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Takeshi Yamamuro resolved SPARK-25863. -------------------------------------- Resolution: Fixed Assignee: Takeshi Yamamuro Fix Version/s: 3.0.0 Resolved by https://github.com/apache/spark/pull/23947 > java.lang.UnsupportedOperationException: empty.max at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.updateAndGetCompilationStats(CodeGenerator.scala:1475) > ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- > > Key: SPARK-25863 > URL: https://issues.apache.org/jira/browse/SPARK-25863 > Project: Spark > Issue Type: Bug > Components: Optimizer, Spark Core > Affects Versions: 2.3.1, 2.3.2 > Reporter: Ruslan Dautkhanov > Assignee: Takeshi Yamamuro > Priority: Major > Labels: cache, catalyst, code-generation > Fix For: 3.0.0 > > > Failing task : > {noformat} > An error occurred while calling o2875.collectToPython. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 58 > in stage 21413.0 failed 4 times, most recent failure: Lost task 58.3 in stage > 21413.0 (TID 4057314, pc1udatahad117, executor 431): > java.lang.UnsupportedOperationException: empty.max > at scala.collection.TraversableOnce$class.max(TraversableOnce.scala:229) > at scala.collection.AbstractTraversable.max(Traversable.scala:104) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.updateAndGetCompilationStats(CodeGenerator.scala:1475) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.org$apache$spark$sql$catalyst$expressions$codegen$CodeGenerator$$doCompile(CodeGenerator.scala:1418) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1493) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1490) > at > org.spark_project.guava.cache.LocalCache$LoadingValueReference.loadFuture(LocalCache.java:3599) > at > org.spark_project.guava.cache.LocalCache$Segment.loadSync(LocalCache.java:2379) > at > org.spark_project.guava.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2342) > at org.spark_project.guava.cache.LocalCache$Segment.get(LocalCache.java:2257) > at org.spark_project.guava.cache.LocalCache.get(LocalCache.java:4000) > at org.spark_project.guava.cache.LocalCache.getOrLoad(LocalCache.java:4004) > at > org.spark_project.guava.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:4874) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.compile(CodeGenerator.scala:1365) > at > org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.create(GeneratePredicate.scala:81) > at > org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.create(GeneratePredicate.scala:40) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1321) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1318) > at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:401) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$filteredCachedBatches$1.apply(InMemoryTableScanExec.scala:263) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$filteredCachedBatches$1.apply(InMemoryTableScanExec.scala:262) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:818) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:818) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) > at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) > at org.apache.spark.scheduler.Task.run(Task.scala:109) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748) > {noformat} > > Driver stack trace: > {noformat} > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1609) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1597) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1596) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1596) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) > at scala.Option.foreach(Option.scala:257) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1830) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1779) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1768) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074) > at > org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:363) > at > org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38) > at > org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3195) > at > org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3192) > at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3254) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77) > at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3253) > at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3192) > at sun.reflect.GeneratedMethodAccessor82.invoke(Unknown Source) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:498) > at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) > at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) > at py4j.Gateway.invoke(Gateway.java:282) > at > py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) > at py4j.commands.CallCommand.execute(CallCommand.java:79) > at py4j.GatewayConnection.run(GatewayConnection.java:238) > at java.lang.Thread.run(Thread.java:748) > {noformat} > > Caused by: > {noformat} > Caused by: java.lang.UnsupportedOperationException: empty.max > at > scala.collection.TraversableOnce$class.max(TraversableOnce.scala:229) > at scala.collection.AbstractTraversable.max(Traversable.scala:104) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.updateAndGetCompilationStats(CodeGenerator.scala:1475) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.org$apache$spark$sql$catalyst$expressions$codegen$CodeGenerator$$doCompile(CodeGenerator.scala:1418) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1493) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1490) > at > org.spark_project.guava.cache.LocalCache$LoadingValueReference.loadFuture(LocalCache.java:3599) > at > org.spark_project.guava.cache.LocalCache$Segment.loadSync(LocalCache.java:2379) > at > org.spark_project.guava.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2342) > at > org.spark_project.guava.cache.LocalCache$Segment.get(LocalCache.java:2257) > at org.spark_project.guava.cache.LocalCache.get(LocalCache.java:4000) > at > org.spark_project.guava.cache.LocalCache.getOrLoad(LocalCache.java:4004) > at > org.spark_project.guava.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:4874) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.compile(CodeGenerator.scala:1365) > at > org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.create(GeneratePredicate.scala:81) > at > org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate$.create(GeneratePredicate.scala:40) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1321) > at > org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1318) > at > org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:401) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$filteredCachedBatches$1.apply(InMemoryTableScanExec.scala:263) > at > org.apache.spark.sql.execution.columnar.InMemoryTableScanExec$$anonfun$filteredCachedBatches$1.apply(InMemoryTableScanExec.scala:262) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:818) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:818) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) > at org.apache.spark.scheduler.Task.run(Task.scala:109) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > ... 1 more > {noformat} -- This message was sent by Atlassian JIRA (v7.6.3#76005) 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