + logFilesToRead.iterator.map { file => logDebug(s"Creating log reader with $file") - new WriteAheadLogReader(file, hadoopConf) + new FileBasedWriteAheadLogReader(file, hadoopConf) } flatMap { x => x } } @@ -129,7 +140,7 @@ private[streaming] class WriteAheadLogManager( * deleted. This should be set to true only for testing. Else the files will be deleted * asynchronously. */ - def cleanupOldLogs(threshTime: Long, waitForCompletion: Boolean): Unit = { + def clean(threshTime: Long, waitForCompletion: Boolean): Unit = { val oldLogFiles = synchronized { pastLogs.filter { _.endTime < threshTime } } logInfo(s"Attempting to clear ${oldLogFiles.size} old log files in $logDirectory " + s"older than $threshTime: ${oldLogFiles.map { _.path }.mkString("\n")}") @@ -160,7 +171,7 @@ private[streaming] class WriteAheadLogManager( /** Stop the manager, close any open log writer */ - def stop(): Unit = synchronized { + def close(): Unit = synchronized { if (currentLogWriter != null) { currentLogWriter.close() } @@ -169,7 +180,7 @@ private[streaming] class WriteAheadLogManager( } /** Get the current log writer while taking care of rotation */ - private def getLogWriter(currentTime: Long): WriteAheadLogWriter = synchronized { + private def getLogWriter(currentTime: Long): FileBasedWriteAheadLogWriter = synchronized { if (currentLogWriter == null || currentTime > currentLogWriterStopTime) { resetWriter() currentLogPath.foreach { @@ -180,7 +191,7 @@ private[streaming] class WriteAheadLogManager( val newLogPath = new Path(logDirectory, timeToLogFile(currentLogWriterStartTime, currentLogWriterStopTime)) currentLogPath = Some(newLogPath.toString) - currentLogWriter = new WriteAheadLogWriter(currentLogPath.get, hadoopConf) + currentLogWriter = new FileBasedWriteAheadLogWriter(currentLogPath.get, hadoopConf) } currentLogWriter } @@ -207,7 +218,7 @@ private[streaming] class WriteAheadLogManager( } } -private[util] object WriteAheadLogManager { +private[streaming] object FileBasedWriteAheadLog { case class LogInfo(startTime: Long, endTime: Long, path: String) @@ -217,6 +228,11 @@ private[util] object WriteAheadLogManager { s"log-$startTime-$stopTime" } + def getCallerName(): Option[String] = { + val stackTraceClasses = Thread.currentThread.getStackTrace().map(_.getClassName) + stackTraceClasses.find(!_.contains("WriteAheadLog")).flatMap(_.split(".").lastOption) + } + /** Convert a sequence of files to a sequence of sorted LogInfo objects */ def logFilesTologInfo(files: Seq[Path]): Seq[LogInfo] = { files.flatMap { file => diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogRandomReader.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogRandomReader.scala similarity index 83% rename from streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogRandomReader.scala rename to streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogRandomReader.scala index 003989092a42a..f7168229ec15a 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogRandomReader.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogRandomReader.scala @@ -23,16 +23,16 @@ import org.apache.hadoop.conf.Configuration /** * A random access reader for reading write ahead log files written using - * [[org.apache.spark.streaming.util.WriteAheadLogWriter]]. Given the file segment info, - * this reads the record (bytebuffer) from the log file. + * [[org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter]]. Given the file segment info, + * this reads the record (ByteBuffer) from the log file. */ -private[streaming] class WriteAheadLogRandomReader(path: String, conf: Configuration) +private[streaming] class FileBasedWriteAheadLogRandomReader(path: String, conf: Configuration) extends Closeable { private val instream = HdfsUtils.getInputStream(path, conf) private var closed = false - def read(segment: WriteAheadLogFileSegment): ByteBuffer = synchronized { + def read(segment: FileBasedWriteAheadLogSegment): ByteBuffer = synchronized { assertOpen() instream.seek(segment.offset) val nextLength = instream.readInt() diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogReader.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogReader.scala similarity index 93% rename from streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogReader.scala rename to streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogReader.scala index 2afc0d1551acf..c3bb59f3fef94 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogReader.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogReader.scala @@ -24,11 +24,11 @@ import org.apache.spark.Logging /** * A reader for reading write ahead log files written using - * [[org.apache.spark.streaming.util.WriteAheadLogWriter]]. This reads + * [[org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter]]. This reads * the records (bytebuffers) in the log file sequentially and return them as an * iterator of bytebuffers. */ -private[streaming] class WriteAheadLogReader(path: String, conf: Configuration) +private[streaming] class FileBasedWriteAheadLogReader(path: String, conf: Configuration) extends Iterator[ByteBuffer] with Closeable with Logging { private val instream = HdfsUtils.getInputStream(path, conf) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogFileSegment.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogSegment.scala similarity index 86% rename from streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogFileSegment.scala rename to streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogSegment.scala index 1005a2c8ec303..2e1f1528fad20 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogFileSegment.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogSegment.scala @@ -17,4 +17,5 @@ package org.apache.spark.streaming.util /** Class for representing a segment of data in a write ahead log file */ -private[streaming] case class WriteAheadLogFileSegment (path: String, offset: Long, length: Int) +private[streaming] case class FileBasedWriteAheadLogSegment(path: String, offset: Long, length: Int) + extends WriteAheadLogRecordHandle diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogWriter.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogWriter.scala similarity index 88% rename from streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogWriter.scala rename to streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogWriter.scala index 679f6a6dfd7c1..e146bec32a456 100644 --- a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogWriter.scala +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/FileBasedWriteAheadLogWriter.scala @@ -17,18 +17,17 @@ package org.apache.spark.streaming.util import java.io._ -import java.net.URI import java.nio.ByteBuffer import scala.util.Try import org.apache.hadoop.conf.Configuration -import org.apache.hadoop.fs.{FSDataOutputStream, FileSystem} +import org.apache.hadoop.fs.FSDataOutputStream /** * A writer for writing byte-buffers to a write ahead log file. */ -private[streaming] class WriteAheadLogWriter(path: String, hadoopConf: Configuration) +private[streaming] class FileBasedWriteAheadLogWriter(path: String, hadoopConf: Configuration) extends Closeable { private lazy val stream = HdfsUtils.getOutputStream(path, hadoopConf) @@ -43,11 +42,11 @@ private[streaming] class WriteAheadLogWriter(path: String, hadoopConf: Configura private var closed = false /** Write the bytebuffer to the log file */ - def write(data: ByteBuffer): WriteAheadLogFileSegment = synchronized { + def write(data: ByteBuffer): FileBasedWriteAheadLogSegment = synchronized { assertOpen() data.rewind() // Rewind to ensure all data in the buffer is retrieved val lengthToWrite = data.remaining() - val segment = new WriteAheadLogFileSegment(path, nextOffset, lengthToWrite) + val segment = new FileBasedWriteAheadLogSegment(path, nextOffset, lengthToWrite) stream.writeInt(lengthToWrite) if (data.hasArray) { stream.write(data.array()) diff --git a/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogUtils.scala b/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogUtils.scala new file mode 100644 index 0000000000000..7f6ff12c58d47 --- /dev/null +++ b/streaming/src/main/scala/org/apache/spark/streaming/util/WriteAheadLogUtils.scala @@ -0,0 +1,129 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streaming.util + +import scala.util.control.NonFatal + +import org.apache.hadoop.conf.Configuration + +import org.apache.spark.util.Utils +import org.apache.spark.{Logging, SparkConf, SparkException} + +/** A helper class with utility functions related to the WriteAheadLog interface */ +private[streaming] object WriteAheadLogUtils extends Logging { + val RECEIVER_WAL_ENABLE_CONF_KEY = "spark.streaming.receiver.writeAheadLog.enable" + val RECEIVER_WAL_CLASS_CONF_KEY = "spark.streaming.receiver.writeAheadLog.class" + val RECEIVER_WAL_ROLLING_INTERVAL_CONF_KEY = + "spark.streaming.receiver.writeAheadLog.rollingIntervalSecs" + val RECEIVER_WAL_MAX_FAILURES_CONF_KEY = "spark.streaming.receiver.writeAheadLog.maxFailures" + + val DRIVER_WAL_CLASS_CONF_KEY = "spark.streaming.driver.writeAheadLog.class" + val DRIVER_WAL_ROLLING_INTERVAL_CONF_KEY = + "spark.streaming.driver.writeAheadLog.rollingIntervalSecs" + val DRIVER_WAL_MAX_FAILURES_CONF_KEY = "spark.streaming.driver.writeAheadLog.maxFailures" + + val DEFAULT_ROLLING_INTERVAL_SECS = 60 + val DEFAULT_MAX_FAILURES = 3 + + def enableReceiverLog(conf: SparkConf): Boolean = { + conf.getBoolean(RECEIVER_WAL_ENABLE_CONF_KEY, false) + } + + def getRollingIntervalSecs(conf: SparkConf, isDriver: Boolean): Int = { + if (isDriver) { + conf.getInt(DRIVER_WAL_ROLLING_INTERVAL_CONF_KEY, DEFAULT_ROLLING_INTERVAL_SECS) + } else { + conf.getInt(RECEIVER_WAL_ROLLING_INTERVAL_CONF_KEY, DEFAULT_ROLLING_INTERVAL_SECS) + } + } + + def getMaxFailures(conf: SparkConf, isDriver: Boolean): Int = { + if (isDriver) { + conf.getInt(DRIVER_WAL_MAX_FAILURES_CONF_KEY, DEFAULT_MAX_FAILURES) + } else { + conf.getInt(RECEIVER_WAL_MAX_FAILURES_CONF_KEY, DEFAULT_MAX_FAILURES) + } + } + + /** + * Create a WriteAheadLog for the driver. If configured with custom WAL class, it will try + * to create instance of that class, otherwise it will create the default FileBasedWriteAheadLog. + */ + def createLogForDriver( + sparkConf: SparkConf, + fileWalLogDirectory: String, + fileWalHadoopConf: Configuration + ): WriteAheadLog = { + createLog(true, sparkConf, fileWalLogDirectory, fileWalHadoopConf) + } + + /** + * Create a WriteAheadLog for the receiver. If configured with custom WAL class, it will try + * to create instance of that class, otherwise it will create the default FileBasedWriteAheadLog. + */ + def createLogForReceiver( + sparkConf: SparkConf, + fileWalLogDirectory: String, + fileWalHadoopConf: Configuration + ): WriteAheadLog = { + createLog(false, sparkConf, fileWalLogDirectory, fileWalHadoopConf) + } + + /** + * Create a WriteAheadLog based on the value of the given config key. The config key is used + * to get the class name from the SparkConf. If the class is configured, it will try to + * create instance of that class by first trying `new CustomWAL(sparkConf, logDir)` then trying + * `new CustomWAL(sparkConf)`. If either fails, it will fail. If no class is configured, then + * it will create the default FileBasedWriteAheadLog. + */ + private def createLog( + isDriver: Boolean, + sparkConf: SparkConf, + fileWalLogDirectory: String, + fileWalHadoopConf: Configuration + ): WriteAheadLog = { + + val classNameOption = if (isDriver) { + sparkConf.getOption(DRIVER_WAL_CLASS_CONF_KEY) + } else { + sparkConf.getOption(RECEIVER_WAL_CLASS_CONF_KEY) + } + classNameOption.map { className => + try { + instantiateClass( + Utils.classForName(className).asInstanceOf[Class[_ <: WriteAheadLog]], sparkConf) + } catch { + case NonFatal(e) => + throw new SparkException(s"Could not create a write ahead log of class $className", e) + } + }.getOrElse { + new FileBasedWriteAheadLog(sparkConf, fileWalLogDirectory, fileWalHadoopConf, + getRollingIntervalSecs(sparkConf, isDriver), getMaxFailures(sparkConf, isDriver)) + } + } + + /** Instantiate the class, either using single arg constructor or zero arg constructor */ + private def instantiateClass(cls: Class[_ <: WriteAheadLog], conf: SparkConf): WriteAheadLog = { + try { + cls.getConstructor(classOf[SparkConf]).newInstance(conf) + } catch { + case nsme: NoSuchMethodException => + cls.getConstructor().newInstance() + } + } +} diff --git a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java index 90340753a4eed..b1adf881dd0f5 100644 --- a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java +++ b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java @@ -21,11 +21,13 @@ import java.lang.Iterable; import java.nio.charset.Charset; import java.util.*; +import java.util.concurrent.atomic.AtomicBoolean; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; + import scala.Tuple2; import org.junit.Assert; @@ -45,6 +47,7 @@ import org.apache.spark.storage.StorageLevel; import org.apache.spark.streaming.api.java.*; import org.apache.spark.util.Utils; +import org.apache.spark.SparkConf; // The test suite itself is Serializable so that anonymous Function implementations can be // serialized, as an alternative to converting these anonymous classes to static inner classes; @@ -929,7 +932,7 @@ public void testPairMap() { // Maps pair -> pair of different type public Tuple2 call(Tuple2 in) throws Exception { return in.swap(); } - }); + }); JavaTestUtils.attachTestOutputStream(reversed); List>> result = JavaTestUtils.runStreams(ssc, 2, 2); @@ -987,12 +990,12 @@ public void testPairMap2() { // Maps pair -> single JavaDStream> stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1); JavaPairDStream pairStream = JavaPairDStream.fromJavaDStream(stream); JavaDStream reversed = pairStream.map( - new Function, Integer>() { - @Override - public Integer call(Tuple2 in) throws Exception { - return in._2(); - } - }); + new Function, Integer>() { + @Override + public Integer call(Tuple2 in) throws Exception { + return in._2(); + } + }); JavaTestUtils.attachTestOutputStream(reversed); List> result = JavaTestUtils.runStreams(ssc, 2, 2); @@ -1123,7 +1126,7 @@ public void testCombineByKey() { JavaPairDStream combined = pairStream.combineByKey( new Function() { - @Override + @Override public Integer call(Integer i) throws Exception { return i; } @@ -1144,14 +1147,14 @@ public void testCountByValue() { Arrays.asList("hello")); List>> expected = Arrays.asList( - Arrays.asList( - new Tuple2("hello", 1L), - new Tuple2("world", 1L)), - Arrays.asList( - new Tuple2("hello", 1L), - new Tuple2("moon", 1L)), - Arrays.asList( - new Tuple2("hello", 1L))); + Arrays.asList( + new Tuple2("hello", 1L), + new Tuple2("world", 1L)), + Arrays.asList( + new Tuple2("hello", 1L), + new Tuple2("moon", 1L)), + Arrays.asList( + new Tuple2("hello", 1L))); JavaDStream stream = JavaTestUtils.attachTestInputStream(ssc, inputData, 1); JavaPairDStream counted = stream.countByValue(); @@ -1249,17 +1252,17 @@ public void testUpdateStateByKey() { JavaPairDStream updated = pairStream.updateStateByKey( new Function2, Optional, Optional>() { - @Override - public Optional call(List values, Optional state) { - int out = 0; - if (state.isPresent()) { - out = out + state.get(); - } - for (Integer v: values) { - out = out + v; + @Override + public Optional call(List values, Optional state) { + int out = 0; + if (state.isPresent()) { + out = out + state.get(); + } + for (Integer v : values) { + out = out + v; + } + return Optional.of(out); } - return Optional.of(out); - } }); JavaTestUtils.attachTestOutputStream(updated); List>> result = JavaTestUtils.runStreams(ssc, 3, 3); @@ -1292,17 +1295,17 @@ public void testUpdateStateByKeyWithInitial() { JavaPairDStream updated = pairStream.updateStateByKey( new Function2, Optional, Optional>() { - @Override - public Optional call(List values, Optional state) { - int out = 0; - if (state.isPresent()) { - out = out + state.get(); - } - for (Integer v: values) { - out = out + v; + @Override + public Optional call(List values, Optional state) { + int out = 0; + if (state.isPresent()) { + out = out + state.get(); + } + for (Integer v : values) { + out = out + v; + } + return Optional.of(out); } - return Optional.of(out); - } }, new HashPartitioner(1), initialRDD); JavaTestUtils.attachTestOutputStream(updated); List>> result = JavaTestUtils.runStreams(ssc, 3, 3); @@ -1328,7 +1331,7 @@ public void testReduceByKeyAndWindowWithInverse() { JavaPairDStream reduceWindowed = pairStream.reduceByKeyAndWindow(new IntegerSum(), new IntegerDifference(), - new Duration(2000), new Duration(1000)); + new Duration(2000), new Duration(1000)); JavaTestUtils.attachTestOutputStream(reduceWindowed); List>> result = JavaTestUtils.runStreams(ssc, 3, 3); @@ -1707,6 +1710,74 @@ public Integer call(String s) throws Exception { Utils.deleteRecursively(tempDir); } + @SuppressWarnings("unchecked") + @Test + public void testContextGetOrCreate() throws InterruptedException { + + final SparkConf conf = new SparkConf() + .setMaster("local[2]") + .setAppName("test") + .set("newContext", "true"); + + File emptyDir = Files.createTempDir(); + emptyDir.deleteOnExit(); + StreamingContextSuite contextSuite = new StreamingContextSuite(); + String corruptedCheckpointDir = contextSuite.createCorruptedCheckpoint(); + String checkpointDir = contextSuite.createValidCheckpoint(); + + // Function to create JavaStreamingContext without any output operations + // (used to detect the new context) + final AtomicBoolean newContextCreated = new AtomicBoolean(false); + Function0 creatingFunc = new Function0() { + public JavaStreamingContext call() { + newContextCreated.set(true); + return new JavaStreamingContext(conf, Seconds.apply(1)); + } + }; + + newContextCreated.set(false); + ssc = JavaStreamingContext.getOrCreate(emptyDir.getAbsolutePath(), creatingFunc); + Assert.assertTrue("new context not created", newContextCreated.get()); + ssc.stop(); + + newContextCreated.set(false); + ssc = JavaStreamingContext.getOrCreate(corruptedCheckpointDir, creatingFunc, + new org.apache.hadoop.conf.Configuration(), true); + Assert.assertTrue("new context not created", newContextCreated.get()); + ssc.stop(); + + newContextCreated.set(false); + ssc = JavaStreamingContext.getOrCreate(checkpointDir, creatingFunc, + new org.apache.hadoop.conf.Configuration()); + Assert.assertTrue("old context not recovered", !newContextCreated.get()); + ssc.stop(); + + // Function to create JavaStreamingContext using existing JavaSparkContext + // without any output operations (used to detect the new context) + Function creatingFunc2 = + new Function() { + public JavaStreamingContext call(JavaSparkContext context) { + newContextCreated.set(true); + return new JavaStreamingContext(context, Seconds.apply(1)); + } + }; + + JavaSparkContext sc = new JavaSparkContext(conf); + newContextCreated.set(false); + ssc = JavaStreamingContext.getOrCreate(emptyDir.getAbsolutePath(), creatingFunc2, sc); + Assert.assertTrue("new context not created", newContextCreated.get()); + ssc.stop(false); + + newContextCreated.set(false); + ssc = JavaStreamingContext.getOrCreate(corruptedCheckpointDir, creatingFunc2, sc, true); + Assert.assertTrue("new context not created", newContextCreated.get()); + ssc.stop(false); + + newContextCreated.set(false); + ssc = JavaStreamingContext.getOrCreate(checkpointDir, creatingFunc2, sc); + Assert.assertTrue("old context not recovered", !newContextCreated.get()); + ssc.stop(); + } /* TEST DISABLED: Pending a discussion about checkpoint() semantics with TD @SuppressWarnings("unchecked") diff --git a/streaming/src/test/java/org/apache/spark/streaming/JavaWriteAheadLogSuite.java b/streaming/src/test/java/org/apache/spark/streaming/JavaWriteAheadLogSuite.java new file mode 100644 index 0000000000000..50e8f9fc159c8 --- /dev/null +++ b/streaming/src/test/java/org/apache/spark/streaming/JavaWriteAheadLogSuite.java @@ -0,0 +1,129 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streaming; + +import java.util.ArrayList; +import java.nio.ByteBuffer; +import java.util.Arrays; +import java.util.Collection; + +import org.apache.commons.collections.CollectionUtils; +import org.apache.commons.collections.Transformer; +import org.apache.spark.SparkConf; +import org.apache.spark.streaming.util.WriteAheadLog; +import org.apache.spark.streaming.util.WriteAheadLogRecordHandle; +import org.apache.spark.streaming.util.WriteAheadLogUtils; + +import org.junit.Test; +import org.junit.Assert; + +class JavaWriteAheadLogSuiteHandle extends WriteAheadLogRecordHandle { + int index = -1; + public JavaWriteAheadLogSuiteHandle(int idx) { + index = idx; + } +} + +public class JavaWriteAheadLogSuite extends WriteAheadLog { + + class Record { + long time; + int index; + ByteBuffer buffer; + + public Record(long tym, int idx, ByteBuffer buf) { + index = idx; + time = tym; + buffer = buf; + } + } + private int index = -1; + private ArrayList records = new ArrayList(); + + + // Methods for WriteAheadLog + @Override + public WriteAheadLogRecordHandle write(java.nio.ByteBuffer record, long time) { + index += 1; + records.add(new org.apache.spark.streaming.JavaWriteAheadLogSuite.Record(time, index, record)); + return new JavaWriteAheadLogSuiteHandle(index); + } + + @Override + public java.nio.ByteBuffer read(WriteAheadLogRecordHandle handle) { + if (handle instanceof JavaWriteAheadLogSuiteHandle) { + int reqdIndex = ((JavaWriteAheadLogSuiteHandle) handle).index; + for (Record record: records) { + if (record.index == reqdIndex) { + return record.buffer; + } + } + } + return null; + } + + @Override + public java.util.Iterator readAll() { + Collection buffers = CollectionUtils.collect(records, new Transformer() { + @Override + public Object transform(Object input) { + return ((Record) input).buffer; + } + }); + return buffers.iterator(); + } + + @Override + public void clean(long threshTime, boolean waitForCompletion) { + for (int i = 0; i < records.size(); i++) { + if (records.get(i).time < threshTime) { + records.remove(i); + i--; + } + } + } + + @Override + public void close() { + records.clear(); + } + + @Test + public void testCustomWAL() { + SparkConf conf = new SparkConf(); + conf.set("spark.streaming.driver.writeAheadLog.class", JavaWriteAheadLogSuite.class.getName()); + WriteAheadLog wal = WriteAheadLogUtils.createLogForDriver(conf, null, null); + + String data1 = "data1"; + WriteAheadLogRecordHandle handle = wal.write(ByteBuffer.wrap(data1.getBytes()), 1234); + Assert.assertTrue(handle instanceof JavaWriteAheadLogSuiteHandle); + Assert.assertTrue(new String(wal.read(handle).array()).equals(data1)); + + wal.write(ByteBuffer.wrap("data2".getBytes()), 1235); + wal.write(ByteBuffer.wrap("data3".getBytes()), 1236); + wal.write(ByteBuffer.wrap("data4".getBytes()), 1237); + wal.clean(1236, false); + + java.util.Iterator dataIterator = wal.readAll(); + ArrayList readData = new ArrayList(); + while (dataIterator.hasNext()) { + readData.add(new String(dataIterator.next().array())); + } + Assert.assertTrue(readData.equals(Arrays.asList("data3", "data4"))); + } +} diff --git a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala index 54c30440a6e8d..6b0a3f91d4d06 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala @@ -430,9 +430,8 @@ class CheckpointSuite extends TestSuiteBase { assert(recordedFiles(ssc) === Seq(1, 2, 3) && batchCounter.getNumStartedBatches === 3) } // Wait for a checkpoint to be written - val fs = new Path(checkpointDir).getFileSystem(ssc.sc.hadoopConfiguration) eventually(eventuallyTimeout) { - assert(Checkpoint.getCheckpointFiles(checkpointDir, fs).size === 6) + assert(Checkpoint.getCheckpointFiles(checkpointDir).size === 6) } ssc.stop() // Check that we shut down while the third batch was being processed diff --git a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala index e6ac4975c5e68..eb136758249d5 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala @@ -27,17 +27,18 @@ import scala.collection.mutable.{SynchronizedBuffer, ArrayBuffer, SynchronizedQu import scala.language.postfixOps import com.google.common.io.Files +import org.apache.hadoop.io.{Text, LongWritable} +import org.apache.hadoop.mapreduce.lib.input.TextInputFormat +import org.apache.hadoop.fs.Path import org.scalatest.BeforeAndAfter import org.scalatest.concurrent.Eventually._ import org.apache.spark.Logging +import org.apache.spark.rdd.RDD import org.apache.spark.storage.StorageLevel import org.apache.spark.util.{ManualClock, Utils} +import org.apache.spark.streaming.dstream.{InputDStream, ReceiverInputDStream} import org.apache.spark.streaming.receiver.Receiver -import org.apache.spark.rdd.RDD -import org.apache.hadoop.io.{Text, LongWritable} -import org.apache.hadoop.mapreduce.lib.input.TextInputFormat -import org.apache.hadoop.fs.Path class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { @@ -278,6 +279,30 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter { } } + test("test track the number of input stream") { + val ssc = new StreamingContext(conf, batchDuration) + + class TestInputDStream extends InputDStream[String](ssc) { + def start() { } + def stop() { } + def compute(validTime: Time): Option[RDD[String]] = None + } + + class TestReceiverInputDStream extends ReceiverInputDStream[String](ssc) { + def getReceiver: Receiver[String] = null + } + + // Register input streams + val receiverInputStreams = Array(new TestReceiverInputDStream, new TestReceiverInputDStream) + val inputStreams = Array(new TestInputDStream, new TestInputDStream, new TestInputDStream) + + assert(ssc.graph.getInputStreams().length == receiverInputStreams.length + inputStreams.length) + assert(ssc.graph.getReceiverInputStreams().length == receiverInputStreams.length) + assert(ssc.graph.getReceiverInputStreams() === receiverInputStreams) + assert(ssc.graph.getInputStreams().map(_.id) === Array.tabulate(5)(i => i)) + assert(receiverInputStreams.map(_.id) === Array(0, 1)) + } + def testFileStream(newFilesOnly: Boolean) { val testDir: File = null try { diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala index c090eaec2928d..23804237bda80 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockHandlerSuite.scala @@ -43,7 +43,7 @@ import WriteAheadLogSuite._ class ReceivedBlockHandlerSuite extends FunSuite with BeforeAndAfter with Matchers with Logging { - val conf = new SparkConf().set("spark.streaming.receiver.writeAheadLog.rollingInterval", "1") + val conf = new SparkConf().set("spark.streaming.receiver.writeAheadLog.rollingIntervalSecs", "1") val hadoopConf = new Configuration() val storageLevel = StorageLevel.MEMORY_ONLY_SER val streamId = 1 @@ -130,10 +130,13 @@ class ReceivedBlockHandlerSuite extends FunSuite with BeforeAndAfter with Matche "Unexpected store result type" ) // Verify the data in write ahead log files is correct - val fileSegments = storeResults.map { _.asInstanceOf[WriteAheadLogBasedStoreResult].segment} - val loggedData = fileSegments.flatMap { segment => - val reader = new WriteAheadLogRandomReader(segment.path, hadoopConf) - val bytes = reader.read(segment) + val walSegments = storeResults.map { result => + result.asInstanceOf[WriteAheadLogBasedStoreResult].walRecordHandle + } + val loggedData = walSegments.flatMap { walSegment => + val fileSegment = walSegment.asInstanceOf[FileBasedWriteAheadLogSegment] + val reader = new FileBasedWriteAheadLogRandomReader(fileSegment.path, hadoopConf) + val bytes = reader.read(fileSegment) reader.close() blockManager.dataDeserialize(generateBlockId(), bytes).toList } @@ -148,13 +151,13 @@ class ReceivedBlockHandlerSuite extends FunSuite with BeforeAndAfter with Matche } } - test("WriteAheadLogBasedBlockHandler - cleanup old blocks") { + test("WriteAheadLogBasedBlockHandler - clean old blocks") { withWriteAheadLogBasedBlockHandler { handler => val blocks = Seq.tabulate(10) { i => IteratorBlock(Iterator(1 to i)) } storeBlocks(handler, blocks) val preCleanupLogFiles = getWriteAheadLogFiles() - preCleanupLogFiles.size should be > 1 + require(preCleanupLogFiles.size > 1) // this depends on the number of blocks inserted using generateAndStoreData() manualClock.getTimeMillis() shouldEqual 5000L @@ -218,6 +221,7 @@ class ReceivedBlockHandlerSuite extends FunSuite with BeforeAndAfter with Matche /** Instantiate a WriteAheadLogBasedBlockHandler and run a code with it */ private def withWriteAheadLogBasedBlockHandler(body: WriteAheadLogBasedBlockHandler => Unit) { + require(WriteAheadLogUtils.getRollingIntervalSecs(conf, isDriver = false) === 1) val receivedBlockHandler = new WriteAheadLogBasedBlockHandler(blockManager, 1, storageLevel, conf, hadoopConf, tempDirectory.toString, manualClock) try { diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala index b63b37d9f9cef..8317fb9720416 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceivedBlockTrackerSuite.scala @@ -32,7 +32,7 @@ import org.apache.spark.{Logging, SparkConf, SparkException} import org.apache.spark.storage.StreamBlockId import org.apache.spark.streaming.receiver.BlockManagerBasedStoreResult import org.apache.spark.streaming.scheduler._ -import org.apache.spark.streaming.util.WriteAheadLogReader +import org.apache.spark.streaming.util.{WriteAheadLogUtils, FileBasedWriteAheadLogReader} import org.apache.spark.streaming.util.WriteAheadLogSuite._ import org.apache.spark.util.{Clock, ManualClock, SystemClock, Utils} @@ -59,7 +59,7 @@ class ReceivedBlockTrackerSuite test("block addition, and block to batch allocation") { val receivedBlockTracker = createTracker(setCheckpointDir = false) - receivedBlockTracker.isLogManagerEnabled should be (false) // should be disable by default + receivedBlockTracker.isWriteAheadLogEnabled should be (false) // should be disable by default receivedBlockTracker.getUnallocatedBlocks(streamId) shouldEqual Seq.empty val blockInfos = generateBlockInfos() @@ -88,7 +88,7 @@ class ReceivedBlockTrackerSuite receivedBlockTracker.getUnallocatedBlocks(streamId) shouldEqual blockInfos } - test("block addition, block to batch allocation and cleanup with write ahead log") { + test("block addition, block to batch allocation and clean up with write ahead log") { val manualClock = new ManualClock // Set the time increment level to twice the rotation interval so that every increment creates // a new log file @@ -113,11 +113,15 @@ class ReceivedBlockTrackerSuite logInfo(s"\n\n=====================\n$message\n$fileContents\n=====================\n") } - // Start tracker and add blocks + // Set WAL configuration conf.set("spark.streaming.receiver.writeAheadLog.enable", "true") - conf.set("spark.streaming.receivedBlockTracker.writeAheadLog.rotationIntervalSecs", "1") + conf.set("spark.streaming.driver.writeAheadLog.rollingIntervalSecs", "1") + require(WriteAheadLogUtils.enableReceiverLog(conf)) + require(WriteAheadLogUtils.getRollingIntervalSecs(conf, isDriver = true) === 1) + + // Start tracker and add blocks val tracker1 = createTracker(clock = manualClock) - tracker1.isLogManagerEnabled should be (true) + tracker1.isWriteAheadLogEnabled should be (true) val blockInfos1 = addBlockInfos(tracker1) tracker1.getUnallocatedBlocks(streamId).toList shouldEqual blockInfos1 @@ -171,7 +175,7 @@ class ReceivedBlockTrackerSuite eventually(timeout(10 seconds), interval(10 millisecond)) { getWriteAheadLogFiles() should not contain oldestLogFile } - printLogFiles("After cleanup") + printLogFiles("After clean") // Restart tracker and verify recovered state, specifically whether info about the first // batch has been removed, but not the second batch @@ -192,17 +196,17 @@ class ReceivedBlockTrackerSuite test("setting checkpoint dir but not enabling write ahead log") { // When WAL config is not set, log manager should not be enabled val tracker1 = createTracker(setCheckpointDir = true) - tracker1.isLogManagerEnabled should be (false) + tracker1.isWriteAheadLogEnabled should be (false) // When WAL is explicitly disabled, log manager should not be enabled conf.set("spark.streaming.receiver.writeAheadLog.enable", "false") val tracker2 = createTracker(setCheckpointDir = true) - tracker2.isLogManagerEnabled should be(false) + tracker2.isWriteAheadLogEnabled should be(false) } /** * Create tracker object with the optional provided clock. Use fake clock if you - * want to control time by manually incrementing it to test log cleanup. + * want to control time by manually incrementing it to test log clean. */ def createTracker( setCheckpointDir: Boolean = true, @@ -231,7 +235,7 @@ class ReceivedBlockTrackerSuite def getWrittenLogData(logFiles: Seq[String] = getWriteAheadLogFiles) : Seq[ReceivedBlockTrackerLogEvent] = { logFiles.flatMap { - file => new WriteAheadLogReader(file, hadoopConf).toSeq + file => new FileBasedWriteAheadLogReader(file, hadoopConf).toSeq }.map { byteBuffer => Utils.deserialize[ReceivedBlockTrackerLogEvent](byteBuffer.array) }.toList @@ -250,7 +254,7 @@ class ReceivedBlockTrackerSuite BatchAllocationEvent(time, AllocatedBlocks(Map((streamId -> blockInfos)))) } - /** Create batch cleanup object from the given info */ + /** Create batch clean object from the given info */ def createBatchCleanup(time: Long, moreTimes: Long*): BatchCleanupEvent = { BatchCleanupEvent((Seq(time) ++ moreTimes).map(Time.apply)) } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala index b84129fd70dd4..393a360cfe150 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/ReceiverSuite.scala @@ -225,7 +225,7 @@ class ReceiverSuite extends TestSuiteBase with Timeouts with Serializable { .setAppName(framework) .set("spark.ui.enabled", "true") .set("spark.streaming.receiver.writeAheadLog.enable", "true") - .set("spark.streaming.receiver.writeAheadLog.rollingInterval", "1") + .set("spark.streaming.receiver.writeAheadLog.rollingIntervalSecs", "1") val batchDuration = Milliseconds(500) val tempDirectory = Utils.createTempDir() val logDirectory1 = new File(checkpointDirToLogDir(tempDirectory.getAbsolutePath, 0)) diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala index 58353a5f97c8a..5207b7109e69b 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingContextSuite.scala @@ -17,8 +17,10 @@ package org.apache.spark.streaming +import java.io.File import java.util.concurrent.atomic.AtomicInteger +import org.apache.commons.io.FileUtils import org.scalatest.{Assertions, BeforeAndAfter, FunSuite} import org.scalatest.concurrent.Timeouts import org.scalatest.concurrent.Eventually._ @@ -330,6 +332,139 @@ class StreamingContextSuite extends FunSuite with BeforeAndAfter with Timeouts w } } + test("getOrCreate") { + val conf = new SparkConf().setMaster(master).setAppName(appName) + + // Function to create StreamingContext that has a config to identify it to be new context + var newContextCreated = false + def creatingFunction(): StreamingContext = { + newContextCreated = true + new StreamingContext(conf, batchDuration) + } + + // Call ssc.stop after a body of code + def testGetOrCreate(body: => Unit): Unit = { + newContextCreated = false + try { + body + } finally { + if (ssc != null) { + ssc.stop() + } + ssc = null + } + } + + val emptyPath = Utils.createTempDir().getAbsolutePath() + + // getOrCreate should create new context with empty path + testGetOrCreate { + ssc = StreamingContext.getOrCreate(emptyPath, creatingFunction _) + assert(ssc != null, "no context created") + assert(newContextCreated, "new context not created") + } + + val corrutedCheckpointPath = createCorruptedCheckpoint() + + // getOrCreate should throw exception with fake checkpoint file and createOnError = false + intercept[Exception] { + ssc = StreamingContext.getOrCreate(corrutedCheckpointPath, creatingFunction _) + } + + // getOrCreate should throw exception with fake checkpoint file + intercept[Exception] { + ssc = StreamingContext.getOrCreate( + corrutedCheckpointPath, creatingFunction _, createOnError = false) + } + + // getOrCreate should create new context with fake checkpoint file and createOnError = true + testGetOrCreate { + ssc = StreamingContext.getOrCreate( + corrutedCheckpointPath, creatingFunction _, createOnError = true) + assert(ssc != null, "no context created") + assert(newContextCreated, "new context not created") + } + + val checkpointPath = createValidCheckpoint() + + // getOrCreate should recover context with checkpoint path, and recover old configuration + testGetOrCreate { + ssc = StreamingContext.getOrCreate(checkpointPath, creatingFunction _) + assert(ssc != null, "no context created") + assert(!newContextCreated, "old context not recovered") + assert(ssc.conf.get("someKey") === "someValue") + } + } + + test("getOrCreate with existing SparkContext") { + val conf = new SparkConf().setMaster(master).setAppName(appName) + sc = new SparkContext(conf) + + // Function to create StreamingContext that has a config to identify it to be new context + var newContextCreated = false + def creatingFunction(sparkContext: SparkContext): StreamingContext = { + newContextCreated = true + new StreamingContext(sparkContext, batchDuration) + } + + // Call ssc.stop(stopSparkContext = false) after a body of cody + def testGetOrCreate(body: => Unit): Unit = { + newContextCreated = false + try { + body + } finally { + if (ssc != null) { + ssc.stop(stopSparkContext = false) + } + ssc = null + } + } + + val emptyPath = Utils.createTempDir().getAbsolutePath() + + // getOrCreate should create new context with empty path + testGetOrCreate { + ssc = StreamingContext.getOrCreate(emptyPath, creatingFunction _, sc, createOnError = true) + assert(ssc != null, "no context created") + assert(newContextCreated, "new context not created") + assert(ssc.sparkContext === sc, "new StreamingContext does not use existing SparkContext") + } + + val corrutedCheckpointPath = createCorruptedCheckpoint() + + // getOrCreate should throw exception with fake checkpoint file and createOnError = false + intercept[Exception] { + ssc = StreamingContext.getOrCreate(corrutedCheckpointPath, creatingFunction _, sc) + } + + // getOrCreate should throw exception with fake checkpoint file + intercept[Exception] { + ssc = StreamingContext.getOrCreate( + corrutedCheckpointPath, creatingFunction _, sc, createOnError = false) + } + + // getOrCreate should create new context with fake checkpoint file and createOnError = true + testGetOrCreate { + ssc = StreamingContext.getOrCreate( + corrutedCheckpointPath, creatingFunction _, sc, createOnError = true) + assert(ssc != null, "no context created") + assert(newContextCreated, "new context not created") + assert(ssc.sparkContext === sc, "new StreamingContext does not use existing SparkContext") + } + + val checkpointPath = createValidCheckpoint() + + // StreamingContext.getOrCreate should recover context with checkpoint path + testGetOrCreate { + ssc = StreamingContext.getOrCreate(checkpointPath, creatingFunction _, sc) + assert(ssc != null, "no context created") + assert(!newContextCreated, "old context not recovered") + assert(ssc.sparkContext === sc, "new StreamingContext does not use existing SparkContext") + assert(!ssc.conf.contains("someKey"), + "recovered StreamingContext unexpectedly has old config") + } + } + test("DStream and generated RDD creation sites") { testPackage.test() } @@ -339,6 +474,30 @@ class StreamingContextSuite extends FunSuite with BeforeAndAfter with Timeouts w val inputStream = new TestInputStream(s, input, 1) inputStream } + + def createValidCheckpoint(): String = { + val testDirectory = Utils.createTempDir().getAbsolutePath() + val checkpointDirectory = Utils.createTempDir().getAbsolutePath() + val conf = new SparkConf().setMaster(master).setAppName(appName) + conf.set("someKey", "someValue") + ssc = new StreamingContext(conf, batchDuration) + ssc.checkpoint(checkpointDirectory) + ssc.textFileStream(testDirectory).foreachRDD { rdd => rdd.count() } + ssc.start() + eventually(timeout(10000 millis)) { + assert(Checkpoint.getCheckpointFiles(checkpointDirectory).size > 1) + } + ssc.stop() + checkpointDirectory + } + + def createCorruptedCheckpoint(): String = { + val checkpointDirectory = Utils.createTempDir().getAbsolutePath() + val fakeCheckpointFile = Checkpoint.checkpointFile(checkpointDirectory, Time(1000)) + FileUtils.write(new File(fakeCheckpointFile.toString()), "blablabla") + assert(Checkpoint.getCheckpointFiles(checkpointDirectory).nonEmpty) + checkpointDirectory + } } class TestException(msg: String) extends Exception(msg) @@ -363,7 +522,7 @@ class TestReceiver extends Receiver[Int](StorageLevel.MEMORY_ONLY) with Logging } def onStop() { - // no cleanup to be done, the receiving thread should stop on it own + // no clean to be done, the receiving thread should stop on it own } } @@ -396,7 +555,7 @@ class SlowTestReceiver(totalRecords: Int, recordsPerSecond: Int) def onStop() { // Simulate slow receiver by waiting for all records to be produced while(!SlowTestReceiver.receivedAllRecords) Thread.sleep(100) - // no cleanup to be done, the receiving thread should stop on it own + // no clean to be done, the receiving thread should stop on it own } } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala index 7210439509541..312cce408cfe7 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/StreamingListenerSuite.scala @@ -17,7 +17,7 @@ package org.apache.spark.streaming -import scala.collection.mutable.ArrayBuffer +import scala.collection.mutable.{ArrayBuffer, SynchronizedBuffer} import scala.concurrent.Future import scala.concurrent.ExecutionContext.Implicits.global @@ -57,6 +57,11 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers { info.totalDelay should be (None) }) + batchInfosSubmitted.foreach { info => + info.numRecords should be (1L) + info.streamIdToNumRecords should be (Map(0 -> 1L)) + } + isInIncreasingOrder(batchInfosSubmitted.map(_.submissionTime)) should be (true) // SPARK-6766: processingStartTime of batch info should not be None when starting @@ -70,6 +75,11 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers { info.totalDelay should be (None) }) + batchInfosStarted.foreach { info => + info.numRecords should be (1L) + info.streamIdToNumRecords should be (Map(0 -> 1L)) + } + isInIncreasingOrder(batchInfosStarted.map(_.submissionTime)) should be (true) isInIncreasingOrder(batchInfosStarted.map(_.processingStartTime.get)) should be (true) @@ -86,6 +96,11 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers { info.totalDelay.get should be >= 0L }) + batchInfosCompleted.foreach { info => + info.numRecords should be (1L) + info.streamIdToNumRecords should be (Map(0 -> 1L)) + } + isInIncreasingOrder(batchInfosCompleted.map(_.submissionTime)) should be (true) isInIncreasingOrder(batchInfosCompleted.map(_.processingStartTime.get)) should be (true) isInIncreasingOrder(batchInfosCompleted.map(_.processingEndTime.get)) should be (true) @@ -127,9 +142,9 @@ class StreamingListenerSuite extends TestSuiteBase with Matchers { /** Listener that collects information on processed batches */ class BatchInfoCollector extends StreamingListener { - val batchInfosCompleted = new ArrayBuffer[BatchInfo] - val batchInfosStarted = new ArrayBuffer[BatchInfo] - val batchInfosSubmitted = new ArrayBuffer[BatchInfo] + val batchInfosCompleted = new ArrayBuffer[BatchInfo] with SynchronizedBuffer[BatchInfo] + val batchInfosStarted = new ArrayBuffer[BatchInfo] with SynchronizedBuffer[BatchInfo] + val batchInfosSubmitted = new ArrayBuffer[BatchInfo] with SynchronizedBuffer[BatchInfo] override def onBatchSubmitted(batchSubmitted: StreamingListenerBatchSubmitted) { batchInfosSubmitted += batchSubmitted.batchInfo @@ -146,9 +161,10 @@ class BatchInfoCollector extends StreamingListener { /** Listener that collects information on processed batches */ class ReceiverInfoCollector extends StreamingListener { - val startedReceiverStreamIds = new ArrayBuffer[Int] - val stoppedReceiverStreamIds = new ArrayBuffer[Int]() - val receiverErrors = new ArrayBuffer[(Int, String, String)]() + val startedReceiverStreamIds = new ArrayBuffer[Int] with SynchronizedBuffer[Int] + val stoppedReceiverStreamIds = new ArrayBuffer[Int] with SynchronizedBuffer[Int] + val receiverErrors = + new ArrayBuffer[(Int, String, String)] with SynchronizedBuffer[(Int, String, String)] override def onReceiverStarted(receiverStarted: StreamingListenerReceiverStarted) { startedReceiverStreamIds += receiverStarted.receiverInfo.streamId diff --git a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala index c3cae8aeb6d15..2ba86aeaf9d51 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/TestSuiteBase.scala @@ -29,10 +29,10 @@ import org.scalatest.time.{Span, Seconds => ScalaTestSeconds} import org.scalatest.concurrent.Eventually.timeout import org.scalatest.concurrent.PatienceConfiguration -import org.apache.spark.streaming.dstream.{DStream, InputDStream, ForEachDStream} -import org.apache.spark.streaming.scheduler.{StreamingListenerBatchStarted, StreamingListenerBatchCompleted, StreamingListener} import org.apache.spark.{SparkConf, Logging} import org.apache.spark.rdd.RDD +import org.apache.spark.streaming.dstream.{DStream, InputDStream, ForEachDStream} +import org.apache.spark.streaming.scheduler._ import org.apache.spark.util.{ManualClock, Utils} /** @@ -57,6 +57,10 @@ class TestInputStream[T: ClassTag](ssc_ : StreamingContext, input: Seq[Seq[T]], return None } + // Report the input data's information to InputInfoTracker for testing + val inputInfo = InputInfo(id, selectedInput.length.toLong) + ssc.scheduler.inputInfoTracker.reportInfo(validTime, inputInfo) + val rdd = ssc.sc.makeRDD(selectedInput, numPartitions) logInfo("Created RDD " + rdd.id + " with " + selectedInput) Some(rdd) diff --git a/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala index 205ddf6dbe9b0..8de43baabc21d 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/UISeleniumSuite.scala @@ -17,6 +17,8 @@ package org.apache.spark.streaming +import scala.collection.mutable.Queue + import org.openqa.selenium.WebDriver import org.openqa.selenium.htmlunit.HtmlUnitDriver import org.scalatest._ @@ -60,8 +62,28 @@ class UISeleniumSuite ssc } + private def setupStreams(ssc: StreamingContext): Unit = { + val rdds = Queue(ssc.sc.parallelize(1 to 4, 4)) + val inputStream = ssc.queueStream(rdds) + inputStream.foreachRDD { rdd => + rdd.foreach(_ => {}) + rdd.foreach(_ => {}) + } + inputStream.foreachRDD { rdd => + rdd.foreach(_ => {}) + try { + rdd.foreach(_ => throw new RuntimeException("Oops")) + } catch { + case e: SparkException if e.getMessage.contains("Oops") => + } + } + } + test("attaching and detaching a Streaming tab") { withStreamingContext(newSparkStreamingContext()) { ssc => + setupStreams(ssc) + ssc.start() + val sparkUI = ssc.sparkContext.ui.get eventually(timeout(10 seconds), interval(50 milliseconds)) { @@ -77,8 +99,8 @@ class UISeleniumSuite statisticText should contain("Batch interval:") val h4Text = findAll(cssSelector("h4")).map(_.text).toSeq - h4Text should contain("Active Batches (0)") - h4Text should contain("Completed Batches (last 0 out of 0)") + h4Text.exists(_.matches("Active Batches \\(\\d+\\)")) should be (true) + h4Text.exists(_.matches("Completed Batches \\(last \\d+ out of \\d+\\)")) should be (true) findAll(cssSelector("""#active-batches-table th""")).map(_.text).toSeq should be { List("Batch Time", "Input Size", "Scheduling Delay", "Processing Time", "Status") @@ -86,6 +108,63 @@ class UISeleniumSuite findAll(cssSelector("""#completed-batches-table th""")).map(_.text).toSeq should be { List("Batch Time", "Input Size", "Scheduling Delay", "Processing Time", "Total Delay") } + + val batchLinks = + findAll(cssSelector("""#completed-batches-table a""")).flatMap(_.attribute("href")).toSeq + batchLinks.size should be >= 1 + + // Check a normal batch page + go to (batchLinks.last) // Last should be the first batch, so it will have some jobs + val summaryText = findAll(cssSelector("li strong")).map(_.text).toSeq + summaryText should contain ("Batch Duration:") + summaryText should contain ("Input data size:") + summaryText should contain ("Scheduling delay:") + summaryText should contain ("Processing time:") + summaryText should contain ("Total delay:") + + findAll(cssSelector("""#batch-job-table th""")).map(_.text).toSeq should be { + List("Output Op Id", "Description", "Duration", "Job Id", "Duration", + "Stages: Succeeded/Total", "Tasks (for all stages): Succeeded/Total", "Error") + } + + // Check we have 2 output op ids + val outputOpIds = findAll(cssSelector(".output-op-id-cell")).toSeq + outputOpIds.map(_.attribute("rowspan")) should be (List(Some("2"), Some("2"))) + outputOpIds.map(_.text) should be (List("0", "1")) + + // Check job ids + val jobIdCells = findAll(cssSelector( """#batch-job-table a""")).toSeq + jobIdCells.map(_.text) should be (List("0", "1", "2", "3")) + + val jobLinks = jobIdCells.flatMap(_.attribute("href")) + jobLinks.size should be (4) + + // Check stage progress + findAll(cssSelector(""".stage-progress-cell""")).map(_.text).toSeq should be + (List("1/1", "1/1", "1/1", "0/1 (1 failed)")) + + // Check job progress + findAll(cssSelector(""".progress-cell""")).map(_.text).toSeq should be + (List("1/1", "1/1", "1/1", "0/1 (1 failed)")) + + // Check stacktrace + val errorCells = findAll(cssSelector(""".stacktrace-details""")).map(_.text).toSeq + errorCells should have size 1 + errorCells(0) should include("java.lang.RuntimeException: Oops") + + // Check the job link in the batch page is right + go to (jobLinks(0)) + val jobDetails = findAll(cssSelector("li strong")).map(_.text).toSeq + jobDetails should contain("Status:") + jobDetails should contain("Completed Stages:") + + // Check a batch page without id + go to (sparkUI.appUIAddress.stripSuffix("/") + "/streaming/batch/") + webDriver.getPageSource should include ("Missing id parameter") + + // Check a non-exist batch + go to (sparkUI.appUIAddress.stripSuffix("/") + "/streaming/batch/?id=12345") + webDriver.getPageSource should include ("does not exist") } ssc.stop(false) diff --git a/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala index c3602a5b73732..8b300d8dd3fbe 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/rdd/WriteAheadLogBackedBlockRDDSuite.scala @@ -21,12 +21,12 @@ import java.io.File import scala.util.Random import org.apache.hadoop.conf.Configuration -import org.scalatest.{BeforeAndAfterEach, BeforeAndAfterAll, FunSuite} +import org.scalatest.{BeforeAndAfterAll, BeforeAndAfterEach, FunSuite} -import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.storage.{BlockId, BlockManager, StorageLevel, StreamBlockId} -import org.apache.spark.streaming.util.{WriteAheadLogFileSegment, WriteAheadLogWriter} +import org.apache.spark.streaming.util.{FileBasedWriteAheadLogSegment, FileBasedWriteAheadLogWriter} import org.apache.spark.util.Utils +import org.apache.spark.{SparkConf, SparkContext} class WriteAheadLogBackedBlockRDDSuite extends FunSuite with BeforeAndAfterAll with BeforeAndAfterEach { @@ -100,9 +100,10 @@ class WriteAheadLogBackedBlockRDDSuite blockManager.putIterator(blockId, block.iterator, StorageLevel.MEMORY_ONLY_SER) } - // Generate write ahead log segments - val segments = generateFakeSegments(numPartitionsInBM) ++ - writeLogSegments(data.takeRight(numPartitionsInWAL), blockIds.takeRight(numPartitionsInWAL)) + // Generate write ahead log file segments + val recordHandles = generateFakeRecordHandles(numPartitionsInBM) ++ + generateWALRecordHandles(data.takeRight(numPartitionsInWAL), + blockIds.takeRight(numPartitionsInWAL)) // Make sure that the left `numPartitionsInBM` blocks are in block manager, and others are not require( @@ -116,24 +117,24 @@ class WriteAheadLogBackedBlockRDDSuite // Make sure that the right `numPartitionsInWAL` blocks are in WALs, and other are not require( - segments.takeRight(numPartitionsInWAL).forall(s => + recordHandles.takeRight(numPartitionsInWAL).forall(s => new File(s.path.stripPrefix("file://")).exists()), "Expected blocks not in write ahead log" ) require( - segments.take(numPartitionsInBM).forall(s => + recordHandles.take(numPartitionsInBM).forall(s => !new File(s.path.stripPrefix("file://")).exists()), "Unexpected blocks in write ahead log" ) // Create the RDD and verify whether the returned data is correct val rdd = new WriteAheadLogBackedBlockRDD[String](sparkContext, blockIds.toArray, - segments.toArray, storeInBlockManager = false, StorageLevel.MEMORY_ONLY) + recordHandles.toArray, storeInBlockManager = false, StorageLevel.MEMORY_ONLY) assert(rdd.collect() === data.flatten) if (testStoreInBM) { val rdd2 = new WriteAheadLogBackedBlockRDD[String](sparkContext, blockIds.toArray, - segments.toArray, storeInBlockManager = true, StorageLevel.MEMORY_ONLY) + recordHandles.toArray, storeInBlockManager = true, StorageLevel.MEMORY_ONLY) assert(rdd2.collect() === data.flatten) assert( blockIds.forall(blockManager.get(_).nonEmpty), @@ -142,12 +143,12 @@ class WriteAheadLogBackedBlockRDDSuite } } - private def writeLogSegments( + private def generateWALRecordHandles( blockData: Seq[Seq[String]], blockIds: Seq[BlockId] - ): Seq[WriteAheadLogFileSegment] = { + ): Seq[FileBasedWriteAheadLogSegment] = { require(blockData.size === blockIds.size) - val writer = new WriteAheadLogWriter(new File(dir, "logFile").toString, hadoopConf) + val writer = new FileBasedWriteAheadLogWriter(new File(dir, "logFile").toString, hadoopConf) val segments = blockData.zip(blockIds).map { case (data, id) => writer.write(blockManager.dataSerialize(id, data.iterator)) } @@ -155,7 +156,7 @@ class WriteAheadLogBackedBlockRDDSuite segments } - private def generateFakeSegments(count: Int): Seq[WriteAheadLogFileSegment] = { - Array.fill(count)(new WriteAheadLogFileSegment("random", 0L, 0)) + private def generateFakeRecordHandles(count: Int): Seq[FileBasedWriteAheadLogSegment] = { + Array.fill(count)(new FileBasedWriteAheadLogSegment("random", 0L, 0)) } } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/scheduler/InputInfoTrackerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/scheduler/InputInfoTrackerSuite.scala new file mode 100644 index 0000000000000..5478b41845943 --- /dev/null +++ b/streaming/src/test/scala/org/apache/spark/streaming/scheduler/InputInfoTrackerSuite.scala @@ -0,0 +1,79 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.streaming.scheduler + +import org.scalatest.{BeforeAndAfter, FunSuite} + +import org.apache.spark.SparkConf +import org.apache.spark.streaming.{Time, Duration, StreamingContext} + +class InputInfoTrackerSuite extends FunSuite with BeforeAndAfter { + + private var ssc: StreamingContext = _ + + before { + val conf = new SparkConf().setMaster("local[2]").setAppName("DirectStreamTacker") + if (ssc == null) { + ssc = new StreamingContext(conf, Duration(1000)) + } + } + + after { + if (ssc != null) { + ssc.stop() + ssc = null + } + } + + test("test report and get InputInfo from InputInfoTracker") { + val inputInfoTracker = new InputInfoTracker(ssc) + + val streamId1 = 0 + val streamId2 = 1 + val time = Time(0L) + val inputInfo1 = InputInfo(streamId1, 100L) + val inputInfo2 = InputInfo(streamId2, 300L) + inputInfoTracker.reportInfo(time, inputInfo1) + inputInfoTracker.reportInfo(time, inputInfo2) + + val batchTimeToInputInfos = inputInfoTracker.getInfo(time) + assert(batchTimeToInputInfos.size == 2) + assert(batchTimeToInputInfos.keys === Set(streamId1, streamId2)) + assert(batchTimeToInputInfos(streamId1) === inputInfo1) + assert(batchTimeToInputInfos(streamId2) === inputInfo2) + assert(inputInfoTracker.getInfo(time)(streamId1) === inputInfo1) + } + + test("test cleanup InputInfo from InputInfoTracker") { + val inputInfoTracker = new InputInfoTracker(ssc) + + val streamId1 = 0 + val inputInfo1 = InputInfo(streamId1, 100L) + val inputInfo2 = InputInfo(streamId1, 300L) + inputInfoTracker.reportInfo(Time(0), inputInfo1) + inputInfoTracker.reportInfo(Time(1), inputInfo2) + + inputInfoTracker.cleanup(Time(0)) + assert(inputInfoTracker.getInfo(Time(0))(streamId1) === inputInfo1) + assert(inputInfoTracker.getInfo(Time(1))(streamId1) === inputInfo2) + + inputInfoTracker.cleanup(Time(1)) + assert(inputInfoTracker.getInfo(Time(0)).get(streamId1) === None) + assert(inputInfoTracker.getInfo(Time(1))(streamId1) === inputInfo2) + } +} diff --git a/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala index 94b1985116feb..e874536e63518 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/ui/StreamingJobProgressListenerSuite.scala @@ -17,8 +17,11 @@ package org.apache.spark.streaming.ui +import java.util.Properties + import org.scalatest.Matchers +import org.apache.spark.scheduler.SparkListenerJobStart import org.apache.spark.streaming.dstream.DStream import org.apache.spark.streaming.scheduler._ import org.apache.spark.streaming.{Duration, Time, Milliseconds, TestSuiteBase} @@ -28,6 +31,17 @@ class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers { val input = (1 to 4).map(Seq(_)).toSeq val operation = (d: DStream[Int]) => d.map(x => x) + private def createJobStart( + batchTime: Time, outputOpId: Int, jobId: Int): SparkListenerJobStart = { + val properties = new Properties() + properties.setProperty(JobScheduler.BATCH_TIME_PROPERTY_KEY, batchTime.milliseconds.toString) + properties.setProperty(JobScheduler.OUTPUT_OP_ID_PROPERTY_KEY, outputOpId.toString) + SparkListenerJobStart(jobId = jobId, + 0L, // unused + Nil, // unused + properties) + } + override def batchDuration: Duration = Milliseconds(100) test("onBatchSubmitted, onBatchStarted, onBatchCompleted, " + @@ -35,15 +49,12 @@ class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers { val ssc = setupStreams(input, operation) val listener = new StreamingJobProgressListener(ssc) - val receivedBlockInfo = Map( - 0 -> Array(ReceivedBlockInfo(0, 100, null), ReceivedBlockInfo(0, 200, null)), - 1 -> Array(ReceivedBlockInfo(1, 300, null)) - ) + val streamIdToNumRecords = Map(0 -> 300L, 1 -> 300L) // onBatchSubmitted - val batchInfoSubmitted = BatchInfo(Time(1000), receivedBlockInfo, 1000, None, None) + val batchInfoSubmitted = BatchInfo(Time(1000), streamIdToNumRecords, 1000, None, None) listener.onBatchSubmitted(StreamingListenerBatchSubmitted(batchInfoSubmitted)) - listener.waitingBatches should be (List(batchInfoSubmitted)) + listener.waitingBatches should be (List(BatchUIData(batchInfoSubmitted))) listener.runningBatches should be (Nil) listener.retainedCompletedBatches should be (Nil) listener.lastCompletedBatch should be (None) @@ -53,10 +64,10 @@ class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers { listener.numTotalReceivedRecords should be (0) // onBatchStarted - val batchInfoStarted = BatchInfo(Time(1000), receivedBlockInfo, 1000, Some(2000), None) + val batchInfoStarted = BatchInfo(Time(1000), streamIdToNumRecords, 1000, Some(2000), None) listener.onBatchStarted(StreamingListenerBatchStarted(batchInfoStarted)) listener.waitingBatches should be (Nil) - listener.runningBatches should be (List(batchInfoStarted)) + listener.runningBatches should be (List(BatchUIData(batchInfoStarted))) listener.retainedCompletedBatches should be (Nil) listener.lastCompletedBatch should be (None) listener.numUnprocessedBatches should be (1) @@ -64,13 +75,40 @@ class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers { listener.numTotalProcessedRecords should be (0) listener.numTotalReceivedRecords should be (600) + // onJobStart + val jobStart1 = createJobStart(Time(1000), outputOpId = 0, jobId = 0) + listener.onJobStart(jobStart1) + + val jobStart2 = createJobStart(Time(1000), outputOpId = 0, jobId = 1) + listener.onJobStart(jobStart2) + + val jobStart3 = createJobStart(Time(1000), outputOpId = 1, jobId = 0) + listener.onJobStart(jobStart3) + + val jobStart4 = createJobStart(Time(1000), outputOpId = 1, jobId = 1) + listener.onJobStart(jobStart4) + + val batchUIData = listener.getBatchUIData(Time(1000)) + batchUIData should not be None + batchUIData.get.batchTime should be (batchInfoStarted.batchTime) + batchUIData.get.schedulingDelay should be (batchInfoStarted.schedulingDelay) + batchUIData.get.processingDelay should be (batchInfoStarted.processingDelay) + batchUIData.get.totalDelay should be (batchInfoStarted.totalDelay) + batchUIData.get.receiverNumRecords should be (Map(0 -> 300L, 1 -> 300L)) + batchUIData.get.numRecords should be(600) + batchUIData.get.outputOpIdSparkJobIdPairs should be + Seq(OutputOpIdAndSparkJobId(0, 0), + OutputOpIdAndSparkJobId(0, 1), + OutputOpIdAndSparkJobId(1, 0), + OutputOpIdAndSparkJobId(1, 1)) + // onBatchCompleted - val batchInfoCompleted = BatchInfo(Time(1000), receivedBlockInfo, 1000, Some(2000), None) + val batchInfoCompleted = BatchInfo(Time(1000), streamIdToNumRecords, 1000, Some(2000), None) listener.onBatchCompleted(StreamingListenerBatchCompleted(batchInfoCompleted)) listener.waitingBatches should be (Nil) listener.runningBatches should be (Nil) - listener.retainedCompletedBatches should be (List(batchInfoCompleted)) - listener.lastCompletedBatch should be (Some(batchInfoCompleted)) + listener.retainedCompletedBatches should be (List(BatchUIData(batchInfoCompleted))) + listener.lastCompletedBatch should be (Some(BatchUIData(batchInfoCompleted))) listener.numUnprocessedBatches should be (0) listener.numTotalCompletedBatches should be (1) listener.numTotalProcessedRecords should be (600) @@ -103,11 +141,9 @@ class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers { val limit = ssc.conf.getInt("spark.streaming.ui.retainedBatches", 100) val listener = new StreamingJobProgressListener(ssc) - val receivedBlockInfo = Map( - 0 -> Array(ReceivedBlockInfo(0, 100, null), ReceivedBlockInfo(0, 200, null)), - 1 -> Array(ReceivedBlockInfo(1, 300, null)) - ) - val batchInfoCompleted = BatchInfo(Time(1000), receivedBlockInfo, 1000, Some(2000), None) + val streamIdToNumRecords = Map(0 -> 300L, 1 -> 300L) + + val batchInfoCompleted = BatchInfo(Time(1000), streamIdToNumRecords, 1000, Some(2000), None) for(_ <- 0 until (limit + 10)) { listener.onBatchCompleted(StreamingListenerBatchCompleted(batchInfoCompleted)) @@ -116,4 +152,55 @@ class StreamingJobProgressListenerSuite extends TestSuiteBase with Matchers { listener.retainedCompletedBatches.size should be (limit) listener.numTotalCompletedBatches should be(limit + 10) } + + test("out-of-order onJobStart and onBatchXXX") { + val ssc = setupStreams(input, operation) + val limit = ssc.conf.getInt("spark.streaming.ui.retainedBatches", 100) + val listener = new StreamingJobProgressListener(ssc) + + // fulfill completedBatchInfos + for(i <- 0 until limit) { + val batchInfoCompleted = + BatchInfo(Time(1000 + i * 100), Map.empty, 1000 + i * 100, Some(2000 + i * 100), None) + listener.onBatchCompleted(StreamingListenerBatchCompleted(batchInfoCompleted)) + val jobStart = createJobStart(Time(1000 + i * 100), outputOpId = 0, jobId = 1) + listener.onJobStart(jobStart) + } + + // onJobStart happens before onBatchSubmitted + val jobStart = createJobStart(Time(1000 + limit * 100), outputOpId = 0, jobId = 0) + listener.onJobStart(jobStart) + + val batchInfoSubmitted = + BatchInfo(Time(1000 + limit * 100), Map.empty, (1000 + limit * 100), None, None) + listener.onBatchSubmitted(StreamingListenerBatchSubmitted(batchInfoSubmitted)) + + // We still can see the info retrieved from onJobStart + val batchUIData = listener.getBatchUIData(Time(1000 + limit * 100)) + batchUIData should not be None + batchUIData.get.batchTime should be (batchInfoSubmitted.batchTime) + batchUIData.get.schedulingDelay should be (batchInfoSubmitted.schedulingDelay) + batchUIData.get.processingDelay should be (batchInfoSubmitted.processingDelay) + batchUIData.get.totalDelay should be (batchInfoSubmitted.totalDelay) + batchUIData.get.receiverNumRecords should be (Map.empty) + batchUIData.get.numRecords should be (0) + batchUIData.get.outputOpIdSparkJobIdPairs should be (Seq(OutputOpIdAndSparkJobId(0, 0))) + + // A lot of "onBatchCompleted"s happen before "onJobStart" + for(i <- limit + 1 to limit * 2) { + val batchInfoCompleted = + BatchInfo(Time(1000 + i * 100), Map.empty, 1000 + i * 100, Some(2000 + i * 100), None) + listener.onBatchCompleted(StreamingListenerBatchCompleted(batchInfoCompleted)) + } + + for(i <- limit + 1 to limit * 2) { + val jobStart = createJobStart(Time(1000 + i * 100), outputOpId = 0, jobId = 1) + listener.onJobStart(jobStart) + } + + // We should not leak memory + listener.batchTimeToOutputOpIdSparkJobIdPair.size() should be <= + (listener.waitingBatches.size + listener.runningBatches.size + + listener.retainedCompletedBatches.size + 10) + } } diff --git a/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala index a3919c43b95b4..79098bcf4861c 100644 --- a/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala +++ b/streaming/src/test/scala/org/apache/spark/streaming/util/WriteAheadLogSuite.scala @@ -18,33 +18,38 @@ package org.apache.spark.streaming.util import java.io._ import java.nio.ByteBuffer +import java.util import scala.collection.mutable.ArrayBuffer import scala.concurrent.duration._ import scala.language.{implicitConversions, postfixOps} +import scala.reflect.ClassTag -import WriteAheadLogSuite._ import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.Path -import org.apache.spark.util.{ManualClock, Utils} -import org.scalatest.{BeforeAndAfter, FunSuite} import org.scalatest.concurrent.Eventually._ +import org.scalatest.{BeforeAndAfter, FunSuite} + +import org.apache.spark.util.{ManualClock, Utils} +import org.apache.spark.{SparkConf, SparkException} class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { + import WriteAheadLogSuite._ + val hadoopConf = new Configuration() var tempDir: File = null var testDir: String = null var testFile: String = null - var manager: WriteAheadLogManager = null + var writeAheadLog: FileBasedWriteAheadLog = null before { tempDir = Utils.createTempDir() testDir = tempDir.toString testFile = new File(tempDir, "testFile").toString - if (manager != null) { - manager.stop() - manager = null + if (writeAheadLog != null) { + writeAheadLog.close() + writeAheadLog = null } } @@ -52,16 +57,60 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { Utils.deleteRecursively(tempDir) } - test("WriteAheadLogWriter - writing data") { + test("WriteAheadLogUtils - log selection and creation") { + val logDir = Utils.createTempDir().getAbsolutePath() + + def assertDriverLogClass[T <: WriteAheadLog: ClassTag](conf: SparkConf): WriteAheadLog = { + val log = WriteAheadLogUtils.createLogForDriver(conf, logDir, hadoopConf) + assert(log.getClass === implicitly[ClassTag[T]].runtimeClass) + log + } + + def assertReceiverLogClass[T: ClassTag](conf: SparkConf): WriteAheadLog = { + val log = WriteAheadLogUtils.createLogForReceiver(conf, logDir, hadoopConf) + assert(log.getClass === implicitly[ClassTag[T]].runtimeClass) + log + } + + val emptyConf = new SparkConf() // no log configuration + assertDriverLogClass[FileBasedWriteAheadLog](emptyConf) + assertReceiverLogClass[FileBasedWriteAheadLog](emptyConf) + + // Verify setting driver WAL class + val conf1 = new SparkConf().set("spark.streaming.driver.writeAheadLog.class", + classOf[MockWriteAheadLog0].getName()) + assertDriverLogClass[MockWriteAheadLog0](conf1) + assertReceiverLogClass[FileBasedWriteAheadLog](conf1) + + // Verify setting receiver WAL class + val receiverWALConf = new SparkConf().set("spark.streaming.receiver.writeAheadLog.class", + classOf[MockWriteAheadLog0].getName()) + assertDriverLogClass[FileBasedWriteAheadLog](receiverWALConf) + assertReceiverLogClass[MockWriteAheadLog0](receiverWALConf) + + // Verify setting receiver WAL class with 1-arg constructor + val receiverWALConf2 = new SparkConf().set("spark.streaming.receiver.writeAheadLog.class", + classOf[MockWriteAheadLog1].getName()) + assertReceiverLogClass[MockWriteAheadLog1](receiverWALConf2) + + // Verify failure setting receiver WAL class with 2-arg constructor + intercept[SparkException] { + val receiverWALConf3 = new SparkConf().set("spark.streaming.receiver.writeAheadLog.class", + classOf[MockWriteAheadLog2].getName()) + assertReceiverLogClass[MockWriteAheadLog1](receiverWALConf3) + } + } + + test("FileBasedWriteAheadLogWriter - writing data") { val dataToWrite = generateRandomData() val segments = writeDataUsingWriter(testFile, dataToWrite) val writtenData = readDataManually(segments) assert(writtenData === dataToWrite) } - test("WriteAheadLogWriter - syncing of data by writing and reading immediately") { + test("FileBasedWriteAheadLogWriter - syncing of data by writing and reading immediately") { val dataToWrite = generateRandomData() - val writer = new WriteAheadLogWriter(testFile, hadoopConf) + val writer = new FileBasedWriteAheadLogWriter(testFile, hadoopConf) dataToWrite.foreach { data => val segment = writer.write(stringToByteBuffer(data)) val dataRead = readDataManually(Seq(segment)).head @@ -70,10 +119,10 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { writer.close() } - test("WriteAheadLogReader - sequentially reading data") { + test("FileBasedWriteAheadLogReader - sequentially reading data") { val writtenData = generateRandomData() writeDataManually(writtenData, testFile) - val reader = new WriteAheadLogReader(testFile, hadoopConf) + val reader = new FileBasedWriteAheadLogReader(testFile, hadoopConf) val readData = reader.toSeq.map(byteBufferToString) assert(readData === writtenData) assert(reader.hasNext === false) @@ -83,14 +132,14 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { reader.close() } - test("WriteAheadLogReader - sequentially reading data written with writer") { + test("FileBasedWriteAheadLogReader - sequentially reading data written with writer") { val dataToWrite = generateRandomData() writeDataUsingWriter(testFile, dataToWrite) val readData = readDataUsingReader(testFile) assert(readData === dataToWrite) } - test("WriteAheadLogReader - reading data written with writer after corrupted write") { + test("FileBasedWriteAheadLogReader - reading data written with writer after corrupted write") { // Write data manually for testing the sequential reader val dataToWrite = generateRandomData() writeDataUsingWriter(testFile, dataToWrite) @@ -113,38 +162,38 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { assert(readDataUsingReader(testFile) === (dataToWrite.dropRight(1))) } - test("WriteAheadLogRandomReader - reading data using random reader") { + test("FileBasedWriteAheadLogRandomReader - reading data using random reader") { // Write data manually for testing the random reader val writtenData = generateRandomData() val segments = writeDataManually(writtenData, testFile) // Get a random order of these segments and read them back val writtenDataAndSegments = writtenData.zip(segments).toSeq.permutations.take(10).flatten - val reader = new WriteAheadLogRandomReader(testFile, hadoopConf) + val reader = new FileBasedWriteAheadLogRandomReader(testFile, hadoopConf) writtenDataAndSegments.foreach { case (data, segment) => assert(data === byteBufferToString(reader.read(segment))) } reader.close() } - test("WriteAheadLogRandomReader - reading data using random reader written with writer") { + test("FileBasedWriteAheadLogRandomReader- reading data using random reader written with writer") { // Write data using writer for testing the random reader val data = generateRandomData() val segments = writeDataUsingWriter(testFile, data) // Read a random sequence of segments and verify read data val dataAndSegments = data.zip(segments).toSeq.permutations.take(10).flatten - val reader = new WriteAheadLogRandomReader(testFile, hadoopConf) + val reader = new FileBasedWriteAheadLogRandomReader(testFile, hadoopConf) dataAndSegments.foreach { case (data, segment) => assert(data === byteBufferToString(reader.read(segment))) } reader.close() } - test("WriteAheadLogManager - write rotating logs") { - // Write data using manager + test("FileBasedWriteAheadLog - write rotating logs") { + // Write data with rotation using WriteAheadLog class val dataToWrite = generateRandomData() - writeDataUsingManager(testDir, dataToWrite) + writeDataUsingWriteAheadLog(testDir, dataToWrite) // Read data manually to verify the written data val logFiles = getLogFilesInDirectory(testDir) @@ -153,8 +202,8 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { assert(writtenData === dataToWrite) } - test("WriteAheadLogManager - read rotating logs") { - // Write data manually for testing reading through manager + test("FileBasedWriteAheadLog - read rotating logs") { + // Write data manually for testing reading through WriteAheadLog val writtenData = (1 to 10).map { i => val data = generateRandomData() val file = testDir + s"/log-$i-$i" @@ -167,25 +216,25 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { assert(fileSystem.exists(logDirectoryPath) === true) // Read data using manager and verify - val readData = readDataUsingManager(testDir) + val readData = readDataUsingWriteAheadLog(testDir) assert(readData === writtenData) } - test("WriteAheadLogManager - recover past logs when creating new manager") { + test("FileBasedWriteAheadLog - recover past logs when creating new manager") { // Write data with manager, recover with new manager and verify val dataToWrite = generateRandomData() - writeDataUsingManager(testDir, dataToWrite) + writeDataUsingWriteAheadLog(testDir, dataToWrite) val logFiles = getLogFilesInDirectory(testDir) assert(logFiles.size > 1) - val readData = readDataUsingManager(testDir) + val readData = readDataUsingWriteAheadLog(testDir) assert(dataToWrite === readData) } - test("WriteAheadLogManager - cleanup old logs") { + test("FileBasedWriteAheadLog - clean old logs") { logCleanUpTest(waitForCompletion = false) } - test("WriteAheadLogManager - cleanup old logs synchronously") { + test("FileBasedWriteAheadLog - clean old logs synchronously") { logCleanUpTest(waitForCompletion = true) } @@ -193,11 +242,11 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { // Write data with manager, recover with new manager and verify val manualClock = new ManualClock val dataToWrite = generateRandomData() - manager = writeDataUsingManager(testDir, dataToWrite, manualClock, stopManager = false) + writeAheadLog = writeDataUsingWriteAheadLog(testDir, dataToWrite, manualClock, closeLog = false) val logFiles = getLogFilesInDirectory(testDir) assert(logFiles.size > 1) - manager.cleanupOldLogs(manualClock.getTimeMillis() / 2, waitForCompletion) + writeAheadLog.clean(manualClock.getTimeMillis() / 2, waitForCompletion) if (waitForCompletion) { assert(getLogFilesInDirectory(testDir).size < logFiles.size) @@ -208,11 +257,11 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { } } - test("WriteAheadLogManager - handling file errors while reading rotating logs") { + test("FileBasedWriteAheadLog - handling file errors while reading rotating logs") { // Generate a set of log files val manualClock = new ManualClock val dataToWrite1 = generateRandomData() - writeDataUsingManager(testDir, dataToWrite1, manualClock) + writeDataUsingWriteAheadLog(testDir, dataToWrite1, manualClock) val logFiles1 = getLogFilesInDirectory(testDir) assert(logFiles1.size > 1) @@ -220,12 +269,12 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { // Recover old files and generate a second set of log files val dataToWrite2 = generateRandomData() manualClock.advance(100000) - writeDataUsingManager(testDir, dataToWrite2, manualClock) + writeDataUsingWriteAheadLog(testDir, dataToWrite2, manualClock) val logFiles2 = getLogFilesInDirectory(testDir) assert(logFiles2.size > logFiles1.size) // Read the files and verify that all the written data can be read - val readData1 = readDataUsingManager(testDir) + val readData1 = readDataUsingWriteAheadLog(testDir) assert(readData1 === (dataToWrite1 ++ dataToWrite2)) // Corrupt the first set of files so that they are basically unreadable @@ -236,25 +285,51 @@ class WriteAheadLogSuite extends FunSuite with BeforeAndAfter { } // Verify that the corrupted files do not prevent reading of the second set of data - val readData = readDataUsingManager(testDir) + val readData = readDataUsingWriteAheadLog(testDir) assert(readData === dataToWrite2) } + + test("FileBasedWriteAheadLog - do not create directories or files unless write") { + val nonexistentTempPath = File.createTempFile("test", "") + nonexistentTempPath.delete() + assert(!nonexistentTempPath.exists()) + + val writtenSegment = writeDataManually(generateRandomData(), testFile) + val wal = new FileBasedWriteAheadLog( + new SparkConf(), tempDir.getAbsolutePath, new Configuration(), 1, 1) + assert(!nonexistentTempPath.exists(), "Directory created just by creating log object") + wal.read(writtenSegment.head) + assert(!nonexistentTempPath.exists(), "Directory created just by attempting to read segment") + } } object WriteAheadLogSuite { + class MockWriteAheadLog0() extends WriteAheadLog { + override def write(record: ByteBuffer, time: Long): WriteAheadLogRecordHandle = { null } + override def read(handle: WriteAheadLogRecordHandle): ByteBuffer = { null } + override def readAll(): util.Iterator[ByteBuffer] = { null } + override def clean(threshTime: Long, waitForCompletion: Boolean): Unit = { } + override def close(): Unit = { } + } + + class MockWriteAheadLog1(val conf: SparkConf) extends MockWriteAheadLog0() + + class MockWriteAheadLog2(val conf: SparkConf, x: Int) extends MockWriteAheadLog0() + + private val hadoopConf = new Configuration() /** Write data to a file directly and return an array of the file segments written. */ - def writeDataManually(data: Seq[String], file: String): Seq[WriteAheadLogFileSegment] = { - val segments = new ArrayBuffer[WriteAheadLogFileSegment]() + def writeDataManually(data: Seq[String], file: String): Seq[FileBasedWriteAheadLogSegment] = { + val segments = new ArrayBuffer[FileBasedWriteAheadLogSegment]() val writer = HdfsUtils.getOutputStream(file, hadoopConf) data.foreach { item => val offset = writer.getPos val bytes = Utils.serialize(item) writer.writeInt(bytes.size) writer.write(bytes) - segments += WriteAheadLogFileSegment(file, offset, bytes.size) + segments += FileBasedWriteAheadLogSegment(file, offset, bytes.size) } writer.close() segments @@ -263,8 +338,11 @@ object WriteAheadLogSuite { /** * Write data to a file using the writer class and return an array of the file segments written. */ - def writeDataUsingWriter(filePath: String, data: Seq[String]): Seq[WriteAheadLogFileSegment] = { - val writer = new WriteAheadLogWriter(filePath, hadoopConf) + def writeDataUsingWriter( + filePath: String, + data: Seq[String] + ): Seq[FileBasedWriteAheadLogSegment] = { + val writer = new FileBasedWriteAheadLogWriter(filePath, hadoopConf) val segments = data.map { item => writer.write(item) } @@ -272,27 +350,27 @@ object WriteAheadLogSuite { segments } - /** Write data to rotating files in log directory using the manager class. */ - def writeDataUsingManager( + /** Write data to rotating files in log directory using the WriteAheadLog class. */ + def writeDataUsingWriteAheadLog( logDirectory: String, data: Seq[String], manualClock: ManualClock = new ManualClock, - stopManager: Boolean = true - ): WriteAheadLogManager = { + closeLog: Boolean = true + ): FileBasedWriteAheadLog = { if (manualClock.getTimeMillis() < 100000) manualClock.setTime(10000) - val manager = new WriteAheadLogManager(logDirectory, hadoopConf, - rollingIntervalSecs = 1, callerName = "WriteAheadLogSuite", clock = manualClock) + val wal = new FileBasedWriteAheadLog(new SparkConf(), logDirectory, hadoopConf, 1, 1) + // Ensure that 500 does not get sorted after 2000, so put a high base value. data.foreach { item => manualClock.advance(500) - manager.writeToLog(item) + wal.write(item, manualClock.getTimeMillis()) } - if (stopManager) manager.stop() - manager + if (closeLog) wal.close() + wal } /** Read data from a segments of a log file directly and return the list of byte buffers. */ - def readDataManually(segments: Seq[WriteAheadLogFileSegment]): Seq[String] = { + def readDataManually(segments: Seq[FileBasedWriteAheadLogSegment]): Seq[String] = { segments.map { segment => val reader = HdfsUtils.getInputStream(segment.path, hadoopConf) try { @@ -331,18 +409,18 @@ object WriteAheadLogSuite { /** Read all the data from a log file using reader class and return the list of byte buffers. */ def readDataUsingReader(file: String): Seq[String] = { - val reader = new WriteAheadLogReader(file, hadoopConf) + val reader = new FileBasedWriteAheadLogReader(file, hadoopConf) val readData = reader.toList.map(byteBufferToString) reader.close() readData } - /** Read all the data in the log file in a directory using the manager class. */ - def readDataUsingManager(logDirectory: String): Seq[String] = { - val manager = new WriteAheadLogManager(logDirectory, hadoopConf, - callerName = "WriteAheadLogSuite") - val data = manager.readFromLog().map(byteBufferToString).toSeq - manager.stop() + /** Read all the data in the log file in a directory using the WriteAheadLog class. */ + def readDataUsingWriteAheadLog(logDirectory: String): Seq[String] = { + import scala.collection.JavaConversions._ + val wal = new FileBasedWriteAheadLog(new SparkConf(), logDirectory, hadoopConf, 1, 1) + val data = wal.readAll().map(byteBufferToString).toSeq + wal.close() data } diff --git a/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala b/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala index f2d135397ce2f..baa97616eaff3 100644 --- a/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala +++ b/tools/src/main/scala/org/apache/spark/tools/StoragePerfTester.scala @@ -46,7 +46,8 @@ object StoragePerfTester { val totalRecords = dataSizeMb * 1000 val recordsPerMap = totalRecords / numMaps - val writeData = "1" * recordLength + val writeKey = "1" * (recordLength / 2) + val writeValue = "1" * (recordLength / 2) val executor = Executors.newFixedThreadPool(numMaps) val conf = new SparkConf() @@ -63,7 +64,7 @@ object StoragePerfTester { new KryoSerializer(sc.conf), new ShuffleWriteMetrics()) val writers = shuffle.writers for (i <- 1 to recordsPerMap) { - writers(i % numOutputSplits).write(writeData) + writers(i % numOutputSplits).write(writeKey, writeValue) } writers.map { w => w.commitAndClose() diff --git a/unsafe/pom.xml b/unsafe/pom.xml new file mode 100644 index 0000000000000..5b0733206b2bc --- /dev/null +++ b/unsafe/pom.xml @@ -0,0 +1,93 @@ + + + + + 4.0.0 + + org.apache.spark + spark-parent_2.10 + 1.4.0-SNAPSHOT + ../pom.xml + + + org.apache.spark + spark-unsafe_2.10 + jar + Spark Project Unsafe + http://spark.apache.org/ + + unsafe + + + + + + + com.google.code.findbugs + jsr305 + + + + + org.slf4j + slf4j-api + provided + + + + + junit + junit + test + + + com.novocode + junit-interface + test + + + + target/scala-${scala.binary.version}/classes + target/scala-${scala.binary.version}/test-classes + + + + net.alchim31.maven + scala-maven-plugin + + + + -XDignore.symbol.file + + + + + org.apache.maven.plugins + maven-compiler-plugin + + + + -XDignore.symbol.file + + + + + + + diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/PlatformDependent.java b/unsafe/src/main/java/org/apache/spark/unsafe/PlatformDependent.java new file mode 100644 index 0000000000000..24b2892098059 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/PlatformDependent.java @@ -0,0 +1,162 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe; + +import java.lang.reflect.Field; + +import sun.misc.Unsafe; + +public final class PlatformDependent { + + /** + * Facade in front of {@link sun.misc.Unsafe}, used to avoid directly exposing Unsafe outside of + * this package. This also lets us aovid accidental use of deprecated methods or methods that + * aren't present in Java 6. + */ + public static final class UNSAFE { + + private UNSAFE() { } + + public static int getInt(Object object, long offset) { + return _UNSAFE.getInt(object, offset); + } + + public static void putInt(Object object, long offset, int value) { + _UNSAFE.putInt(object, offset, value); + } + + public static boolean getBoolean(Object object, long offset) { + return _UNSAFE.getBoolean(object, offset); + } + + public static void putBoolean(Object object, long offset, boolean value) { + _UNSAFE.putBoolean(object, offset, value); + } + + public static byte getByte(Object object, long offset) { + return _UNSAFE.getByte(object, offset); + } + + public static void putByte(Object object, long offset, byte value) { + _UNSAFE.putByte(object, offset, value); + } + + public static short getShort(Object object, long offset) { + return _UNSAFE.getShort(object, offset); + } + + public static void putShort(Object object, long offset, short value) { + _UNSAFE.putShort(object, offset, value); + } + + public static long getLong(Object object, long offset) { + return _UNSAFE.getLong(object, offset); + } + + public static void putLong(Object object, long offset, long value) { + _UNSAFE.putLong(object, offset, value); + } + + public static float getFloat(Object object, long offset) { + return _UNSAFE.getFloat(object, offset); + } + + public static void putFloat(Object object, long offset, float value) { + _UNSAFE.putFloat(object, offset, value); + } + + public static double getDouble(Object object, long offset) { + return _UNSAFE.getDouble(object, offset); + } + + public static void putDouble(Object object, long offset, double value) { + _UNSAFE.putDouble(object, offset, value); + } + + public static long allocateMemory(long size) { + return _UNSAFE.allocateMemory(size); + } + + public static void freeMemory(long address) { + _UNSAFE.freeMemory(address); + } + + } + + private static final Unsafe _UNSAFE; + + public static final int BYTE_ARRAY_OFFSET; + + public static final int INT_ARRAY_OFFSET; + + public static final int LONG_ARRAY_OFFSET; + + public static final int DOUBLE_ARRAY_OFFSET; + + /** + * Limits the number of bytes to copy per {@link Unsafe#copyMemory(long, long, long)} to + * allow safepoint polling during a large copy. + */ + private static final long UNSAFE_COPY_THRESHOLD = 1024L * 1024L; + + static { + sun.misc.Unsafe unsafe; + try { + Field unsafeField = Unsafe.class.getDeclaredField("theUnsafe"); + unsafeField.setAccessible(true); + unsafe = (sun.misc.Unsafe) unsafeField.get(null); + } catch (Throwable cause) { + unsafe = null; + } + _UNSAFE = unsafe; + + if (_UNSAFE != null) { + BYTE_ARRAY_OFFSET = _UNSAFE.arrayBaseOffset(byte[].class); + INT_ARRAY_OFFSET = _UNSAFE.arrayBaseOffset(int[].class); + LONG_ARRAY_OFFSET = _UNSAFE.arrayBaseOffset(long[].class); + DOUBLE_ARRAY_OFFSET = _UNSAFE.arrayBaseOffset(double[].class); + } else { + BYTE_ARRAY_OFFSET = 0; + INT_ARRAY_OFFSET = 0; + LONG_ARRAY_OFFSET = 0; + DOUBLE_ARRAY_OFFSET = 0; + } + } + + static public void copyMemory( + Object src, + long srcOffset, + Object dst, + long dstOffset, + long length) { + while (length > 0) { + long size = Math.min(length, UNSAFE_COPY_THRESHOLD); + _UNSAFE.copyMemory(src, srcOffset, dst, dstOffset, size); + length -= size; + srcOffset += size; + dstOffset += size; + } + } + + /** + * Raises an exception bypassing compiler checks for checked exceptions. + */ + public static void throwException(Throwable t) { + _UNSAFE.throwException(t); + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/array/ByteArrayMethods.java b/unsafe/src/main/java/org/apache/spark/unsafe/array/ByteArrayMethods.java new file mode 100644 index 0000000000000..53eadf96a6b52 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/array/ByteArrayMethods.java @@ -0,0 +1,56 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.array; + +import org.apache.spark.unsafe.PlatformDependent; + +public class ByteArrayMethods { + + private ByteArrayMethods() { + // Private constructor, since this class only contains static methods. + } + + public static int roundNumberOfBytesToNearestWord(int numBytes) { + int remainder = numBytes & 0x07; // This is equivalent to `numBytes % 8` + if (remainder == 0) { + return numBytes; + } else { + return numBytes + (8 - remainder); + } + } + + /** + * Optimized byte array equality check for 8-byte-word-aligned byte arrays. + * @return true if the arrays are equal, false otherwise + */ + public static boolean wordAlignedArrayEquals( + Object leftBaseObject, + long leftBaseOffset, + Object rightBaseObject, + long rightBaseOffset, + long arrayLengthInBytes) { + for (int i = 0; i < arrayLengthInBytes; i += 8) { + final long left = + PlatformDependent.UNSAFE.getLong(leftBaseObject, leftBaseOffset + i); + final long right = + PlatformDependent.UNSAFE.getLong(rightBaseObject, rightBaseOffset + i); + if (left != right) return false; + } + return true; + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/array/LongArray.java b/unsafe/src/main/java/org/apache/spark/unsafe/array/LongArray.java new file mode 100644 index 0000000000000..18d1f0d2d7eb2 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/array/LongArray.java @@ -0,0 +1,78 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.array; + +import org.apache.spark.unsafe.PlatformDependent; +import org.apache.spark.unsafe.memory.MemoryBlock; + +/** + * An array of long values. Compared with native JVM arrays, this: + *
    + *
  • supports using both in-heap and off-heap memory
    • + *
  • has no bound checking, and thus can crash the JVM process when assert is turned off
    • + *
+ */ +public final class LongArray { + + // This is a long so that we perform long multiplications when computing offsets. + private static final long WIDTH = 8; + + private final MemoryBlock memory; + private final Object baseObj; + private final long baseOffset; + + private final long length; + + public LongArray(MemoryBlock memory) { + assert memory.size() % WIDTH == 0 : "Memory not aligned (" + memory.size() + ")"; + assert memory.size() < (long) Integer.MAX_VALUE * 8: "Array size > 4 billion elements"; + this.memory = memory; + this.baseObj = memory.getBaseObject(); + this.baseOffset = memory.getBaseOffset(); + this.length = memory.size() / WIDTH; + } + + public MemoryBlock memoryBlock() { + return memory; + } + + /** + * Returns the number of elements this array can hold. + */ + public long size() { + return length; + } + + /** + * Sets the value at position {@code index}. + */ + public void set(int index, long value) { + assert index >= 0 : "index (" + index + ") should >= 0"; + assert index < length : "index (" + index + ") should < length (" + length + ")"; + PlatformDependent.UNSAFE.putLong(baseObj, baseOffset + index * WIDTH, value); + } + + /** + * Returns the value at position {@code index}. + */ + public long get(int index) { + assert index >= 0 : "index (" + index + ") should >= 0"; + assert index < length : "index (" + index + ") should < length (" + length + ")"; + return PlatformDependent.UNSAFE.getLong(baseObj, baseOffset + index * WIDTH); + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/bitset/BitSet.java b/unsafe/src/main/java/org/apache/spark/unsafe/bitset/BitSet.java new file mode 100644 index 0000000000000..f72e07fce92fd --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/bitset/BitSet.java @@ -0,0 +1,105 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.bitset; + +import org.apache.spark.unsafe.array.LongArray; +import org.apache.spark.unsafe.memory.MemoryBlock; + +/** + * A fixed size uncompressed bit set backed by a {@link LongArray}. + * + * Each bit occupies exactly one bit of storage. + */ +public final class BitSet { + + /** A long array for the bits. */ + private final LongArray words; + + /** Length of the long array. */ + private final int numWords; + + private final Object baseObject; + private final long baseOffset; + + /** + * Creates a new {@link BitSet} using the specified memory block. Size of the memory block must be + * multiple of 8 bytes (i.e. 64 bits). + */ + public BitSet(MemoryBlock memory) { + words = new LongArray(memory); + assert (words.size() <= Integer.MAX_VALUE); + numWords = (int) words.size(); + baseObject = words.memoryBlock().getBaseObject(); + baseOffset = words.memoryBlock().getBaseOffset(); + } + + public MemoryBlock memoryBlock() { + return words.memoryBlock(); + } + + /** + * Returns the number of bits in this {@code BitSet}. + */ + public long capacity() { + return numWords * 64; + } + + /** + * Sets the bit at the specified index to {@code true}. + */ + public void set(int index) { + assert index < numWords * 64 : "index (" + index + ") should < length (" + numWords * 64 + ")"; + BitSetMethods.set(baseObject, baseOffset, index); + } + + /** + * Sets the bit at the specified index to {@code false}. + */ + public void unset(int index) { + assert index < numWords * 64 : "index (" + index + ") should < length (" + numWords * 64 + ")"; + BitSetMethods.unset(baseObject, baseOffset, index); + } + + /** + * Returns {@code true} if the bit is set at the specified index. + */ + public boolean isSet(int index) { + assert index < numWords * 64 : "index (" + index + ") should < length (" + numWords * 64 + ")"; + return BitSetMethods.isSet(baseObject, baseOffset, index); + } + + /** + * Returns the index of the first bit that is set to true that occurs on or after the + * specified starting index. If no such bit exists then {@code -1} is returned. + *

+ * To iterate over the true bits in a BitSet, use the following loop: + * 

+   * 
+   *  for (long i = bs.nextSetBit(0); i >= 0; i = bs.nextSetBit(i + 1)) {
+   *    // operate on index i here
+   *  }
+   * 
+   *
+ * + * @param fromIndex the index to start checking from (inclusive) + * @return the index of the next set bit, or -1 if there is no such bit + */ + public int nextSetBit(int fromIndex) { + return BitSetMethods.nextSetBit(baseObject, baseOffset, fromIndex, numWords); + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/bitset/BitSetMethods.java b/unsafe/src/main/java/org/apache/spark/unsafe/bitset/BitSetMethods.java new file mode 100644 index 0000000000000..f30626d8f4317 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/bitset/BitSetMethods.java @@ -0,0 +1,129 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.bitset; + +import org.apache.spark.unsafe.PlatformDependent; + +/** + * Methods for working with fixed-size uncompressed bitsets. + * + * We assume that the bitset data is word-aligned (that is, a multiple of 8 bytes in length). + * + * Each bit occupies exactly one bit of storage. + */ +public final class BitSetMethods { + + private static final long WORD_SIZE = 8; + + private BitSetMethods() { + // Make the default constructor private, since this only holds static methods. + } + + /** + * Sets the bit at the specified index to {@code true}. + */ + public static void set(Object baseObject, long baseOffset, int index) { + assert index >= 0 : "index (" + index + ") should >= 0"; + final long mask = 1L << (index & 0x3f); // mod 64 and shift + final long wordOffset = baseOffset + (index >> 6) * WORD_SIZE; + final long word = PlatformDependent.UNSAFE.getLong(baseObject, wordOffset); + PlatformDependent.UNSAFE.putLong(baseObject, wordOffset, word | mask); + } + + /** + * Sets the bit at the specified index to {@code false}. + */ + public static void unset(Object baseObject, long baseOffset, int index) { + assert index >= 0 : "index (" + index + ") should >= 0"; + final long mask = 1L << (index & 0x3f); // mod 64 and shift + final long wordOffset = baseOffset + (index >> 6) * WORD_SIZE; + final long word = PlatformDependent.UNSAFE.getLong(baseObject, wordOffset); + PlatformDependent.UNSAFE.putLong(baseObject, wordOffset, word & ~mask); + } + + /** + * Returns {@code true} if the bit is set at the specified index. + */ + public static boolean isSet(Object baseObject, long baseOffset, int index) { + assert index >= 0 : "index (" + index + ") should >= 0"; + final long mask = 1L << (index & 0x3f); // mod 64 and shift + final long wordOffset = baseOffset + (index >> 6) * WORD_SIZE; + final long word = PlatformDependent.UNSAFE.getLong(baseObject, wordOffset); + return (word & mask) != 0; + } + + /** + * Returns {@code true} if any bit is set. + */ + public static boolean anySet(Object baseObject, long baseOffset, long bitSetWidthInBytes) { + for (int i = 0; i <= bitSetWidthInBytes; i++) { + if (PlatformDependent.UNSAFE.getByte(baseObject, baseOffset + i) != 0) { + return true; + } + } + return false; + } + + /** + * Returns the index of the first bit that is set to true that occurs on or after the + * specified starting index. If no such bit exists then {@code -1} is returned. + *

+ * To iterate over the true bits in a BitSet, use the following loop: + * 

+   * 
+   *  for (long i = bs.nextSetBit(0, sizeInWords); i >= 0; i = bs.nextSetBit(i + 1, sizeInWords)) {
+   *    // operate on index i here
+   *  }
+   * 
+   *
+ * + * @param fromIndex the index to start checking from (inclusive) + * @param bitsetSizeInWords the size of the bitset, measured in 8-byte words + * @return the index of the next set bit, or -1 if there is no such bit + */ + public static int nextSetBit( + Object baseObject, + long baseOffset, + int fromIndex, + int bitsetSizeInWords) { + int wi = fromIndex >> 6; + if (wi >= bitsetSizeInWords) { + return -1; + } + + // Try to find the next set bit in the current word + final int subIndex = fromIndex & 0x3f; + long word = + PlatformDependent.UNSAFE.getLong(baseObject, baseOffset + wi * WORD_SIZE) >> subIndex; + if (word != 0) { + return (wi << 6) + subIndex + java.lang.Long.numberOfTrailingZeros(word); + } + + // Find the next set bit in the rest of the words + wi += 1; + while (wi < bitsetSizeInWords) { + word = PlatformDependent.UNSAFE.getLong(baseObject, baseOffset + wi * WORD_SIZE); + if (word != 0) { + return (wi << 6) + java.lang.Long.numberOfTrailingZeros(word); + } + wi += 1; + } + + return -1; + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/hash/Murmur3_x86_32.java b/unsafe/src/main/java/org/apache/spark/unsafe/hash/Murmur3_x86_32.java new file mode 100644 index 0000000000000..85cd02469adb7 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/hash/Murmur3_x86_32.java @@ -0,0 +1,96 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.hash; + +import org.apache.spark.unsafe.PlatformDependent; + +/** + * 32-bit Murmur3 hasher. This is based on Guava's Murmur3_32HashFunction. + */ +public final class Murmur3_x86_32 { + private static final int C1 = 0xcc9e2d51; + private static final int C2 = 0x1b873593; + + private final int seed; + + public Murmur3_x86_32(int seed) { + this.seed = seed; + } + + @Override + public String toString() { + return "Murmur3_32(seed=" + seed + ")"; + } + + public int hashInt(int input) { + int k1 = mixK1(input); + int h1 = mixH1(seed, k1); + + return fmix(h1, 4); + } + + public int hashUnsafeWords(Object baseObject, long baseOffset, int lengthInBytes) { + // This is based on Guava's `Murmur32_Hasher.processRemaining(ByteBuffer)` method. + assert (lengthInBytes % 8 == 0): "lengthInBytes must be a multiple of 8 (word-aligned)"; + int h1 = seed; + for (int offset = 0; offset < lengthInBytes; offset += 4) { + int halfWord = PlatformDependent.UNSAFE.getInt(baseObject, baseOffset + offset); + int k1 = mixK1(halfWord); + h1 = mixH1(h1, k1); + } + return fmix(h1, lengthInBytes); + } + + public int hashLong(long input) { + int low = (int) input; + int high = (int) (input >>> 32); + + int k1 = mixK1(low); + int h1 = mixH1(seed, k1); + + k1 = mixK1(high); + h1 = mixH1(h1, k1); + + return fmix(h1, 8); + } + + private static int mixK1(int k1) { + k1 *= C1; + k1 = Integer.rotateLeft(k1, 15); + k1 *= C2; + return k1; + } + + private static int mixH1(int h1, int k1) { + h1 ^= k1; + h1 = Integer.rotateLeft(h1, 13); + h1 = h1 * 5 + 0xe6546b64; + return h1; + } + + // Finalization mix - force all bits of a hash block to avalanche + private static int fmix(int h1, int length) { + h1 ^= length; + h1 ^= h1 >>> 16; + h1 *= 0x85ebca6b; + h1 ^= h1 >>> 13; + h1 *= 0xc2b2ae35; + h1 ^= h1 >>> 16; + return h1; + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/map/BytesToBytesMap.java b/unsafe/src/main/java/org/apache/spark/unsafe/map/BytesToBytesMap.java new file mode 100644 index 0000000000000..4e5ebc402be35 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/map/BytesToBytesMap.java @@ -0,0 +1,548 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.map; + +import java.lang.Override; +import java.lang.UnsupportedOperationException; +import java.util.Iterator; +import java.util.LinkedList; +import java.util.List; + +import org.apache.spark.unsafe.*; +import org.apache.spark.unsafe.array.ByteArrayMethods; +import org.apache.spark.unsafe.array.LongArray; +import org.apache.spark.unsafe.bitset.BitSet; +import org.apache.spark.unsafe.hash.Murmur3_x86_32; +import org.apache.spark.unsafe.memory.*; + +/** + * An append-only hash map where keys and values are contiguous regions of bytes. + *

+ * This is backed by a power-of-2-sized hash table, using quadratic probing with triangular numbers, + * which is guaranteed to exhaust the space. + *

+ * The map can support up to 2^31 keys because we use 32 bit MurmurHash. If the key cardinality is + * higher than this, you should probably be using sorting instead of hashing for better cache + * locality. + *

+ * This class is not thread safe. + */ +public final class BytesToBytesMap { + + private static final Murmur3_x86_32 HASHER = new Murmur3_x86_32(0); + + private static final HashMapGrowthStrategy growthStrategy = HashMapGrowthStrategy.DOUBLING; + + private final TaskMemoryManager memoryManager; + + /** + * A linked list for tracking all allocated data pages so that we can free all of our memory. + */ + private final List dataPages = new LinkedList(); + + /** + * The data page that will be used to store keys and values for new hashtable entries. When this + * page becomes full, a new page will be allocated and this pointer will change to point to that + * new page. + */ + private MemoryBlock currentDataPage = null; + + /** + * Offset into `currentDataPage` that points to the location where new data can be inserted into + * the page. + */ + private long pageCursor = 0; + + /** + * The size of the data pages that hold key and value data. Map entries cannot span multiple + * pages, so this limits the maximum entry size. + */ + private static final long PAGE_SIZE_BYTES = 1L << 26; // 64 megabytes + + // This choice of page table size and page size means that we can address up to 500 gigabytes + // of memory. + + /** + * A single array to store the key and value. + * + * Position {@code 2 * i} in the array is used to track a pointer to the key at index {@code i}, + * while position {@code 2 * i + 1} in the array holds key's full 32-bit hashcode. + */ + private LongArray longArray; + // TODO: we're wasting 32 bits of space here; we can probably store fewer bits of the hashcode + // and exploit word-alignment to use fewer bits to hold the address. This might let us store + // only one long per map entry, increasing the chance that this array will fit in cache at the + // expense of maybe performing more lookups if we have hash collisions. Say that we stored only + // 27 bits of the hashcode and 37 bits of the address. 37 bits is enough to address 1 terabyte + // of RAM given word-alignment. If we use 13 bits of this for our page table, that gives us a + // maximum page size of 2^24 * 8 = ~134 megabytes per page. This change will require us to store + // full base addresses in the page table for off-heap mode so that we can reconstruct the full + // absolute memory addresses. + + /** + * A {@link BitSet} used to track location of the map where the key is set. + * Size of the bitset should be half of the size of the long array. + */ + private BitSet bitset; + + private final double loadFactor; + + /** + * Number of keys defined in the map. + */ + private int size; + + /** + * The map will be expanded once the number of keys exceeds this threshold. + */ + private int growthThreshold; + + /** + * Mask for truncating hashcodes so that they do not exceed the long array's size. + * This is a strength reduction optimization; we're essentially performing a modulus operation, + * but doing so with a bitmask because this is a power-of-2-sized hash map. + */ + private int mask; + + /** + * Return value of {@link BytesToBytesMap#lookup(Object, long, int)}. + */ + private final Location loc; + + private final boolean enablePerfMetrics; + + private long timeSpentResizingNs = 0; + + private long numProbes = 0; + + private long numKeyLookups = 0; + + private long numHashCollisions = 0; + + public BytesToBytesMap( + TaskMemoryManager memoryManager, + int initialCapacity, + double loadFactor, + boolean enablePerfMetrics) { + this.memoryManager = memoryManager; + this.loadFactor = loadFactor; + this.loc = new Location(); + this.enablePerfMetrics = enablePerfMetrics; + allocate(initialCapacity); + } + + public BytesToBytesMap(TaskMemoryManager memoryManager, int initialCapacity) { + this(memoryManager, initialCapacity, 0.70, false); + } + + public BytesToBytesMap( + TaskMemoryManager memoryManager, + int initialCapacity, + boolean enablePerfMetrics) { + this(memoryManager, initialCapacity, 0.70, enablePerfMetrics); + } + + /** + * Returns the number of keys defined in the map. + */ + public int size() { return size; } + + /** + * Returns an iterator for iterating over the entries of this map. + * + * For efficiency, all calls to `next()` will return the same {@link Location} object. + * + * If any other lookups or operations are performed on this map while iterating over it, including + * `lookup()`, the behavior of the returned iterator is undefined. + */ + public Iterator iterator() { + return new Iterator() { + + private int nextPos = bitset.nextSetBit(0); + + @Override + public boolean hasNext() { + return nextPos != -1; + } + + @Override + public Location next() { + final int pos = nextPos; + nextPos = bitset.nextSetBit(nextPos + 1); + return loc.with(pos, 0, true); + } + + @Override + public void remove() { + throw new UnsupportedOperationException(); + } + }; + } + + /** + * Looks up a key, and return a {@link Location} handle that can be used to test existence + * and read/write values. + * + * This function always return the same {@link Location} instance to avoid object allocation. + */ + public Location lookup( + Object keyBaseObject, + long keyBaseOffset, + int keyRowLengthBytes) { + if (enablePerfMetrics) { + numKeyLookups++; + } + final int hashcode = HASHER.hashUnsafeWords(keyBaseObject, keyBaseOffset, keyRowLengthBytes); + int pos = hashcode & mask; + int step = 1; + while (true) { + if (enablePerfMetrics) { + numProbes++; + } + if (!bitset.isSet(pos)) { + // This is a new key. + return loc.with(pos, hashcode, false); + } else { + long stored = longArray.get(pos * 2 + 1); + if ((int) (stored) == hashcode) { + // Full hash code matches. Let's compare the keys for equality. + loc.with(pos, hashcode, true); + if (loc.getKeyLength() == keyRowLengthBytes) { + final MemoryLocation keyAddress = loc.getKeyAddress(); + final Object storedKeyBaseObject = keyAddress.getBaseObject(); + final long storedKeyBaseOffset = keyAddress.getBaseOffset(); + final boolean areEqual = ByteArrayMethods.wordAlignedArrayEquals( + keyBaseObject, + keyBaseOffset, + storedKeyBaseObject, + storedKeyBaseOffset, + keyRowLengthBytes + ); + if (areEqual) { + return loc; + } else { + if (enablePerfMetrics) { + numHashCollisions++; + } + } + } + } + } + pos = (pos + step) & mask; + step++; + } + } + + /** + * Handle returned by {@link BytesToBytesMap#lookup(Object, long, int)} function. + */ + public final class Location { + /** An index into the hash map's Long array */ + private int pos; + /** True if this location points to a position where a key is defined, false otherwise */ + private boolean isDefined; + /** + * The hashcode of the most recent key passed to + * {@link BytesToBytesMap#lookup(Object, long, int)}. Caching this hashcode here allows us to + * avoid re-hashing the key when storing a value for that key. + */ + private int keyHashcode; + private final MemoryLocation keyMemoryLocation = new MemoryLocation(); + private final MemoryLocation valueMemoryLocation = new MemoryLocation(); + private int keyLength; + private int valueLength; + + private void updateAddressesAndSizes(long fullKeyAddress) { + final Object page = memoryManager.getPage(fullKeyAddress); + final long keyOffsetInPage = memoryManager.getOffsetInPage(fullKeyAddress); + long position = keyOffsetInPage; + keyLength = (int) PlatformDependent.UNSAFE.getLong(page, position); + position += 8; // word used to store the key size + keyMemoryLocation.setObjAndOffset(page, position); + position += keyLength; + valueLength = (int) PlatformDependent.UNSAFE.getLong(page, position); + position += 8; // word used to store the key size + valueMemoryLocation.setObjAndOffset(page, position); + } + + Location with(int pos, int keyHashcode, boolean isDefined) { + this.pos = pos; + this.isDefined = isDefined; + this.keyHashcode = keyHashcode; + if (isDefined) { + final long fullKeyAddress = longArray.get(pos * 2); + updateAddressesAndSizes(fullKeyAddress); + } + return this; + } + + /** + * Returns true if the key is defined at this position, and false otherwise. + */ + public boolean isDefined() { + return isDefined; + } + + /** + * Returns the address of the key defined at this position. + * This points to the first byte of the key data. + * Unspecified behavior if the key is not defined. + * For efficiency reasons, calls to this method always returns the same MemoryLocation object. + */ + public MemoryLocation getKeyAddress() { + assert (isDefined); + return keyMemoryLocation; + } + + /** + * Returns the length of the key defined at this position. + * Unspecified behavior if the key is not defined. + */ + public int getKeyLength() { + assert (isDefined); + return keyLength; + } + + /** + * Returns the address of the value defined at this position. + * This points to the first byte of the value data. + * Unspecified behavior if the key is not defined. + * For efficiency reasons, calls to this method always returns the same MemoryLocation object. + */ + public MemoryLocation getValueAddress() { + assert (isDefined); + return valueMemoryLocation; + } + + /** + * Returns the length of the value defined at this position. + * Unspecified behavior if the key is not defined. + */ + public int getValueLength() { + assert (isDefined); + return valueLength; + } + + /** + * Store a new key and value. This method may only be called once for a given key; if you want + * to update the value associated with a key, then you can directly manipulate the bytes stored + * at the value address. + *

+ * It is only valid to call this method immediately after calling `lookup()` using the same key. + *

+ * After calling this method, calls to `get[Key|Value]Address()` and `get[Key|Value]Length` + * will return information on the data stored by this `putNewKey` call. + *

+ * As an example usage, here's the proper way to store a new key: + *

+ * 

+     *   Location loc = map.lookup(keyBaseOffset, keyBaseObject, keyLengthInBytes);
+     *   if (!loc.isDefined()) {
+     *     loc.putNewKey(keyBaseOffset, keyBaseObject, keyLengthInBytes, ...)
+     *   }
+     *
+ *

+ * Unspecified behavior if the key is not defined. + */ + public void putNewKey( + Object keyBaseObject, + long keyBaseOffset, + int keyLengthBytes, + Object valueBaseObject, + long valueBaseOffset, + int valueLengthBytes) { + assert (!isDefined) : "Can only set value once for a key"; + isDefined = true; + assert (keyLengthBytes % 8 == 0); + assert (valueLengthBytes % 8 == 0); + // Here, we'll copy the data into our data pages. Because we only store a relative offset from + // the key address instead of storing the absolute address of the value, the key and value + // must be stored in the same memory page. + // (8 byte key length) (key) (8 byte value length) (value) + final long requiredSize = 8 + keyLengthBytes + 8 + valueLengthBytes; + assert(requiredSize <= PAGE_SIZE_BYTES); + size++; + bitset.set(pos); + + // If there's not enough space in the current page, allocate a new page: + if (currentDataPage == null || PAGE_SIZE_BYTES - pageCursor < requiredSize) { + MemoryBlock newPage = memoryManager.allocatePage(PAGE_SIZE_BYTES); + dataPages.add(newPage); + pageCursor = 0; + currentDataPage = newPage; + } + + // Compute all of our offsets up-front: + final Object pageBaseObject = currentDataPage.getBaseObject(); + final long pageBaseOffset = currentDataPage.getBaseOffset(); + final long keySizeOffsetInPage = pageBaseOffset + pageCursor; + pageCursor += 8; // word used to store the key size + final long keyDataOffsetInPage = pageBaseOffset + pageCursor; + pageCursor += keyLengthBytes; + final long valueSizeOffsetInPage = pageBaseOffset + pageCursor; + pageCursor += 8; // word used to store the value size + final long valueDataOffsetInPage = pageBaseOffset + pageCursor; + pageCursor += valueLengthBytes; + + // Copy the key + PlatformDependent.UNSAFE.putLong(pageBaseObject, keySizeOffsetInPage, keyLengthBytes); + PlatformDependent.copyMemory( + keyBaseObject, keyBaseOffset, pageBaseObject, keyDataOffsetInPage, keyLengthBytes); + // Copy the value + PlatformDependent.UNSAFE.putLong(pageBaseObject, valueSizeOffsetInPage, valueLengthBytes); + PlatformDependent.copyMemory( + valueBaseObject, valueBaseOffset, pageBaseObject, valueDataOffsetInPage, valueLengthBytes); + + final long storedKeyAddress = memoryManager.encodePageNumberAndOffset( + currentDataPage, keySizeOffsetInPage); + longArray.set(pos * 2, storedKeyAddress); + longArray.set(pos * 2 + 1, keyHashcode); + updateAddressesAndSizes(storedKeyAddress); + isDefined = true; + if (size > growthThreshold) { + growAndRehash(); + } + } + } + + /** + * Allocate new data structures for this map. When calling this outside of the constructor, + * make sure to keep references to the old data structures so that you can free them. + * + * @param capacity the new map capacity + */ + private void allocate(int capacity) { + capacity = Math.max((int) Math.min(Integer.MAX_VALUE, nextPowerOf2(capacity)), 64); + longArray = new LongArray(memoryManager.allocate(capacity * 8 * 2)); + bitset = new BitSet(MemoryBlock.fromLongArray(new long[capacity / 64])); + + this.growthThreshold = (int) (capacity * loadFactor); + this.mask = capacity - 1; + } + + /** + * Free all allocated memory associated with this map, including the storage for keys and values + * as well as the hash map array itself. + * + * This method is idempotent. + */ + public void free() { + if (longArray != null) { + memoryManager.free(longArray.memoryBlock()); + longArray = null; + } + if (bitset != null) { + // The bitset's heap memory isn't managed by a memory manager, so no need to free it here. + bitset = null; + } + Iterator dataPagesIterator = dataPages.iterator(); + while (dataPagesIterator.hasNext()) { + memoryManager.freePage(dataPagesIterator.next()); + dataPagesIterator.remove(); + } + assert(dataPages.isEmpty()); + } + + /** Returns the total amount of memory, in bytes, consumed by this map's managed structures. */ + public long getTotalMemoryConsumption() { + return ( + dataPages.size() * PAGE_SIZE_BYTES + + bitset.memoryBlock().size() + + longArray.memoryBlock().size()); + } + + /** + * Returns the total amount of time spent resizing this map (in nanoseconds). + */ + public long getTimeSpentResizingNs() { + if (!enablePerfMetrics) { + throw new IllegalStateException(); + } + return timeSpentResizingNs; + } + + + /** + * Returns the average number of probes per key lookup. + */ + public double getAverageProbesPerLookup() { + if (!enablePerfMetrics) { + throw new IllegalStateException(); + } + return (1.0 * numProbes) / numKeyLookups; + } + + public long getNumHashCollisions() { + if (!enablePerfMetrics) { + throw new IllegalStateException(); + } + return numHashCollisions; + } + + /** + * Grows the size of the hash table and re-hash everything. + */ + private void growAndRehash() { + long resizeStartTime = -1; + if (enablePerfMetrics) { + resizeStartTime = System.nanoTime(); + } + // Store references to the old data structures to be used when we re-hash + final LongArray oldLongArray = longArray; + final BitSet oldBitSet = bitset; + final int oldCapacity = (int) oldBitSet.capacity(); + + // Allocate the new data structures + allocate(Math.min(Integer.MAX_VALUE, growthStrategy.nextCapacity(oldCapacity))); + + // Re-mask (we don't recompute the hashcode because we stored all 32 bits of it) + for (int pos = oldBitSet.nextSetBit(0); pos >= 0; pos = oldBitSet.nextSetBit(pos + 1)) { + final long keyPointer = oldLongArray.get(pos * 2); + final int hashcode = (int) oldLongArray.get(pos * 2 + 1); + int newPos = hashcode & mask; + int step = 1; + boolean keepGoing = true; + + // No need to check for equality here when we insert so this has one less if branch than + // the similar code path in addWithoutResize. + while (keepGoing) { + if (!bitset.isSet(newPos)) { + bitset.set(newPos); + longArray.set(newPos * 2, keyPointer); + longArray.set(newPos * 2 + 1, hashcode); + keepGoing = false; + } else { + newPos = (newPos + step) & mask; + step++; + } + } + } + + // Deallocate the old data structures. + memoryManager.free(oldLongArray.memoryBlock()); + if (enablePerfMetrics) { + timeSpentResizingNs += System.nanoTime() - resizeStartTime; + } + } + + /** Returns the next number greater or equal num that is power of 2. */ + private static long nextPowerOf2(long num) { + final long highBit = Long.highestOneBit(num); + return (highBit == num) ? num : highBit << 1; + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/map/HashMapGrowthStrategy.java b/unsafe/src/main/java/org/apache/spark/unsafe/map/HashMapGrowthStrategy.java new file mode 100644 index 0000000000000..7c321baffe82d --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/map/HashMapGrowthStrategy.java @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.map; + +/** + * Interface that defines how we can grow the size of a hash map when it is over a threshold. + */ +public interface HashMapGrowthStrategy { + + int nextCapacity(int currentCapacity); + + /** + * Double the size of the hash map every time. + */ + HashMapGrowthStrategy DOUBLING = new Doubling(); + + class Doubling implements HashMapGrowthStrategy { + @Override + public int nextCapacity(int currentCapacity) { + return currentCapacity * 2; + } + } + +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/memory/ExecutorMemoryManager.java b/unsafe/src/main/java/org/apache/spark/unsafe/memory/ExecutorMemoryManager.java new file mode 100644 index 0000000000000..62c29c8cc1e4d --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/ExecutorMemoryManager.java @@ -0,0 +1,58 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +/** + * Manages memory for an executor. Individual operators / tasks allocate memory through + * {@link TaskMemoryManager} objects, which obtain their memory from ExecutorMemoryManager. + */ +public class ExecutorMemoryManager { + + /** + * Allocator, exposed for enabling untracked allocations of temporary data structures. + */ + public final MemoryAllocator allocator; + + /** + * Tracks whether memory will be allocated on the JVM heap or off-heap using sun.misc.Unsafe. + */ + final boolean inHeap; + + /** + * Construct a new ExecutorMemoryManager. + * + * @param allocator the allocator that will be used + */ + public ExecutorMemoryManager(MemoryAllocator allocator) { + this.inHeap = allocator instanceof HeapMemoryAllocator; + this.allocator = allocator; + } + + /** + * Allocates a contiguous block of memory. Note that the allocated memory is not guaranteed + * to be zeroed out (call `zero()` on the result if this is necessary). + */ + MemoryBlock allocate(long size) throws OutOfMemoryError { + return allocator.allocate(size); + } + + void free(MemoryBlock memory) { + allocator.free(memory); + } + +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/memory/HeapMemoryAllocator.java b/unsafe/src/main/java/org/apache/spark/unsafe/memory/HeapMemoryAllocator.java new file mode 100644 index 0000000000000..bbe83d36cf36b --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/HeapMemoryAllocator.java @@ -0,0 +1,35 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +/** + * A simple {@link MemoryAllocator} that can allocate up to 16GB using a JVM long primitive array. + */ +public class HeapMemoryAllocator implements MemoryAllocator { + + @Override + public MemoryBlock allocate(long size) throws OutOfMemoryError { + long[] array = new long[(int) (size / 8)]; + return MemoryBlock.fromLongArray(array); + } + + @Override + public void free(MemoryBlock memory) { + // Do nothing + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryAllocator.java b/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryAllocator.java new file mode 100644 index 0000000000000..5192f68c862cf --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryAllocator.java @@ -0,0 +1,33 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +public interface MemoryAllocator { + + /** + * Allocates a contiguous block of memory. Note that the allocated memory is not guaranteed + * to be zeroed out (call `zero()` on the result if this is necessary). + */ + MemoryBlock allocate(long size) throws OutOfMemoryError; + + void free(MemoryBlock memory); + + MemoryAllocator UNSAFE = new UnsafeMemoryAllocator(); + + MemoryAllocator HEAP = new HeapMemoryAllocator(); +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryBlock.java b/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryBlock.java new file mode 100644 index 0000000000000..3dc82d8c2eb39 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryBlock.java @@ -0,0 +1,55 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +import javax.annotation.Nullable; + +import org.apache.spark.unsafe.PlatformDependent; + +/** + * A consecutive block of memory, starting at a {@link MemoryLocation} with a fixed size. + */ +public class MemoryBlock extends MemoryLocation { + + private final long length; + + /** + * Optional page number; used when this MemoryBlock represents a page allocated by a + * MemoryManager. This is package-private and is modified by MemoryManager. + */ + int pageNumber = -1; + + MemoryBlock(@Nullable Object obj, long offset, long length) { + super(obj, offset); + this.length = length; + } + + /** + * Returns the size of the memory block. + */ + public long size() { + return length; + } + + /** + * Creates a memory block pointing to the memory used by the long array. + */ + public static MemoryBlock fromLongArray(final long[] array) { + return new MemoryBlock(array, PlatformDependent.LONG_ARRAY_OFFSET, array.length * 8); + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryLocation.java b/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryLocation.java new file mode 100644 index 0000000000000..74ebc87dc978c --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryLocation.java @@ -0,0 +1,54 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +import javax.annotation.Nullable; + +/** + * A memory location. Tracked either by a memory address (with off-heap allocation), + * or by an offset from a JVM object (in-heap allocation). + */ +public class MemoryLocation { + + @Nullable + Object obj; + + long offset; + + public MemoryLocation(@Nullable Object obj, long offset) { + this.obj = obj; + this.offset = offset; + } + + public MemoryLocation() { + this(null, 0); + } + + public void setObjAndOffset(Object newObj, long newOffset) { + this.obj = newObj; + this.offset = newOffset; + } + + public final Object getBaseObject() { + return obj; + } + + public final long getBaseOffset() { + return offset; + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/memory/TaskMemoryManager.java b/unsafe/src/main/java/org/apache/spark/unsafe/memory/TaskMemoryManager.java new file mode 100644 index 0000000000000..9224988e6ad69 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/TaskMemoryManager.java @@ -0,0 +1,237 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +import java.util.*; + +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +/** + * Manages the memory allocated by an individual task. + *

+ * Most of the complexity in this class deals with encoding of off-heap addresses into 64-bit longs. + * In off-heap mode, memory can be directly addressed with 64-bit longs. In on-heap mode, memory is + * addressed by the combination of a base Object reference and a 64-bit offset within that object. + * This is a problem when we want to store pointers to data structures inside of other structures, + * such as record pointers inside hashmaps or sorting buffers. Even if we decided to use 128 bits + * to address memory, we can't just store the address of the base object since it's not guaranteed + * to remain stable as the heap gets reorganized due to GC. + *

+ * Instead, we use the following approach to encode record pointers in 64-bit longs: for off-heap + * mode, just store the raw address, and for on-heap mode use the upper 13 bits of the address to + * store a "page number" and the lower 51 bits to store an offset within this page. These page + * numbers are used to index into a "page table" array inside of the MemoryManager in order to + * retrieve the base object. + *

+ * This allows us to address 8192 pages. In on-heap mode, the maximum page size is limited by the + * maximum size of a long[] array, allowing us to address 8192 * 2^32 * 8 bytes, which is + * approximately 35 terabytes of memory. + */ +public final class TaskMemoryManager { + + private final Logger logger = LoggerFactory.getLogger(TaskMemoryManager.class); + + /** + * The number of entries in the page table. + */ + private static final int PAGE_TABLE_SIZE = 1 << 13; + + /** Bit mask for the lower 51 bits of a long. */ + private static final long MASK_LONG_LOWER_51_BITS = 0x7FFFFFFFFFFFFL; + + /** Bit mask for the upper 13 bits of a long */ + private static final long MASK_LONG_UPPER_13_BITS = ~MASK_LONG_LOWER_51_BITS; + + /** + * Similar to an operating system's page table, this array maps page numbers into base object + * pointers, allowing us to translate between the hashtable's internal 64-bit address + * representation and the baseObject+offset representation which we use to support both in- and + * off-heap addresses. When using an off-heap allocator, every entry in this map will be `null`. + * When using an in-heap allocator, the entries in this map will point to pages' base objects. + * Entries are added to this map as new data pages are allocated. + */ + private final MemoryBlock[] pageTable = new MemoryBlock[PAGE_TABLE_SIZE]; + + /** + * Bitmap for tracking free pages. + */ + private final BitSet allocatedPages = new BitSet(PAGE_TABLE_SIZE); + + /** + * Tracks memory allocated with {@link TaskMemoryManager#allocate(long)}, used to detect / clean + * up leaked memory. + */ + private final HashSet allocatedNonPageMemory = new HashSet(); + + private final ExecutorMemoryManager executorMemoryManager; + + /** + * Tracks whether we're in-heap or off-heap. For off-heap, we short-circuit most of these methods + * without doing any masking or lookups. Since this branching should be well-predicted by the JIT, + * this extra layer of indirection / abstraction hopefully shouldn't be too expensive. + */ + private final boolean inHeap; + + /** + * Construct a new MemoryManager. + */ + public TaskMemoryManager(ExecutorMemoryManager executorMemoryManager) { + this.inHeap = executorMemoryManager.inHeap; + this.executorMemoryManager = executorMemoryManager; + } + + /** + * Allocate a block of memory that will be tracked in the MemoryManager's page table; this is + * intended for allocating large blocks of memory that will be shared between operators. + */ + public MemoryBlock allocatePage(long size) { + if (logger.isTraceEnabled()) { + logger.trace("Allocating {} byte page", size); + } + if (size >= (1L << 51)) { + throw new IllegalArgumentException("Cannot allocate a page with more than 2^51 bytes"); + } + + final int pageNumber; + synchronized (this) { + pageNumber = allocatedPages.nextClearBit(0); + if (pageNumber >= PAGE_TABLE_SIZE) { + throw new IllegalStateException( + "Have already allocated a maximum of " + PAGE_TABLE_SIZE + " pages"); + } + allocatedPages.set(pageNumber); + } + final MemoryBlock page = executorMemoryManager.allocate(size); + page.pageNumber = pageNumber; + pageTable[pageNumber] = page; + if (logger.isDebugEnabled()) { + logger.debug("Allocate page number {} ({} bytes)", pageNumber, size); + } + return page; + } + + /** + * Free a block of memory allocated via {@link TaskMemoryManager#allocatePage(long)}. + */ + public void freePage(MemoryBlock page) { + if (logger.isTraceEnabled()) { + logger.trace("Freeing page number {} ({} bytes)", page.pageNumber, page.size()); + } + assert (page.pageNumber != -1) : + "Called freePage() on memory that wasn't allocated with allocatePage()"; + executorMemoryManager.free(page); + synchronized (this) { + allocatedPages.clear(page.pageNumber); + } + pageTable[page.pageNumber] = null; + if (logger.isDebugEnabled()) { + logger.debug("Freed page number {} ({} bytes)", page.pageNumber, page.size()); + } + } + + /** + * Allocates a contiguous block of memory. Note that the allocated memory is not guaranteed + * to be zeroed out (call `zero()` on the result if this is necessary). This method is intended + * to be used for allocating operators' internal data structures. For data pages that you want to + * exchange between operators, consider using {@link TaskMemoryManager#allocatePage(long)}, since + * that will enable intra-memory pointers (see + * {@link TaskMemoryManager#encodePageNumberAndOffset(MemoryBlock, long)} and this class's + * top-level Javadoc for more details). + */ + public MemoryBlock allocate(long size) throws OutOfMemoryError { + final MemoryBlock memory = executorMemoryManager.allocate(size); + allocatedNonPageMemory.add(memory); + return memory; + } + + /** + * Free memory allocated by {@link TaskMemoryManager#allocate(long)}. + */ + public void free(MemoryBlock memory) { + assert (memory.pageNumber == -1) : "Should call freePage() for pages, not free()"; + executorMemoryManager.free(memory); + final boolean wasAlreadyRemoved = !allocatedNonPageMemory.remove(memory); + assert (!wasAlreadyRemoved) : "Called free() on memory that was already freed!"; + } + + /** + * Given a memory page and offset within that page, encode this address into a 64-bit long. + * This address will remain valid as long as the corresponding page has not been freed. + */ + public long encodePageNumberAndOffset(MemoryBlock page, long offsetInPage) { + if (inHeap) { + assert (page.pageNumber != -1) : "encodePageNumberAndOffset called with invalid page"; + return (((long) page.pageNumber) << 51) | (offsetInPage & MASK_LONG_LOWER_51_BITS); + } else { + return offsetInPage; + } + } + + /** + * Get the page associated with an address encoded by + * {@link TaskMemoryManager#encodePageNumberAndOffset(MemoryBlock, long)} + */ + public Object getPage(long pagePlusOffsetAddress) { + if (inHeap) { + final int pageNumber = (int) ((pagePlusOffsetAddress & MASK_LONG_UPPER_13_BITS) >>> 51); + assert (pageNumber >= 0 && pageNumber < PAGE_TABLE_SIZE); + final Object page = pageTable[pageNumber].getBaseObject(); + assert (page != null); + return page; + } else { + return null; + } + } + + /** + * Get the offset associated with an address encoded by + * {@link TaskMemoryManager#encodePageNumberAndOffset(MemoryBlock, long)} + */ + public long getOffsetInPage(long pagePlusOffsetAddress) { + if (inHeap) { + return (pagePlusOffsetAddress & MASK_LONG_LOWER_51_BITS); + } else { + return pagePlusOffsetAddress; + } + } + + /** + * Clean up all allocated memory and pages. Returns the number of bytes freed. A non-zero return + * value can be used to detect memory leaks. + */ + public long cleanUpAllAllocatedMemory() { + long freedBytes = 0; + for (MemoryBlock page : pageTable) { + if (page != null) { + freedBytes += page.size(); + freePage(page); + } + } + final Iterator iter = allocatedNonPageMemory.iterator(); + while (iter.hasNext()) { + final MemoryBlock memory = iter.next(); + freedBytes += memory.size(); + // We don't call free() here because that calls Set.remove, which would lead to a + // ConcurrentModificationException here. + executorMemoryManager.free(memory); + iter.remove(); + } + return freedBytes; + } +} diff --git a/unsafe/src/main/java/org/apache/spark/unsafe/memory/UnsafeMemoryAllocator.java b/unsafe/src/main/java/org/apache/spark/unsafe/memory/UnsafeMemoryAllocator.java new file mode 100644 index 0000000000000..15898771fef25 --- /dev/null +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/UnsafeMemoryAllocator.java @@ -0,0 +1,39 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +import org.apache.spark.unsafe.PlatformDependent; + +/** + * A simple {@link MemoryAllocator} that uses {@code Unsafe} to allocate off-heap memory. + */ +public class UnsafeMemoryAllocator implements MemoryAllocator { + + @Override + public MemoryBlock allocate(long size) throws OutOfMemoryError { + long address = PlatformDependent.UNSAFE.allocateMemory(size); + return new MemoryBlock(null, address, size); + } + + @Override + public void free(MemoryBlock memory) { + assert (memory.obj == null) : + "baseObject not null; are you trying to use the off-heap allocator to free on-heap memory?"; + PlatformDependent.UNSAFE.freeMemory(memory.offset); + } +} diff --git a/unsafe/src/test/java/org/apache/spark/unsafe/array/LongArraySuite.java b/unsafe/src/test/java/org/apache/spark/unsafe/array/LongArraySuite.java new file mode 100644 index 0000000000000..5974cf91ff993 --- /dev/null +++ b/unsafe/src/test/java/org/apache/spark/unsafe/array/LongArraySuite.java @@ -0,0 +1,38 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.array; + +import org.junit.Assert; +import org.junit.Test; + +import org.apache.spark.unsafe.memory.MemoryBlock; + +public class LongArraySuite { + + @Test + public void basicTest() { + long[] bytes = new long[2]; + LongArray arr = new LongArray(MemoryBlock.fromLongArray(bytes)); + arr.set(0, 1L); + arr.set(1, 2L); + arr.set(1, 3L); + Assert.assertEquals(2, arr.size()); + Assert.assertEquals(1L, arr.get(0)); + Assert.assertEquals(3L, arr.get(1)); + } +} diff --git a/unsafe/src/test/java/org/apache/spark/unsafe/bitset/BitSetSuite.java b/unsafe/src/test/java/org/apache/spark/unsafe/bitset/BitSetSuite.java new file mode 100644 index 0000000000000..e3a824e29b768 --- /dev/null +++ b/unsafe/src/test/java/org/apache/spark/unsafe/bitset/BitSetSuite.java @@ -0,0 +1,82 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.bitset; + +import junit.framework.Assert; +import org.apache.spark.unsafe.bitset.BitSet; +import org.junit.Test; + +import org.apache.spark.unsafe.memory.MemoryBlock; + +public class BitSetSuite { + + private static BitSet createBitSet(int capacity) { + assert capacity % 64 == 0; + return new BitSet(MemoryBlock.fromLongArray(new long[capacity / 64])); + } + + @Test + public void basicOps() { + BitSet bs = createBitSet(64); + Assert.assertEquals(64, bs.capacity()); + + // Make sure the bit set starts empty. + for (int i = 0; i < bs.capacity(); i++) { + Assert.assertFalse(bs.isSet(i)); + } + + // Set every bit and check it. + for (int i = 0; i < bs.capacity(); i++) { + bs.set(i); + Assert.assertTrue(bs.isSet(i)); + } + + // Unset every bit and check it. + for (int i = 0; i < bs.capacity(); i++) { + Assert.assertTrue(bs.isSet(i)); + bs.unset(i); + Assert.assertFalse(bs.isSet(i)); + } + } + + @Test + public void traversal() { + BitSet bs = createBitSet(256); + + Assert.assertEquals(-1, bs.nextSetBit(0)); + Assert.assertEquals(-1, bs.nextSetBit(10)); + Assert.assertEquals(-1, bs.nextSetBit(64)); + + bs.set(10); + Assert.assertEquals(10, bs.nextSetBit(0)); + Assert.assertEquals(10, bs.nextSetBit(1)); + Assert.assertEquals(10, bs.nextSetBit(10)); + Assert.assertEquals(-1, bs.nextSetBit(11)); + + bs.set(11); + Assert.assertEquals(10, bs.nextSetBit(10)); + Assert.assertEquals(11, bs.nextSetBit(11)); + + // Skip a whole word and find it + bs.set(190); + Assert.assertEquals(190, bs.nextSetBit(12)); + + Assert.assertEquals(-1, bs.nextSetBit(191)); + Assert.assertEquals(-1, bs.nextSetBit(256)); + } +} diff --git a/unsafe/src/test/java/org/apache/spark/unsafe/hash/Murmur3_x86_32Suite.java b/unsafe/src/test/java/org/apache/spark/unsafe/hash/Murmur3_x86_32Suite.java new file mode 100644 index 0000000000000..3b9175835229c --- /dev/null +++ b/unsafe/src/test/java/org/apache/spark/unsafe/hash/Murmur3_x86_32Suite.java @@ -0,0 +1,119 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.hash; + +import java.util.HashSet; +import java.util.Random; +import java.util.Set; + +import junit.framework.Assert; +import org.apache.spark.unsafe.PlatformDependent; +import org.junit.Test; + +/** + * Test file based on Guava's Murmur3Hash32Test. + */ +public class Murmur3_x86_32Suite { + + private static final Murmur3_x86_32 hasher = new Murmur3_x86_32(0); + + @Test + public void testKnownIntegerInputs() { + Assert.assertEquals(593689054, hasher.hashInt(0)); + Assert.assertEquals(-189366624, hasher.hashInt(-42)); + Assert.assertEquals(-1134849565, hasher.hashInt(42)); + Assert.assertEquals(-1718298732, hasher.hashInt(Integer.MIN_VALUE)); + Assert.assertEquals(-1653689534, hasher.hashInt(Integer.MAX_VALUE)); + } + + @Test + public void testKnownLongInputs() { + Assert.assertEquals(1669671676, hasher.hashLong(0L)); + Assert.assertEquals(-846261623, hasher.hashLong(-42L)); + Assert.assertEquals(1871679806, hasher.hashLong(42L)); + Assert.assertEquals(1366273829, hasher.hashLong(Long.MIN_VALUE)); + Assert.assertEquals(-2106506049, hasher.hashLong(Long.MAX_VALUE)); + } + + @Test + public void randomizedStressTest() { + int size = 65536; + Random rand = new Random(); + + // A set used to track collision rate. + Set hashcodes = new HashSet(); + for (int i = 0; i < size; i++) { + int vint = rand.nextInt(); + long lint = rand.nextLong(); + Assert.assertEquals(hasher.hashInt(vint), hasher.hashInt(vint)); + Assert.assertEquals(hasher.hashLong(lint), hasher.hashLong(lint)); + + hashcodes.add(hasher.hashLong(lint)); + } + + // A very loose bound. + Assert.assertTrue(hashcodes.size() > size * 0.95); + } + + @Test + public void randomizedStressTestBytes() { + int size = 65536; + Random rand = new Random(); + + // A set used to track collision rate. + Set hashcodes = new HashSet(); + for (int i = 0; i < size; i++) { + int byteArrSize = rand.nextInt(100) * 8; + byte[] bytes = new byte[byteArrSize]; + rand.nextBytes(bytes); + + Assert.assertEquals( + hasher.hashUnsafeWords(bytes, PlatformDependent.BYTE_ARRAY_OFFSET, byteArrSize), + hasher.hashUnsafeWords(bytes, PlatformDependent.BYTE_ARRAY_OFFSET, byteArrSize)); + + hashcodes.add(hasher.hashUnsafeWords( + bytes, PlatformDependent.BYTE_ARRAY_OFFSET, byteArrSize)); + } + + // A very loose bound. + Assert.assertTrue(hashcodes.size() > size * 0.95); + } + + @Test + public void randomizedStressTestPaddedStrings() { + int size = 64000; + // A set used to track collision rate. + Set hashcodes = new HashSet(); + for (int i = 0; i < size; i++) { + int byteArrSize = 8; + byte[] strBytes = ("" + i).getBytes(); + byte[] paddedBytes = new byte[byteArrSize]; + System.arraycopy(strBytes, 0, paddedBytes, 0, strBytes.length); + + Assert.assertEquals( + hasher.hashUnsafeWords(paddedBytes, PlatformDependent.BYTE_ARRAY_OFFSET, byteArrSize), + hasher.hashUnsafeWords(paddedBytes, PlatformDependent.BYTE_ARRAY_OFFSET, byteArrSize)); + + hashcodes.add(hasher.hashUnsafeWords( + paddedBytes, PlatformDependent.BYTE_ARRAY_OFFSET, byteArrSize)); + } + + // A very loose bound. + Assert.assertTrue(hashcodes.size() > size * 0.95); + } +} diff --git a/unsafe/src/test/java/org/apache/spark/unsafe/map/AbstractBytesToBytesMapSuite.java b/unsafe/src/test/java/org/apache/spark/unsafe/map/AbstractBytesToBytesMapSuite.java new file mode 100644 index 0000000000000..7a5c0622d1ffb --- /dev/null +++ b/unsafe/src/test/java/org/apache/spark/unsafe/map/AbstractBytesToBytesMapSuite.java @@ -0,0 +1,250 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.map; + +import java.lang.Exception; +import java.nio.ByteBuffer; +import java.util.*; + +import org.junit.After; +import org.junit.Assert; +import org.junit.Before; +import org.junit.Test; + +import org.apache.spark.unsafe.array.ByteArrayMethods; +import org.apache.spark.unsafe.PlatformDependent; +import static org.apache.spark.unsafe.PlatformDependent.BYTE_ARRAY_OFFSET; +import org.apache.spark.unsafe.memory.ExecutorMemoryManager; +import org.apache.spark.unsafe.memory.MemoryAllocator; +import org.apache.spark.unsafe.memory.MemoryLocation; +import org.apache.spark.unsafe.memory.TaskMemoryManager; + +public abstract class AbstractBytesToBytesMapSuite { + + private final Random rand = new Random(42); + + private TaskMemoryManager memoryManager; + + @Before + public void setup() { + memoryManager = new TaskMemoryManager(new ExecutorMemoryManager(getMemoryAllocator())); + } + + @After + public void tearDown() { + if (memoryManager != null) { + memoryManager.cleanUpAllAllocatedMemory(); + memoryManager = null; + } + } + + protected abstract MemoryAllocator getMemoryAllocator(); + + private static byte[] getByteArray(MemoryLocation loc, int size) { + final byte[] arr = new byte[size]; + PlatformDependent.copyMemory( + loc.getBaseObject(), + loc.getBaseOffset(), + arr, + BYTE_ARRAY_OFFSET, + size + ); + return arr; + } + + private byte[] getRandomByteArray(int numWords) { + Assert.assertTrue(numWords > 0); + final int lengthInBytes = numWords * 8; + final byte[] bytes = new byte[lengthInBytes]; + rand.nextBytes(bytes); + return bytes; + } + + /** + * Fast equality checking for byte arrays, since these comparisons are a bottleneck + * in our stress tests. + */ + private static boolean arrayEquals( + byte[] expected, + MemoryLocation actualAddr, + long actualLengthBytes) { + return (actualLengthBytes == expected.length) && ByteArrayMethods.wordAlignedArrayEquals( + expected, + BYTE_ARRAY_OFFSET, + actualAddr.getBaseObject(), + actualAddr.getBaseOffset(), + expected.length + ); + } + + @Test + public void emptyMap() { + BytesToBytesMap map = new BytesToBytesMap(memoryManager, 64); + try { + Assert.assertEquals(0, map.size()); + final int keyLengthInWords = 10; + final int keyLengthInBytes = keyLengthInWords * 8; + final byte[] key = getRandomByteArray(keyLengthInWords); + Assert.assertFalse(map.lookup(key, BYTE_ARRAY_OFFSET, keyLengthInBytes).isDefined()); + } finally { + map.free(); + } + } + + @Test + public void setAndRetrieveAKey() { + BytesToBytesMap map = new BytesToBytesMap(memoryManager, 64); + final int recordLengthWords = 10; + final int recordLengthBytes = recordLengthWords * 8; + final byte[] keyData = getRandomByteArray(recordLengthWords); + final byte[] valueData = getRandomByteArray(recordLengthWords); + try { + final BytesToBytesMap.Location loc = + map.lookup(keyData, BYTE_ARRAY_OFFSET, recordLengthBytes); + Assert.assertFalse(loc.isDefined()); + loc.putNewKey( + keyData, + BYTE_ARRAY_OFFSET, + recordLengthBytes, + valueData, + BYTE_ARRAY_OFFSET, + recordLengthBytes + ); + // After storing the key and value, the other location methods should return results that + // reflect the result of this store without us having to call lookup() again on the same key. + Assert.assertEquals(recordLengthBytes, loc.getKeyLength()); + Assert.assertEquals(recordLengthBytes, loc.getValueLength()); + Assert.assertArrayEquals(keyData, getByteArray(loc.getKeyAddress(), recordLengthBytes)); + Assert.assertArrayEquals(valueData, getByteArray(loc.getValueAddress(), recordLengthBytes)); + + // After calling lookup() the location should still point to the correct data. + Assert.assertTrue(map.lookup(keyData, BYTE_ARRAY_OFFSET, recordLengthBytes).isDefined()); + Assert.assertEquals(recordLengthBytes, loc.getKeyLength()); + Assert.assertEquals(recordLengthBytes, loc.getValueLength()); + Assert.assertArrayEquals(keyData, getByteArray(loc.getKeyAddress(), recordLengthBytes)); + Assert.assertArrayEquals(valueData, getByteArray(loc.getValueAddress(), recordLengthBytes)); + + try { + loc.putNewKey( + keyData, + BYTE_ARRAY_OFFSET, + recordLengthBytes, + valueData, + BYTE_ARRAY_OFFSET, + recordLengthBytes + ); + Assert.fail("Should not be able to set a new value for a key"); + } catch (AssertionError e) { + // Expected exception; do nothing. + } + } finally { + map.free(); + } + } + + @Test + public void iteratorTest() throws Exception { + final int size = 128; + BytesToBytesMap map = new BytesToBytesMap(memoryManager, size / 2); + try { + for (long i = 0; i < size; i++) { + final long[] value = new long[] { i }; + final BytesToBytesMap.Location loc = + map.lookup(value, PlatformDependent.LONG_ARRAY_OFFSET, 8); + Assert.assertFalse(loc.isDefined()); + loc.putNewKey( + value, + PlatformDependent.LONG_ARRAY_OFFSET, + 8, + value, + PlatformDependent.LONG_ARRAY_OFFSET, + 8 + ); + } + final java.util.BitSet valuesSeen = new java.util.BitSet(size); + final Iterator iter = map.iterator(); + while (iter.hasNext()) { + final BytesToBytesMap.Location loc = iter.next(); + Assert.assertTrue(loc.isDefined()); + final MemoryLocation keyAddress = loc.getKeyAddress(); + final MemoryLocation valueAddress = loc.getValueAddress(); + final long key = PlatformDependent.UNSAFE.getLong( + keyAddress.getBaseObject(), keyAddress.getBaseOffset()); + final long value = PlatformDependent.UNSAFE.getLong( + valueAddress.getBaseObject(), valueAddress.getBaseOffset()); + Assert.assertEquals(key, value); + valuesSeen.set((int) value); + } + Assert.assertEquals(size, valuesSeen.cardinality()); + } finally { + map.free(); + } + } + + @Test + public void randomizedStressTest() { + final int size = 65536; + // Java arrays' hashCodes() aren't based on the arrays' contents, so we need to wrap arrays + // into ByteBuffers in order to use them as keys here. + final Map expected = new HashMap(); + final BytesToBytesMap map = new BytesToBytesMap(memoryManager, size); + + try { + // Fill the map to 90% full so that we can trigger probing + for (int i = 0; i < size * 0.9; i++) { + final byte[] key = getRandomByteArray(rand.nextInt(256) + 1); + final byte[] value = getRandomByteArray(rand.nextInt(512) + 1); + if (!expected.containsKey(ByteBuffer.wrap(key))) { + expected.put(ByteBuffer.wrap(key), value); + final BytesToBytesMap.Location loc = map.lookup( + key, + BYTE_ARRAY_OFFSET, + key.length + ); + Assert.assertFalse(loc.isDefined()); + loc.putNewKey( + key, + BYTE_ARRAY_OFFSET, + key.length, + value, + BYTE_ARRAY_OFFSET, + value.length + ); + // After calling putNewKey, the following should be true, even before calling + // lookup(): + Assert.assertTrue(loc.isDefined()); + Assert.assertEquals(key.length, loc.getKeyLength()); + Assert.assertEquals(value.length, loc.getValueLength()); + Assert.assertTrue(arrayEquals(key, loc.getKeyAddress(), key.length)); + Assert.assertTrue(arrayEquals(value, loc.getValueAddress(), value.length)); + } + } + + for (Map.Entry entry : expected.entrySet()) { + final byte[] key = entry.getKey().array(); + final byte[] value = entry.getValue(); + final BytesToBytesMap.Location loc = map.lookup(key, BYTE_ARRAY_OFFSET, key.length); + Assert.assertTrue(loc.isDefined()); + Assert.assertTrue(arrayEquals(key, loc.getKeyAddress(), loc.getKeyLength())); + Assert.assertTrue(arrayEquals(value, loc.getValueAddress(), loc.getValueLength())); + } + } finally { + map.free(); + } + } +} diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala b/unsafe/src/test/java/org/apache/spark/unsafe/map/BytesToBytesMapOffHeapSuite.java similarity index 63% rename from sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala rename to unsafe/src/test/java/org/apache/spark/unsafe/map/BytesToBytesMapOffHeapSuite.java index f5fea3f015dc4..5a10de49f54fe 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala +++ b/unsafe/src/test/java/org/apache/spark/unsafe/map/BytesToBytesMapOffHeapSuite.java @@ -15,22 +15,15 @@ * limitations under the License. */ -package org.apache.spark.sql.catalyst.expressions +package org.apache.spark.unsafe.map; -import java.util.Random +import org.apache.spark.unsafe.memory.MemoryAllocator; -import org.apache.spark.sql.types.{DataType, DoubleType} +public class BytesToBytesMapOffHeapSuite extends AbstractBytesToBytesMapSuite { - -case object Rand extends LeafExpression { - override def dataType: DataType = DoubleType - override def nullable: Boolean = false - - private[this] lazy val rand = new Random - - override def eval(input: Row = null): EvaluatedType = { - rand.nextDouble().asInstanceOf[EvaluatedType] + @Override + protected MemoryAllocator getMemoryAllocator() { + return MemoryAllocator.UNSAFE; } - override def toString: String = "RAND()" } diff --git a/unsafe/src/test/java/org/apache/spark/unsafe/map/BytesToBytesMapOnHeapSuite.java b/unsafe/src/test/java/org/apache/spark/unsafe/map/BytesToBytesMapOnHeapSuite.java new file mode 100644 index 0000000000000..12cc9b25d93b3 --- /dev/null +++ b/unsafe/src/test/java/org/apache/spark/unsafe/map/BytesToBytesMapOnHeapSuite.java @@ -0,0 +1,29 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.map; + +import org.apache.spark.unsafe.memory.MemoryAllocator; + +public class BytesToBytesMapOnHeapSuite extends AbstractBytesToBytesMapSuite { + + @Override + protected MemoryAllocator getMemoryAllocator() { + return MemoryAllocator.HEAP; + } + +} diff --git a/unsafe/src/test/java/org/apache/spark/unsafe/memory/TaskMemoryManagerSuite.java b/unsafe/src/test/java/org/apache/spark/unsafe/memory/TaskMemoryManagerSuite.java new file mode 100644 index 0000000000000..932882f1ca248 --- /dev/null +++ b/unsafe/src/test/java/org/apache/spark/unsafe/memory/TaskMemoryManagerSuite.java @@ -0,0 +1,41 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.unsafe.memory; + +import org.junit.Assert; +import org.junit.Test; + +public class TaskMemoryManagerSuite { + + @Test + public void leakedNonPageMemoryIsDetected() { + final TaskMemoryManager manager = + new TaskMemoryManager(new ExecutorMemoryManager(MemoryAllocator.HEAP)); + manager.allocate(1024); // leak memory + Assert.assertEquals(1024, manager.cleanUpAllAllocatedMemory()); + } + + @Test + public void leakedPageMemoryIsDetected() { + final TaskMemoryManager manager = + new TaskMemoryManager(new ExecutorMemoryManager(MemoryAllocator.HEAP)); + manager.allocatePage(4096); // leak memory + Assert.assertEquals(4096, manager.cleanUpAllAllocatedMemory()); + } + +} diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala new file mode 100644 index 0000000000000..aaae6f9734a85 --- /dev/null +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala @@ -0,0 +1,205 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.spark.deploy.yarn + +import java.security.PrivilegedExceptionAction +import java.util.concurrent.{Executors, TimeUnit} + +import scala.language.postfixOps + +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.{FileSystem, Path} +import org.apache.hadoop.security.UserGroupInformation +import org.apache.spark.deploy.SparkHadoopUtil + +import org.apache.spark.{Logging, SparkConf} +import org.apache.spark.util.ThreadUtils + +/* + * The following methods are primarily meant to make sure long-running apps like Spark + * Streaming apps can run without interruption while writing to secure HDFS. The + * scheduleLoginFromKeytab method is called on the driver when the + * CoarseGrainedScheduledBackend starts up. This method wakes up a thread that logs into the KDC + * once 75% of the renewal interval of the original delegation tokens used for the container + * has elapsed. It then creates new delegation tokens and writes them to HDFS in a + * pre-specified location - the prefix of which is specified in the sparkConf by + * spark.yarn.credentials.file (so the file(s) would be named c-1, c-2 etc. - each update goes + * to a new file, with a monotonically increasing suffix). After this, the credentials are + * updated once 75% of the new tokens renewal interval has elapsed. + * + * On the executor side, the updateCredentialsIfRequired method is called once 80% of the + * validity of the original tokens has elapsed. At that time the executor finds the + * credentials file with the latest timestamp and checks if it has read those credentials + * before (by keeping track of the suffix of the last file it read). If a new file has + * appeared, it will read the credentials and update the currently running UGI with it. This + * process happens again once 80% of the validity of this has expired. + */ +private[yarn] class AMDelegationTokenRenewer( + sparkConf: SparkConf, + hadoopConf: Configuration) extends Logging { + + private var lastCredentialsFileSuffix = 0 + + private val delegationTokenRenewer = + Executors.newSingleThreadScheduledExecutor( + ThreadUtils.namedThreadFactory("Delegation Token Refresh Thread")) + + private val hadoopUtil = YarnSparkHadoopUtil.get + + private val daysToKeepFiles = sparkConf.getInt("spark.yarn.credentials.file.retention.days", 5) + private val numFilesToKeep = sparkConf.getInt("spark.yarn.credentials.file.retention.count", 5) + + /** + * Schedule a login from the keytab and principal set using the --principal and --keytab + * arguments to spark-submit. This login happens only when the credentials of the current user + * are about to expire. This method reads spark.yarn.principal and spark.yarn.keytab from + * SparkConf to do the login. This method is a no-op in non-YARN mode. + * + */ + private[spark] def scheduleLoginFromKeytab(): Unit = { + val principal = sparkConf.get("spark.yarn.principal") + val keytab = sparkConf.get("spark.yarn.keytab") + + /** + * Schedule re-login and creation of new tokens. If tokens have already expired, this method + * will synchronously create new ones. + */ + def scheduleRenewal(runnable: Runnable): Unit = { + val credentials = UserGroupInformation.getCurrentUser.getCredentials + val renewalInterval = hadoopUtil.getTimeFromNowToRenewal(sparkConf, 0.75, credentials) + // Run now! + if (renewalInterval <= 0) { + logInfo("HDFS tokens have expired, creating new tokens now.") + runnable.run() + } else { + logInfo(s"Scheduling login from keytab in $renewalInterval millis.") + delegationTokenRenewer.schedule(runnable, renewalInterval, TimeUnit.MILLISECONDS) + } + } + + // This thread periodically runs on the driver to update the delegation tokens on HDFS. + val driverTokenRenewerRunnable = + new Runnable { + override def run(): Unit = { + try { + writeNewTokensToHDFS(principal, keytab) + cleanupOldFiles() + } catch { + case e: Exception => + // Log the error and try to write new tokens back in an hour + logWarning("Failed to write out new credentials to HDFS, will try again in an " + + "hour! If this happens too often tasks will fail.", e) + delegationTokenRenewer.schedule(this, 1, TimeUnit.HOURS) + return + } + scheduleRenewal(this) + } + } + // Schedule update of credentials. This handles the case of updating the tokens right now + // as well, since the renenwal interval will be 0, and the thread will get scheduled + // immediately. + scheduleRenewal(driverTokenRenewerRunnable) + } + + // Keeps only files that are newer than daysToKeepFiles days, and deletes everything else. At + // least numFilesToKeep files are kept for safety + private def cleanupOldFiles(): Unit = { + import scala.concurrent.duration._ + try { + val remoteFs = FileSystem.get(hadoopConf) + val credentialsPath = new Path(sparkConf.get("spark.yarn.credentials.file")) + val thresholdTime = System.currentTimeMillis() - (daysToKeepFiles days).toMillis + hadoopUtil.listFilesSorted( + remoteFs, credentialsPath.getParent, + credentialsPath.getName, SparkHadoopUtil.SPARK_YARN_CREDS_TEMP_EXTENSION) + .dropRight(numFilesToKeep) + .takeWhile(_.getModificationTime < thresholdTime) + .foreach(x => remoteFs.delete(x.getPath, true)) + } catch { + // Such errors are not fatal, so don't throw. Make sure they are logged though + case e: Exception => + logWarning("Error while attempting to cleanup old tokens. If you are seeing many such " + + "warnings there may be an issue with your HDFS cluster.", e) + } + } + + private def writeNewTokensToHDFS(principal: String, keytab: String): Unit = { + // Keytab is copied by YARN to the working directory of the AM, so full path is + // not needed. + + // HACK: + // HDFS will not issue new delegation tokens, if the Credentials object + // passed in already has tokens for that FS even if the tokens are expired (it really only + // checks if there are tokens for the service, and not if they are valid). So the only real + // way to get new tokens is to make sure a different Credentials object is used each time to + // get new tokens and then the new tokens are copied over the the current user's Credentials. + // So: + // - we login as a different user and get the UGI + // - use that UGI to get the tokens (see doAs block below) + // - copy the tokens over to the current user's credentials (this will overwrite the tokens + // in the current user's Credentials object for this FS). + // The login to KDC happens each time new tokens are required, but this is rare enough to not + // have to worry about (like once every day or so). This makes this code clearer than having + // to login and then relogin every time (the HDFS API may not relogin since we don't use this + // UGI directly for HDFS communication. + logInfo(s"Attempting to login to KDC using principal: $principal") + val keytabLoggedInUGI = UserGroupInformation.loginUserFromKeytabAndReturnUGI(principal, keytab) + logInfo("Successfully logged into KDC.") + val tempCreds = keytabLoggedInUGI.getCredentials + val credentialsPath = new Path(sparkConf.get("spark.yarn.credentials.file")) + val dst = credentialsPath.getParent + keytabLoggedInUGI.doAs(new PrivilegedExceptionAction[Void] { + // Get a copy of the credentials + override def run(): Void = { + val nns = YarnSparkHadoopUtil.get.getNameNodesToAccess(sparkConf) + dst + hadoopUtil.obtainTokensForNamenodes(nns, hadoopConf, tempCreds) + null + } + }) + // Add the temp credentials back to the original ones. + UserGroupInformation.getCurrentUser.addCredentials(tempCreds) + val remoteFs = FileSystem.get(hadoopConf) + // If lastCredentialsFileSuffix is 0, then the AM is either started or restarted. If the AM + // was restarted, then the lastCredentialsFileSuffix might be > 0, so find the newest file + // and update the lastCredentialsFileSuffix. + if (lastCredentialsFileSuffix == 0) { + hadoopUtil.listFilesSorted( + remoteFs, credentialsPath.getParent, + credentialsPath.getName, SparkHadoopUtil.SPARK_YARN_CREDS_TEMP_EXTENSION) + .lastOption.foreach { status => + lastCredentialsFileSuffix = hadoopUtil.getSuffixForCredentialsPath(status.getPath) + } + } + val nextSuffix = lastCredentialsFileSuffix + 1 + val tokenPathStr = + sparkConf.get("spark.yarn.credentials.file") + + SparkHadoopUtil.SPARK_YARN_CREDS_COUNTER_DELIM + nextSuffix + val tokenPath = new Path(tokenPathStr) + val tempTokenPath = new Path(tokenPathStr + SparkHadoopUtil.SPARK_YARN_CREDS_TEMP_EXTENSION) + logInfo("Writing out delegation tokens to " + tempTokenPath.toString) + val credentials = UserGroupInformation.getCurrentUser.getCredentials + credentials.writeTokenStorageFile(tempTokenPath, hadoopConf) + logInfo(s"Delegation Tokens written out successfully. Renaming file to $tokenPathStr") + remoteFs.rename(tempTokenPath, tokenPath) + logInfo("Delegation token file rename complete.") + lastCredentialsFileSuffix = nextSuffix + } + + def stop(): Unit = { + delegationTokenRenewer.shutdown() + } +} diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala index 70cb57ffd8c69..e1694c1f64a9f 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala @@ -75,6 +75,8 @@ private[spark] class ApplicationMaster( // Fields used in cluster mode. private val sparkContextRef = new AtomicReference[SparkContext](null) + private var delegationTokenRenewerOption: Option[AMDelegationTokenRenewer] = None + final def run(): Int = { try { val appAttemptId = client.getAttemptId() @@ -89,6 +91,10 @@ private[spark] class ApplicationMaster( // Propagate the application ID so that YarnClusterSchedulerBackend can pick it up. System.setProperty("spark.yarn.app.id", appAttemptId.getApplicationId().toString()) + + // Propagate the attempt if, so that in case of event logging, + // different attempt's logs gets created in different directory + System.setProperty("spark.yarn.app.attemptId", appAttemptId.getAttemptId().toString()) } logInfo("ApplicationAttemptId: " + appAttemptId) @@ -125,6 +131,15 @@ private[spark] class ApplicationMaster( // doAs in order for the credentials to be passed on to the executor containers. val securityMgr = new SecurityManager(sparkConf) + // If the credentials file config is present, we must periodically renew tokens. So create + // a new AMDelegationTokenRenewer + if (sparkConf.contains("spark.yarn.credentials.file")) { + delegationTokenRenewerOption = Some(new AMDelegationTokenRenewer(sparkConf, yarnConf)) + // If a principal and keytab have been set, use that to create new credentials for executors + // periodically + delegationTokenRenewerOption.foreach(_.scheduleLoginFromKeytab()) + } + if (isClusterMode) { runDriver(securityMgr) } else { @@ -189,6 +204,7 @@ private[spark] class ApplicationMaster( logDebug("shutting down user thread") userClassThread.interrupt() } + if (!inShutdown) delegationTokenRenewerOption.foreach(_.stop()) } } } @@ -208,10 +224,11 @@ private[spark] class ApplicationMaster( val sc = sparkContextRef.get() val appId = client.getAttemptId().getApplicationId().toString() + val attemptId = client.getAttemptId().getAttemptId().toString() val historyAddress = sparkConf.getOption("spark.yarn.historyServer.address") .map { text => SparkHadoopUtil.get.substituteHadoopVariables(text, yarnConf) } - .map { address => s"${address}${HistoryServer.UI_PATH_PREFIX}/${appId}" } + .map { address => s"${address}${HistoryServer.UI_PATH_PREFIX}/${appId}/${attemptId}" } .getOrElse("") allocator = client.register(yarnConf, @@ -235,12 +252,12 @@ private[spark] class ApplicationMaster( host: String, port: String, isClusterMode: Boolean): Unit = { - val driverEndpont = rpcEnv.setupEndpointRef( + val driverEndpoint = rpcEnv.setupEndpointRef( SparkEnv.driverActorSystemName, RpcAddress(host, port.toInt), YarnSchedulerBackend.ENDPOINT_NAME) amEndpoint = - rpcEnv.setupEndpoint("YarnAM", new AMEndpoint(rpcEnv, driverEndpont, isClusterMode)) + rpcEnv.setupEndpoint("YarnAM", new AMEndpoint(rpcEnv, driverEndpoint, isClusterMode)) } private def runDriver(securityMgr: SecurityManager): Unit = { @@ -494,6 +511,7 @@ private[spark] class ApplicationMaster( override def onStart(): Unit = { driver.send(RegisterClusterManager(self)) + } override def receive: PartialFunction[Any, Unit] = { diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala index 741239c953794..20ecaf092e3f8 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala @@ -17,9 +17,11 @@ package org.apache.spark.deploy.yarn -import java.io.{File, FileOutputStream} +import java.io.{ByteArrayInputStream, DataInputStream, File, FileOutputStream} import java.net.{InetAddress, UnknownHostException, URI, URISyntaxException} import java.nio.ByteBuffer +import java.security.PrivilegedExceptionAction +import java.util.UUID import java.util.zip.{ZipEntry, ZipOutputStream} import scala.collection.JavaConversions._ @@ -36,10 +38,9 @@ import org.apache.hadoop.hdfs.security.token.delegation.DelegationTokenIdentifie import org.apache.hadoop.fs._ import org.apache.hadoop.fs.permission.FsPermission import org.apache.hadoop.io.Text -import org.apache.hadoop.mapred.Master import org.apache.hadoop.mapreduce.MRJobConfig import org.apache.hadoop.security.{Credentials, UserGroupInformation} -import org.apache.hadoop.security.token.Token +import org.apache.hadoop.security.token.{TokenIdentifier, Token} import org.apache.hadoop.util.StringUtils import org.apache.hadoop.yarn.api._ import org.apache.hadoop.yarn.api.ApplicationConstants.Environment @@ -50,8 +51,8 @@ import org.apache.hadoop.yarn.conf.YarnConfiguration import org.apache.hadoop.yarn.exceptions.ApplicationNotFoundException import org.apache.hadoop.yarn.util.Records -import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkContext, SparkException} import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkContext, SparkException} import org.apache.spark.util.Utils private[spark] class Client( @@ -69,11 +70,13 @@ private[spark] class Client( private val yarnClient = YarnClient.createYarnClient private val yarnConf = new YarnConfiguration(hadoopConf) - private val credentials = UserGroupInformation.getCurrentUser.getCredentials + private var credentials: Credentials = null private val amMemoryOverhead = args.amMemoryOverhead // MB private val executorMemoryOverhead = args.executorMemoryOverhead // MB private val distCacheMgr = new ClientDistributedCacheManager() private val isClusterMode = args.isClusterMode + + private var loginFromKeytab = false private val fireAndForget = isClusterMode && !sparkConf.getBoolean("spark.yarn.submit.waitAppCompletion", true) @@ -88,6 +91,8 @@ private[spark] class Client( * available in the alpha API. */ def submitApplication(): ApplicationId = { + // Setup the credentials before doing anything else, so we have don't have issues at any point. + setupCredentials() yarnClient.init(yarnConf) yarnClient.start() @@ -219,13 +224,14 @@ private[spark] class Client( // and add them as local resources to the application master. val fs = FileSystem.get(hadoopConf) val dst = new Path(fs.getHomeDirectory(), appStagingDir) - val nns = getNameNodesToAccess(sparkConf) + dst + val nns = YarnSparkHadoopUtil.get.getNameNodesToAccess(sparkConf) + dst + YarnSparkHadoopUtil.get.obtainTokensForNamenodes(nns, hadoopConf, credentials) // Used to keep track of URIs added to the distributed cache. If the same URI is added // multiple times, YARN will fail to launch containers for the app with an internal // error. val distributedUris = new HashSet[String] - obtainTokensForNamenodes(nns, hadoopConf, credentials) obtainTokenForHiveMetastore(hadoopConf, credentials) + obtainTokenForHBase(hadoopConf, credentials) val replication = sparkConf.getInt("spark.yarn.submit.file.replication", fs.getDefaultReplication(dst)).toShort @@ -242,6 +248,20 @@ private[spark] class Client( "for alternatives.") } + // If we passed in a keytab, make sure we copy the keytab to the staging directory on + // HDFS, and setup the relevant environment vars, so the AM can login again. + if (loginFromKeytab) { + logInfo("To enable the AM to login from keytab, credentials are being copied over to the AM" + + " via the YARN Secure Distributed Cache.") + val localUri = new URI(args.keytab) + val localPath = getQualifiedLocalPath(localUri, hadoopConf) + val destinationPath = copyFileToRemote(dst, localPath, replication) + val destFs = FileSystem.get(destinationPath.toUri(), hadoopConf) + distCacheMgr.addResource( + destFs, hadoopConf, destinationPath, localResources, LocalResourceType.FILE, + sparkConf.get("spark.yarn.keytab"), statCache, appMasterOnly = true) + } + def addDistributedUri(uri: URI): Boolean = { val uriStr = uri.toString() if (distributedUris.contains(uriStr)) { @@ -370,9 +390,11 @@ private[spark] class Client( try { hadoopConfStream.setLevel(0) hadoopConfFiles.foreach { case (name, file) => - hadoopConfStream.putNextEntry(new ZipEntry(name)) - Files.copy(file, hadoopConfStream) - hadoopConfStream.closeEntry() + if (file.canRead()) { + hadoopConfStream.putNextEntry(new ZipEntry(name)) + Files.copy(file, hadoopConfStream) + hadoopConfStream.closeEntry() + } } } finally { hadoopConfStream.close() @@ -384,6 +406,28 @@ private[spark] class Client( } } + /** + * Get the renewal interval for tokens. + */ + private def getTokenRenewalInterval(stagingDirPath: Path): Long = { + // We cannot use the tokens generated above since those have renewer yarn. Trying to renew + // those will fail with an access control issue. So create new tokens with the logged in + // user as renewer. + val creds = new Credentials() + val nns = YarnSparkHadoopUtil.get.getNameNodesToAccess(sparkConf) + stagingDirPath + YarnSparkHadoopUtil.get.obtainTokensForNamenodes( + nns, hadoopConf, creds, Some(sparkConf.get("spark.yarn.principal"))) + val t = creds.getAllTokens + .filter(_.getKind == DelegationTokenIdentifier.HDFS_DELEGATION_KIND) + .head + val newExpiration = t.renew(hadoopConf) + val identifier = new DelegationTokenIdentifier() + identifier.readFields(new DataInputStream(new ByteArrayInputStream(t.getIdentifier))) + val interval = newExpiration - identifier.getIssueDate + logInfo(s"Renewal Interval set to $interval") + interval + } + /** * Set up the environment for launching our ApplicationMaster container. */ @@ -395,7 +439,16 @@ private[spark] class Client( env("SPARK_YARN_MODE") = "true" env("SPARK_YARN_STAGING_DIR") = stagingDir env("SPARK_USER") = UserGroupInformation.getCurrentUser().getShortUserName() - + if (loginFromKeytab) { + val remoteFs = FileSystem.get(hadoopConf) + val stagingDirPath = new Path(remoteFs.getHomeDirectory, stagingDir) + val credentialsFile = "credentials-" + UUID.randomUUID().toString + sparkConf.set( + "spark.yarn.credentials.file", new Path(stagingDirPath, credentialsFile).toString) + logInfo(s"Credentials file set to: $credentialsFile") + val renewalInterval = getTokenRenewalInterval(stagingDirPath) + sparkConf.set("spark.yarn.token.renewal.interval", renewalInterval.toString) + } // Set the environment variables to be passed on to the executors. distCacheMgr.setDistFilesEnv(env) distCacheMgr.setDistArchivesEnv(env) @@ -460,7 +513,6 @@ private[spark] class Client( private def createContainerLaunchContext(newAppResponse: GetNewApplicationResponse) : ContainerLaunchContext = { logInfo("Setting up container launch context for our AM") - val appId = newAppResponse.getApplicationId val appStagingDir = getAppStagingDir(appId) val localResources = prepareLocalResources(appStagingDir) @@ -541,6 +593,10 @@ private[spark] class Client( } javaOpts ++= Utils.splitCommandString(opts).map(YarnSparkHadoopUtil.escapeForShell) } + + sparkConf.getOption("spark.yarn.am.extraLibraryPath").foreach { paths => + prefixEnv = Some(Utils.libraryPathEnvPrefix(Seq(paths))) + } } // For log4j configuration to reference @@ -631,6 +687,24 @@ private[spark] class Client( amContainer } + def setupCredentials(): Unit = { + if (args.principal != null) { + require(args.keytab != null, "Keytab must be specified when principal is specified.") + logInfo("Attempting to login to the Kerberos" + + s" using principal: ${args.principal} and keytab: ${args.keytab}") + val f = new File(args.keytab) + // Generate a file name that can be used for the keytab file, that does not conflict + // with any user file. + val keytabFileName = f.getName + "-" + UUID.randomUUID().toString + UserGroupInformation.loginUserFromKeytab(args.principal, args.keytab) + loginFromKeytab = true + sparkConf.set("spark.yarn.keytab", keytabFileName) + sparkConf.set("spark.yarn.principal", args.principal) + logInfo("Successfully logged into the KDC.") + } + credentials = UserGroupInformation.getCurrentUser.getCredentials + } + /** * Report the state of an application until it has exited, either successfully or * due to some failure, then return a pair of the yarn application state (FINISHED, FAILED, @@ -986,46 +1060,6 @@ object Client extends Logging { private def addClasspathEntry(path: String, env: HashMap[String, String]): Unit = YarnSparkHadoopUtil.addPathToEnvironment(env, Environment.CLASSPATH.name, path) - /** - * Get the list of namenodes the user may access. - */ - private[yarn] def getNameNodesToAccess(sparkConf: SparkConf): Set[Path] = { - sparkConf.get("spark.yarn.access.namenodes", "") - .split(",") - .map(_.trim()) - .filter(!_.isEmpty) - .map(new Path(_)) - .toSet - } - - private[yarn] def getTokenRenewer(conf: Configuration): String = { - val delegTokenRenewer = Master.getMasterPrincipal(conf) - logDebug("delegation token renewer is: " + delegTokenRenewer) - if (delegTokenRenewer == null || delegTokenRenewer.length() == 0) { - val errorMessage = "Can't get Master Kerberos principal for use as renewer" - logError(errorMessage) - throw new SparkException(errorMessage) - } - delegTokenRenewer - } - - /** - * Obtains tokens for the namenodes passed in and adds them to the credentials. - */ - private def obtainTokensForNamenodes( - paths: Set[Path], - conf: Configuration, - creds: Credentials): Unit = { - if (UserGroupInformation.isSecurityEnabled()) { - val delegTokenRenewer = getTokenRenewer(conf) - paths.foreach { dst => - val dstFs = dst.getFileSystem(conf) - logDebug("getting token for namenode: " + dst) - dstFs.addDelegationTokens(delegTokenRenewer, creds) - } - } - } - /** * Obtains token for the Hive metastore and adds them to the credentials. */ @@ -1084,6 +1118,41 @@ object Client extends Logging { } } + /** + * Obtain security token for HBase. + */ + def obtainTokenForHBase(conf: Configuration, credentials: Credentials): Unit = { + if (UserGroupInformation.isSecurityEnabled) { + val mirror = universe.runtimeMirror(getClass.getClassLoader) + + try { + val confCreate = mirror.classLoader. + loadClass("org.apache.hadoop.hbase.HBaseConfiguration"). + getMethod("create", classOf[Configuration]) + val obtainToken = mirror.classLoader. + loadClass("org.apache.hadoop.hbase.security.token.TokenUtil"). + getMethod("obtainToken", classOf[Configuration]) + + logDebug("Attempting to fetch HBase security token.") + + val hbaseConf = confCreate.invoke(null, conf) + val token = obtainToken.invoke(null, hbaseConf).asInstanceOf[Token[TokenIdentifier]] + credentials.addToken(token.getService, token) + + logInfo("Added HBase security token to credentials.") + } catch { + case e:java.lang.NoSuchMethodException => + logInfo("HBase Method not found: " + e) + case e:java.lang.ClassNotFoundException => + logDebug("HBase Class not found: " + e) + case e:java.lang.NoClassDefFoundError => + logDebug("HBase Class not found: " + e) + case e:Exception => + logError("Exception when obtaining HBase security token: " + e) + } + } + } + /** * Return whether the two file systems are the same. */ diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala index 1423533470fc0..5653c9f14dc6d 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala @@ -42,6 +42,8 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) var amCores: Int = 1 var appName: String = "Spark" var priority = 0 + var principal: String = null + var keytab: String = null def isClusterMode: Boolean = userClass != null private var driverMemory: Int = 512 // MB @@ -231,6 +233,14 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) archives = value args = tail + case ("--principal") :: value :: tail => + principal = value + args = tail + + case ("--keytab") :: value :: tail => + keytab = value + args = tail + case Nil => case _ => diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorDelegationTokenUpdater.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorDelegationTokenUpdater.scala new file mode 100644 index 0000000000000..229c2c4d5eb36 --- /dev/null +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorDelegationTokenUpdater.scala @@ -0,0 +1,106 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.spark.deploy.yarn + +import java.util.concurrent.{Executors, TimeUnit} + +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.{FileSystem, Path} +import org.apache.hadoop.security.{Credentials, UserGroupInformation} + +import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.{Logging, SparkConf} +import org.apache.spark.util.{ThreadUtils, Utils} + +import scala.util.control.NonFatal + +private[spark] class ExecutorDelegationTokenUpdater( + sparkConf: SparkConf, + hadoopConf: Configuration) extends Logging { + + @volatile private var lastCredentialsFileSuffix = 0 + + private val credentialsFile = sparkConf.get("spark.yarn.credentials.file") + + private val delegationTokenRenewer = + Executors.newSingleThreadScheduledExecutor( + ThreadUtils.namedThreadFactory("Delegation Token Refresh Thread")) + + // On the executor, this thread wakes up and picks up new tokens from HDFS, if any. + private val executorUpdaterRunnable = + new Runnable { + override def run(): Unit = Utils.logUncaughtExceptions(updateCredentialsIfRequired()) + } + + def updateCredentialsIfRequired(): Unit = { + try { + val credentialsFilePath = new Path(credentialsFile) + val remoteFs = FileSystem.get(hadoopConf) + SparkHadoopUtil.get.listFilesSorted( + remoteFs, credentialsFilePath.getParent, + credentialsFilePath.getName, SparkHadoopUtil.SPARK_YARN_CREDS_TEMP_EXTENSION) + .lastOption.foreach { credentialsStatus => + val suffix = SparkHadoopUtil.get.getSuffixForCredentialsPath(credentialsStatus.getPath) + if (suffix > lastCredentialsFileSuffix) { + logInfo("Reading new delegation tokens from " + credentialsStatus.getPath) + val newCredentials = getCredentialsFromHDFSFile(remoteFs, credentialsStatus.getPath) + lastCredentialsFileSuffix = suffix + UserGroupInformation.getCurrentUser.addCredentials(newCredentials) + logInfo("Tokens updated from credentials file.") + } else { + // Check every hour to see if new credentials arrived. + logInfo("Updated delegation tokens were expected, but the driver has not updated the " + + "tokens yet, will check again in an hour.") + delegationTokenRenewer.schedule(executorUpdaterRunnable, 1, TimeUnit.HOURS) + return + } + } + val timeFromNowToRenewal = + SparkHadoopUtil.get.getTimeFromNowToRenewal( + sparkConf, 0.8, UserGroupInformation.getCurrentUser.getCredentials) + if (timeFromNowToRenewal <= 0) { + executorUpdaterRunnable.run() + } else { + logInfo(s"Scheduling token refresh from HDFS in $timeFromNowToRenewal millis.") + delegationTokenRenewer.schedule( + executorUpdaterRunnable, timeFromNowToRenewal, TimeUnit.MILLISECONDS) + } + } catch { + // Since the file may get deleted while we are reading it, catch the Exception and come + // back in an hour to try again + case NonFatal(e) => + logWarning("Error while trying to update credentials, will try again in 1 hour", e) + delegationTokenRenewer.schedule(executorUpdaterRunnable, 1, TimeUnit.HOURS) + } + } + + private def getCredentialsFromHDFSFile(remoteFs: FileSystem, tokenPath: Path): Credentials = { + val stream = remoteFs.open(tokenPath) + try { + val newCredentials = new Credentials() + newCredentials.readTokenStorageStream(stream) + newCredentials + } finally { + stream.close() + } + } + + def stop(): Unit = { + delegationTokenRenewer.shutdown() + } + +} diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala index 5881dc5ffa3ad..ba91872107d0c 100644 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala @@ -24,18 +24,19 @@ import java.util.regex.Pattern import scala.collection.mutable.HashMap import scala.util.Try +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.Path import org.apache.hadoop.io.Text -import org.apache.hadoop.mapred.JobConf +import org.apache.hadoop.mapred.{Master, JobConf} import org.apache.hadoop.security.Credentials import org.apache.hadoop.security.UserGroupInformation import org.apache.hadoop.yarn.conf.YarnConfiguration import org.apache.hadoop.yarn.api.ApplicationConstants import org.apache.hadoop.yarn.api.ApplicationConstants.Environment import org.apache.hadoop.yarn.api.records.{Priority, ApplicationAccessType} -import org.apache.hadoop.conf.Configuration -import org.apache.spark.{SecurityManager, SparkConf} import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.{SecurityManager, SparkConf, SparkException} import org.apache.spark.util.Utils /** @@ -43,6 +44,8 @@ import org.apache.spark.util.Utils */ class YarnSparkHadoopUtil extends SparkHadoopUtil { + private var tokenRenewer: Option[ExecutorDelegationTokenUpdater] = None + override def transferCredentials(source: UserGroupInformation, dest: UserGroupInformation) { dest.addCredentials(source.getCredentials()) } @@ -82,6 +85,57 @@ class YarnSparkHadoopUtil extends SparkHadoopUtil { if (credentials != null) credentials.getSecretKey(new Text(key)) else null } + /** + * Get the list of namenodes the user may access. + */ + def getNameNodesToAccess(sparkConf: SparkConf): Set[Path] = { + sparkConf.get("spark.yarn.access.namenodes", "") + .split(",") + .map(_.trim()) + .filter(!_.isEmpty) + .map(new Path(_)) + .toSet + } + + def getTokenRenewer(conf: Configuration): String = { + val delegTokenRenewer = Master.getMasterPrincipal(conf) + logDebug("delegation token renewer is: " + delegTokenRenewer) + if (delegTokenRenewer == null || delegTokenRenewer.length() == 0) { + val errorMessage = "Can't get Master Kerberos principal for use as renewer" + logError(errorMessage) + throw new SparkException(errorMessage) + } + delegTokenRenewer + } + + /** + * Obtains tokens for the namenodes passed in and adds them to the credentials. + */ + def obtainTokensForNamenodes( + paths: Set[Path], + conf: Configuration, + creds: Credentials, + renewer: Option[String] = None + ): Unit = { + if (UserGroupInformation.isSecurityEnabled()) { + val delegTokenRenewer = renewer.getOrElse(getTokenRenewer(conf)) + paths.foreach { dst => + val dstFs = dst.getFileSystem(conf) + logInfo("getting token for namenode: " + dst) + dstFs.addDelegationTokens(delegTokenRenewer, creds) + } + } + } + + private[spark] override def startExecutorDelegationTokenRenewer(sparkConf: SparkConf): Unit = { + tokenRenewer = Some(new ExecutorDelegationTokenUpdater(sparkConf, conf)) + tokenRenewer.get.updateCredentialsIfRequired() + } + + private[spark] override def stopExecutorDelegationTokenRenewer(): Unit = { + tokenRenewer.foreach(_.stop()) + } + } object YarnSparkHadoopUtil { @@ -100,6 +154,14 @@ object YarnSparkHadoopUtil { // request types (like map/reduce in hadoop for example) val RM_REQUEST_PRIORITY = Priority.newInstance(1) + def get: YarnSparkHadoopUtil = { + val yarnMode = java.lang.Boolean.valueOf( + System.getProperty("SPARK_YARN_MODE", System.getenv("SPARK_YARN_MODE"))) + if (!yarnMode) { + throw new SparkException("YarnSparkHadoopUtil is not available in non-YARN mode!") + } + SparkHadoopUtil.get.asInstanceOf[YarnSparkHadoopUtil] + } /** * Add a path variable to the given environment map. * If the map already contains this key, append the value to the existing value instead. @@ -212,3 +274,4 @@ object YarnSparkHadoopUtil { classPathSeparatorField.get(null).asInstanceOf[String] } } + diff --git a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala index b1de81e6a8b0f..aeb218a575455 100644 --- a/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala +++ b/yarn/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala @@ -39,12 +39,18 @@ private[spark] class YarnClusterSchedulerBackend( } override def applicationId(): String = - // In YARN Cluster mode, spark.yarn.app.id is expect to be set - // before user application is launched. - // So, if spark.yarn.app.id is not set, it is something wrong. + // In YARN Cluster mode, the application ID is expected to be set, so log an error if it's + // not found. sc.getConf.getOption("spark.yarn.app.id").getOrElse { logError("Application ID is not set.") super.applicationId } + override def applicationAttemptId(): Option[String] = + // In YARN Cluster mode, the attempt ID is expected to be set, so log an error if it's + // not found. + sc.getConf.getOption("spark.yarn.app.attemptId").orElse { + logError("Application attempt ID is not set.") + super.applicationAttemptId + } } diff --git a/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala b/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala index a51c2005cb472..508819e242a26 100644 --- a/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala +++ b/yarn/src/test/scala/org/apache/spark/deploy/yarn/ClientSuite.scala @@ -151,57 +151,6 @@ class ClientSuite extends FunSuite with Matchers with BeforeAndAfterAll { } } - test("check access nns empty") { - val sparkConf = new SparkConf() - sparkConf.set("spark.yarn.access.namenodes", "") - val nns = Client.getNameNodesToAccess(sparkConf) - nns should be(Set()) - } - - test("check access nns unset") { - val sparkConf = new SparkConf() - val nns = Client.getNameNodesToAccess(sparkConf) - nns should be(Set()) - } - - test("check access nns") { - val sparkConf = new SparkConf() - sparkConf.set("spark.yarn.access.namenodes", "hdfs://nn1:8032") - val nns = Client.getNameNodesToAccess(sparkConf) - nns should be(Set(new Path("hdfs://nn1:8032"))) - } - - test("check access nns space") { - val sparkConf = new SparkConf() - sparkConf.set("spark.yarn.access.namenodes", "hdfs://nn1:8032, ") - val nns = Client.getNameNodesToAccess(sparkConf) - nns should be(Set(new Path("hdfs://nn1:8032"))) - } - - test("check access two nns") { - val sparkConf = new SparkConf() - sparkConf.set("spark.yarn.access.namenodes", "hdfs://nn1:8032,hdfs://nn2:8032") - val nns = Client.getNameNodesToAccess(sparkConf) - nns should be(Set(new Path("hdfs://nn1:8032"), new Path("hdfs://nn2:8032"))) - } - - test("check token renewer") { - val hadoopConf = new Configuration() - hadoopConf.set("yarn.resourcemanager.address", "myrm:8033") - hadoopConf.set("yarn.resourcemanager.principal", "yarn/myrm:8032@SPARKTEST.COM") - val renewer = Client.getTokenRenewer(hadoopConf) - renewer should be ("yarn/myrm:8032@SPARKTEST.COM") - } - - test("check token renewer default") { - val hadoopConf = new Configuration() - val caught = - intercept[SparkException] { - Client.getTokenRenewer(hadoopConf) - } - assert(caught.getMessage === "Can't get Master Kerberos principal for use as renewer") - } - object Fixtures { val knownDefYarnAppCP: Seq[String] = diff --git a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala index 3877da4120e7c..d3c606e0ed998 100644 --- a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala +++ b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnClusterSuite.scala @@ -86,6 +86,7 @@ class YarnClusterSuite extends FunSuite with BeforeAndAfterAll with Matchers wit tempDir = Utils.createTempDir() logConfDir = new File(tempDir, "log4j") logConfDir.mkdir() + System.setProperty("SPARK_YARN_MODE", "true") val logConfFile = new File(logConfDir, "log4j.properties") Files.write(LOG4J_CONF, logConfFile, UTF_8) @@ -128,6 +129,7 @@ class YarnClusterSuite extends FunSuite with BeforeAndAfterAll with Matchers wit override def afterAll() { yarnCluster.stop() + System.clearProperty("SPARK_YARN_MODE") super.afterAll() } diff --git a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala index 9395316b71ff4..e10b985c3c236 100644 --- a/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala +++ b/yarn/src/test/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtilSuite.scala @@ -20,6 +20,8 @@ package org.apache.spark.deploy.yarn import java.io.{File, IOException} import com.google.common.io.{ByteStreams, Files} +import org.apache.hadoop.conf.Configuration +import org.apache.hadoop.fs.Path import org.apache.hadoop.yarn.api.ApplicationConstants import org.apache.hadoop.yarn.api.ApplicationConstants.Environment import org.apache.hadoop.yarn.conf.YarnConfiguration @@ -27,7 +29,7 @@ import org.scalatest.{FunSuite, Matchers} import org.apache.hadoop.yarn.api.records.ApplicationAccessType -import org.apache.spark.{Logging, SecurityManager, SparkConf} +import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkException} import org.apache.spark.util.Utils @@ -173,4 +175,62 @@ class YarnSparkHadoopUtilSuite extends FunSuite with Matchers with Logging { YarnSparkHadoopUtil.getClassPathSeparator() should be (":") } } + + test("check access nns empty") { + val sparkConf = new SparkConf() + val util = new YarnSparkHadoopUtil + sparkConf.set("spark.yarn.access.namenodes", "") + val nns = util.getNameNodesToAccess(sparkConf) + nns should be(Set()) + } + + test("check access nns unset") { + val sparkConf = new SparkConf() + val util = new YarnSparkHadoopUtil + val nns = util.getNameNodesToAccess(sparkConf) + nns should be(Set()) + } + + test("check access nns") { + val sparkConf = new SparkConf() + sparkConf.set("spark.yarn.access.namenodes", "hdfs://nn1:8032") + val util = new YarnSparkHadoopUtil + val nns = util.getNameNodesToAccess(sparkConf) + nns should be(Set(new Path("hdfs://nn1:8032"))) + } + + test("check access nns space") { + val sparkConf = new SparkConf() + sparkConf.set("spark.yarn.access.namenodes", "hdfs://nn1:8032, ") + val util = new YarnSparkHadoopUtil + val nns = util.getNameNodesToAccess(sparkConf) + nns should be(Set(new Path("hdfs://nn1:8032"))) + } + + test("check access two nns") { + val sparkConf = new SparkConf() + sparkConf.set("spark.yarn.access.namenodes", "hdfs://nn1:8032,hdfs://nn2:8032") + val util = new YarnSparkHadoopUtil + val nns = util.getNameNodesToAccess(sparkConf) + nns should be(Set(new Path("hdfs://nn1:8032"), new Path("hdfs://nn2:8032"))) + } + + test("check token renewer") { + val hadoopConf = new Configuration() + hadoopConf.set("yarn.resourcemanager.address", "myrm:8033") + hadoopConf.set("yarn.resourcemanager.principal", "yarn/myrm:8032@SPARKTEST.COM") + val util = new YarnSparkHadoopUtil + val renewer = util.getTokenRenewer(hadoopConf) + renewer should be ("yarn/myrm:8032@SPARKTEST.COM") + } + + test("check token renewer default") { + val hadoopConf = new Configuration() + val util = new YarnSparkHadoopUtil + val caught = + intercept[SparkException] { + util.getTokenRenewer(hadoopConf) + } + assert(caught.getMessage === "Can't get Master Kerberos principal for use as renewer") + } }