A0 at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2403) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2403) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1162) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1162) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1162) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2643) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2585) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2574) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:940) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2227) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2248) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2267) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:490) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:443) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3833) at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2832) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3824) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:109) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3822) at org.apache.spark.sql.Dataset.head(Dataset.scala:2832) at org.apache.spark.sql.Dataset.take(Dataset.scala:3053) at org.apache.spark.sql.Dataset.getRows(Dataset.scala:288) at org.apache.spark.sql.Dataset.showString(Dataset.scala:327) at org.apache.spark.sql.Dataset.show(Dataset.scala:807) at org.apache.spark.sql.Dataset.show(Dataset.scala:766) ... 47 elided Caused by: java.lang.ArrayIndexOutOfBoundsException: 4096 at org.apache.spark.sql.execution.datasources.orc.OrcArrayColumnVector.getArray(OrcArrayColumnVector.java:53) at org.apache.spark.sql.vectorized.ColumnarArray.getArray(ColumnarArray.java:170) at org.apache.spark.sql.vectorized.ColumnarArray.getArray(ColumnarArray.java:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:363) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365) at org.apache.spark.rdd.RDD.iterator(RDD.scala:329) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:136) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:507) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1468) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:510) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745)
> reading nested columns with ORC vectorized reader can cause > ArrayIndexOutOfBoundsException > ------------------------------------------------------------------------------------------ > > Key: SPARK-37728 > URL: https://issues.apache.org/jira/browse/SPARK-37728 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 3.0.3, 3.1.2, 3.2.0 > Reporter: Yimin Yang > Priority: Major > > When spark.sql.orc.enableNestedColumnVectorizedReader is set to true, reading > nested columns of ORC files can cause ArrayIndexOutOfBoundsException. Here is > a simple reproduction: > 1) create an ORC file which contains records of type Array<Array<String>>: > {code:java} > ./bin/spark-shell {code} > {code:java} > case class Item(record: Array[Array[String]]) > val data = new Array[Array[Array[String]]](100) > for (i <- 0 to 99) { > val temp = new Array[Array[String]](50) > for (j <- 0 to 49) { > temp(j) = new Array[String](1000) > for (k <- 0 to 999) { > temp(j)(k) = k.toString > } > } > data(i) = temp > } > val rdd = spark.sparkContext.parallelize(data, 1) > val df = rdd.map(x => Item(x)).toDF > df.write.orc("file:///home/user_name/data"){code} > > 2) read the orc with spark.sql.orc.enableNestedColumnVectorizedReader=true > {code:java} > ./bin/spark-shell --conf spark.sql.orc.enableVectorizedReader=true --conf > spark.sql.codegen.wholeStage=true --conf > spark.sql.orc.enableNestedColumnVectorizedReader=true --conf > spark.sql.orc.columnarReaderBatchSize=4096 {code} > {code:java} > val df = spark.read.orc("file:///home/user_name/data") > df.show(100) {code} > > Then Spark threw ArrayIndexOutOfBoundsException: > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2455) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2404) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2403) > at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) > at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2403) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1162) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1162) > at scala.Option.foreach(Option.scala:407) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1162) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2643) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2585) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2574) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) > at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:940) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2227) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2248) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2267) > at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:490) > at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:443) > at > org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) > at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3833) > at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2832) > at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3824) > at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:109) > at > org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169) > at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95) > at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) > at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3822) > at org.apache.spark.sql.Dataset.head(Dataset.scala:2832) > at org.apache.spark.sql.Dataset.take(Dataset.scala:3053) > at org.apache.spark.sql.Dataset.getRows(Dataset.scala:288) > at org.apache.spark.sql.Dataset.showString(Dataset.scala:327) > at org.apache.spark.sql.Dataset.show(Dataset.scala:807) > at org.apache.spark.sql.Dataset.show(Dataset.scala:766) > ... 47 elided > Caused by: java.lang.ArrayIndexOutOfBoundsException: 4096 > at > org.apache.spark.sql.execution.datasources.orc.OrcArrayColumnVector.getArray(OrcArrayColumnVector.java:53) > at > org.apache.spark.sql.vectorized.ColumnarArray.getArray(ColumnarArray.java:170) > at > org.apache.spark.sql.vectorized.ColumnarArray.getArray(ColumnarArray.java:31) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760) > at > org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:363) > at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:329) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) > at org.apache.spark.scheduler.Task.run(Task.scala:136) > at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:507) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1468) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:510) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > -- This message was sent by Atlassian Jira (v8.20.1#820001) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
