Zhang Liang created SPARK-43242: ----------------------------------- Summary: shuffle diagnoseCorruption should not throw Unexpected type of BlockId for ShuffleBlockBatchId Key: SPARK-43242 URL: https://issues.apache.org/jira/browse/SPARK-43242 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 3.2.4 Reporter: Zhang Liang
Some of our spark app throw "Unexpected type of BlockId" exception as shown below According to BlockId.scala, we can found format such as **shuffle_12_5868_518_523** is type of `ShuffleBlockBatchId`, which is not handled properly in `ShuffleBlockFetcherIterator.diagnoseCorruption`. Moreover, the new exception thrown in `diagnose` swallow the real exception in certain cases. Since diagnoseCorruption is always used in exception handling as a sidedish, I think it shouldn't throw exception at all 23/03/07 03:01:24,485 [task-result-getter-1] WARN TaskSetManager: Lost task 104.0 in stage 36.0 (TID 6169): java.lang.IllegalArgumentException: Unexpected type of BlockId, shuffle_12_5868_518_523 at org.apache.spark.storage.ShuffleBlockFetcherIterator.diagnoseCorruption(ShuffleBlockFetcherIterator.scala:1079)at org.apache.spark.storage.BufferReleasingInputStream.$anonfun$tryOrFetchFailedException$1(ShuffleBlockFetcherIterator.scala:1314) at scala.Option.map(Option.scala:230)at org.apache.spark.storage.BufferReleasingInputStream.tryOrFetchFailedException(ShuffleBlockFetcherIterator.scala:1313) at org.apache.spark.storage.BufferReleasingInputStream.read(ShuffleBlockFetcherIterator.scala:1299) at java.io.BufferedInputStream.fill(BufferedInputStream.java:246) at java.io.BufferedInputStream.read1(BufferedInputStream.java:286) at java.io.BufferedInputStream.read(BufferedInputStream.java:345) at java.io.DataInputStream.read(DataInputStream.java:149) at org.sparkproject.guava.io.ByteStreams.read(ByteStreams.java:899) at org.sparkproject.guava.io.ByteStreams.readFully(ByteStreams.java:733) at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$2$$anon$3.next(UnsafeRowSerializer.scala:127) at org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$2$$anon$3.next(UnsafeRowSerializer.scala:110) at scala.collection.Iterator$$anon$11.next(Iterator.scala:496) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29) at org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:40) at scala.collection.Iterator$$anon$10.next(Iterator.scala:461) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7.sort_addToSorter_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:82) at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.advancedStreamed(SortMergeJoinExec.scala:1065) at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.findNextOuterJoinRows(SortMergeJoinExec.scala:1024) at org.apache.spark.sql.execution.joins.OneSideOuterIterator.advanceStream(SortMergeJoinExec.scala:1201) at org.apache.spark.sql.execution.joins.OneSideOuterIterator.advanceNext(SortMergeJoinExec.scala:1240) at org.apache.spark.sql.execution.RowIteratorToScala.hasNext(RowIterator.scala:67) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage9.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225) at org.apache.spark.sql.execution.SortExec.$anonfun$doExecute$1(SortExec.scala:119) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:137) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1510) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) ``` -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org