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

AjayHN — Thu, 28 Oct 2021 11:22:49 GMT

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:

Spark 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

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

jose_gonzalez — Sat, 13 Nov 2021 00:48:13 GMT

Hi @Ajay Nanjundappa ,

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.

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

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

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