如何在Google Cloud Storage上保存Spark Streaming检查点？

时间：2019-05-15 15:06:28

标签： scala google-cloud-platform google-cloud-storage spark-streaming spark-checkpoint

我正在尝试运行Spark结构化流作业并将检查点保存到Google Storage，我有几个作业，一个没有聚合工作完美，但是第二个聚合抛出异常。我发现有人在S3上有类似的检查点问题，因为S3不支持写后语义https://blog.yuvalitzchakov.com/improving-spark-streaming-checkpoint-performance-with-aws-efs/，但GS确实支持，一切应该没问题，如果有人可以分享他们在检查点方面的经验，我会感到很高兴。 

val writeToKafka = stream.writeStream
  .format("kafka")
  .trigger(ProcessingTime(5000))
  .option("kafka.bootstrap.servers", "localhost:29092")
  .option("topic", "test_topic")
  .option("checkpointLocation", "gs://test/check_test/Job1")
  .start()

    Executor task launch worker for task 1] INFO org.apache.kafka.common.utils.AppInfoParser - Kafka version : 2.0.0
[Executor task launch worker for task 1] INFO org.apache.kafka.common.utils.AppInfoParser - Kafka commitId : 3402a8361b734732
[Executor task launch worker for task 1] INFO org.apache.spark.sql.execution.datasources.v2.DataWritingSparkTask - Committed partition 0 (task 1, attempt 0stage 1.0)
[Executor task launch worker for task 1] INFO org.apache.spark.sql.execution.streaming.CheckpointFileManager - Writing atomically to gs://test/check_test/Job1/state/0/0/1.delta using temp file gs://test/check_test/Job1/state/0/0/.1.delta.8a93d644-0d8e-4cb9-82b5-6418b9e63ffd.TID1.tmp
[Executor task launch worker for task 1] ERROR org.apache.spark.TaskContextImpl - Error in TaskCompletionListener
java.lang.NullPointerException
    at com.google.cloud.hadoop.fs.gcs.GoogleHadoopOutputStream.write(GoogleHadoopOutputStream.java:114)
    at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.write(FSDataOutputStream.java:58)
    at java.io.DataOutputStream.write(DataOutputStream.java:107)
    at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.write(FSDataOutputStream.java:58)
    at java.io.DataOutputStream.write(DataOutputStream.java:107)
    at net.jpountz.lz4.LZ4BlockOutputStream.finish(LZ4BlockOutputStream.java:261)
    at net.jpountz.lz4.LZ4BlockOutputStream.close(LZ4BlockOutputStream.java:193)
    at java.io.FilterOutputStream.close(FilterOutputStream.java:159)
    at org.apache.commons.io.IOUtils.closeQuietly(IOUtils.java:303)
    at org.apache.commons.io.IOUtils.closeQuietly(IOUtils.java:274)
    at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider.org$apache$spark$sql$execution$streaming$state$HDFSBackedStateStoreProvider$$cancelDeltaFile(HDFSBackedStateStoreProvider.scala:508)
    at org.apache.spark.sql.execution.streaming.state.HDFSBackedStateStoreProvider$HDFSBackedStateStore.abort(HDFSBackedStateStoreProvider.scala:150)
    at org.apache.spark.sql.execution.streaming.state.package$StateStoreOps$$anonfun$1$$anonfun$apply$1.apply(package.scala:65)
    at org.apache.spark.sql.execution.streaming.state.package$StateStoreOps$$anonfun$1$$anonfun$apply$1.apply(package.scala:64)
    at org.apache.spark.TaskContext$$anon$1.onTaskCompletion(TaskContext.scala:131)
    at org.apache.spark.TaskContextImpl$$anonfun$markTaskCompleted$1.apply(TaskContextImpl.scala:117)
    at org.apache.spark.TaskContextImpl$$anonfun$markTaskCompleted$1.apply(TaskContextImpl.scala:117)
    at org.apache.spark.TaskContextImpl$$anonfun$invokeListeners$1.apply(TaskContextImpl.scala:130)
    at org.apache.spark.TaskContextImpl$$anonfun$invokeListeners$1.apply(TaskContextImpl.scala:128)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:128)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
[Executor task launch worker for task 1] ERROR org.apache.spark.executor.Executor - Exception in task 0.0 in stage 1.0 (TID 1)
org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
[task-result-getter-1] WARN org.apache.spark.scheduler.TaskSetManager - Lost task 0.0 in stage 1.0 (TID 1, localhost, executor driver): org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

[task-result-getter-1] ERROR org.apache.spark.scheduler.TaskSetManager - Task 0 in stage 1.0 failed 1 times; aborting job
[task-result-getter-1] INFO org.apache.spark.scheduler.TaskSchedulerImpl - Removed TaskSet 1.0, whose tasks have all completed, from pool
[dag-scheduler-event-loop] INFO org.apache.spark.scheduler.TaskSchedulerImpl - Cancelling stage 1
[dag-scheduler-event-loop] INFO org.apache.spark.scheduler.TaskSchedulerImpl - Killing all running tasks in stage 1: Stage cancelled
[dag-scheduler-event-loop] INFO org.apache.spark.scheduler.DAGScheduler - ResultStage 1 (start at Job1.scala:53) failed in 9.863 s due to Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1, localhost, executor driver): org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
[stream execution thread for [id = f130d772-fc9e-4b0f-a81e-942af0741ae9, runId = 7dc1cb33-c5f2-4ebe-8707-251de2503ee1]] INFO org.apache.spark.scheduler.DAGScheduler - Job 0 failed: start at Job1.scala:53, took 20.926657 s
[stream execution thread for [id = f130d772-fc9e-4b0f-a81e-942af0741ae9, runId = 7dc1cb33-c5f2-4ebe-8707-251de2503ee1]] ERROR org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec - Data source writer org.apache.spark.sql.execution.streaming.sources.MicroBatchWriter@228cec9e is aborting.
[stream execution thread for [id = f130d772-fc9e-4b0f-a81e-942af0741ae9, runId = 7dc1cb33-c5f2-4ebe-8707-251de2503ee1]] ERROR org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec - Data source writer org.apache.spark.sql.execution.streaming.sources.MicroBatchWriter@228cec9e aborted.
[stream execution thread for [id = f130d772-fc9e-4b0f-a81e-942af0741ae9, runId = 7dc1cb33-c5f2-4ebe-8707-251de2503ee1]] ERROR org.apache.spark.sql.execution.streaming.MicroBatchExecution - Query [id = f130d772-fc9e-4b0f-a81e-942af0741ae9, runId = 7dc1cb33-c5f2-4ebe-8707-251de2503ee1] terminated with error
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$$anonfun$execute$1.apply(SparkPlan.scala:131)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
    at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:296)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3384)
    at org.apache.spark.sql.Dataset$$anonfun$collect$1.apply(Dataset.scala:2783)
    at org.apache.spark.sql.Dataset$$anonfun$collect$1.apply(Dataset.scala:2783)
    at org.apache.spark.sql.Dataset$$anonfun$53.apply(Dataset.scala:3365)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3364)
    at org.apache.spark.sql.Dataset.collect(Dataset.scala:2783)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5$$anonfun$apply$17.apply(MicroBatchExecution.scala:537)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5.apply(MicroBatchExecution.scala:532)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:531)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:198)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:166)
    at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1, localhost, executor driver): org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.doExecute(WriteToDataSourceV2Exec.scala:64)
    ... 35 more
Caused by: org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Exception in thread "main" org.apache.spark.sql.streaming.StreamingQueryException: Writing job aborted.
=== Streaming Query ===
Identifier: [id = f130d772-fc9e-4b0f-a81e-942af0741ae9, runId = 7dc1cb33-c5f2-4ebe-8707-251de2503ee1]
Current Committed Offsets: {}
Current Available Offsets: {KafkaV2[Subscribe[NormalizedEvents]]: {"NormalizedEvents":{"0":46564}}}

Current State: ACTIVE
Thread State: RUNNABLE
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:295)
    at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
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$$anonfun$execute$1.apply(SparkPlan.scala:131)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
    at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
    at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
    at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:296)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3384)
    at org.apache.spark.sql.Dataset$$anonfun$collect$1.apply(Dataset.scala:2783)
    at org.apache.spark.sql.Dataset$$anonfun$collect$1.apply(Dataset.scala:2783)
    at org.apache.spark.sql.Dataset$$anonfun$53.apply(Dataset.scala:3365)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3364)
    at org.apache.spark.sql.Dataset.collect(Dataset.scala:2783)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5$$anonfun$apply$17.apply(MicroBatchExecution.scala:537)
    at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
    at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5.apply(MicroBatchExecution.scala:532)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:531)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:198)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
    at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
    at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:166)
    at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
    at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160)
    at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279)
    ... 1 more
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1, localhost, executor driver): org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.sql.execution.datasources.v2.WriteToDataSourceV2Exec.doExecute(WriteToDataSourceV2Exec.scala:64)
    ... 35 more
Caused by: org.apache.spark.util.TaskCompletionListenerException: null
    at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:138)
    at org.apache.spark.TaskContextImpl.markTaskCompleted(TaskContextImpl.scala:116)
    at org.apache.spark.scheduler.Task.run(Task.scala:137)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
[Thread-1] INFO org.apache.spark.SparkContext - Invoking stop() from shutdown hook
[Thread-1] INFO org.spark_project.jetty.server.AbstractConnector - Stopped Spark@1ce93c18{HTTP/1.1,[http/1.1]}{0.0.0.0:4041}
[Thread-1] INFO org.apache.spark.ui.SparkUI - Stopped Spark web UI at http://10.25.12.222:4041
[dispatcher-event-loop-0] INFO org.apache.spark.MapOutputTrackerMasterEndpoint - MapOutputTrackerMasterEndpoint stopped!
[Thread-1] INFO org.apache.spark.storage.memory.MemoryStore - MemoryStore cleared
[Thread-1] INFO org.apache.spark.storage.BlockManager - BlockManager stopped
[Thread-1] INFO org.apache.spark.storage.BlockManagerMaster - BlockManagerMaster stopped
[dispatcher-event-loop-1] INFO org.apache.spark.scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint - OutputCommitCoordinator stopped!
[Thread-1] INFO org.apache.spark.SparkContext - Successfully stopped SparkContext
[Thread-1] INFO org.apache.spark.util.ShutdownHookManager - Shutdown hook called
[Thread-1] INFO org.apache.spark.util.ShutdownHookManager - Deleting directory /private/var/folders/_t/7m21x7313gs74_yfv4txsr69b8yh87/T/temporaryReader-75fdf46f-7de0-4ca7-9c77-8bd034e4f5a3
[Thread-1] INFO org.apache.spark.util.ShutdownHookManager - Deleting directory /private/var/folders/_t/7m21x7313gs74_yfv4txsr69b8yh87/T/spark-bde783f1-fa66-420f-87e7-5c1895ab7ccc

3 个答案:

答案 0 :(得分：1)

火花流作业检查点指向Google Cloud Storage {{3}}。此修复程序将包含在GCS连接器2.1.4和2.2.0版本中。

答案 1 :(得分：0)

如果至少在2.1.3版（hadoop 2）中在流中进行聚合，则不能将GCS用作检查点存储。如果您的转换不包含任何groupBy，那就很好了，但是如果是这样，您应该将检查点保存在HDFS或其他格式中。

尝试在Spark 2.4.4中将流写入GCS时遇到相同的问题。使用GCS作为写流没有问题，但是当使用GCS作为检查点位置时，我遇到了相同的空指针异常。当我在Google Dataproc上运行spark时，我可以使用节点的dataproc HDFS功能。

答案 2 :(得分：0)

我不得不将代码从私有云移植到gcs。在完成这些之后，我做了一些更改以运行代码

  • 对于gcs，我设置了双重区域，并为其设置了保留策略。 （我知道这很奇怪，但是我发现这对我有用）。虽然我只设置了一天。您也可以根据需要设置生命周期策略。
  • 我用OutputMode.Append代替了Update
  • 我用agg函数替换了flapMapGroupWithState。

例如，这是示例代码

       events.withWatermark(eventTime = "timestamp", delayThreshold = configs(waterMarkConst))
          .groupBy("timestamp", "name").agg(expr("sum(count) as cnt")).select("timestamp", "name", "cnt").toDF().as[(Timestamp, String, Double)]
          .map(record => M(record._2, record._3, record._1))

已被以下代码取代：

events.withWatermark(eventTime = "timestamp", delayThreshold = configs(waterMarkConst))
      .groupByKey(m => m._1 + "." + m._2)
      .flatMapGroupsWithState(OutputMode.Append(), GroupStateTimeout.EventTimeTimeout())(updateSentMetricsAggregatedState)
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