利用docker快速搭建Spark集群

发表:2017-04-13 09:31:20

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

  1. 安装docker

  2. (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

  1. 集群管理器(Mesos, Yarn或者standalone Mode)

  2. 工作节点(worker)

如何docker化(本例使用Standalone模式)

  1. 将spark集群拆分

    • base(基础镜像)

    • master(主节点镜像)

    • worker(工作镜像)

  2. 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:7
MAINTAINER 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 Java
ENV 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 7077
ENV SPARK_MASTER_WEBUI_PORT 8080
ENV SPARK_MASTER_LOG /spark/logs
EXPOSE 8080 7077 6066
CMD ["/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

ersion: '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
  1. 测试集群

    docker-compose up

    访问http://localhost:50003/ 结果如图


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