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From Dmitry Goldenberg <dgoldenberg...@gmail.com>
Subject Re: How to fix OutOfMemoryError: GC overhead limit exceeded when using Spark Streaming checkpointing
Date Mon, 10 Aug 2015 16:34:11 GMT
Thanks, Cody, will try that. Unfortunately due to a reinstall I don't have
the original checkpointing directory :(  Thanks for the clarification on
spark.driver.memory, I'll keep testing (at 2g things seem OK for now).

On Mon, Aug 10, 2015 at 12:10 PM, Cody Koeninger <cody@koeninger.org> wrote:

> That looks like it's during recovery from a checkpoint, so it'd be driver
> memory not executor memory.
>
> How big is the checkpoint directory that you're trying to restore from?
>
> On Mon, Aug 10, 2015 at 10:57 AM, Dmitry Goldenberg <
> dgoldenberg123@gmail.com> wrote:
>
>> We're getting the below error.  Tried increasing spark.executor.memory
>> e.g. from 1g to 2g but the below error still happens.
>>
>> Any recommendations? Something to do with specifying -Xmx in the submit
>> job scripts?
>>
>> Thanks.
>>
>> Exception in thread "main" java.lang.OutOfMemoryError: GC overhead limit
>> exceeded
>> at java.util.Arrays.copyOf(Arrays.java:3332)
>> at
>> java.lang.AbstractStringBuilder.expandCapacity(AbstractStringBuilder.java:137)
>> at
>> java.lang.AbstractStringBuilder.ensureCapacityInternal(AbstractStringBuilder.java:121)
>> at java.lang.AbstractStringBuilder.append(AbstractStringBuilder.java:421)
>> at java.lang.StringBuilder.append(StringBuilder.java:136)
>> at java.lang.StackTraceElement.toString(StackTraceElement.java:173)
>> at
>> org.apache.spark.util.Utils$$anonfun$getCallSite$1.apply(Utils.scala:1212)
>> at
>> org.apache.spark.util.Utils$$anonfun$getCallSite$1.apply(Utils.scala:1190)
>> at
>> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
>> at org.apache.spark.util.Utils$.getCallSite(Utils.scala:1190)
>> at
>> org.apache.spark.SparkContext$$anonfun$getCallSite$2.apply(SparkContext.scala:1441)
>> at
>> org.apache.spark.SparkContext$$anonfun$getCallSite$2.apply(SparkContext.scala:1441)
>> at scala.Option.getOrElse(Option.scala:120)
>> at org.apache.spark.SparkContext.getCallSite(SparkContext.scala:1441)
>> at org.apache.spark.rdd.RDD.<init>(RDD.scala:1365)
>> at org.apache.spark.streaming.kafka.KafkaRDD.<init>(KafkaRDD.scala:46)
>> at
>> org.apache.spark.streaming.kafka.DirectKafkaInputDStream$DirectKafkaInputDStreamCheckpointData$$anonfun$restore$2.apply(DirectKafkaInputDStream.scala:155)
>> at
>> org.apache.spark.streaming.kafka.DirectKafkaInputDStream$DirectKafkaInputDStreamCheckpointData$$anonfun$restore$2.apply(DirectKafkaInputDStream.scala:153)
>> at
>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>> at
>> org.apache.spark.streaming.kafka.DirectKafkaInputDStream$DirectKafkaInputDStreamCheckpointData.restore(DirectKafkaInputDStream.scala:153)
>> at
>> org.apache.spark.streaming.dstream.DStream.restoreCheckpointData(DStream.scala:402)
>> at
>> org.apache.spark.streaming.dstream.DStream$$anonfun$restoreCheckpointData$2.apply(DStream.scala:403)
>> at
>> org.apache.spark.streaming.dstream.DStream$$anonfun$restoreCheckpointData$2.apply(DStream.scala:403)
>> at scala.collection.immutable.List.foreach(List.scala:318)
>> at
>> org.apache.spark.streaming.dstream.DStream.restoreCheckpointData(DStream.scala:403)
>> at
>> org.apache.spark.streaming.dstream.DStream$$anonfun$restoreCheckpointData$2.apply(DStream.scala:403)
>> at
>> org.apache.spark.streaming.dstream.DStream$$anonfun$restoreCheckpointData$2.apply(DStream.scala:403)
>> at scala.collection.immutable.List.foreach(List.scala:318)
>> at
>> org.apache.spark.streaming.dstream.DStream.restoreCheckpointData(DStream.scala:403)
>> at
>> org.apache.spark.streaming.DStreamGraph$$anonfun$restoreCheckpointData$2.apply(DStreamGraph.scala:149)
>>
>>
>>
>>
>

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