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https://issues.apache.org/jira/browse/SPARK-1391?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13966332#comment-13966332
]
Mridul Muralidharan commented on SPARK-1391:
--------------------------------------------
Another place where this is relevant is here :
java.lang.IllegalArgumentException: Size exceeds Integer.MAX_VALUE
at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:789)
at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:98)
at
org.apache.spark.storage.BlockManager.doGetLocal(BlockManager.scala:413)
at
org.apache.spark.storage.BlockManager.getLocal(BlockManager.scala:339)
at org.apache.spark.storage.BlockManager.get(BlockManager.scala:506)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:39)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:233)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
at org.apache.spark.scheduler.Task.run(Task.scala:52)
at
org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:211)
at
org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:43)
at
org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:42)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at
org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1262)
at
org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:42)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:176)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:722)
So we might want to change the abstraction from single ByteBuffer to a sequence
of bytebuffers ...
> BlockManager cannot transfer blocks larger than 2G in size
> ----------------------------------------------------------
>
> Key: SPARK-1391
> URL: https://issues.apache.org/jira/browse/SPARK-1391
> Project: Spark
> Issue Type: Bug
> Components: Block Manager, Shuffle
> Affects Versions: 1.0.0
> Reporter: Shivaram Venkataraman
> Assignee: Min Zhou
> Attachments: SPARK-1391.diff
>
>
> If a task tries to remotely access a cached RDD block, I get an exception
> when the block size is > 2G. The exception is pasted below.
> Memory capacities are huge these days (> 60G), and many workflows depend on
> having large blocks in memory, so it would be good to fix this bug.
> I don't know if the same thing happens on shuffles if one transfer (from
> mapper to reducer) is > 2G.
> {noformat}
> 14/04/02 02:33:10 ERROR storage.BlockManagerWorker: Exception handling buffer
> message
> java.lang.ArrayIndexOutOfBoundsException
> at
> it.unimi.dsi.fastutil.io.FastByteArrayOutputStream.write(FastByteArrayOutputStream.java:96)
> at
> it.unimi.dsi.fastutil.io.FastBufferedOutputStream.dumpBuffer(FastBufferedOutputStream.java:134)
> at
> it.unimi.dsi.fastutil.io.FastBufferedOutputStream.write(FastBufferedOutputStream.java:164)
> at
> java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1876)
> at
> java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1785)
> at
> java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1188)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
> at
> org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:38)
> at
> org.apache.spark.serializer.SerializationStream$class.writeAll(Serializer.scala:93)
> at
> org.apache.spark.serializer.JavaSerializationStream.writeAll(JavaSerializer.scala:26)
> at
> org.apache.spark.storage.BlockManager.dataSerializeStream(BlockManager.scala:913)
> at
> org.apache.spark.storage.BlockManager.dataSerialize(BlockManager.scala:922)
> at
> org.apache.spark.storage.MemoryStore.getBytes(MemoryStore.scala:102)
> at
> org.apache.spark.storage.BlockManager.doGetLocal(BlockManager.scala:348)
> at
> org.apache.spark.storage.BlockManager.getLocalBytes(BlockManager.scala:323)
> at
> org.apache.spark.storage.BlockManagerWorker.getBlock(BlockManagerWorker.scala:90)
> at
> org.apache.spark.storage.BlockManagerWorker.processBlockMessage(BlockManagerWorker.scala:69)
> at
> org.apache.spark.storage.BlockManagerWorker$$anonfun$2.apply(BlockManagerWorker.scala:44)
> at
> org.apache.spark.storage.BlockManagerWorker$$anonfun$2.apply(BlockManagerWorker.scala:44)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> at
> org.apache.spark.storage.BlockMessageArray.foreach(BlockMessageArray.scala:28)
> at
> scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at
> org.apache.spark.storage.BlockMessageArray.map(BlockMessageArray.scala:28)
> at
> org.apache.spark.storage.BlockManagerWorker.onBlockMessageReceive(BlockManagerWorker.scala:44)
> at
> org.apache.spark.storage.BlockManagerWorker$$anonfun$1.apply(BlockManagerWorker.scala:34)
> at
> org.apache.spark.storage.BlockManagerWorker$$anonfun$1.apply(BlockManagerWorker.scala:34)
> at
> org.apache.spark.network.ConnectionManager.org$apache$spark$network$ConnectionManager$$handleMessage(ConnectionManager.scala:661)
> at
> org.apache.spark.network.ConnectionManager$$anon$9.run(ConnectionManager.scala:503)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> {noformat}
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