From ba49eb1625b1190d8aaf2c55dc1f6309ac3e080c Mon Sep 17 00:00:00 2001 From: DB Tsai Date: Wed, 29 Apr 2015 21:44:41 -0700 Subject: [PATCH 01/33] Some code clean up. Author: DB Tsai Closes #5794 from dbtsai/clean and squashes the following commits: ad639dd [DB Tsai] Indentation 834d527 [DB Tsai] Some code clean up. --- .../spark/mllib/util/LinearDataGenerator.scala | 17 ++++++++--------- 1 file changed, 8 insertions(+), 9 deletions(-) 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 91c2f4ccd3d17..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)} /** @@ -105,13 +105,12 @@ object LinearDataGenerator { val x = Array.fill[Array[Double]](nPoints)( Array.fill[Double](weights.length)(rnd.nextDouble())) - x.foreach { - case v => - var i = 0 - while (i < v.length) { - v(i) = (v(i) - 0.5) * math.sqrt(12.0 * xVariance(i)) + xMean(i) - i += 1 - } + x.foreach { v => + var i = 0 + 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 => From 4459514497eb76e6f2465d071857854390453805 Mon Sep 17 00:00:00 2001 From: Zhongshuai Pei <799203320@qq.com> Date: Wed, 29 Apr 2015 22:44:14 -0700 Subject: [PATCH 02/33] [SPARK-7225][SQL] CombineLimits optimizer does not work SQL ``` select key from (select key from src limit 100) t2 limit 10 ``` Optimized Logical Plan before modifying ``` == Optimized Logical Plan == Limit 10 Limit 100 Project key#3 MetastoreRelation default, src, None ``` Optimized Logical Plan after modifying ``` == Optimized Logical Plan == Limit 10 Project [key#1] MetastoreRelation default, src, None ``` Author: Zhongshuai Pei <799203320@qq.com> Author: DoingDone9 <799203320@qq.com> Closes #5770 from DoingDone9/limitOptimizer and squashes the following commits: c68eaa7 [Zhongshuai Pei] Update CombiningLimitsSuite.scala 97e18cf [Zhongshuai Pei] Update Optimizer.scala 19ab875 [Zhongshuai Pei] Update CombiningLimitsSuite.scala 7db4566 [Zhongshuai Pei] Update CombiningLimitsSuite.scala e2a491d [Zhongshuai Pei] Update Optimizer.scala f03fe7f [Zhongshuai Pei] Merge pull request #12 from apache/master f12fa50 [Zhongshuai Pei] Merge pull request #10 from apache/master f61210c [Zhongshuai Pei] Merge pull request #9 from apache/master 34b1a9a [Zhongshuai Pei] Merge pull request #8 from apache/master 802261c [DoingDone9] Merge pull request #7 from apache/master d00303b [DoingDone9] Merge pull request #6 from apache/master 98b134f [DoingDone9] Merge pull request #5 from apache/master 161cae3 [DoingDone9] Merge pull request #4 from apache/master c87e8b6 [DoingDone9] Merge pull request #3 from apache/master cb1852d [DoingDone9] Merge pull request #2 from apache/master c3f046f [DoingDone9] Merge pull request #1 from apache/master --- .../sql/catalyst/optimizer/Optimizer.scala | 15 +++++++-------- .../optimizer/CombiningLimitsSuite.scala | 19 +++++++++++++++++++ 2 files changed, 26 insertions(+), 8 deletions(-) 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..485761dd8538b 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 } 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) + } } From 254e0509762937acc9c72b432d5d953bf72c3c52 Mon Sep 17 00:00:00 2001 From: Vincenzo Selvaggio Date: Wed, 29 Apr 2015 23:21:21 -0700 Subject: [PATCH 03/33] [SPARK-1406] Mllib pmml model export See PDF attached to the JIRA issue 1406. The contribution is my original work and I license the work to the project under the project's open source license. Author: Vincenzo Selvaggio Author: Xiangrui Meng Author: selvinsource Closes #3062 from selvinsource/mllib_pmml_model_export_SPARK-1406 and squashes the following commits: 852aac6 [Vincenzo Selvaggio] [SPARK-1406] Update JPMML version to 1.1.15 in LICENSE file 085cf42 [Vincenzo Selvaggio] [SPARK-1406] Added Double Min and Max Fixed scala style 30165c4 [Vincenzo Selvaggio] [SPARK-1406] Fixed extreme cases for logit 7a5e0ec [Vincenzo Selvaggio] [SPARK-1406] Binary classification for SVM and Logistic Regression cfcb596 [Vincenzo Selvaggio] [SPARK-1406] Throw IllegalArgumentException when exporting a multinomial logistic regression 25dce33 [Vincenzo Selvaggio] [SPARK-1406] Update code to latest pmml model dea98ca [Vincenzo Selvaggio] [SPARK-1406] Exclude transitive dependency for pmml model 66b7c12 [Vincenzo Selvaggio] [SPARK-1406] Updated pmml model lib to 1.1.15, latest Java 6 compatible a0a55f7 [Vincenzo Selvaggio] Merge pull request #2 from mengxr/SPARK-1406 3c22f79 [Xiangrui Meng] more code style e2313df [Vincenzo Selvaggio] Merge pull request #1 from mengxr/SPARK-1406 472d757 [Xiangrui Meng] fix code style 1676e15 [Vincenzo Selvaggio] fixed scala issue e2ffae8 [Vincenzo Selvaggio] fixed scala style b8823b0 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406 b25bbf7 [Vincenzo Selvaggio] [SPARK-1406] Added export of pmml to distributed file system using the spark context 7a949d0 [Vincenzo Selvaggio] [SPARK-1406] Fixed scala style f46c75c [Vincenzo Selvaggio] [SPARK-1406] Added PMMLExportable to supported models 7b33b4e [Vincenzo Selvaggio] [SPARK-1406] Added a PMMLExportable interface Restructured code in a new package mllib.pmml Supported models implements the new PMMLExportable interface: LogisticRegression, SVM, KMeansModel, LinearRegression, RidgeRegression, Lasso d559ec5 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406 8fe12bb [Vincenzo Selvaggio] [SPARK-1406] Adjusted logistic regression export description and target categories 03bc3a5 [Vincenzo Selvaggio] added logistic regression da2ec11 [Vincenzo Selvaggio] [SPARK-1406] added linear SVM PMML export 82f2131 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406 19adf29 [Vincenzo Selvaggio] [SPARK-1406] Fixed scala style 1faf985 [Vincenzo Selvaggio] [SPARK-1406] Added target field to the regression model for completeness Adjusted unit test to deal with this change 3ae8ae5 [Vincenzo Selvaggio] [SPARK-1406] Adjusted imported order according to the guidelines c67ce81 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406 78515ec [Vincenzo Selvaggio] [SPARK-1406] added pmml export for LinearRegressionModel, RidgeRegressionModel and LassoModel e29dfb9 [Vincenzo Selvaggio] removed version, by default is set to 4.2 (latest from jpmml) removed copyright ae8b993 [Vincenzo Selvaggio] updated some commented tests to use the new ModelExporter object reordered the imports df8a89e [Vincenzo Selvaggio] added pmml version to pmml model changed the copyright to spark a1b4dc3 [Vincenzo Selvaggio] updated imports 834ca44 [Vincenzo Selvaggio] reordered the import accordingly to the guidelines 349a76b [Vincenzo Selvaggio] new helper object to serialize the models to pmml format c3ef9b8 [Vincenzo Selvaggio] set it to private 6357b98 [Vincenzo Selvaggio] set it to private e1eb251 [Vincenzo Selvaggio] removed serialization part, this will be part of the ModelExporter helper object aba5ee1 [Vincenzo Selvaggio] fixed cluster export cd6c07c [Vincenzo Selvaggio] fixed scala style to run tests f75b988 [Vincenzo Selvaggio] Merge remote-tracking branch 'origin/master' into mllib_pmml_model_export_SPARK-1406 07a29bf [selvinsource] Update LICENSE 8841439 [Vincenzo Selvaggio] adjust scala style in order to compile 1433b11 [Vincenzo Selvaggio] complete suite tests 8e71b8d [Vincenzo Selvaggio] kmeans pmml export implementation 9bc494f [Vincenzo Selvaggio] added scala suite tests added saveLocalFile to ModelExport trait 226e184 [Vincenzo Selvaggio] added javadoc and export model type in case there is a need to support other types of export (not just PMML) a0e3679 [Vincenzo Selvaggio] export and pmml export traits kmeans test implementation --- LICENSE | 1 + mllib/pom.xml | 15 +++ .../classification/LogisticRegression.scala | 3 +- .../spark/mllib/classification/SVM.scala | 3 +- .../spark/mllib/clustering/KMeansModel.scala | 4 +- .../spark/mllib/pmml/PMMLExportable.scala | 74 +++++++++++++++ .../BinaryClassificationPMMLModelExport.scala | 90 ++++++++++++++++++ .../GeneralizedLinearPMMLModelExport.scala | 75 +++++++++++++++ .../pmml/export/KMeansPMMLModelExport.scala | 83 ++++++++++++++++ .../mllib/pmml/export/PMMLModelExport.scala | 47 +++++++++ .../pmml/export/PMMLModelExportFactory.scala | 64 +++++++++++++ .../apache/spark/mllib/regression/Lasso.scala | 3 +- .../mllib/regression/LinearRegression.scala | 3 +- .../mllib/regression/RidgeRegression.scala | 3 +- ...ryClassificationPMMLModelExportSuite.scala | 84 ++++++++++++++++ ...eneralizedLinearPMMLModelExportSuite.scala | 84 ++++++++++++++++ .../export/KMeansPMMLModelExportSuite.scala | 49 ++++++++++ .../export/PMMLModelExportFactorySuite.scala | 95 +++++++++++++++++++ 18 files changed, 774 insertions(+), 6 deletions(-) create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExport.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExport.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExport.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExport.scala create mode 100644 mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactory.scala create mode 100644 mllib/src/test/scala/org/apache/spark/mllib/pmml/export/BinaryClassificationPMMLModelExportSuite.scala create mode 100644 mllib/src/test/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExportSuite.scala create mode 100644 mllib/src/test/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExportSuite.scala create mode 100644 mllib/src/test/scala/org/apache/spark/mllib/pmml/export/PMMLModelExportFactorySuite.scala 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/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/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/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/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/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) + } + } +} From 47bf406d608c4777f5f383ba439608f673034a1d Mon Sep 17 00:00:00 2001 From: Patrick Wendell Date: Thu, 30 Apr 2015 01:02:33 -0700 Subject: [PATCH 04/33] [HOTFIX] Disabling flaky test (fix in progress as part of SPARK-7224) --- .../test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) 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( From 7dacc08ab36188991a001df23880167433844767 Mon Sep 17 00:00:00 2001 From: Burak Yavuz Date: Thu, 30 Apr 2015 10:19:08 -0700 Subject: [PATCH 05/33] [SPARK-7224] added mock repository generator for --packages tests This patch contains an `IvyTestUtils` file, which dynamically generates jars and pom files to test the `--packages` feature without having to rely on the internet, and Maven Central. cc pwendell I know that there existed Util functions to create Jars and stuff already, but they didn't really serve my purposes as they appended random prefixes that was breaking things. I also added the local repository tests. Notice that they work without passing the `repo` to `resolveMavenCoordinates`. Author: Burak Yavuz Closes #5790 from brkyvz/maven-utils and squashes the following commits: 3ec79b7 [Burak Yavuz] addressed comments v0.2 a39151b [Burak Yavuz] address comments v0.1 172dfef [Burak Yavuz] use Ivy format 7476d06 [Burak Yavuz] added mock repository generator --- .../scala/org/apache/spark/TestUtils.scala | 27 +- .../org/apache/spark/deploy/SparkSubmit.scala | 129 +++++---- .../apache/spark/deploy/IvyTestUtils.scala | 262 ++++++++++++++++++ .../spark/deploy/SparkSubmitSuite.scala | 25 +- .../spark/deploy/SparkSubmitUtilsSuite.scala | 57 ++-- 5 files changed, 403 insertions(+), 97 deletions(-) create mode 100644 core/src/test/scala/org/apache/spark/deploy/IvyTestUtils.scala diff --git a/core/src/main/scala/org/apache/spark/TestUtils.scala b/core/src/main/scala/org/apache/spark/TestUtils.scala index 398ca41e16151..fe6320b504e15 100644 --- a/core/src/main/scala/org/apache/spark/TestUtils.scala +++ b/core/src/main/scala/org/apache/spark/TestUtils.scala @@ -105,23 +105,18 @@ private[spark] object TestUtils { URI.create(s"string:///${name.replace(".", "/")}${SOURCE.extension}") } - private class JavaSourceFromString(val name: String, val code: String) + private[spark] class JavaSourceFromString(val name: String, val code: String) extends SimpleJavaFileObject(createURI(name), SOURCE) { override def getCharContent(ignoreEncodingErrors: Boolean): String = code } - /** Creates a compiled class with the given name. Class file will be placed in destDir. */ + /** Creates a compiled class with the source file. Class file will be placed in destDir. */ def createCompiledClass( className: String, destDir: File, - toStringValue: String = "", - baseClass: String = null, - classpathUrls: Seq[URL] = Seq()): File = { + sourceFile: JavaSourceFromString, + classpathUrls: Seq[URL]): File = { val compiler = ToolProvider.getSystemJavaCompiler - val extendsText = Option(baseClass).map { c => s" extends ${c}" }.getOrElse("") - val sourceFile = new JavaSourceFromString(className, - "public class " + className + extendsText + " implements java.io.Serializable {" + - " @Override public String toString() { return \"" + toStringValue + "\"; }}") // Calling this outputs a class file in pwd. It's easier to just rename the file than // build a custom FileManager that controls the output location. @@ -144,4 +139,18 @@ private[spark] object TestUtils { assert(out.exists(), "Destination file not moved: " + out.getAbsolutePath()) out } + + /** Creates a compiled class with the given name. Class file will be placed in destDir. */ + def createCompiledClass( + className: String, + destDir: File, + toStringValue: String = "", + baseClass: String = null, + classpathUrls: Seq[URL] = Seq()): File = { + val extendsText = Option(baseClass).map { c => s" extends ${c}" }.getOrElse("") + val sourceFile = new JavaSourceFromString(className, + "public class " + className + extendsText + " implements java.io.Serializable {" + + " @Override public String toString() { return \"" + toStringValue + "\"; }}") + createCompiledClass(className, destDir, sourceFile, classpathUrls) + } } diff --git a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala index b8ae4af18d1d1..0d149e703aff2 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala @@ -20,6 +20,7 @@ package org.apache.spark.deploy import java.io.{File, PrintStream} import java.lang.reflect.{InvocationTargetException, Modifier, UndeclaredThrowableException} import java.net.URL +import java.nio.file.{Path => JavaPath} import java.security.PrivilegedExceptionAction import scala.collection.mutable.{ArrayBuffer, HashMap, Map} @@ -708,7 +709,9 @@ private[deploy] object SparkSubmitUtils { * @param artifactId the artifactId of the coordinate * @param version the version of the coordinate */ - private[deploy] case class MavenCoordinate(groupId: String, artifactId: String, version: String) + private[deploy] case class MavenCoordinate(groupId: String, artifactId: String, version: String) { + override def toString: String = s"$groupId:$artifactId:$version" + } /** * Extracts maven coordinates from a comma-delimited string. Coordinates should be provided @@ -731,6 +734,10 @@ private[deploy] object SparkSubmitUtils { } } + /** Path of the local Maven cache. */ + private[spark] def m2Path: JavaPath = new File(System.getProperty("user.home"), + ".m2" + File.separator + "repository" + File.separator).toPath + /** * Extracts maven coordinates from a comma-delimited string * @param remoteRepos Comma-delimited string of remote repositories @@ -744,8 +751,7 @@ private[deploy] object SparkSubmitUtils { 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.setRoot(m2Path.toUri.toString) localM2.setUsepoms(true) localM2.setName("local-m2-cache") cr.add(localM2) @@ -870,69 +876,72 @@ private[deploy] object SparkSubmitUtils { "" } else { val sysOut = System.out - // To prevent ivy from logging to system out - System.setOut(printStream) - val artifacts = extractMavenCoordinates(coordinates) - // Default configuration name for ivy - val ivyConfName = "default" - // set ivy settings for location of cache - val ivySettings: IvySettings = new IvySettings - // Directories for caching downloads through ivy and storing the jars when maven coordinates - // are supplied to spark-submit - val alternateIvyCache = ivyPath.getOrElse("") - val packagesDirectory: File = - if (alternateIvyCache.trim.isEmpty) { - new File(ivySettings.getDefaultIvyUserDir, "jars") + try { + // To prevent ivy from logging to system out + System.setOut(printStream) + val artifacts = extractMavenCoordinates(coordinates) + // Default configuration name for ivy + val ivyConfName = "default" + // set ivy settings for location of cache + val ivySettings: IvySettings = new IvySettings + // Directories for caching downloads through ivy and storing the jars when maven coordinates + // are supplied to spark-submit + val alternateIvyCache = ivyPath.getOrElse("") + val packagesDirectory: File = + 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") + } + printStream.println( + s"Ivy Default Cache set to: ${ivySettings.getDefaultCache.getAbsolutePath}") + printStream.println(s"The jars for the packages stored in: $packagesDirectory") + // create a pattern matcher + ivySettings.addMatcher(new GlobPatternMatcher) + // create the dependency resolvers + val repoResolver = createRepoResolvers(remoteRepos, ivySettings) + ivySettings.addResolver(repoResolver) + ivySettings.setDefaultResolver(repoResolver.getName) + + val ivy = Ivy.newInstance(ivySettings) + // Set resolve options to download transitive dependencies as well + val resolveOptions = new ResolveOptions + resolveOptions.setTransitive(true) + val retrieveOptions = new RetrieveOptions + // Turn downloading and logging off for testing + if (isTest) { + resolveOptions.setDownload(false) + resolveOptions.setLog(LogOptions.LOG_QUIET) + retrieveOptions.setLog(LogOptions.LOG_QUIET) } else { - ivySettings.setDefaultIvyUserDir(new File(alternateIvyCache)) - ivySettings.setDefaultCache(new File(alternateIvyCache, "cache")) - new File(alternateIvyCache, "jars") + resolveOptions.setDownload(true) } - printStream.println( - s"Ivy Default Cache set to: ${ivySettings.getDefaultCache.getAbsolutePath}") - printStream.println(s"The jars for the packages stored in: $packagesDirectory") - // create a pattern matcher - ivySettings.addMatcher(new GlobPatternMatcher) - // create the dependency resolvers - val repoResolver = createRepoResolvers(remoteRepos, ivySettings) - ivySettings.addResolver(repoResolver) - ivySettings.setDefaultResolver(repoResolver.getName) - - val ivy = Ivy.newInstance(ivySettings) - // Set resolve options to download transitive dependencies as well - val resolveOptions = new ResolveOptions - resolveOptions.setTransitive(true) - val retrieveOptions = new RetrieveOptions - // Turn downloading and logging off for testing - if (isTest) { - resolveOptions.setDownload(false) - resolveOptions.setLog(LogOptions.LOG_QUIET) - retrieveOptions.setLog(LogOptions.LOG_QUIET) - } else { - resolveOptions.setDownload(true) - } - // A Module descriptor must be specified. Entries are dummy strings - val md = getModuleDescriptor - md.setDefaultConf(ivyConfName) + // A Module descriptor must be specified. Entries are dummy strings + val md = getModuleDescriptor + md.setDefaultConf(ivyConfName) - // Add exclusion rules for Spark and Scala Library - addExclusionRules(ivySettings, ivyConfName, md) - // add all supplied maven artifacts as dependencies - addDependenciesToIvy(md, artifacts, ivyConfName) + // Add exclusion rules for Spark and Scala Library + addExclusionRules(ivySettings, ivyConfName, md) + // add all supplied maven artifacts as dependencies + addDependenciesToIvy(md, artifacts, ivyConfName) - // resolve dependencies - val rr: ResolveReport = ivy.resolve(md, resolveOptions) - if (rr.hasError) { - throw new RuntimeException(rr.getAllProblemMessages.toString) + // resolve dependencies + val rr: ResolveReport = ivy.resolve(md, resolveOptions) + if (rr.hasError) { + throw new RuntimeException(rr.getAllProblemMessages.toString) + } + // retrieve all resolved dependencies + ivy.retrieve(rr.getModuleDescriptor.getModuleRevisionId, + packagesDirectory.getAbsolutePath + File.separator + + "[organization]_[artifact]-[revision].[ext]", + retrieveOptions.setConfs(Array(ivyConfName))) + resolveDependencyPaths(rr.getArtifacts.toArray, packagesDirectory) + } finally { + System.setOut(sysOut) } - // retrieve all resolved dependencies - ivy.retrieve(rr.getModuleDescriptor.getModuleRevisionId, - 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/test/scala/org/apache/spark/deploy/IvyTestUtils.scala b/core/src/test/scala/org/apache/spark/deploy/IvyTestUtils.scala new file mode 100644 index 0000000000000..529f91e8eaf9e --- /dev/null +++ b/core/src/test/scala/org/apache/spark/deploy/IvyTestUtils.scala @@ -0,0 +1,262 @@ +/* + * 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 + +import java.io.{File, FileInputStream, FileOutputStream} +import java.nio.file.{Files, Path} +import java.util.jar.{JarEntry, JarOutputStream} + +import org.apache.spark.TestUtils.{createCompiledClass, JavaSourceFromString} + +import com.google.common.io.ByteStreams + +import org.apache.commons.io.FileUtils + +import org.apache.spark.deploy.SparkSubmitUtils.MavenCoordinate + +private[deploy] object IvyTestUtils { + + /** + * Create the path for the jar and pom from the maven coordinate. Extension should be `jar` + * or `pom`. + */ + private def pathFromCoordinate( + artifact: MavenCoordinate, + prefix: Path, + ext: String, + useIvyLayout: Boolean): Path = { + val groupDirs = artifact.groupId.replace(".", File.separator) + val artifactDirs = artifact.artifactId + val artifactPath = + if (!useIvyLayout) { + Seq(groupDirs, artifactDirs, artifact.version).mkString(File.separator) + } else { + Seq(groupDirs, artifactDirs, artifact.version, ext + "s").mkString(File.separator) + } + new File(prefix.toFile, artifactPath).toPath + } + + private def artifactName(artifact: MavenCoordinate, ext: String = ".jar"): String = { + s"${artifact.artifactId}-${artifact.version}$ext" + } + + /** Write the contents to a file to the supplied directory. */ + private def writeFile(dir: File, fileName: String, contents: String): File = { + val outputFile = new File(dir, fileName) + val outputStream = new FileOutputStream(outputFile) + outputStream.write(contents.toCharArray.map(_.toByte)) + outputStream.close() + outputFile + } + + /** Create an example Python file. */ + private def createPythonFile(dir: File): File = { + val contents = + """def myfunc(x): + | return x + 1 + """.stripMargin + writeFile(dir, "mylib.py", contents) + } + + /** Create a simple testable Class. */ + private def createJavaClass(dir: File, className: String, packageName: String): File = { + val contents = + s"""package $packageName; + | + |import java.lang.Integer; + | + |class $className implements java.io.Serializable { + | + | public $className() {} + | + | public Integer myFunc(Integer x) { + | return x + 1; + | } + |} + """.stripMargin + val sourceFile = + new JavaSourceFromString(new File(dir, className + ".java").getAbsolutePath, contents) + createCompiledClass(className, dir, sourceFile, Seq.empty) + } + + /** Helper method to write artifact information in the pom. */ + private def pomArtifactWriter(artifact: MavenCoordinate, tabCount: Int = 1): String = { + var result = "\n" + " " * tabCount + s"${artifact.groupId}" + result += "\n" + " " * tabCount + s"${artifact.artifactId}" + result += "\n" + " " * tabCount + s"${artifact.version}" + result + } + + /** Create a pom file for this artifact. */ + private def createPom( + dir: File, + artifact: MavenCoordinate, + dependencies: Option[Seq[MavenCoordinate]]): File = { + var content = """ + | + | + | 4.0.0 + """.stripMargin.trim + content += pomArtifactWriter(artifact) + content += dependencies.map { deps => + val inside = deps.map { dep => + "\t" + pomArtifactWriter(dep, 3) + "\n\t" + }.mkString("\n") + "\n \n" + inside + "\n " + }.getOrElse("") + content += "\n" + writeFile(dir, artifactName(artifact, ".pom"), content.trim) + } + + /** Create the jar for the given maven coordinate, using the supplied files. */ + private def packJar( + dir: File, + artifact: MavenCoordinate, + files: Seq[(String, File)]): File = { + val jarFile = new File(dir, artifactName(artifact)) + val jarFileStream = new FileOutputStream(jarFile) + val jarStream = new JarOutputStream(jarFileStream, new java.util.jar.Manifest()) + + for (file <- files) { + val jarEntry = new JarEntry(file._1) + jarStream.putNextEntry(jarEntry) + + val in = new FileInputStream(file._2) + ByteStreams.copy(in, jarStream) + in.close() + } + jarStream.close() + jarFileStream.close() + + jarFile + } + + /** + * Creates a jar and pom file, mocking a Maven repository. The root path can be supplied with + * `tempDir`, dependencies can be created into the same repo, and python files can also be packed + * inside the jar. + * + * @param artifact The maven coordinate to generate the jar and pom for. + * @param dependencies List of dependencies this artifact might have to also create jars and poms. + * @param tempDir The root folder of the repository + * @param useIvyLayout whether to mock the Ivy layout for local repository testing + * @param withPython Whether to pack python files inside the jar for extensive testing. + * @return Root path of the repository + */ + private def createLocalRepository( + artifact: MavenCoordinate, + dependencies: Option[Seq[MavenCoordinate]] = None, + tempDir: Option[Path] = None, + useIvyLayout: Boolean = false, + withPython: Boolean = false): Path = { + // Where the root of the repository exists, and what Ivy will search in + val tempPath = tempDir.getOrElse(Files.createTempDirectory(null)) + // Create directory if it doesn't exist + Files.createDirectories(tempPath) + // Where to create temporary class files and such + val root = Files.createTempDirectory(tempPath, null).toFile + try { + val jarPath = pathFromCoordinate(artifact, tempPath, "jar", useIvyLayout) + Files.createDirectories(jarPath) + val className = "MyLib" + + val javaClass = createJavaClass(root, className, artifact.groupId) + // A tuple of files representation in the jar, and the file + val javaFile = (artifact.groupId.replace(".", "/") + "/" + javaClass.getName, javaClass) + val allFiles = + if (withPython) { + val pythonFile = createPythonFile(root) + Seq(javaFile, (pythonFile.getName, pythonFile)) + } else { + Seq(javaFile) + } + val jarFile = packJar(jarPath.toFile, artifact, allFiles) + assert(jarFile.exists(), "Problem creating Jar file") + val pomPath = pathFromCoordinate(artifact, tempPath, "pom", useIvyLayout) + Files.createDirectories(pomPath) + val pomFile = createPom(pomPath.toFile, artifact, dependencies) + assert(pomFile.exists(), "Problem creating Pom file") + } finally { + FileUtils.deleteDirectory(root) + } + tempPath + } + + /** + * Creates a suite of jars and poms, with or without dependencies, mocking a maven repository. + * @param artifact The main maven coordinate to generate the jar and pom for. + * @param dependencies List of dependencies this artifact might have to also create jars and poms. + * @param rootDir The root folder of the repository (like `~/.m2/repositories`) + * @param useIvyLayout whether to mock the Ivy layout for local repository testing + * @param withPython Whether to pack python files inside the jar for extensive testing. + * @return Root path of the repository. Will be `rootDir` if supplied. + */ + private[deploy] def createLocalRepositoryForTests( + artifact: MavenCoordinate, + dependencies: Option[String], + rootDir: Option[Path], + useIvyLayout: Boolean = false, + withPython: Boolean = false): Path = { + val deps = dependencies.map(SparkSubmitUtils.extractMavenCoordinates) + val mainRepo = createLocalRepository(artifact, deps, rootDir, useIvyLayout, withPython) + deps.foreach { seq => seq.foreach { dep => + createLocalRepository(dep, None, Some(mainRepo), useIvyLayout, withPython = false) + }} + mainRepo + } + + /** + * Creates a repository for a test, and cleans it up afterwards. + * + * @param artifact The main maven coordinate to generate the jar and pom for. + * @param dependencies List of dependencies this artifact might have to also create jars and poms. + * @param rootDir The root folder of the repository (like `~/.m2/repositories`) + * @param useIvyLayout whether to mock the Ivy layout for local repository testing + * @param withPython Whether to pack python files inside the jar for extensive testing. + * @return Root path of the repository. Will be `rootDir` if supplied. + */ + private[deploy] def withRepository( + artifact: MavenCoordinate, + dependencies: Option[String], + rootDir: Option[Path], + useIvyLayout: Boolean = false, + withPython: Boolean = false)(f: String => Unit): Unit = { + val repo = createLocalRepositoryForTests(artifact, dependencies, rootDir, useIvyLayout, + withPython) + try { + f(repo.toUri.toString) + } finally { + // Clean up + if (repo.toString.contains(".m2") || repo.toString.contains(".ivy2")) { + FileUtils.deleteDirectory(new File(repo.toFile, + artifact.groupId.replace(".", File.separator) + File.separator + artifact.artifactId)) + dependencies.map(SparkSubmitUtils.extractMavenCoordinates).foreach { seq => + seq.foreach { dep => + FileUtils.deleteDirectory(new File(repo.toFile, + dep.artifactId.replace(".", File.separator))) + } + } + } else { + FileUtils.deleteDirectory(repo.toFile) + } + } + } +} 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 029a1156fda6b..8360b94599547 100644 --- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala @@ -30,6 +30,7 @@ import org.scalatest.time.SpanSugar._ import org.apache.spark._ import org.apache.spark.deploy.SparkSubmit._ +import org.apache.spark.deploy.SparkSubmitUtils.MavenCoordinate import org.apache.spark.util.{ResetSystemProperties, Utils} // Note: this suite mixes in ResetSystemProperties because SparkSubmit.main() sets a bunch @@ -336,16 +337,20 @@ class SparkSubmitSuite extends FunSuite with Matchers with ResetSystemProperties 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( - "--class", JarCreationTest.getClass.getName.stripSuffix("$"), - "--name", "testApp", - "--master", "local-cluster[2,1,512]", - "--packages", packagesString, - "--conf", "spark.ui.enabled=false", - unusedJar.toString, - "com.databricks.spark.csv.DefaultSource", "com.databricks.spark.avro.DefaultSource") - runSparkSubmit(args) + val main = MavenCoordinate("my.great.lib", "mylib", "0.1") + val dep = MavenCoordinate("my.great.dep", "mylib", "0.1") + IvyTestUtils.withRepository(main, Some(dep.toString), None) { repo => + val args = Seq( + "--class", JarCreationTest.getClass.getName.stripSuffix("$"), + "--name", "testApp", + "--master", "local-cluster[2,1,512]", + "--packages", Seq(main, dep).mkString(","), + "--repositories", repo, + "--conf", "spark.ui.enabled=false", + unusedJar.toString, + "my.great.lib.MyLib", "my.great.dep.MyLib") + runSparkSubmit(args) + } } test("resolves command line argument paths correctly") { 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 1b2b699cb11e6..cc79ee7ea20b4 100644 --- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitUtilsSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitUtilsSuite.scala @@ -19,15 +19,15 @@ 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} import org.apache.ivy.core.module.descriptor.MDArtifact +import org.apache.ivy.core.settings.IvySettings import org.apache.ivy.plugins.resolver.IBiblioResolver +import org.apache.spark.deploy.SparkSubmitUtils.MavenCoordinate + class SparkSubmitUtilsSuite extends FunSuite with BeforeAndAfterAll { private val noOpOutputStream = new OutputStream { @@ -89,7 +89,7 @@ class SparkSubmitUtilsSuite extends FunSuite with BeforeAndAfterAll { } test("ivy path works correctly") { - val ivyPath = "dummy/ivy" + val ivyPath = "dummy" + File.separator + "ivy" val md = SparkSubmitUtils.getModuleDescriptor val artifacts = for (i <- 0 until 3) yield new MDArtifact(md, s"jar-$i", "jar", "jar") var jPaths = SparkSubmitUtils.resolveDependencyPaths(artifacts.toArray, new File(ivyPath)) @@ -98,17 +98,38 @@ class SparkSubmitUtilsSuite extends FunSuite with BeforeAndAfterAll { assert(index >= 0) jPaths = jPaths.substring(index + ivyPath.length) } - // end to end - val jarPath = SparkSubmitUtils.resolveMavenCoordinates( - "com.databricks:spark-csv_2.10:0.1", None, Option(ivyPath), true) - assert(jarPath.indexOf(ivyPath) >= 0, "should use non-default ivy path") + val main = MavenCoordinate("my.awesome.lib", "mylib", "0.1") + IvyTestUtils.withRepository(main, None, None) { repo => + // end to end + val jarPath = SparkSubmitUtils.resolveMavenCoordinates(main.toString, Option(repo), + Option(ivyPath), true) + assert(jarPath.indexOf(ivyPath) >= 0, "should use non-default ivy path") + } } - test("search for artifact at other repositories") { - val path = SparkSubmitUtils.resolveMavenCoordinates("com.agimatec:agimatec-validation:0.9.3", - Option("https://oss.sonatype.org/content/repositories/agimatec/"), None, true) - assert(path.indexOf("agimatec-validation") >= 0, "should find package. If it doesn't, check" + - "if package still exists. If it has been removed, replace the example in this test.") + test("search for artifact at local repositories") { + val main = new MavenCoordinate("my.awesome.lib", "mylib", "0.1") + // Local M2 repository + IvyTestUtils.withRepository(main, None, Some(SparkSubmitUtils.m2Path)) { repo => + val jarPath = SparkSubmitUtils.resolveMavenCoordinates(main.toString, None, None, true) + assert(jarPath.indexOf("mylib") >= 0, "should find artifact") + } + // Local Ivy Repository + val settings = new IvySettings + val ivyLocal = new File(settings.getDefaultIvyUserDir, "local" + File.separator) + IvyTestUtils.withRepository(main, None, Some(ivyLocal.toPath), true) { repo => + val jarPath = SparkSubmitUtils.resolveMavenCoordinates(main.toString, None, None, true) + assert(jarPath.indexOf("mylib") >= 0, "should find artifact") + } + // Local ivy repository with modified home + val dummyIvyPath = "dummy" + File.separator + "ivy" + val dummyIvyLocal = new File(dummyIvyPath, "local" + File.separator) + IvyTestUtils.withRepository(main, None, Some(dummyIvyLocal.toPath), true) { repo => + val jarPath = SparkSubmitUtils.resolveMavenCoordinates(main.toString, None, + Some(dummyIvyPath), true) + assert(jarPath.indexOf("mylib") >= 0, "should find artifact") + assert(jarPath.indexOf(dummyIvyPath) >= 0, "should be in new ivy path") + } } test("dependency not found throws RuntimeException") { @@ -127,11 +148,11 @@ class SparkSubmitUtilsSuite extends FunSuite with BeforeAndAfterAll { val path = SparkSubmitUtils.resolveMavenCoordinates(coordinates, None, None, true) assert(path === "", "should return empty path") - // Should not exclude the following dependency. Will throw an error, because it doesn't exist, - // but the fact that it is checking means that it wasn't excluded. - intercept[RuntimeException] { - SparkSubmitUtils.resolveMavenCoordinates(coordinates + - ",org.apache.spark:spark-streaming-kafka-assembly_2.10:1.2.0", None, None, true) + val main = MavenCoordinate("org.apache.spark", "spark-streaming-kafka-assembly_2.10", "1.2.0") + IvyTestUtils.withRepository(main, None, None) { repo => + val files = SparkSubmitUtils.resolveMavenCoordinates(coordinates + "," + main.toString, + Some(repo), None, true) + assert(files.indexOf(main.artifactId) >= 0, "Did not return artifact") } } } From 6c65da6bb7d1213e6a4a9f7fd1597d029d87d07c Mon Sep 17 00:00:00 2001 From: Hari Shreedharan Date: Thu, 30 Apr 2015 13:03:23 -0500 Subject: [PATCH 06/33] [SPARK-5342] [YARN] Allow long running Spark apps to run on secure YARN/HDFS Current Spark apps running on Secure YARN/HDFS would not be able to write data to HDFS after 7 days, since delegation tokens cannot be renewed beyond that. This means Spark Streaming apps will not be able to run on Secure YARN. This commit adds basic functionality to fix this issue. In this patch: - new parameters are added - principal and keytab, which can be used to login to a KDC - the client logs in, and then get tokens to start the AM - the keytab is copied to the staging directory - the AM waits for 60% of the time till expiry of the tokens and then logs in using the keytab - each time after 60% of the time, new tokens are created and sent to the executors Currently, to avoid complicating the architecture, we set the keytab and principal in the SparkHadoopUtil singleton, and schedule a login. Once the login is completed, a callback is scheduled. This is being posted for feedback, so I can gather feedback on the general implementation. There are currently a bunch of things to do: - [x] logging - [x] testing - I plan to manually test this soon. If you have ideas of how to add unit tests, comment. - [x] add code to ensure that if these params are set in non-YARN cluster mode, we complain - [x] documentation - [x] Have the executors request for credentials from the AM, so that retries are possible. Author: Hari Shreedharan Closes #4688 from harishreedharan/kerberos-longrunning and squashes the following commits: 36eb8a9 [Hari Shreedharan] Change the renewal interval config param. Fix a bunch of comments. 611923a [Hari Shreedharan] Make sure the namenodes are listed correctly for creating tokens. 09fe224 [Hari Shreedharan] Use token.renew to get token's renewal interval rather than using hdfs-site.xml 6963bbc [Hari Shreedharan] Schedule renewal in AM before starting user class. Else, a restarted AM cannot access HDFS if the user class tries to. 072659e [Hari Shreedharan] Fix build failure caused by thread factory getting moved to ThreadUtils. f041dd3 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning 42eead4 [Hari Shreedharan] Remove RPC part. Refactor and move methods around, use renewal interval rather than max lifetime to create new tokens. ebb36f5 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning bc083e3 [Hari Shreedharan] Overload RegisteredExecutor to send tokens. Minor doc updates. 7b19643 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning 8a4f268 [Hari Shreedharan] Added docs in the security guide. Changed some code to ensure that the renewer objects are created only if required. e800c8b [Hari Shreedharan] Restore original RegisteredExecutor message, and send new tokens via NewTokens message. 0e9507e [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning 7f1bc58 [Hari Shreedharan] Minor fixes, cleanup. bcd11f9 [Hari Shreedharan] Refactor AM and Executor token update code into separate classes, also send tokens via akka on executor startup. f74303c [Hari Shreedharan] Move the new logic into specialized classes. Add cleanup for old credentials files. 2f9975c [Hari Shreedharan] Ensure new tokens are written out immediately on AM restart. Also, pikc up the latest suffix from HDFS if the AM is restarted. 61b2b27 [Hari Shreedharan] Account for AM restarts by making sure lastSuffix is read from the files on HDFS. 62c45ce [Hari Shreedharan] Relogin from keytab periodically. fa233bd [Hari Shreedharan] Adding logging, fixing minor formatting and ordering issues. 42813b4 [Hari Shreedharan] Remove utils.sh, which was re-added due to merge with master. 0de27ee [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning 55522e3 [Hari Shreedharan] Fix failure caused by Preconditions ambiguity. 9ef5f1b [Hari Shreedharan] Added explanation of how the credentials refresh works, some other minor fixes. f4fd711 [Hari Shreedharan] Fix SparkConf usage. 2debcea [Hari Shreedharan] Change the file structure for credentials files. I will push a followup patch which adds a cleanup mechanism for old credentials files. The credentials files are small and few enough for it to cause issues on HDFS. af6d5f0 [Hari Shreedharan] Cleaning up files where changes weren't required. f0f54cb [Hari Shreedharan] Be more defensive when updating the credentials file. f6954da [Hari Shreedharan] Got rid of Akka communication to renew, instead the executors check a known file's modification time to read the credentials. 5c11c3e [Hari Shreedharan] Move tests to YarnSparkHadoopUtil to fix compile issues. b4cb917 [Hari Shreedharan] Send keytab to AM via DistributedCache rather than directly via HDFS 0985b4e [Hari Shreedharan] Write tokens to HDFS and read them back when required, rather than sending them over the wire. d79b2b9 [Hari Shreedharan] Make sure correct credentials are passed to FileSystem#addDelegationTokens() 8c6928a [Hari Shreedharan] Fix issue caused by direct creation of Actor object. fb27f46 [Hari Shreedharan] Make sure principal and keytab are set before CoarseGrainedSchedulerBackend is started. Also schedule re-logins in CoarseGrainedSchedulerBackend#start() 41efde0 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning d282d7a [Hari Shreedharan] Fix ClientSuite to set YARN mode, so that the correct class is used in tests. bcfc374 [Hari Shreedharan] Fix Hadoop-1 build by adding no-op methods in SparkHadoopUtil, with impl in YarnSparkHadoopUtil. f8fe694 [Hari Shreedharan] Handle None if keytab-login is not scheduled. 2b0d745 [Hari Shreedharan] [SPARK-5342][YARN] Allow long running Spark apps to run on secure YARN/HDFS. ccba5bc [Hari Shreedharan] WIP: More changes wrt kerberos 77914dd [Hari Shreedharan] WIP: Add kerberos principal and keytab to YARN client. --- .../ExecutorDelegationTokenUpdater.scala | 105 +++++++++ .../apache/spark/deploy/SparkHadoopUtil.scala | 69 +++++- .../org/apache/spark/deploy/SparkSubmit.scala | 4 + .../spark/deploy/SparkSubmitArguments.scala | 15 ++ .../CoarseGrainedExecutorBackend.scala | 13 +- .../CoarseGrainedSchedulerBackend.scala | 4 +- docs/security.md | 2 + .../launcher/SparkSubmitOptionParser.java | 6 +- .../yarn/AMDelegationTokenRenewer.scala | 203 ++++++++++++++++++ .../spark/deploy/yarn/ApplicationMaster.scala | 17 +- .../org/apache/spark/deploy/yarn/Client.scala | 123 ++++++----- .../spark/deploy/yarn/ClientArguments.scala | 10 + .../deploy/yarn/YarnSparkHadoopUtil.scala | 60 +++++- .../spark/deploy/yarn/ClientSuite.scala | 51 ----- .../spark/deploy/yarn/YarnClusterSuite.scala | 2 + .../yarn/YarnSparkHadoopUtilSuite.scala | 62 +++++- 16 files changed, 635 insertions(+), 111 deletions(-) create mode 100644 core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala create mode 100644 yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala diff --git a/core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala b/core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala new file mode 100644 index 0000000000000..80363aa3a1e0b --- /dev/null +++ b/core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala @@ -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.deploy + +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.{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/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala index cfaebf9ea5050..00194fba84ff7 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 +36,7 @@ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.util.Utils import scala.collection.JavaConversions._ +import scala.concurrent.duration._ /** * :: DeveloperApi :: @@ -39,7 +44,8 @@ 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 +207,61 @@ 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 /** @@ -251,6 +312,10 @@ 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 0d149e703aff2..4b89ede427486 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala @@ -401,6 +401,10 @@ 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"), 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/executor/CoarseGrainedExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala index 79aed90b53e2f..9e0f06ab765f1 100644 --- a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala @@ -26,7 +26,7 @@ import scala.util.{Failure, Success} import org.apache.spark.rpc._ import org.apache.spark._ import org.apache.spark.TaskState.TaskState -import org.apache.spark.deploy.SparkHadoopUtil +import org.apache.spark.deploy.{ExecutorDelegationTokenUpdater, SparkHadoopUtil} import org.apache.spark.deploy.worker.WorkerWatcher import org.apache.spark.scheduler.TaskDescription import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._ @@ -168,6 +168,16 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { driverConf.set(key, value) } } + var tokenUpdaterOption: Option[ExecutorDelegationTokenUpdater] = None + if (driverConf.contains("spark.yarn.credentials.file")) { + logInfo("Will periodically update credentials from: " + + driverConf.get("spark.yarn.credentials.file")) + // Periodically update the credentials for this user to ensure HDFS tokens get updated. + tokenUpdaterOption = + Some(new ExecutorDelegationTokenUpdater(driverConf, SparkHadoopUtil.get.conf)) + tokenUpdaterOption.get.updateCredentialsIfRequired() + } + val env = SparkEnv.createExecutorEnv( driverConf, executorId, hostname, port, cores, isLocal = false) @@ -183,6 +193,7 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { env.rpcEnv.setupEndpoint("WorkerWatcher", new WorkerWatcher(env.rpcEnv, url)) } env.rpcEnv.awaitTermination() + tokenUpdaterOption.foreach(_.stop()) } } 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 7352fa1fe9ebd..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)) 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/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/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..9ff02046de805 --- /dev/null +++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala @@ -0,0 +1,203 @@ +/* + * 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 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.") + } + } + + 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..82f2b7e1dd288 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() @@ -125,6 +127,15 @@ 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 +200,7 @@ private[spark] class ApplicationMaster( logDebug("shutting down user thread") userClassThread.interrupt() } + if (!inShutdown) delegationTokenRenewerOption.foreach(_.stop()) } } } @@ -235,12 +247,12 @@ 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 +506,7 @@ 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 4abcf7307a388..bb126a46374d5 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._ @@ -36,7 +38,6 @@ 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.{TokenIdentifier, Token} @@ -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() @@ -219,12 +224,12 @@ 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) @@ -243,6 +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)) { @@ -385,6 +404,28 @@ 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. */ @@ -396,7 +437,16 @@ 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) @@ -461,7 +511,6 @@ 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) @@ -632,6 +681,24 @@ 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, @@ -987,46 +1054,6 @@ 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. */ 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/YarnSparkHadoopUtil.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala index 5881dc5ffa3ad..a5c454e2e5c5e 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 @@ -17,25 +17,26 @@ package org.apache.spark.deploy.yarn -import java.io.File +import java.io._ import java.util.regex.Matcher 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._ 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 /** @@ -82,6 +83,48 @@ 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) + } + } + } + } object YarnSparkHadoopUtil { @@ -100,6 +143,14 @@ 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 +263,4 @@ object YarnSparkHadoopUtil { classPathSeparatorField.get(null).asInstanceOf[String] } } + 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") + } } From adbdb19a7d2cc939795f0cecbdc07c605dc946c1 Mon Sep 17 00:00:00 2001 From: "Joseph K. Bradley" Date: Thu, 30 Apr 2015 14:39:27 -0700 Subject: [PATCH 07/33] [SPARK-7207] [ML] [BUILD] Added ml.recommendation, ml.regression to SparkBuild Added ml.recommendation, ml.regression to SparkBuild CC: mengxr Author: Joseph K. Bradley Closes #5758 from jkbradley/SPARK-7207 and squashes the following commits: a28158a [Joseph K. Bradley] Added ml.recommendation, ml.regression to SparkBuild --- project/SparkBuild.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index b7dbcd9bc562a..4bfa8cede7a85 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -467,7 +467,7 @@ 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" From e0628f2fae7f99d096f9dd625876a60d11020d9b Mon Sep 17 00:00:00 2001 From: Patrick Wendell Date: Thu, 30 Apr 2015 14:59:20 -0700 Subject: [PATCH 08/33] Revert "[SPARK-5342] [YARN] Allow long running Spark apps to run on secure YARN/HDFS" This reverts commit 6c65da6bb7d1213e6a4a9f7fd1597d029d87d07c. --- .../ExecutorDelegationTokenUpdater.scala | 105 --------- .../apache/spark/deploy/SparkHadoopUtil.scala | 69 +----- .../org/apache/spark/deploy/SparkSubmit.scala | 4 - .../spark/deploy/SparkSubmitArguments.scala | 15 -- .../CoarseGrainedExecutorBackend.scala | 13 +- .../CoarseGrainedSchedulerBackend.scala | 4 +- docs/security.md | 2 - .../launcher/SparkSubmitOptionParser.java | 6 +- .../yarn/AMDelegationTokenRenewer.scala | 203 ------------------ .../spark/deploy/yarn/ApplicationMaster.scala | 17 +- .../org/apache/spark/deploy/yarn/Client.scala | 123 +++++------ .../spark/deploy/yarn/ClientArguments.scala | 10 - .../deploy/yarn/YarnSparkHadoopUtil.scala | 60 +----- .../spark/deploy/yarn/ClientSuite.scala | 51 +++++ .../spark/deploy/yarn/YarnClusterSuite.scala | 2 - .../yarn/YarnSparkHadoopUtilSuite.scala | 62 +----- 16 files changed, 111 insertions(+), 635 deletions(-) delete mode 100644 core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala delete mode 100644 yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala diff --git a/core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala b/core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala deleted file mode 100644 index 80363aa3a1e0b..0000000000000 --- a/core/src/main/scala/org/apache/spark/deploy/ExecutorDelegationTokenUpdater.scala +++ /dev/null @@ -1,105 +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.deploy - -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.{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/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala index 00194fba84ff7..cfaebf9ea5050 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala @@ -17,16 +17,12 @@ 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, PathFilter} +import org.apache.hadoop.fs.{FileStatus, FileSystem, Path} 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} @@ -36,7 +32,6 @@ import org.apache.spark.annotation.DeveloperApi import org.apache.spark.util.Utils import scala.collection.JavaConversions._ -import scala.concurrent.duration._ /** * :: DeveloperApi :: @@ -44,8 +39,7 @@ import scala.concurrent.duration._ */ @DeveloperApi class SparkHadoopUtil extends Logging { - private val sparkConf = new SparkConf() - val conf: Configuration = newConfiguration(sparkConf) + val conf: Configuration = newConfiguration(new SparkConf()) UserGroupInformation.setConfiguration(conf) /** @@ -207,61 +201,6 @@ 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 /** @@ -312,10 +251,6 @@ 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 4b89ede427486..0d149e703aff2 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala @@ -401,10 +401,6 @@ 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"), 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 c0e4c771908b3..c621b8fc86f94 100644 --- a/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala +++ b/core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala @@ -63,8 +63,6 @@ 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 @@ -395,12 +393,6 @@ 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) @@ -514,13 +506,6 @@ 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/executor/CoarseGrainedExecutorBackend.scala b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala index 9e0f06ab765f1..79aed90b53e2f 100644 --- a/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala +++ b/core/src/main/scala/org/apache/spark/executor/CoarseGrainedExecutorBackend.scala @@ -26,7 +26,7 @@ import scala.util.{Failure, Success} import org.apache.spark.rpc._ import org.apache.spark._ import org.apache.spark.TaskState.TaskState -import org.apache.spark.deploy.{ExecutorDelegationTokenUpdater, SparkHadoopUtil} +import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.deploy.worker.WorkerWatcher import org.apache.spark.scheduler.TaskDescription import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._ @@ -168,16 +168,6 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { driverConf.set(key, value) } } - var tokenUpdaterOption: Option[ExecutorDelegationTokenUpdater] = None - if (driverConf.contains("spark.yarn.credentials.file")) { - logInfo("Will periodically update credentials from: " + - driverConf.get("spark.yarn.credentials.file")) - // Periodically update the credentials for this user to ensure HDFS tokens get updated. - tokenUpdaterOption = - Some(new ExecutorDelegationTokenUpdater(driverConf, SparkHadoopUtil.get.conf)) - tokenUpdaterOption.get.updateCredentialsIfRequired() - } - val env = SparkEnv.createExecutorEnv( driverConf, executorId, hostname, port, cores, isLocal = false) @@ -193,7 +183,6 @@ private[spark] object CoarseGrainedExecutorBackend extends Logging { env.rpcEnv.setupEndpoint("WorkerWatcher", new WorkerWatcher(env.rpcEnv, url)) } env.rpcEnv.awaitTermination() - tokenUpdaterOption.foreach(_.stop()) } } 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 f107148f3b8c6..7352fa1fe9ebd 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 @@ -68,7 +68,6 @@ 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] @@ -113,7 +112,6 @@ 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] = { @@ -124,6 +122,7 @@ 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) @@ -244,7 +243,6 @@ 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)) diff --git a/docs/security.md b/docs/security.md index d4ffa60e59a33..c034ba12ff1fc 100644 --- a/docs/security.md +++ b/docs/security.md @@ -32,8 +32,6 @@ 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/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java index 229000087688f..8526d2e7cfa3f 100644 --- a/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java +++ b/launcher/src/main/java/org/apache/spark/launcher/SparkSubmitOptionParser.java @@ -69,10 +69,8 @@ class SparkSubmitOptionParser { // YARN-only options. protected final String ARCHIVES = "--archives"; protected final String EXECUTOR_CORES = "--executor-cores"; - protected final String KEYTAB = "--keytab"; - protected final String NUM_EXECUTORS = "--num-executors"; - protected final String PRINCIPAL = "--principal"; protected final String QUEUE = "--queue"; + protected final String NUM_EXECUTORS = "--num-executors"; /** * This is the canonical list of spark-submit options. Each entry in the array contains the @@ -98,13 +96,11 @@ class SparkSubmitOptionParser { { EXECUTOR_MEMORY }, { FILES }, { JARS }, - { KEYTAB }, { KILL_SUBMISSION }, { MASTER }, { NAME }, { NUM_EXECUTORS }, { PACKAGES }, - { PRINCIPAL }, { PROPERTIES_FILE }, { PROXY_USER }, { PY_FILES }, 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 deleted file mode 100644 index 9ff02046de805..0000000000000 --- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala +++ /dev/null @@ -1,203 +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.deploy.yarn - -import java.security.PrivilegedExceptionAction -import java.util.concurrent.{Executors, TimeUnit} - -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.") - } - } - - 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 82f2b7e1dd288..70cb57ffd8c69 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 @@ -75,8 +75,6 @@ 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() @@ -127,15 +125,6 @@ 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 { @@ -200,7 +189,6 @@ private[spark] class ApplicationMaster( logDebug("shutting down user thread") userClassThread.interrupt() } - if (!inShutdown) delegationTokenRenewerOption.foreach(_.stop()) } } } @@ -247,12 +235,12 @@ private[spark] class ApplicationMaster( host: String, port: String, isClusterMode: Boolean): Unit = { - val driverEndpoint = rpcEnv.setupEndpointRef( + val driverEndpont = rpcEnv.setupEndpointRef( SparkEnv.driverActorSystemName, RpcAddress(host, port.toInt), YarnSchedulerBackend.ENDPOINT_NAME) amEndpoint = - rpcEnv.setupEndpoint("YarnAM", new AMEndpoint(rpcEnv, driverEndpoint, isClusterMode)) + rpcEnv.setupEndpoint("YarnAM", new AMEndpoint(rpcEnv, driverEndpont, isClusterMode)) } private def runDriver(securityMgr: SecurityManager): Unit = { @@ -506,7 +494,6 @@ 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 bb126a46374d5..4abcf7307a388 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 @@ -17,11 +17,9 @@ package org.apache.spark.deploy.yarn -import java.io.{ByteArrayInputStream, DataInputStream, File, FileOutputStream} +import java.io.{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._ @@ -38,6 +36,7 @@ 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.{TokenIdentifier, Token} @@ -51,8 +50,8 @@ 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.deploy.SparkHadoopUtil import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkContext, SparkException} +import org.apache.spark.deploy.SparkHadoopUtil import org.apache.spark.util.Utils private[spark] class Client( @@ -70,13 +69,11 @@ private[spark] class Client( private val yarnClient = YarnClient.createYarnClient private val yarnConf = new YarnConfiguration(hadoopConf) - private var credentials: Credentials = null + private val credentials = UserGroupInformation.getCurrentUser.getCredentials 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) @@ -91,8 +88,6 @@ 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() @@ -224,12 +219,12 @@ 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 = YarnSparkHadoopUtil.get.getNameNodesToAccess(sparkConf) + dst - YarnSparkHadoopUtil.get.obtainTokensForNamenodes(nns, hadoopConf, credentials) + val nns = getNameNodesToAccess(sparkConf) + dst // 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) @@ -248,20 +243,6 @@ 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)) { @@ -404,28 +385,6 @@ 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. */ @@ -437,16 +396,7 @@ 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) @@ -511,6 +461,7 @@ 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) @@ -681,24 +632,6 @@ 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, @@ -1054,6 +987,46 @@ 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. */ 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 5653c9f14dc6d..1423533470fc0 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 @@ -42,8 +42,6 @@ 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 @@ -233,14 +231,6 @@ 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/YarnSparkHadoopUtil.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnSparkHadoopUtil.scala index a5c454e2e5c5e..5881dc5ffa3ad 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 @@ -17,26 +17,25 @@ package org.apache.spark.deploy.yarn -import java.io._ +import java.io.File import java.util.regex.Matcher 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._ import org.apache.hadoop.io.Text -import org.apache.hadoop.mapred.{Master, JobConf} +import org.apache.hadoop.mapred.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 /** @@ -83,48 +82,6 @@ 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) - } - } - } - } object YarnSparkHadoopUtil { @@ -143,14 +100,6 @@ 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. @@ -263,4 +212,3 @@ object YarnSparkHadoopUtil { classPathSeparatorField.get(null).asInstanceOf[String] } } - 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 508819e242a26..a51c2005cb472 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 @@ -151,6 +151,57 @@ 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 d3c606e0ed998..3877da4120e7c 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 @@ -86,7 +86,6 @@ 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) @@ -129,7 +128,6 @@ 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 e10b985c3c236..9395316b71ff4 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 @@ -20,8 +20,6 @@ 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 @@ -29,7 +27,7 @@ import org.scalatest.{FunSuite, Matchers} import org.apache.hadoop.yarn.api.records.ApplicationAccessType -import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkException} +import org.apache.spark.{Logging, SecurityManager, SparkConf} import org.apache.spark.util.Utils @@ -175,62 +173,4 @@ 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") - } } From 6702324b60f99dab55912c08ccd3d03805f6b7b2 Mon Sep 17 00:00:00 2001 From: Liang-Chi Hsieh Date: Thu, 30 Apr 2015 15:13:43 -0700 Subject: [PATCH 09/33] [SPARK-7196][SQL] Support precision and scale of decimal type for JDBC JIRA: https://issues.apache.org/jira/browse/SPARK-7196 Author: Liang-Chi Hsieh Closes #5777 from viirya/jdbc_precision and squashes the following commits: f40f5e6 [Liang-Chi Hsieh] Support precision and scale for NUMERIC type. 49acbf9 [Liang-Chi Hsieh] Add unit test. a509e19 [Liang-Chi Hsieh] Support precision and scale of decimal type for JDBC. --- .../main/scala/org/apache/spark/sql/jdbc/JDBCRDD.scala | 10 ++++++++-- .../scala/org/apache/spark/sql/jdbc/JDBCSuite.scala | 2 ++ 2 files changed, 10 insertions(+), 2 deletions(-) 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..cef92abbdc586 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 } @@ -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/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/jdbc/JDBCSuite.scala index 856a806781ec4..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._ @@ -271,6 +272,7 @@ class JDBCSuite extends FunSuite with BeforeAndAfter { 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") { From 07a86205f9efc43ea1ec5edb97c21c32abe7fb8a Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Thu, 30 Apr 2015 15:21:00 -0700 Subject: [PATCH 10/33] [SPARK-7288] Suppress compiler warnings due to use of sun.misc.Unsafe; add facade in front of Unsafe; remove use of Unsafe.setMemory This patch suppresses compiler warnings due to our use of `sun.misc.Unsafe` (introduced in #5725). These warnings can only be suppressed via the `-XDignore.symbol.file` javac flag; the `SuppressWarnings` annotation won't work for these. In order to restrict uses of this compiler flag to the `unsafe` module, I placed a facade in front of `Unsafe` so that other modules won't call it directly. This facade also will also help us to avoid accidental usage of deprecated Unsafe methods or methods that aren't supported in Java 6. I also removed an unnecessary use of `Unsafe.setMemory`, which isn't present in certain versions of Java 6, and excluded the new `unsafe` module from Javadoc. Author: Josh Rosen Closes #5814 from JoshRosen/unsafe-compiler-warnings-fixes and squashes the following commits: 9e8c483 [Josh Rosen] Exclude new unsafe module from Javadoc ba75ecf [Josh Rosen] Only apply -XDignore.symbol.file flag in unsafe project. 7403345 [Josh Rosen] Put facade in front of Unsafe. 50230c0 [Josh Rosen] Remove usage of Unsafe.setMemory 96d41c9 [Josh Rosen] Use -XDignore.symbol.file to suppress warnings about sun.misc.Unsafe usage --- project/SparkBuild.scala | 11 +++ unsafe/pom.xml | 24 +++++ .../spark/unsafe/PlatformDependent.java | 93 +++++++++++++++++-- .../spark/unsafe/map/BytesToBytesMap.java | 9 +- .../spark/unsafe/memory/MemoryBlock.java | 8 -- .../spark/unsafe/bitset/BitSetSuite.java | 2 +- .../map/AbstractBytesToBytesMapSuite.java | 2 +- 7 files changed, 125 insertions(+), 24 deletions(-) diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala index 4bfa8cede7a85..a93aa12ce1aac 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -163,6 +163,9 @@ object SparkBuild extends PomBuild { 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 +219,13 @@ 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 +434,7 @@ 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"))) diff --git a/unsafe/pom.xml b/unsafe/pom.xml index 8901d77591932..5b0733206b2bc 100644 --- a/unsafe/pom.xml +++ b/unsafe/pom.xml @@ -65,5 +65,29 @@ 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 index 91b2f9aa43921..24b2892098059 100644 --- a/unsafe/src/main/java/org/apache/spark/unsafe/PlatformDependent.java +++ b/unsafe/src/main/java/org/apache/spark/unsafe/PlatformDependent.java @@ -23,7 +23,82 @@ public final class PlatformDependent { - public static final Unsafe UNSAFE; + /** + * 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; @@ -48,13 +123,13 @@ public final class PlatformDependent { } catch (Throwable cause) { unsafe = null; } - UNSAFE = unsafe; + _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); + 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; @@ -71,7 +146,7 @@ static public void copyMemory( long length) { while (length > 0) { long size = Math.min(length, UNSAFE_COPY_THRESHOLD); - UNSAFE.copyMemory(src, srcOffset, dst, dstOffset, size); + _UNSAFE.copyMemory(src, srcOffset, dst, dstOffset, size); length -= size; srcOffset += size; dstOffset += size; @@ -82,6 +157,6 @@ static public void copyMemory( * Raises an exception bypassing compiler checks for checked exceptions. */ public static void throwException(Throwable t) { - UNSAFE.throwException(t); + _UNSAFE.throwException(t); } } 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 index 85b64c0833803..4e5ebc402be35 100644 --- a/unsafe/src/main/java/org/apache/spark/unsafe/map/BytesToBytesMap.java +++ b/unsafe/src/main/java/org/apache/spark/unsafe/map/BytesToBytesMap.java @@ -401,11 +401,11 @@ public void putNewKey( // Copy the key PlatformDependent.UNSAFE.putLong(pageBaseObject, keySizeOffsetInPage, keyLengthBytes); - PlatformDependent.UNSAFE.copyMemory( + PlatformDependent.copyMemory( keyBaseObject, keyBaseOffset, pageBaseObject, keyDataOffsetInPage, keyLengthBytes); // Copy the value PlatformDependent.UNSAFE.putLong(pageBaseObject, valueSizeOffsetInPage, valueLengthBytes); - PlatformDependent.UNSAFE.copyMemory( + PlatformDependent.copyMemory( valueBaseObject, valueBaseOffset, pageBaseObject, valueDataOffsetInPage, valueLengthBytes); final long storedKeyAddress = memoryManager.encodePageNumberAndOffset( @@ -429,7 +429,7 @@ public void putNewKey( 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(memoryManager.allocate(capacity / 8).zero()); + bitset = new BitSet(MemoryBlock.fromLongArray(new long[capacity / 64])); this.growthThreshold = (int) (capacity * loadFactor); this.mask = capacity - 1; @@ -447,7 +447,7 @@ public void free() { longArray = null; } if (bitset != null) { - memoryManager.free(bitset.memoryBlock()); + // 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(); @@ -535,7 +535,6 @@ private void growAndRehash() { // Deallocate the old data structures. memoryManager.free(oldLongArray.memoryBlock()); - memoryManager.free(oldBitSet.memoryBlock()); if (enablePerfMetrics) { timeSpentResizingNs += System.nanoTime() - resizeStartTime; } 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 index 0beb743e5644e..3dc82d8c2eb39 100644 --- a/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryBlock.java +++ b/unsafe/src/main/java/org/apache/spark/unsafe/memory/MemoryBlock.java @@ -46,14 +46,6 @@ public long size() { return length; } - /** - * Clear the contents of this memory block. Returns `this` to facilitate chaining. - */ - public MemoryBlock zero() { - PlatformDependent.UNSAFE.setMemory(obj, offset, length, (byte) 0); - return this; - } - /** * Creates a memory block pointing to the memory used by the long array. */ 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 index 4bf132fd4053e..e3a824e29b768 100644 --- a/unsafe/src/test/java/org/apache/spark/unsafe/bitset/BitSetSuite.java +++ b/unsafe/src/test/java/org/apache/spark/unsafe/bitset/BitSetSuite.java @@ -27,7 +27,7 @@ public class BitSetSuite { private static BitSet createBitSet(int capacity) { assert capacity % 64 == 0; - return new BitSet(MemoryBlock.fromLongArray(new long[capacity / 64]).zero()); + return new BitSet(MemoryBlock.fromLongArray(new long[capacity / 64])); } @Test 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 index 9038cf567f1e2..7a5c0622d1ffb 100644 --- a/unsafe/src/test/java/org/apache/spark/unsafe/map/AbstractBytesToBytesMapSuite.java +++ b/unsafe/src/test/java/org/apache/spark/unsafe/map/AbstractBytesToBytesMapSuite.java @@ -57,7 +57,7 @@ public void tearDown() { private static byte[] getByteArray(MemoryLocation loc, int size) { final byte[] arr = new byte[size]; - PlatformDependent.UNSAFE.copyMemory( + PlatformDependent.copyMemory( loc.getBaseObject(), loc.getBaseOffset(), arr, From 77cc25fb7473d8a06b727d2ba5ee62db1c651cf8 Mon Sep 17 00:00:00 2001 From: Zhongshuai Pei <799203320@qq.com> Date: Thu, 30 Apr 2015 15:22:13 -0700 Subject: [PATCH 11/33] [SPARK-7267][SQL]Push down Project when it's child is Limit SQL ``` select key from (select key,value from t1 limit 100) t2 limit 10 ``` Optimized Logical Plan before modifying ``` == Optimized Logical Plan == Limit 10 Project key#228 Limit 100 MetastoreRelation default, t1, None ``` Optimized Logical Plan after modifying ``` == Optimized Logical Plan == Limit 10 Limit 100 Project key#228 MetastoreRelation default, t1, None ``` After this, we can combine limits Author: Zhongshuai Pei <799203320@qq.com> Author: DoingDone9 <799203320@qq.com> Closes #5797 from DoingDone9/ProjectLimit and squashes the following commits: 70d0fca [Zhongshuai Pei] Update FilterPushdownSuite.scala dc83ae9 [Zhongshuai Pei] Update FilterPushdownSuite.scala 485c61c [Zhongshuai Pei] Update Optimizer.scala f03fe7f [Zhongshuai Pei] Merge pull request #12 from apache/master f12fa50 [Zhongshuai Pei] Merge pull request #10 from apache/master f61210c [Zhongshuai Pei] Merge pull request #9 from apache/master 34b1a9a [Zhongshuai Pei] Merge pull request #8 from apache/master 802261c [DoingDone9] Merge pull request #7 from apache/master d00303b [DoingDone9] Merge pull request #6 from apache/master 98b134f [DoingDone9] Merge pull request #5 from apache/master 161cae3 [DoingDone9] Merge pull request #4 from apache/master c87e8b6 [DoingDone9] Merge pull request #3 from apache/master cb1852d [DoingDone9] Merge pull request #2 from apache/master c3f046f [DoingDone9] Merge pull request #1 from apache/master --- .../spark/sql/catalyst/optimizer/Optimizer.scala | 3 +++ .../catalyst/optimizer/FilterPushdownSuite.scala | 16 ++++++++++++++++ 2 files changed, 19 insertions(+) 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 485761dd8538b..63669e970b1ec 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 @@ -170,6 +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 } 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..2ad73941ab978 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 @@ -90,7 +90,23 @@ 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 = From fa01bec484fc000e0a31645b722ffde48556c4df Mon Sep 17 00:00:00 2001 From: Josh Rosen Date: Thu, 30 Apr 2015 16:23:01 -0700 Subject: [PATCH 12/33] [Build] Enable MiMa checks for SQL Now that 1.3 has been released, we should enable MiMa checks for the `sql` subproject. Author: Josh Rosen Closes #5727 from JoshRosen/enable-more-mima-checks and squashes the following commits: 3ad302b [Josh Rosen] Merge remote-tracking branch 'origin/master' into enable-more-mima-checks 0c48e4d [Josh Rosen] Merge remote-tracking branch 'origin/master' into enable-more-mima-checks e276cee [Josh Rosen] Fix SQL MiMa checks via excludes and private[sql] 44d0d01 [Josh Rosen] Add back 'launcher' exclude 1aae027 [Josh Rosen] Enable MiMa checks for launcher and sql projects. --- project/MimaExcludes.scala | 16 ++++++++++++++++ project/SparkBuild.scala | 5 ++--- .../apache/spark/sql/execution/ExistingRDD.scala | 5 +++-- .../spark/sql/execution/LocalTableScan.scala | 2 +- .../apache/spark/sql/execution/commands.scala | 2 +- 5 files changed, 23 insertions(+), 7 deletions(-) diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 3beafa158eb97..bf343d4b7e40b 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -88,6 +88,22 @@ object MimaExcludes { "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 a93aa12ce1aac..b4431c7ee05b6 100644 --- a/project/SparkBuild.scala +++ b/project/SparkBuild.scala @@ -156,9 +156,8 @@ 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, + // 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) } 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/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/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 From 1c3e402e669d047410b00de9193adf3c329844a2 Mon Sep 17 00:00:00 2001 From: DB Tsai Date: Thu, 30 Apr 2015 16:26:51 -0700 Subject: [PATCH 13/33] [SPARK-7279] Removed diffSum which is theoretical zero in LinearRegression and coding formating Author: DB Tsai Closes #5809 from dbtsai/format and squashes the following commits: 6904eed [DB Tsai] triger jenkins 9146e19 [DB Tsai] initial commit --- .../spark/ml/regression/LinearRegression.scala | 18 ++++++------------ 1 file changed, 6 insertions(+), 12 deletions(-) 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 11c6cea0f8c8c..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 @@ -25,8 +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.{HasTol, HasElasticNetParam, HasMaxIter, - HasRegParam} +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._ @@ -103,9 +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))( { @@ -146,8 +143,7 @@ class LinearRegression extends Regressor[Vector, LinearRegression, LinearRegress val optimizer = if (paramMap(elasticNetParam) == 0.0 || effectiveRegParam == 0.0) { new BreezeLBFGS[BDV[Double]](paramMap(maxIter), 10, paramMap(tol)) } else { - new BreezeOWLQN[Int, BDV[Double]](paramMap(maxIter), 10, effectiveL1RegParam, - paramMap(tol)) + new BreezeOWLQN[Int, BDV[Double]](paramMap(maxIter), 10, effectiveL1RegParam, paramMap(tol)) } val initialWeights = Vectors.zeros(numFeatures) @@ -304,9 +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() @@ -323,9 +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 @@ -350,7 +346,6 @@ private class LeastSquaresAggregator( } } lossSum += diff * diff / 2.0 - diffSum += diff } totalCnt += 1 @@ -372,7 +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 From 149b3ee2dac992355adbe44e989570726c1f35d0 Mon Sep 17 00:00:00 2001 From: Burak Yavuz Date: Thu, 30 Apr 2015 16:40:32 -0700 Subject: [PATCH 14/33] [SPARK-7242][SQL][MLLIB] Frequent items for DataFrames Finding frequent items with possibly false positives, using the algorithm described in `http://www.cs.umd.edu/~samir/498/karp.pdf`. public API under: ``` df.stat.freqItems(cols: Array[String], support: Double = 0.001): DataFrame ``` The output is a local DataFrame having the input column names with `-freqItems` appended to it. This is a single pass algorithm that may return false positives, but no false negatives. cc mengxr rxin Let's get the implementations in, I can add python API in a follow up PR. Author: Burak Yavuz Closes #5799 from brkyvz/freq-items and squashes the following commits: a6ec82c [Burak Yavuz] addressed comments v? 39b1bba [Burak Yavuz] removed toSeq 0915e23 [Burak Yavuz] addressed comments v2.1 3a5c177 [Burak Yavuz] addressed comments v2.0 482e741 [Burak Yavuz] removed old import 38e784d [Burak Yavuz] addressed comments v1.0 8279d4d [Burak Yavuz] added default value for support 3d82168 [Burak Yavuz] made base implementation --- .../org/apache/spark/sql/DataFrame.scala | 11 ++ .../spark/sql/DataFrameStatFunctions.scala | 68 ++++++++++ .../sql/execution/stat/FrequentItems.scala | 121 ++++++++++++++++++ .../apache/spark/sql/JavaDataFrameSuite.java | 14 +- .../apache/spark/sql/DataFrameStatSuite.scala | 47 +++++++ 5 files changed, 256 insertions(+), 5 deletions(-) create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala create mode 100644 sql/core/src/main/scala/org/apache/spark/sql/execution/stat/FrequentItems.scala create mode 100644 sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.scala 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 2669300029545..7be2a01da17e8 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]]. * 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..42e5cbc05e1e0 --- /dev/null +++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala @@ -0,0 +1,68 @@ +/* +* 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.FrequentItems + +/** + * :: 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) + } + + /** + * Runs `freqItems` with 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: List[String], support: Double): DataFrame = { + FrequentItems.singlePassFreqItems(df, cols, support) + } + + /** + * Python friendly implementation for `freqItems` with a default `support` of 1%. + */ + def freqItems(cols: List[String]): DataFrame = { + FrequentItems.singlePassFreqItems(df, cols, 0.01) + } +} 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/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java b/sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java index e5c9504d21042..966d879e1fc9f 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.*; @@ -178,5 +175,12 @@ 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)); + } } 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..bb1d29c71d23b --- /dev/null +++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameStatSuite.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.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 { + + val sqlCtx = TestSQLContext + + test("Frequent Items") { + def toLetter(i: Int): String = (i + 96).toChar.toString + 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) + + } +} From ee04413935f74b3178adbb6d8dee19b3320803e9 Mon Sep 17 00:00:00 2001 From: rakeshchalasani Date: Thu, 30 Apr 2015 17:42:50 -0700 Subject: [PATCH 15/33] [SPARK-7280][SQL] Add "drop" column/s on a data frame Takes a column name/s and returns a new DataFrame that drops a column/s. Author: rakeshchalasani Closes #5818 from rakeshchalasani/SPARK-7280 and squashes the following commits: ce2ec09 [rakeshchalasani] Minor edit 45c06f1 [rakeshchalasani] Change withColumnRename and format changes f68945a [rakeshchalasani] Minor fix 0b9104d [rakeshchalasani] Drop one column at a time 289afd2 [rakeshchalasani] [SPARK-7280][SQL] Add "drop" column/s on a data frame --- .../org/apache/spark/sql/DataFrame.scala | 33 ++++++++++++++++--- .../org/apache/spark/sql/DataFrameSuite.scala | 16 +++++++++ 2 files changed, 45 insertions(+), 4 deletions(-) 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 7be2a01da17e8..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 @@ -851,15 +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 :_*) } /** 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 b70e127b4ed1a..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") From 079733817f02c61ef814f5d9c0c8227498ff0058 Mon Sep 17 00:00:00 2001 From: scwf Date: Thu, 30 Apr 2015 18:15:56 -0700 Subject: [PATCH 16/33] [SPARK-7093] [SQL] Using newPredicate in NestedLoopJoin to enable code generation Using newPredicate in NestedLoopJoin instead of InterpretedPredicate to make it can make use of code generation Author: scwf Closes #5665 from scwf/NLP and squashes the following commits: d19dd31 [scwf] improvement a887c02 [scwf] improve for NLP boundCondition --- .../spark/sql/execution/joins/BroadcastNestedLoopJoin.scala | 5 +---- .../apache/spark/sql/execution/joins/LeftSemiJoinBNL.scala | 5 +---- 2 files changed, 2 insertions(+), 8 deletions(-) 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 = From a0d8a61ab198b8c0ddbb3072bbe1d0e1dabc3e45 Mon Sep 17 00:00:00 2001 From: wangfei Date: Thu, 30 Apr 2015 18:18:54 -0700 Subject: [PATCH 17/33] [SPARK-7109] [SQL] Push down left side filter for left semi join Now in spark sql optimizer we only push down right side filter for left semi join, actually we can push down left side filter because left semi join is doing filter on left table essentially. Author: wangfei Author: scwf Closes #5677 from scwf/leftsemi and squashes the following commits: 483d205 [wangfei] update with master to fix compile issue 82df0e1 [wangfei] Merge branch 'master' of https://github.com/apache/spark into leftsemi d68a053 [wangfei] added apply 8f48a3d [scwf] added test ebadaa9 [wangfei] left filter push down for left semi join --- .../sql/catalyst/optimizer/Optimizer.scala | 8 +++---- .../optimizer/FilterPushdownSuite.scala | 21 ++++++++++++++++++- 2 files changed, 24 insertions(+), 5 deletions(-) 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 63669e970b1ec..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 @@ -571,7 +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) @@ -579,7 +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. @@ -588,14 +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/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 2ad73941ab978..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 = @@ -213,6 +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) From e991255e7203a0f7080efbd71f57574f46076711 Mon Sep 17 00:00:00 2001 From: Vyacheslav Baranov Date: Thu, 30 Apr 2015 18:45:14 -0700 Subject: [PATCH 18/33] [SPARK-6913][SQL] Fixed "java.sql.SQLException: No suitable driver found" Fixed `java.sql.SQLException: No suitable driver found` when loading DataFrame into Spark SQL if the driver is supplied with `--jars` argument. The problem is in `java.sql.DriverManager` class that can't access drivers loaded by Spark ClassLoader. Wrappers that forward requests are created for these drivers. Also, it's not necessary any more to include JDBC drivers in `--driver-class-path` in local mode, specifying in `--jars` argument is sufficient. Author: Vyacheslav Baranov Closes #5782 from SlavikBaranov/SPARK-6913 and squashes the following commits: 510c43f [Vyacheslav Baranov] [SPARK-6913] Fixed review comments b2a727c [Vyacheslav Baranov] [SPARK-6913] Fixed thread race on driver registration c8294ae [Vyacheslav Baranov] [SPARK-6913] Fixed "No suitable driver found" when using using JDBC driver added with SparkContext.addJar --- .../org/apache/spark/sql/jdbc/JDBCRDD.scala | 2 +- .../apache/spark/sql/jdbc/JDBCRelation.scala | 4 +- .../org/apache/spark/sql/jdbc/jdbc.scala | 60 ++++++++++++++++++- 3 files changed, 62 insertions(+), 4 deletions(-) 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 cef92abbdc586..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 @@ -159,7 +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); 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..ae9af1eabe68e 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} +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 +183,58 @@ 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 + + override def getParentLogger: java.util.logging.Logger = wrapped.getParentLogger + + 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 From 3ba5aaab8266822545ac82b9e733fd25cc215a77 Mon Sep 17 00:00:00 2001 From: Cheng Hao Date: Thu, 30 Apr 2015 18:49:06 -0700 Subject: [PATCH 19/33] [SPARK-5213] [SQL] Pluggable SQL Parser Support This PR aims to make the SQL Parser Pluggable, and user can register it's own parser via Spark SQL CLI. ``` # add the jar into the classpath $hchengmydesktop:spark>bin/spark-sql --jars sql99.jar -- 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; -- switch to a custom 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 default sql dialect ("sql" for SQLContext and "hiveql" for HiveContext) ``` Author: Cheng Hao Closes #4015 from chenghao-intel/sqlparser and squashes the following commits: 493775c [Cheng Hao] update the code as feedback 81a731f [Cheng Hao] remove the unecessary comment aab0b0b [Cheng Hao] polish the code a little bit 49b9d81 [Cheng Hao] shrink the comment for rebasing --- .../sql/catalyst/AbstractSparkSQLParser.scala | 11 ++- .../apache/spark/sql/catalyst/Dialect.scala | 33 ++++++++ .../spark/sql/catalyst/errors/package.scala | 2 + .../org/apache/spark/sql/SQLContext.scala | 82 +++++++++++++++---- .../org/apache/spark/sql/sources/ddl.scala | 6 +- .../org/apache/spark/sql/SQLQuerySuite.scala | 22 +++++ .../apache/spark/sql/hive/HiveContext.scala | 41 ++++++---- .../apache/spark/sql/hive/test/TestHive.scala | 5 +- .../sql/hive/execution/SQLQuerySuite.scala | 39 ++++++++- 9 files changed, 199 insertions(+), 42 deletions(-) create mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/Dialect.scala 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/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/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index bd4a55fa132fb..77f51dfd88d6f 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 +47,45 @@ 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 = { + val catalystSqlParser = new catalyst.SqlParser + new SparkSQLParser(catalystSqlParser.parse) + } + + 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. @@ -132,17 +174,27 @@ class SQLContext(@transient val sparkContext: SparkContext) protected[sql] lazy val optimizer: Optimizer = DefaultOptimizer @transient - 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 ddlParser = new DDLParser((sql: String) => { getSQLDialect().parse(sql) }) + + 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 _ => @@ -945,11 +1003,7 @@ 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)) } /** 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/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index 9e02e69fda3f2..255f8c3982cdc 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 @@ -64,6 +69,23 @@ 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/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/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/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( From 473552fa5db9fa81f1a800f4ebacd23472e8c212 Mon Sep 17 00:00:00 2001 From: scwf Date: Thu, 30 Apr 2015 18:50:14 -0700 Subject: [PATCH 20/33] [SPARK-7123] [SQL] support table.star in sqlcontext Run following sql get error `SELECT r.* FROM testData l join testData2 r on (l.key = r.a)` Author: scwf Closes #5690 from scwf/tablestar and squashes the following commits: 3b2e2b6 [scwf] support table.star --- .../org/apache/spark/sql/catalyst/SqlParser.scala | 1 + .../scala/org/apache/spark/sql/SQLQuerySuite.scala | 10 ++++++++++ 2 files changed, 11 insertions(+) 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/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala index 255f8c3982cdc..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 @@ -51,6 +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)) From beeafcfd6ee1e460c4d564cd1515d8781989b422 Mon Sep 17 00:00:00 2001 From: Patrick Wendell Date: Thu, 30 Apr 2015 20:33:36 -0700 Subject: [PATCH 21/33] Revert "[SPARK-5213] [SQL] Pluggable SQL Parser Support" This reverts commit 3ba5aaab8266822545ac82b9e733fd25cc215a77. --- .../sql/catalyst/AbstractSparkSQLParser.scala | 11 +-- .../apache/spark/sql/catalyst/Dialect.scala | 33 -------- .../spark/sql/catalyst/errors/package.scala | 2 - .../org/apache/spark/sql/SQLContext.scala | 82 ++++--------------- .../org/apache/spark/sql/sources/ddl.scala | 6 +- .../org/apache/spark/sql/SQLQuerySuite.scala | 22 ----- .../apache/spark/sql/hive/HiveContext.scala | 41 ++++------ .../apache/spark/sql/hive/test/TestHive.scala | 5 +- .../sql/hive/execution/SQLQuerySuite.scala | 39 +-------- 9 files changed, 42 insertions(+), 199 deletions(-) delete mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/Dialect.scala 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 2eb3e167baad5..1f3c02478bd68 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 @@ -25,6 +25,10 @@ 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 { @@ -38,7 +42,7 @@ private[sql] abstract class AbstractSparkSQLParser } protected case class Keyword(str: String) { - def normalize: String = lexical.normalizeKeyword(str) + def normalize: String = KeywordNormalizer(str) def parser: Parser[String] = normalize } @@ -86,16 +90,13 @@ 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 = normalizeKeyword(name) + val token = KeywordNormalizer(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 deleted file mode 100644 index 977003493d471..0000000000000 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/Dialect.scala +++ /dev/null @@ -1,33 +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.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/errors/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/errors/package.scala index 0fd4f9b374ee0..bdeb660b1ecb7 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 @@ -38,8 +38,6 @@ 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/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala index 77f51dfd88d6f..bd4a55fa132fb 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 @@ -24,7 +24,6 @@ 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 @@ -33,11 +32,9 @@ 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} @@ -47,45 +44,6 @@ 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 = { - val catalystSqlParser = new catalyst.SqlParser - new SparkSQLParser(catalystSqlParser.parse) - } - - 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. @@ -174,27 +132,17 @@ class SQLContext(@transient val sparkContext: SparkContext) protected[sql] lazy val optimizer: Optimizer = DefaultOptimizer @transient - protected[sql] val ddlParser = new DDLParser((sql: String) => { getSQLDialect().parse(sql) }) - - 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] val ddlParser = new DDLParser(sqlParser.parse(_)) + + @transient + protected[sql] val sqlParser = { + val fallback = new catalyst.SqlParser + new SparkSQLParser(fallback.parse(_)) } - protected[sql] def parseSql(sql: String): LogicalPlan = ddlParser.parse(sql, false) + protected[sql] def parseSql(sql: String): LogicalPlan = { + ddlParser.parse(sql, false).getOrElse(sqlParser.parse(sql)) + } protected[sql] def executeSql(sql: String): this.QueryExecution = executePlan(parseSql(sql)) @@ -208,12 +156,6 @@ 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 _ => @@ -1003,7 +945,11 @@ class SQLContext(@transient val sparkContext: SparkContext) * @group basic */ def sql(sqlText: String): DataFrame = { - DataFrame(this, parseSql(sqlText)) + if (conf.dialect == "sql") { + DataFrame(this, parseSql(sqlText)) + } else { + sys.error(s"Unsupported SQL dialect: ${conf.dialect}") + } } /** 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 1abf3aa51cb25..e7a0685e013d8 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): LogicalPlan = { + def parse(input: String, exceptionOnError: Boolean): Option[LogicalPlan] = { try { - parse(input) + Some(parse(input)) } catch { case ddlException: DDLException => throw ddlException - case _ if !exceptionOnError => parseQuery(input) + case _ if !exceptionOnError => None case x: Throwable => throw x } } 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 0ab8558c1db13..d8e7cdbd3a94e 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 @@ -19,18 +19,13 @@ 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 @@ -79,23 +74,6 @@ 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/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 1d8d0b5c322ad..dd06b2620c5ee 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 @@ -20,9 +20,6 @@ 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 @@ -45,15 +42,6 @@ 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. @@ -93,16 +81,25 @@ class HiveContext(sc: SparkContext) extends SQLContext(sc) { protected[sql] def convertCTAS: Boolean = getConf("spark.sql.hive.convertCTAS", "false").toBoolean - @transient - 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) + @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'") + } + } + /** * 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 @@ -359,12 +356,6 @@ 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/test/TestHive.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/test/TestHive.scala index edeab5158df62..9f17bca083d13 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 @@ -107,10 +107,7 @@ 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 - - // 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") + override def dialect: String = getConf(SQLConf.DIALECT, "hiveql") } } 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 630dec8fa05a0..4f8d0ac0e7656 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 @@ -18,17 +18,14 @@ package org.apache.spark.sql.hive.execution import org.apache.spark.sql.catalyst.analysis.EliminateSubQueries -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.{MetastoreRelation, HiveShim} 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) @@ -48,9 +45,6 @@ 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 @@ -235,35 +229,6 @@ 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( From 69a739c7f5fd002432ece203957e1458deb2f4c3 Mon Sep 17 00:00:00 2001 From: zsxwing Date: Thu, 30 Apr 2015 21:32:11 -0700 Subject: [PATCH 22/33] [SPARK-7282] [STREAMING] Fix the race conditions in StreamingListenerSuite Fixed the following flaky test ```Scala [info] StreamingListenerSuite: [info] - batch info reporting (782 milliseconds) [info] - receiver info reporting *** FAILED *** (3 seconds, 911 milliseconds) [info] The code passed to eventually never returned normally. Attempted 10 times over 3.4735783689999997 seconds. Last failure message: 0 did not equal 1. (StreamingListenerSuite.scala:104) [info] org.scalatest.exceptions.TestFailedDueToTimeoutException: [info] at org.scalatest.concurrent.Eventually$class.tryTryAgain$1(Eventually.scala:420) [info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:438) [info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478) [info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:307) [info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply$mcV$sp(StreamingListenerSuite.scala:104) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94) [info] at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22) [info] at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85) [info] at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104) [info] at org.scalatest.Transformer.apply(Transformer.scala:22) [info] at org.scalatest.Transformer.apply(Transformer.scala:20) [info] at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166) [info] at org.scalatest.Suite$class.withFixture(Suite.scala:1122) [info] at org.scalatest.FunSuite.withFixture(FunSuite.scala:1555) [info] at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163) [info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175) [info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175) [info] at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306) [info] at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:175) [info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$runTest(StreamingListenerSuite.scala:34) [info] at org.scalatest.BeforeAndAfter$class.runTest(BeforeAndAfter.scala:200) [info] at org.apache.spark.streaming.StreamingListenerSuite.runTest(StreamingListenerSuite.scala:34) [info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208) [info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208) [info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:413) [info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:401) [info] at scala.collection.immutable.List.foreach(List.scala:318) [info] at org.scalatest.SuperEngine.traverseSubNodes$1(Engine.scala:401) [info] at org.scalatest.SuperEngine.org$scalatest$SuperEngine$$runTestsInBranch(Engine.scala:396) [info] at org.scalatest.SuperEngine.runTestsImpl(Engine.scala:483) [info] at org.scalatest.FunSuiteLike$class.runTests(FunSuiteLike.scala:208) [info] at org.scalatest.FunSuite.runTests(FunSuite.scala:1555) [info] at org.scalatest.Suite$class.run(Suite.scala:1424) [info] at org.scalatest.FunSuite.org$scalatest$FunSuiteLike$$super$run(FunSuite.scala:1555) [info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212) [info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212) [info] at org.scalatest.SuperEngine.runImpl(Engine.scala:545) [info] at org.scalatest.FunSuiteLike$class.run(FunSuiteLike.scala:212) [info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$run(StreamingListenerSuite.scala:34) [info] at org.scalatest.BeforeAndAfter$class.run(BeforeAndAfter.scala:241) [info] at org.apache.spark.streaming.StreamingListenerSuite.run(StreamingListenerSuite.scala:34) [info] at org.scalatest.tools.Framework.org$scalatest$tools$Framework$$runSuite(Framework.scala:462) [info] at org.scalatest.tools.Framework$ScalaTestTask.execute(Framework.scala:671) [info] at sbt.ForkMain$Run$2.call(ForkMain.java:294) [info] at sbt.ForkMain$Run$2.call(ForkMain.java:284) [info] at java.util.concurrent.FutureTask.run(FutureTask.java:262) [info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) [info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) [info] at java.lang.Thread.run(Thread.java:745) [info] Cause: org.scalatest.exceptions.TestFailedException: 0 did not equal 1 [info] at org.scalatest.MatchersHelper$.newTestFailedException(MatchersHelper.scala:160) [info] at org.scalatest.Matchers$ShouldMethodHelper$.shouldMatcher(Matchers.scala:6231) [info] at org.scalatest.Matchers$AnyShouldWrapper.should(Matchers.scala:6277) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2$$anonfun$apply$mcV$sp$1.apply$mcV$sp(StreamingListenerSuite.scala:105) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2$$anonfun$apply$mcV$sp$1.apply(StreamingListenerSuite.scala:104) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2$$anonfun$apply$mcV$sp$1.apply(StreamingListenerSuite.scala:104) [info] at org.scalatest.concurrent.Eventually$class.makeAValiantAttempt$1(Eventually.scala:394) [info] at org.scalatest.concurrent.Eventually$class.tryTryAgain$1(Eventually.scala:408) [info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:438) [info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478) [info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:307) [info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply$mcV$sp(StreamingListenerSuite.scala:104) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94) [info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94) [info] at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22) [info] at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85) [info] at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104) [info] at org.scalatest.Transformer.apply(Transformer.scala:22) [info] at org.scalatest.Transformer.apply(Transformer.scala:20) [info] at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166) [info] at org.scalatest.Suite$class.withFixture(Suite.scala:1122) [info] at org.scalatest.FunSuite.withFixture(FunSuite.scala:1555) [info] at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163) [info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175) [info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175) [info] at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306) [info] at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:175) [info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$runTest(StreamingListenerSuite.scala:34) [info] at org.scalatest.BeforeAndAfter$class.runTest(BeforeAndAfter.scala:200) [info] at org.apache.spark.streaming.StreamingListenerSuite.runTest(StreamingListenerSuite.scala:34) [info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208) [info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208) [info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:413) [info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:401) [info] at scala.collection.immutable.List.foreach(List.scala:318) [info] at org.scalatest.SuperEngine.traverseSubNodes$1(Engine.scala:401) [info] at org.scalatest.SuperEngine.org$scalatest$SuperEngine$$runTestsInBranch(Engine.scala:396) [info] at org.scalatest.SuperEngine.runTestsImpl(Engine.scala:483) [info] at org.scalatest.FunSuiteLike$class.runTests(FunSuiteLike.scala:208) [info] at org.scalatest.FunSuite.runTests(FunSuite.scala:1555) [info] at org.scalatest.Suite$class.run(Suite.scala:1424) [info] at org.scalatest.FunSuite.org$scalatest$FunSuiteLike$$super$run(FunSuite.scala:1555) [info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212) [info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212) [info] at org.scalatest.SuperEngine.runImpl(Engine.scala:545) [info] at org.scalatest.FunSuiteLike$class.run(FunSuiteLike.scala:212) [info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$run(StreamingListenerSuite.scala:34) [info] at org.scalatest.BeforeAndAfter$class.run(BeforeAndAfter.scala:241) [info] at org.apache.spark.streaming.StreamingListenerSuite.run(StreamingListenerSuite.scala:34) [info] at org.scalatest.tools.Framework.org$scalatest$tools$Framework$$runSuite(Framework.scala:462) [info] at org.scalatest.tools.Framework$ScalaTestTask.execute(Framework.scala:671) [info] at sbt.ForkMain$Run$2.call(ForkMain.java:294) [info] at sbt.ForkMain$Run$2.call(ForkMain.java:284) [info] at java.util.concurrent.FutureTask.run(FutureTask.java:262) [info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) [info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) [info] at java.lang.Thread.run(Thread.java:745) ``` The original codes didn't have a memory barrier in the `eventually` closure, which might fail the test, because JVM doesn't guarantee the memory consistency between different threads without a memory barrier. This PR used `ConcurrentLinkedQueue` to set up the memory barrier. Author: zsxwing Closes #5812 from zsxwing/SPARK-7282 and squashes the following commits: 59115ef [zsxwing] Use SynchronizedBuffer 014dd2b [zsxwing] Fix the race conditions in StreamingListenerSuite --- .../spark/streaming/StreamingListenerSuite.scala | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) 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..9020be166acf0 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 @@ -127,9 +127,9 @@ 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 +146,10 @@ 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 From b5347a4664625ede6ab9d8ef6558457a34ae423f Mon Sep 17 00:00:00 2001 From: Burak Yavuz Date: Thu, 30 Apr 2015 21:56:03 -0700 Subject: [PATCH 23/33] [SPARK-7248] implemented random number generators for DataFrames Adds the functions `rand` (Uniform Dist) and `randn` (Normal Dist.) as expressions to DataFrames. cc mengxr rxin Author: Burak Yavuz Closes #5819 from brkyvz/df-rng and squashes the following commits: 50d69d4 [Burak Yavuz] add seed for test that failed 4234c3a [Burak Yavuz] fix Rand expression 13cad5c [Burak Yavuz] couple fixes 7d53953 [Burak Yavuz] waiting for hive tests b453716 [Burak Yavuz] move radn with seed down 03637f0 [Burak Yavuz] fix broken hive func c5909eb [Burak Yavuz] deleted old implementation of Rand 6d43895 [Burak Yavuz] implemented random generators --- python/pyspark/sql/functions.py | 25 ++++++++- python/pyspark/sql/tests.py | 10 ++++ .../spark/sql/catalyst/expressions/Rand.scala | 36 ------------ .../sql/catalyst/expressions/random.scala | 56 +++++++++++++++++++ .../optimizer/ConstantFoldingSuite.scala | 4 +- .../org/apache/spark/sql/functions.scala | 30 +++++++++- .../org/apache/spark/sql/mathfunctions.scala | 2 - .../apache/spark/sql/JavaDataFrameSuite.java | 3 + .../spark/sql/ColumnExpressionSuite.scala | 22 ++++++++ .../org/apache/spark/sql/hive/HiveQl.scala | 7 +-- 10 files changed, 149 insertions(+), 46 deletions(-) delete mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala create mode 100644 sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/random.scala diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py index 555c2fa5e7071..241f82175726f 100644 --- a/python/pyspark/sql/functions.py +++ b/python/pyspark/sql/functions.py @@ -67,7 +67,6 @@ 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 +74,30 @@ def _(col): __all__.sort() +def rand(seed=None): + """ + Generate 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): + """ + Generate 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 approxCountDistinct(col, rsd=None): """Returns a new :class:`Column` for approximate distinct count of ``col``. diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py index 2ffd18ebd7c89..5640bb5ea2346 100644 --- a/python/pyspark/sql/tests.py +++ b/python/pyspark/sql/tests.py @@ -416,6 +416,16 @@ def assert_close(a, b): 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/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala deleted file mode 100644 index f5fea3f015dc4..0000000000000 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala +++ /dev/null @@ -1,36 +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.sql.catalyst.expressions - -import java.util.Random - -import org.apache.spark.sql.types.{DataType, DoubleType} - - -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 def toString: String = "RAND()" -} 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/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/core/src/main/scala/org/apache/spark/sql/functions.scala b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala index aa31d04a0cbe4..242e64d3ff881 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 @@ -25,7 +25,7 @@ import org.apache.spark.sql.catalyst.ScalaReflection import org.apache.spark.sql.catalyst.analysis.{UnresolvedFunction, Star} import org.apache.spark.sql.catalyst.expressions._ import org.apache.spark.sql.types._ - +import org.apache.spark.util.Utils /** * :: Experimental :: @@ -346,6 +346,34 @@ 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. * 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 d901542b7eaf3..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 @@ -27,8 +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 */ @Experimental // scalastyle:off 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 966d879e1fc9f..ebe96e649d940 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 @@ -104,6 +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 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/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 0a86519e1412b..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._ @@ -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) => From 36a7a6807ee58c8ba309c0e09e547919246b7f82 Mon Sep 17 00:00:00 2001 From: Zhan Zhang Date: Thu, 30 Apr 2015 22:24:31 -0700 Subject: [PATCH 24/33] [SPARK-6479] [BLOCK MANAGER] Create off-heap block storage API This is the classes for creating off-heap block storage API. It also includes the migration for Tachyon. The diff seems to be big, but it mainly just rename tachyon to offheap. New implementation for hdfs will be submit for review in spark-6112. Author: Zhan Zhang Closes #5430 from zhzhan/SPARK-6479 and squashes the following commits: 60acd84 [Zhan Zhang] minor change to kickoff the test 12f54c9 [Zhan Zhang] solve merge conflicts a54132c [Zhan Zhang] solve review comments ffb8e00 [Zhan Zhang] rebase to sparkcontext change 6e121e0 [Zhan Zhang] resolve review comments and restructure blockmanasger code a7aed6c [Zhan Zhang] add Tachyon migration code 186de31 [Zhan Zhang] initial commit for off-heap block storage api --- .../scala/org/apache/spark/SparkContext.scala | 8 +- .../spark/executor/ExecutorExitCode.scala | 16 +- .../main/scala/org/apache/spark/rdd/RDD.scala | 4 +- .../apache/spark/storage/BlockManager.scala | 63 +++--- .../spark/storage/BlockManagerMaster.scala | 5 +- .../storage/BlockManagerMasterEndpoint.scala | 29 +-- .../spark/storage/BlockManagerMessages.scala | 6 +- .../spark/storage/ExternalBlockManager.scala | 102 ++++++++++ .../spark/storage/ExternalBlockStore.scala | 181 ++++++++++++++++++ .../org/apache/spark/storage/RDDInfo.scala | 9 +- .../apache/spark/storage/StorageLevel.scala | 8 +- .../apache/spark/storage/StorageUtils.scala | 19 +- .../spark/storage/TachyonBlockManager.scala | 138 +++++++++---- .../spark/storage/TachyonFileSegment.scala | 30 --- .../apache/spark/storage/TachyonStore.scala | 128 ------------- .../apache/spark/ui/storage/StoragePage.scala | 4 +- .../org/apache/spark/util/JsonProtocol.scala | 24 ++- .../spark/storage/BlockManagerSuite.scala | 1 + .../apache/spark/storage/StorageSuite.scala | 8 +- .../spark/ui/storage/StorageTabSuite.scala | 6 +- .../apache/spark/util/JsonProtocolSuite.scala | 56 +++--- docs/configuration.md | 22 ++- 22 files changed, 536 insertions(+), 331 deletions(-) create mode 100644 core/src/main/scala/org/apache/spark/storage/ExternalBlockManager.scala create mode 100644 core/src/main/scala/org/apache/spark/storage/ExternalBlockStore.scala delete mode 100644 core/src/main/scala/org/apache/spark/storage/TachyonFileSegment.scala delete mode 100644 core/src/main/scala/org/apache/spark/storage/TachyonStore.scala diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index bae951f388337..fe24260cdb4c5 100644 --- a/core/src/main/scala/org/apache/spark/SparkContext.scala +++ b/core/src/main/scala/org/apache/spark/SparkContext.scala @@ -247,9 +247,11 @@ 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[")) @@ -386,7 +388,7 @@ 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") 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/rdd/RDD.scala b/core/src/main/scala/org/apache/spark/rdd/RDD.scala index 330255f89247f..31c07c73fe07b 100644 --- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala @@ -1475,9 +1475,9 @@ 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/storage/BlockManager.scala b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala index 55718e584c195..402ee1c7648c5 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) @@ -320,13 +312,13 @@ 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 +368,10 @@ 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 +389,17 @@ 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 +479,11 @@ 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 +492,7 @@ 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 +760,8 @@ 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 +796,7 @@ 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 +1093,11 @@ 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 +1131,7 @@ 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 +1211,8 @@ 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 9bfc4201d37c0..a85e1c7632973 100644 --- a/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala +++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala @@ -54,9 +54,10 @@ class BlockManagerMaster( storageLevel: StorageLevel, memSize: Long, diskSize: Long, - tachyonSize: Long): Boolean = { + externalBlockStoreSize: Long): Boolean = { val res = driverEndpoint.askWithRetry[Boolean]( - UpdateBlockInfo(blockManagerId, blockId, storageLevel, memSize, diskSize, tachyonSize)) + UpdateBlockInfo(blockManagerId, blockId, storageLevel, + memSize, diskSize, externalBlockStoreSize)) logDebug(s"Updated info of block $blockId") res } 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 7212362df5d71..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)) @@ -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/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 034525b56f59c..ad53a3edc7cc1 100644 --- a/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala +++ b/core/src/main/scala/org/apache/spark/storage/RDDInfo.scala @@ -32,16 +32,17 @@ 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 ("RDD \"%s\" (%d) StorageLevel: %s; CachedPartitions: %d; TotalPartitions: %d; " + - "MemorySize: %s; TachyonSize: %s; DiskSize: %s").format( + "MemorySize: %s; ExternalBlockStoreSize: %s; DiskSize: %s").format( name, id, storageLevel.toString, numCachedPartitions, numPartitions, - bytesToString(memSize), bytesToString(tachyonSize), bytesToString(diskSize)) + bytesToString(memSize), bytesToString(externalBlockStoreSize), bytesToString(diskSize)) } override def compare(that: RDDInfo): Int = { 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/TachyonFileSegment.scala b/core/src/main/scala/org/apache/spark/storage/TachyonFileSegment.scala deleted file mode 100644 index 65fa81704c365..0000000000000 --- a/core/src/main/scala/org/apache/spark/storage/TachyonFileSegment.scala +++ /dev/null @@ -1,30 +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 tachyon.client.TachyonFile - -/** - * References a particular segment of a file (potentially the entire file), based off an offset and - * a length. - */ -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) - } -} 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/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/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala index 474f79fb756f6..44d274956d693 100644 --- a/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala +++ b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala @@ -373,14 +373,14 @@ 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) } @@ -389,7 +389,7 @@ 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) } @@ -787,13 +787,15 @@ 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) rddInfo.numCachedPartitions = numCachedPartitions rddInfo.memSize = memSize - rddInfo.tachyonSize = tachyonSize + rddInfo.externalBlockStoreSize = externalBlockStoreSize rddInfo.diskSize = diskSize rddInfo } @@ -801,18 +803,22 @@ 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/test/scala/org/apache/spark/storage/BlockManagerSuite.scala b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala index f5b410f41da27..151955ef7f435 100644 --- a/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala +++ b/core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala @@ -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/StorageSuite.scala b/core/src/test/scala/org/apache/spark/storage/StorageSuite.scala index ef5c55f91c39a..ee1071cbcde69 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/storage/StorageTabSuite.scala b/core/src/test/scala/org/apache/spark/ui/storage/StorageTabSuite.scala index 3744e479d2f05..0ea9ea47b4288 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 @@ -133,12 +133,12 @@ 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) @@ -155,7 +155,7 @@ 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/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala index a2be724254d7c..2d039cb75a6e0 100644 --- a/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala +++ b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala @@ -785,14 +785,14 @@ 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 | } | ], @@ -969,12 +969,12 @@ 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 | } | } @@ -1052,12 +1052,12 @@ 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 | } | } @@ -1135,12 +1135,12 @@ 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 | } | } @@ -1168,14 +1168,14 @@ 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 | } | ], @@ -1207,14 +1207,14 @@ 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 | }, | { @@ -1223,14 +1223,14 @@ 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 | } | ], @@ -1262,14 +1262,14 @@ 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 | }, | { @@ -1278,14 +1278,14 @@ 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 | }, | { @@ -1294,14 +1294,14 @@ 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 | } | ], @@ -1333,14 +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": 800, | "Number of Cached Partitions": 1200, | "Memory Size": 1600, - | "Tachyon Size": 0, + | "ExternalBlockStore Size": 0, | "Disk Size": 2000 | }, | { @@ -1349,14 +1349,14 @@ 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 | }, | { @@ -1365,14 +1365,14 @@ 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 | }, | { @@ -1381,14 +1381,14 @@ 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 | } | ], diff --git a/docs/configuration.md b/docs/configuration.md index 72105feba4919..7239b252a9fcc 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. From a9fc50552ec96cd7817dfd19fc681b3368545ee3 Mon Sep 17 00:00:00 2001 From: Patrick Wendell Date: Thu, 30 Apr 2015 22:39:58 -0700 Subject: [PATCH 25/33] HOTFIX: Disable buggy dependency checker --- dev/run-tests-jenkins | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) 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 () { From 0a2b15ce43cf6096e1a7ae060b7c8a4010ce3b92 Mon Sep 17 00:00:00 2001 From: Sandy Ryza Date: Thu, 30 Apr 2015 23:14:14 -0700 Subject: [PATCH 26/33] [SPARK-4550] In sort-based shuffle, store map outputs in serialized form Refer to the JIRA for the design doc and some perf results. I wanted to call out some of the more possibly controversial changes up front: * Map outputs are only stored in serialized form when Kryo is in use. I'm still unsure whether Java-serialized objects can be relocated. At the very least, Java serialization writes out a stream header which causes problems with the current approach, so I decided to leave investigating this to future work. * The shuffle now explicitly operates on key-value pairs instead of any object. Data is written to shuffle files in alternating keys and values instead of key-value tuples. `BlockObjectWriter.write` now accepts a key argument and a value argument instead of any object. * The map output buffer can hold a max of Integer.MAX_VALUE bytes. Though this wouldn't be terribly difficult to change. * When spilling occurs, the objects that still in memory at merge time end up serialized and deserialized an extra time. Author: Sandy Ryza Closes #4450 from sryza/sandy-spark-4550 and squashes the following commits: 8c70dd9 [Sandy Ryza] Fix serialization 9c16fe6 [Sandy Ryza] Fix a couple tests and move getAutoReset to KryoSerializerInstance 6c54e06 [Sandy Ryza] Fix scalastyle d8462d8 [Sandy Ryza] SPARK-4550 --- .../spark/serializer/KryoSerializer.scala | 10 + .../apache/spark/serializer/Serializer.scala | 31 +++ .../shuffle/hash/HashShuffleWriter.scala | 2 +- .../spark/storage/BlockObjectWriter.scala | 37 ++- .../storage/ShuffleBlockFetcherIterator.scala | 6 +- .../spark/util/collection/ChainedBuffer.scala | 144 ++++++++++ .../collection/ExternalAppendOnlyMap.scala | 6 +- .../util/collection/ExternalSorter.scala | 144 +++++----- ...airCollection.scala => PairIterator.scala} | 16 +- .../collection/PartitionedAppendOnlyMap.scala | 44 +++ ...ffer.scala => PartitionedPairBuffer.scala} | 58 ++-- .../PartitionedSerializedPairBuffer.scala | 254 ++++++++++++++++++ .../SizeTrackingAppendOnlyMap.scala | 2 +- .../WritablePartitionedPairCollection.scala | 113 ++++++++ .../serializer/KryoSerializerSuite.scala | 15 ++ .../spark/serializer/TestSerializer.scala | 4 +- .../hash/HashShuffleManagerSuite.scala | 12 +- .../storage/BlockObjectWriterSuite.scala | 8 +- .../util/collection/ChainedBufferSuite.scala | 143 ++++++++++ .../util/collection/ExternalSorterSuite.scala | 189 +++++++++---- ...PartitionedSerializedPairBufferSuite.scala | 149 ++++++++++ .../sql/execution/SparkSqlSerializer2.scala | 38 ++- .../spark/tools/StoragePerfTester.scala | 5 +- 23 files changed, 1240 insertions(+), 190 deletions(-) create mode 100644 core/src/main/scala/org/apache/spark/util/collection/ChainedBuffer.scala rename core/src/main/scala/org/apache/spark/util/collection/{SizeTrackingPairCollection.scala => PairIterator.scala} (55%) create mode 100644 core/src/main/scala/org/apache/spark/util/collection/PartitionedAppendOnlyMap.scala rename core/src/main/scala/org/apache/spark/util/collection/{SizeTrackingPairBuffer.scala => PartitionedPairBuffer.scala} (66%) create mode 100644 core/src/main/scala/org/apache/spark/util/collection/PartitionedSerializedPairBuffer.scala create mode 100644 core/src/main/scala/org/apache/spark/util/collection/WritablePartitionedPairCollection.scala create mode 100644 core/src/test/scala/org/apache/spark/util/collection/ChainedBufferSuite.scala create mode 100644 core/src/test/scala/org/apache/spark/util/collection/PartitionedSerializedPairBufferSuite.scala 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/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/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/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/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 4ed8a740f99db..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)) } } @@ -618,8 +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 @@ -695,27 +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)) } } @@ -762,15 +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() @@ -799,7 +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 = { @@ -829,6 +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/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/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/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 de26aa351b0d2..20fd22b78ef5d 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) @@ -344,7 +393,7 @@ class ExternalSorterSuite extends FunSuite with LocalSparkContext with PrivateMe } 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) @@ -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) @@ -517,8 +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) @@ -534,8 +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) @@ -552,7 +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) @@ -609,7 +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) @@ -632,7 +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) @@ -656,7 +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) @@ -685,7 +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) @@ -718,8 +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/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/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() From 7cf1eb79b1fa290aa1d867a8a1eaaea86d6b2239 Mon Sep 17 00:00:00 2001 From: Burak Yavuz Date: Thu, 30 Apr 2015 23:39:58 -0700 Subject: [PATCH 27/33] [SPARK-7287] enabled fixed test andrewor14 pwendell I reenabled the test. Let's see if it's fixed. I did also notice that `--jars` started to fail after this was ignored though in the JIRA. like [here](https://amplab.cs.berkeley.edu/jenkins/job/Spark-Master-SBT/AMPLAB_JENKINS_BUILD_PROFILE=hadoop2.0,label=centos/2238/consoleFull), you see that --jars fails for the same exact reason. Has any change been made to Spark Submit recently? Did the test setup on Jenkins change? If we look into flaky tests last month, you wouldn't find this test among them. Author: Burak Yavuz Closes #5826 from brkyvz/restart-test and squashes the following commits: f509f68 [Burak Yavuz] enabled fixed test --- .../test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) 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 8360b94599547..35382be7e0ef1 100644 --- a/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala +++ b/core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala @@ -335,7 +335,7 @@ class SparkSubmitSuite extends FunSuite with Matchers with ResetSystemProperties runSparkSubmit(args) } - ignore("includes jars passed in through --packages") { + test("includes jars passed in through --packages") { val unusedJar = TestUtils.createJarWithClasses(Seq.empty) val main = MavenCoordinate("my.great.lib", "mylib", "0.1") val dep = MavenCoordinate("my.great.dep", "mylib", "0.1") From 14b32886fa01aef6cc0dfbc263eb6d4c9d2876fa Mon Sep 17 00:00:00 2001 From: zsxwing Date: Thu, 30 Apr 2015 23:44:33 -0700 Subject: [PATCH 28/33] [SPARK-7291] [CORE] Fix a flaky test in AkkaRpcEnvSuite Read the port from RpcEnv to check the result so that it will success even if port conflicts Author: zsxwing Closes #5822 from zsxwing/SPARK-7291 and squashes the following commits: e521b84 [zsxwing] Fix a flaky test in AkkaRpcEnvSuite --- .../test/scala/org/apache/spark/rpc/akka/AkkaRpcEnvSuite.scala | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) 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() From c24aeb6a310b49dba8db1f4642531780a2e27253 Mon Sep 17 00:00:00 2001 From: MechCoder Date: Thu, 30 Apr 2015 23:51:00 -0700 Subject: [PATCH 29/33] [SPARK-6257] [PYSPARK] [MLLIB] MLlib API missing items in Recommendation Adds rank, recommendUsers and RecommendProducts to MatrixFactorizationModel in PySpark. Author: MechCoder Closes #5807 from MechCoder/spark-6257 and squashes the following commits: 09629c6 [MechCoder] doc 953b326 [MechCoder] [SPARK-6257] MLlib API missing items in Recommendation --- docs/mllib-collaborative-filtering.md | 2 +- python/pyspark/mllib/recommendation.py | 39 ++++++++++++++++++++++++++ 2 files changed, 40 insertions(+), 1 deletion(-) 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/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) From 7fe0f3f2b46c61a5cc4af9166781624409fda8a4 Mon Sep 17 00:00:00 2001 From: Kousuke Saruta Date: Fri, 1 May 2015 01:39:56 -0700 Subject: [PATCH 30/33] [SPARK-3468] [WEBUI] Timeline-View feature I sometimes trouble-shoot and analyse the cause of long time spending job. At the time, I find the stages which spends long time or fails, then I find the tasks which spends long time or fails, next I analyse the proportion of each phase in a task. Another case, I find executors which spends long time for running a task and analyse the details of a task. In such situation, I think it's helpful to visualize timeline for each application, job, task and the details of proportion of activity for each task. I added 3 timeline features to existing Web UI. [Application Timeline View] This view shows following things. * When each executor was added/removed and the reason why it's removed. * When each job was started/finished. * Status of each job. ![screenshot from 2015-04-01 16 49 25](https://cloud.githubusercontent.com/assets/4736016/6936886/e35fd582-d891-11e4-980d-8de13f50e442.png) [Stage Timeline View] Similar to Application Timeline View, this view shows following things. * When each executor was added/removed and the reason why it's removed. * When each job was started/finished. * Status of each stage. ![screenshot from 2015-04-01 16 50 59](https://cloud.githubusercontent.com/assets/4736016/6936900/0dca6526-d892-11e4-84a8-efd9037af444.png) [Task Assignment Timeline View] This view shows following things. * When each task started/finished * How long each task spent and the proportion. * Status of each task. * Where each task ran on. ![screenshot from 2015-04-01 16 51 54](https://cloud.githubusercontent.com/assets/4736016/6936910/20fd5acc-d892-11e4-9018-80e463881fc2.png) All the view above is zoomable by mouse wheel action and scrollable by drag action. Author: Kousuke Saruta Closes #2342 from sarutak/timeline-viewer-feature and squashes the following commits: 11fe67d [Kousuke Saruta] Fixed conflict 79ac03d [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature a91abd3 [Kousuke Saruta] Merge branch 'master' of https://github.com/apache/spark into timeline-viewer-feature ef34a5b [Kousuke Saruta] Implement tooltip using bootstrap b09d0c5 [Kousuke Saruta] Move `stroke` and `fill` attribute of rect elements to css d3c63c8 [Kousuke Saruta] Fixed a little bit bugs a36291b [Kousuke Saruta] Merge branch 'master' of https://github.com/apache/spark into timeline-viewer-feature 28714b6 [Kousuke Saruta] Fixed highlight issue 0dc4278 [Kousuke Saruta] Addressed most of Patrics's feedbacks 8110acf [Kousuke Saruta] Added scroll limit to Job timeline 974a64a [Kousuke Saruta] Removed unused function ee7a7f0 [Kousuke Saruta] Refactored 6a91872 [Kousuke Saruta] Temporary commit 6693f34 [Kousuke Saruta] Added link to job/stage box in the timeline in order to move to corresponding row when we click 8f88222 [Kousuke Saruta] Added job/stage description aeed4b1 [Kousuke Saruta] Removed stage timeline fc1696c [Kousuke Saruta] Merge branch 'timeline-viewer-feature' of github.com:sarutak/spark into timeline-viewer-feature 999ccd4 [Kousuke Saruta] Improved scalability 0fc6a31 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature 19815ae [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature 68b7540 [Kousuke Saruta] Merge branch 'timeline-viewer-feature' of github.com:sarutak/spark into timeline-viewer-feature 52b5f0b [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature dec85db [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature fcdab7d [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature dab7cc1 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature 09cce97 [Kousuke Saruta] Cleanuped 16f82cf [Kousuke Saruta] Cleanuped 9fb522e [Kousuke Saruta] Cleanuped d05f2c2 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature e85e9aa [Kousuke Saruta] Cleanup: Added TimelineViewUtils.scala a76e569 [Kousuke Saruta] Removed unused setting in timeline-view.css 5ce1b21 [Kousuke Saruta] Added vis.min.js, vis.min.css and vis.map to .rat-exclude 082f709 [Kousuke Saruta] Added Timeline-View feature for Applications, Jobs and Stages --- .rat-excludes | 3 + .../apache/spark/ui/static/timeline-view.css | 182 ++++++++++++++++ .../apache/spark/ui/static/timeline-view.js | 168 +++++++++++++++ .../org/apache/spark/ui/static/vis.map | 1 + .../org/apache/spark/ui/static/vis.min.css | 1 + .../org/apache/spark/ui/static/vis.min.js | 39 ++++ .../apache/spark/scheduler/StageInfo.scala | 12 ++ .../scala/org/apache/spark/ui/UIUtils.scala | 5 + .../apache/spark/ui/exec/ExecutorsTab.scala | 11 + .../apache/spark/ui/jobs/AllJobsPage.scala | 200 ++++++++++++++++-- .../org/apache/spark/ui/jobs/JobPage.scala | 174 ++++++++++++++- .../spark/ui/jobs/JobProgressListener.scala | 7 + .../org/apache/spark/ui/jobs/JobsTab.scala | 6 +- .../org/apache/spark/ui/jobs/StageTable.scala | 3 +- .../org/apache/spark/ui/jobs/UIData.scala | 5 + 15 files changed, 785 insertions(+), 32 deletions(-) create mode 100644 core/src/main/resources/org/apache/spark/ui/static/timeline-view.css create mode 100644 core/src/main/resources/org/apache/spark/ui/static/timeline-view.js create mode 100644 core/src/main/resources/org/apache/spark/ui/static/vis.map create mode 100644 core/src/main/resources/org/apache/spark/ui/static/vis.min.css create mode 100644 core/src/main/resources/org/apache/spark/ui/static/vis.min.js diff --git a/.rat-excludes b/.rat-excludes index 8aca5a7f7a967..4468da19008bc 100644 --- a/.rat-excludes +++ b/.rat-excludes @@ -30,6 +30,9 @@ log4j-defaults.properties bootstrap-tooltip.js jquery-1.11.1.min.js sorttable.js +vis.min.js +vis.min.css +vis.map .*avsc .*txt .*json 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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0===i&&(i="#FF0000"),4==t.childrenCount&&(this._drawBranch(t.children.NW,e),this._drawBranch(t.children.NE,e),this._drawBranch(t.children.SE,e),this._drawBranch(t.children.SW,e)),e.strokeStyle=i,e.beginPath(),e.moveTo(t.range.minX,t.range.minY),e.lineTo(t.range.maxX,t.range.minY),e.stroke(),e.beginPath(),e.moveTo(t.range.maxX,t.range.minY),e.lineTo(t.range.maxX,t.range.maxY),e.stroke(),e.beginPath(),e.moveTo(t.range.maxX,t.range.maxY),e.lineTo(t.range.minX,t.range.maxY),e.stroke(),e.beginPath(),e.moveTo(t.range.minX,t.range.maxY),e.lineTo(t.range.minX,t.range.minY),e.stroke()}},function(t){t.exports=function(t){return t.webpackPolyfill||(t.deprecate=function(){},t.paths=[],t.children=[],t.webpackPolyfill=1),t}},function(t,e){(function(e){t.exports=e}).call(e,{})}])}); +//# sourceMappingURL=vis.map 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 c6dc3369ba5cc..cf3db0b94a0b3 100644 --- a/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala +++ b/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala @@ -47,6 +47,18 @@ 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/ui/UIUtils.scala b/core/src/main/scala/org/apache/spark/ui/UIUtils.scala index f07864141a21c..395af2ea30b9d 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" /> + + + + } /** Returns a spark page with correctly formatted headers */ 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 7541d3e9c72e7..dd968e124738e 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 @@ -17,20 +17,167 @@ 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 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") @@ -54,11 +201,11 @@ private[ui] class JobPage(parent: JobsTab) extends WebUIPage("job") { new StageInfo(stageId, 0, "Unknown", 0, 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 @@ -75,18 +222,18 @@ 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 @@ -154,6 +301,11 @@ private[ui] class JobPage(parent: JobsTab) extends WebUIPage("job") { var content = summary + val appStartTime = listener.startTime + val executorListener = parent.executorListener + content ++= makeTimeline(activeStages ++ completedStages ++ failedStages, + executorListener.executorIdToData, appStartTime) + 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 625596885faa1..d6d716de25920 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 @@ -50,6 +50,9 @@ 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]() @@ -75,6 +78,7 @@ 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 @@ -516,6 +520,9 @@ class JobProgressListener(conf: SparkConf) extends SparkListener with Logging { } } + override def onApplicationStart(appStarted: SparkListenerApplicationStart) { + startTime = appStarted.time + } } private object JobProgressListener { 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 7ffcf291b5cc6..342787f1a3c2d 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 @@ -24,8 +24,10 @@ 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) - val listener = parent.jobProgressListener + def isFairScheduler: Boolean = + jobProgresslistener.schedulingMode.exists(_ == SchedulingMode.FAIR) + val jobProgresslistener = parent.jobProgressListener + val executorListener = parent.executorsListener 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..6d8c7e1fda8d8 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 @@ -174,7 +174,8 @@ 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 935c8a4f80e7b..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 @@ -108,4 +108,9 @@ private[spark] 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) } From 3052f4916e7f2c7fbc4837f00f4463b7d0b34718 Mon Sep 17 00:00:00 2001 From: Marcelo Vanzin Date: Fri, 1 May 2015 09:50:55 -0500 Subject: [PATCH 31/33] [SPARK-4705] Handle multiple app attempts event logs, history server. This change modifies the event logging listener to write the logs for different application attempts to different files. The attempt ID is set by the scheduler backend, so as long as the backend returns that ID to SparkContext, things should work. Currently, the YARN backend does that. The history server was also modified to model multiple attempts per application. Each attempt has its own UI and a separate row in the listing table, so that users can look at all the attempts separately. The UI "adapts" itself to avoid showing attempt-specific info when all the applications being shown have a single attempt. Author: Marcelo Vanzin Author: twinkle sachdeva Author: twinkle.sachdeva Author: twinkle sachdeva Closes #5432 from vanzin/SPARK-4705 and squashes the following commits: 7e289fa [Marcelo Vanzin] Review feedback. f66dcc5 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705 bc885b7 [Marcelo Vanzin] Review feedback. 76a3651 [Marcelo Vanzin] Fix log cleaner, add test. 7c381ec [Marcelo Vanzin] Merge branch 'master' into SPARK-4705 1aa309d [Marcelo Vanzin] Improve sorting of app attempts. 2ad77e7 [Marcelo Vanzin] Missed a reference to the old property name. 9d59d92 [Marcelo Vanzin] Scalastyle... d5a9c37 [Marcelo Vanzin] Update JsonProtocol test, make property name consistent. ba34b69 [Marcelo Vanzin] Use Option[String] for attempt id. f1cb9b3 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705 c14ec19 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705 9092d39 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705 86de638 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705 07446c6 [Marcelo Vanzin] Disable striping for app id / name when multiple attempts exist. 9092af5 [Marcelo Vanzin] Fix HistoryServer test. 3a14503 [Marcelo Vanzin] Argh scalastyle. 657ec18 [Marcelo Vanzin] Fix yarn history URL, app links. c3e0a82 [Marcelo Vanzin] Move app name to app info, more UI fixes. ce5ee5d [Marcelo Vanzin] Misc UI, test, style fixes. cbe8bba [Marcelo Vanzin] Attempt ID in listener event should be an option. 88b1de8 [Marcelo Vanzin] Add a test for apps with multiple attempts. 3245aa2 [Marcelo Vanzin] Make app attempts part of the history server model. 5fd5c6f [Marcelo Vanzin] Fix my broken rebase. 318525a [twinkle.sachdeva] SPARK-4705: 1) moved from directory structure to single file, as per the master branch. 2) Added the attempt id inside the SparkListenerApplicationStart, to make the info available independent of directory structure. 3) Changes in History Server to render the UI as per the snaphot II 6b2e521 [twinkle sachdeva] SPARK-4705 Incorporating the review comments regarding formatting, will do the rest of the changes after this 4c1fc26 [twinkle sachdeva] SPARK-4705 Incorporating the review comments regarding formatting, will do the rest of the changes after this 0eb7722 [twinkle sachdeva] SPARK-4705: Doing cherry-pick of fix into master --- .../scala/org/apache/spark/SparkContext.scala | 8 +- .../history/ApplicationHistoryProvider.scala | 13 +- .../deploy/history/FsHistoryProvider.scala | 211 +++++++++------ .../spark/deploy/history/HistoryPage.scala | 111 ++++++-- .../spark/deploy/history/HistoryServer.scala | 24 +- .../apache/spark/deploy/master/Master.scala | 20 +- .../scheduler/ApplicationEventListener.scala | 2 + .../scheduler/EventLoggingListener.scala | 28 +- .../spark/scheduler/SchedulerBackend.scala | 8 + .../spark/scheduler/SparkListener.scala | 4 +- .../spark/scheduler/TaskScheduler.scala | 10 +- .../spark/scheduler/TaskSchedulerImpl.scala | 2 + .../org/apache/spark/util/JsonProtocol.scala | 6 +- .../history/FsHistoryProviderSuite.scala | 243 ++++++++++++++---- .../deploy/history/HistoryServerSuite.scala | 3 +- .../spark/scheduler/DAGSchedulerSuite.scala | 2 + .../scheduler/EventLoggingListenerSuite.scala | 18 +- .../spark/scheduler/ReplayListenerSuite.scala | 4 +- .../apache/spark/util/JsonProtocolSuite.scala | 11 +- .../spark/deploy/yarn/ApplicationMaster.scala | 7 +- .../cluster/YarnClusterSchedulerBackend.scala | 12 +- 21 files changed, 546 insertions(+), 201 deletions(-) diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala index fe24260cdb4c5..3f7cba6dbcdb5 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 @@ -315,6 +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 @@ -472,6 +474,7 @@ 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) @@ -484,7 +487,8 @@ 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) @@ -1868,7 +1872,7 @@ 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/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..dc6077f3d132b 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") @@ -758,24 +758,24 @@ 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 +859,8 @@ 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/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/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/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/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/util/JsonProtocol.scala b/core/src/main/scala/org/apache/spark/util/JsonProtocol.scala index 44d274956d693..ee02fbd9ce069 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 = { @@ -562,7 +563,8 @@ 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 = { 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/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/util/JsonProtocolSuite.scala b/core/src/test/scala/org/apache/spark/util/JsonProtocolSuite.scala index 2d039cb75a6e0..0c9cf5bc685c1 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)) } @@ -1497,8 +1500,10 @@ 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/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..27f804782f355 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 @@ -89,6 +89,10 @@ 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) @@ -208,10 +212,11 @@ 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, 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 + } } From 3b514af8a0c2ca496315b99a2b09bc887ac6c5e1 Mon Sep 17 00:00:00 2001 From: Debasish Das Date: Fri, 1 May 2015 08:27:46 -0700 Subject: [PATCH 32/33] [SPARK-3066] [MLLIB] Support recommendAll in matrix factorization model This is based on #3098 from debasish83. 1. BLAS' GEMM is used to compute inner products. 2. Reverted changes to MovieLensALS. SPARK-4231 should be addressed in a separate PR. 3. ~~Fixed a bug in topByKey~~ Closes #3098 debasish83 coderxiang Author: Debasish Das Author: Xiangrui Meng Closes #5829 from mengxr/SPARK-3066 and squashes the following commits: 22e6a87 [Xiangrui Meng] topByKey was correct. update its usage 389b381 [Xiangrui Meng] fix indentation 49953de [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-3066 cb9799a [Xiangrui Meng] revert MovieLensALS f864f5e [Xiangrui Meng] update test and fix a bug in topByKey c5e0181 [Xiangrui Meng] use GEMM and topByKey 3a0c4eb [Debasish Das] updated with spark master 98fa424 [Debasish Das] updated with master ee99571 [Debasish Das] addressed initial review comments;merged with master;added tests for batch predict APIs in matrix factorization 3f97c49 [Debasish Das] fixed spark coding style for imports 7163a5c [Debasish Das] Added API for batch user and product recommendation; MAP calculation for product recommendation per user using randomized split d144f57 [Debasish Das] recommendAll API to MatrixFactorizationModel, uses topK finding using BoundedPriorityQueue similar to RDD.top f38a1b5 [Debasish Das] use sampleByKey for per user sampling 10cbb37 [Debasish Das] provide ratio for topN product validation; generate MAP and prec@k metric for movielens dataset 9fa063e [Debasish Das] import scala.math.round 4bbae0f [Debasish Das] comments fixed as per scalastyle cd3ab31 [Debasish Das] merged with AbstractParams serialization bug 9b3951f [Debasish Das] validate user/product on MovieLens dataset through user input and compute map measure along with rmse --- .../spark/mllib/rdd/MLPairRDDFunctions.scala | 4 +- .../MatrixFactorizationModel.scala | 132 +++++++++++++++--- .../mllib/rdd/MLPairRDDFunctionsSuite.scala | 4 +- .../MatrixFactorizationModelSuite.scala | 20 +++ 4 files changed, 138 insertions(+), 22 deletions(-) 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/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) + } } From 7630213cab1f653212828f045cf1d7d1870abea0 Mon Sep 17 00:00:00 2001 From: Liang-Chi Hsieh Date: Fri, 1 May 2015 08:31:01 -0700 Subject: [PATCH 33/33] [SPARK-5891] [ML] Add Binarizer ML Transformer JIRA: https://issues.apache.org/jira/browse/SPARK-5891 Author: Liang-Chi Hsieh Closes #5699 from viirya/add_binarizer and squashes the following commits: 1a0b9a4 [Liang-Chi Hsieh] For comments. bc397f2 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into add_binarizer cc4f03c [Liang-Chi Hsieh] Implement threshold param and use merged params map. 7564c63 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into add_binarizer 1682f8c [Liang-Chi Hsieh] Add Binarizer ML Transformer. --- .../apache/spark/ml/feature/Binarizer.scala | 85 +++++++++++++++++++ .../spark/ml/feature/BinarizerSuite.scala | 69 +++++++++++++++ 2 files changed, 154 insertions(+) create mode 100644 mllib/src/main/scala/org/apache/spark/ml/feature/Binarizer.scala create mode 100644 mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala 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/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.") + } + } +}