[ https://issues.apache.org/jira/browse/SPARK-34790?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun reassigned SPARK-34790: ------------------------------------- Assignee: hezuojiao > Fail in fetch shuffle blocks in batch when i/o encryption is enabled. > --------------------------------------------------------------------- > > Key: SPARK-34790 > URL: https://issues.apache.org/jira/browse/SPARK-34790 > Project: Spark > Issue Type: Sub-task > Components: Spark Core > Affects Versions: 3.1.1 > Reporter: hezuojiao > Assignee: hezuojiao > Priority: Critical > > When set spark.io.encryption.enabled=true, lots of test cases in > AdaptiveQueryExecSuite will be failed. Fetching shuffle blocks in batch is > incompatible with io encryption. > For example: > After set spark.io.encryption.enabled=true, run the following test suite > which in AdaptiveQueryExecSuite: > > {code:java} > test("SPARK-33494: Do not use local shuffle reader for repartition") { > withSQLConf(SQLConf.ADAPTIVE_EXECUTION_ENABLED.key -> "true") { > val df = spark.table("testData").repartition('key) > df.collect() > // local shuffle reader breaks partitioning and shouldn't be used for > repartition operation > // which is specified by users. > checkNumLocalShuffleReaders(df.queryExecution.executedPlan, > numShufflesWithoutLocalReader = 1) > } > } > {code} > > I got the following error message: > {code:java} > 14:05:52.638 WARN org.apache.spark.scheduler.TaskSetManager: Lost task 1.0 in > stage 2.0 (TID 3) (11.240.37.88 executor driver): > FetchFailed(BlockManagerId(driver, 11.240.37.88, 63574, None), shuffleId=0, > mapIndex=0, mapId=0, reduceId=2, message=14:05:52.638 WARN > org.apache.spark.scheduler.TaskSetManager: Lost task 1.0 in stage 2.0 (TID 3) > (11.240.37.88 executor driver): FetchFailed(BlockManagerId(driver, > 11.240.37.88, 63574, None), shuffleId=0, mapIndex=0, mapId=0, reduceId=2, > message=org.apache.spark.shuffle.FetchFailedException: Stream is corrupted at > org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:772) > at > org.apache.spark.storage.BufferReleasingInputStream.read(ShuffleBlockFetcherIterator.scala:845) > at java.io.BufferedInputStream.fill(BufferedInputStream.java:246) at > java.io.BufferedInputStream.read(BufferedInputStream.java:265) at > java.io.DataInputStream.readInt(DataInputStream.java:387) at > org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$2$$anon$3.readSize(UnsafeRowSerializer.scala:113) > at > org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$2$$anon$3.next(UnsafeRowSerializer.scala:129) > at > org.apache.spark.sql.execution.UnsafeRowSerializerInstance$$anon$2$$anon$3.next(UnsafeRowSerializer.scala:110) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:494) at > scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at > org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29) at > org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:40) > at scala.collection.Iterator$$anon$10.next(Iterator.scala:459) at > org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:345) > at org.apache.spark.rdd.RDD.$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:131) at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:498) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1437) at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:501) at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748)Caused by: java.io.IOException: > Stream is corrupted at > net.jpountz.lz4.LZ4BlockInputStream.refill(LZ4BlockInputStream.java:200) at > net.jpountz.lz4.LZ4BlockInputStream.refill(LZ4BlockInputStream.java:226) at > net.jpountz.lz4.LZ4BlockInputStream.read(LZ4BlockInputStream.java:157) at > org.apache.spark.storage.BufferReleasingInputStream.read(ShuffleBlockFetcherIterator.scala:841) > ... 25 more > ) > {code} > > -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org