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Notebook failing in job-cluster but runs fine in all-purpose-cluster with the same configuration

AjayHN
New Contributor II

I have a notebook with many join and few persist operations (which runs fine on all-purpose-cluster (with worker nodes - i3.xlarge and autoscale enabled), but the same notebook failing in job-cluster with the same cluster definition (to be frank the job-cluster has even better worker nodes - i3.8xlarge)

Cluster Conf:

job-clusterall-purpose-clusterSpark Conf:

spark.databricks.delta.optimizeWrite.enabled true
spark.databricks.adaptive.autoOptimizedShuffle.enabled true

Error:

Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 69 (sql at command-3296064203992845:4) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Connection reset by peer 	at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:749) 	at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:662) 	at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:69) 	at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29) 	at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484) 	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490) 	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) 	at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) 	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) 	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) 	at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:240) 	at org.apache.spark.sql.execution.SortExec$$anon$2.sortedIterator(SortExec.scala:133) 	at org.apache.spark.sql.execution.SortExec$$anon$2.hasNext(SortExec.scala:147) 	at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83) 	at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.advancedBufferedToRowWithNullFreeJoinKey(SortMergeJoinExec.scala:950) 	at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.<init>(SortMergeJoinExec.scala:820) 	at org.apache.spark.sql.execution.joins.SortMergeJoinExec.$anonfun$doExecute$1(SortMergeJoinExec.scala:258) 	at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:101) 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:356) 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:320) 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:356) 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:320) 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:356) 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:320) 	at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) 	at org.apache.spark.scheduler.Task.doRunTask(Task.scala:144) 	at org.apache.spark.scheduler.Task.run(Task.scala:117) 	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$9(Executor.scala:655) 	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1581) 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:658) 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) 	at java.lang.Thread.run(Thread.java:748) Caused by: java.io.IOException: Connection reset by peer 	at sun.nio.ch.FileDispatcherImpl.read0(Native Method) 	at sun.nio.ch.SocketDispatcher.read(SocketDispatcher.java:39) 	at sun.nio.ch.IOUtil.readIntoNativeBuffer(IOUtil.java:223) 	at sun.nio.ch.IOUtil.read(IOUtil.java:192) 	at sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:379) 	at io.netty.buffer.PooledByteBuf.setBytes(PooledByteBuf.java:253) 	at io.netty.buffer.AbstractByteBuf.writeBytes(AbstractByteBuf.java:1133) 	at io.netty.channel.socket.nio.NioSocketChannel.doReadBytes(NioSocketChannel.java:350) 	at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:148) 	at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:714) 	at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:650) 	at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:576) 	at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:493) 	at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:989) 	at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74) 	at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30) 	... 1 more 
	at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2519)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2466)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2460)
	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2460)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:2050)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2718)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2668)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2656)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)

Note: If you also notice the EBS Volume Type in job-cluster is displayed as Autoscaling Local Storage instead of General Purpose SSD, as I have set it as General Purpose SSD

1 ACCEPTED SOLUTION

Accepted Solutions

jose_gonzalez
Databricks Employee
Databricks Employee

Hi @Ajay Nanjundappaโ€‹ ,

Check "Event log" tab. Search for any spot terminations events. It seems like all your nodes are spot instances. The error "FetchFailedException" is associated with spot termination nodes.

View solution in original post

1 REPLY 1

jose_gonzalez
Databricks Employee
Databricks Employee

Hi @Ajay Nanjundappaโ€‹ ,

Check "Event log" tab. Search for any spot terminations events. It seems like all your nodes are spot instances. The error "FetchFailedException" is associated with spot termination nodes.

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