[ https://issues.apache.org/jira/browse/SPARK-31931?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Adrian Jones updated SPARK-31931: --------------------------------- Attachment: spark-structured-streaming-error > When using GCS as checkpoint location for Structured Streaming aggregation > pipeline, the Spark writing job is aborted > --------------------------------------------------------------------------------------------------------------------- > > Key: SPARK-31931 > URL: https://issues.apache.org/jira/browse/SPARK-31931 > Project: Spark > Issue Type: Bug > Components: Structured Streaming > Affects Versions: 2.4.5 > Environment: GCP Dataproc 1.5 Debian 10 (Hadoop 2.10.0, Spark 2.4.5, > Cloud Storage Connector hadoop2.2.1.3, Scala 2.12.10) > Reporter: Adrian Jones > Priority: Blocker > Attachments: spark-structured-streaming-error > > > Structured streaming checkpointing does not work with Google Cloud Storage > when there are aggregations included in the streaming pipeline. > Using GCS as the external store works fine when there are no aggregations > present in the pipeline (i.e. groupBy); however, once an aggregation is > introduced, the below error is thrown. > The error is only thrown when aggregating and pointing checkpointLocation to > GCS. The exact code works fine when pointing checkpointLocation to HDFS. > Is it expected for GCS to function as a checkpoint location for aggregated > pipelines? Are efforts currently in progress to enable this? Is it on a > roadmap? > _org.apache.spark.sql.streaming.StreamingQueryException: Query [id = > 612a550b-992b-41cb-82f9-a95c12c51379, runId = > 90a8e64a-5f64-4bd0-90e7-5df14630c577] terminated with exception: Writing job > aborted.```org.apache.spark.sql.streaming.StreamingQueryException: Query [id > = 612a550b-992b-41cb-82f9-a95c12c51379, runId = > 90a8e64a-5f64-4bd0-90e7-5df14630c577] terminated with exception: Writing job > aborted. at > org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:302) > at > org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:193)Caused > by: org.apache.spark.SparkException: Writing job aborted. at > org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.doExecute(WriteToDataSourceV2Exec.scala:92) > at > org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:131) > at > org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:155) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152) > at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127) at > org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247) > at > org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:296) > at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3389) at > org.apache.spark.sql.Dataset.$anonfun$collect$1(Dataset.scala:2788) at > org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:3370) at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:80) > at > org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75) > at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3370) at > org.apache.spark.sql.Dataset.collect(Dataset.scala:2788) at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$15(MicroBatchExecution.scala:540) > at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:80) > at > org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:127) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:75) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$14(MicroBatchExecution.scala:536) > at > org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:351) > at > org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:349) > at > org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:535) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:198) > at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) > at > org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:351) > at > org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:349) > at > org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:166) > at > org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160) > at > org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:281) > ... 1 moreCaused by: org.apache.spark.SparkException: Job aborted due to > stage failure: Task 2 in stage 1.0 failed 4 times, most recent failure: Lost > task 2.3 in stage 1.0 (TID 12, > spark-structured-streaming-w-0.c.pso-wmt-sandbox.internal, executor 1): > org.apache.spark.util.TaskCompletionListenerException: null at > org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138) > at > org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:117) > at org.apache.spark.scheduler.Task.run(Task.scala:139) at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:411) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) 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)_ > _Driver stacktrace: at > org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:1892) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1880) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1879) > 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:1879) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:927) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:927) > at scala.Option.foreach(Option.scala:407) at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:927) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2113) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2062) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2051) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:738) at > org.apache.spark.SparkContext.runJob(SparkContext.scala:2061) at > org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.doExecute(WriteToDataSourceV2Exec.scala:64) > ... 34 moreCaused by: > org.apache.spark.util.TaskCompletionListenerException: null at > org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138) > at > org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:117) > at org.apache.spark.scheduler.Task.run(Task.scala:139) at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:411) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748)_ -- 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