适用人群
正在使用spark的开发者
正在学习docker或者spark的开发者
准备工作
安装docker
(可选)下载java和spark with hadoop
Spark集群
Spark运行时架构图
Spark Cluster(Spark集群).png
如上图: Spark集群由以下两个部分组成
集群管理器(Mesos, Yarn或者standalone Mode)
工作节点(worker)
如何docker化(本例使用Standalone模式)
将spark集群拆分
base(基础镜像)
master(主节点镜像)
worker(工作镜像)
编写base Dockerfile
注: 为方便切换版本基础镜像选择的是centos, 所以要下载java和spark, 方便调试, 可以下载好安装文件后本地搭建一个静态文件服务器, 使用Node.js 的http-server可以快速搞定,命令如下
npm install http-server -g http-server -p 54321 ~/Downloads
正式开始写Dockerfile
FROM centos:7MAINTAINER RavenZZ <raven.zhu@outlook.com># 安装系统工具RUN yum update -y RUN yum upgrade -y RUN yum install -y byobu curl htop man unzip nano wget RUN yum clean all# 安装 JavaENV JDK_VERSION 8u11 ENV JDK_BUILD_VERSION b12# 如果网速快,可以直接从源站下载#RUN curl -LO "http://download.oracle.com/otn-pub/java/jdk/$JDK_VERSION-$JDK_BUILD_VERSION/jdk-$JDK_VERSION-linux-x64.rpm" -H 'Cookie: oraclelicense=accept-securebackup-cookie' && rpm -i jdk-$JDK_VERSION-linux-x64.rpm; rm -f jdk-$JDK_VERSION-linux-x64.rpm;RUN curl -LO "http://192.168.199.102:54321/jdk-8u11-linux-x64.rpm" && rpm -i jdk-$JDK_VERSION-linux-x64.rpm; rm -f jdk-$JDK_VERSION-linux-x64.rpm; ENV JAVA_HOME /usr/java/default RUN yum remove curl; yum clean all WORKDIR spark RUN \ curl -LO 'http://192.168.199.102:54321/spark-2.1.0-bin-hadoop2.7.tgz' && \ tar zxf spark-2.1.0-bin-hadoop2.7.tgz RUN rm -rf spark-2.1.0-bin-hadoop2.7.tgz RUN mv spark-2.1.0-bin-hadoop2.7/* ./ ENV SPARK_HOME /spark ENV PATH /spark/bin:$PATH ENV PATH /spark/sbin:$PATH
编写master Dockerfile
FROM ravenzz/spark-hadoop MAINTAINER RavenZZ <raven.zhu@outlook.com> COPY master.sh / ENV SPARK_MASTER_PORT 7077ENV SPARK_MASTER_WEBUI_PORT 8080ENV SPARK_MASTER_LOG /spark/logs EXPOSE 8080 7077 6066CMD ["/bin/bash","/master.sh"]
编写worker Dockerfile
FROM ravenzz/spark-hadoop MAINTAINER RavenZZ <raven.zhu@outlook.com> COPY worker.sh / ENV SPARK_WORKER_WEBUI_PORT 8081 ENV SPARK_WORKER_LOG /spark/logs ENV SPARK_MASTER "spark://spark-master:32769" EXPOSE 8081 CMD ["/bin/bash","/worker.sh"]
docker-compose
version: '3'services: spark-master: build: context: ./master dockerfile: Dockerfile ports: - "50001:6066" - "50002:7077" # SPARK_MASTER_PORT - "50003:8080" # SPARK_MASTER_WEBUI_PORT expose: - 7077 spark-worker1: build: context: ./worker dockerfile: Dockerfile ports: - "50004:8081" links: - spark-master environment: - SPARK_MASTER=spark://spark-master:7077 spark-worker2: build: context: ./worker dockerfile: Dockerfile ports: - "50005:8081" links: - spark-master environment: - SPARK_MASTER=spark://spark-master:7077
测试集群
docker-compose up
访问http://localhost:50003/ 结果如图
Paste_Image.png
本文仅供参考, 希望读者能够按照思路自己编译需要的Spark版本和各种依赖
作者:RavenZZ
链接:https://www.jianshu.com/p/4801bb7ab9e0