Hi,
The array size you (or the serializer) tries to allocate is just too big
for the JVM. No configuration can help :
https://plumbr.eu/outofmemoryerror/requested-array-size-exceeds-vm-limit
The only option is to split you problem further by increasing parallelism.
Guillaume
Hi,
I’m using Spark 1.1.0 and I’m having some issues to setup memory options.
I get “Requested array size exceeds VM limit” and I’m probably missing
something regarding memory configuration
<https://spark.apache.org/docs/1.1.0/configuration.html>.
My server has 30G of memory and this are my current settings.
##this one seams that was deprecated
export SPARK_MEM=‘25g’
## worker memory options seams to be the memory for each worker (by
default we have a worker for each core)
export SPARK_WORKER_MEMORY=‘5g’
I probably need to specify some options using SPARK_DAEMON_JAVA_OPTS,
but I’m not quite sure how.
I have tried some different options like the following, but I still
couldn’t make it right:
export SPARK_DAEMON_JAVA_OPTS='-Xmx8G -XX:+UseCompressedOops'
export JAVA_OPTS='-Xmx8G -XX:+UseCompressedOops'
Does anyone has any idea how can I approach this?
14/10/11 13:00:16 INFO BlockFetcherIterator$BasicBlockFetcherIterator:
maxBytesInFlight: 50331648, targetRequestSize: 10066329
14/10/11 13:00:16 INFO BlockFetcherIterator$BasicBlockFetcherIterator:
Getting 1566 non-empty blocks out of 1566 blocks
14/10/11 13:00:16 INFO BlockFetcherIterator$BasicBlockFetcherIterator:
Started 0 remote fetches in 4 ms
14/10/11 13:02:06 INFO ExternalAppendOnlyMap: Thread 63 spilling
in-memory map of 3925 MB to disk (1 time so far)
14/10/11 13:05:17 INFO ExternalAppendOnlyMap: Thread 63 spilling
in-memory map of 3925 MB to disk (2 times so far)
14/10/11 13:09:15 ERROR Executor: Exception in task 0.0 in stage 0.0
(TID 1566)
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.util.Arrays.copyOf(Arrays.java:2271)
at
java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at
java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:140)
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1876)
at
java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1785)
at
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1188)
at
java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:42)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:73)
at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
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:745)
14/10/11 13:09:15 ERROR ExecutorUncaughtExceptionHandler: Uncaught
exception in thread Thread[Executor task launch worker-2,5,main]
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.util.Arrays.copyOf(Arrays.java:2271)
at
java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at
java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:140
Arian
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