【发布时间】：2019-08-22 02:31:14
【问题描述】：
我将 Dockerfile 设置为：
# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License
ARG BASE_CONTAINER=jupyter/scipy-notebook
FROM $BASE_CONTAINER
LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
USER root
# Spark dependencies
ENV SPARK_VERSION 2.3.2
ENV SPARK_HADOOP_PROFILE 2.7
ENV SPARK_SRC_URL https://www.apache.org/dist/spark/spark-$SPARK_VERSION/spark-${SPARK_VERSION}-bin-hadoop${SPARK_HADOOP_PROFILE}.tgz
ENV SPARK_HOME=/opt/spark
ENV PATH $PATH:$SPARK_HOME/bin
RUN apt-get update && \
apt-get install -y openjdk-8-jdk-headless \
postgresql && \
rm -rf /var/lib/apt/lists/*
ENV JAVA_HOME /usr/lib/jvm/java-8-openjdk-amd64/
ENV PATH $PATH:$JAVA_HOME/bin
RUN wget ${SPARK_SRC_URL}
RUN tar -xzf spark-${SPARK_VERSION}-bin-hadoop${SPARK_HADOOP_PROFILE}.tgz
RUN mv spark-${SPARK_VERSION}-bin-hadoop${SPARK_HADOOP_PROFILE} /opt/spark
RUN rm -f spark-${SPARK_VERSION}-bin-hadoop${SPARK_HADOOP_PROFILE}.tgz
USER $NB_UID
ENV POST_URL https://jdbc.postgresql.org/download/postgresql-42.2.5.jar
RUN wget ${POST_URL}
RUN mv postgresql-42.2.5.jar $SPARK_HOME/jars
# Install pyarrow
RUN conda install --quiet -y 'pyarrow' && \
conda install pyspark==2.3.2 && \
conda clean -tipsy && \
fix-permissions $CONDA_DIR && \
fix-permissions /home/$NB_USER
WORKDIR $SPARK_HOME
然后我运行命令将 my_notebook 图像设置为： docker build -t my_notebook .
然后我制作了三个容器 Master、Worker 和 Notebook 如下：
掌握使用 docker-compose 文件：
master:
image: my_notebook
command: bin/spark-class org.apache.spark.deploy.master.Master -h master
hostname: master
environment:
MASTER: spark://master:7077
SPARK_CONF_DIR: /conf
SPARK_PUBLIC_DNS: 192.168.XXX.XXX
expose:
- 7001
- 7002
- 7003
- 7004
- 7005
- 7077
- 6066
ports:
- 4040:4040
- 6066:6066
- 7077:7077
- 8080:8080
volumes:
- ./conf/master:/conf
- ./data:/tmp/data
工人使用 docker-compose 文件：
worker:
image: my_notebook
command: bin/spark-class org.apache.spark.deploy.worker.Worker spark://192.168.XXX.XXX:7077
hostname: worker
environment:
SPARK_CONF_DIR: /conf
SPARK_WORKER_CORES: 4
SPARK_WORKER_MEMORY: 4g
SPARK_WORKER_PORT: 8881
SPARK_WORKER_WEBUI_PORT: 8081
SPARK_BLOCKMGR_PORT: 5003
SPARK_PUBLIC_DNS: localhost
expose:
- 7012
- 7013
- 7014
- 7015
- 8881
- 5001
- 5003
ports:
- 8081:8081
volumes:
- ./conf/worker:/conf
- ./data:/tmp/data
使用 docker-compose 文件的笔记本：
notebook:
image: my_notebook
command: jupyter notebook
hostname: notebook
environment:
SPARK_PUBLIC_DNS: 192.168.XXX.XXX
expose:
- 7012
- 7013
- 7014
- 7015
- 8881
- 8888
ports:
- 8888:8888
首先，我在一台机器上启动了 Master 容器： “码头工人组成” 然后在另一台机器“docker-compose up”上启动 Worker 然后在其他机器“docker-compose up”中启动笔记本
Spark 集群已设置。 Spark UI 是可访问的。工人也在集群中注册。Jupyter notebook 也成功启动。但面临的问题是，当我通过 jupyter worker 执行程序运行 pyspark 应用程序时，无法连接回 spark 驱动程序。 错误日志是：
Spark Executor Command: "/usr/lib/jvm/java-8-openjdk-amd64//bin/java" "-cp" "/conf/:/opt/spark/jars/*" "-Xmx1024M" "-Dspark.driver.port=35147" "org.apache.spark.executor.CoarseGrainedExecutorBackend" "--driver-url" "spark://CoarseGrainedScheduler@notebook:35147" "--executor-id" "31" "--hostname" "172.17.0.3" "--cores" "2" "--app-id" "app-20190101134023-0001" "--worker-url" "spark://Worker@172.17.0.3:8881"
========================================
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:63)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.run(CoarseGrainedExecutorBackend.scala:188)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$.main(CoarseGrainedExecutorBackend.scala:293)
at org.apache.spark.executor.CoarseGrainedExecutorBackend.main(CoarseGrainedExecutorBackend.scala)
Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult:
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205)
at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:101)
at org.apache.spark.executor.CoarseGrainedExecutorBackend$$anonfun$run$1.apply$mcV$sp(CoarseGrainedExecutorBackend.scala:201)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$2.run(SparkHadoopUtil.scala:64)
at org.apache.spark.deploy.SparkHadoopUtil$$anon$2.run(SparkHadoopUtil.scala:63)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
... 4 more
Caused by: java.io.IOException: Failed to connect to notebook:35147
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:245)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:187)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:198)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:194)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:190)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.UnknownHostException: notebook
at java.net.InetAddress.getAllByName0(InetAddress.java:1281)
at java.net.InetAddress.getAllByName(InetAddress.java:1193)
at java.net.InetAddress.getAllByName(InetAddress.java:1127)
at java.net.InetAddress.getByName(InetAddress.java:1077)
at io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:146)
at io.netty.util.internal.SocketUtils$8.run(SocketUtils.java:143)
at java.security.AccessController.doPrivileged(Native Method)
at io.netty.util.internal.SocketUtils.addressByName(SocketUtils.java:143)
at io.netty.resolver.DefaultNameResolver.doResolve(DefaultNameResolver.java:43)
at io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:63)
at io.netty.resolver.SimpleNameResolver.resolve(SimpleNameResolver.java:55)
at io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:57)
at io.netty.resolver.InetSocketAddressResolver.doResolve(InetSocketAddressResolver.java:32)
at io.netty.resolver.AbstractAddressResolver.resolve(AbstractAddressResolver.java:108)
at io.netty.bootstrap.Bootstrap.doResolveAndConnect0(Bootstrap.java:208)
at io.netty.bootstrap.Bootstrap.access$000(Bootstrap.java:49)
at io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:188)
at io.netty.bootstrap.Bootstrap$1.operationComplete(Bootstrap.java:174)
at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:507)
at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:481)
at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:420)
at io.netty.util.concurrent.DefaultPromise.trySuccess(DefaultPromise.java:104)
at io.netty.channel.DefaultChannelPromise.trySuccess(DefaultChannelPromise.java:82)
at io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetSuccess(AbstractChannel.java:978)
at io.netty.channel.AbstractChannel$AbstractUnsafe.register0(AbstractChannel.java:512)
at io.netty.channel.AbstractChannel$AbstractUnsafe.access$200(AbstractChannel.java:423)
at io.netty.channel.AbstractChannel$AbstractUnsafe$1.run(AbstractChannel.java:482)
at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:163)
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:403)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:463)
at io.netty.util.concurrent.SingleThreadEventExecutor$5.run(SingleThreadEventExecutor.java:858)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
... 1 more
谁能帮帮我？
【问题讨论】：
标签： docker apache-spark