Spark 2.4.0 Master понижается - PullRequest
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Spark 2.4.0 Master понижается

0 голосов
/ 27 февраля 2019

Мы работаем с Spark 2.4.0 / Scala 2.11 и запускаем несколько потоковых приложений Spark, слушающих темы Kafka.

Это потоковый API Spark Kafka Direct, у нас запущено 4 потоковых приложения Spark, которые слушают 4 различные темы.

Мы получаем в среднем 10-20 сообщений в секунду.Мастер Спарк выходит из строя через 1-2 часа работы.Исключение дано ниже.Наряду с этим искры также убивают исполнителей.

Это не происходило со Spark 2.1.1, это начиналось со Spark 2.4.0, любая помощь / предложение приветствуется.

Исключение, которое мы видимэто:

Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1713)
    at org.apache.spark.deploy.SparkHadoopUtil.runAsSparkUser(SparkHadoopUtil.scala:64)
    at org.apache.spark.executor.CoarseGrainedExecutorBackend$.run(CoarseGrainedExecutorBackend.scala:188)
    at org.apache.spark.executor.CoarseGrainedExecutorBackend$.main(CoarseGrainedExecutorBackend.scala:281)
    at org.apache.spark.executor.CoarseGrainedExecutorBackend.main(CoarseGrainedExecutorBackend.scala)
Caused by: org.apache.spark.rpc.RpcTimeoutException: Cannot receive any reply from 192.168.43.167:40007 in 120 seconds. This timeout is controlled by spark.rpc.askTimeout
    at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:47)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:62)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:58)
    at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
    at scala.util.Failure$$anonfun$recover$1.apply(Try.scala:216)
    at scala.util.Try$.apply(Try.scala:192)
    at scala.util.Failure.recover(Try.scala:216)
    at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:326)
    at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:326)
    at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:36)
    at org.spark_project.guava.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293)
    at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:136)
    at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:44)
    at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:252)
    at scala.concurrent.Promise$class.complete(Promise.scala:55)
    at scala.concurrent.impl.Promise$DefaultPromise.complete(Promise.scala:157)
    at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:237)
    at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:237)
    at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:36)
    at scala.concurrent.BatchingExecutor$Batch$$anonfun$run$1.processBatch$1(BatchingExecutor.scala:63)
    at scala.concurrent.BatchingExecutor$Batch$$anonfun$run$1.apply$mcV$sp(BatchingExecutor.scala:78)
    at scala.concurrent.BatchingExecutor$Batch$$anonfun$run$1.apply(BatchingExecutor.scala:55)
    at scala.concurrent.BatchingExecutor$Batch$$anonfun$run$1.apply(BatchingExecutor.scala:55)
    at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
    at scala.concurrent.BatchingExecutor$Batch.run(BatchingExecutor.scala:54)
    at scala.concurrent.Future$InternalCallbackExecutor$.unbatchedExecute(Future.scala:601)
    at scala.concurrent.BatchingExecutor$class.execute(BatchingExecutor.scala:106)
    at scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:599)
    at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:44)
    at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:252)
    at scala.concurrent.Promise$class.tryFailure(Promise.scala:112)
    at scala.concurrent.impl.Promise$DefaultPromise.tryFailure(Promise.scala:157)
    at org.apache.spark.rpc.netty.NettyRpcEnv.org$apache$spark$rpc$netty$NettyRpcEnv$$onFailure$1(NettyRpcEnv.scala:206)
    at org.apache.spark.rpc.netty.NettyRpcEnv$$anon$1.run(NettyRpcEnv.scala:243)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
    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)
Caused by: java.util.concurrent.TimeoutException: Cannot receive any reply from 192.168.43.167:40007 in 120 seconds

1 Ответ

0 голосов
/ 28 февраля 2019

Попробуйте увеличить значение spark.rpc.askTimeout до значения, превышающего значение по умолчанию.

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