Since you specified +PrintGCDetails, you should be able to get some more detail from the GC log.
Also, which JDK version are you using ? Please use Java 8 where G1GC is more reliable. On Sat, Jul 23, 2016 at 10:38 AM, Ascot Moss <ascot.m...@gmail.com> wrote: > Hi, > > I added the following parameter: > > --conf "spark.executor.extraJavaOptions=-XX:+UseG1GC > -XX:MaxGCPauseMillis=200 -XX:ParallelGCThreads=20 -XX:ConcGCThreads=5 > -XX:InitiatingHeapOccupancyPercent=70 -XX:+PrintGCDetails > -XX:+PrintGCTimeStamps" > > Still got Java heap space error. > > Any idea to resolve? (my spark is 1.6.1) > > > 16/07/23 23:31:50 WARN TaskSetManager: Lost task 1.0 in stage 6.0 (TID 22, > n1791): java.lang.OutOfMemoryError: Java heap space at > scala.reflect.ManifestFactory$$anon$12.newArray(Manifest.scala:138) > > at > scala.reflect.ManifestFactory$$anon$12.newArray(Manifest.scala:136) > > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:248) > > at > org.apache.spark.util.collection.CompactBuffer.toArray(CompactBuffer.scala:30) > > at > org.apache.spark.mllib.tree.DecisionTree$.org$apache$spark$mllib$tree$DecisionTree$$findSplits$1(DecisionTree.scala:1009) > at > org.apache.spark.mllib.tree.DecisionTree$$anonfun$29.apply(DecisionTree.scala:1042) > > at > org.apache.spark.mllib.tree.DecisionTree$$anonfun$29.apply(DecisionTree.scala:1042) > > at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) > > at scala.collection.Iterator$class.foreach(Iterator.scala:727) > at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) > > at > scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) > > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) > > at > scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) > > at > scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273) > > at scala.collection.AbstractIterator.to(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) > > at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) > > at > scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) > > at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) > > at > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927) > > at > org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at > org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) > > at > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) > > at org.apache.spark.scheduler.Task.run(Task.scala:89) > > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) > > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > > at java.lang.Thread.run(Thread.java:745) > > Regards > > > > On Sat, Jul 23, 2016 at 9:49 AM, Ascot Moss <ascot.m...@gmail.com> wrote: > >> Thanks. Trying with extra conf now. >> >> On Sat, Jul 23, 2016 at 6:59 AM, RK Aduri <rkad...@collectivei.com> >> wrote: >> >>> I can see large number of collections happening on driver and >>> eventually, driver is running out of memory. ( am not sure whether you have >>> persisted any rdd or data frame). May be you would want to avoid doing so >>> many collections or persist unwanted data in memory. >>> >>> To begin with, you may want to re-run the job with this following >>> config: --conf "spark.executor.extraJavaOptions=-XX:+UseG1GC >>> -XX:+PrintGCDetails -XX:+PrintGCTimeStamps” —> and this will give you an >>> idea of how you are getting OOM. >>> >>> >>> On Jul 22, 2016, at 3:52 PM, Ascot Moss <ascot.m...@gmail.com> wrote: >>> >>> Hi >>> >>> Please help! >>> >>> When running random forest training phase in cluster mode, I got GC >>> overhead limit exceeded. >>> >>> I have used two parameters when submitting the job to cluster >>> >>> --driver-memory 64g \ >>> >>> --executor-memory 8g \ >>> >>> My Current settings: >>> >>> (spark-defaults.conf) >>> >>> spark.executor.memory 8g >>> >>> (spark-env.sh) >>> >>> export SPARK_WORKER_MEMORY=8g >>> >>> export HADOOP_HEAPSIZE=8000 >>> >>> >>> Any idea how to resolve it? >>> >>> Regards >>> >>> >>> >>> >>> >>> >>> ### (the erro log) ### >>> >>> 16/07/23 04:34:04 WARN TaskSetManager: Lost task 2.0 in stage 6.1 (TID >>> 30, n1794): java.lang.OutOfMemoryError: GC overhead limit exceeded >>> >>> at >>> scala.reflect.ManifestFactory$$anon$12.newArray(Manifest.scala:138) >>> >>> at >>> scala.reflect.ManifestFactory$$anon$12.newArray(Manifest.scala:136) >>> >>> at >>> org.apache.spark.util.collection.CompactBuffer.growToSize(CompactBuffer.scala:144) >>> >>> at >>> org.apache.spark.util.collection.CompactBuffer.$plus$plus$eq(CompactBuffer.scala:90) >>> >>> at >>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$groupByKey$1$$anonfun$10.apply(PairRDDFunctions.scala:505) >>> >>> at >>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$groupByKey$1$$anonfun$10.apply(PairRDDFunctions.scala:505) >>> >>> at >>> org.apache.spark.util.collection.ExternalAppendOnlyMap$ExternalIterator.mergeIfKeyExists(ExternalAppendOnlyMap.scala:318) >>> >>> at >>> org.apache.spark.util.collection.ExternalAppendOnlyMap$ExternalIterator.next(ExternalAppendOnlyMap.scala:365) >>> >>> at >>> org.apache.spark.util.collection.ExternalAppendOnlyMap$ExternalIterator.next(ExternalAppendOnlyMap.scala:265) >>> >>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328) >>> >>> at scala.collection.Iterator$class.foreach(Iterator.scala:727) >>> >>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157) >>> >>> at >>> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48) >>> >>> at >>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103) >>> >>> at >>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47) >>> >>> at scala.collection.TraversableOnce$class.to >>> (TraversableOnce.scala:273) >>> >>> at scala.collection.AbstractIterator.to >>> <http://scala.collection.abstractiterator.to/>(Iterator.scala:1157) >>> >>> at >>> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265) >>> >>> at >>> scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157) >>> >>> at >>> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252) >>> >>> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157) >>> >>> at >>> org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927) >>> >>> at >>> org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927) >>> >>> at >>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) >>> >>> at >>> org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858) >>> >>> at >>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) >>> >>> at org.apache.spark.scheduler.Task.run(Task.scala:89) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) >>> >>> at java.lang.Thread.run(Thread.java:745) >>> >>> >>> >>> Collective[i] dramatically improves sales and marketing performance >>> using technology, applications and a revolutionary network designed to >>> provide next generation analytics and decision-support directly to business >>> users. 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