18.Hadoop:Spark环境部署

本节主要内容：

Spark环境部署

Spark拥有Hadoop MapReduce所具有的优点；但不同于MapReduce的是--Job中间输出结果可以保存在内存中，从而不再需要读写HDFS，因此Spark能更好地适用于数据挖掘与机器学习等需要迭代的MapReduce的算法。

spark5个组件

spark-core: spark核心包

spark-worker: spark-worker用的脚本

spark-master: spark-master用的脚本

spark-python: Spark的Python客户端

spark-history-server: 任务历史服务

1.系统环境：

OS：CentOS Linux release 7.5.1804 (Core)

CPU：2核心

Memory：1GB

运行用户：root

JDK版本：1.8.0_252

Hadoop版本：cdh5.16.2

2.集群各节点角色规划为：

172.26.37.245 node1.hadoop.com---->namenode，zookeeper，journalnode，hadoop-hdfs-zkfc，resourcenode，historyserver，hbase，hbase-master，hive，hive-metastore，hive-server2,hive-hbase，sqoop，impala，impala-server，impala-state-store，impala-catalog，pig，spark-core，spark-master，spark-worker，spark-python

172.26.37.246 node2.hadoop.com---->datanode，zookeeper，journalnode，nodemanager，hadoop-client，mapreduce，hbase-regionserver，impala，impala-server，hive，spark-core，spark-worker，spark-history-server，spark-python

172.26.37.247 node3.hadoop.com---->datanode，nodemanager，hadoop-client，mapreduce，hive，mysql-server，impala，impala-server，

172.26.37.248 node4.hadoop.com---->namenode，zookeeper，journalnode，hadoop-hdfs-zkfc，hive，hive-server2，impala-shell

3.环境说明：

本次追加部署

172.26.37.245 node1.hadoop.com---->spark-core，spark-master，spark-worker，spark-python

172.26.37.246 node2.hadoop.com---->spark-core，spark-worker，spark-history-server，spark-python

一.安装

node1节点

# yum install -y spark-core spark-master spark-worker spark-python

node2节点

# yum install -y spark-core spark-worker spark-history-server spark-python

二.配置

node1、node2节点

# cp -p /etc/spark/conf/spark-env.sh /etc/spark/conf/spark-env.sh.20200705

# vi /etc/spark/conf/spark-env.sh

插入以下内容

export STANDALONE_SPARK_MASTER_HOST=‘node1.hadoop.com‘ #注意，这里要改为单引号。

Spark History Server需要的hdfs文件夹 /user/spark/applicationHistory/

# sudo -u hdfs hadoop fs -mkdir -p /user/spark/applicationHistory

# sudo -u hdfs hadoop fs -chown -R spark:spark /user/spark

# sudo -u hdfs hadoop fs -chmod 1777 /user/spark/applicationHistory

node1、node2节点

在spark worker端，修改/etc/spark/conf/spark-defaults.conf

# cp -p /etc/spark/conf/spark-defaults.conf /etc/spark/conf/spark-defaults.conf.20200705

# vi /etc/spark/conf/spark-defaults.conf

插入以下内容：

spark.eventLog.dir hdfs://cluser1/user/spark/applicationHistory

spark.eventLog.enabled=true

node1、node2节点复制hdfs-site.xml到/etc/spark/conf下

# cp /etc/hadoop/conf/hdfs-site.xml /etc/spark/conf/

三.启动Spark

Node1节点

# service spark-master start

# service spark-master status

# service spark-worker start

# service spark-worker status

Node2节点

# service spark-worker start

# service spark-worker status

# service spark-history-server start

# service spark-history-server status

打开浏览器访问 http://172.26.37.245:18080 可以看到Spark的管理界面

使用 spark-shell 命令进入spark shell

# sudo -u spark spark-shell

Setting default log level to "WARN".

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