【问题标题】:How to setup Apache Spark and Zeppelin on Docker如何在 Docker 上设置 Apache Spark 和 Zeppelin
【发布时间】:2019-12-29 12:27:51
【问题描述】:

我正在尝试在 Docker 上使用 Zeppelin 设置 Spark 开发环境,但在连接 Zeppelin 和 Spark 容器时遇到问题。

我正在使用当前的 docker-compose 部署 Docker Stack

version: '3'
services:

  spark-master:
    image: gettyimages/spark
    command: bin/spark-class org.apache.spark.deploy.master.Master -h spark-master
    hostname: spark-master
    environment:
      SPARK_CONF_DIR: /conf
      SPARK_PUBLIC_DNS: 10.129.34.90
    volumes:
      - spark-master-volume:/conf
      - spark-master-volume:/tmp/data
    ports: 
      - 8000:8080

  spark-worker:
    image: gettyimages/spark
    command: bin/spark-class org.apache.spark.deploy.worker.Worker spark://spark-master:7077
    hostname: spark-worker
    environment:
      SPARK_MASTER_URL: spark-master:7077
      SPARK_CONF_DIR: /conf
      SPARK_PUBLIC_DNS: 10.129.34.90
      SPARK_WORKER_CORES: 2
      SPARK_WORKER_MEMORY: 2g
    volumes:
      - spark-worker-volume:/conf
      - spark-worker-volume:/tmp/data
    ports:
      - "8081-8100:8081-8100" 

  zeppelin:
    image: apache/zeppelin:0.8.0
    ports: 
      - 8080:8080
      - 8443:8443
    volumes:
      - spark-master-volume:/opt/zeppelin/logs
      - spark-master-volume:/opt/zeppelin/notebookcd
    environment:
      MASTER: "spark://spark-master:7077"
      SPARK_MASTER: "spark://spark-master:7077"
      SPARK_HOME: /usr/spark-2.4.1
    depends_on:
      - spark-master

volumes:
  spark-master-volume:
    driver: local
  spark-worker-volume:
    driver: local

它正常构建,但是当我尝试在 Zeppelin 上运行 Spark 时,它抛出了我:

java.lang.RuntimeException: /zeppelin/bin/interpreter.sh: line 231: /usr/spark-2.4.1/bin/spark-submit: No such file or directory

我认为问题出在卷上,但我不知道如何正确处理。

【问题讨论】:

  • 您好,您的问题解决了吗?你能分享解决方案吗?谢谢。

标签: docker apache-spark docker-compose apache-zeppelin


【解决方案1】:

您需要在 zeppelin docker 实例上安装 spark 以使用 spark-submit 并更新 spark 解释器配置以将其指向您的 spark 集群

zeppelin_notebook_server:
    container_name: zeppelin_notebook_server
    build:
      context: zeppelin/
    restart: unless-stopped
    volumes:
      - ./zeppelin/config/interpreter.json:/zeppelin/conf/interpreter.json:rw
      - ./zeppelin/notebooks:/zeppelin/notebook
      - ../sample-data:/sample-data:ro
    ports:
      - "8085:8080"
    networks:
      - general
    labels:
      container_group: "notebook"

  spark_base:
    container_name: spark-base
    build:
      context: spark/base
    image: spark-base:latest

  spark_master:
    container_name: spark-master
    build:
      context: spark/master/
    networks:
      - general
    hostname: spark-master
    ports:
      - "3030:8080"
      - "7077:7077"
    environment:
      - "SPARK_LOCAL_IP=spark-master"
    depends_on:
      - spark_base
    volumes:
      - ./spark/apps/jars:/opt/spark-apps
      - ./spark/apps/data:/opt/spark-data
      - ../sample-data:/sample-data:ro

  spark_worker_1:
    container_name: spark-worker-1
    build:
      context: spark/worker/
    networks:
      - general
    hostname: spark-worker-1
    ports:
      - "3031:8081"
    env_file: spark/spark-worker-env.sh
    environment:
      - "SPARK_LOCAL_IP=spark-worker-1"
    depends_on:
      - spark_master
    volumes:
      - ./spark/apps/jars:/opt/spark-apps
      - ./spark/apps/data:/opt/spark-data
      - ../sample-data:/sample-data:ro

  spark_worker_2:
    container_name: spark-worker-2
    build:
      context: spark/worker/
    networks:
      - general
    hostname: spark-worker-2
    ports:
      - "3032:8082"
    env_file: spark/spark-worker-env.sh
    environment:
      - "SPARK_LOCAL_IP=spark-worker-2"
    depends_on:
      - spark_master
    volumes:
      - ./spark/apps/jars:/opt/spark-apps
      - ./spark/apps/data:/opt/spark-data
      - ../sample-data:/sample-data:ro

Zeppelin 泊坞窗文件:

FROM "apache/zeppelin:0.8.1"

RUN wget http://apache.mirror.iphh.net/spark/spark-2.4.3/spark-2.4.3-bin-hadoop2.7.tgz --progress=bar:force && \
    tar xvf spark-2.4.3-bin-hadoop2.7.tgz && \
    mkdir -p /usr/local/spark && \
    mv spark-2.4.3-bin-hadoop2.7/* /usr/local/spark/. && \
    mkdir -p /sample-data

ENV SPARK_HOME "/usr/local/spark/"

确保您的 zeppelin spark 解释器配置与以下内容相同:

【讨论】:

    【解决方案2】:

    使用内容构建 Dockerfile

    FROM gettyimages/spark
    
    ENV APACHE_SPARK_VERSION 2.4.1
    ENV APACHE_HADOOP_VERSION 2.8.0
    ENV ZEPPELIN_VERSION 0.8.1
    
    RUN apt-get update 
    RUN set -x \
        && curl -fSL "http://www-eu.apache.org/dist/zeppelin/zeppelin-0.8.1/zeppelin-0.8.1-bin-all.tgz" -o /tmp/zeppelin.tgz \
        && tar -xzvf /tmp/zeppelin.tgz -C /opt/ \
        && mv /opt/zeppelin-* /opt/zeppelin \
        && rm /tmp/zeppelin.tgz 
    
    ENV SPARK_SUBMIT_OPTIONS "--jars /opt/zeppelin/sansa-examples-spark-2016-12.jar"
    ENV SPARK_HOME "/usr/spark-2.4.1/"
    
    WORKDIR /opt/zeppelin
    
    CMD ["/opt/zeppelin/bin/zeppelin.sh"]
    

    然后在带有前缀的 docker-compose.yml 文件中定义您的服务

    version: '3'
    services:
      zeppelin:
        build: ./zeppelin
        image: zeppelin:0.8.1-hadoop-2.8.0-spark-2.4.1
        ...
    

    最后在docker stack deploy之前使用docker-compose -f docker-compose.yml build构建自定义镜像

    【讨论】:

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