大数据:spark集群搭建
创建spark用户组,组ID1000
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groupadd -g 1000 spark
在spark用户组下创建用户ID 2000的spark用户 获取视频中文档资料及完整视频的伙伴请加QQ群:947967114
useradd -u 2000 -g spark spark
设置密码
passwd spark
修改sudo权限
chmod u+w /etc/sudoers
vi /etc/sudoers
找到
root ALL=(ALL) ALL
添加
spark ALL=(ALL) ALL
创建一个app目录用来存放spark的软件环境(jdk、scala、spark)
mkdir /app
修改这个文件的属组和属主
chown -R spark:spark /app
创建soft
mkdir /app/soft
创建spark
mkdir /app/spark
创建/spark/work
mkdir -p /home/spark/work
改变/spark/work属组和属主
chown -R spark:spark /home/spark/work
切换用户
su root
解压JDK
cd /tmp/
tar zxvf jdk-8u192-linux-x64.tar.gz -C /app/soft/
如果没有权限首先使用chmod 777 -R /tmp修改权限
cd /app/soft/
ll -a
配置/etc/profile
sudo vi /etc/profile,所有需要的配置都添加了
JAVA_HOME=/app/soft/jdk1.8.0_192
PATH=$JAVA_HOME/bin:$PATH:$HOME/bin
export PATH
让配置生效 获取视频中文档资料及完整视频的伙伴请加QQ群:947967114
source /etc/profile
安装scala:
tar zxvf /tmp/scala-2.11.12.tgz -C /app/soft/
配置环境变量
sudo vi /etc/profile
JAVA_HOME=/app/soft/jdk1.8.0_192
SCALA_HOME=/app/soft/scala-2.11.12/
PATH=$JAVA_HOME/bin:$PATH:$HOME/bin:$SCALA_HOME/bin
export PATH
配置ssh无秘登录
ssh-keygen -t rsa
cd ~/
cd .ssh/
修改公钥的名字
master节点:mv id_rsa.pub authorized_keys_master.pub
slave1节点:mv id_rsa.pub authorized_keys_slave1.pub
slave2节点:mv id_rsa.pub authorized_keys_slave2.pub
把slave1和slave2的公钥给master
slave1节点:scp authorized_keys_slave1.pub spark@master:/home/spark/.ssh/
slave2节点:scp authorized_keys_slave2.pub spark@master:/home/spark/.ssh/
把三个节点的公钥都写在一个文件中
cat authorized_keys_master.pub >> authorized_keys
cat authorized_keys_slave1.pub >> authorized_keys
cat authorized_keys_slave2.pub >> authorized_keys
查看一下总的公钥文件
vi authorized_keys
把总的公钥文件authorized_keys给到slave1和slave2节点
scp authorized_keys spark@slave1:/home/spark/.ssh
scp authorized_keys spark@slave2:/home/spark/.ssh
修改authorized_keys的操作权限,三个节点都需要修改
chmod 400 authorized_keys
验证免密登录是否成功
ssh master
ssh slave1
ssh slave2
ssh master
安装spark:
tar -zxf /tmp/spark-2.1.0-bin-hadoop2.6.gz -C /app/spark/
cd /app/spark/
ls
cd spark-2.1.0-bin-hadoop2.6/
配置环境变量:
vi /etc/profile
JAVA_HOME=/app/soft/jdk1.8.0_192
SCALA_HOME=/app/soft/scala-2.11.12/
SPARK_HOME=/app/spark/spark-2.1.0-bin-hadoop2.6
PATH=$SPARK_HOME/bin:$SPARK_HOME/sbin:$JAVA_HOME/bin:$PATH:$HOME/bin:$SCALA_HOME/bin
export PATH
配置spark的核心文件:
cd spark-2.1.0-bin-hadoop2.6/
cd conf/
配置slaves
mv slaves.template slaves
vi slaves 添加三个节点
master
slave1
slave2
配置spark-env.sh
cp spark-env.sh.template spark-env.sh
vi spark-env.sh
export JAVA_HOME=/app/soft/jdk1.8.0_192
export SCALA_HOME=/app/soft/scala-2.11.12
export SPARK_MASTER_IP=master
export SPARK_MASTER_PORT=7077
export SPARK_EXECUTOR_INSTANCES=1
export SPARK_WORKER_INSTANCES=1
export SPARK_WORKER_CORES=1
export SPARK_WORKER_MEMORY=1024M
export SPARK_MASTER_WEBUI=8080
export SPARK_CONF_DIR=/app/spark/spark-2.1.0-bin-hadoop2.6/conf/
把所有的节点的app的work和soft权限都改成777:在所有的节点上执行 chmod 777 -R /app/soft 和chmod 777 -R /app/spark
scp -r /app/spark/ spark@slave1:/app/
scp -r /app/soft/ spark@slave1:/app/
到此spark集群已经搭建完成:
开启:start-all.sh获取视频中文档资料及完整视频的伙伴请加QQ群:947967114
jps可以看到如下进程:
master节点:
3617 Worker
3507 Master
4156 Jps
slave1节点:
3361 Worker
3702 Jps
slave2节点:
3319 Worker
3647 Jps
开启spark-shell验证:
spark-shell --master spark://master:7077 --executor-memory 1024m --driver-memory 1024m
启动之后会显示如下内容:
18/11/29 16:13:46 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
18/11/29 16:13:47 WARN ObjectStore: Failed to get database global_temp, returning NoSuchObjectException
Spark context Web UI available at http://192.168.0.10:4040
Spark context available as 'sc' (master = spark://master:7077, app id = app-20181129161336-0000).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
// ./_,// //_\ version 2.1.0
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_192)
Type in expressions to have them evaluated.
Type :help for more information.
scala>
就可以在>后面书写spark代码了:
g NoSuchObjectException
Spark context Web UI available at http://192.168.0.10:4040
Spark context available as 'sc' (master = spark://master:7077, app id = app-20181129161336-0000).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
// ./_,// //_\ version 2.1.0
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_192)
Type in expressions to have them evaluated.
Type :help for more information.
scala> sc.textFile("/app/spark/spark-2.1.0-bin-hadoop2.6/README.md").flatMap(.split(" ")).map(x=>(x,1)).reduceByKey(+_).map(x=>(x._2,x._1)).sortByKey(false).map(x=>(x._2,x._1)).take(10)
res0: Array[(String, Int)] = Array(("",71), (the,24), (to,17), (Spark,16), (for,12), (and,9), (##,8), (a,8), (can,7), (run,7))
scala>获取视频中文档资料及完整视频的伙伴请加QQ群:947967114
名称栏目:大数据:spark集群搭建
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