I have a SparkApp that runs completes in 45 mins for 5 files (5*750MB size) and it takes 16 executors to do so.
I wanted to run it against 10 files of each input type (10*3 files as there are three inputs that are transformed). [Input1 = 10*750 MB, Input2=10*2.5GB, Input3 = 10*1.5G], Hence i used 32 executors. I see multiple 5/04/28 09:23:31 WARN executor.Executor: Issue communicating with driver in heartbeater org.apache.spark.SparkException: Error sending message [message = Heartbeat(22,[Lscala.Tuple2;@2e4c404a,BlockManagerId(22, phxaishdc9dn1048.stratus.phx.ebay.com, 39505))] at org.apache.spark.util.AkkaUtils$.askWithReply(AkkaUtils.scala:209) at org.apache.spark.executor.Executor$$anon$1.run(Executor.scala:427) Caused by: java.util.concurrent.TimeoutException: Futures timed out after [30 seconds] at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219) at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223) at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107) at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53) at scala.concurrent.Await$.result(package.scala:107) at org.apache.spark.util.AkkaUtils$.askWithReply(AkkaUtils.scala:195) ... 1 more When i searched deeper, i found OOM error. 15/04/28 09:10:15 INFO storage.BlockManagerMasterActor: Removing block manager BlockManagerId(17, phxdpehdc9dn2643.stratus.phx.ebay.com, 36819) 15/04/28 09:11:26 WARN storage.BlockManagerMasterActor: Removing BlockManager BlockManagerId(9, phxaishdc9dn1783.stratus.phx.ebay.com, 48304) with no recent heart beats: 121200ms exceeds 120000ms 15/04/28 09:11:26 INFO storage.BlockManagerMasterActor: Removing block manager BlockManagerId(9, phxaishdc9dn1783.stratus.phx.ebay.com, 48304) 15/04/28 09:11:26 ERROR util.Utils: Uncaught exception in thread task-result-getter-3 java.lang.OutOfMemoryError: Java heap space at java.util.Arrays.copyOf(Arrays.java:2245) at java.util.Arrays.copyOf(Arrays.java:2219) at java.util.ArrayList.grow(ArrayList.java:242) at java.util.ArrayList.ensureExplicitCapacity(ArrayList.java:216) at java.util.ArrayList.ensureCapacityInternal(ArrayList.java:208) at java.util.ArrayList.add(ArrayList.java:440) at com.esotericsoftware.kryo.util.MapReferenceResolver.nextReadId(MapReferenceResolver.java:33) at com.esotericsoftware.kryo.Kryo.readReferenceOrNull(Kryo.java:766) at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:727) at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338) at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293) at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729) at org.apache.spark.serializer.KryoSerializerInstance.deserialize(KryoSerializer.scala:173) at org.apache.spark.scheduler.DirectTaskResult.value(TaskResult.scala:79) at org.apache.spark.scheduler.TaskSetManager.handleSuccessfulTask(TaskSetManager.scala:621) at org.apache.spark.scheduler.TaskSchedulerImpl.handleSuccessfulTask(TaskSchedulerImpl.scala:379) at org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply$mcV$sp(TaskResultGetter.scala:82) at org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply(TaskResultGetter.scala:51) at org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply(TaskResultGetter.scala:51) at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1618) at org.apache.spark.scheduler.TaskResultGetter$$anon$2.run(TaskResultGetter.scala:50) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) Exception in thread "task-result-getter-3" java.lang.OutOfMemoryError: Java heap space at java.util.Arrays.copyOf(Arrays.java:2245) at java.util.Arrays.copyOf(Arrays.java:2219) at java.util.ArrayList.grow(ArrayList.java:242) at java.util.ArrayList.ensureExplicitCapacity(ArrayList.java:216) at java.util.ArrayList.ensureCapacityInternal(ArrayList.java:208) at java.util.ArrayList.add(ArrayList.java:440) at com.esotericsoftware.kryo.util.MapReferenceResolver.nextReadId(MapReferenceResolver.java:33) at com.esotericsoftware.kryo.Kryo.readReferenceOrNull(Kryo.java:766) at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:727) at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:338) at com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read(DefaultArraySerializers.java:293) at com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729) at org.apache.spark.serializer.KryoSerializerInstance.deserialize(KryoSerializer.scala:173) at org.apache.spark.scheduler.DirectTaskResult.value(TaskResult.scala:79) at org.apache.spark.scheduler.TaskSetManager.handleSuccessfulTask(TaskSetManager.scala:621) at org.apache.spark.scheduler.TaskSchedulerImpl.handleSuccessfulTask(TaskSchedulerImpl.scala:379) at org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply$mcV$sp(TaskResultGetter.scala:82) at org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply(TaskResultGetter.scala:51) at org.apache.spark.scheduler.TaskResultGetter$$anon$2$$anonfun$run$1.apply(TaskResultGetter.scala:51) at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1618) at org.apache.spark.scheduler.TaskResultGetter$$anon$2.run(TaskResultGetter.scala:50) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) LogType: stdout LogLength: 96 Log Contents: hdfs://hostName:8020/sys/edw/dw_lstg_item/snapshot/2015/04/28/00/part-r-0000* Spark Command: ./bin/spark-submit -v --master yarn-cluster --driver-class-path /apache/hadoop/share/hadoop/common/hadoop-common-2.4.1-EBAY-2.jar:/apache/hadoop/lib/hadoop-lzo-0.6.0.jar:/apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/yarn/lib/guava-11.0.2.jar:/apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/hdfs/hadoop-hdfs-2.4.1-EBAY-2.jar --jars /apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/hdfs/hadoop-hdfs-2.4.1-EBAY-2.jar,/home/dvasthimal/spark1.3/1.3.1.lib/spark_reporting_dep_only-1.0-SNAPSHOT-jar-with-dependencies.jar --num-executors 32 --driver-memory 12g --driver-java-options "-XX:MaxPermSize=8G" --executor-memory 12g --executor-cores 4 --queue hdmi-express --class com.ebay.ep.poc.spark.reporting.SparkApp /home/dvasthimal/spark1.3/1.3.1.lib/spark_reporting-1.0-SNAPSHOT.jar startDate=2015-04-6 endDate=2015-04-7 input=/user/dvasthimal/epdatasets_small/exptsession subcommand=viewItem output=/user/dvasthimal/epdatasets/viewItem buffersize=128 maxbuffersize=1068 maxResultSize=200G askTimeout=1200 There is 12G limit on memory that i can use as this Spark is running over YARN. Spark Version: 1.3.1 Should i increase the number of executors form 32? -- Deepak
