小贝子编程

flink: Flink Shell throws NullPointerException


  1. 我正在使用 Flink Interactive Shell 来执行 WordCount。它适用于10MB的文件大小。但是对于一个100MB的文件，shell会抛出一个NullPointerException：

：

java.lang.NullPointerException
    at org.apache.flink.api.common.accumulators.SerializedListAccumulator.deserializeList(SerializedListAccumulator.java:93)
    at org.apache.flink.api.scala.DataSet.collect(DataSet.scala:549)
    at .<init>(<console>:22)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:734)
at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:983)
at scala.tools.nsc.interpreter.IMain.loadAndRunReq$1(IMain.scala:573)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:604)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:568)
at scala.tools.nsc.interpreter.ILoop.reallyInterpret$1(ILoop.scala:760)
at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:805)
at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:717)
at scala.tools.nsc.interpreter.ILoop.processLine$1(ILoop.scala:581)
at scala.tools.nsc.interpreter.ILoop.innerLoop$1(ILoop.scala:588)
at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:591)
at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(ILoop.scala:601)
at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(ILoop.scala:598)
at scala.reflect.io.Streamable$Chars$class.applyReader(Streamable.scala:104)
at scala.reflect.io.File.applyReader(File.scala:82)
at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ILoop.scala:598)
at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1.apply(ILoop.scala:598)
at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1.apply(ILoop.scala:598)
at scala.tools.nsc.interpreter.ILoop.savingReplayStack(ILoop.scala:130)
at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1.apply(ILoop.scala:597)
at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1.apply(ILoop.scala:597)
at scala.tools.nsc.interpreter.ILoop.savingReader(ILoop.scala:135)
at scala.tools.nsc.interpreter.ILoop.interpretAllFrom(ILoop.scala:596)
at scala.tools.nsc.interpreter.ILoop$$anonfun$loadCommand$1.apply(ILoop.scala:660)
at scala.tools.nsc.interpreter.ILoop$$anonfun$loadCommand$1.apply(ILoop.scala:659)
at scala.tools.nsc.interpreter.ILoop.withFile(ILoop.scala:653)
at scala.tools.nsc.interpreter.ILoop.loadCommand(ILoop.scala:659)
at scala.tools.nsc.interpreter.ILoop$$anonfun$standardCommands$7.apply(ILoop.scala:262)
at scala.tools.nsc.interpreter.ILoop$$anonfun$standardCommands$7.apply(ILoop.scala:262)
at scala.tools.nsc.interpreter.LoopCommands$LineCmd.apply(LoopCommands.scala:81)
at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:712)
at scala.tools.nsc.interpreter.ILoop.processLine$1(ILoop.scala:581)
at scala.tools.nsc.interpreter.ILoop.innerLoop$1(ILoop.scala:588)
at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:591)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:882)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837)
at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:837)
at org.apache.flink.api.scala.FlinkShell$.startShell(FlinkShell.scala:84)
at org.apache.flink.api.scala.FlinkShell$.main(FlinkShell.scala:54)
at org.apache.flink.api.scala.FlinkShell.main(FlinkShell.scala)

我在Linux系统(16MB RAM(上工作。那里可能有什么问题？

我的代码(改编自 https://ci.apache.org/projects/flink/flink-docs-release-0.9/quickstart/scala_api_quickstart.html(：

 var filename = new String(<myFileName>)
 var text = env.readTextFile(filename)
 var counts = text.flatMap { _.toLowerCase.split("\W+") }.map { (_, 1)   }.groupBy(0).sum(1)
 var result = counts.collect()
  1. 我还注意到，flink 只在一个内核上执行程序。在使用 env.getConfig.setParallelism(4( 设置并行性并再次运行程序后，又发生了另一个异常：

篇一：

    org.apache.flink.client.program.ProgramInvocationException: The program execution failed: Job execution failed.
    at org.apache.flink.client.program.Client.run(Client.java:413)
    at org.apache.flink.client.program.Client.run(Client.java:356)
    at org.apache.flink.client.program.Client.run(Client.java:349)
    at org.apache.flink.client.RemoteExecutor.executePlanWithJars(RemoteExecutor.java:89)
    at org.apache.flink.client.RemoteExecutor.executePlan(RemoteExecutor.java:82)
    at org.apache.flink.api.java.ScalaShellRemoteEnvironment.execute(ScalaShellRemoteEnvironment.java:68)
    at org.apache.flink.api.java.ExecutionEnvironment.execute(ExecutionEnvironment.java:789)
    at org.apache.flink.api.scala.ExecutionEnvironment.execute(ExecutionEnvironment.scala:576)
    at org.apache.flink.api.scala.DataSet.collect(DataSet.scala:544)
    at .<init>(<console>:28)
    at .<clinit>(<console>)
    at .<init>(<console>:7)
    at .<clinit>(<console>)
    at $print(<console>)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:734)
    at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:983)
    at scala.tools.nsc.interpreter.IMain.loadAndRunReq$1(IMain.scala:573)
    at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:604)
    at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:568)
    at scala.tools.nsc.interpreter.ILoop.reallyInterpret$1(ILoop.scala:760)
    at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:805)
    at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:717)
    at scala.tools.nsc.interpreter.ILoop.processLine$1(ILoop.scala:581)
    at scala.tools.nsc.interpreter.ILoop.innerLoop$1(ILoop.scala:588)
    at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:591)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(ILoop.scala:601)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1$$anonfun$apply$mcV$sp$2.apply(ILoop.scala:598)
    at scala.reflect.io.Streamable$Chars$class.applyReader(Streamable.scala:104)
    at scala.reflect.io.File.applyReader(File.scala:82)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ILoop.scala:598)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1.apply(ILoop.scala:598)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1$$anonfun$apply$mcV$sp$1.apply(ILoop.scala:598)
    at scala.tools.nsc.interpreter.ILoop.savingReplayStack(ILoop.scala:130)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1.apply(ILoop.scala:597)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$interpretAllFrom$1.apply(ILoop.scala:597)
    at scala.tools.nsc.interpreter.ILoop.savingReader(ILoop.scala:135)
    at scala.tools.nsc.interpreter.ILoop.interpretAllFrom(ILoop.scala:596)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$loadCommand$1.apply(ILoop.scala:660)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$loadCommand$1.apply(ILoop.scala:659)
    at scala.tools.nsc.interpreter.ILoop.withFile(ILoop.scala:653)
    at scala.tools.nsc.interpreter.ILoop.loadCommand(ILoop.scala:659)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$standardCommands$7.apply(ILoop.scala:262)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$standardCommands$7.apply(ILoop.scala:262)
    at scala.tools.nsc.interpreter.LoopCommands$LineCmd.apply(LoopCommands.scala:81)
    at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:712)
    at scala.tools.nsc.interpreter.ILoop.processLine$1(ILoop.scala:581)
    at scala.tools.nsc.interpreter.ILoop.innerLoop$1(ILoop.scala:588)
    at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:591)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:882)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:837)
    at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
    at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:837)
    at org.apache.flink.api.scala.FlinkShell$.startShell(FlinkShell.scala:84)
    at org.apache.flink.api.scala.FlinkShell$.main(FlinkShell.scala:54)
    at org.apache.flink.api.scala.FlinkShell.main(FlinkShell.scala)

篇二：

Caused by: org.apache.flink.runtime.client.JobExecutionException: Job execution failed.
    at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$receiveWithLogMessages$1.applyOrElse(JobManager.scala:314)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
    at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
    at org.apache.flink.runtime.ActorLogMessages$$anon$1.apply(ActorLogMessages.scala:43)
    at org.apache.flink.runtime.ActorLogMessages$$anon$1.apply(ActorLogMessages.scala:29)
    at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
    at org.apache.flink.runtime.ActorLogMessages$$anon$1.applyOrElse(ActorLogMessages.scala:29)
    at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
    at org.apache.flink.runtime.jobmanager.JobManager.aroundReceive(JobManager.scala:92)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
    at akka.actor.ActorCell.invoke(ActorCell.scala:487)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:254)
    at akka.dispatch.Mailbox.run(Mailbox.scala:221)
    at akka.dispatch.Mailbox.exec(Mailbox.scala:231)
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: org.apache.flink.runtime.jobmanager.scheduler.NoResourceAvailableException: Not enough free slots available to run the job. You can decrease the operator parallelism or increase the number of slots per TaskManager in the configuration. Task to schedule: < Attempt #0 (CHAIN DataSource (at .<init>(<console>:26) (org.apache.flink.api.java.io.TextInputFormat)) -> FlatMap (FlatMap at .<init>(<console>:27)) -> Map (Map at .<init>(<console>:27)) -> Combine(SUM(1)) (2/4)) @ (unassigned) - [SCHEDULED] > with groupID < fc507fbb50fea681c726ca1d824c7577 > in sharing group < SlotSharingGroup [fc507fbb50fea681c726ca1d824c7577, fb90f780c9d5a4a9dbf983cb06bec946, 52b8abe5a21ed808f0473a599d89f046] >. Resources available to scheduler: Number of instances=1, total number of slots=1, available slots=0
    at org.apache.flink.runtime.jobmanager.scheduler.Scheduler.scheduleTask(Scheduler.java:250)
    at org.apache.flink.runtime.jobmanager.scheduler.Scheduler.scheduleImmediately(Scheduler.java:126)
    at org.apache.flink.runtime.executiongraph.Execution.scheduleForExecution(Execution.java:271)
    at org.apache.flink.runtime.executiongraph.ExecutionVertex.scheduleForExecution(ExecutionVertex.java:430)
    at org.apache.flink.runtime.executiongraph.ExecutionJobVertex.scheduleAll(ExecutionJobVertex.java:307)
    at org.apache.flink.runtime.executiongraph.ExecutionGraph.scheduleForExecution(ExecutionGraph.java:508)
    at org.apache.flink.runtime.jobmanager.JobManager.org$apache$flink$runtime$jobmanager$JobManager$$submitJob(JobManager.scala:606)
    at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$receiveWithLogMessages$1.applyOrElse(JobManager.scala:190)
    ... 18 more

这是否意味着taskmanager.numberOfTaskSlots？在我的 flink-conf.yaml 中，这个键设置为 4。但是如何在外壳中设置它呢？

你问了两个问题：

  1. 为什么print()不适用于大DataSet？

当你在DataSet上使用count()、collect()或print()时，所有在任务管理器上分区的数据都必须通过作业管理器传输到客户端。最好只使用这些方法进行测试或实现小DataSet。对于大数据，请使用 Apache Flink 中提供的接收器之一，例如 writeAsTextFile(..) .对于每个并行任务，将创建一个输出文件。

如果您仍想将所有数据传输到客户端，可以通过增加 Akka 的帧大小来实现。Akka 是 Flink 在引擎盖下使用的消息传递库。为此，请在 flink-conf.yaml 中设置akka.framesize。默认值为 10485760 字节 (10 MB(。 akka.framesize: 100mb会将其增加到 100 MB。

对于 Apache Flink 1.0，一些提交者已经考虑删除此限制，并且已经有一个拉取请求对大型物化数据集使用另一种传输方式。

  1. 什么是任务槽，它们与并行性有何关系？

Flink 的默认配置为每个任务管理器启动一个任务槽。当你在本地模式下启动 Scala shell 时，它只会启动一个任务管理器。因此，任务槽的总数为 1。将并行度更改为 N 时，至少需要 N 个任务槽才能并行执行此操作。因此，要么增加flink-conf.yaml中的任务槽数，要么启动其他任务管理器。如果您只是在本地运行，我建议您简单地增加任务槽的数量。有关更多信息，请参阅 Flink 关于 http://flink.apache.org 的文档。

编辑：如果你运行 Scala-Shell，一个嵌入式的 Flink 集群只用一个任务管理器启动。您可以使用 ./bin/start-local.sh 启动本地集群，然后使用 Scala shell 的主机和端口参数(主机：localhost，端口：6123(连接到该集群。

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