[
https://issues.apache.org/jira/browse/SPARK-1391?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13957522#comment-13957522
]
Min Zhou commented on SPARK-1391:
---------------------------------
Finally, I can explain the whole thing. Apologies to Shivaram, you didn't miss
anything.
>From the above, we can see that the position can be a negative value.
Run below code under fastutils 6.5.7 we will get
{noformat}
import it.unimi.dsi.fastutil.io.FastByteArrayOutputStream;
public class ArrayIndex {
public static void main(String[] args) throws Exception {
FastByteArrayOutputStream outputStream = new
FastByteArrayOutputStream(4096);
outputStream.position(Integer.MAX_VALUE);
outputStream.write(new byte[1024], 0, 1024);
outputStream.close();
}
}
Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException
at java.lang.System.arraycopy(Native Method)
at
it.unimi.dsi.fastutil.io.FastByteArrayOutputStream.write(FastByteArrayOutputStream.java:96)
at mzhou.shuffle.perf.ArrayOutofIndex.main(ArrayOutofIndex.java:29)
{noformat}
We can see the line number FastByteArrayOutputStream.java:96 is correct, the
same as Shivaram's. The only different is that the stack frame "at
java.lang.System.arraycopy(Native Method)" does exists in Shivaram's report.
After some investigation on jdk source code, I get the answer,
System.arraycopy got Just-in-Time compiled.
{noformat}
public class ArrayCopy {
public static void main(String[] args) throws Exception {
byte[] src = new byte[8];
byte[] dst = new byte[8];
for(int i = 0; i < 100000; i++) {
System.arraycopy(src,0,dst,0, dst.length);
}
System.arraycopy(src,0,dst,-1, dst.length);
}
Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException
at mzhou.shuffle.perf.ArrayOutofIndex.main(ArrayOutofIndex.java:36)
}
{noformat}
See? That stack trace has gone.
> 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
>
> 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.
> 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)
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