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Spark 分布式环境搭建

2020-12-30 13:31:23 作者：互联网

Spark 分布式环境搭建

1. scala环境搭建

1）下载scala安装包scala2.12.10.tgz安装到 /usr/scala

[root@hadoop001 scala]# tar -zxvf scala-2.12.10.tgz
[root@hadoop001 scala]# ln -s scala-2.12.10.tgz scala

2）添加Scala环境变量，在/etc/profile中添加：

export SCALA_HOME=/usr/scala/scala
export PATH=$SCALA_HOME/bin:$PATH

3)保存后刷新

[root@hadoop001 scala]:~# source /etc/profile

4）使用scala -version命令确认

[root@hadoop001 scala]# scala -version

2. Spark安装

2.1 解压

[hadoop@hadoop001 software]$ tar -zxvf spark-2.4.6-bin-2.6.0-cdh5.16.2.tgz -C ~/app/

软连接

[hadoop@hadoop001 app]$ ln -s spark-2.4.6-bin-2.6.0-cdh5.16.2/ spark

2.2 修改环境配置文件

[hadoop@hadoop001 app]$ vi /home/hadoop/.bashrc

#spark

export SPARK_HOME=/home/hadoop/app/spark
export PATH=$PATH:$SPARK_HOME/bin

修改spark配置文件

[hadoop@hadoop001 conf]$ cp spark-env.sh.template spark-env.sh


 export JAVA_HOME=/usr/java/jdk
 export SCALA_HOME=/usr/scala/scala
 export HADOOP_HOME=/home/hadoop/app/hadoop
 export HADOOP_CONF_DIR=/home/hadoop/app/hadoop/etc/hadoop
 export SPARK_MASTER_IP=192.168.1.148
 export SPARK_MASTER_HOST=192.168.1.148
 #export SPARK_LOCAL_IP=11.24.24.112
 #export SPARK_LOCAL_IP=11.24.24.113
 export SPARK_LOCAL_IP=0.0.0.0
 export SPARK_WORKER_MEMORY=1g
 export SPARK_WORKER_CORES=2
 export SPARK_HOME=/home/hadoop/app/spark
 export SPARK_DIST_CLASSPATH=$(/home/hadoop/app/hadoop/bin/hadoop classpath)

2.3 修改slaves

[hadoop@hadoop001 conf]$ mv slaves.template slaves
[hadoop@hadoop001 conf]$ vim slaves
删除localhost
hadoop001
hadoop002
hadoop003

2.4 配置hadoop002 hadoop003 的配置文件

#spark
export SPARK_HOME=/home/hadoop/app/spark
export PATH=$PATH:$SPARK_HOME/bin

source .bashrc

2.5 scp到hadoop002 hadoop003

[hadoop@hadoop001 ~]$ scp -r /home/hadoop/app/spark-2.4.6-bin-2.6.0-cdh5.16.2 hadoop002:/home/hadoop/app/
软连接
[hadoop@hadoop003 app]$ ln -s spark-2.4.6-bin-2.6.0-cdh5.16.2/ spark

2.6 配置hadoop002 hadoop003 spark 的配置文件

[hadoop@hadoop002 conf]$ pwd
/home/hadoop/app/spark/conf
[hadoop@hadoop002 conf]$ vim spark-env.sh
配置成他们自己的ip


export SPARK_LOCAL_IP=192.168.1.183
export SPARK_LOCAL_IP=192.168.1.175

3. Scala分发

[root@hadoop001 usr]# scp -r /usr/scala/ hadoop002:/usr/

[root@hadoop001 usr]# scp -r /usr/scala/ hadoop003:/usr/

[root@hadoop001 usr]# scp /etc/profile hadoop002:/etc/
profile                                                                                                                   100% 2016   890.7KB/s   00:00
[root@hadoop001 usr]# scp /etc/profile hadoop003:/etc/
profile       

[root@hadoop002 ~]# source /etc/profile            
[root@hadoop003 ~]# source /etc/profile

4. 启动

[hadoop@hadoop001 spark]$ sbin/start-all.sh

Spark IDEA 配置

官网查看spark版本与scala版本相匹配的版本

idea创建spark module 然后配置pom文件

<dependencies>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.12</artifactId>
        <version>2.4.5</version>
    </dependency>
</dependencies>
<build>
    <plugins>
        <!-- 该插件用于将Scala代码编译成class文件 -->
        <plugin>
            <groupId>net.alchim31.maven</groupId>
            <artifactId>scala-maven-plugin</artifactId>
            <version>3.2.2</version>
            <executions>
                <execution>
                    <!-- 声明绑定到maven的compile阶段 -->
                    <goals>
                        <goal>testCompile</goal>
                    </goals>
                </execution>
            </executions>
        </plugin>
        <plugin>
            <groupId>org.apache.maven.plugins</groupId>
            <artifactId>maven-assembly-plugin</artifactId>
            <version>3.0.0</version>
            <configuration>
                <descriptorRefs>
                    <descriptorRef>jar-with-dependencies</descriptorRef>
                </descriptorRefs>
            </configuration>
            <executions>
                <execution>
                    <id>make-assembly</id>
                    <phase>package</phase>
                    <goals>
                        <goal>single</goal>
                    </goals>
                </execution>
            </executions>
        </plugin>
    </plugins>
</build>

import之后下载安装scala

https://www.scala-lang.org/download/

然后在idea的setting里下载scala插件
打开Setting 里的Plugins 搜索scala 然后下载

如果提示安装不成功选择本地安装开启vpn下载更快

https://plugins.jetbrains.com/plugin/1347-scala

在setting的右上角选择设置纽 install from disk

选好与idea 想匹配的版本

然后配置scala的jdk

ctrl+shift+alt + S

打开Project structure
然后配置Global Libraries里的scala jdk

标签：SPARK,scala,hadoop,hadoop001,export,spark,分布式,Spark,搭建
来源： https://blog.csdn.net/weixin_43866666/article/details/111970755