1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
|
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package spark.scheduler
import java.io._
import java.util.{HashMap => JHashMap}
import java.util.zip.{GZIPInputStream, GZIPOutputStream}
import scala.collection.mutable.{ArrayBuffer, HashMap}
import scala.collection.JavaConversions._
import it.unimi.dsi.fastutil.io.FastBufferedOutputStream
import com.ning.compress.lzf.LZFInputStream
import com.ning.compress.lzf.LZFOutputStream
import spark._
import spark.executor.ShuffleWriteMetrics
import spark.storage._
import spark.util.{TimeStampedHashMap, MetadataCleaner}
private[spark] object ShuffleMapTask {
// A simple map between the stage id to the serialized byte array of a task.
// Served as a cache for task serialization because serialization can be
// expensive on the master node if it needs to launch thousands of tasks.
val serializedInfoCache = new TimeStampedHashMap[Int, Array[Byte]]
val metadataCleaner = new MetadataCleaner("ShuffleMapTask", serializedInfoCache.clearOldValues)
def serializeInfo(stageId: Int, rdd: RDD[_], dep: ShuffleDependency[_,_]): Array[Byte] = {
synchronized {
val old = serializedInfoCache.get(stageId).orNull
if (old != null) {
return old
} else {
val out = new ByteArrayOutputStream
val ser = SparkEnv.get.closureSerializer.newInstance()
val objOut = ser.serializeStream(new GZIPOutputStream(out))
objOut.writeObject(rdd)
objOut.writeObject(dep)
objOut.close()
val bytes = out.toByteArray
serializedInfoCache.put(stageId, bytes)
return bytes
}
}
}
def deserializeInfo(stageId: Int, bytes: Array[Byte]): (RDD[_], ShuffleDependency[_,_]) = {
synchronized {
val loader = Thread.currentThread.getContextClassLoader
val in = new GZIPInputStream(new ByteArrayInputStream(bytes))
val ser = SparkEnv.get.closureSerializer.newInstance()
val objIn = ser.deserializeStream(in)
val rdd = objIn.readObject().asInstanceOf[RDD[_]]
val dep = objIn.readObject().asInstanceOf[ShuffleDependency[_,_]]
return (rdd, dep)
}
}
// Since both the JarSet and FileSet have the same format this is used for both.
def deserializeFileSet(bytes: Array[Byte]) : HashMap[String, Long] = {
val in = new GZIPInputStream(new ByteArrayInputStream(bytes))
val objIn = new ObjectInputStream(in)
val set = objIn.readObject().asInstanceOf[Array[(String, Long)]].toMap
return (HashMap(set.toSeq: _*))
}
def clearCache() {
synchronized {
serializedInfoCache.clear()
}
}
}
private[spark] class ShuffleMapTask(
stageId: Int,
var rdd: RDD[_],
var dep: ShuffleDependency[_,_],
var partition: Int,
@transient private var locs: Seq[String])
extends Task[MapStatus](stageId)
with Externalizable
with Logging {
protected def this() = this(0, null, null, 0, null)
@transient private val preferredLocs: Seq[String] = if (locs == null) Nil else locs.toSet.toSeq
{
// DEBUG code
preferredLocs.foreach (hostPort => Utils.checkHost(Utils.parseHostPort(hostPort)._1, "preferredLocs : " + preferredLocs))
}
var split = if (rdd == null) {
null
} else {
rdd.partitions(partition)
}
override def writeExternal(out: ObjectOutput) {
RDDCheckpointData.synchronized {
split = rdd.partitions(partition)
out.writeInt(stageId)
val bytes = ShuffleMapTask.serializeInfo(stageId, rdd, dep)
out.writeInt(bytes.length)
out.write(bytes)
out.writeInt(partition)
out.writeLong(generation)
out.writeObject(split)
}
}
override def readExternal(in: ObjectInput) {
val stageId = in.readInt()
val numBytes = in.readInt()
val bytes = new Array[Byte](numBytes)
in.readFully(bytes)
val (rdd_, dep_) = ShuffleMapTask.deserializeInfo(stageId, bytes)
rdd = rdd_
dep = dep_
partition = in.readInt()
generation = in.readLong()
split = in.readObject().asInstanceOf[Partition]
}
override def run(attemptId: Long): MapStatus = {
val numOutputSplits = dep.partitioner.numPartitions
val taskContext = new TaskContext(stageId, partition, attemptId)
metrics = Some(taskContext.taskMetrics)
val blockManager = SparkEnv.get.blockManager
var shuffle: ShuffleBlocks = null
var buckets: ShuffleWriterGroup = null
try {
// Obtain all the block writers for shuffle blocks.
val ser = SparkEnv.get.serializerManager.get(dep.serializerClass)
shuffle = blockManager.shuffleBlockManager.forShuffle(dep.shuffleId, numOutputSplits, ser)
buckets = shuffle.acquireWriters(partition)
// Write the map output to its associated buckets.
for (elem <- rdd.iterator(split, taskContext)) {
val pair = elem.asInstanceOf[(Any, Any)]
val bucketId = dep.partitioner.getPartition(pair._1)
buckets.writers(bucketId).write(pair)
}
// Commit the writes. Get the size of each bucket block (total block size).
var totalBytes = 0L
val compressedSizes: Array[Byte] = buckets.writers.map { writer: BlockObjectWriter =>
writer.commit()
writer.close()
val size = writer.size()
totalBytes += size
MapOutputTracker.compressSize(size)
}
// Update shuffle metrics.
val shuffleMetrics = new ShuffleWriteMetrics
shuffleMetrics.shuffleBytesWritten = totalBytes
metrics.get.shuffleWriteMetrics = Some(shuffleMetrics)
return new MapStatus(blockManager.blockManagerId, compressedSizes)
} catch { case e: Exception =>
// If there is an exception from running the task, revert the partial writes
// and throw the exception upstream to Spark.
if (buckets != null) {
buckets.writers.foreach(_.revertPartialWrites())
}
throw e
} finally {
// Release the writers back to the shuffle block manager.
if (shuffle != null && buckets != null) {
shuffle.releaseWriters(buckets)
}
// Execute the callbacks on task completion.
taskContext.executeOnCompleteCallbacks()
}
}
override def preferredLocations: Seq[String] = preferredLocs
override def toString = "ShuffleMapTask(%d, %d)".format(stageId, partition)
}
|
