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jupyter-notebook 以yarn模式运行出现的问题及解决

时间:2021-03-16 04:28:33

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jupyter-notebook 以yarn模式运行出现的问题及解决

jupyter-notebook 以yarn模式运行出现的问题及解决

原创小白programmer 最后发布于-11-21 10:53:01 阅读数 519 收藏

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jupyter-notebook 以yarn模式运行的出现的问题及解决方法

之前用pyspark虚拟机只跑了单机程序,现在想试试分布式运算。

在做之前找了书和博客来看,总是有各种各样的问题,无法成功。现在特记录一下过程:

这里一共有两个虚拟机,一个做master,一个做slave1

虚拟机slave1安装spark

slave1之前已经安装了hadoop,并且可以成功进行Hadoop集群运算。这里就不多说了。

将master的spark安装包复制到slave1,

(1)进入到spark/conf文件夹中,将slaves.template复制成slaves,在里面添加slave1

(2)增加路径到/etc/profile

master与slave1都要做(1),(2)的步骤

slave1安装anaconda

可以用scp直接将master的anaconda复制过来,接下来修改/etc/profile就可。上面的图已经显示了修改的内容

启动,这时候遇到了好多问题

在master终端输入start-all.sh,使用jps查看,master和slave1都能正常启动

在master终端输入

HADOOP_CONF_DIR=/hadoop/hadoop/etc/hadoop PYSPARK_DRIVER_PYTHON="jupyter" PYSPARK_DRIVER_PYTHON_OPTS="notebook" MASTER=yarn-client pyspark

看资料说,如果没有在spark.env.sh中配置HADOOP_CONF_DIR,需要像上面代码在终端写出。这时候,jupyter-notebook可以成功启动,但是我在其中写入sc.master看它是何种模式运行时,却给我报了好多错误

[root@master home]#HADOOP_CONF_IR=/hadoop/hadoop/etc/hadoop PYSPARK_DRIVER_PYTHON="jupyter"

PYSPARK_DRIVER_PYTHON_OPTS="notebook" pyspark

[I 18:58:24.475 NotebookApp]

[nb_conda_kernels] enabled, 2 kernels found

[I 18:58:25.101 NotebookApp] ✓ nbpresent HTML export ENABLED

[W 18:58:25.101 NotebookApp] ✗ nbpresent PDF export DISABLED: No module named 'nbbrowserpdf'

[I 18:58:25.163 NotebookApp]

[nb_anacondacloud] enabled

[I 18:58:25.167 NotebookApp] [nb_conda] enabled

[I 18:58:25.167 NotebookApp] Serving

notebooks from local directory: /home

[I 18:58:25.167 NotebookApp] 0 active

kernels

[I 18:58:25.168 NotebookApp] The Jupyter

Notebook is running at: http://localhost:8888/

[I 18:58:25.168 NotebookApp] Use Control-C

to stop this server and shut down all kernels (twice to skip confirmation).

[I 18:58:33.844 NotebookApp] Kernel

started: c15aabde-b441-45f2-b78d-9933e6534c27

Exception in thread "main"

java.lang.Exception: When running with master 'yarn-client' either

HADOOP_CONF_DIR or YARN_CONF_DIR must be set in the environment.

at

org.apache.spark.deploy.SparkSubmitArguments.validateSubmitArguments(SparkSubmitArguments.scala:263)

at

org.apache.spark.deploy.SparkSubmitArguments.validateArguments(SparkSubmitArguments.scala:240)

at

org.apache.spark.deploy.SparkSubmitArguments.<init>(SparkSubmitArguments.scala:116)

at

org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112)

at

org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

[IPKernelApp] WARNING | Unknown error in

handling PYTHONSTARTUP file /hadoop/spark/python/pyspark/shell.py:

[I 19:00:33.829 NotebookApp] Saving file at

/Untitled2.ipynb

[I 19:00:57.754 NotebookApp] Creating new

notebook in

[I 19:00:59.174 NotebookApp] Kernel

started: ebfbdfd5-2343-4149-9fef-28877967d6c6

Exception in thread "main"

java.lang.Exception: When running with master 'yarn-client' either

HADOOP_CONF_DIR or YARN_CONF_DIR must be set in the environment.

at

org.apache.spark.deploy.SparkSubmitArguments.validateSubmitArguments(SparkSubmitArguments.scala:263)

at

org.apache.spark.deploy.SparkSubmitArguments.validateArguments(SparkSubmitArguments.scala:240)

at

org.apache.spark.deploy.SparkSubmitArguments.<init>(SparkSubmitArguments.scala:116)

at

org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112)

at

org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

[IPKernelApp] WARNING | Unknown error in

handling PYTHONSTARTUP file /hadoop/spark/python/pyspark/shell.py:

[I 19:01:12.315 NotebookApp] Saving file at

/Untitled3.ipynb

^C[I 19:01:15.971 NotebookApp] interrupted

Serving notebooks from local directory:

/home

2 active kernels

The Jupyter Notebook is running at:

http://localhost:8888/

Shutdown this notebook server (y/[n])? y

[C 19:01:17.674 NotebookApp] Shutdown

confirmed

[I 19:01:17.675 NotebookApp] Shutting down

kernels

[I 19:01:18.189 NotebookApp] Kernel

shutdown: ebfbdfd5-2343-4149-9fef-28877967d6c6

[I 19:01:18.190 NotebookApp] Kernel

shutdown: c15aabde-b441-45f2-b78d-9933e6534c27

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通过日志显示:

Exception in thread "main" java.lang.Exception: When running with master 'yarn-client' either HADOOP_CONF_DIR or YARN_CONF_DIR must be set in the environment.

1

于是配置spark.env.sh

再次运行:

[root@master conf]#

HADOOP_CONF_DIR=/hadoop/hadoop/etc/hadoop pyspark --master yarn --deploy-mode

client

[TerminalIPythonApp] WARNING | Subcommand

`ipython notebook` is deprecated and will be removed in future versions.

[TerminalIPythonApp] WARNING | You likely

want to use `jupyter notebook` in the future

[I 19:15:28.816 NotebookApp]

[nb_conda_kernels] enabled, 2 kernels found

[I 19:15:28.923 NotebookApp] ✓ nbpresent HTML export ENABLED

[W 19:15:28.923 NotebookApp] ✗ nbpresent PDF export DISABLED: No module named 'nbbrowserpdf'

[I 19:15:28.986 NotebookApp]

[nb_anacondacloud] enabled

[I 19:15:28.989 NotebookApp] [nb_conda]

enabled

[I 19:15:28.990 NotebookApp] Serving

notebooks from local directory: /hadoop/spark/conf

[I 19:15:28.990 NotebookApp] 0 active

kernels

[I 19:15:28.990 NotebookApp] The Jupyter

Notebook is running at: http://localhost:8888/

[I 19:15:28.990 NotebookApp] Use Control-C

to stop this server and shut down all kernels (twice to skip confirmation).

[I 19:15:44.862 NotebookApp] Creating new

notebook in

[I 19:15:45.742 NotebookApp] Kernel

started: 98d8605a-804a-47af-83fb-2efc8b5a3d60

Setting default log level to

"WARN".

To adjust logging level use

sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).

18/11/20 19:15:48 WARN

util.NativeCodeLoader: Unable to load native-hadoop library for your

platform... using builtin-java classes where applicable

18/11/20 19:15:51 WARN yarn.Client: Neither

spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading

libraries under SPARK_HOME.

[W 19:15:55.943 NotebookApp] Timeout

waiting for kernel_info reply from 98d8605a-804a-47af-83fb-2efc8b5a3d60

18/11/20 19:16:11 ERROR spark.SparkContext:

Error initializing SparkContext.

org.apache.spark.SparkException: Yarn

application has already ended! It might have been killed or unable to launch

application master.

at

org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:85)

at

org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)

at

org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173)

at

org.apache.spark.SparkContext.<init>(SparkContext.scala:509)

at

org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)

at

sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)

at

java.lang.reflect.Constructor.newInstance(Constructor.java:423)

at

py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)

at

py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

at

py4j.Gateway.invoke(Gateway.java:236)

at

mands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)

at

mands.ConstructorCommand.execute(ConstructorCommand.java:69)

at

py4j.GatewayConnection.run(GatewayConnection.java:214)

at

java.lang.Thread.run(Thread.java:748)

18/11/20 19:16:11 ERROR

client.TransportClient: Failed to send RPC 7790789781121901013 to

/192.168.127.131:55928: java.nio.channels.ClosedChannelException

java.nio.channels.ClosedChannelException

at

ty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

18/11/20 19:16:11 ERROR

cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Sending

RequestExecutors(0,0,Map(),Set()) to AM was unsuccessful

java.io.IOException: Failed to send RPC

7790789781121901013 to /192.168.127.131:55928:

java.nio.channels.ClosedChannelException

at

org.work.client.TransportClient.lambda$sendRpc$2(TransportClient.java:237)

at

ty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)

at

ty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)

at

ty.util.concurrent.DefaultPromise.access$000(DefaultPromise.java:34)

at

ty.util.concurrent.DefaultPromise$1.run(DefaultPromise.java:431)

at

ty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)

at

ty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)

at

ty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)

at

ty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)

at

java.lang.Thread.run(Thread.java:748)

Caused by: java.nio.channels.ClosedChannelException

at

ty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

18/11/20 19:16:11 ERROR util.Utils:

Uncaught exception in thread Thread-2

org.apache.spark.SparkException: Exception

thrown in awaitResult:

at

org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)

at

org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)

at

org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.requestTotalExecutors(CoarseGrainedSchedulerBackend.scala:551)

at

org.apache.spark.scheduler.cluster.YarnSchedulerBackend.stop(YarnSchedulerBackend.scala:93)

at

org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.stop(YarnClientSchedulerBackend.scala:151)

at

org.apache.spark.scheduler.TaskSchedulerImpl.stop(TaskSchedulerImpl.scala:517)

at

org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1652)

at

org.apache.spark.SparkContext$$anonfun$stop$8.apply$mcV$sp(SparkContext.scala:1921)

at

org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1317)

at

org.apache.spark.SparkContext.stop(SparkContext.scala:1920)

at

org.apache.spark.SparkContext.<init>(SparkContext.scala:587)

at

org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)

at

sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)

at

java.lang.reflect.Constructor.newInstance(Constructor.java:423)

at

py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)

at

py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

at

py4j.Gateway.invoke(Gateway.java:236)

at

mands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)

at

mands.ConstructorCommand.execute(ConstructorCommand.java:69)

at

py4j.GatewayConnection.run(GatewayConnection.java:214)

at

java.lang.Thread.run(Thread.java:748)

Caused by: java.io.IOException: Failed to

send RPC 7790789781121901013 to /192.168.127.131:55928:

java.nio.channels.ClosedChannelException

at

org.work.client.TransportClient.lambda$sendRpc$2(TransportClient.java:237)

at

ty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)

at

ty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)

at

ty.util.concurrent.DefaultPromise.access$000(DefaultPromise.java:34)

at

ty.util.concurrent.DefaultPromise$1.run(DefaultPromise.java:431)

at

ty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)

at

ty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)

at

ty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)

at

ty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)

...

1 more

Caused by:

java.nio.channels.ClosedChannelException

at

ty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

18/11/20 19:16:11 WARN metrics.MetricsSystem:

Stopping a MetricsSystem that is not running

18/11/20 19:16:11 WARN spark.SparkContext:

Another SparkContext is being constructed (or threw an exception in its constructor). This may indicate an error, since only one

SparkContext may be running in this JVM (see SPARK-2243). The other

SparkContext was created at:

org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)

sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native

Method)

sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)

sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)

java.lang.reflect.Constructor.newInstance(Constructor.java:423)

py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)

py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

py4j.Gateway.invoke(Gateway.java:236)

mands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)

mands.ConstructorCommand.execute(ConstructorCommand.java:69)

py4j.GatewayConnection.run(GatewayConnection.java:214)

java.lang.Thread.run(Thread.java:748)

18/11/20 19:16:11 WARN yarn.Client: Neither

spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading

libraries under SPARK_HOME.

18/11/20 19:16:29 ERROR spark.SparkContext:

Error initializing SparkContext.

org.apache.spark.SparkException: Yarn

application has already ended! It might have been killed or unable to launch

application master.

at

org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:85)

at

org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:62)

at

org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:173)

at

org.apache.spark.SparkContext.<init>(SparkContext.scala:509)

at

org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)

at

sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)

at

java.lang.reflect.Constructor.newInstance(Constructor.java:423)

at

py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)

at

py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

at

py4j.Gateway.invoke(Gateway.java:236)

at

mands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)

at

mands.ConstructorCommand.execute(ConstructorCommand.java:69)

at

py4j.GatewayConnection.run(GatewayConnection.java:214)

at

java.lang.Thread.run(Thread.java:748)

18/11/20 19:16:29 ERROR

client.TransportClient: Failed to send RPC 6243011927050432229 to

/192.168.127.131:59702: java.nio.channels.ClosedChannelException

java.nio.channels.ClosedChannelException

at

ty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

18/11/20 19:16:29 ERROR

cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Sending

RequestExecutors(0,0,Map(),Set()) to AM was unsuccessful

java.io.IOException: Failed to send RPC 6243011927050432229

to /192.168.127.131:59702: java.nio.channels.ClosedChannelException

at

org.work.client.TransportClient.lambda$sendRpc$2(TransportClient.java:237)

at

ty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)

at

ty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)

at

ty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:420)

at

ty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:122)

at

ty.channel.AbstractChannel$AbstractUnsafe.safeSetFailure(AbstractChannel.java:852)

at

ty.channel.AbstractChannel$AbstractUnsafe.write(AbstractChannel.java:738)

at

ty.channel.DefaultChannelPipeline$HeadContext.write(DefaultChannelPipeline.java:1251)

at

ty.channel.AbstractChannelHandlerContext.invokeWrite0(AbstractChannelHandlerContext.java:733)

at

ty.channel.AbstractChannelHandlerContext.invokeWrite(AbstractChannelHandlerContext.java:725)

at

ty.channel.AbstractChannelHandlerContext.access$1900(AbstractChannelHandlerContext.java:35)

at

ty.channel.AbstractChannelHandlerContext$AbstractWriteTask.write(AbstractChannelHandlerContext.java:1062)

at

ty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:1116)

at

ty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:1051)

at

ty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)

at

ty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)

at

ty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)

at

ty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)

at

java.lang.Thread.run(Thread.java:748)

Caused by:

java.nio.channels.ClosedChannelException

at

ty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

18/11/20 19:16:29 ERROR util.Utils:

Uncaught exception in thread Thread-2

org.apache.spark.SparkException: Exception

thrown in awaitResult:

at

org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)

at

org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)

at

org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.requestTotalExecutors(CoarseGrainedSchedulerBackend.scala:551)

at

org.apache.spark.scheduler.cluster.YarnSchedulerBackend.stop(YarnSchedulerBackend.scala:93)

at

org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.stop(YarnClientSchedulerBackend.scala:151)

at

org.apache.spark.scheduler.TaskSchedulerImpl.stop(TaskSchedulerImpl.scala:517)

at

org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1652)

at

org.apache.spark.SparkContext$$anonfun$stop$8.apply$mcV$sp(SparkContext.scala:1921)

at

org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1317)

at

org.apache.spark.SparkContext.stop(SparkContext.scala:1920)

at

org.apache.spark.SparkContext.<init>(SparkContext.scala:587)

at

org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

at

sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)

at

sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)

at

java.lang.reflect.Constructor.newInstance(Constructor.java:423)

at

py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)

at

py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

at

py4j.Gateway.invoke(Gateway.java:236)

at

mands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)

at

mands.ConstructorCommand.execute(ConstructorCommand.java:69)

at

py4j.GatewayConnection.run(GatewayConnection.java:214)

at

java.lang.Thread.run(Thread.java:748)

Caused by: java.io.IOException: Failed to

send RPC 6243011927050432229 to /192.168.127.131:59702:

java.nio.channels.ClosedChannelException

at

org.work.client.TransportClient.lambda$sendRpc$2(TransportClient.java:237)

at

ty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)

at

ty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)

at

ty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:420)

at

ty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:122)

at

ty.channel.AbstractChannel$AbstractUnsafe.safeSetFailure(AbstractChannel.java:852)

at

ty.channel.AbstractChannel$AbstractUnsafe.write(AbstractChannel.java:738)

at

ty.channel.DefaultChannelPipeline$HeadContext.write(DefaultChannelPipeline.java:1251)

at

ty.channel.AbstractChannelHandlerContext.invokeWrite0(AbstractChannelHandlerContext.java:733)

at

ty.channel.AbstractChannelHandlerContext.invokeWrite(AbstractChannelHandlerContext.java:725)

at

ty.channel.AbstractChannelHandlerContext.access$1900(AbstractChannelHandlerContext.java:35)

at

ty.channel.AbstractChannelHandlerContext$AbstractWriteTask.write(AbstractChannelHandlerContext.java:1062)

at

ty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:1116)

at

ty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:1051)

at

ty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:399)

at

ty.channel.nio.NioEventLoop.run(NioEventLoop.java:446)

at

ty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:131)

at

ty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)

...

1 more

Caused by:

java.nio.channels.ClosedChannelException

at

ty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source)

18/11/20 19:16:29 WARN

metrics.MetricsSystem: Stopping a MetricsSystem that is not running

[IPKernelApp] WARNING | Unknown error in

handling PYTHONSTARTUP file /hadoop/spark/python/pyspark/shell.py:

[I 19:17:00.221 NotebookApp] Saving file at

/Untitled.ipynb

^C[I 19:17:03.428 NotebookApp] interrupted

Serving notebooks from local directory:

/hadoop/spark/conf

1 active kernels

The Jupyter Notebook is running at:

http://localhost:8888/

Shutdown this notebook server (y/[n])? y

[C 19:17:04.983 NotebookApp] Shutdown confirmed

[I 19:17:04.983 NotebookApp] Shutting down

kernels

[I 19:17:05.587 NotebookApp] Kernel

shutdown: 98d8605a-804a-47af-83fb-2efc8b5a3d60

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这里主要出现了两个错误:

(1)

18/11/20 19:16:11 ERROR spark.SparkContext:

Error initializing SparkContext.

org.apache.spark.SparkException: Yarn

application has already ended! It might have been killed or unable to launch

application master.

1

2

3

4

5

6

7

(2)

Caused by: java.io.IOException: Failed to

send RPC 7790789781121901013 to /192.168.127.131:55928:

java.nio.channels.ClosedChannelException

1

2

3

分别将这两个错误百度下

有的说是内存不足,有的说是需要两个内核

对于内存不足,在yarn-site.xml增加两个点

就是下面图片上的最后两个点

又修改虚拟机设置给slave1增加了两个处理器,使它变成两个核

然而仍旧出现相同的错误

继续修改,中间不知道修改了什么,再次运行

出现了不一样的错误

[root@master hadoop]# pyspark --master yarn

[TerminalIPythonApp] WARNING | Subcommand

`ipython notebook` is deprecated and will be removed in future versions.

[TerminalIPythonApp] WARNING | You likely

want to use `jupyter notebook` in the future

[I 21:04:49.200 NotebookApp]

[nb_conda_kernels] enabled, 2 kernels found

[I 21:04:49.310 NotebookApp] ✓ nbpresent HTML export ENABLED

[W 21:04:49.310 NotebookApp] ✗ nbpresent PDF export DISABLED: No module named 'nbbrowserpdf'

[I 21:04:49.373 NotebookApp]

[nb_anacondacloud] enabled

[I 21:04:49.376 NotebookApp] [nb_conda]

enabled

[I 21:04:49.377 NotebookApp] Serving

notebooks from local directory: /hadoop/hadoop/etc/hadoop

[I 21:04:49.377 NotebookApp] 0 active

kernels

[I 21:04:49.377 NotebookApp] The Jupyter

Notebook is running at: http://localhost:8888/

[I 21:04:49.377 NotebookApp] Use Control-C

to stop this server and shut down all kernels (twice to skip confirmation).

[I 21:04:54.440 NotebookApp] Creating new

notebook in

[I 21:04:55.832 NotebookApp] Kernel

started: c526700a-7ee9-4bdc-9bf1-675db15d1799

SLF4J: Class path contains multiple SLF4J

bindings.

SLF4J: Found binding in

[jar:file:/hadoop/spark/jars/slf4j-log4j12-1.7.16.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: Found binding in

[jar:file:/hadoop/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: See

/codes.html#multiple_bindings for an explanation.

SLF4J: Actual binding is of type

[org.slf4j.impl.Log4jLoggerFactory]

Setting default log level to

"WARN".

To adjust logging level use sc.setLogLevel(newLevel).

For SparkR, use setLogLevel(newLevel).

18/11/20 21:04:59 WARN util.NativeCodeLoader:

Unable to load native-hadoop library for your platform... using builtin-java

classes where applicable

18/11/20 21:05:02 WARN yarn.Client: Neither

spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading

libraries under SPARK_HOME.

[W 21:05:05.954 NotebookApp] Timeout

waiting for kernel_info reply from c526700a-7ee9-4bdc-9bf1-675db15d1799

18/11/20 21:06:09 WARN hdfs.DFSClient:

DataStreamer Exception

org.apache.hadoop.ipc.RemoteException(java.io.IOException):

File /user/root/.sparkStaging/application_1542716519992_0009/__spark_libs__6100798743446340760.zip

could only be replicated to 0 nodes instead of minReplication (=1). There are 1 datanode(s) running and 1 node(s)

are excluded in this operation.

at

org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1562)

at

org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3245)

at

org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:663)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:482)

at

org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:619)

at

org.apache.hadoop.ipc.RPC$Server.call(RPC.java:962)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2040)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2036)

at

java.security.AccessController.doPrivileged(Native Method)

at

javax.security.auth.Subject.doAs(Subject.java:422)

at

org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1656)

at

org.apache.hadoop.ipc.Server$Handler.run(Server.java:2034)

at

org.apache.hadoop.ipc.Client.call(Client.java:1470)

at

org.apache.hadoop.ipc.Client.call(Client.java:1401)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)

at

com.sun.proxy.$Proxy11.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:399)

at

sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at

sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at

sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at

java.lang.reflect.Method.invoke(Method.java:498)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)

at

com.sun.proxy.$Proxy12.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1528)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1345)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:587)

18/11/20 21:06:09 ERROR spark.SparkContext:

Error initializing SparkContext.

org.apache.hadoop.ipc.RemoteException(java.io.IOException):

File /user/root/.sparkStaging/application_1542716519992_0009/__spark_libs__6100798743446340760.zip

could only be replicated to 0 nodes instead of minReplication (=1). There are 1 datanode(s) running and 1 node(s)

are excluded in this operation.

at

org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1562)

at

org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3245)

at

org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:663)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:482)

at

org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:619)

at

org.apache.hadoop.ipc.RPC$Server.call(RPC.java:962)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2040)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2036)

at

java.security.AccessController.doPrivileged(Native Method)

at

javax.security.auth.Subject.doAs(Subject.java:422)

at

org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1656)

at

org.apache.hadoop.ipc.Server$Handler.run(Server.java:2034)

at

org.apache.hadoop.ipc.Client.call(Client.java:1470)

at

org.apache.hadoop.ipc.Client.call(Client.java:1401)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)

at

com.sun.proxy.$Proxy11.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:399)

at

sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at

sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at

sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at

java.lang.reflect.Method.invoke(Method.java:498)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)

at

com.sun.proxy.$Proxy12.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1528)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1345)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:587)

18/11/20 21:06:09 WARN

cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Attempted to request

executors before the AM has registered!

18/11/20 21:06:09 WARN

metrics.MetricsSystem: Stopping a MetricsSystem that is not running

18/11/20 21:06:09 WARN spark.SparkContext:

Another SparkContext is being constructed (or threw an exception in its

constructor). This may indicate an

error, since only one SparkContext may be running in this JVM (see SPARK-2243).

The other SparkContext was created at:

org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)

sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native

Method)

sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)

sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)

java.lang.reflect.Constructor.newInstance(Constructor.java:423)

py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)

py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)

py4j.Gateway.invoke(Gateway.java:236)

mands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)

mands.ConstructorCommand.execute(ConstructorCommand.java:69)

py4j.GatewayConnection.run(GatewayConnection.java:214)

java.lang.Thread.run(Thread.java:748)

18/11/20 21:06:09 WARN yarn.Client: Neither

spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading

libraries under SPARK_HOME.

[I 21:06:55.876 NotebookApp] Saving file at

/Untitled.ipynb

18/11/20 21:07:16 WARN hdfs.DFSClient:

DataStreamer Exception

org.apache.hadoop.ipc.RemoteException(java.io.IOException):

File /user/root/.sparkStaging/application_1542716519992_0010/__spark_libs__8564260734942060287.zip

could only be replicated to 0 nodes instead of minReplication (=1). There are 0 datanode(s) running and 1 node(s)

are excluded in this operation.

at

org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1562)

at

org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3245)

at

org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:663)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:482)

at

org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:619)

at

org.apache.hadoop.ipc.RPC$Server.call(RPC.java:962)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2040)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2036)

at

java.security.AccessController.doPrivileged(Native Method)

at

javax.security.auth.Subject.doAs(Subject.java:422)

at

org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1656)

at

org.apache.hadoop.ipc.Server$Handler.run(Server.java:2034)

at

org.apache.hadoop.ipc.Client.call(Client.java:1470)

at

org.apache.hadoop.ipc.Client.call(Client.java:1401)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)

at

com.sun.proxy.$Proxy11.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:399)

at

sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at

sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at

sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at

java.lang.reflect.Method.invoke(Method.java:498)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)

at

com.sun.proxy.$Proxy12.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1528)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1345)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:587)

18/11/20 21:07:16 ERROR spark.SparkContext:

Error initializing SparkContext.

org.apache.hadoop.ipc.RemoteException(java.io.IOException):

File

/user/root/.sparkStaging/application_1542716519992_0010/__spark_libs__8564260734942060287.zip

could only be replicated to 0 nodes instead of minReplication (=1). There are 0 datanode(s) running and 1 node(s)

are excluded in this operation.

at

org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1562)

at

org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3245)

at

org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:663)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:482)

at

org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:619)

at

org.apache.hadoop.ipc.RPC$Server.call(RPC.java:962)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2040)

at

org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2036)

at

java.security.AccessController.doPrivileged(Native Method)

at

javax.security.auth.Subject.doAs(Subject.java:422)

at

org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1656)

at

org.apache.hadoop.ipc.Server$Handler.run(Server.java:2034)

at

org.apache.hadoop.ipc.Client.call(Client.java:1470)

at

org.apache.hadoop.ipc.Client.call(Client.java:1401)

at

org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232)

at

com.sun.proxy.$Proxy11.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:399)

at

sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at

sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at

sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at

java.lang.reflect.Method.invoke(Method.java:498)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)

at

org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)

at

com.sun.proxy.$Proxy12.addBlock(Unknown Source)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:1528)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:1345)

at

org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:587)

18/11/20 21:07:16 WARN

cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Attempted to request executors

before the AM has registered!

18/11/20 21:07:16 WARN

metrics.MetricsSystem: Stopping a MetricsSystem that is not running

[IPKernelApp] WARNING | Unknown error in

handling PYTHONSTARTUP file /hadoop/spark/python/pyspark/shell.py:

[I 21:07:36.291 NotebookApp] Saving file at

/Untitled.ipynb

[I 21:07:42.092 NotebookApp] Kernel

shutdown: c526700a-7ee9-4bdc-9bf1-675db15d1799

[W 21:07:42.095 NotebookApp] delete

/Untitled.ipynb

^C[I 21:07:46.458 NotebookApp] interrupted

Serving notebooks from local directory: /hadoop/hadoop/etc/hadoop

0 active kernels

The Jupyter Notebook is running at:

http://localhost:8888/

Shutdown this notebook server (y/[n])? y

[C 21:07:48.224 NotebookApp] Shutdown

confirmed

[I 21:07:48.225 NotebookApp] Shutting down

kernels

1

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继续按照日志给出的信息继续寻找,

当我用

hadoop dfsadmin -report 查看一下磁盘使用情况时

1

Configured Capacity: 0 (0 B)

Present Capacity: 0 (0 B)

DFS Remaining: 0 (0 B)

DFS Used: 0 (0 B)

DFS Used%: NaN%

Under replicated blocks: 0

Blocks with corrupt replicas: 0

Missing blocks: 0

1

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于是重新格式化namenode,

因为上面提到hdfs,我有修改了一下hdfs-site.xml。将里面的replication值从1变到2

再一次start-all.sh,

[root@master bin]# hadoop dfsadmin -report

DEPRECATED: Use of this script to execute

hdfs command is deprecated.

Instead use the hdfs command for it.

Configured Capacity: 18238930944 (16.99 GB)

Present Capacity: 6707884032 (6.25 GB)

DFS Remaining: 6707879936 (6.25 GB)

DFS Used: 4096 (4 KB)

DFS Used%: 0.00%

Under replicated blocks: 0

Blocks with corrupt replicas: 0

Missing blocks: 0

-------------------------------------------------

Live datanodes (1):

Name: 192.168.127.131:50010 (slave1)

Hostname: slave1

Decommission Status : Normal

Configured Capacity: 18238930944 (16.99 GB)

DFS Used: 4096 (4 KB)

Non DFS Used: 11531046912 (10.74 GB)

DFS Remaining: 6707879936 (6.25 GB)

DFS Used%: 0.00%

DFS Remaining%: 36.78%

Configured Cache Capacity: 0 (0 B)

Cache Used: 0 (0 B)

Cache Remaining: 0 (0 B)

Cache Used%: 100.00%

Cache Remaining%: 0.00%

Xceivers: 1

Last contact: Tue Nov 20 21:26:11 CST

在终端输入

pyspark --master yarn

惊喜了一下,结果出来了

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