diff --git a/core/src/main/java/org/apache/spark/network/netty/FileServerHandler.java b/core/src/main/java/org/apache/spark/network/netty/FileServerHandler.java
index cfd8132891a11cc49ed46cbe9fbec36d022d254a..172c6e4b1cce198020a314b4f6fb3062b3dd5cff 100644
--- a/core/src/main/java/org/apache/spark/network/netty/FileServerHandler.java
+++ b/core/src/main/java/org/apache/spark/network/netty/FileServerHandler.java
@@ -25,6 +25,7 @@ import io.netty.channel.ChannelInboundMessageHandlerAdapter;
import io.netty.channel.DefaultFileRegion;
import org.apache.spark.storage.BlockId;
+import org.apache.spark.storage.FileSegment;
class FileServerHandler extends ChannelInboundMessageHandlerAdapter<String> {
@@ -37,40 +38,34 @@ class FileServerHandler extends ChannelInboundMessageHandlerAdapter<String> {
@Override
public void messageReceived(ChannelHandlerContext ctx, String blockIdString) {
BlockId blockId = BlockId.apply(blockIdString);
- String path = pResolver.getAbsolutePath(blockId.name());
- // if getFilePath returns null, close the channel
- if (path == null) {
+ FileSegment fileSegment = pResolver.getBlockLocation(blockId);
+ // if getBlockLocation returns null, close the channel
+ if (fileSegment == null) {
//ctx.close();
return;
}
- File file = new File(path);
+ File file = fileSegment.file();
if (file.exists()) {
if (!file.isFile()) {
- //logger.info("Not a file : " + file.getAbsolutePath());
ctx.write(new FileHeader(0, blockId).buffer());
ctx.flush();
return;
}
- long length = file.length();
+ long length = fileSegment.length();
if (length > Integer.MAX_VALUE || length <= 0) {
- //logger.info("too large file : " + file.getAbsolutePath() + " of size "+ length);
ctx.write(new FileHeader(0, blockId).buffer());
ctx.flush();
return;
}
int len = new Long(length).intValue();
- //logger.info("Sending block "+blockId+" filelen = "+len);
- //logger.info("header = "+ (new FileHeader(len, blockId)).buffer());
ctx.write((new FileHeader(len, blockId)).buffer());
try {
ctx.sendFile(new DefaultFileRegion(new FileInputStream(file)
- .getChannel(), 0, file.length()));
+ .getChannel(), fileSegment.offset(), fileSegment.length()));
} catch (Exception e) {
- //logger.warning("Exception when sending file : " + file.getAbsolutePath());
e.printStackTrace();
}
} else {
- //logger.warning("File not found: " + file.getAbsolutePath());
ctx.write(new FileHeader(0, blockId).buffer());
}
ctx.flush();
diff --git a/core/src/main/java/org/apache/spark/network/netty/PathResolver.java b/core/src/main/java/org/apache/spark/network/netty/PathResolver.java
index 94c034cad0119397bc6332dde066fa2be2ab75a8..9f7ced44cf93da741b20d75e1b7f2f454272f8b4 100755
--- a/core/src/main/java/org/apache/spark/network/netty/PathResolver.java
+++ b/core/src/main/java/org/apache/spark/network/netty/PathResolver.java
@@ -17,13 +17,10 @@
package org.apache.spark.network.netty;
+import org.apache.spark.storage.BlockId;
+import org.apache.spark.storage.FileSegment;
public interface PathResolver {
- /**
- * Get the absolute path of the file
- *
- * @param fileId
- * @return the absolute path of file
- */
- public String getAbsolutePath(String fileId);
+ /** Get the file segment in which the given block resides. */
+ public FileSegment getBlockLocation(BlockId blockId);
}
diff --git a/core/src/main/scala/org/apache/hadoop/mapred/SparkHadoopMapRedUtil.scala b/core/src/main/scala/org/apache/hadoop/mapred/SparkHadoopMapRedUtil.scala
index f87460039b0217855b0b4e262976078e8cb8d71f..0c47afae54c8b6e81af33a5690f1f8f1a7b3f10b 100644
--- a/core/src/main/scala/org/apache/hadoop/mapred/SparkHadoopMapRedUtil.scala
+++ b/core/src/main/scala/org/apache/hadoop/mapred/SparkHadoopMapRedUtil.scala
@@ -17,20 +17,29 @@
package org.apache.hadoop.mapred
+private[apache]
trait SparkHadoopMapRedUtil {
def newJobContext(conf: JobConf, jobId: JobID): JobContext = {
- val klass = firstAvailableClass("org.apache.hadoop.mapred.JobContextImpl", "org.apache.hadoop.mapred.JobContext");
- val ctor = klass.getDeclaredConstructor(classOf[JobConf], classOf[org.apache.hadoop.mapreduce.JobID])
+ val klass = firstAvailableClass("org.apache.hadoop.mapred.JobContextImpl",
+ "org.apache.hadoop.mapred.JobContext")
+ val ctor = klass.getDeclaredConstructor(classOf[JobConf],
+ classOf[org.apache.hadoop.mapreduce.JobID])
ctor.newInstance(conf, jobId).asInstanceOf[JobContext]
}
def newTaskAttemptContext(conf: JobConf, attemptId: TaskAttemptID): TaskAttemptContext = {
- val klass = firstAvailableClass("org.apache.hadoop.mapred.TaskAttemptContextImpl", "org.apache.hadoop.mapred.TaskAttemptContext")
+ val klass = firstAvailableClass("org.apache.hadoop.mapred.TaskAttemptContextImpl",
+ "org.apache.hadoop.mapred.TaskAttemptContext")
val ctor = klass.getDeclaredConstructor(classOf[JobConf], classOf[TaskAttemptID])
ctor.newInstance(conf, attemptId).asInstanceOf[TaskAttemptContext]
}
- def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = {
+ def newTaskAttemptID(
+ jtIdentifier: String,
+ jobId: Int,
+ isMap: Boolean,
+ taskId: Int,
+ attemptId: Int) = {
new TaskAttemptID(jtIdentifier, jobId, isMap, taskId, attemptId)
}
diff --git a/core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala b/core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala
index 93180307fa3a5c4293485cb93e1301fb7e1bdfa1..32429f01acab81e9d4dcdb9fd7289240d9ef44b0 100644
--- a/core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala
+++ b/core/src/main/scala/org/apache/hadoop/mapreduce/SparkHadoopMapReduceUtil.scala
@@ -17,9 +17,10 @@
package org.apache.hadoop.mapreduce
-import org.apache.hadoop.conf.Configuration
import java.lang.{Integer => JInteger, Boolean => JBoolean}
+import org.apache.hadoop.conf.Configuration
+private[apache]
trait SparkHadoopMapReduceUtil {
def newJobContext(conf: Configuration, jobId: JobID): JobContext = {
val klass = firstAvailableClass(
@@ -37,23 +38,31 @@ trait SparkHadoopMapReduceUtil {
ctor.newInstance(conf, attemptId).asInstanceOf[TaskAttemptContext]
}
- def newTaskAttemptID(jtIdentifier: String, jobId: Int, isMap: Boolean, taskId: Int, attemptId: Int) = {
- val klass = Class.forName("org.apache.hadoop.mapreduce.TaskAttemptID");
+ def newTaskAttemptID(
+ jtIdentifier: String,
+ jobId: Int,
+ isMap: Boolean,
+ taskId: Int,
+ attemptId: Int) = {
+ val klass = Class.forName("org.apache.hadoop.mapreduce.TaskAttemptID")
try {
- // first, attempt to use the old-style constructor that takes a boolean isMap (not available in YARN)
+ // First, attempt to use the old-style constructor that takes a boolean isMap
+ // (not available in YARN)
val ctor = klass.getDeclaredConstructor(classOf[String], classOf[Int], classOf[Boolean],
- classOf[Int], classOf[Int])
- ctor.newInstance(jtIdentifier, new JInteger(jobId), new JBoolean(isMap), new JInteger(taskId), new
- JInteger(attemptId)).asInstanceOf[TaskAttemptID]
+ classOf[Int], classOf[Int])
+ ctor.newInstance(jtIdentifier, new JInteger(jobId), new JBoolean(isMap), new JInteger(taskId),
+ new JInteger(attemptId)).asInstanceOf[TaskAttemptID]
} catch {
case exc: NoSuchMethodException => {
- // failed, look for the new ctor that takes a TaskType (not available in 1.x)
- val taskTypeClass = Class.forName("org.apache.hadoop.mapreduce.TaskType").asInstanceOf[Class[Enum[_]]]
- val taskType = taskTypeClass.getMethod("valueOf", classOf[String]).invoke(taskTypeClass, if(isMap) "MAP" else "REDUCE")
+ // If that failed, look for the new constructor that takes a TaskType (not available in 1.x)
+ val taskTypeClass = Class.forName("org.apache.hadoop.mapreduce.TaskType")
+ .asInstanceOf[Class[Enum[_]]]
+ val taskType = taskTypeClass.getMethod("valueOf", classOf[String]).invoke(
+ taskTypeClass, if(isMap) "MAP" else "REDUCE")
val ctor = klass.getDeclaredConstructor(classOf[String], classOf[Int], taskTypeClass,
classOf[Int], classOf[Int])
- ctor.newInstance(jtIdentifier, new JInteger(jobId), taskType, new JInteger(taskId), new
- JInteger(attemptId)).asInstanceOf[TaskAttemptID]
+ ctor.newInstance(jtIdentifier, new JInteger(jobId), taskType, new JInteger(taskId),
+ new JInteger(attemptId)).asInstanceOf[TaskAttemptID]
}
}
}
diff --git a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala
index 1e3f1ebfafaafcc1f35f4179da6aae5b3445590f..5e465fa22c1ac05486c1e7097029307e5fdeac36 100644
--- a/core/src/main/scala/org/apache/spark/MapOutputTracker.scala
+++ b/core/src/main/scala/org/apache/spark/MapOutputTracker.scala
@@ -20,13 +20,11 @@ package org.apache.spark
import java.io._
import java.util.zip.{GZIPInputStream, GZIPOutputStream}
-import scala.collection.mutable.HashMap
import scala.collection.mutable.HashSet
import akka.actor._
import akka.dispatch._
import akka.pattern.ask
-import akka.remote._
import akka.util.Duration
@@ -40,11 +38,12 @@ private[spark] case class GetMapOutputStatuses(shuffleId: Int, requester: String
extends MapOutputTrackerMessage
private[spark] case object StopMapOutputTracker extends MapOutputTrackerMessage
-private[spark] class MapOutputTrackerActor(tracker: MapOutputTracker) extends Actor with Logging {
+private[spark] class MapOutputTrackerMasterActor(tracker: MapOutputTrackerMaster)
+ extends Actor with Logging {
def receive = {
case GetMapOutputStatuses(shuffleId: Int, requester: String) =>
logInfo("Asked to send map output locations for shuffle " + shuffleId + " to " + requester)
- sender ! tracker.getSerializedLocations(shuffleId)
+ sender ! tracker.getSerializedMapOutputStatuses(shuffleId)
case StopMapOutputTracker =>
logInfo("MapOutputTrackerActor stopped!")
@@ -60,22 +59,19 @@ private[spark] class MapOutputTracker extends Logging {
// Set to the MapOutputTrackerActor living on the driver
var trackerActor: ActorRef = _
- private var mapStatuses = new TimeStampedHashMap[Int, Array[MapStatus]]
+ protected val mapStatuses = new TimeStampedHashMap[Int, Array[MapStatus]]
// Incremented every time a fetch fails so that client nodes know to clear
// their cache of map output locations if this happens.
- private var epoch: Long = 0
- private val epochLock = new java.lang.Object
+ protected var epoch: Long = 0
+ protected val epochLock = new java.lang.Object
- // Cache a serialized version of the output statuses for each shuffle to send them out faster
- var cacheEpoch = epoch
- private val cachedSerializedStatuses = new TimeStampedHashMap[Int, Array[Byte]]
-
- val metadataCleaner = new MetadataCleaner(MetadataCleanerType.MAP_OUTPUT_TRACKER, this.cleanup)
+ private val metadataCleaner =
+ new MetadataCleaner(MetadataCleanerType.MAP_OUTPUT_TRACKER, this.cleanup)
// Send a message to the trackerActor and get its result within a default timeout, or
// throw a SparkException if this fails.
- def askTracker(message: Any): Any = {
+ private def askTracker(message: Any): Any = {
try {
val future = trackerActor.ask(message)(timeout)
return Await.result(future, timeout)
@@ -86,50 +82,12 @@ private[spark] class MapOutputTracker extends Logging {
}
// Send a one-way message to the trackerActor, to which we expect it to reply with true.
- def communicate(message: Any) {
+ private def communicate(message: Any) {
if (askTracker(message) != true) {
throw new SparkException("Error reply received from MapOutputTracker")
}
}
- def registerShuffle(shuffleId: Int, numMaps: Int) {
- if (mapStatuses.putIfAbsent(shuffleId, new Array[MapStatus](numMaps)).isDefined) {
- throw new IllegalArgumentException("Shuffle ID " + shuffleId + " registered twice")
- }
- }
-
- def registerMapOutput(shuffleId: Int, mapId: Int, status: MapStatus) {
- var array = mapStatuses(shuffleId)
- array.synchronized {
- array(mapId) = status
- }
- }
-
- def registerMapOutputs(
- shuffleId: Int,
- statuses: Array[MapStatus],
- changeEpoch: Boolean = false) {
- mapStatuses.put(shuffleId, Array[MapStatus]() ++ statuses)
- if (changeEpoch) {
- incrementEpoch()
- }
- }
-
- def unregisterMapOutput(shuffleId: Int, mapId: Int, bmAddress: BlockManagerId) {
- var arrayOpt = mapStatuses.get(shuffleId)
- if (arrayOpt.isDefined && arrayOpt.get != null) {
- var array = arrayOpt.get
- array.synchronized {
- if (array(mapId) != null && array(mapId).location == bmAddress) {
- array(mapId) = null
- }
- }
- incrementEpoch()
- } else {
- throw new SparkException("unregisterMapOutput called for nonexistent shuffle ID")
- }
- }
-
// Remembers which map output locations are currently being fetched on a worker
private val fetching = new HashSet[Int]
@@ -168,7 +126,7 @@ private[spark] class MapOutputTracker extends Logging {
try {
val fetchedBytes =
askTracker(GetMapOutputStatuses(shuffleId, hostPort)).asInstanceOf[Array[Byte]]
- fetchedStatuses = deserializeStatuses(fetchedBytes)
+ fetchedStatuses = MapOutputTracker.deserializeMapStatuses(fetchedBytes)
logInfo("Got the output locations")
mapStatuses.put(shuffleId, fetchedStatuses)
} finally {
@@ -194,9 +152,8 @@ private[spark] class MapOutputTracker extends Logging {
}
}
- private def cleanup(cleanupTime: Long) {
+ protected def cleanup(cleanupTime: Long) {
mapStatuses.clearOldValues(cleanupTime)
- cachedSerializedStatuses.clearOldValues(cleanupTime)
}
def stop() {
@@ -206,15 +163,7 @@ private[spark] class MapOutputTracker extends Logging {
trackerActor = null
}
- // Called on master to increment the epoch number
- def incrementEpoch() {
- epochLock.synchronized {
- epoch += 1
- logDebug("Increasing epoch to " + epoch)
- }
- }
-
- // Called on master or workers to get current epoch number
+ // Called to get current epoch number
def getEpoch: Long = {
epochLock.synchronized {
return epoch
@@ -228,14 +177,62 @@ private[spark] class MapOutputTracker extends Logging {
epochLock.synchronized {
if (newEpoch > epoch) {
logInfo("Updating epoch to " + newEpoch + " and clearing cache")
- // mapStatuses = new TimeStampedHashMap[Int, Array[MapStatus]]
- mapStatuses.clear()
epoch = newEpoch
+ mapStatuses.clear()
+ }
+ }
+ }
+}
+
+private[spark] class MapOutputTrackerMaster extends MapOutputTracker {
+
+ // Cache a serialized version of the output statuses for each shuffle to send them out faster
+ private var cacheEpoch = epoch
+ private val cachedSerializedStatuses = new TimeStampedHashMap[Int, Array[Byte]]
+
+ def registerShuffle(shuffleId: Int, numMaps: Int) {
+ if (mapStatuses.putIfAbsent(shuffleId, new Array[MapStatus](numMaps)).isDefined) {
+ throw new IllegalArgumentException("Shuffle ID " + shuffleId + " registered twice")
+ }
+ }
+
+ def registerMapOutput(shuffleId: Int, mapId: Int, status: MapStatus) {
+ val array = mapStatuses(shuffleId)
+ array.synchronized {
+ array(mapId) = status
+ }
+ }
+
+ def registerMapOutputs(shuffleId: Int, statuses: Array[MapStatus], changeEpoch: Boolean = false) {
+ mapStatuses.put(shuffleId, Array[MapStatus]() ++ statuses)
+ if (changeEpoch) {
+ incrementEpoch()
+ }
+ }
+
+ def unregisterMapOutput(shuffleId: Int, mapId: Int, bmAddress: BlockManagerId) {
+ val arrayOpt = mapStatuses.get(shuffleId)
+ if (arrayOpt.isDefined && arrayOpt.get != null) {
+ val array = arrayOpt.get
+ array.synchronized {
+ if (array(mapId) != null && array(mapId).location == bmAddress) {
+ array(mapId) = null
+ }
}
+ incrementEpoch()
+ } else {
+ throw new SparkException("unregisterMapOutput called for nonexistent shuffle ID")
}
}
- def getSerializedLocations(shuffleId: Int): Array[Byte] = {
+ def incrementEpoch() {
+ epochLock.synchronized {
+ epoch += 1
+ logDebug("Increasing epoch to " + epoch)
+ }
+ }
+
+ def getSerializedMapOutputStatuses(shuffleId: Int): Array[Byte] = {
var statuses: Array[MapStatus] = null
var epochGotten: Long = -1
epochLock.synchronized {
@@ -253,7 +250,7 @@ private[spark] class MapOutputTracker extends Logging {
}
// If we got here, we failed to find the serialized locations in the cache, so we pulled
// out a snapshot of the locations as "locs"; let's serialize and return that
- val bytes = serializeStatuses(statuses)
+ val bytes = MapOutputTracker.serializeMapStatuses(statuses)
logInfo("Size of output statuses for shuffle %d is %d bytes".format(shuffleId, bytes.length))
// Add them into the table only if the epoch hasn't changed while we were working
epochLock.synchronized {
@@ -261,13 +258,31 @@ private[spark] class MapOutputTracker extends Logging {
cachedSerializedStatuses(shuffleId) = bytes
}
}
- return bytes
+ bytes
+ }
+
+ protected override def cleanup(cleanupTime: Long) {
+ super.cleanup(cleanupTime)
+ cachedSerializedStatuses.clearOldValues(cleanupTime)
}
+ override def stop() {
+ super.stop()
+ cachedSerializedStatuses.clear()
+ }
+
+ override def updateEpoch(newEpoch: Long) {
+ // This might be called on the MapOutputTrackerMaster if we're running in local mode.
+ }
+}
+
+private[spark] object MapOutputTracker {
+ private val LOG_BASE = 1.1
+
// Serialize an array of map output locations into an efficient byte format so that we can send
// it to reduce tasks. We do this by compressing the serialized bytes using GZIP. They will
// generally be pretty compressible because many map outputs will be on the same hostname.
- private def serializeStatuses(statuses: Array[MapStatus]): Array[Byte] = {
+ def serializeMapStatuses(statuses: Array[MapStatus]): Array[Byte] = {
val out = new ByteArrayOutputStream
val objOut = new ObjectOutputStream(new GZIPOutputStream(out))
// Since statuses can be modified in parallel, sync on it
@@ -278,18 +293,11 @@ private[spark] class MapOutputTracker extends Logging {
out.toByteArray
}
- // Opposite of serializeStatuses.
- def deserializeStatuses(bytes: Array[Byte]): Array[MapStatus] = {
+ // Opposite of serializeMapStatuses.
+ def deserializeMapStatuses(bytes: Array[Byte]): Array[MapStatus] = {
val objIn = new ObjectInputStream(new GZIPInputStream(new ByteArrayInputStream(bytes)))
- objIn.readObject().
- // // drop all null's from status - not sure why they are occuring though. Causes NPE downstream in slave if present
- // comment this out - nulls could be due to missing location ?
- asInstanceOf[Array[MapStatus]] // .filter( _ != null )
+ objIn.readObject().asInstanceOf[Array[MapStatus]]
}
-}
-
-private[spark] object MapOutputTracker {
- private val LOG_BASE = 1.1
// Convert an array of MapStatuses to locations and sizes for a given reduce ID. If
// any of the statuses is null (indicating a missing location due to a failed mapper),
diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala
index ebd2f461739b7921935fd214672325d340d9f651..564466cfd519e35b0931550a050e65c5b947191e 100644
--- a/core/src/main/scala/org/apache/spark/SparkContext.scala
+++ b/core/src/main/scala/org/apache/spark/SparkContext.scala
@@ -156,8 +156,8 @@ class SparkContext(
val LOCAL_CLUSTER_REGEX = """local-cluster\[\s*([0-9]+)\s*,\s*([0-9]+)\s*,\s*([0-9]+)\s*]""".r
// Regular expression for connecting to Spark deploy clusters
val SPARK_REGEX = """spark://(.*)""".r
- //Regular expression for connection to Mesos cluster
- val MESOS_REGEX = """(mesos://.*)""".r
+ // Regular expression for connection to Mesos cluster
+ val MESOS_REGEX = """mesos://(.*)""".r
master match {
case "local" =>
diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala
index 29968c273c31d59e5b45e1b8237f860c9eb21bdf..aaab717bcf1eeee98a441b517e7cc2a9c34d0d7b 100644
--- a/core/src/main/scala/org/apache/spark/SparkEnv.scala
+++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala
@@ -187,10 +187,14 @@ object SparkEnv extends Logging {
// Have to assign trackerActor after initialization as MapOutputTrackerActor
// requires the MapOutputTracker itself
- val mapOutputTracker = new MapOutputTracker()
+ val mapOutputTracker = if (isDriver) {
+ new MapOutputTrackerMaster()
+ } else {
+ new MapOutputTracker()
+ }
mapOutputTracker.trackerActor = registerOrLookup(
"MapOutputTracker",
- new MapOutputTrackerActor(mapOutputTracker))
+ new MapOutputTrackerMasterActor(mapOutputTracker.asInstanceOf[MapOutputTrackerMaster]))
val shuffleFetcher = instantiateClass[ShuffleFetcher](
"spark.shuffle.fetcher", "org.apache.spark.BlockStoreShuffleFetcher")
diff --git a/core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala b/core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala
index afa76a4a76c412fbd2fe20b8800e6882a9ec56e7..103a1c205185f1effde97fbac116076221c298b8 100644
--- a/core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala
+++ b/core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala
@@ -17,14 +17,14 @@
package org.apache.hadoop.mapred
-import org.apache.hadoop.fs.FileSystem
-import org.apache.hadoop.fs.Path
-
+import java.io.IOException
import java.text.SimpleDateFormat
import java.text.NumberFormat
-import java.io.IOException
import java.util.Date
+import org.apache.hadoop.fs.FileSystem
+import org.apache.hadoop.fs.Path
+
import org.apache.spark.Logging
import org.apache.spark.SerializableWritable
@@ -36,6 +36,7 @@ import org.apache.spark.SerializableWritable
* Saves the RDD using a JobConf, which should contain an output key class, an output value class,
* a filename to write to, etc, exactly like in a Hadoop MapReduce job.
*/
+private[apache]
class SparkHadoopWriter(@transient jobConf: JobConf)
extends Logging
with SparkHadoopMapRedUtil
@@ -86,13 +87,11 @@ class SparkHadoopWriter(@transient jobConf: JobConf)
}
getOutputCommitter().setupTask(getTaskContext())
- writer = getOutputFormat().getRecordWriter(
- fs, conf.value, outputName, Reporter.NULL)
+ writer = getOutputFormat().getRecordWriter(fs, conf.value, outputName, Reporter.NULL)
}
def write(key: AnyRef, value: AnyRef) {
- if (writer!=null) {
- //println (">>> Writing ("+key.toString+": " + key.getClass.toString + ", " + value.toString + ": " + value.getClass.toString + ")")
+ if (writer != null) {
writer.write(key, value)
} else {
throw new IOException("Writer is null, open() has not been called")
@@ -182,6 +181,7 @@ class SparkHadoopWriter(@transient jobConf: JobConf)
}
}
+private[apache]
object SparkHadoopWriter {
def createJobID(time: Date, id: Int): JobID = {
val formatter = new SimpleDateFormat("yyyyMMddHHmm")
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java
index 4830067f7a0db2a7b483c5c962483a876b0788ff..3e85052cd03e8323f208bed5d37c86979ca75a96 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java
+++ b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFlatMapFunction.java
@@ -18,8 +18,6 @@
package org.apache.spark.api.java.function;
-import scala.runtime.AbstractFunction1;
-
import java.io.Serializable;
/**
@@ -27,11 +25,7 @@ import java.io.Serializable;
*/
// DoubleFlatMapFunction does not extend FlatMapFunction because flatMap is
// overloaded for both FlatMapFunction and DoubleFlatMapFunction.
-public abstract class DoubleFlatMapFunction<T> extends AbstractFunction1<T, Iterable<Double>>
+public abstract class DoubleFlatMapFunction<T> extends WrappedFunction1<T, Iterable<Double>>
implements Serializable {
-
- public abstract Iterable<Double> call(T t);
-
- @Override
- public final Iterable<Double> apply(T t) { return call(t); }
+ // Intentionally left blank
}
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java
index db34cd190ad3a583c73b0a1825f4118970855d03..5e9b8c48b89aa575d1800159dc5d5208500983cc 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java
+++ b/core/src/main/scala/org/apache/spark/api/java/function/DoubleFunction.java
@@ -18,8 +18,6 @@
package org.apache.spark.api.java.function;
-import scala.runtime.AbstractFunction1;
-
import java.io.Serializable;
/**
@@ -29,6 +27,5 @@ import java.io.Serializable;
// are overloaded for both Function and DoubleFunction.
public abstract class DoubleFunction<T> extends WrappedFunction1<T, Double>
implements Serializable {
-
- public abstract Double call(T t) throws Exception;
+ // Intentionally left blank
}
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction.scala b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction.scala
index 158539a8461f94aa85ea6440786d50d461436825..2dfda8b09a88068b2af3db5ff62ad5a589f8684d 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction.scala
+++ b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction.scala
@@ -21,8 +21,5 @@ package org.apache.spark.api.java.function
* A function that returns zero or more output records from each input record.
*/
abstract class FlatMapFunction[T, R] extends Function[T, java.lang.Iterable[R]] {
- @throws(classOf[Exception])
- def call(x: T) : java.lang.Iterable[R]
-
def elementType() : ClassManifest[R] = ClassManifest.Any.asInstanceOf[ClassManifest[R]]
}
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction2.scala b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction2.scala
index 5ef6a814f5a4f2aa347dc1f7487b7011308bcfce..528e1c0a7cd648f405d472804a6557fe15030eeb 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction2.scala
+++ b/core/src/main/scala/org/apache/spark/api/java/function/FlatMapFunction2.scala
@@ -21,8 +21,5 @@ package org.apache.spark.api.java.function
* A function that takes two inputs and returns zero or more output records.
*/
abstract class FlatMapFunction2[A, B, C] extends Function2[A, B, java.lang.Iterable[C]] {
- @throws(classOf[Exception])
- def call(a: A, b:B) : java.lang.Iterable[C]
-
def elementType() : ClassManifest[C] = ClassManifest.Any.asInstanceOf[ClassManifest[C]]
}
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/Function.java b/core/src/main/scala/org/apache/spark/api/java/function/Function.java
index b9070cfd837eb68743042ae79500ced87815eb4c..ce368ee01b295577d8e288681617215caf4997ef 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/Function.java
+++ b/core/src/main/scala/org/apache/spark/api/java/function/Function.java
@@ -19,7 +19,6 @@ package org.apache.spark.api.java.function;
import scala.reflect.ClassManifest;
import scala.reflect.ClassManifest$;
-import scala.runtime.AbstractFunction1;
import java.io.Serializable;
@@ -30,8 +29,6 @@ import java.io.Serializable;
* when mapping RDDs of other types.
*/
public abstract class Function<T, R> extends WrappedFunction1<T, R> implements Serializable {
- public abstract R call(T t) throws Exception;
-
public ClassManifest<R> returnType() {
return (ClassManifest<R>) ClassManifest$.MODULE$.fromClass(Object.class);
}
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/Function2.java b/core/src/main/scala/org/apache/spark/api/java/function/Function2.java
index d4c9154869fe9ac14a4432951ca8cb4a490b5eb2..44ad559d48474c364981212d707fe1a40dae5081 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/Function2.java
+++ b/core/src/main/scala/org/apache/spark/api/java/function/Function2.java
@@ -19,7 +19,6 @@ package org.apache.spark.api.java.function;
import scala.reflect.ClassManifest;
import scala.reflect.ClassManifest$;
-import scala.runtime.AbstractFunction2;
import java.io.Serializable;
@@ -29,8 +28,6 @@ import java.io.Serializable;
public abstract class Function2<T1, T2, R> extends WrappedFunction2<T1, T2, R>
implements Serializable {
- public abstract R call(T1 t1, T2 t2) throws Exception;
-
public ClassManifest<R> returnType() {
return (ClassManifest<R>) ClassManifest$.MODULE$.fromClass(Object.class);
}
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/PairFlatMapFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/PairFlatMapFunction.java
index c0e5544b7dff0d66576243d1e422bf4e57ee15dc..6d76a8f970f7c2e812337f26796df8c0ee5afc68 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/PairFlatMapFunction.java
+++ b/core/src/main/scala/org/apache/spark/api/java/function/PairFlatMapFunction.java
@@ -20,7 +20,6 @@ package org.apache.spark.api.java.function;
import scala.Tuple2;
import scala.reflect.ClassManifest;
import scala.reflect.ClassManifest$;
-import scala.runtime.AbstractFunction1;
import java.io.Serializable;
@@ -34,8 +33,6 @@ public abstract class PairFlatMapFunction<T, K, V>
extends WrappedFunction1<T, Iterable<Tuple2<K, V>>>
implements Serializable {
- public abstract Iterable<Tuple2<K, V>> call(T t) throws Exception;
-
public ClassManifest<K> keyType() {
return (ClassManifest<K>) ClassManifest$.MODULE$.fromClass(Object.class);
}
diff --git a/core/src/main/scala/org/apache/spark/api/java/function/PairFunction.java b/core/src/main/scala/org/apache/spark/api/java/function/PairFunction.java
index 40480fe8e816055494be1b8138a9bb487b357326..ede7ceefb5d297edfaf63ed365a0a1a3f78a4466 100644
--- a/core/src/main/scala/org/apache/spark/api/java/function/PairFunction.java
+++ b/core/src/main/scala/org/apache/spark/api/java/function/PairFunction.java
@@ -20,7 +20,6 @@ package org.apache.spark.api.java.function;
import scala.Tuple2;
import scala.reflect.ClassManifest;
import scala.reflect.ClassManifest$;
-import scala.runtime.AbstractFunction1;
import java.io.Serializable;
@@ -29,12 +28,9 @@ import java.io.Serializable;
*/
// PairFunction does not extend Function because some UDF functions, like map,
// are overloaded for both Function and PairFunction.
-public abstract class PairFunction<T, K, V>
- extends WrappedFunction1<T, Tuple2<K, V>>
+public abstract class PairFunction<T, K, V> extends WrappedFunction1<T, Tuple2<K, V>>
implements Serializable {
- public abstract Tuple2<K, V> call(T t) throws Exception;
-
public ClassManifest<K> keyType() {
return (ClassManifest<K>) ClassManifest$.MODULE$.fromClass(Object.class);
}
diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
index 1f8ad688a649dec0d14228e4db97c600d1877e7f..12b4d94a567ceec4713299fa49a54349b08c0cef 100644
--- a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
+++ b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
@@ -308,7 +308,7 @@ private class BytesToString extends org.apache.spark.api.java.function.Function[
* Internal class that acts as an `AccumulatorParam` for Python accumulators. Inside, it
* collects a list of pickled strings that we pass to Python through a socket.
*/
-class PythonAccumulatorParam(@transient serverHost: String, serverPort: Int)
+private class PythonAccumulatorParam(@transient serverHost: String, serverPort: Int)
extends AccumulatorParam[JList[Array[Byte]]] {
Utils.checkHost(serverHost, "Expected hostname")
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 993ba6bd3dbfad6faeed86d8d4f4ef39535dd00e..83cd3df5fa20e5fa2b6b96803cff19a082a38b13 100644
--- a/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
+++ b/core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
@@ -17,26 +17,31 @@
package org.apache.spark.deploy
-import com.google.common.collect.MapMaker
-
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.mapred.JobConf
+import com.google.common.collect.MapMaker
+
/**
- * Contains util methods to interact with Hadoop from spark.
+ * Contains util methods to interact with Hadoop from Spark.
*/
+private[spark]
class SparkHadoopUtil {
// A general, soft-reference map for metadata needed during HadoopRDD split computation
// (e.g., HadoopFileRDD uses this to cache JobConfs and InputFormats).
private[spark] val hadoopJobMetadata = new MapMaker().softValues().makeMap[String, Any]()
- // Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop
- // subsystems
+ /**
+ * Return an appropriate (subclass) of Configuration. Creating config can initializes some Hadoop
+ * subsystems.
+ */
def newConfiguration(): Configuration = new Configuration()
- // Add any user credentials to the job conf which are necessary for running on a secure Hadoop
- // cluster
+ /**
+ * Add any user credentials to the job conf which are necessary for running on a secure Hadoop
+ * cluster.
+ */
def addCredentials(conf: JobConf) {}
def isYarnMode(): Boolean = { false }
diff --git a/core/src/main/scala/org/apache/spark/network/netty/ShuffleSender.scala b/core/src/main/scala/org/apache/spark/network/netty/ShuffleSender.scala
index 1586dff254df2234f799a700b50333df48182f1d..546d921067175a2db075f8896e101782eb6c40c4 100644
--- a/core/src/main/scala/org/apache/spark/network/netty/ShuffleSender.scala
+++ b/core/src/main/scala/org/apache/spark/network/netty/ShuffleSender.scala
@@ -21,7 +21,7 @@ import java.io.File
import org.apache.spark.Logging
import org.apache.spark.util.Utils
-import org.apache.spark.storage.BlockId
+import org.apache.spark.storage.{BlockId, FileSegment}
private[spark] class ShuffleSender(portIn: Int, val pResolver: PathResolver) extends Logging {
@@ -54,8 +54,7 @@ private[spark] object ShuffleSender {
val localDirs = args.drop(2).map(new File(_))
val pResovler = new PathResolver {
- override def getAbsolutePath(blockIdString: String): String = {
- val blockId = BlockId(blockIdString)
+ override def getBlockLocation(blockId: BlockId): FileSegment = {
if (!blockId.isShuffle) {
throw new Exception("Block " + blockId + " is not a shuffle block")
}
@@ -65,7 +64,7 @@ private[spark] object ShuffleSender {
val subDirId = (hash / localDirs.length) % subDirsPerLocalDir
val subDir = new File(localDirs(dirId), "%02x".format(subDirId))
val file = new File(subDir, blockId.name)
- return file.getAbsolutePath
+ return new FileSegment(file, 0, file.length())
}
}
val sender = new ShuffleSender(port, pResovler)
diff --git a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
index 9478360c68a66f98c32631f71fa0621d9933b68f..4cef0825dd6c0aab711df8a58700bd37fb91c0e0 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
@@ -52,13 +52,14 @@ import org.apache.spark.util.{MetadataCleaner, MetadataCleanerType, TimeStampedH
private[spark]
class DAGScheduler(
taskSched: TaskScheduler,
- mapOutputTracker: MapOutputTracker,
+ mapOutputTracker: MapOutputTrackerMaster,
blockManagerMaster: BlockManagerMaster,
env: SparkEnv)
extends Logging {
def this(taskSched: TaskScheduler) {
- this(taskSched, SparkEnv.get.mapOutputTracker, SparkEnv.get.blockManager.master, SparkEnv.get)
+ this(taskSched, SparkEnv.get.mapOutputTracker.asInstanceOf[MapOutputTrackerMaster],
+ SparkEnv.get.blockManager.master, SparkEnv.get)
}
taskSched.setDAGScheduler(this)
@@ -187,7 +188,7 @@ class DAGScheduler(
shuffleToMapStage.get(shuffleDep.shuffleId) match {
case Some(stage) => stage
case None =>
- val stage = newStage(shuffleDep.rdd, Some(shuffleDep), jobId)
+ val stage = newStage(shuffleDep.rdd, shuffleDep.rdd.partitions.size, Some(shuffleDep), jobId)
shuffleToMapStage(shuffleDep.shuffleId) = stage
stage
}
@@ -200,6 +201,7 @@ class DAGScheduler(
*/
private def newStage(
rdd: RDD[_],
+ numTasks: Int,
shuffleDep: Option[ShuffleDependency[_,_]],
jobId: Int,
callSite: Option[String] = None)
@@ -212,9 +214,10 @@ class DAGScheduler(
mapOutputTracker.registerShuffle(shuffleDep.get.shuffleId, rdd.partitions.size)
}
val id = nextStageId.getAndIncrement()
- val stage = new Stage(id, rdd, shuffleDep, getParentStages(rdd, jobId), jobId, callSite)
+ val stage =
+ new Stage(id, rdd, numTasks, shuffleDep, getParentStages(rdd, jobId), jobId, callSite)
stageIdToStage(id) = stage
- stageToInfos(stage) = StageInfo(stage)
+ stageToInfos(stage) = new StageInfo(stage)
stage
}
@@ -366,7 +369,7 @@ class DAGScheduler(
private[scheduler] def processEvent(event: DAGSchedulerEvent): Boolean = {
event match {
case JobSubmitted(jobId, rdd, func, partitions, allowLocal, callSite, listener, properties) =>
- val finalStage = newStage(rdd, None, jobId, Some(callSite))
+ val finalStage = newStage(rdd, partitions.size, None, jobId, Some(callSite))
val job = new ActiveJob(jobId, finalStage, func, partitions, callSite, listener, properties)
clearCacheLocs()
logInfo("Got job " + job.jobId + " (" + callSite + ") with " + partitions.length +
@@ -592,7 +595,7 @@ class DAGScheduler(
// must be run listener before possible NotSerializableException
// should be "StageSubmitted" first and then "JobEnded"
- listenerBus.post(SparkListenerStageSubmitted(stage, tasks.size, properties))
+ listenerBus.post(SparkListenerStageSubmitted(stageToInfos(stage), properties))
if (tasks.size > 0) {
// Preemptively serialize a task to make sure it can be serialized. We are catching this
@@ -613,9 +616,7 @@ class DAGScheduler(
logDebug("New pending tasks: " + myPending)
taskSched.submitTasks(
new TaskSet(tasks.toArray, stage.id, stage.newAttemptId(), stage.jobId, properties))
- if (!stage.submissionTime.isDefined) {
- stage.submissionTime = Some(System.currentTimeMillis())
- }
+ stageToInfos(stage).submissionTime = Some(System.currentTimeMillis())
} else {
logDebug("Stage " + stage + " is actually done; %b %d %d".format(
stage.isAvailable, stage.numAvailableOutputs, stage.numPartitions))
@@ -637,12 +638,12 @@ class DAGScheduler(
val stage = stageIdToStage(task.stageId)
def markStageAsFinished(stage: Stage) = {
- val serviceTime = stage.submissionTime match {
+ val serviceTime = stageToInfos(stage).submissionTime match {
case Some(t) => "%.03f".format((System.currentTimeMillis() - t) / 1000.0)
- case _ => "Unkown"
+ case _ => "Unknown"
}
logInfo("%s (%s) finished in %s s".format(stage, stage.name, serviceTime))
- stage.completionTime = Some(System.currentTimeMillis)
+ stageToInfos(stage).completionTime = Some(System.currentTimeMillis())
listenerBus.post(StageCompleted(stageToInfos(stage)))
running -= stage
}
@@ -812,7 +813,7 @@ class DAGScheduler(
*/
private def abortStage(failedStage: Stage, reason: String) {
val dependentStages = resultStageToJob.keys.filter(x => stageDependsOn(x, failedStage)).toSeq
- failedStage.completionTime = Some(System.currentTimeMillis())
+ stageToInfos(failedStage).completionTime = Some(System.currentTimeMillis())
for (resultStage <- dependentStages) {
val job = resultStageToJob(resultStage)
val error = new SparkException("Job aborted: " + reason)
diff --git a/core/src/main/scala/org/apache/spark/scheduler/JobLogger.scala b/core/src/main/scala/org/apache/spark/scheduler/JobLogger.scala
index 3628b1b078de8b0f21ce95d14f2fe6bade88b0fa..12b0d74fb5346867bdafd27bb3dd877bf277b489 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/JobLogger.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/JobLogger.scala
@@ -24,56 +24,54 @@ import java.text.SimpleDateFormat
import java.util.{Date, Properties}
import java.util.concurrent.LinkedBlockingQueue
-import scala.collection.mutable.{Map, HashMap, ListBuffer}
-import scala.io.Source
+import scala.collection.mutable.{HashMap, ListBuffer}
import org.apache.spark._
import org.apache.spark.rdd.RDD
import org.apache.spark.executor.TaskMetrics
-// Used to record runtime information for each job, including RDD graph
-// tasks' start/stop shuffle information and information from outside
-
+/**
+ * A logger class to record runtime information for jobs in Spark. This class outputs one log file
+ * per Spark job with information such as RDD graph, tasks start/stop, shuffle information.
+ *
+ * @param logDirName The base directory for the log files.
+ */
class JobLogger(val logDirName: String) extends SparkListener with Logging {
- private val logDir =
- if (System.getenv("SPARK_LOG_DIR") != null)
- System.getenv("SPARK_LOG_DIR")
- else
- "/tmp/spark"
+
+ private val logDir = Option(System.getenv("SPARK_LOG_DIR")).getOrElse("/tmp/spark")
+
private val jobIDToPrintWriter = new HashMap[Int, PrintWriter]
private val stageIDToJobID = new HashMap[Int, Int]
private val jobIDToStages = new HashMap[Int, ListBuffer[Stage]]
private val DATE_FORMAT = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss")
private val eventQueue = new LinkedBlockingQueue[SparkListenerEvents]
-
+
createLogDir()
def this() = this(String.valueOf(System.currentTimeMillis()))
-
- def getLogDir = logDir
- def getJobIDtoPrintWriter = jobIDToPrintWriter
- def getStageIDToJobID = stageIDToJobID
- def getJobIDToStages = jobIDToStages
- def getEventQueue = eventQueue
-
+
+ // The following 5 functions are used only in testing.
+ private[scheduler] def getLogDir = logDir
+ private[scheduler] def getJobIDtoPrintWriter = jobIDToPrintWriter
+ private[scheduler] def getStageIDToJobID = stageIDToJobID
+ private[scheduler] def getJobIDToStages = jobIDToStages
+ private[scheduler] def getEventQueue = eventQueue
+
// Create a folder for log files, the folder's name is the creation time of the jobLogger
protected def createLogDir() {
val dir = new File(logDir + "/" + logDirName + "/")
- if (dir.exists()) {
- return
- }
- if (dir.mkdirs() == false) {
- logError("create log directory error:" + logDir + "/" + logDirName + "/")
+ if (!dir.exists() && !dir.mkdirs()) {
+ logError("Error creating log directory: " + logDir + "/" + logDirName + "/")
}
}
// Create a log file for one job, the file name is the jobID
protected def createLogWriter(jobID: Int) {
- try{
+ try {
val fileWriter = new PrintWriter(logDir + "/" + logDirName + "/" + jobID)
jobIDToPrintWriter += (jobID -> fileWriter)
- } catch {
- case e: FileNotFoundException => e.printStackTrace()
- }
+ } catch {
+ case e: FileNotFoundException => e.printStackTrace()
+ }
}
// Close log file, and clean the stage relationship in stageIDToJobID
@@ -118,10 +116,9 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging {
def getRddsInStage(rdd: RDD[_]): ListBuffer[RDD[_]] = {
var rddList = new ListBuffer[RDD[_]]
rddList += rdd
- rdd.dependencies.foreach{ dep => dep match {
- case shufDep: ShuffleDependency[_,_] =>
- case _ => rddList ++= getRddsInStage(dep.rdd)
- }
+ rdd.dependencies.foreach {
+ case shufDep: ShuffleDependency[_, _] =>
+ case dep: Dependency[_] => rddList ++= getRddsInStage(dep.rdd)
}
rddList
}
@@ -161,29 +158,27 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging {
protected def recordRddInStageGraph(jobID: Int, rdd: RDD[_], indent: Int) {
val rddInfo = "RDD_ID=" + rdd.id + "(" + getRddName(rdd) + "," + rdd.generator + ")"
jobLogInfo(jobID, indentString(indent) + rddInfo, false)
- rdd.dependencies.foreach{ dep => dep match {
- case shufDep: ShuffleDependency[_,_] =>
- val depInfo = "SHUFFLE_ID=" + shufDep.shuffleId
- jobLogInfo(jobID, indentString(indent + 1) + depInfo, false)
- case _ => recordRddInStageGraph(jobID, dep.rdd, indent + 1)
- }
+ rdd.dependencies.foreach {
+ case shufDep: ShuffleDependency[_, _] =>
+ val depInfo = "SHUFFLE_ID=" + shufDep.shuffleId
+ jobLogInfo(jobID, indentString(indent + 1) + depInfo, false)
+ case dep: Dependency[_] => recordRddInStageGraph(jobID, dep.rdd, indent + 1)
}
}
protected def recordStageDepGraph(jobID: Int, stage: Stage, indent: Int = 0) {
- var stageInfo: String = ""
- if (stage.isShuffleMap) {
- stageInfo = "STAGE_ID=" + stage.id + " MAP_STAGE SHUFFLE_ID=" +
- stage.shuffleDep.get.shuffleId
- }else{
- stageInfo = "STAGE_ID=" + stage.id + " RESULT_STAGE"
+ val stageInfo = if (stage.isShuffleMap) {
+ "STAGE_ID=" + stage.id + " MAP_STAGE SHUFFLE_ID=" + stage.shuffleDep.get.shuffleId
+ } else {
+ "STAGE_ID=" + stage.id + " RESULT_STAGE"
}
if (stage.jobId == jobID) {
jobLogInfo(jobID, indentString(indent) + stageInfo, false)
recordRddInStageGraph(jobID, stage.rdd, indent)
stage.parents.foreach(recordStageDepGraph(jobID, _, indent + 2))
- } else
+ } else {
jobLogInfo(jobID, indentString(indent) + stageInfo + " JOB_ID=" + stage.jobId, false)
+ }
}
// Record task metrics into job log files
@@ -193,39 +188,32 @@ class JobLogger(val logDirName: String) extends SparkListener with Logging {
" START_TIME=" + taskInfo.launchTime + " FINISH_TIME=" + taskInfo.finishTime +
" EXECUTOR_ID=" + taskInfo.executorId + " HOST=" + taskMetrics.hostname
val executorRunTime = " EXECUTOR_RUN_TIME=" + taskMetrics.executorRunTime
- val readMetrics =
- taskMetrics.shuffleReadMetrics match {
- case Some(metrics) =>
- " SHUFFLE_FINISH_TIME=" + metrics.shuffleFinishTime +
- " BLOCK_FETCHED_TOTAL=" + metrics.totalBlocksFetched +
- " BLOCK_FETCHED_LOCAL=" + metrics.localBlocksFetched +
- " BLOCK_FETCHED_REMOTE=" + metrics.remoteBlocksFetched +
- " REMOTE_FETCH_WAIT_TIME=" + metrics.fetchWaitTime +
- " REMOTE_FETCH_TIME=" + metrics.remoteFetchTime +
- " REMOTE_BYTES_READ=" + metrics.remoteBytesRead
- case None => ""
- }
- val writeMetrics =
- taskMetrics.shuffleWriteMetrics match {
- case Some(metrics) =>
- " SHUFFLE_BYTES_WRITTEN=" + metrics.shuffleBytesWritten
- case None => ""
- }
+ val readMetrics = taskMetrics.shuffleReadMetrics match {
+ case Some(metrics) =>
+ " SHUFFLE_FINISH_TIME=" + metrics.shuffleFinishTime +
+ " BLOCK_FETCHED_TOTAL=" + metrics.totalBlocksFetched +
+ " BLOCK_FETCHED_LOCAL=" + metrics.localBlocksFetched +
+ " BLOCK_FETCHED_REMOTE=" + metrics.remoteBlocksFetched +
+ " REMOTE_FETCH_WAIT_TIME=" + metrics.fetchWaitTime +
+ " REMOTE_FETCH_TIME=" + metrics.remoteFetchTime +
+ " REMOTE_BYTES_READ=" + metrics.remoteBytesRead
+ case None => ""
+ }
+ val writeMetrics = taskMetrics.shuffleWriteMetrics match {
+ case Some(metrics) => " SHUFFLE_BYTES_WRITTEN=" + metrics.shuffleBytesWritten
+ case None => ""
+ }
stageLogInfo(stageID, status + info + executorRunTime + readMetrics + writeMetrics)
}
override def onStageSubmitted(stageSubmitted: SparkListenerStageSubmitted) {
- stageLogInfo(
- stageSubmitted.stage.id,
- "STAGE_ID=%d STATUS=SUBMITTED TASK_SIZE=%d".format(
- stageSubmitted.stage.id, stageSubmitted.taskSize))
+ stageLogInfo(stageSubmitted.stage.stageId,"STAGE_ID=%d STATUS=SUBMITTED TASK_SIZE=%d".format(
+ stageSubmitted.stage.stageId, stageSubmitted.stage.numTasks))
}
override def onStageCompleted(stageCompleted: StageCompleted) {
- stageLogInfo(
- stageCompleted.stageInfo.stage.id,
- "STAGE_ID=%d STATUS=COMPLETED".format(stageCompleted.stageInfo.stage.id))
-
+ stageLogInfo(stageCompleted.stage.stageId, "STAGE_ID=%d STATUS=COMPLETED".format(
+ stageCompleted.stage.stageId))
}
override def onTaskStart(taskStart: SparkListenerTaskStart) { }
diff --git a/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala
index 40baea69e8c44592a2b97e20ae57041d9e42c3ef..24d97da6eb6e0fdef25c0b78f5d6c427fc28cb76 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/ShuffleMapTask.scala
@@ -167,8 +167,7 @@ private[spark] class ShuffleMapTask(
var totalTime = 0L
val compressedSizes: Array[Byte] = buckets.writers.map { writer: BlockObjectWriter =>
writer.commit()
- writer.close()
- val size = writer.size()
+ val size = writer.fileSegment().length
totalBytes += size
totalTime += writer.timeWriting()
MapOutputTracker.compressSize(size)
@@ -191,6 +190,7 @@ private[spark] class ShuffleMapTask(
} finally {
// Release the writers back to the shuffle block manager.
if (shuffle != null && buckets != null) {
+ buckets.writers.foreach(_.close())
shuffle.releaseWriters(buckets)
}
// Execute the callbacks on task completion.
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 de24c022f1c7b395e5b39267464999de25a68d73..a35081f7b10d7040d8b45302ce50941cef3e7960 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala
@@ -24,10 +24,10 @@ import org.apache.spark.executor.TaskMetrics
sealed trait SparkListenerEvents
-case class SparkListenerStageSubmitted(stage: Stage, taskSize: Int, properties: Properties)
+case class SparkListenerStageSubmitted(stage: StageInfo, properties: Properties)
extends SparkListenerEvents
-case class StageCompleted(val stageInfo: StageInfo) extends SparkListenerEvents
+case class StageCompleted(val stage: StageInfo) extends SparkListenerEvents
case class SparkListenerTaskStart(task: Task[_], taskInfo: TaskInfo) extends SparkListenerEvents
@@ -89,7 +89,7 @@ class StatsReportListener extends SparkListener with Logging {
override def onStageCompleted(stageCompleted: StageCompleted) {
import org.apache.spark.scheduler.StatsReportListener._
implicit val sc = stageCompleted
- this.logInfo("Finished stage: " + stageCompleted.stageInfo)
+ this.logInfo("Finished stage: " + stageCompleted.stage)
showMillisDistribution("task runtime:", (info, _) => Some(info.duration))
//shuffle write
@@ -102,7 +102,7 @@ class StatsReportListener extends SparkListener with Logging {
//runtime breakdown
- val runtimePcts = stageCompleted.stageInfo.taskInfos.map{
+ val runtimePcts = stageCompleted.stage.taskInfos.map{
case (info, metrics) => RuntimePercentage(info.duration, metrics)
}
showDistribution("executor (non-fetch) time pct: ", Distribution(runtimePcts.map{_.executorPct * 100}), "%2.0f %%")
@@ -120,7 +120,7 @@ object StatsReportListener extends Logging {
val percentilesHeader = "\t" + percentiles.mkString("%\t") + "%"
def extractDoubleDistribution(stage:StageCompleted, getMetric: (TaskInfo,TaskMetrics) => Option[Double]): Option[Distribution] = {
- Distribution(stage.stageInfo.taskInfos.flatMap{
+ Distribution(stage.stage.taskInfos.flatMap {
case ((info,metric)) => getMetric(info, metric)})
}
diff --git a/core/src/main/scala/org/apache/spark/scheduler/Stage.scala b/core/src/main/scala/org/apache/spark/scheduler/Stage.scala
index aa293dc6b31b5c03784cd7745ce5ccd134f1fde4..7cb3fe46e5baf6c9880d804b80cb3015b64a3045 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/Stage.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/Stage.scala
@@ -39,6 +39,7 @@ import org.apache.spark.storage.BlockManagerId
private[spark] class Stage(
val id: Int,
val rdd: RDD[_],
+ val numTasks: Int,
val shuffleDep: Option[ShuffleDependency[_,_]], // Output shuffle if stage is a map stage
val parents: List[Stage],
val jobId: Int,
@@ -49,11 +50,6 @@ private[spark] class Stage(
val numPartitions = rdd.partitions.size
val outputLocs = Array.fill[List[MapStatus]](numPartitions)(Nil)
var numAvailableOutputs = 0
-
- /** When first task was submitted to scheduler. */
- var submissionTime: Option[Long] = None
- var completionTime: Option[Long] = None
-
private var nextAttemptId = 0
def isAvailable: Boolean = {
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 b6f11969e575efbe889d13cf8ef2dcc7eaccfe0a..37bb0891f6b14f2591504e95f98a19ab92027c75 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/StageInfo.scala
@@ -21,9 +21,18 @@ import scala.collection._
import org.apache.spark.executor.TaskMetrics
-case class StageInfo(
- val stage: Stage,
+class StageInfo(
+ stage: Stage,
val taskInfos: mutable.Buffer[(TaskInfo, TaskMetrics)] = mutable.Buffer[(TaskInfo, TaskMetrics)]()
) {
- override def toString = stage.rdd.toString
+ val stageId = stage.id
+ /** When this stage was submitted from the DAGScheduler to a TaskScheduler. */
+ var submissionTime: Option[Long] = None
+ var completionTime: Option[Long] = None
+ val rddName = stage.rdd.name
+ val name = stage.name
+ val numPartitions = stage.numPartitions
+ val numTasks = stage.numTasks
+
+ override def toString = rddName
}
diff --git a/core/src/main/scala/org/apache/spark/scheduler/Task.scala b/core/src/main/scala/org/apache/spark/scheduler/Task.scala
index 1fe0d0e4e20d7affc7b345670fde4dcd361018b4..69b42e86eae3e3dd4c737355d143b10bb18185c3 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/Task.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/Task.scala
@@ -45,7 +45,7 @@ import org.apache.spark.util.ByteBufferInputStream
*/
private[spark] abstract class Task[T](val stageId: Int, var partitionId: Int) extends Serializable {
- def run(attemptId: Long): T = {
+ final def run(attemptId: Long): T = {
context = new TaskContext(stageId, partitionId, attemptId, runningLocally = false)
if (_killed) {
kill()
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 768e5a647f76dc8d24daf663bc95fee601103d08..e6329cbd47576553b8fee871b639d550b79c8c87 100644
--- a/core/src/main/scala/org/apache/spark/storage/BlockManager.scala
+++ b/core/src/main/scala/org/apache/spark/storage/BlockManager.scala
@@ -28,7 +28,7 @@ import akka.dispatch.{Await, Future}
import akka.util.Duration
import akka.util.duration._
-import it.unimi.dsi.fastutil.io.FastByteArrayOutputStream
+import it.unimi.dsi.fastutil.io.{FastBufferedOutputStream, FastByteArrayOutputStream}
import org.apache.spark.{Logging, SparkEnv, SparkException}
import org.apache.spark.io.CompressionCodec
@@ -102,18 +102,19 @@ private[spark] class BlockManager(
}
val shuffleBlockManager = new ShuffleBlockManager(this)
+ val diskBlockManager = new DiskBlockManager(
+ System.getProperty("spark.local.dir", System.getProperty("java.io.tmpdir")))
private val blockInfo = new TimeStampedHashMap[BlockId, BlockInfo]
private[storage] val memoryStore: BlockStore = new MemoryStore(this, maxMemory)
- private[storage] val diskStore: DiskStore =
- new DiskStore(this, System.getProperty("spark.local.dir", System.getProperty("java.io.tmpdir")))
+ private[storage] val diskStore = new DiskStore(this, diskBlockManager)
// If we use Netty for shuffle, start a new Netty-based shuffle sender service.
private val nettyPort: Int = {
val useNetty = System.getProperty("spark.shuffle.use.netty", "false").toBoolean
val nettyPortConfig = System.getProperty("spark.shuffle.sender.port", "0").toInt
- if (useNetty) diskStore.startShuffleBlockSender(nettyPortConfig) else 0
+ if (useNetty) diskBlockManager.startShuffleBlockSender(nettyPortConfig) else 0
}
val connectionManager = new ConnectionManager(0)
@@ -512,16 +513,20 @@ private[spark] class BlockManager(
/**
* A short circuited method to get a block writer that can write data directly to disk.
+ * The Block will be appended to the File specified by filename.
* This is currently used for writing shuffle files out. Callers should handle error
* cases.
*/
- def getDiskBlockWriter(blockId: BlockId, serializer: Serializer, bufferSize: Int)
+ def getDiskWriter(blockId: BlockId, filename: String, serializer: Serializer, bufferSize: Int)
: BlockObjectWriter = {
- val writer = diskStore.getBlockWriter(blockId, serializer, bufferSize)
+ val compressStream: OutputStream => OutputStream = wrapForCompression(blockId, _)
+ val file = diskBlockManager.createBlockFile(blockId, filename, allowAppending = true)
+ val writer = new DiskBlockObjectWriter(blockId, file, serializer, bufferSize, compressStream)
writer.registerCloseEventHandler(() => {
+ diskBlockManager.mapBlockToFileSegment(blockId, writer.fileSegment())
val myInfo = new BlockInfo(StorageLevel.DISK_ONLY, false)
blockInfo.put(blockId, myInfo)
- myInfo.markReady(writer.size())
+ myInfo.markReady(writer.fileSegment().length)
})
writer
}
@@ -862,13 +867,24 @@ private[spark] class BlockManager(
if (shouldCompress(blockId)) compressionCodec.compressedInputStream(s) else s
}
+ /** Serializes into a stream. */
+ def dataSerializeStream(
+ blockId: BlockId,
+ outputStream: OutputStream,
+ values: Iterator[Any],
+ serializer: Serializer = defaultSerializer) {
+ val byteStream = new FastBufferedOutputStream(outputStream)
+ val ser = serializer.newInstance()
+ ser.serializeStream(wrapForCompression(blockId, byteStream)).writeAll(values).close()
+ }
+
+ /** Serializes into a byte buffer. */
def dataSerialize(
blockId: BlockId,
values: Iterator[Any],
serializer: Serializer = defaultSerializer): ByteBuffer = {
val byteStream = new FastByteArrayOutputStream(4096)
- val ser = serializer.newInstance()
- ser.serializeStream(wrapForCompression(blockId, byteStream)).writeAll(values).close()
+ dataSerializeStream(blockId, byteStream, values, serializer)
byteStream.trim()
ByteBuffer.wrap(byteStream.array)
}
diff --git a/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala b/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala
index 951503019f765001bd0313d17c663f6b3695afa2..3a65e5573383451bdc3d3a2a1f3e4d94a1c407f9 100644
--- a/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala
+++ b/core/src/main/scala/org/apache/spark/storage/BlockManagerSlaveActor.scala
@@ -26,6 +26,7 @@ import org.apache.spark.storage.BlockManagerMessages._
* An actor to take commands from the master to execute options. For example,
* this is used to remove blocks from the slave's BlockManager.
*/
+private[storage]
class BlockManagerSlaveActor(blockManager: BlockManager) extends Actor {
override def receive = {
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 76c92cefd8072871fd4fbfea210293a4098b4d2b..32d2dd06943a0952f7a6763397cbb81000b17933 100644
--- a/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala
+++ b/core/src/main/scala/org/apache/spark/storage/BlockObjectWriter.scala
@@ -17,6 +17,13 @@
package org.apache.spark.storage
+import java.io.{FileOutputStream, File, OutputStream}
+import java.nio.channels.FileChannel
+
+import it.unimi.dsi.fastutil.io.FastBufferedOutputStream
+
+import org.apache.spark.Logging
+import org.apache.spark.serializer.{SerializationStream, Serializer}
/**
* An interface for writing JVM objects to some underlying storage. This interface allows
@@ -59,12 +66,129 @@ abstract class BlockObjectWriter(val blockId: BlockId) {
def write(value: Any)
/**
- * Size of the valid writes, in bytes.
+ * Returns the file segment of committed data that this Writer has written.
*/
- def size(): Long
+ def fileSegment(): FileSegment
/**
* Cumulative time spent performing blocking writes, in ns.
*/
def timeWriting(): Long
}
+
+/** BlockObjectWriter which writes directly to a file on disk. Appends to the given file. */
+class DiskBlockObjectWriter(
+ blockId: BlockId,
+ file: File,
+ serializer: Serializer,
+ bufferSize: Int,
+ compressStream: OutputStream => OutputStream)
+ extends BlockObjectWriter(blockId)
+ with Logging
+{
+
+ /** Intercepts write calls and tracks total time spent writing. Not thread safe. */
+ private class TimeTrackingOutputStream(out: OutputStream) extends OutputStream {
+ def timeWriting = _timeWriting
+ private var _timeWriting = 0L
+
+ private def callWithTiming(f: => Unit) = {
+ val start = System.nanoTime()
+ f
+ _timeWriting += (System.nanoTime() - start)
+ }
+
+ def write(i: Int): Unit = callWithTiming(out.write(i))
+ override def write(b: Array[Byte]) = callWithTiming(out.write(b))
+ override def write(b: Array[Byte], off: Int, len: Int) = callWithTiming(out.write(b, off, len))
+ }
+
+ private val syncWrites = System.getProperty("spark.shuffle.sync", "false").toBoolean
+
+ /** The file channel, used for repositioning / truncating the file. */
+ private var channel: FileChannel = null
+ private var bs: OutputStream = null
+ private var fos: FileOutputStream = null
+ private var ts: TimeTrackingOutputStream = null
+ private var objOut: SerializationStream = null
+ private var initialPosition = 0L
+ private var lastValidPosition = 0L
+ private var initialized = false
+ private var _timeWriting = 0L
+
+ override def open(): BlockObjectWriter = {
+ fos = new FileOutputStream(file, true)
+ ts = new TimeTrackingOutputStream(fos)
+ channel = fos.getChannel()
+ initialPosition = channel.position
+ lastValidPosition = initialPosition
+ bs = compressStream(new FastBufferedOutputStream(ts, bufferSize))
+ objOut = serializer.newInstance().serializeStream(bs)
+ initialized = true
+ this
+ }
+
+ override def close() {
+ if (initialized) {
+ if (syncWrites) {
+ // Force outstanding writes to disk and track how long it takes
+ objOut.flush()
+ val start = System.nanoTime()
+ fos.getFD.sync()
+ _timeWriting += System.nanoTime() - start
+ }
+ objOut.close()
+
+ _timeWriting += ts.timeWriting
+
+ channel = null
+ bs = null
+ fos = null
+ ts = null
+ objOut = null
+ }
+ // Invoke the close callback handler.
+ super.close()
+ }
+
+ override def isOpen: Boolean = objOut != null
+
+ override def commit(): Long = {
+ if (initialized) {
+ // NOTE: Flush the serializer first and then the compressed/buffered output stream
+ objOut.flush()
+ bs.flush()
+ val prevPos = lastValidPosition
+ lastValidPosition = channel.position()
+ lastValidPosition - prevPos
+ } else {
+ // lastValidPosition is zero if stream is uninitialized
+ lastValidPosition
+ }
+ }
+
+ override def revertPartialWrites() {
+ if (initialized) {
+ // Discard current writes. We do this by flushing the outstanding writes and
+ // truncate the file to the last valid position.
+ objOut.flush()
+ bs.flush()
+ channel.truncate(lastValidPosition)
+ }
+ }
+
+ override def write(value: Any) {
+ if (!initialized) {
+ open()
+ }
+ objOut.writeObject(value)
+ }
+
+ override def fileSegment(): FileSegment = {
+ val bytesWritten = lastValidPosition - initialPosition
+ new FileSegment(file, initialPosition, bytesWritten)
+ }
+
+ // Only valid if called after close()
+ override def timeWriting() = _timeWriting
+}
diff --git a/core/src/main/scala/org/apache/spark/storage/DiskBlockManager.scala b/core/src/main/scala/org/apache/spark/storage/DiskBlockManager.scala
new file mode 100644
index 0000000000000000000000000000000000000000..bcb58ad9467e6c8ff6fcf611ec570edaebb5c735
--- /dev/null
+++ b/core/src/main/scala/org/apache/spark/storage/DiskBlockManager.scala
@@ -0,0 +1,184 @@
+/*
+ * 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.File
+import java.text.SimpleDateFormat
+import java.util.{Date, Random}
+import java.util.concurrent.ConcurrentHashMap
+
+import org.apache.spark.Logging
+import org.apache.spark.executor.ExecutorExitCode
+import org.apache.spark.network.netty.{PathResolver, ShuffleSender}
+import org.apache.spark.util.{MetadataCleaner, MetadataCleanerType, TimeStampedHashMap, Utils}
+
+/**
+ * Creates and maintains the logical mapping between logical blocks and physical on-disk
+ * locations. By default, one block is mapped to one file with a name given by its BlockId.
+ * However, it is also possible to have a block map to only a segment of a file, by calling
+ * mapBlockToFileSegment().
+ *
+ * @param rootDirs The directories to use for storing block files. Data will be hashed among these.
+ */
+private[spark] class DiskBlockManager(rootDirs: String) extends PathResolver with Logging {
+
+ private val MAX_DIR_CREATION_ATTEMPTS: Int = 10
+ private val subDirsPerLocalDir = System.getProperty("spark.diskStore.subDirectories", "64").toInt
+
+ // Create one local directory for each path mentioned in spark.local.dir; 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.
+ private val localDirs: Array[File] = createLocalDirs()
+ private val subDirs = Array.fill(localDirs.length)(new Array[File](subDirsPerLocalDir))
+ private var shuffleSender : ShuffleSender = null
+
+ // Stores only Blocks which have been specifically mapped to segments of files
+ // (rather than the default, which maps a Block to a whole file).
+ // This keeps our bookkeeping down, since the file system itself tracks the standalone Blocks.
+ private val blockToFileSegmentMap = new TimeStampedHashMap[BlockId, FileSegment]
+
+ val metadataCleaner = new MetadataCleaner(MetadataCleanerType.DISK_BLOCK_MANAGER, this.cleanup)
+
+ addShutdownHook()
+
+ /**
+ * Creates a logical mapping from the given BlockId to a segment of a file.
+ * This will cause any accesses of the logical BlockId to be directed to the specified
+ * physical location.
+ */
+ def mapBlockToFileSegment(blockId: BlockId, fileSegment: FileSegment) {
+ blockToFileSegmentMap.put(blockId, fileSegment)
+ }
+
+ /**
+ * Returns the phyiscal file segment in which the given BlockId is located.
+ * If the BlockId has been mapped to a specific FileSegment, that will be returned.
+ * Otherwise, we assume the Block is mapped to a whole file identified by the BlockId directly.
+ */
+ def getBlockLocation(blockId: BlockId): FileSegment = {
+ if (blockToFileSegmentMap.internalMap.containsKey(blockId)) {
+ blockToFileSegmentMap.get(blockId).get
+ } else {
+ val file = getFile(blockId.name)
+ new FileSegment(file, 0, file.length())
+ }
+ }
+
+ /**
+ * Simply returns a File to place the given Block into. This does not physically create the file.
+ * If filename is given, that file will be used. Otherwise, we will use the BlockId to get
+ * a unique filename.
+ */
+ def createBlockFile(blockId: BlockId, filename: String = "", allowAppending: Boolean): File = {
+ val actualFilename = if (filename == "") blockId.name else filename
+ val file = getFile(actualFilename)
+ if (!allowAppending && file.exists()) {
+ throw new IllegalStateException(
+ "Attempted to create file that already exists: " + actualFilename)
+ }
+ file
+ }
+
+ private def getFile(filename: String): File = {
+ // Figure out which local directory it hashes to, and which subdirectory in that
+ val hash = Utils.nonNegativeHash(filename)
+ val dirId = hash % localDirs.length
+ val subDirId = (hash / localDirs.length) % subDirsPerLocalDir
+
+ // Create the subdirectory if it doesn't already exist
+ var subDir = subDirs(dirId)(subDirId)
+ if (subDir == null) {
+ subDir = subDirs(dirId).synchronized {
+ val old = subDirs(dirId)(subDirId)
+ if (old != null) {
+ old
+ } else {
+ val newDir = new File(localDirs(dirId), "%02x".format(subDirId))
+ newDir.mkdir()
+ subDirs(dirId)(subDirId) = newDir
+ newDir
+ }
+ }
+ }
+
+ new File(subDir, filename)
+ }
+
+ private def createLocalDirs(): Array[File] = {
+ logDebug("Creating local directories at root dirs '" + rootDirs + "'")
+ val dateFormat = new SimpleDateFormat("yyyyMMddHHmmss")
+ rootDirs.split(",").map { rootDir =>
+ var foundLocalDir = false
+ var localDir: File = null
+ var localDirId: String = null
+ var tries = 0
+ val rand = new Random()
+ while (!foundLocalDir && tries < MAX_DIR_CREATION_ATTEMPTS) {
+ tries += 1
+ try {
+ localDirId = "%s-%04x".format(dateFormat.format(new Date), rand.nextInt(65536))
+ localDir = new File(rootDir, "spark-local-" + localDirId)
+ if (!localDir.exists) {
+ foundLocalDir = localDir.mkdirs()
+ }
+ } catch {
+ case e: Exception =>
+ logWarning("Attempt " + tries + " to create local dir " + localDir + " failed", e)
+ }
+ }
+ if (!foundLocalDir) {
+ logError("Failed " + MAX_DIR_CREATION_ATTEMPTS +
+ " attempts to create local dir in " + rootDir)
+ System.exit(ExecutorExitCode.DISK_STORE_FAILED_TO_CREATE_DIR)
+ }
+ logInfo("Created local directory at " + localDir)
+ localDir
+ }
+ }
+
+ private def cleanup(cleanupTime: Long) {
+ blockToFileSegmentMap.clearOldValues(cleanupTime)
+ }
+
+ private def addShutdownHook() {
+ localDirs.foreach(localDir => Utils.registerShutdownDeleteDir(localDir))
+ Runtime.getRuntime.addShutdownHook(new Thread("delete Spark local dirs") {
+ override def run() {
+ logDebug("Shutdown hook called")
+ localDirs.foreach { localDir =>
+ try {
+ if (!Utils.hasRootAsShutdownDeleteDir(localDir)) Utils.deleteRecursively(localDir)
+ } catch {
+ case t: Throwable =>
+ logError("Exception while deleting local spark dir: " + localDir, t)
+ }
+ }
+
+ if (shuffleSender != null) {
+ shuffleSender.stop()
+ }
+ }
+ })
+ }
+
+ private[storage] def startShuffleBlockSender(port: Int): Int = {
+ shuffleSender = new ShuffleSender(port, this)
+ logInfo("Created ShuffleSender binding to port : " + shuffleSender.port)
+ shuffleSender.port
+ }
+}
diff --git a/core/src/main/scala/org/apache/spark/storage/DiskStore.scala b/core/src/main/scala/org/apache/spark/storage/DiskStore.scala
index 2a9a3f61bd3bac274b4101d17511e15f9d308649..a3c496f9e05c517f198510095471ab6623b40d22 100644
--- a/core/src/main/scala/org/apache/spark/storage/DiskStore.scala
+++ b/core/src/main/scala/org/apache/spark/storage/DiskStore.scala
@@ -17,158 +17,25 @@
package org.apache.spark.storage
-import java.io.{File, FileOutputStream, OutputStream, RandomAccessFile}
+import java.io.{FileOutputStream, RandomAccessFile}
import java.nio.ByteBuffer
-import java.nio.channels.FileChannel
import java.nio.channels.FileChannel.MapMode
-import java.util.{Random, Date}
-import java.text.SimpleDateFormat
import scala.collection.mutable.ArrayBuffer
-import it.unimi.dsi.fastutil.io.FastBufferedOutputStream
-
-import org.apache.spark.executor.ExecutorExitCode
-import org.apache.spark.serializer.{Serializer, SerializationStream}
import org.apache.spark.Logging
-import org.apache.spark.network.netty.ShuffleSender
-import org.apache.spark.network.netty.PathResolver
+import org.apache.spark.serializer.Serializer
import org.apache.spark.util.Utils
/**
* Stores BlockManager blocks on disk.
*/
-private class DiskStore(blockManager: BlockManager, rootDirs: String)
+private class DiskStore(blockManager: BlockManager, diskManager: DiskBlockManager)
extends BlockStore(blockManager) with Logging {
- class DiskBlockObjectWriter(blockId: BlockId, serializer: Serializer, bufferSize: Int)
- extends BlockObjectWriter(blockId) {
-
- /** Intercepts write calls and tracks total time spent writing. Not thread safe. */
- private class TimeTrackingOutputStream(out: OutputStream) extends OutputStream {
- def timeWriting = _timeWriting
- private var _timeWriting = 0L
-
- private def callWithTiming(f: => Unit) = {
- val start = System.nanoTime()
- f
- _timeWriting += (System.nanoTime() - start)
- }
-
- def write(i: Int): Unit = callWithTiming(out.write(i))
- override def write(b: Array[Byte]) = callWithTiming(out.write(b))
- override def write(b: Array[Byte], off: Int, len: Int) = callWithTiming(out.write(b, off, len))
- }
-
- private val f: File = createFile(blockId /*, allowAppendExisting */)
- private val syncWrites = System.getProperty("spark.shuffle.sync", "false").toBoolean
-
- // The file channel, used for repositioning / truncating the file.
- private var channel: FileChannel = null
- private var bs: OutputStream = null
- private var fos: FileOutputStream = null
- private var ts: TimeTrackingOutputStream = null
- private var objOut: SerializationStream = null
- private var lastValidPosition = 0L
- private var initialized = false
- private var _timeWriting = 0L
-
- override def open(): DiskBlockObjectWriter = {
- fos = new FileOutputStream(f, true)
- ts = new TimeTrackingOutputStream(fos)
- channel = fos.getChannel()
- bs = blockManager.wrapForCompression(blockId, new FastBufferedOutputStream(ts, bufferSize))
- objOut = serializer.newInstance().serializeStream(bs)
- initialized = true
- this
- }
-
- override def close() {
- if (initialized) {
- if (syncWrites) {
- // Force outstanding writes to disk and track how long it takes
- objOut.flush()
- val start = System.nanoTime()
- fos.getFD.sync()
- _timeWriting += System.nanoTime() - start
- objOut.close()
- } else {
- objOut.close()
- }
-
- _timeWriting += ts.timeWriting
-
- channel = null
- bs = null
- fos = null
- ts = null
- objOut = null
- }
- // Invoke the close callback handler.
- super.close()
- }
-
- override def isOpen: Boolean = objOut != null
-
- // Flush the partial writes, and set valid length to be the length of the entire file.
- // Return the number of bytes written for this commit.
- override def commit(): Long = {
- if (initialized) {
- // NOTE: Flush the serializer first and then the compressed/buffered output stream
- objOut.flush()
- bs.flush()
- val prevPos = lastValidPosition
- lastValidPosition = channel.position()
- lastValidPosition - prevPos
- } else {
- // lastValidPosition is zero if stream is uninitialized
- lastValidPosition
- }
- }
-
- override def revertPartialWrites() {
- if (initialized) {
- // Discard current writes. We do this by flushing the outstanding writes and
- // truncate the file to the last valid position.
- objOut.flush()
- bs.flush()
- channel.truncate(lastValidPosition)
- }
- }
-
- override def write(value: Any) {
- if (!initialized) {
- open()
- }
- objOut.writeObject(value)
- }
-
- override def size(): Long = lastValidPosition
-
- // Only valid if called after close()
- override def timeWriting = _timeWriting
- }
-
- private val MAX_DIR_CREATION_ATTEMPTS: Int = 10
- private val subDirsPerLocalDir = System.getProperty("spark.diskStore.subDirectories", "64").toInt
-
- private var shuffleSender : ShuffleSender = null
- // Create one local directory for each path mentioned in spark.local.dir; 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.
- private val localDirs: Array[File] = createLocalDirs()
- private val subDirs = Array.fill(localDirs.length)(new Array[File](subDirsPerLocalDir))
-
- addShutdownHook()
-
- def getBlockWriter(blockId: BlockId, serializer: Serializer, bufferSize: Int)
- : BlockObjectWriter = {
- new DiskBlockObjectWriter(blockId, serializer, bufferSize)
- }
-
override def getSize(blockId: BlockId): Long = {
- getFile(blockId).length()
+ diskManager.getBlockLocation(blockId).length
}
override def putBytes(blockId: BlockId, _bytes: ByteBuffer, level: StorageLevel) {
@@ -177,27 +44,15 @@ private class DiskStore(blockManager: BlockManager, rootDirs: String)
val bytes = _bytes.duplicate()
logDebug("Attempting to put block " + blockId)
val startTime = System.currentTimeMillis
- val file = createFile(blockId)
- val channel = new RandomAccessFile(file, "rw").getChannel()
+ val file = diskManager.createBlockFile(blockId, allowAppending = false)
+ val channel = new FileOutputStream(file).getChannel()
while (bytes.remaining > 0) {
channel.write(bytes)
}
channel.close()
val finishTime = System.currentTimeMillis
logDebug("Block %s stored as %s file on disk in %d ms".format(
- blockId, Utils.bytesToString(bytes.limit), (finishTime - startTime)))
- }
-
- private def getFileBytes(file: File): ByteBuffer = {
- val length = file.length()
- val channel = new RandomAccessFile(file, "r").getChannel()
- val buffer = try {
- channel.map(MapMode.READ_ONLY, 0, length)
- } finally {
- channel.close()
- }
-
- buffer
+ file.getName, Utils.bytesToString(bytes.limit), (finishTime - startTime)))
}
override def putValues(
@@ -209,21 +64,18 @@ private class DiskStore(blockManager: BlockManager, rootDirs: String)
logDebug("Attempting to write values for block " + blockId)
val startTime = System.currentTimeMillis
- val file = createFile(blockId)
- val fileOut = blockManager.wrapForCompression(blockId,
- new FastBufferedOutputStream(new FileOutputStream(file)))
- val objOut = blockManager.defaultSerializer.newInstance().serializeStream(fileOut)
- objOut.writeAll(values.iterator)
- objOut.close()
- val length = file.length()
+ val file = diskManager.createBlockFile(blockId, allowAppending = false)
+ val outputStream = new FileOutputStream(file)
+ blockManager.dataSerializeStream(blockId, outputStream, values.iterator)
+ val length = file.length
val timeTaken = System.currentTimeMillis - startTime
logDebug("Block %s stored as %s file on disk in %d ms".format(
- blockId, Utils.bytesToString(length), timeTaken))
+ file.getName, Utils.bytesToString(length), timeTaken))
if (returnValues) {
// Return a byte buffer for the contents of the file
- val buffer = getFileBytes(file)
+ val buffer = getBytes(blockId).get
PutResult(length, Right(buffer))
} else {
PutResult(length, null)
@@ -231,13 +83,18 @@ private class DiskStore(blockManager: BlockManager, rootDirs: String)
}
override def getBytes(blockId: BlockId): Option[ByteBuffer] = {
- val file = getFile(blockId)
- val bytes = getFileBytes(file)
- Some(bytes)
+ val segment = diskManager.getBlockLocation(blockId)
+ val channel = new RandomAccessFile(segment.file, "r").getChannel()
+ val buffer = try {
+ channel.map(MapMode.READ_ONLY, segment.offset, segment.length)
+ } finally {
+ channel.close()
+ }
+ Some(buffer)
}
override def getValues(blockId: BlockId): Option[Iterator[Any]] = {
- getBytes(blockId).map(bytes => blockManager.dataDeserialize(blockId, bytes))
+ getBytes(blockId).map(buffer => blockManager.dataDeserialize(blockId, buffer))
}
/**
@@ -249,118 +106,20 @@ private class DiskStore(blockManager: BlockManager, rootDirs: String)
}
override def remove(blockId: BlockId): Boolean = {
- val file = getFile(blockId)
- if (file.exists()) {
+ val fileSegment = diskManager.getBlockLocation(blockId)
+ val file = fileSegment.file
+ if (file.exists() && file.length() == fileSegment.length) {
file.delete()
} else {
+ if (fileSegment.length < file.length()) {
+ logWarning("Could not delete block associated with only a part of a file: " + blockId)
+ }
false
}
}
override def contains(blockId: BlockId): Boolean = {
- getFile(blockId).exists()
- }
-
- private def createFile(blockId: BlockId, allowAppendExisting: Boolean = false): File = {
- val file = getFile(blockId)
- if (!allowAppendExisting && file.exists()) {
- // NOTE(shivaram): Delete the file if it exists. This might happen if a ShuffleMap task
- // was rescheduled on the same machine as the old task.
- logWarning("File for block " + blockId + " already exists on disk: " + file + ". Deleting")
- file.delete()
- }
- file
- }
-
- private def getFile(blockId: BlockId): File = {
- logDebug("Getting file for block " + blockId)
-
- // Figure out which local directory it hashes to, and which subdirectory in that
- val hash = Utils.nonNegativeHash(blockId)
- val dirId = hash % localDirs.length
- val subDirId = (hash / localDirs.length) % subDirsPerLocalDir
-
- // Create the subdirectory if it doesn't already exist
- var subDir = subDirs(dirId)(subDirId)
- if (subDir == null) {
- subDir = subDirs(dirId).synchronized {
- val old = subDirs(dirId)(subDirId)
- if (old != null) {
- old
- } else {
- val newDir = new File(localDirs(dirId), "%02x".format(subDirId))
- newDir.mkdir()
- subDirs(dirId)(subDirId) = newDir
- newDir
- }
- }
- }
-
- new File(subDir, blockId.name)
- }
-
- private def createLocalDirs(): Array[File] = {
- logDebug("Creating local directories at root dirs '" + rootDirs + "'")
- val dateFormat = new SimpleDateFormat("yyyyMMddHHmmss")
- rootDirs.split(",").map { rootDir =>
- var foundLocalDir = false
- var localDir: File = null
- var localDirId: String = null
- var tries = 0
- val rand = new Random()
- while (!foundLocalDir && tries < MAX_DIR_CREATION_ATTEMPTS) {
- tries += 1
- try {
- localDirId = "%s-%04x".format(dateFormat.format(new Date), rand.nextInt(65536))
- localDir = new File(rootDir, "spark-local-" + localDirId)
- if (!localDir.exists) {
- foundLocalDir = localDir.mkdirs()
- }
- } catch {
- case e: Exception =>
- logWarning("Attempt " + tries + " to create local dir " + localDir + " failed", e)
- }
- }
- if (!foundLocalDir) {
- logError("Failed " + MAX_DIR_CREATION_ATTEMPTS +
- " attempts to create local dir in " + rootDir)
- System.exit(ExecutorExitCode.DISK_STORE_FAILED_TO_CREATE_DIR)
- }
- logInfo("Created local directory at " + localDir)
- localDir
- }
- }
-
- private def addShutdownHook() {
- localDirs.foreach(localDir => Utils.registerShutdownDeleteDir(localDir))
- Runtime.getRuntime.addShutdownHook(new Thread("delete Spark local dirs") {
- override def run() {
- logDebug("Shutdown hook called")
- localDirs.foreach { localDir =>
- try {
- if (!Utils.hasRootAsShutdownDeleteDir(localDir)) Utils.deleteRecursively(localDir)
- } catch {
- case t: Throwable =>
- logError("Exception while deleting local spark dir: " + localDir, t)
- }
- }
- if (shuffleSender != null) {
- shuffleSender.stop()
- }
- }
- })
- }
-
- private[storage] def startShuffleBlockSender(port: Int): Int = {
- val pResolver = new PathResolver {
- override def getAbsolutePath(blockIdString: String): String = {
- val blockId = BlockId(blockIdString)
- if (!blockId.isShuffle) null
- else DiskStore.this.getFile(blockId).getAbsolutePath
- }
- }
- shuffleSender = new ShuffleSender(port, pResolver)
- logInfo("Created ShuffleSender binding to port : "+ shuffleSender.port)
- shuffleSender.port
+ val file = diskManager.getBlockLocation(blockId).file
+ file.exists()
}
}
diff --git a/core/src/main/scala/org/apache/spark/storage/FileSegment.scala b/core/src/main/scala/org/apache/spark/storage/FileSegment.scala
new file mode 100644
index 0000000000000000000000000000000000000000..555486830a7693a42fc1e874bdee647b5b657b58
--- /dev/null
+++ b/core/src/main/scala/org/apache/spark/storage/FileSegment.scala
@@ -0,0 +1,28 @@
+/*
+ * 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.File
+
+/**
+ * References a particular segment of a file (potentially the entire file),
+ * based off an offset and a length.
+ */
+private[spark] class FileSegment(val file: File, val offset: Long, val length : Long) {
+ override def toString = "(name=%s, offset=%d, length=%d)".format(file.getName, offset, length)
+}
diff --git a/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala
index f39fcd87fb0c8a7f1c5f8764775b5d144aad6f31..229178c09512ba25f6ca6c22cde1246de7d7761c 100644
--- a/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala
+++ b/core/src/main/scala/org/apache/spark/storage/ShuffleBlockManager.scala
@@ -17,12 +17,13 @@
package org.apache.spark.storage
-import org.apache.spark.serializer.Serializer
+import java.util.concurrent.ConcurrentLinkedQueue
+import java.util.concurrent.atomic.AtomicInteger
+import org.apache.spark.serializer.Serializer
private[spark]
-class ShuffleWriterGroup(val id: Int, val writers: Array[BlockObjectWriter])
-
+class ShuffleWriterGroup(val id: Int, val fileId: Int, val writers: Array[BlockObjectWriter])
private[spark]
trait ShuffleBlocks {
@@ -30,24 +31,61 @@ trait ShuffleBlocks {
def releaseWriters(group: ShuffleWriterGroup)
}
+/**
+ * Manages assigning disk-based block writers to shuffle tasks. Each shuffle task gets one writer
+ * per reducer.
+ *
+ * As an optimization to reduce the number of physical shuffle files produced, multiple shuffle
+ * blocks are aggregated into the same file. There is one "combined shuffle file" per reducer
+ * per concurrently executing shuffle task. As soon as a task finishes writing to its shuffle files,
+ * it releases them for another task.
+ * Regarding the implementation of this feature, shuffle files are identified by a 3-tuple:
+ * - shuffleId: The unique id given to the entire shuffle stage.
+ * - bucketId: The id of the output partition (i.e., reducer id)
+ * - fileId: The unique id identifying a group of "combined shuffle files." Only one task at a
+ * time owns a particular fileId, and this id is returned to a pool when the task finishes.
+ */
private[spark]
class ShuffleBlockManager(blockManager: BlockManager) {
+ // Turning off shuffle file consolidation causes all shuffle Blocks to get their own file.
+ // TODO: Remove this once the shuffle file consolidation feature is stable.
+ val consolidateShuffleFiles =
+ System.getProperty("spark.shuffle.consolidateFiles", "true").toBoolean
+
+ var nextFileId = new AtomicInteger(0)
+ val unusedFileIds = new ConcurrentLinkedQueue[java.lang.Integer]()
- def forShuffle(shuffleId: Int, numBuckets: Int, serializer: Serializer): ShuffleBlocks = {
+ def forShuffle(shuffleId: Int, numBuckets: Int, serializer: Serializer) = {
new ShuffleBlocks {
// Get a group of writers for a map task.
override def acquireWriters(mapId: Int): ShuffleWriterGroup = {
val bufferSize = System.getProperty("spark.shuffle.file.buffer.kb", "100").toInt * 1024
+ val fileId = getUnusedFileId()
val writers = Array.tabulate[BlockObjectWriter](numBuckets) { bucketId =>
val blockId = ShuffleBlockId(shuffleId, mapId, bucketId)
- blockManager.getDiskBlockWriter(blockId, serializer, bufferSize)
+ val filename = physicalFileName(shuffleId, bucketId, fileId)
+ blockManager.getDiskWriter(blockId, filename, serializer, bufferSize)
}
- new ShuffleWriterGroup(mapId, writers)
+ new ShuffleWriterGroup(mapId, fileId, writers)
}
- override def releaseWriters(group: ShuffleWriterGroup) = {
- // Nothing really to release here.
+ override def releaseWriters(group: ShuffleWriterGroup) {
+ recycleFileId(group.fileId)
}
}
}
+
+ private def getUnusedFileId(): Int = {
+ val fileId = unusedFileIds.poll()
+ if (fileId == null) nextFileId.getAndIncrement() else fileId
+ }
+
+ private def recycleFileId(fileId: Int) {
+ if (!consolidateShuffleFiles) { return } // ensures we always generate new file id
+ unusedFileIds.add(fileId)
+ }
+
+ private def physicalFileName(shuffleId: Int, bucketId: Int, fileId: Int) = {
+ "merged_shuffle_%d_%d_%d".format(shuffleId, bucketId, fileId)
+ }
}
diff --git a/core/src/main/scala/spark/storage/StoragePerfTester.scala b/core/src/main/scala/org/apache/spark/storage/StoragePerfTester.scala
similarity index 93%
rename from core/src/main/scala/spark/storage/StoragePerfTester.scala
rename to core/src/main/scala/org/apache/spark/storage/StoragePerfTester.scala
index 5f30383fd03667007cd629ce3264d3c451ecd393..7dcadc380542cbe93413a339d8573f835b633546 100644
--- a/core/src/main/scala/spark/storage/StoragePerfTester.scala
+++ b/core/src/main/scala/org/apache/spark/storage/StoragePerfTester.scala
@@ -7,9 +7,11 @@ import org.apache.spark.serializer.KryoSerializer
import org.apache.spark.SparkContext
import org.apache.spark.util.Utils
-/** Utility for micro-benchmarking shuffle write performance.
- *
- * Writes simulated shuffle output from several threads and records the observed throughput*/
+/**
+ * Utility for micro-benchmarking shuffle write performance.
+ *
+ * Writes simulated shuffle output from several threads and records the observed throughput.
+ */
object StoragePerfTester {
def main(args: Array[String]) = {
/** Total amount of data to generate. Distributed evenly amongst maps and reduce splits. */
@@ -44,7 +46,7 @@ object StoragePerfTester {
}
buckets.writers.map {w =>
w.commit()
- total.addAndGet(w.size())
+ total.addAndGet(w.fileSegment().length)
w.close()
}
diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/IndexPage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/IndexPage.scala
index b39c0e9769d48ee27b7d3c96277fad601f1d0c73..ca5a28625b7de522c1975c8381282e8677481ad7 100644
--- a/core/src/main/scala/org/apache/spark/ui/jobs/IndexPage.scala
+++ b/core/src/main/scala/org/apache/spark/ui/jobs/IndexPage.scala
@@ -38,7 +38,7 @@ private[spark] class IndexPage(parent: JobProgressUI) {
val now = System.currentTimeMillis()
var activeTime = 0L
- for (tasks <- listener.stageToTasksActive.values; t <- tasks) {
+ for (tasks <- listener.stageIdToTasksActive.values; t <- tasks) {
activeTime += t.timeRunning(now)
}
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 913f7ec22fcd3d4109d82be95a403cf8098d2413..6b854740d6a2425e51cac0505a2e6ecc58cecf30 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
@@ -36,52 +36,52 @@ private[spark] class JobProgressListener(val sc: SparkContext) extends SparkList
val RETAINED_STAGES = System.getProperty("spark.ui.retained_stages", "1000").toInt
val DEFAULT_POOL_NAME = "default"
- val stageToPool = new HashMap[Stage, String]()
- val stageToDescription = new HashMap[Stage, String]()
- val poolToActiveStages = new HashMap[String, HashSet[Stage]]()
+ val stageIdToPool = new HashMap[Int, String]()
+ val stageIdToDescription = new HashMap[Int, String]()
+ val poolToActiveStages = new HashMap[String, HashSet[StageInfo]]()
- val activeStages = HashSet[Stage]()
- val completedStages = ListBuffer[Stage]()
- val failedStages = ListBuffer[Stage]()
+ val activeStages = HashSet[StageInfo]()
+ val completedStages = ListBuffer[StageInfo]()
+ val failedStages = ListBuffer[StageInfo]()
// Total metrics reflect metrics only for completed tasks
var totalTime = 0L
var totalShuffleRead = 0L
var totalShuffleWrite = 0L
- val stageToTime = HashMap[Int, Long]()
- val stageToShuffleRead = HashMap[Int, Long]()
- val stageToShuffleWrite = HashMap[Int, Long]()
- val stageToTasksActive = HashMap[Int, HashSet[TaskInfo]]()
- val stageToTasksComplete = HashMap[Int, Int]()
- val stageToTasksFailed = HashMap[Int, Int]()
- val stageToTaskInfos =
+ val stageIdToTime = HashMap[Int, Long]()
+ val stageIdToShuffleRead = HashMap[Int, Long]()
+ val stageIdToShuffleWrite = HashMap[Int, Long]()
+ val stageIdToTasksActive = HashMap[Int, HashSet[TaskInfo]]()
+ val stageIdToTasksComplete = HashMap[Int, Int]()
+ val stageIdToTasksFailed = HashMap[Int, Int]()
+ val stageIdToTaskInfos =
HashMap[Int, HashSet[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]]()
override def onJobStart(jobStart: SparkListenerJobStart) {}
override def onStageCompleted(stageCompleted: StageCompleted) = synchronized {
- val stage = stageCompleted.stageInfo.stage
- poolToActiveStages(stageToPool(stage)) -= stage
+ val stage = stageCompleted.stage
+ poolToActiveStages(stageIdToPool(stage.stageId)) -= stage
activeStages -= stage
completedStages += stage
trimIfNecessary(completedStages)
}
/** If stages is too large, remove and garbage collect old stages */
- def trimIfNecessary(stages: ListBuffer[Stage]) = synchronized {
+ def trimIfNecessary(stages: ListBuffer[StageInfo]) = synchronized {
if (stages.size > RETAINED_STAGES) {
val toRemove = RETAINED_STAGES / 10
stages.takeRight(toRemove).foreach( s => {
- stageToTaskInfos.remove(s.id)
- stageToTime.remove(s.id)
- stageToShuffleRead.remove(s.id)
- stageToShuffleWrite.remove(s.id)
- stageToTasksActive.remove(s.id)
- stageToTasksComplete.remove(s.id)
- stageToTasksFailed.remove(s.id)
- stageToPool.remove(s)
- if (stageToDescription.contains(s)) {stageToDescription.remove(s)}
+ stageIdToTaskInfos.remove(s.stageId)
+ stageIdToTime.remove(s.stageId)
+ stageIdToShuffleRead.remove(s.stageId)
+ stageIdToShuffleWrite.remove(s.stageId)
+ stageIdToTasksActive.remove(s.stageId)
+ stageIdToTasksComplete.remove(s.stageId)
+ stageIdToTasksFailed.remove(s.stageId)
+ stageIdToPool.remove(s.stageId)
+ if (stageIdToDescription.contains(s.stageId)) {stageIdToDescription.remove(s.stageId)}
})
stages.trimEnd(toRemove)
}
@@ -95,25 +95,25 @@ private[spark] class JobProgressListener(val sc: SparkContext) extends SparkList
val poolName = Option(stageSubmitted.properties).map {
p => p.getProperty("spark.scheduler.pool", DEFAULT_POOL_NAME)
}.getOrElse(DEFAULT_POOL_NAME)
- stageToPool(stage) = poolName
+ stageIdToPool(stage.stageId) = poolName
val description = Option(stageSubmitted.properties).flatMap {
p => Option(p.getProperty(SparkContext.SPARK_JOB_DESCRIPTION))
}
- description.map(d => stageToDescription(stage) = d)
+ description.map(d => stageIdToDescription(stage.stageId) = d)
- val stages = poolToActiveStages.getOrElseUpdate(poolName, new HashSet[Stage]())
+ val stages = poolToActiveStages.getOrElseUpdate(poolName, new HashSet[StageInfo]())
stages += stage
}
override def onTaskStart(taskStart: SparkListenerTaskStart) = synchronized {
val sid = taskStart.task.stageId
- val tasksActive = stageToTasksActive.getOrElseUpdate(sid, new HashSet[TaskInfo]())
+ val tasksActive = stageIdToTasksActive.getOrElseUpdate(sid, new HashSet[TaskInfo]())
tasksActive += taskStart.taskInfo
- val taskList = stageToTaskInfos.getOrElse(
+ val taskList = stageIdToTaskInfos.getOrElse(
sid, HashSet[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]())
taskList += ((taskStart.taskInfo, None, None))
- stageToTaskInfos(sid) = taskList
+ stageIdToTaskInfos(sid) = taskList
}
override def onTaskGettingResult(taskGettingResult: SparkListenerTaskGettingResult)
@@ -124,40 +124,40 @@ private[spark] class JobProgressListener(val sc: SparkContext) extends SparkList
override def onTaskEnd(taskEnd: SparkListenerTaskEnd) = synchronized {
val sid = taskEnd.task.stageId
- val tasksActive = stageToTasksActive.getOrElseUpdate(sid, new HashSet[TaskInfo]())
+ val tasksActive = stageIdToTasksActive.getOrElseUpdate(sid, new HashSet[TaskInfo]())
tasksActive -= taskEnd.taskInfo
val (failureInfo, metrics): (Option[ExceptionFailure], Option[TaskMetrics]) =
taskEnd.reason match {
case e: ExceptionFailure =>
- stageToTasksFailed(sid) = stageToTasksFailed.getOrElse(sid, 0) + 1
+ stageIdToTasksFailed(sid) = stageIdToTasksFailed.getOrElse(sid, 0) + 1
(Some(e), e.metrics)
case _ =>
- stageToTasksComplete(sid) = stageToTasksComplete.getOrElse(sid, 0) + 1
+ stageIdToTasksComplete(sid) = stageIdToTasksComplete.getOrElse(sid, 0) + 1
(None, Option(taskEnd.taskMetrics))
}
- stageToTime.getOrElseUpdate(sid, 0L)
+ stageIdToTime.getOrElseUpdate(sid, 0L)
val time = metrics.map(m => m.executorRunTime).getOrElse(0)
- stageToTime(sid) += time
+ stageIdToTime(sid) += time
totalTime += time
- stageToShuffleRead.getOrElseUpdate(sid, 0L)
+ stageIdToShuffleRead.getOrElseUpdate(sid, 0L)
val shuffleRead = metrics.flatMap(m => m.shuffleReadMetrics).map(s =>
s.remoteBytesRead).getOrElse(0L)
- stageToShuffleRead(sid) += shuffleRead
+ stageIdToShuffleRead(sid) += shuffleRead
totalShuffleRead += shuffleRead
- stageToShuffleWrite.getOrElseUpdate(sid, 0L)
+ stageIdToShuffleWrite.getOrElseUpdate(sid, 0L)
val shuffleWrite = metrics.flatMap(m => m.shuffleWriteMetrics).map(s =>
s.shuffleBytesWritten).getOrElse(0L)
- stageToShuffleWrite(sid) += shuffleWrite
+ stageIdToShuffleWrite(sid) += shuffleWrite
totalShuffleWrite += shuffleWrite
- val taskList = stageToTaskInfos.getOrElse(
+ val taskList = stageIdToTaskInfos.getOrElse(
sid, HashSet[(TaskInfo, Option[TaskMetrics], Option[ExceptionFailure])]())
taskList -= ((taskEnd.taskInfo, None, None))
taskList += ((taskEnd.taskInfo, metrics, failureInfo))
- stageToTaskInfos(sid) = taskList
+ stageIdToTaskInfos(sid) = taskList
}
override def onJobEnd(jobEnd: SparkListenerJobEnd) = synchronized {
@@ -165,10 +165,15 @@ private[spark] class JobProgressListener(val sc: SparkContext) extends SparkList
case end: SparkListenerJobEnd =>
end.jobResult match {
case JobFailed(ex, Some(stage)) =>
- activeStages -= stage
- poolToActiveStages(stageToPool(stage)) -= stage
- failedStages += stage
- trimIfNecessary(failedStages)
+ /* If two jobs share a stage we could get this failure message twice. So we first
+ * check whether we've already retired this stage. */
+ val stageInfo = activeStages.filter(s => s.stageId == stage.id).headOption
+ stageInfo.foreach {s =>
+ activeStages -= s
+ poolToActiveStages(stageIdToPool(stage.id)) -= s
+ failedStages += s
+ trimIfNecessary(failedStages)
+ }
case _ =>
}
case _ =>
diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/PoolTable.scala b/core/src/main/scala/org/apache/spark/ui/jobs/PoolTable.scala
index 06810d8dbc2926f8ededb16d58ca4767804ed41d..cfeeccda41713c41c8acbf7c7f69dc5291cb38c4 100644
--- a/core/src/main/scala/org/apache/spark/ui/jobs/PoolTable.scala
+++ b/core/src/main/scala/org/apache/spark/ui/jobs/PoolTable.scala
@@ -21,13 +21,13 @@ import scala.collection.mutable.HashMap
import scala.collection.mutable.HashSet
import scala.xml.Node
-import org.apache.spark.scheduler.{Schedulable, Stage}
+import org.apache.spark.scheduler.{Schedulable, StageInfo}
import org.apache.spark.ui.UIUtils
/** Table showing list of pools */
private[spark] class PoolTable(pools: Seq[Schedulable], listener: JobProgressListener) {
- var poolToActiveStages: HashMap[String, HashSet[Stage]] = listener.poolToActiveStages
+ var poolToActiveStages: HashMap[String, HashSet[StageInfo]] = listener.poolToActiveStages
def toNodeSeq(): Seq[Node] = {
listener.synchronized {
@@ -35,7 +35,7 @@ private[spark] class PoolTable(pools: Seq[Schedulable], listener: JobProgressLis
}
}
- private def poolTable(makeRow: (Schedulable, HashMap[String, HashSet[Stage]]) => Seq[Node],
+ private def poolTable(makeRow: (Schedulable, HashMap[String, HashSet[StageInfo]]) => Seq[Node],
rows: Seq[Schedulable]
): Seq[Node] = {
<table class="table table-bordered table-striped table-condensed sortable table-fixed">
@@ -53,7 +53,7 @@ private[spark] class PoolTable(pools: Seq[Schedulable], listener: JobProgressLis
</table>
}
- private def poolRow(p: Schedulable, poolToActiveStages: HashMap[String, HashSet[Stage]])
+ private def poolRow(p: Schedulable, poolToActiveStages: HashMap[String, HashSet[StageInfo]])
: Seq[Node] = {
val activeStages = poolToActiveStages.get(p.name) match {
case Some(stages) => stages.size
diff --git a/core/src/main/scala/org/apache/spark/ui/jobs/StagePage.scala b/core/src/main/scala/org/apache/spark/ui/jobs/StagePage.scala
index b7c81d091cd22fdd9f916feca35d6c5e03769d1c..0dd57235e36516e54de5fb89071810888d1de974 100644
--- a/core/src/main/scala/org/apache/spark/ui/jobs/StagePage.scala
+++ b/core/src/main/scala/org/apache/spark/ui/jobs/StagePage.scala
@@ -40,7 +40,7 @@ private[spark] class StagePage(parent: JobProgressUI) {
val stageId = request.getParameter("id").toInt
val now = System.currentTimeMillis()
- if (!listener.stageToTaskInfos.contains(stageId)) {
+ if (!listener.stageIdToTaskInfos.contains(stageId)) {
val content =
<div>
<h4>Summary Metrics</h4> No tasks have started yet
@@ -49,23 +49,23 @@ private[spark] class StagePage(parent: JobProgressUI) {
return headerSparkPage(content, parent.sc, "Details for Stage %s".format(stageId), Stages)
}
- val tasks = listener.stageToTaskInfos(stageId).toSeq.sortBy(_._1.launchTime)
+ val tasks = listener.stageIdToTaskInfos(stageId).toSeq.sortBy(_._1.launchTime)
val numCompleted = tasks.count(_._1.finished)
- val shuffleReadBytes = listener.stageToShuffleRead.getOrElse(stageId, 0L)
+ val shuffleReadBytes = listener.stageIdToShuffleRead.getOrElse(stageId, 0L)
val hasShuffleRead = shuffleReadBytes > 0
- val shuffleWriteBytes = listener.stageToShuffleWrite.getOrElse(stageId, 0L)
+ val shuffleWriteBytes = listener.stageIdToShuffleWrite.getOrElse(stageId, 0L)
val hasShuffleWrite = shuffleWriteBytes > 0
var activeTime = 0L
- listener.stageToTasksActive(stageId).foreach(activeTime += _.timeRunning(now))
+ listener.stageIdToTasksActive(stageId).foreach(activeTime += _.timeRunning(now))
val summary =
<div>
<ul class="unstyled">
<li>
<strong>CPU time: </strong>
- {parent.formatDuration(listener.stageToTime.getOrElse(stageId, 0L) + activeTime)}
+ {parent.formatDuration(listener.stageIdToTime.getOrElse(stageId, 0L) + activeTime)}
</li>
{if (hasShuffleRead)
<li>
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 07db8622da4718be7a73bd56d708eed4d2bd6036..2c29ea7d443f29e721db1857612df4909b44f0db 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
@@ -22,13 +22,13 @@ import java.util.Date
import scala.xml.Node
import scala.collection.mutable.HashSet
-import org.apache.spark.scheduler.{SchedulingMode, Stage, TaskInfo}
+import org.apache.spark.scheduler.{SchedulingMode, StageInfo, TaskInfo}
import org.apache.spark.ui.UIUtils
import org.apache.spark.util.Utils
/** Page showing list of all ongoing and recently finished stages */
-private[spark] class StageTable(val stages: Seq[Stage], val parent: JobProgressUI) {
+private[spark] class StageTable(val stages: Seq[StageInfo], val parent: JobProgressUI) {
val listener = parent.listener
val dateFmt = parent.dateFmt
@@ -73,40 +73,40 @@ private[spark] class StageTable(val stages: Seq[Stage], val parent: JobProgressU
}
- private def stageRow(s: Stage): Seq[Node] = {
+ private def stageRow(s: StageInfo): Seq[Node] = {
val submissionTime = s.submissionTime match {
case Some(t) => dateFmt.format(new Date(t))
case None => "Unknown"
}
- val shuffleRead = listener.stageToShuffleRead.getOrElse(s.id, 0L) match {
+ val shuffleRead = listener.stageIdToShuffleRead.getOrElse(s.stageId, 0L) match {
case 0 => ""
case b => Utils.bytesToString(b)
}
- val shuffleWrite = listener.stageToShuffleWrite.getOrElse(s.id, 0L) match {
+ val shuffleWrite = listener.stageIdToShuffleWrite.getOrElse(s.stageId, 0L) match {
case 0 => ""
case b => Utils.bytesToString(b)
}
- val startedTasks = listener.stageToTasksActive.getOrElse(s.id, HashSet[TaskInfo]()).size
- val completedTasks = listener.stageToTasksComplete.getOrElse(s.id, 0)
- val failedTasks = listener.stageToTasksFailed.getOrElse(s.id, 0) match {
+ val startedTasks = listener.stageIdToTasksActive.getOrElse(s.stageId, HashSet[TaskInfo]()).size
+ val completedTasks = listener.stageIdToTasksComplete.getOrElse(s.stageId, 0)
+ val failedTasks = listener.stageIdToTasksFailed.getOrElse(s.stageId, 0) match {
case f if f > 0 => "(%s failed)".format(f)
case _ => ""
}
- val totalTasks = s.numPartitions
+ val totalTasks = s.numTasks
- val poolName = listener.stageToPool.get(s)
+ val poolName = listener.stageIdToPool.get(s.stageId)
val nameLink =
- <a href={"%s/stages/stage?id=%s".format(UIUtils.prependBaseUri(),s.id)}>{s.name}</a>
- val description = listener.stageToDescription.get(s)
+ <a href={"%s/stages/stage?id=%s".format(UIUtils.prependBaseUri(),s.stageId)}>{s.toString}</a>
+ val description = listener.stageIdToDescription.get(s.stageId)
.map(d => <div><em>{d}</em></div><div>{nameLink}</div>).getOrElse(nameLink)
val finishTime = s.completionTime.getOrElse(System.currentTimeMillis())
val duration = s.submissionTime.map(t => finishTime - t)
<tr>
- <td>{s.id}</td>
+ <td>{s.stageId}</td>
{if (isFairScheduler) {
<td><a href={"%s/stages/pool?poolname=%s".format(UIUtils.prependBaseUri(),poolName.get)}>
{poolName.get}</a></td>}
diff --git a/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala
index 0ce1394c77f59b2188d4e9f715e7653931b2e651..3f963727d98ddd3aca90c8bb327e410dceb6f546 100644
--- a/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala
+++ b/core/src/main/scala/org/apache/spark/util/MetadataCleaner.scala
@@ -56,9 +56,10 @@ class MetadataCleaner(cleanerType: MetadataCleanerType.MetadataCleanerType, clea
}
object MetadataCleanerType extends Enumeration("MapOutputTracker", "SparkContext", "HttpBroadcast", "DagScheduler", "ResultTask",
- "ShuffleMapTask", "BlockManager", "BroadcastVars") {
+ "ShuffleMapTask", "BlockManager", "DiskBlockManager", "BroadcastVars") {
- val MAP_OUTPUT_TRACKER, SPARK_CONTEXT, HTTP_BROADCAST, DAG_SCHEDULER, RESULT_TASK, SHUFFLE_MAP_TASK, BLOCK_MANAGER, BROADCAST_VARS = Value
+ val MAP_OUTPUT_TRACKER, SPARK_CONTEXT, HTTP_BROADCAST, DAG_SCHEDULER, RESULT_TASK,
+ SHUFFLE_MAP_TASK, BLOCK_MANAGER, DISK_BLOCK_MANAGER, BROADCAST_VARS = Value
type MetadataCleanerType = Value
diff --git a/core/src/test/scala/org/apache/spark/MapOutputTrackerSuite.scala b/core/src/test/scala/org/apache/spark/MapOutputTrackerSuite.scala
index 6013320eaab730c202acce87de87714c99af65fb..b7eb268bd504c1d8ed9872c60e2394795ea50c56 100644
--- a/core/src/test/scala/org/apache/spark/MapOutputTrackerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/MapOutputTrackerSuite.scala
@@ -48,15 +48,15 @@ class MapOutputTrackerSuite extends FunSuite with LocalSparkContext {
test("master start and stop") {
val actorSystem = ActorSystem("test")
- val tracker = new MapOutputTracker()
- tracker.trackerActor = actorSystem.actorOf(Props(new MapOutputTrackerActor(tracker)))
+ val tracker = new MapOutputTrackerMaster()
+ tracker.trackerActor = actorSystem.actorOf(Props(new MapOutputTrackerMasterActor(tracker)))
tracker.stop()
}
test("master register and fetch") {
val actorSystem = ActorSystem("test")
- val tracker = new MapOutputTracker()
- tracker.trackerActor = actorSystem.actorOf(Props(new MapOutputTrackerActor(tracker)))
+ val tracker = new MapOutputTrackerMaster()
+ tracker.trackerActor = actorSystem.actorOf(Props(new MapOutputTrackerMasterActor(tracker)))
tracker.registerShuffle(10, 2)
val compressedSize1000 = MapOutputTracker.compressSize(1000L)
val compressedSize10000 = MapOutputTracker.compressSize(10000L)
@@ -74,19 +74,17 @@ class MapOutputTrackerSuite extends FunSuite with LocalSparkContext {
test("master register and unregister and fetch") {
val actorSystem = ActorSystem("test")
- val tracker = new MapOutputTracker()
- tracker.trackerActor = actorSystem.actorOf(Props(new MapOutputTrackerActor(tracker)))
+ val tracker = new MapOutputTrackerMaster()
+ tracker.trackerActor = actorSystem.actorOf(Props(new MapOutputTrackerMasterActor(tracker)))
tracker.registerShuffle(10, 2)
val compressedSize1000 = MapOutputTracker.compressSize(1000L)
val compressedSize10000 = MapOutputTracker.compressSize(10000L)
- val size1000 = MapOutputTracker.decompressSize(compressedSize1000)
- val size10000 = MapOutputTracker.decompressSize(compressedSize10000)
tracker.registerMapOutput(10, 0, new MapStatus(BlockManagerId("a", "hostA", 1000, 0),
Array(compressedSize1000, compressedSize1000, compressedSize1000)))
tracker.registerMapOutput(10, 1, new MapStatus(BlockManagerId("b", "hostB", 1000, 0),
Array(compressedSize10000, compressedSize1000, compressedSize1000)))
- // As if we had two simulatenous fetch failures
+ // As if we had two simultaneous fetch failures
tracker.unregisterMapOutput(10, 0, BlockManagerId("a", "hostA", 1000, 0))
tracker.unregisterMapOutput(10, 0, BlockManagerId("a", "hostA", 1000, 0))
@@ -102,9 +100,9 @@ class MapOutputTrackerSuite extends FunSuite with LocalSparkContext {
System.setProperty("spark.driver.port", boundPort.toString) // Will be cleared by LocalSparkContext
System.setProperty("spark.hostPort", hostname + ":" + boundPort)
- val masterTracker = new MapOutputTracker()
+ val masterTracker = new MapOutputTrackerMaster()
masterTracker.trackerActor = actorSystem.actorOf(
- Props(new MapOutputTrackerActor(masterTracker)), "MapOutputTracker")
+ Props(new MapOutputTrackerMasterActor(masterTracker)), "MapOutputTracker")
val (slaveSystem, _) = AkkaUtils.createActorSystem("spark-slave", hostname, 0)
val slaveTracker = new MapOutputTracker()
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 2a2f828be69676986a188a2a120305ba6a57a611..00f2fdd657bfc97561060e0167d8664a33827d93 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/DAGSchedulerSuite.scala
@@ -23,7 +23,7 @@ import org.scalatest.FunSuite
import org.scalatest.BeforeAndAfter
import org.apache.spark.LocalSparkContext
-import org.apache.spark.MapOutputTracker
+import org.apache.spark.MapOutputTrackerMaster
import org.apache.spark.SparkContext
import org.apache.spark.Partition
import org.apache.spark.TaskContext
@@ -64,7 +64,7 @@ class DAGSchedulerSuite extends FunSuite with BeforeAndAfter with LocalSparkCont
override def defaultParallelism() = 2
}
- var mapOutputTracker: MapOutputTracker = null
+ var mapOutputTracker: MapOutputTrackerMaster = null
var scheduler: DAGScheduler = null
/**
@@ -99,7 +99,7 @@ class DAGSchedulerSuite extends FunSuite with BeforeAndAfter with LocalSparkCont
taskSets.clear()
cacheLocations.clear()
results.clear()
- mapOutputTracker = new MapOutputTracker()
+ mapOutputTracker = new MapOutputTrackerMaster()
scheduler = new DAGScheduler(taskScheduler, mapOutputTracker, blockManagerMaster, null) {
override def runLocally(job: ActiveJob) {
// don't bother with the thread while unit testing
diff --git a/core/src/test/scala/org/apache/spark/scheduler/JobLoggerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/JobLoggerSuite.scala
index cece60dda726b30d49091cc7950e6d8fd39fa215..8406093246dac26994aecf2ee56f558a8faa2b51 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/JobLoggerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/JobLoggerSuite.scala
@@ -58,10 +58,13 @@ class JobLoggerSuite extends FunSuite with LocalSparkContext with ShouldMatchers
val parentRdd = makeRdd(4, Nil)
val shuffleDep = new ShuffleDependency(parentRdd, null)
val rootRdd = makeRdd(4, List(shuffleDep))
- val shuffleMapStage = new Stage(1, parentRdd, Some(shuffleDep), Nil, jobID, None)
- val rootStage = new Stage(0, rootRdd, None, List(shuffleMapStage), jobID, None)
-
- joblogger.onStageSubmitted(SparkListenerStageSubmitted(rootStage, 4, null))
+ val shuffleMapStage =
+ new Stage(1, parentRdd, parentRdd.partitions.size, Some(shuffleDep), Nil, jobID, None)
+ val rootStage =
+ new Stage(0, rootRdd, rootRdd.partitions.size, None, List(shuffleMapStage), jobID, None)
+ val rootStageInfo = new StageInfo(rootStage)
+
+ joblogger.onStageSubmitted(SparkListenerStageSubmitted(rootStageInfo, null))
joblogger.getRddNameTest(parentRdd) should be (parentRdd.getClass.getName)
parentRdd.setName("MyRDD")
joblogger.getRddNameTest(parentRdd) should be ("MyRDD")
diff --git a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
index b2fab254b2d9ed24e4a79482833e2c46b3dcb88f..c844dad6b656c6ca8b21c2a6c56feaf94b113520 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
@@ -19,17 +19,57 @@ package org.apache.spark.scheduler
import scala.collection.mutable.{Buffer, HashSet}
-import org.scalatest.FunSuite
+import org.scalatest.{BeforeAndAfter, FunSuite}
import org.scalatest.matchers.ShouldMatchers
-import org.apache.spark.{SparkContext, LocalSparkContext}
+import org.apache.spark.{LocalSparkContext, SparkContext}
import org.apache.spark.SparkContext._
-class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatchers {
+class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatchers
+ with BeforeAndAfter {
+ /** Length of time to wait while draining listener events. */
val WAIT_TIMEOUT_MILLIS = 10000
+ before {
+ sc = new SparkContext("local", "DAGSchedulerSuite")
+ }
+
+ test("basic creation of StageInfo") {
+ val listener = new SaveStageInfo
+ sc.addSparkListener(listener)
+ val rdd1 = sc.parallelize(1 to 100, 4)
+ val rdd2 = rdd1.map(x => x.toString)
+ rdd2.setName("Target RDD")
+ rdd2.count
+
+ assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
+
+ listener.stageInfos.size should be {1}
+ val first = listener.stageInfos.head
+ first.rddName should be {"Target RDD"}
+ first.numTasks should be {4}
+ first.numPartitions should be {4}
+ first.submissionTime should be ('defined)
+ first.completionTime should be ('defined)
+ first.taskInfos.length should be {4}
+ }
+
+ test("StageInfo with fewer tasks than partitions") {
+ val listener = new SaveStageInfo
+ sc.addSparkListener(listener)
+ val rdd1 = sc.parallelize(1 to 100, 4)
+ val rdd2 = rdd1.map(x => x.toString)
+ sc.runJob(rdd2, (items: Iterator[String]) => items.size, Seq(0, 1), true)
+
+ assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
+
+ listener.stageInfos.size should be {1}
+ val first = listener.stageInfos.head
+ first.numTasks should be {2}
+ first.numPartitions should be {4}
+ }
+
test("local metrics") {
- sc = new SparkContext("local[4]", "test")
val listener = new SaveStageInfo
sc.addSparkListener(listener)
sc.addSparkListener(new StatsReportListener)
@@ -66,7 +106,7 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatc
checkNonZeroAvg(
stageInfo.taskInfos.map{_._2.executorDeserializeTime.toLong},
stageInfo + " executorDeserializeTime")
- if (stageInfo.stage.rdd.name == d4.name) {
+ if (stageInfo.rddName == d4.name) {
checkNonZeroAvg(
stageInfo.taskInfos.map{_._2.shuffleReadMetrics.get.fetchWaitTime},
stageInfo + " fetchWaitTime")
@@ -74,11 +114,11 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatc
stageInfo.taskInfos.foreach { case (taskInfo, taskMetrics) =>
taskMetrics.resultSize should be > (0l)
- if (isStage(stageInfo, Set(d2.name, d3.name), Set(d4.name))) {
+ if (stageInfo.rddName == d2.name || stageInfo.rddName == d3.name) {
taskMetrics.shuffleWriteMetrics should be ('defined)
taskMetrics.shuffleWriteMetrics.get.shuffleBytesWritten should be > (0l)
}
- if (stageInfo.stage.rdd.name == d4.name) {
+ if (stageInfo.rddName == d4.name) {
taskMetrics.shuffleReadMetrics should be ('defined)
val sm = taskMetrics.shuffleReadMetrics.get
sm.totalBlocksFetched should be > (0)
@@ -136,15 +176,10 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatc
assert(m.sum / m.size.toDouble > 0.0, msg)
}
- def isStage(stageInfo: StageInfo, rddNames: Set[String], excludedNames: Set[String]) = {
- val names = Set(stageInfo.stage.rdd.name) ++ stageInfo.stage.rdd.dependencies.map{_.rdd.name}
- !names.intersect(rddNames).isEmpty && names.intersect(excludedNames).isEmpty
- }
-
class SaveStageInfo extends SparkListener {
val stageInfos = Buffer[StageInfo]()
override def onStageCompleted(stage: StageCompleted) {
- stageInfos += stage.stageInfo
+ stageInfos += stage.stage
}
}
diff --git a/docs/python-programming-guide.md b/docs/python-programming-guide.md
index 6c2336ad0c233c36cbe1563cca90f2bfbb6dbb39..55e39b1de17a06c4c4a9e025769c66b0977cffb8 100644
--- a/docs/python-programming-guide.md
+++ b/docs/python-programming-guide.md
@@ -131,6 +131,17 @@ sc = SparkContext("local", "App Name", pyFiles=['MyFile.py', 'lib.zip', 'app.egg
Files listed here will be added to the `PYTHONPATH` and shipped to remote worker machines.
Code dependencies can be added to an existing SparkContext using its `addPyFile()` method.
+You can set [system properties](configuration.html#system-properties)
+using `SparkContext.setSystemProperty()` class method *before*
+instantiating SparkContext. For example, to set the amount of memory
+per executor process:
+
+{% highlight python %}
+from pyspark import SparkContext
+SparkContext.setSystemProperty('spark.executor.memory', '2g')
+sc = SparkContext("local", "App Name")
+{% endhighlight %}
+
# API Docs
[API documentation](api/pyspark/index.html) for PySpark is available as Epydoc.
diff --git a/docs/scala-programming-guide.md b/docs/scala-programming-guide.md
index 03647a2ad26cbfb729d56a082590d388e5e25d0e..94e8563a8b69321bdd8e9922e06580a267229df0 100644
--- a/docs/scala-programming-guide.md
+++ b/docs/scala-programming-guide.md
@@ -142,7 +142,7 @@ All transformations in Spark are <i>lazy</i>, in that they do not compute their
By default, each transformed RDD is recomputed each time you run an action on it. However, you may also *persist* an RDD in memory using the `persist` (or `cache`) method, in which case Spark will keep the elements around on the cluster for much faster access the next time you query it. There is also support for persisting datasets on disk, or replicated across the cluster. The next section in this document describes these options.
-The following tables list the transformations and actions currently supported (see also the [RDD API doc](api/core/index.html#org.apache.spark.RDD) for details):
+The following tables list the transformations and actions currently supported (see also the [RDD API doc](api/core/index.html#org.apache.spark.rdd.RDD) for details):
### Transformations
@@ -211,7 +211,7 @@ The following tables list the transformations and actions currently supported (s
</tr>
</table>
-A complete list of transformations is available in the [RDD API doc](api/core/index.html#org.apache.spark.RDD).
+A complete list of transformations is available in the [RDD API doc](api/core/index.html#org.apache.spark.rdd.RDD).
### Actions
@@ -259,7 +259,7 @@ A complete list of transformations is available in the [RDD API doc](api/core/in
</tr>
</table>
-A complete list of actions is available in the [RDD API doc](api/core/index.html#org.apache.spark.RDD).
+A complete list of actions is available in the [RDD API doc](api/core/index.html#org.apache.spark.rdd.RDD).
## RDD Persistence
diff --git a/examples/pom.xml b/examples/pom.xml
index 15399a8a334273914348e2cafcc54c9764592654..aee371fbc7d1ae89ab427c55e8be32de1479f7c3 100644
--- a/examples/pom.xml
+++ b/examples/pom.xml
@@ -32,13 +32,20 @@
<url>http://spark.incubator.apache.org/</url>
<repositories>
- <!-- A repository in the local filesystem for the Kafka JAR, which we modified for Scala 2.9 -->
<repository>
- <id>lib</id>
- <url>file://${project.basedir}/lib</url>
+ <id>apache-repo</id>
+ <name>Apache Repository</name>
+ <url>https://repository.apache.org/content/repositories/releases</url>
+ <releases>
+ <enabled>true</enabled>
+ </releases>
+ <snapshots>
+ <enabled>false</enabled>
+ </snapshots>
</repository>
</repositories>
+
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
@@ -81,9 +88,18 @@
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
- <artifactId>kafka</artifactId>
- <version>0.7.2-spark</version> <!-- Comes from our in-project repository -->
- <scope>provided</scope>
+ <artifactId>kafka_2.9.2</artifactId>
+ <version>0.8.0-beta1</version>
+ <exclusions>
+ <exclusion>
+ <groupId>com.sun.jmx</groupId>
+ <artifactId>jmxri</artifactId>
+ </exclusion>
+ <exclusion>
+ <groupId>com.sun.jdmk</groupId>
+ <artifactId>jmxtools</artifactId>
+ </exclusion>
+ </exclusions>
</dependency>
<dependency>
<groupId>org.eclipse.jetty</groupId>
diff --git a/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java b/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java
new file mode 100644
index 0000000000000000000000000000000000000000..9a8e4209eddc7da8d87401dafe81b46f3456065a
--- /dev/null
+++ b/examples/src/main/java/org/apache/spark/streaming/examples/JavaKafkaWordCount.java
@@ -0,0 +1,98 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.examples;
+
+import java.util.Map;
+import java.util.HashMap;
+
+import com.google.common.collect.Lists;
+import org.apache.spark.api.java.function.FlatMapFunction;
+import org.apache.spark.api.java.function.Function;
+import org.apache.spark.api.java.function.Function2;
+import org.apache.spark.api.java.function.PairFunction;
+import org.apache.spark.streaming.Duration;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaPairDStream;
+import org.apache.spark.streaming.api.java.JavaStreamingContext;
+import scala.Tuple2;
+
+/**
+ * Consumes messages from one or more topics in Kafka and does wordcount.
+ * Usage: JavaKafkaWordCount <master> <zkQuorum> <group> <topics> <numThreads>
+ * <master> is the Spark master URL. In local mode, <master> should be 'local[n]' with n > 1.
+ * <zkQuorum> is a list of one or more zookeeper servers that make quorum
+ * <group> is the name of kafka consumer group
+ * <topics> is a list of one or more kafka topics to consume from
+ * <numThreads> is the number of threads the kafka consumer should use
+ *
+ * Example:
+ * `./run-example org.apache.spark.streaming.examples.JavaKafkaWordCount local[2] zoo01,zoo02,
+ * zoo03 my-consumer-group topic1,topic2 1`
+ */
+
+public class JavaKafkaWordCount {
+ public static void main(String[] args) {
+ if (args.length < 5) {
+ System.err.println("Usage: KafkaWordCount <master> <zkQuorum> <group> <topics> <numThreads>");
+ System.exit(1);
+ }
+
+ // Create the context with a 1 second batch size
+ JavaStreamingContext ssc = new JavaStreamingContext(args[0], "NetworkWordCount",
+ new Duration(2000), System.getenv("SPARK_HOME"), System.getenv("SPARK_EXAMPLES_JAR"));
+
+ int numThreads = Integer.parseInt(args[4]);
+ Map<String, Integer> topicMap = new HashMap<String, Integer>();
+ String[] topics = args[3].split(",");
+ for (String topic: topics) {
+ topicMap.put(topic, numThreads);
+ }
+
+ JavaPairDStream<String, String> messages = ssc.kafkaStream(args[1], args[2], topicMap);
+
+ JavaDStream<String> lines = messages.map(new Function<Tuple2<String, String>, String>() {
+ @Override
+ public String call(Tuple2<String, String> tuple2) throws Exception {
+ return tuple2._2();
+ }
+ });
+
+ JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
+ @Override
+ public Iterable<String> call(String x) {
+ return Lists.newArrayList(x.split(" "));
+ }
+ });
+
+ JavaPairDStream<String, Integer> wordCounts = words.map(
+ new PairFunction<String, String, Integer>() {
+ @Override
+ public Tuple2<String, Integer> call(String s) throws Exception {
+ return new Tuple2<String, Integer>(s, 1);
+ }
+ }).reduceByKey(new Function2<Integer, Integer, Integer>() {
+ @Override
+ public Integer call(Integer i1, Integer i2) throws Exception {
+ return i1 + i2;
+ }
+ });
+
+ wordCounts.print();
+ ssc.start();
+ }
+}
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala b/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala
index 12f939d5a7e4b529c05c8dfe77d67e8c3f254b40..570ba4c81a1d2c3cc00144727f04bc8a45dc071f 100644
--- a/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala
+++ b/examples/src/main/scala/org/apache/spark/streaming/examples/KafkaWordCount.scala
@@ -18,13 +18,11 @@
package org.apache.spark.streaming.examples
import java.util.Properties
-import kafka.message.Message
-import kafka.producer.SyncProducerConfig
+
import kafka.producer._
-import org.apache.spark.SparkContext
+
import org.apache.spark.streaming._
import org.apache.spark.streaming.StreamingContext._
-import org.apache.spark.storage.StorageLevel
import org.apache.spark.streaming.util.RawTextHelper._
/**
@@ -54,9 +52,10 @@ object KafkaWordCount {
ssc.checkpoint("checkpoint")
val topicpMap = topics.split(",").map((_,numThreads.toInt)).toMap
- val lines = ssc.kafkaStream(zkQuorum, group, topicpMap)
+ val lines = ssc.kafkaStream(zkQuorum, group, topicpMap).map(_._2)
val words = lines.flatMap(_.split(" "))
- val wordCounts = words.map(x => (x, 1l)).reduceByKeyAndWindow(add _, subtract _, Minutes(10), Seconds(2), 2)
+ val wordCounts = words.map(x => (x, 1l))
+ .reduceByKeyAndWindow(add _, subtract _, Minutes(10), Seconds(2), 2)
wordCounts.print()
ssc.start()
@@ -68,15 +67,16 @@ object KafkaWordCountProducer {
def main(args: Array[String]) {
if (args.length < 2) {
- System.err.println("Usage: KafkaWordCountProducer <zkQuorum> <topic> <messagesPerSec> <wordsPerMessage>")
+ System.err.println("Usage: KafkaWordCountProducer <metadataBrokerList> <topic> " +
+ "<messagesPerSec> <wordsPerMessage>")
System.exit(1)
}
- val Array(zkQuorum, topic, messagesPerSec, wordsPerMessage) = args
+ val Array(brokers, topic, messagesPerSec, wordsPerMessage) = args
// Zookeper connection properties
val props = new Properties()
- props.put("zk.connect", zkQuorum)
+ props.put("metadata.broker.list", brokers)
props.put("serializer.class", "kafka.serializer.StringEncoder")
val config = new ProducerConfig(props)
@@ -85,11 +85,13 @@ object KafkaWordCountProducer {
// Send some messages
while(true) {
val messages = (1 to messagesPerSec.toInt).map { messageNum =>
- (1 to wordsPerMessage.toInt).map(x => scala.util.Random.nextInt(10).toString).mkString(" ")
+ val str = (1 to wordsPerMessage.toInt).map(x => scala.util.Random.nextInt(10).toString)
+ .mkString(" ")
+
+ new KeyedMessage[String, String](topic, str)
}.toArray
- println(messages.mkString(","))
- val data = new ProducerData[String, String](topic, messages)
- producer.send(data)
+
+ producer.send(messages: _*)
Thread.sleep(100)
}
}
diff --git a/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala b/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala
new file mode 100644
index 0000000000000000000000000000000000000000..af698a01d511871472751f1fdb779e808cb4d6ab
--- /dev/null
+++ b/examples/src/main/scala/org/apache/spark/streaming/examples/MQTTWordCount.scala
@@ -0,0 +1,107 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.examples
+
+import org.apache.spark.streaming.{ Seconds, StreamingContext }
+import org.apache.spark.streaming.StreamingContext._
+import org.apache.spark.streaming.dstream.MQTTReceiver
+import org.apache.spark.storage.StorageLevel
+
+import org.eclipse.paho.client.mqttv3.MqttClient
+import org.eclipse.paho.client.mqttv3.MqttClientPersistence
+import org.eclipse.paho.client.mqttv3.persist.MqttDefaultFilePersistence
+import org.eclipse.paho.client.mqttv3.MqttException
+import org.eclipse.paho.client.mqttv3.MqttMessage
+import org.eclipse.paho.client.mqttv3.MqttTopic
+
+/**
+ * A simple Mqtt publisher for demonstration purposes, repeatedly publishes
+ * Space separated String Message "hello mqtt demo for spark streaming"
+ */
+object MQTTPublisher {
+
+ var client: MqttClient = _
+
+ def main(args: Array[String]) {
+ if (args.length < 2) {
+ System.err.println("Usage: MQTTPublisher <MqttBrokerUrl> <topic>")
+ System.exit(1)
+ }
+
+ val Seq(brokerUrl, topic) = args.toSeq
+
+ try {
+ var peristance:MqttClientPersistence =new MqttDefaultFilePersistence("/tmp")
+ client = new MqttClient(brokerUrl, MqttClient.generateClientId(), peristance)
+ } catch {
+ case e: MqttException => println("Exception Caught: " + e)
+ }
+
+ client.connect()
+
+ val msgtopic: MqttTopic = client.getTopic(topic);
+ val msg: String = "hello mqtt demo for spark streaming"
+
+ while (true) {
+ val message: MqttMessage = new MqttMessage(String.valueOf(msg).getBytes())
+ msgtopic.publish(message);
+ println("Published data. topic: " + msgtopic.getName() + " Message: " + message)
+ }
+ client.disconnect()
+ }
+}
+
+/**
+ * A sample wordcount with MqttStream stream
+ *
+ * To work with Mqtt, Mqtt Message broker/server required.
+ * Mosquitto (http://mosquitto.org/) is an open source Mqtt Broker
+ * In ubuntu mosquitto can be installed using the command `$ sudo apt-get install mosquitto`
+ * Eclipse paho project provides Java library for Mqtt Client http://www.eclipse.org/paho/
+ * Example Java code for Mqtt Publisher and Subscriber can be found here https://bitbucket.org/mkjinesh/mqttclient
+ * Usage: MQTTWordCount <master> <MqttbrokerUrl> <topic>
+ * In local mode, <master> should be 'local[n]' with n > 1
+ * <MqttbrokerUrl> and <topic> describe where Mqtt publisher is running.
+ *
+ * To run this example locally, you may run publisher as
+ * `$ ./run-example org.apache.spark.streaming.examples.MQTTPublisher tcp://localhost:1883 foo`
+ * and run the example as
+ * `$ ./run-example org.apache.spark.streaming.examples.MQTTWordCount local[2] tcp://localhost:1883 foo`
+ */
+object MQTTWordCount {
+
+ def main(args: Array[String]) {
+ if (args.length < 3) {
+ System.err.println(
+ "Usage: MQTTWordCount <master> <MqttbrokerUrl> <topic>" +
+ " In local mode, <master> should be 'local[n]' with n > 1")
+ System.exit(1)
+ }
+
+ val Seq(master, brokerUrl, topic) = args.toSeq
+
+ val ssc = new StreamingContext(master, "MqttWordCount", Seconds(2), System.getenv("SPARK_HOME"),
+ Seq(System.getenv("SPARK_EXAMPLES_JAR")))
+ val lines = ssc.mqttStream(brokerUrl, topic, StorageLevel.MEMORY_ONLY)
+
+ val words = lines.flatMap(x => x.toString.split(" "))
+ val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)
+ wordCounts.print()
+ ssc.start()
+ }
+}
diff --git a/project/SparkBuild.scala b/project/SparkBuild.scala
index 965c4f3a635d093bd9df1c90c3ea84fef737c3e4..20f2c018faaf640ad0a194866326f58b2b0cd453 100644
--- a/project/SparkBuild.scala
+++ b/project/SparkBuild.scala
@@ -108,7 +108,10 @@ object SparkBuild extends Build {
// Shared between both core and streaming.
resolvers ++= Seq("Akka Repository" at "http://repo.akka.io/releases/"),
- // For Sonatype publishing
+ // Shared between both examples and streaming.
+ resolvers ++= Seq("Mqtt Repository" at "https://repo.eclipse.org/content/repositories/paho-releases/"),
+
+ // For Sonatype publishing
resolvers ++= Seq("sonatype-snapshots" at "https://oss.sonatype.org/content/repositories/snapshots",
"sonatype-staging" at "https://oss.sonatype.org/service/local/staging/deploy/maven2/"),
@@ -278,13 +281,17 @@ object SparkBuild extends Build {
def streamingSettings = sharedSettings ++ Seq(
name := "spark-streaming",
resolvers ++= Seq(
- "Akka Repository" at "http://repo.akka.io/releases/"
+ "Akka Repository" at "http://repo.akka.io/releases/",
+ "Apache repo" at "https://repository.apache.org/content/repositories/releases"
),
libraryDependencies ++= Seq(
+ "org.eclipse.paho" % "mqtt-client" % "0.4.0",
"org.apache.flume" % "flume-ng-sdk" % "1.2.0" % "compile" excludeAll(excludeNetty, excludeSnappy),
- "com.github.sgroschupf" % "zkclient" % "0.1" excludeAll(excludeNetty),
"org.twitter4j" % "twitter4j-stream" % "3.0.3" excludeAll(excludeNetty),
- "com.typesafe.akka" % "akka-zeromq" % "2.0.5" excludeAll(excludeNetty)
+ "com.typesafe.akka" % "akka-zeromq" % "2.0.5" excludeAll(excludeNetty),
+ "org.apache.kafka" % "kafka_2.9.2" % "0.8.0-beta1"
+ exclude("com.sun.jdmk", "jmxtools")
+ exclude("com.sun.jmx", "jmxri")
)
)
diff --git a/python/pyspark/context.py b/python/pyspark/context.py
index 597110321a86370c29063052eb892f9213a4bfb3..a7ca8bc888c6759aff5784d26ad7df015d2fe2f4 100644
--- a/python/pyspark/context.py
+++ b/python/pyspark/context.py
@@ -49,6 +49,7 @@ class SparkContext(object):
_lock = Lock()
_python_includes = None # zip and egg files that need to be added to PYTHONPATH
+
def __init__(self, master, jobName, sparkHome=None, pyFiles=None,
environment=None, batchSize=1024):
"""
@@ -66,19 +67,18 @@ class SparkContext(object):
@param batchSize: The number of Python objects represented as a single
Java object. Set 1 to disable batching or -1 to use an
unlimited batch size.
+
+
+ >>> from pyspark.context import SparkContext
+ >>> sc = SparkContext('local', 'test')
+
+ >>> sc2 = SparkContext('local', 'test2') # doctest: +IGNORE_EXCEPTION_DETAIL
+ Traceback (most recent call last):
+ ...
+ ValueError:...
"""
- with SparkContext._lock:
- if SparkContext._active_spark_context:
- raise ValueError("Cannot run multiple SparkContexts at once")
- else:
- SparkContext._active_spark_context = self
- if not SparkContext._gateway:
- SparkContext._gateway = launch_gateway()
- SparkContext._jvm = SparkContext._gateway.jvm
- SparkContext._writeIteratorToPickleFile = \
- SparkContext._jvm.PythonRDD.writeIteratorToPickleFile
- SparkContext._takePartition = \
- SparkContext._jvm.PythonRDD.takePartition
+ SparkContext._ensure_initialized(self)
+
self.master = master
self.jobName = jobName
self.sparkHome = sparkHome or None # None becomes null in Py4J
@@ -119,6 +119,32 @@ class SparkContext(object):
self._temp_dir = \
self._jvm.org.apache.spark.util.Utils.createTempDir(local_dir).getAbsolutePath()
+ @classmethod
+ def _ensure_initialized(cls, instance=None):
+ with SparkContext._lock:
+ if not SparkContext._gateway:
+ SparkContext._gateway = launch_gateway()
+ SparkContext._jvm = SparkContext._gateway.jvm
+ SparkContext._writeIteratorToPickleFile = \
+ SparkContext._jvm.PythonRDD.writeIteratorToPickleFile
+ SparkContext._takePartition = \
+ SparkContext._jvm.PythonRDD.takePartition
+
+ if instance:
+ if SparkContext._active_spark_context and SparkContext._active_spark_context != instance:
+ raise ValueError("Cannot run multiple SparkContexts at once")
+ else:
+ SparkContext._active_spark_context = instance
+
+ @classmethod
+ def setSystemProperty(cls, key, value):
+ """
+ Set a system property, such as spark.executor.memory. This must be
+ invoked before instantiating SparkContext.
+ """
+ SparkContext._ensure_initialized()
+ SparkContext._jvm.java.lang.System.setProperty(key, value)
+
@property
def defaultParallelism(self):
"""
diff --git a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar b/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar
deleted file mode 100644
index 65f79925a4d06a41b7b98d7e6f92fedb408c9b3a..0000000000000000000000000000000000000000
Binary files a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar and /dev/null differ
diff --git a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar.md5 b/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar.md5
deleted file mode 100644
index 29f45f4adb6975e36cb95ee2f50de53ef76b0c5b..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar.md5
+++ /dev/null
@@ -1 +0,0 @@
-18876b8bc2e4cef28b6d191aa49d963f
\ No newline at end of file
diff --git a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar.sha1 b/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar.sha1
deleted file mode 100644
index e3bd62bac038f6e56f7bbaf554a544f441dfbbaa..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.jar.sha1
+++ /dev/null
@@ -1 +0,0 @@
-06b27270ffa52250a2c08703b397c99127b72060
\ No newline at end of file
diff --git a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom b/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom
deleted file mode 100644
index 082d35726a5afe5edb882bc4caac7bc6a7aafdc0..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom
+++ /dev/null
@@ -1,9 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd" xmlns="http://maven.apache.org/POM/4.0.0"
- xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
- <modelVersion>4.0.0</modelVersion>
- <groupId>org.apache.kafka</groupId>
- <artifactId>kafka</artifactId>
- <version>0.7.2-spark</version>
- <description>POM was created from install:install-file</description>
-</project>
diff --git a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom.md5 b/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom.md5
deleted file mode 100644
index 92c4132b5b01c48b0e17458876a7beeeed3e3084..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom.md5
+++ /dev/null
@@ -1 +0,0 @@
-7bc4322266e6032bdf9ef6eebdd8097d
\ No newline at end of file
diff --git a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom.sha1 b/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom.sha1
deleted file mode 100644
index 8a1d8a097a113cf674588322a978235f73c0d7f4..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/0.7.2-spark/kafka-0.7.2-spark.pom.sha1
+++ /dev/null
@@ -1 +0,0 @@
-d0f79e8eff0db43ca7bcf7dce2c8cd2972685c9d
\ No newline at end of file
diff --git a/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml b/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml
deleted file mode 100644
index 720cd51c2f5e6408a63eae37c92f52210de58d55..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml
+++ /dev/null
@@ -1,12 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<metadata>
- <groupId>org.apache.kafka</groupId>
- <artifactId>kafka</artifactId>
- <versioning>
- <release>0.7.2-spark</release>
- <versions>
- <version>0.7.2-spark</version>
- </versions>
- <lastUpdated>20130121015225</lastUpdated>
- </versioning>
-</metadata>
diff --git a/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml.md5 b/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml.md5
deleted file mode 100644
index a4ce5dc9e8d9b21320106941f0f8b36c3e2b6485..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml.md5
+++ /dev/null
@@ -1 +0,0 @@
-e2b9c7c5f6370dd1d21a0aae5e8dcd77
\ No newline at end of file
diff --git a/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml.sha1 b/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml.sha1
deleted file mode 100644
index b869eaf2a61de2fbaa3f75c2e6c9df874ac92a5e..0000000000000000000000000000000000000000
--- a/streaming/lib/org/apache/kafka/kafka/maven-metadata-local.xml.sha1
+++ /dev/null
@@ -1 +0,0 @@
-2a4341da936b6c07a09383d17ffb185ac558ee91
\ No newline at end of file
diff --git a/streaming/pom.xml b/streaming/pom.xml
index bcbed1644a4003a4cf06bacd6125b0c0cc6e758e..8022c4fe18917a1a671ceed7d779c2bd54ae6705 100644
--- a/streaming/pom.xml
+++ b/streaming/pom.xml
@@ -32,10 +32,16 @@
<url>http://spark.incubator.apache.org/</url>
<repositories>
- <!-- A repository in the local filesystem for the Kafka JAR, which we modified for Scala 2.9 -->
<repository>
- <id>lib</id>
- <url>file://${project.basedir}/lib</url>
+ <id>apache-repo</id>
+ <name>Apache Repository</name>
+ <url>https://repository.apache.org/content/repositories/releases</url>
+ <releases>
+ <enabled>true</enabled>
+ </releases>
+ <snapshots>
+ <enabled>false</enabled>
+ </snapshots>
</repository>
</repositories>
@@ -56,9 +62,18 @@
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
- <artifactId>kafka</artifactId>
- <version>0.7.2-spark</version> <!-- Comes from our in-project repository -->
- <scope>provided</scope>
+ <artifactId>kafka_2.9.2</artifactId>
+ <version>0.8.0-beta1</version>
+ <exclusions>
+ <exclusion>
+ <groupId>com.sun.jmx</groupId>
+ <artifactId>jmxri</artifactId>
+ </exclusion>
+ <exclusion>
+ <groupId>com.sun.jdmk</groupId>
+ <artifactId>jmxtools</artifactId>
+ </exclusion>
+ </exclusions>
</dependency>
<dependency>
<groupId>org.apache.flume</groupId>
@@ -75,17 +90,6 @@
</exclusion>
</exclusions>
</dependency>
- <dependency>
- <groupId>com.github.sgroschupf</groupId>
- <artifactId>zkclient</artifactId>
- <version>0.1</version>
- <exclusions>
- <exclusion>
- <groupId>org.jboss.netty</groupId>
- <artifactId>netty</artifactId>
- </exclusion>
- </exclusions>
- </dependency>
<dependency>
<groupId>org.twitter4j</groupId>
<artifactId>twitter4j-stream</artifactId>
@@ -132,6 +136,11 @@
<artifactId>slf4j-log4j12</artifactId>
<scope>test</scope>
</dependency>
+ <dependency>
+ <groupId>org.eclipse.paho</groupId>
+ <artifactId>mqtt-client</artifactId>
+ <version>0.4.0</version>
+ </dependency>
</dependencies>
<build>
<outputDirectory>target/scala-${scala.version}/classes</outputDirectory>
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
index 098081d245605d2113bc027057a053dbbed4a365..09c2f7fd8e624b808792aeac39b3c8eb2c05ce48 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/StreamingContext.scala
@@ -256,10 +256,14 @@ class StreamingContext private (
groupId: String,
topics: Map[String, Int],
storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY_SER_2
- ): DStream[String] = {
+ ): DStream[(String, String)] = {
val kafkaParams = Map[String, String](
- "zk.connect" -> zkQuorum, "groupid" -> groupId, "zk.connectiontimeout.ms" -> "10000")
- kafkaStream[String, kafka.serializer.StringDecoder](kafkaParams, topics, storageLevel)
+ "zookeeper.connect" -> zkQuorum, "group.id" -> groupId,
+ "zookeeper.connection.timeout.ms" -> "10000")
+ kafkaStream[String, String, kafka.serializer.StringDecoder, kafka.serializer.StringDecoder](
+ kafkaParams,
+ topics,
+ storageLevel)
}
/**
@@ -270,12 +274,16 @@ class StreamingContext private (
* in its own thread.
* @param storageLevel Storage level to use for storing the received objects
*/
- def kafkaStream[T: ClassManifest, D <: kafka.serializer.Decoder[_]: Manifest](
+ def kafkaStream[
+ K: ClassManifest,
+ V: ClassManifest,
+ U <: kafka.serializer.Decoder[_]: Manifest,
+ T <: kafka.serializer.Decoder[_]: Manifest](
kafkaParams: Map[String, String],
topics: Map[String, Int],
storageLevel: StorageLevel
- ): DStream[T] = {
- val inputStream = new KafkaInputDStream[T, D](this, kafkaParams, topics, storageLevel)
+ ): DStream[(K, V)] = {
+ val inputStream = new KafkaInputDStream[K, V, U, T](this, kafkaParams, topics, storageLevel)
registerInputStream(inputStream)
inputStream
}
@@ -454,6 +462,21 @@ class StreamingContext private (
inputStream
}
+/**
+ * Create an input stream that receives messages pushed by a mqtt publisher.
+ * @param brokerUrl Url of remote mqtt publisher
+ * @param topic topic name to subscribe to
+ * @param storageLevel RDD storage level. Defaults to memory-only.
+ */
+
+ def mqttStream(
+ brokerUrl: String,
+ topic: String,
+ storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY_SER_2): DStream[String] = {
+ val inputStream = new MQTTInputDStream[String](this, brokerUrl, topic, storageLevel)
+ registerInputStream(inputStream)
+ inputStream
+ }
/**
* Create a unified DStream from multiple DStreams of the same type and same interval
*/
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala
index 54ba3e602590f806906f75f45ec6df22bde66da3..6423b916b0ac48abaceafa7a874c8d1ff5295f6a 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/api/java/JavaStreamingContext.scala
@@ -141,7 +141,7 @@ class JavaStreamingContext(val ssc: StreamingContext) {
zkQuorum: String,
groupId: String,
topics: JMap[String, JInt])
- : JavaDStream[String] = {
+ : JavaPairDStream[String, String] = {
implicit val cmt: ClassManifest[String] =
implicitly[ClassManifest[AnyRef]].asInstanceOf[ClassManifest[String]]
ssc.kafkaStream(zkQuorum, groupId, Map(topics.mapValues(_.intValue()).toSeq: _*),
@@ -162,7 +162,7 @@ class JavaStreamingContext(val ssc: StreamingContext) {
groupId: String,
topics: JMap[String, JInt],
storageLevel: StorageLevel)
- : JavaDStream[String] = {
+ : JavaPairDStream[String, String] = {
implicit val cmt: ClassManifest[String] =
implicitly[ClassManifest[AnyRef]].asInstanceOf[ClassManifest[String]]
ssc.kafkaStream(zkQuorum, groupId, Map(topics.mapValues(_.intValue()).toSeq: _*),
@@ -171,25 +171,34 @@ class JavaStreamingContext(val ssc: StreamingContext) {
/**
* Create an input stream that pulls messages form a Kafka Broker.
- * @param typeClass Type of RDD
- * @param decoderClass Type of kafka decoder
+ * @param keyTypeClass Key type of RDD
+ * @param valueTypeClass value type of RDD
+ * @param keyDecoderClass Type of kafka key decoder
+ * @param valueDecoderClass Type of kafka value decoder
* @param kafkaParams Map of kafka configuration paramaters.
* See: http://kafka.apache.org/configuration.html
* @param topics Map of (topic_name -> numPartitions) to consume. Each partition is consumed
* in its own thread.
* @param storageLevel RDD storage level. Defaults to memory-only
*/
- def kafkaStream[T, D <: kafka.serializer.Decoder[_]](
- typeClass: Class[T],
- decoderClass: Class[D],
+ def kafkaStream[K, V, U <: kafka.serializer.Decoder[_], T <: kafka.serializer.Decoder[_]](
+ keyTypeClass: Class[K],
+ valueTypeClass: Class[V],
+ keyDecoderClass: Class[U],
+ valueDecoderClass: Class[T],
kafkaParams: JMap[String, String],
topics: JMap[String, JInt],
storageLevel: StorageLevel)
- : JavaDStream[T] = {
- implicit val cmt: ClassManifest[T] =
- implicitly[ClassManifest[AnyRef]].asInstanceOf[ClassManifest[T]]
- implicit val cmd: Manifest[D] = implicitly[Manifest[AnyRef]].asInstanceOf[Manifest[D]]
- ssc.kafkaStream[T, D](
+ : JavaPairDStream[K, V] = {
+ implicit val keyCmt: ClassManifest[K] =
+ implicitly[ClassManifest[AnyRef]].asInstanceOf[ClassManifest[K]]
+ implicit val valueCmt: ClassManifest[V] =
+ implicitly[ClassManifest[AnyRef]].asInstanceOf[ClassManifest[V]]
+
+ implicit val keyCmd: Manifest[U] = implicitly[Manifest[AnyRef]].asInstanceOf[Manifest[U]]
+ implicit val valueCmd: Manifest[T] = implicitly[Manifest[AnyRef]].asInstanceOf[Manifest[T]]
+
+ ssc.kafkaStream[K, V, U, T](
kafkaParams.toMap,
Map(topics.mapValues(_.intValue()).toSeq: _*),
storageLevel)
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/KafkaInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/KafkaInputDStream.scala
index 51e913675d24acbfd04534e6d94ed2edc2cdc4af..a5de5e1fb549c9e5ee6c75adb203200ffbdea09a 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/KafkaInputDStream.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/KafkaInputDStream.scala
@@ -19,22 +19,18 @@ package org.apache.spark.streaming.dstream
import org.apache.spark.Logging
import org.apache.spark.storage.StorageLevel
-import org.apache.spark.streaming.{Time, DStreamCheckpointData, StreamingContext}
+import org.apache.spark.streaming.StreamingContext
import java.util.Properties
import java.util.concurrent.Executors
import kafka.consumer._
-import kafka.message.{Message, MessageSet, MessageAndMetadata}
import kafka.serializer.Decoder
-import kafka.utils.{Utils, ZKGroupTopicDirs}
-import kafka.utils.ZkUtils._
+import kafka.utils.VerifiableProperties
import kafka.utils.ZKStringSerializer
import org.I0Itec.zkclient._
import scala.collection.Map
-import scala.collection.mutable.HashMap
-import scala.collection.JavaConversions._
/**
@@ -46,25 +42,32 @@ import scala.collection.JavaConversions._
* @param storageLevel RDD storage level.
*/
private[streaming]
-class KafkaInputDStream[T: ClassManifest, D <: Decoder[_]: Manifest](
+class KafkaInputDStream[
+ K: ClassManifest,
+ V: ClassManifest,
+ U <: Decoder[_]: Manifest,
+ T <: Decoder[_]: Manifest](
@transient ssc_ : StreamingContext,
kafkaParams: Map[String, String],
topics: Map[String, Int],
storageLevel: StorageLevel
- ) extends NetworkInputDStream[T](ssc_ ) with Logging {
+ ) extends NetworkInputDStream[(K, V)](ssc_) with Logging {
-
- def getReceiver(): NetworkReceiver[T] = {
- new KafkaReceiver[T, D](kafkaParams, topics, storageLevel)
- .asInstanceOf[NetworkReceiver[T]]
+ def getReceiver(): NetworkReceiver[(K, V)] = {
+ new KafkaReceiver[K, V, U, T](kafkaParams, topics, storageLevel)
+ .asInstanceOf[NetworkReceiver[(K, V)]]
}
}
private[streaming]
-class KafkaReceiver[T: ClassManifest, D <: Decoder[_]: Manifest](
- kafkaParams: Map[String, String],
- topics: Map[String, Int],
- storageLevel: StorageLevel
+class KafkaReceiver[
+ K: ClassManifest,
+ V: ClassManifest,
+ U <: Decoder[_]: Manifest,
+ T <: Decoder[_]: Manifest](
+ kafkaParams: Map[String, String],
+ topics: Map[String, Int],
+ storageLevel: StorageLevel
) extends NetworkReceiver[Any] {
// Handles pushing data into the BlockManager
@@ -83,27 +86,34 @@ class KafkaReceiver[T: ClassManifest, D <: Decoder[_]: Manifest](
// In case we are using multiple Threads to handle Kafka Messages
val executorPool = Executors.newFixedThreadPool(topics.values.reduce(_ + _))
- logInfo("Starting Kafka Consumer Stream with group: " + kafkaParams("groupid"))
+ logInfo("Starting Kafka Consumer Stream with group: " + kafkaParams("group.id"))
// Kafka connection properties
val props = new Properties()
kafkaParams.foreach(param => props.put(param._1, param._2))
// Create the connection to the cluster
- logInfo("Connecting to Zookeper: " + kafkaParams("zk.connect"))
+ logInfo("Connecting to Zookeper: " + kafkaParams("zookeeper.connect"))
val consumerConfig = new ConsumerConfig(props)
consumerConnector = Consumer.create(consumerConfig)
- logInfo("Connected to " + kafkaParams("zk.connect"))
+ logInfo("Connected to " + kafkaParams("zookeeper.connect"))
// When autooffset.reset is defined, it is our responsibility to try and whack the
// consumer group zk node.
- if (kafkaParams.contains("autooffset.reset")) {
- tryZookeeperConsumerGroupCleanup(kafkaParams("zk.connect"), kafkaParams("groupid"))
+ if (kafkaParams.contains("auto.offset.reset")) {
+ tryZookeeperConsumerGroupCleanup(kafkaParams("zookeeper.connect"), kafkaParams("group.id"))
}
// Create Threads for each Topic/Message Stream we are listening
- val decoder = manifest[D].erasure.newInstance.asInstanceOf[Decoder[T]]
- val topicMessageStreams = consumerConnector.createMessageStreams(topics, decoder)
+ val keyDecoder = manifest[U].erasure.getConstructor(classOf[VerifiableProperties])
+ .newInstance(consumerConfig.props)
+ .asInstanceOf[Decoder[K]]
+ val valueDecoder = manifest[T].erasure.getConstructor(classOf[VerifiableProperties])
+ .newInstance(consumerConfig.props)
+ .asInstanceOf[Decoder[V]]
+
+ val topicMessageStreams = consumerConnector.createMessageStreams(
+ topics, keyDecoder, valueDecoder)
// Start the messages handler for each partition
topicMessageStreams.values.foreach { streams =>
@@ -112,11 +122,12 @@ class KafkaReceiver[T: ClassManifest, D <: Decoder[_]: Manifest](
}
// Handles Kafka Messages
- private class MessageHandler[T: ClassManifest](stream: KafkaStream[T]) extends Runnable {
+ private class MessageHandler[K: ClassManifest, V: ClassManifest](stream: KafkaStream[K, V])
+ extends Runnable {
def run() {
logInfo("Starting MessageHandler.")
for (msgAndMetadata <- stream) {
- blockGenerator += msgAndMetadata.message
+ blockGenerator += (msgAndMetadata.key, msgAndMetadata.message)
}
}
}
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/MQTTInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/MQTTInputDStream.scala
new file mode 100644
index 0000000000000000000000000000000000000000..ac0528213d3290832d458d4eea91992d99f3cbe9
--- /dev/null
+++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/MQTTInputDStream.scala
@@ -0,0 +1,109 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.dstream
+
+import org.apache.spark.Logging
+import org.apache.spark.storage.StorageLevel
+import org.apache.spark.streaming.{ Time, DStreamCheckpointData, StreamingContext }
+
+import java.util.Properties
+import java.util.concurrent.Executors
+import java.io.IOException
+
+import org.eclipse.paho.client.mqttv3.MqttCallback
+import org.eclipse.paho.client.mqttv3.MqttClient
+import org.eclipse.paho.client.mqttv3.MqttClientPersistence
+import org.eclipse.paho.client.mqttv3.persist.MemoryPersistence
+import org.eclipse.paho.client.mqttv3.IMqttDeliveryToken
+import org.eclipse.paho.client.mqttv3.MqttException
+import org.eclipse.paho.client.mqttv3.MqttMessage
+import org.eclipse.paho.client.mqttv3.MqttTopic
+
+import scala.collection.Map
+import scala.collection.mutable.HashMap
+import scala.collection.JavaConversions._
+
+/**
+ * Input stream that subscribe messages from a Mqtt Broker.
+ * Uses eclipse paho as MqttClient http://www.eclipse.org/paho/
+ * @param brokerUrl Url of remote mqtt publisher
+ * @param topic topic name to subscribe to
+ * @param storageLevel RDD storage level.
+ */
+
+private[streaming]
+class MQTTInputDStream[T: ClassManifest](
+ @transient ssc_ : StreamingContext,
+ brokerUrl: String,
+ topic: String,
+ storageLevel: StorageLevel
+ ) extends NetworkInputDStream[T](ssc_) with Logging {
+
+ def getReceiver(): NetworkReceiver[T] = {
+ new MQTTReceiver(brokerUrl, topic, storageLevel)
+ .asInstanceOf[NetworkReceiver[T]]
+ }
+}
+
+private[streaming]
+class MQTTReceiver(brokerUrl: String,
+ topic: String,
+ storageLevel: StorageLevel
+ ) extends NetworkReceiver[Any] {
+ lazy protected val blockGenerator = new BlockGenerator(storageLevel)
+
+ def onStop() {
+ blockGenerator.stop()
+ }
+
+ def onStart() {
+
+ blockGenerator.start()
+
+ // Set up persistence for messages
+ var peristance: MqttClientPersistence = new MemoryPersistence()
+
+ // Initializing Mqtt Client specifying brokerUrl, clientID and MqttClientPersistance
+ var client: MqttClient = new MqttClient(brokerUrl, "MQTTSub", peristance)
+
+ // Connect to MqttBroker
+ client.connect()
+
+ // Subscribe to Mqtt topic
+ client.subscribe(topic)
+
+ // Callback automatically triggers as and when new message arrives on specified topic
+ var callback: MqttCallback = new MqttCallback() {
+
+ // Handles Mqtt message
+ override def messageArrived(arg0: String, arg1: MqttMessage) {
+ blockGenerator += new String(arg1.getPayload())
+ }
+
+ override def deliveryComplete(arg0: IMqttDeliveryToken) {
+ }
+
+ override def connectionLost(arg0: Throwable) {
+ logInfo("Connection lost " + arg0)
+ }
+ }
+
+ // Set up callback for MqttClient
+ client.setCallback(callback)
+ }
+}
diff --git a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java
index c0d729ff8767373549991e872906a2b63d5fd05d..dc01f1e8aa0ca3ee0935378462c2fbe85bd20c85 100644
--- a/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java
+++ b/streaming/src/test/java/org/apache/spark/streaming/JavaAPISuite.java
@@ -1220,14 +1220,20 @@ public class JavaAPISuite implements Serializable {
@Test
public void testKafkaStream() {
HashMap<String, Integer> topics = Maps.newHashMap();
- JavaDStream test1 = ssc.kafkaStream("localhost:12345", "group", topics);
- JavaDStream test2 = ssc.kafkaStream("localhost:12345", "group", topics,
+ JavaPairDStream<String, String> test1 = ssc.kafkaStream("localhost:12345", "group", topics);
+ JavaPairDStream<String, String> test2 = ssc.kafkaStream("localhost:12345", "group", topics,
StorageLevel.MEMORY_AND_DISK());
HashMap<String, String> kafkaParams = Maps.newHashMap();
- kafkaParams.put("zk.connect","localhost:12345");
- kafkaParams.put("groupid","consumer-group");
- JavaDStream test3 = ssc.kafkaStream(String.class, StringDecoder.class, kafkaParams, topics,
+ kafkaParams.put("zookeeper.connect","localhost:12345");
+ kafkaParams.put("group.id","consumer-group");
+ JavaPairDStream<String, String> test3 = ssc.kafkaStream(
+ String.class,
+ String.class,
+ StringDecoder.class,
+ StringDecoder.class,
+ kafkaParams,
+ topics,
StorageLevel.MEMORY_AND_DISK());
}
diff --git a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
index 42e3e51e3fa15b18de981fe46f40fe999786a276..c29b75ece69f05211be5dc977b0f2e860282cca0 100644
--- a/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
+++ b/streaming/src/test/scala/org/apache/spark/streaming/InputStreamsSuite.scala
@@ -268,8 +268,12 @@ class InputStreamsSuite extends TestSuiteBase with BeforeAndAfter {
val test2 = ssc.kafkaStream("localhost:12345", "group", topics, StorageLevel.MEMORY_AND_DISK)
// Test specifying decoder
- val kafkaParams = Map("zk.connect"->"localhost:12345","groupid"->"consumer-group")
- val test3 = ssc.kafkaStream[String, kafka.serializer.StringDecoder](kafkaParams, topics, StorageLevel.MEMORY_AND_DISK)
+ val kafkaParams = Map("zookeeper.connect"->"localhost:12345","group.id"->"consumer-group")
+ val test3 = ssc.kafkaStream[
+ String,
+ String,
+ kafka.serializer.StringDecoder,
+ kafka.serializer.StringDecoder](kafkaParams, topics, StorageLevel.MEMORY_AND_DISK)
}
}
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 8afb3e39cb8a6a0e7df4c4e41e03083867601b71..1a380ae714534bc06146d62c0921a404bc64ce5e 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
@@ -265,11 +265,7 @@ class Client(conf: Configuration, args: ClientArguments) extends YarnClientImpl
val env = new HashMap[String, String]()
- Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$())
- Apps.addToEnvironment(env, Environment.CLASSPATH.name,
- Environment.PWD.$() + Path.SEPARATOR + "*")
-
- Client.populateHadoopClasspath(yarnConf, env)
+ Client.populateClasspath(yarnConf, log4jConfLocalRes != null, env)
env("SPARK_YARN_MODE") = "true"
env("SPARK_YARN_JAR_PATH") =
localResources("spark.jar").getResource().getScheme.toString() + "://" +
@@ -451,4 +447,30 @@ object Client {
Apps.addToEnvironment(env, Environment.CLASSPATH.name, c.trim)
}
}
+
+ def populateClasspath(conf: Configuration, addLog4j: Boolean, env: HashMap[String, String]) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$())
+ // If log4j present, ensure ours overrides all others
+ if (addLog4j) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + "log4j.properties")
+ }
+ // normally the users app.jar is last in case conflicts with spark jars
+ val userClasspathFirst = System.getProperty("spark.yarn.user.classpath.first", "false")
+ .toBoolean
+ if (userClasspathFirst) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + "app.jar")
+ }
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + "spark.jar")
+ Client.populateHadoopClasspath(conf, env)
+
+ if (!userClasspathFirst) {
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + "app.jar")
+ }
+ Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$() +
+ Path.SEPARATOR + "*")
+ }
}
diff --git a/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala b/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
index 8dac9e02ac0b712fcf712c60575b43b3d2729f9c..ba352daac485d0381a2df87f391b8435a315bc61 100644
--- a/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
+++ b/yarn/src/main/scala/org/apache/spark/deploy/yarn/WorkerRunnable.scala
@@ -121,7 +121,7 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
// TODO: If the OOM is not recoverable by rescheduling it on different node, then do 'something' to fail job ... akin to blacklisting trackers in mapred ?
" -XX:OnOutOfMemoryError='kill %p' " +
JAVA_OPTS +
- " org.apache.spark.executor.StandaloneExecutorBackend " +
+ " org.apache.spark.executor.CoarseGrainedExecutorBackend " +
masterAddress + " " +
slaveId + " " +
hostname + " " +
@@ -216,10 +216,7 @@ class WorkerRunnable(container: Container, conf: Configuration, masterAddress: S
def prepareEnvironment: HashMap[String, String] = {
val env = new HashMap[String, String]()
- Apps.addToEnvironment(env, Environment.CLASSPATH.name, Environment.PWD.$())
- Apps.addToEnvironment(env, Environment.CLASSPATH.name,
- Environment.PWD.$() + Path.SEPARATOR + "*")
- Client.populateHadoopClasspath(yarnConf, env)
+ Client.populateClasspath(yarnConf, System.getenv("SPARK_YARN_LOG4J_PATH") != null, env)
// allow users to specify some environment variables
Apps.setEnvFromInputString(env, System.getenv("SPARK_YARN_USER_ENV"))