Может кто-нибудь помочь мне понять причину этой ошибки:
Exception in thread "stream execution thread for alert[id = 901ebc8b-6ae7-467f-86ff, runId = 4342a5fd-9407-4c21-91da]" org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:355)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:92)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:76)
at org.apache.spark.sql.execution.streaming.state.StateStoreCoordinatorRef.deactivateInstances(StateStoreCoordinator.scala:108)
at org.apache.spark.sql.streaming.StreamingQueryManager.notifyQueryTermination(StreamingQueryManager.scala:399)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anonfun$org$apache$spark$sql$execution$streaming$StreamExecution$$runStream$2.apply(StreamExecution.scala:344)
at org.apache.spark.util.UninterruptibleThread.runUninterruptibly(UninterruptibleThread.scala:77)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:325)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:208)
Caused by: org.apache.spark.rpc.RpcEnvStoppedException: RpcEnv already stopped.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:158)
at org.apache.spark.rpc.netty.Dispatcher.postLocalMessage(Dispatcher.scala:135)
at org.apache.spark.rpc.netty.NettyRpcEnv.ask(NettyRpcEnv.scala:229)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.ask(NettyRpcEnv.scala:523)
at org.apache.spark.rpc.RpcEndpointRef.askSync(RpcEndpointRef.scala:91)
... 7 more
Конфигурации кластера:
Время выполнения блоков данных 5.5 LTS
Scala 2.11
Spark 2.4.3
Драйвер: память 64 ГБ, 16 ядер, 3DBU
Работники: память 64 ГБ, 16 ядер, 3DBU (2-4 рабочих, автоматическое масштабирование)
есть 3 потоковых запроса, выполняющихся параллельно, как определено в fairscheduler. xml file:
<allocations>
<pool name="default">
<schedulingMode>FIFO</schedulingMode>
<weight>2</weight>
<minShare>2</minShare>
</pool>
<pool name="cook">
<schedulingMode>FAIR</schedulingMode>
<weight>1</weight>
<minShare>5</minShare>
</pool>
<pool name="score">
<schedulingMode>FAIR</schedulingMode>
<weight>1</weight>
<minShare>5</minShare>
</pool>
<pool name="alert">
<schedulingMode>FAIR</schedulingMode>
<weight>1</weight>
<minShare>5</minShare>
</pool>
</allocations>
Конфигурации Spark:
spark.sql.autoBroadcastJoinThreshold=-1
spark.sql.broadcastTimeout=1200
spark.executor.instances=4
spark.executor.cores=16
spark.executor.memory=29g
spark.sql.shuffle.partitions=32
spark.default.parallelism=32
spark.driver.maxResultSize=25g
spark.scheduler.mode=FAIR
spark.scheduler.allocation.file=/dbfs/config/fairscheduler.xml