Spark入门之环境搭建

本教程是虚拟机搭建Spark环境和用idea编写脚本

 

一、前提准备

需要已经有搭建好的虚拟机环境,具体见教程大数据学习之路又之从小白到用sqoop导出数据 - 我试试这个昵称好使不 - 博客园 (cnblogs.com)

需要已经安装了idea或着eclipse(教程以idea为例)

 

二、环境搭建

1、下载Spark安装包(我下载的 spark-3.0.1-bin-hadoop2.7.tgz)

下载地址Scala 2.12.8 | The Scala Programming Language (scala-lang.org)

2、上传到虚拟机并解压(没备注就是主节点运行)

tar -zxvf spark-3.0.1-bin-hadoop2.7.tgz

3、修改权限

chown -R hadoop /export/server/spark-3.0.1-bin-hadoop2.7

chgrp -R hadoop /export/server/spark-3.0.1-bin-hadoop2.7

4、创建软连接

ln -s /export/server/spark-3.0.1-bin-hadoop2.7 /export/server/spark

5、启动spark交互式窗口

/export/server/spark/bin/spark-shell

Spark入门之环境搭建

 

还是很炫酷的哈哈哈,出现这个说明spark环境就搭建好了吗?漏!!!

6、配置Spark集群

cd /export/server/spark/conf

mv slaves.template slaves

vim slaves

添加

node02

node03

node04

7.配置master

cd /export/server/spark/conf

mv spark-env.sh.template spark-env.sh

vim spark-env.sh

增加如下内容:

## 设置JAVA安装目录
JAVA_HOME=/linmob/install/jdk1.8.0_141

## HADOOP软件配置文件目录,读取HDFS上文件和运行Spark在YARN集群时需
要,先提前配上
HADOOP_CONF_DIR=/linmob/install/hadoop-3.1.4/etc/hadoop
YARN_CONF_DIR=/linmob/install/hadoop-3.1.4/etc/hadoop

## 指定spark老大Master的IP和提交任务的通信端口
#SPARK_MASTER_HOST=node01
SPARK_MASTER_PORT=7077

SPARK_MASTER_WEBUI_PORT=8080

SPARK_WORKER_CORES=1
SPARK_WORKER_MEMORY=1g

SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=node01:2181,node02:2181,node03:2181,node04:2181 -Dspark.deploy.zookeeper.dir=/spark-ha"

## 配置spark历史日志存储地址
SPARK_HISTORY_OPTS="-Dspark.history.fs.logDirectory=hdfs://node01:8020/sparklog/ -Dspark.history.fs.cleaner.enabled=true"

8、将配置好的将 Spark 安装包分发给集群中其它机器,命令如下:

cd /export/server/

scp -r spark-3.0.1-bin-hadoop2.7 hadoop@node02:$PWD

scp -r spark-3.0.1-bin-hadoop2.7 hadoop@node03:$PWD

scp -r spark-3.0.1-bin-hadoop2.7 hadoop@node04:$PWD

9、创建软连接(每个节点都运行一遍)

ln -s /export/server/spark-3.0.1-bin-hadoop2.7 /export/server/spark

10、配置Yarn历史服务器并关闭资源检查

vim /export/server/hadoop/etc/hadoop/yarn-site.xml

少的部分补上

<configuration>
<!-- 配置yarn主节点的位置 -->
<property>
<name>yarn.resourcemanager.hostname</name>
<value>node01</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<!-- 设置yarn集群的内存分配方案 -->
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>20480</value>
</property>
<property>
<name>yarn.scheduler.minimum-allocation-mb</name>
<value>2048</value>
</property>
<property>
<name>yarn.nodemanager.vmem-pmem-ratio</name>
<value>2.1</value>
</property>
<!-- 开启日志聚合功能 -->
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
<!-- 设置聚合日志在hdfs上的保存时间 -->
<property>
<name>yarn.log-aggregation.retain-seconds</name>
<value>604800</value>
</property>
<!-- 设置yarn历史服务器地址 -->
<property>
<name>yarn.log.server.url</name>
<value>http://node1:19888/jobhistory/logs</value>
</property>
<!-- 关闭yarn内存检查 -->
<property>
<name>yarn.nodemanager.pmem-check-enabled</name>
<value>false</value>
</property>
<property>
<name>yarn.nodemanager.vmem-check-enabled</name>
<value>false</value>
</property>
</configuration>

注意:如果之前没有配置,现在配置了需要分发并重启yarn(重启需要每个节点都运行)

cd /export/server/hadoop/etc/hadoop

scp -r yarn-site.xml hadoop@node02:$PWD

scp -r yarn-site.xml hadoop@node03:$PWD
scp -r yarn-site.xml hadoop@node04:$PWD /export/server/hadoop/sbin/stop-yarn.sh /export/server/hadoop/sbin/start-yarn.sh

11、配置Spark的历史服务器和Yarn的整合

cd /export/server/spark/conf

mv spark-defaults.conf.template spark-defaults.conf

vim spark-defaults.conf

添加

spark.eventLog.enabled true
spark.eventLog.dir hdfs://node01:8020/sparklog/
spark.eventLog.compress true
spark.yarn.historyServer.address node01:18080

手动创建

hadoop fs -mkdir -p /sparklog

12、修改日志级别

cd /export/server/spark/conf

mv log4j.properties.template log4j.properties

vim log4j.properties

修改

Spark入门之环境搭建

 

 

 分发-可选,如果只在node1上提交spark任务到yarn,那么不需要分发

cd /export/server/spark/conf

scp -r spark-env.sh hadoop@node02:$PWD

scp -r spark-env.sh hadoop@node03:$PWD

scp -r spark-env.sh hadoop@node04:$PWD
 

scp -r spark-defaults.conf hadoop@node02:$PWD

scp -r spark-defaults.conf hadoop@node03:$PWD

scp -r spark-defaults.conf hadoop@node04:$PWD


scp -r log4j.properties hadoop@node02:$PWD

scp -r log4j.properties hadoop@node03:$PWD

scp -r log4j.properties hadoop@node04:$PWD

13、配置依赖的Spark的jar包

hadoop fs -mkdir -p /spark/jars/

hadoop fs -put /export/server/spark/jars/* /spark/jars/

vim /export/server/spark/conf/spark-defaults.conf

添加内容

spark.yarn.jars hdfs://node1:8020/spark/jars/*

分发同步-可选

cd /export/server/spark/conf

scp -r spark-defaults.conf hadoop@node02:$PWD

scp -r spark-defaults.conf hadoop@node03:$PWD

scp -r spark-defaults.conf hadoop@node04:$PWD

14、启动服务

- 启动HDFS和YARN服务,在主节点上启动spark集群

/export/server/spark/sbin/start-all.sh

-启动MRHistoryServer服务,在node01执行命令

mr-jobhistory-daemon.sh start historyserver

- 启动Spark HistoryServer服务,,在node01执行命令

/export/server/spark/sbin/start-history-server.sh

15、测试

看下个博客

 

三、总结:

在主节点上启动spark集群

/export/server/spark/sbin/start-all.sh

在主节点上停止spark集群

/export/server/spark/sbin/stop-all.sh

spark: 4040 任务运行web-ui界面端口

spark: 8080 spark集群web-ui界面端口

spark: 7077 spark提交任务时的通信端口

hadoop: 50070集群web-ui界面端口

hadoop:8020/9000(老版本) 文件上传下载通信端口

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