Resolved merge conflict

R/README.md

@@ -6,7 +6,7 @@ SparkR is an R package that provides a light-weight frontend to use Spark from R
 
 #### Build Spark
 
-Build Spark with [Maven](http://spark.apache.org/docs/latest/building-spark.html#building-with-buildmvn) and include the `-PsparkR` profile to build the R package. For example to use the default Hadoop versions you can run
+Build Spark with [Maven](http://spark.apache.org/docs/latest/building-spark.html#building-with-buildmvn) and include the `-Psparkr` profile to build the R package. For example to use the default Hadoop versions you can run
 ```
   build/mvn -DskipTests -Psparkr package
 ```

R/pkg/R/generics.R

@@ -20,7 +20,8 @@
 # @rdname aggregateRDD
 # @seealso reduce
 # @export
-setGeneric("aggregateRDD", function(x, zeroValue, seqOp, combOp) { standardGeneric("aggregateRDD") })
+setGeneric("aggregateRDD",
+           function(x, zeroValue, seqOp, combOp) { standardGeneric("aggregateRDD") })
 
 # @rdname cache-methods
 # @export

R/pkg/R/pairRDD.R

@@ -560,8 +560,8 @@ setMethod("join",
 # Left outer join two RDDs
 #
 # @description
-# \code{leftouterjoin} This function left-outer-joins two RDDs where every element is of the form list(K, V).
-# The key types of the two RDDs should be the same.
+# \code{leftouterjoin} This function left-outer-joins two RDDs where every element is of
+# the form list(K, V). The key types of the two RDDs should be the same.
 #
 # @param x An RDD to be joined. Should be an RDD where each element is
 #             list(K, V).
@@ -597,8 +597,8 @@ setMethod("leftOuterJoin",
 # Right outer join two RDDs
 #
 # @description
-# \code{rightouterjoin} This function right-outer-joins two RDDs where every element is of the form list(K, V).
-# The key types of the two RDDs should be the same.
+# \code{rightouterjoin} This function right-outer-joins two RDDs where every element is of
+# the form list(K, V). The key types of the two RDDs should be the same.
 #
 # @param x An RDD to be joined. Should be an RDD where each element is
 #             list(K, V).
@@ -634,8 +634,8 @@ setMethod("rightOuterJoin",
 # Full outer join two RDDs
 #
 # @description
-# \code{fullouterjoin} This function full-outer-joins two RDDs where every element is of the form list(K, V).
-# The key types of the two RDDs should be the same.
+# \code{fullouterjoin} This function full-outer-joins two RDDs where every element is of
+# the form list(K, V). The key types of the two RDDs should be the same.
 #
 # @param x An RDD to be joined. Should be an RDD where each element is
 #             list(K, V).

R/pkg/R/sparkR.R

@@ -105,7 +105,8 @@ sparkR.init <- function(
   sparkPackages = "") {
 
   if (exists(".sparkRjsc", envir = .sparkREnv)) {
-    cat("Re-using existing Spark Context. Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context\n")
+    cat(paste("Re-using existing Spark Context.",
+              "Please stop SparkR with sparkR.stop() or restart R to create a new Spark Context\n"))
     return(get(".sparkRjsc", envir = .sparkREnv))
   }
 
@@ -180,14 +181,16 @@ sparkR.init <- function(
 
   sparkExecutorEnvMap <- new.env()
   if (!any(names(sparkExecutorEnv) == "LD_LIBRARY_PATH")) {
-    sparkExecutorEnvMap[["LD_LIBRARY_PATH"]] <- paste0("$LD_LIBRARY_PATH:",Sys.getenv("LD_LIBRARY_PATH"))
+    sparkExecutorEnvMap[["LD_LIBRARY_PATH"]] <-
+      paste0("$LD_LIBRARY_PATH:",Sys.getenv("LD_LIBRARY_PATH"))
   }
   for (varname in names(sparkExecutorEnv)) {
     sparkExecutorEnvMap[[varname]] <- sparkExecutorEnv[[varname]]
   }
 
   nonEmptyJars <- Filter(function(x) { x != "" }, jars)
-  localJarPaths <- sapply(nonEmptyJars, function(j) { utils::URLencode(paste("file:", uriSep, j, sep = "")) })
+  localJarPaths <- sapply(nonEmptyJars,
+                          function(j) { utils::URLencode(paste("file:", uriSep, j, sep = "")) })
 
   # Set the start time to identify jobjs
   # Seconds resolution is good enough for this purpose, so use ints

R/pkg/R/utils.R

@@ -334,18 +334,21 @@ getStorageLevel <- function(newLevel = c("DISK_ONLY",
                                          "MEMORY_ONLY_SER_2",
                                          "OFF_HEAP")) {
   match.arg(newLevel)
+  storageLevelClass <- "org.apache.spark.storage.StorageLevel"
   storageLevel <- switch(newLevel,
-                         "DISK_ONLY" = callJStatic("org.apache.spark.storage.StorageLevel", "DISK_ONLY"),
-                         "DISK_ONLY_2" = callJStatic("org.apache.spark.storage.StorageLevel", "DISK_ONLY_2"),
-                         "MEMORY_AND_DISK" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK"),
-                         "MEMORY_AND_DISK_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK_2"),
-                         "MEMORY_AND_DISK_SER" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK_SER"),
-                         "MEMORY_AND_DISK_SER_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_AND_DISK_SER_2"),
-                         "MEMORY_ONLY" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY"),
-                         "MEMORY_ONLY_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY_2"),
-                         "MEMORY_ONLY_SER" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY_SER"),
-                         "MEMORY_ONLY_SER_2" = callJStatic("org.apache.spark.storage.StorageLevel", "MEMORY_ONLY_SER_2"),
-                         "OFF_HEAP" = callJStatic("org.apache.spark.storage.StorageLevel", "OFF_HEAP"))
+                         "DISK_ONLY" = callJStatic(storageLevelClass, "DISK_ONLY"),
+                         "DISK_ONLY_2" = callJStatic(storageLevelClass, "DISK_ONLY_2"),
+                         "MEMORY_AND_DISK" = callJStatic(storageLevelClass, "MEMORY_AND_DISK"),
+                         "MEMORY_AND_DISK_2" = callJStatic(storageLevelClass, "MEMORY_AND_DISK_2"),
+                         "MEMORY_AND_DISK_SER" = callJStatic(storageLevelClass,
+                                                             "MEMORY_AND_DISK_SER"),
+                         "MEMORY_AND_DISK_SER_2" = callJStatic(storageLevelClass,
+                                                               "MEMORY_AND_DISK_SER_2"),
+                         "MEMORY_ONLY" = callJStatic(storageLevelClass, "MEMORY_ONLY"),
+                         "MEMORY_ONLY_2" = callJStatic(storageLevelClass, "MEMORY_ONLY_2"),
+                         "MEMORY_ONLY_SER" = callJStatic(storageLevelClass, "MEMORY_ONLY_SER"),
+                         "MEMORY_ONLY_SER_2" = callJStatic(storageLevelClass, "MEMORY_ONLY_SER_2"),
+                         "OFF_HEAP" = callJStatic(storageLevelClass, "OFF_HEAP"))
 }
 
 # Utility function for functions where an argument needs to be integer but we want to allow
@@ -545,9 +548,11 @@ mergePartitions <- function(rdd, zip) {
         lengthOfKeys <- part[[len - lengthOfValues]]
         stopifnot(len == lengthOfKeys + lengthOfValues)
 
-        # For zip operation, check if corresponding partitions of both RDDs have the same number of elements.
+        # For zip operation, check if corresponding partitions
+        # of both RDDs have the same number of elements.
         if (zip && lengthOfKeys != lengthOfValues) {
-          stop("Can only zip RDDs with same number of elements in each pair of corresponding partitions.")
+          stop(paste("Can only zip RDDs with same number of elements",
+                     "in each pair of corresponding partitions."))
         }
 
         if (lengthOfKeys > 1) {

R/pkg/inst/tests/test_includeJAR.R

@@ -18,8 +18,8 @@ context("include an external JAR in SparkContext")
 
 runScript <- function() {
   sparkHome <- Sys.getenv("SPARK_HOME")
-  jarPath <- paste("--jars",
-                   shQuote(file.path(sparkHome, "R/lib/SparkR/test_support/sparktestjar_2.10-1.0.jar")))
+  sparkTestJarPath <- "R/lib/SparkR/test_support/sparktestjar_2.10-1.0.jar"
+  jarPath <- paste("--jars", shQuote(file.path(sparkHome, sparkTestJarPath)))
   scriptPath <- file.path(sparkHome, "R/lib/SparkR/tests/jarTest.R")
   submitPath <- file.path(sparkHome, "bin/spark-submit")
   res <- system2(command = submitPath,

R/pkg/inst/tests/test_rdd.R

@@ -669,27 +669,31 @@ test_that("fullOuterJoin() on pairwise RDDs", {
   rdd1 <- parallelize(sc, list(list(1,2), list(1,3), list(3,3)))
   rdd2 <- parallelize(sc, list(list(1,1), list(2,4)))
   actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
-  expected <- list(list(1, list(2, 1)), list(1, list(3, 1)), list(2, list(NULL, 4)), list(3, list(3, NULL)))
+  expected <- list(list(1, list(2, 1)), list(1, list(3, 1)),
+                   list(2, list(NULL, 4)), list(3, list(3, NULL)))
   expect_equal(sortKeyValueList(actual), sortKeyValueList(expected))
 
   rdd1 <- parallelize(sc, list(list("a",2), list("a",3), list("c", 1)))
   rdd2 <- parallelize(sc, list(list("a",1), list("b",4)))
   actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
-  expected <- list(list("b", list(NULL, 4)), list("a", list(2, 1)), list("a", list(3, 1)), list("c", list(1, NULL)))
+  expected <- list(list("b", list(NULL, 4)), list("a", list(2, 1)),
+                   list("a", list(3, 1)), list("c", list(1, NULL)))
   expect_equal(sortKeyValueList(actual),
                sortKeyValueList(expected))
 
   rdd1 <- parallelize(sc, list(list(1,1), list(2,2)))
   rdd2 <- parallelize(sc, list(list(3,3), list(4,4)))
   actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
   expect_equal(sortKeyValueList(actual),
-               sortKeyValueList(list(list(1, list(1, NULL)), list(2, list(2, NULL)), list(3, list(NULL, 3)), list(4, list(NULL, 4)))))
+               sortKeyValueList(list(list(1, list(1, NULL)), list(2, list(2, NULL)),
+                                     list(3, list(NULL, 3)), list(4, list(NULL, 4)))))
 
   rdd1 <- parallelize(sc, list(list("a",1), list("b",2)))
   rdd2 <- parallelize(sc, list(list("c",3), list("d",4)))
   actual <- collect(fullOuterJoin(rdd1, rdd2, 2L))
   expect_equal(sortKeyValueList(actual),
-               sortKeyValueList(list(list("a", list(1, NULL)), list("b", list(2, NULL)), list("d", list(NULL, 4)), list("c", list(NULL, 3)))))
+               sortKeyValueList(list(list("a", list(1, NULL)), list("b", list(2, NULL)),
+                                     list("d", list(NULL, 4)), list("c", list(NULL, 3)))))
 })
 
 test_that("sortByKey() on pairwise RDDs", {

R/pkg/inst/tests/test_sparkSQL.R

@@ -391,7 +391,7 @@ test_that("collect() and take() on a DataFrame return the same number of rows an
   expect_equal(ncol(collect(df)), ncol(take(df, 10)))
 })
 
-test_that("multiple pipeline transformations starting with a DataFrame result in an RDD with the correct values", {
+test_that("multiple pipeline transformations result in an RDD with the correct values", {
   df <- jsonFile(sqlContext, jsonPath)
   first <- lapply(df, function(row) {
     row$age <- row$age + 5
@@ -756,7 +756,14 @@ test_that("toJSON() returns an RDD of the correct values", {
 test_that("showDF()", {
   df <- jsonFile(sqlContext, jsonPath)
   s <- capture.output(showDF(df))
-  expect_output(s , "+----+-------+\n| age|   name|\n+----+-------+\n|null|Michael|\n|  30|   Andy|\n|  19| Justin|\n+----+-------+\n")
+  expected <- paste("+----+-------+\n",
+                    "| age|   name|\n",
+                    "+----+-------+\n",
+                    "|null|Michael|\n",
+                    "|  30|   Andy|\n",
+                    "|  19| Justin|\n",
+                    "+----+-------+\n", sep="")
+  expect_output(s , expected)
 })
 
 test_that("isLocal()", {

core/src/main/scala/org/apache/spark/deploy/JsonProtocol.scala

@@ -76,12 +76,13 @@ private[deploy] object JsonProtocol {
   }
 
   def writeMasterState(obj: MasterStateResponse): JObject = {
+    val aliveWorkers = obj.workers.filter(_.isAlive())
     ("url" -> obj.uri) ~
     ("workers" -> obj.workers.toList.map(writeWorkerInfo)) ~
-    ("cores" -> obj.workers.map(_.cores).sum) ~
-    ("coresused" -> obj.workers.map(_.coresUsed).sum) ~
-    ("memory" -> obj.workers.map(_.memory).sum) ~
-    ("memoryused" -> obj.workers.map(_.memoryUsed).sum) ~
+    ("cores" -> aliveWorkers.map(_.cores).sum) ~
+    ("coresused" -> aliveWorkers.map(_.coresUsed).sum) ~
+    ("memory" -> aliveWorkers.map(_.memory).sum) ~
+    ("memoryused" -> aliveWorkers.map(_.memoryUsed).sum) ~
     ("activeapps" -> obj.activeApps.toList.map(writeApplicationInfo)) ~
     ("completedapps" -> obj.completedApps.toList.map(writeApplicationInfo)) ~
     ("activedrivers" -> obj.activeDrivers.toList.map(writeDriverInfo)) ~

core/src/main/scala/org/apache/spark/deploy/master/WorkerInfo.scala

@@ -105,4 +105,6 @@ private[spark] class WorkerInfo(
   def setState(state: WorkerState.Value): Unit = {
     this.state = state
   }
+
+  def isAlive(): Boolean = this.state == WorkerState.ALIVE
 }

core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/CoarseMesosSchedulerBackend.scala

@@ -18,18 +18,18 @@
 package org.apache.spark.scheduler.cluster.mesos
 
 import java.io.File
-import java.util.{Collections, List => JList}
+import java.util.{List => JList}
 
 import scala.collection.JavaConversions._
 import scala.collection.mutable.{HashMap, HashSet}
 
-import org.apache.mesos.Protos.{TaskInfo => MesosTaskInfo, _}
 import org.apache.mesos.{Scheduler => MScheduler, _}
+import org.apache.mesos.Protos.{TaskInfo => MesosTaskInfo, _}
+import org.apache.spark.{SparkContext, SparkEnv, SparkException, TaskState}
 import org.apache.spark.rpc.RpcAddress
 import org.apache.spark.scheduler.TaskSchedulerImpl
 import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
 import org.apache.spark.util.Utils
-import org.apache.spark.{SparkContext, SparkEnv, SparkException, TaskState}
 
 /**
  * A SchedulerBackend that runs tasks on Mesos, but uses "coarse-grained" tasks, where it holds
@@ -66,6 +66,10 @@ private[spark] class CoarseMesosSchedulerBackend(
 
   val extraCoresPerSlave = conf.getInt("spark.mesos.extra.cores", 0)
 
+  // Offer constraints
+  private val slaveOfferConstraints =
+    parseConstraintString(sc.conf.get("spark.mesos.constraints", ""))
+
   var nextMesosTaskId = 0
 
   @volatile var appId: String = _
@@ -170,13 +174,16 @@ private[spark] class CoarseMesosSchedulerBackend(
   override def resourceOffers(d: SchedulerDriver, offers: JList[Offer]) {
     synchronized {
       val filters = Filters.newBuilder().setRefuseSeconds(5).build()
-
       for (offer <- offers) {
+        val offerAttributes = toAttributeMap(offer.getAttributesList)
+        val meetsConstraints = matchesAttributeRequirements(slaveOfferConstraints, offerAttributes)
         val slaveId = offer.getSlaveId.toString
         val mem = getResource(offer.getResourcesList, "mem")
         val cpus = getResource(offer.getResourcesList, "cpus").toInt
-        if (totalCoresAcquired < maxCores &&
-            mem >= MemoryUtils.calculateTotalMemory(sc) &&
+        val id = offer.getId.getValue
+        if (meetsConstraints &&
+            totalCoresAcquired < maxCores &&
+            mem >= calculateTotalMemory(sc) &&
             cpus >= 1 &&
             failuresBySlaveId.getOrElse(slaveId, 0) < MAX_SLAVE_FAILURES &&
             !slaveIdsWithExecutors.contains(slaveId)) {
@@ -193,33 +200,25 @@ private[spark] class CoarseMesosSchedulerBackend(
             .setCommand(createCommand(offer, cpusToUse + extraCoresPerSlave))
             .setName("Task " + taskId)
             .addResources(createResource("cpus", cpusToUse))
-            .addResources(createResource("mem",
-              MemoryUtils.calculateTotalMemory(sc)))
+            .addResources(createResource("mem", calculateTotalMemory(sc)))
 
           sc.conf.getOption("spark.mesos.executor.docker.image").foreach { image =>
             MesosSchedulerBackendUtil
-              .setupContainerBuilderDockerInfo(image, sc.conf, task.getContainerBuilder())
+              .setupContainerBuilderDockerInfo(image, sc.conf, task.getContainerBuilder)
           }
 
-          d.launchTasks(
-            Collections.singleton(offer.getId), Collections.singletonList(task.build()), filters)
+          // accept the offer and launch the task
+          logDebug(s"Accepting offer: $id with attributes: $offerAttributes mem: $mem cpu: $cpus")
+          d.launchTasks(List(offer.getId), List(task.build()), filters)
         } else {
-          // Filter it out
-          d.launchTasks(
-            Collections.singleton(offer.getId), Collections.emptyList[MesosTaskInfo](), filters)
+          // Decline the offer
+          logDebug(s"Declining offer: $id with attributes: $offerAttributes mem: $mem cpu: $cpus")
+          d.declineOffer(offer.getId)
         }
       }
     }
   }
 
-  /** Build a Mesos resource protobuf object */
-  private def createResource(resourceName: String, quantity: Double): Protos.Resource = {
-    Resource.newBuilder()
-      .setName(resourceName)
-      .setType(Value.Type.SCALAR)
-      .setScalar(Value.Scalar.newBuilder().setValue(quantity).build())
-      .build()
-  }
 
   override def statusUpdate(d: SchedulerDriver, status: TaskStatus) {
     val taskId = status.getTaskId.getValue.toInt

core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosClusterScheduler.scala

@@ -29,6 +29,7 @@ import org.apache.mesos.Protos.Environment.Variable
 import org.apache.mesos.Protos.TaskStatus.Reason
 import org.apache.mesos.Protos.{TaskState => MesosTaskState, _}
 import org.apache.mesos.{Scheduler, SchedulerDriver}
+
 import org.apache.spark.deploy.mesos.MesosDriverDescription
 import org.apache.spark.deploy.rest.{CreateSubmissionResponse, KillSubmissionResponse, SubmissionStatusResponse}
 import org.apache.spark.metrics.MetricsSystem