flink: Flink Shell抛出NullPointerException

Question

1. 我使用执行WordCount。它的文件大小为10 of。但是，对于一个100 the的文件，shell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(16 on )上工作。有什么问题吗？

我的代码(改编自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只在一个核心上执行程序。在使用env.getConfig.setParallelism(4)设置并行性并再次运行程序之后，发生了另一个异常：

第一部分：

    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)

第二部分：

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- can . shell中，这个键设置为4，但是我如何在外壳中设置它呢？

Answer 1

你问了两个问题：

1. 为什么print()不适用于大型DataSet？

当您在count()、collect()或print()上使用DataSet时，任务管理器上已分区的所有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来测试或实现小型DataSet。对于大数据，请使用Apache中提供的接收器之一，例如writeAsTextFile(..)。然后，将为每个并行任务创建一个输出文件。

如果您仍然希望将所有数据传输到客户端，则可以通过增加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akka.framesize中设置flink-conf.yaml。缺省值为10485760字节(10 MB)。akka.framesize: 100mb将把它增加到100 MB。

对于Apache 1.0，一些提交者已经考虑取消这一限制，并且已经有一个对大型物化DataSets使用另一种传输方式的拉请求。

1. 什么是任务槽，它们与并行性有什么关系？

Flink的默认配置为每个任务管理器启动一个任务时隙。当您在本地模式下启动Scala时，它只启动一个任务管理器。因此，任务插槽的总数是一个。当您将并行性更改为N时，至少需要N任务槽来并行执行此操作。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，我建议只增加任务插槽的数量。有关更多信息，请参见关于http://flink.apache.org的Flink文档。

编辑：如果运行Shell，则只使用一个任务管理器启动嵌入式Flink集群。您可以使用./bin/start-local.sh启动本地集群，然后使用shell的主机和端口参数(主机: localhost，端口: 6123)连接到它。