diff --git a/core/src/main/scala/spark/executor/Executor.scala b/core/src/main/scala/spark/executor/Executor.scala
index 8a74a8d853afd8abec3cc314c8415abdcc30a113..6bfb1320233435cf04712c0f3ba3d22fd6b6eb4b 100644
--- a/core/src/main/scala/spark/executor/Executor.scala
+++ b/core/src/main/scala/spark/executor/Executor.scala
@@ -17,18 +17,17 @@
package spark.executor
-import java.io.{File, FileOutputStream}
-import java.net.{URI, URL, URLClassLoader}
+import java.io.{File}
+import java.lang.management.ManagementFactory
+import java.nio.ByteBuffer
import java.util.concurrent._
-import org.apache.hadoop.fs.FileUtil
-
-import scala.collection.mutable.{ArrayBuffer, Map, HashMap}
+import scala.collection.JavaConversions._
+import scala.collection.mutable.HashMap
-import spark.broadcast._
import spark.scheduler._
import spark._
-import java.nio.ByteBuffer
+
/**
* The Mesos executor for Spark.
@@ -116,6 +115,9 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert
context.statusUpdate(taskId, TaskState.RUNNING, EMPTY_BYTE_BUFFER)
var attemptedTask: Option[Task[Any]] = None
var taskStart: Long = 0
+ def getTotalGCTime = ManagementFactory.getGarbageCollectorMXBeans.map(g => g.getCollectionTime).sum
+ val startGCTime = getTotalGCTime
+
try {
SparkEnv.set(env)
Accumulators.clear()
@@ -132,6 +134,7 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert
m.hostname = Utils.localHostName
m.executorDeserializeTime = (taskStart - startTime).toInt
m.executorRunTime = (taskFinish - taskStart).toInt
+ m.jvmGCTime = getTotalGCTime - startGCTime
}
//TODO I'd also like to track the time it takes to serialize the task results, but that is huge headache, b/c
// we need to serialize the task metrics first. If TaskMetrics had a custom serialized format, we could
@@ -155,7 +158,10 @@ private[spark] class Executor(executorId: String, slaveHostname: String, propert
case t: Throwable => {
val serviceTime = (System.currentTimeMillis() - taskStart).toInt
val metrics = attemptedTask.flatMap(t => t.metrics)
- metrics.foreach{m => m.executorRunTime = serviceTime}
+ metrics.foreach{m =>
+ m.executorRunTime = serviceTime
+ m.jvmGCTime = getTotalGCTime - startGCTime
+ }
val reason = ExceptionFailure(t.getClass.getName, t.toString, t.getStackTrace, metrics)
context.statusUpdate(taskId, TaskState.FAILED, ser.serialize(reason))
diff --git a/core/src/main/scala/spark/executor/TaskMetrics.scala b/core/src/main/scala/spark/executor/TaskMetrics.scala
index 315162783981f8e2d18e61f86f90c529c4923492..47b8890bee96dc1ef0a2d1fdb7c6e1418e20960f 100644
--- a/core/src/main/scala/spark/executor/TaskMetrics.scala
+++ b/core/src/main/scala/spark/executor/TaskMetrics.scala
@@ -31,13 +31,18 @@ class TaskMetrics extends Serializable {
/**
* Time the executor spends actually running the task (including fetching shuffle data)
*/
- var executorRunTime:Int = _
+ var executorRunTime: Int = _
/**
* The number of bytes this task transmitted back to the driver as the TaskResult
*/
var resultSize: Long = _
+ /**
+ * Amount of time the JVM spent in garbage collection while executing this task
+ */
+ var jvmGCTime: Long = _
+
/**
* If this task reads from shuffle output, metrics on getting shuffle data will be collected here
*/
diff --git a/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala b/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala
index f274b1a767984524df7b0fba6d92f9045c6ce312..322c32543f72067cb88bce53eac7a291fcc181f4 100644
--- a/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala
+++ b/core/src/main/scala/spark/scheduler/local/LocalScheduler.scala
@@ -18,8 +18,11 @@
package spark.scheduler.local
import java.io.File
+import java.lang.management.ManagementFactory
import java.util.concurrent.atomic.AtomicInteger
import java.nio.ByteBuffer
+
+import scala.collection.JavaConversions._
import scala.collection.mutable.ArrayBuffer
import scala.collection.mutable.HashMap
import scala.collection.mutable.HashSet
@@ -31,6 +34,7 @@ import spark.scheduler._
import spark.scheduler.cluster._
import spark.scheduler.cluster.SchedulingMode.SchedulingMode
import akka.actor._
+import management.ManagementFactory
/**
* A FIFO or Fair TaskScheduler implementation that runs tasks locally in a thread pool. Optionally
@@ -173,6 +177,9 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc:
var attemptedTask: Option[Task[_]] = None
val start = System.currentTimeMillis()
var taskStart: Long = 0
+ def getTotalGCTime = ManagementFactory.getGarbageCollectorMXBeans.map(g => g.getCollectionTime).sum
+ val startGCTime = getTotalGCTime
+
try {
Accumulators.clear()
Thread.currentThread().setContextClassLoader(classLoader)
@@ -202,6 +209,7 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc:
val serviceTime = System.currentTimeMillis() - taskStart
logInfo("Finished " + taskId)
deserializedTask.metrics.get.executorRunTime = serviceTime.toInt
+ deserializedTask.metrics.get.jvmGCTime = getTotalGCTime - startGCTime
deserializedTask.metrics.get.executorDeserializeTime = deserTime.toInt
val taskResult = new TaskResult(result, accumUpdates, deserializedTask.metrics.getOrElse(null))
val serializedResult = ser.serialize(taskResult)
@@ -210,7 +218,10 @@ private[spark] class LocalScheduler(threads: Int, val maxFailures: Int, val sc:
case t: Throwable => {
val serviceTime = System.currentTimeMillis() - taskStart
val metrics = attemptedTask.flatMap(t => t.metrics)
- metrics.foreach{m => m.executorRunTime = serviceTime.toInt}
+ metrics.foreach{ m =>
+ m.executorRunTime = serviceTime.toInt
+ m.jvmGCTime = getTotalGCTime - startGCTime
+ }
val failure = new ExceptionFailure(t.getClass.getName, t.toString, t.getStackTrace, metrics)
localActor ! LocalStatusUpdate(taskId, TaskState.FAILED, ser.serialize(failure))
}
diff --git a/core/src/main/scala/spark/ui/jobs/StagePage.scala b/core/src/main/scala/spark/ui/jobs/StagePage.scala
index 884c065deecac9959dcb88704a866968e099e436..ce01f6c17ee3bc78ccb0ae62352ee82d931d7ac8 100644
--- a/core/src/main/scala/spark/ui/jobs/StagePage.scala
+++ b/core/src/main/scala/spark/ui/jobs/StagePage.scala
@@ -85,6 +85,7 @@ private[spark] class StagePage(parent: JobProgressUI) {
Seq("Task ID", "Status", "Duration", "Locality Level", "Worker", "Launch Time") ++
{if (hasShuffleRead) Seq("Shuffle Read") else Nil} ++
{if (hasShuffleWrite) Seq("Shuffle Write") else Nil} ++
+ Seq("GC Time") ++
Seq("Details")
val taskTable = listingTable(taskHeaders, taskRow(hasShuffleRead, hasShuffleWrite), tasks)
@@ -145,6 +146,7 @@ private[spark] class StagePage(parent: JobProgressUI) {
else metrics.map(m => m.executorRunTime).getOrElse(1)
val formatDuration = if (info.status == "RUNNING") parent.formatDuration(duration)
else metrics.map(m => parent.formatDuration(m.executorRunTime)).getOrElse("")
+ val gcTime = metrics.map(m => m.jvmGCTime).getOrElse(0L)
<tr>
<td>{info.taskId}</td>
@@ -163,6 +165,9 @@ private[spark] class StagePage(parent: JobProgressUI) {
<td>{metrics.flatMap{m => m.shuffleWriteMetrics}.map{s =>
Utils.memoryBytesToString(s.shuffleBytesWritten)}.getOrElse("")}</td>
}}
+ <td sortable_customkey={gcTime}>
+ {if (gcTime > 0) {parent.formatDuration(gcTime)} else ""}
+ </td>
<td>{exception.map(e =>
<span>
{e.className} ({e.description})<br/>