【Hadoop】Spark2.0.2在Hadoop2.7.3上的安装

1、安装Scala

a 下载地址：http://www.scala-lang.org/download/

我选择安装scala-2.12.0.tgz 最新版本。

b 将压缩上传至/usr/local 目录

c 解压tar -zxvf scala-2.12.0.tgz

d 变更软连接

ln -s scala-2.12.0 scala

e 修改配置文件安装

vim /etc/profile

//#add by lekko

export SCALA_HOME=/usr/local/scala

export PATH=PATH:SCALA_HOME/bin

f 配置完毕后 让其生效

source /etc/profile

g 可以查看安装好的Scala版本号是否OK，能执行表示已经安装成功

scala -version

2、Spark安装与配置

a 下载： http://spark.apache.org/downloads.html

中选择最新版本 2.02

b 将压缩上传至/usr/local 目录

c 解压tar -zxvf spark-2.0.2-bin-hadoop2.7.tgz

d 变更软连接

ln -s spark-2.0.2-bin-hadoop2.7 spark

e 修改配置文件安装

vim /etc/profile

//#add by lekko

export SPARK_HOME=/usr/local/spark

export PATH=PATH:SPARK_HOME/bin:$SPARK_HOME/sbin

f 配置完毕后 让其生效

source /etc/profile

g测试环境变量设置是否OK，能执行表示已经安装成功

spark-shell –version

h配置Spark

修改spark-env.sh

cd /usr/local/spark/conf/

cp spark-env.sh.template spark-env.sh

vim spark-env.sh

//#追加如下内容

export SCALA_HOME=/usr/local/scala

export JAVA_HOME=/usr/local/jdkaddress/xxxx

export SPARK_MASTER_IP=192.168.XXX.XXX

export SPARK_WORKER_MEMORY=1024m

export HADOOP_CONF_DIR=/usr/local/hadoop/etc/hadoop

I相关启动停止命令

启动Spark

start-all.sh

推荐使用

start-dfs.sh and start-yarn.sh

停止命令

stop-all.sh

推荐使用

stop-dfs.sh and stop-yarn.sh

如果看到：

This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [master]
master: starting namenode, logging to /home/hadoop/hadoop-2.7.3/logs/hadoop-root-namenode-master.out
121.199.7.226: starting datanode, logging to /home/hadoop/hadoop-2.7.3/logs/hadoop-root-datanode-slave1.out
121.199.51.129: starting datanode, logging to /home/hadoop/hadoop-2.7.3/logs/hadoop-root-datanode-slave2.out
121.199.51.174: starting datanode, logging to /home/hadoop/hadoop-2.7.3/logs/hadoop-root-datanode-slave3.out
Starting secondary namenodes [master]
master: starting secondarynamenode, logging to /home/hadoop/hadoop-2.7.3/logs/hadoop-root-secondarynamenode-master.out
starting yarn daemons
starting resourcemanager, logging to /home/hadoop/hadoop-2.7.3/logs/yarn-root-resourcemanager-master.out
121.199.51.129: starting nodemanager, logging to /home/hadoop/hadoop-2.7.3/logs/yarn-root-nodemanager-slave2.out
121.199.7.226: starting nodemanager, logging to /home/hadoop/hadoop-2.7.3/logs/yarn-root-nodemanager-slave1.out
121.199.51.174: starting nodemanager, logging to /home/hadoop/hadoop-2.7.3/logs/yarn-root-nodemanager-slave3.out

可以知道，表示启动hadoop及 spark成功

J提交任务到Spark集群

spark-submit –master spark://192.XXX.XXX.XXX:7077 –class 主函数入口 –name 自己起个名称 jar包的全路径

例：spark-submit –master spark://192.XXX.XXX.XXX:7077 –class cn.XXXX.XXXXXXXXX.TFIDF –name XXXX XXXX.jar

K提交任务到yarn中

spark-submit –master yarn-cluster –class cn.XXXX.XXXXXXXXX.TFIDF –name XXXX XXXX.jar

通过 http://192.XXX.XXX.XXX:8088/ 查看状态