Spark Standalone集群搭建

  1. 环境说明
    • Win10
    • VMware 15.0.2
    • Ubuntu 18.10
  2. 软件版本说明
    • hadoop-2.7.7.tar.gz
    • jdk-8u212-linux-x64.tar.gz
    • sbt-1.2.8.tgz
    • scala-2.12.8.tgz
    • spark-2.4.3-bin-hadoop2.7.tgz
  3. 下载以上压缩包,解压缩后添加环境变量,vi ~./bashrc,在最后添加如下
     1 # set hadoop env
     2 export HARDOOP_HOME=/home/gemsuser/install/hadoop-2.7.7
     3 export PATH=${HARDOOP_HOME}/bin:${PATH}
     4 
     5 # set java env
     6 export JAVA_HOME=/home/gemsuser/install/jdk1.8.0_212
     7 export JRE_HOME=${JAVA_HOME}/jre
     8 export CLASS_PATH=${JAVA_HOME}/lib:${JRE_HOME}/lib
     9 export PATH=${JAVA_HOME}/bin:${PATH}
    10 
    11 # set scala env
    12 export SCALA_HOME=/home/gemsuser/install/scala-2.12.8
    13 export PATH=${SCALA_HOME}/bin:${PATH}
    14 
    15 # set sbt env
    16 export SBT_HOME=/home/gemsuser/install/sbt
    17 export PATH=${SBT_HOME}/bin:${PATH}
    18 
    19 # set spark env
    20 export SPARK_HOME=/home/gemsuser/install/spark-2.4.3-bin-hadoop2.7
    21 export PATH=${SPARK_HOME}/bin:${PATH}
    版本环境
  4. 调整日志级别
    log4j.properties:复制template文件,可修改log4j.rootCategory=INFO, console,更改为WARN,修改日志打印级别
    • spark-env.sh:复制template文件,配置spark运行所需要的环境变量
  5. 配置spark的config文件
     1 export JAVA_HOME=/home/gemsuser/install/jdk1.8.0_212
     2 export SCALA_HOME=/home/gemsuser/install/scala-2.12.8
     3 export SPARK_HOME=/home/gemsuser/install/spark-2.4.3-bin-hadoop2.7
     4 export HADOOP_CONF_DIR=/home/gemsuser/install/spark-2.4.3-bin-hadoop2.7/conf
     5 export SPARK_LOG_DIR=/home/gemsuser/install/spark-2.4.3-bin-hadoop2.7/logs
     6 export SPARK_PID_DIR=/home/gemsuser/install/spark-2.4.3-bin-hadoop2.7/pid
     7 export SPARK_MASTER_IP=localhost
     8 export SPARK_MASTER_HOST=localhost
     9 export SPARK_LOCAL_IP=localhost
    10 export SPARK_WORKER_MEMORY=1G
    Spark Maste Config
    1 maste
    2 slava1
    3 slave2
    Spark Slaves Config
  6. 配置maste无密登录slave
    • ssh-keygen -t rsa
    • cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
    • 修改/etc/ssh/sshd_config:
  7. 启动Spark进程:
原文地址:https://www.cnblogs.com/liudingchao/p/11108324.html