文档编写目的
在进行CDH集群安装部署的时候，官方提供了三种方式，parcels、packages以及tarball，官方推荐使用parcels的方式进行安装，这也是最常用的安装方式，通常我们使用CM图形化界面的操作方式来安装CDH集群，本文档将介绍的是官方提供的另一种安装方式，使用packages安装，即rpm包的方式进行CDH集群的安装，并且本次安装是使用没有CM的方式进行安装。
环境介绍：
·安装部署使用root用户进行操作
·安装的CDH版本为5.10.0
·服务器的操作系统为RedHat7.2
·安装不使用CM
·CDH集群安装在三个节点
安装前置准备
2.1服务器相关设置
安装CDH集群时需要做一些前置的准备，本次安装使用的环境已经做好前置准备，需要做的准备如下：
1.hosts以及hostname配置正确
2.服务器没有启用IPv6且配置了静态IP
3.禁用SELinux
4.关闭防火墙
5.设置swappiness为1
6.关闭透明大页面
7.配置NTP时钟同步
2.2 配置本地Yum源
1.在官网下载好需要的rpm包，地址如下：
http://archive.cloudera.com/cdh5/redhat/7/x86_64/cdh/5.10.0/RPMS/
将上面所有的rpm包下载到服务器，如下：
在浏览器进行验证
2.执行createrepo命令
createrepo .
3.创建repo文件
[rpmrepo] name = rpm_repo baseurl = http://192.168.0.178/cdh_rpm/ enable = true gpgcheck = false
4.执行yum命令，查看本地yum源是否配置成功
yum clean all yum repolist
上图可以看到，下载的rpm包制作的本地yum源成功
CDH组件安装
3.1 ZooKeeper
1.在所有节点安装Zookeeper
yum install zookeepe
2.创建数据目录并修改属主
mkdir -p /var/lib/zookeeper chown -R zookeeper /var/lib/zookeeper
3.修改配置文件/etc/zookeeper/conf/zoo.cfg
maxClientCnxns=60 tickTime=2000 initLimit=10 syncLimit=5 dataDir=/var/lib/zookeeper clientPort=2181 dataLogDir=/var/lib/zookeeper minSessionTimeout=4000 maxSessionTimeout=40000 server.1=cdh178.macro.com:3181:4181 server.2=cdh177.macro.com:3181:4181 server.3=cdh176.macro.com:3181:4181
保存修改并同步到所有节点
4.所有节点创建myid文件并修改属主
5.所有节点启动Zookeeper
/usr/lib/zookeeper/bin/zkServer.sh start
查看所有节点启动状态，三个节点均启动成功
/usr/lib/zookeeper/bin/zkServer.sh status
至此Zookeeper安装完成
3.2 HDFS
1.在所有节点安装HDFS必需的包，由于只有三个节点，所以三个节点都安装DataNode
yum -y install hadoop hadoop-hdfs hadoop-client hadoop-doc hadoop-debuginfo hadoop-hdfs-datanode
2.在一个节点安装NameNode以及SecondaryNameNode
yum -y install hadoop-hdfs-namenode hadoop-hdfs-secondarynamenode
3.创建数据目录并修改属主和权限
所有节点创建DataNode的目录
mkdir -p /data0/dfs/dn chown -R hdfs:hadoop /data0/dfs/dn chmod 700 /data0/dfs/dn
NameNode和SecondaryNameNode节点创建数据目录
mkdir -p /data0/dfs/nn chown -R hdfs:hadoop /data0/dfs/nn chmod 700 /data0/dfs/nn mkdir -p /data0/dfs/snn chown -R hdfs:hadoop /data0/dfs/snn chmod 700 /data0/dfs/snn
4.修改配置文件
/etc/hadoop/conf/core-site.xml
<configuration> <property> <name>fs.defaultFS</name> <value>hdfs://cdh178.macro.com:8020</value> </property> <property> <name>fs.trash.interval</name> <value>1</value> </property> <property> <name>io.compression.codecs</name> <value>org.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.BZip2Codec,org.apache.hadoop.io.compress.DeflateCodec,org.apache.hadoop.io.compress.SnappyCodec,org.apache.hadoop.io.compress.Lz4Codec</value> </property> </configuration>
/etc/hadoop/conf/hdfs-site.xml
<configuration> <property> <name>dfs.namenode.name.dir</name> <value>file:///data0/dfs/nn</value> </property> <property> <name>dfs.datanode.data.dir</name> <value>file:///data0/dfs/dn</value> </property> <property> <name>dfs.namenode.servicerpc-address</name> <value>cdh178.macro.com:8022</value> </property> <property> <name>dfs.https.address</name> <value>cdh178.macro.com:9871</value> </property> <property> <name>dfs.secondary.http.address</name> <value>cdh178.macro.com:50090</value> </property> <property> <name>dfs.https.port</name> <value>9871</value> </property> <property> <name>dfs.namenode.http-address</name> <value>cdh178.macro.com:9870</value> </property> <property> <name>dfs.replication</name> <value>3</value> </property> <property> <name>dfs.blocksize</name> <value>134217728</value> </property> <property> <name>dfs.namenode.checkpoint.dir</name> <value>file:///data0/dfs/snn</value> </property> </configuration>
5.将修改的配置文件保存并同步到所有节点
6.格式化NameNode
hdfs namenode -format
7.在所有节点运行命令启动HDFS
systemctl start hadoop-hdfs-namenode systemctl start hadoop-hdfs-secondarynamenode systemctl start hadoop-hdfs-datanode systemctl status hadoop-hdfs-namenode systemctl status hadoop-hdfs-secondarynamenode systemctl status hadoop-hdfs-datanode ?
8.创建/tmp临时目录，并设置目录权限，然后使用hadoop命令查看创建的目录成功
sudo -u hdfs hadoop fs -mkdir /tmp sudo -u hdfs hadoop fs -chmod -R 1777 /tmp
9.访问NameNode的Web UI
至此HDFS安装完成
3.3 Yarn
1.安装Yarn的包，在一个节点安装ResourceManager和JobHistory Server，另外两个节点安装NodeManager
yum -y install hadoop-yarn hadoop-yarn-resourcemanager hadoop-mapreduce-historyserver hadoop-yarn-proxyserver hadoop-mapreduce
yum -y install hadoop-yarn hadoop-yarn-nodemanager hadoop-mapreduce
2.创建目录并修改属主和权限
在所有节点创建本地目录
mkdir -p /data0/yarn/nm chown yarn:hadoop /data0/yarn/nm mkdir -p /data0/yarn/container-logs chown yarn:hadoop /data0/yarn/container-logs
在HDFS上创建logs目录
sudo -u hdfs hdfs dfs -mkdir /tmp/logs sudo -u hdfs hdfs dfs -chown mapred:hadoop /tmp/logs sudo -u hdfs hdfs dfs -chmod 1777 /tmp/logs ?
在HDFS上创建/user/history目录
sudo -u hdfs hdfs dfs -mkdir -p /user sudo -u hdfs hdfs dfs -chmod 777 /user sudo -u hdfs hdfs dfs -mkdir -p /user/history sudo -u hdfs hdfs dfs -chown mapred:hadoop /user/history sudo -u hdfs hdfs dfs -chmod 1777 /user/history sudo -u hdfs hdfs dfs -mkdir -p /user/history/done sudo -u hdfs hdfs dfs -mkdir -p /user/history/done_intermediate sudo -u hdfs hdfs dfs -chown -R mapred:hadoop /user/history sudo -u hdfs hdfs dfs -chmod 771 /user/history/done sudo -u hdfs hdfs dfs -chmod 1777 /user/history/done_intermediate ?
3.修改配置文件
/etc/hadoop/conf/yarn-site.xml
<configuration> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> <property> <name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name> <value>org.apache.hadoop.mapred.ShuffleHandler</value> </property> <property> <name>yarn.log-aggregation-enable</name> <value>true</value> </property> <property> <name>yarn.nodemanager.local-dirs</name> <value>file:///data0/yarn/nm</value> </property> <property> <name>yarn.nodemanager.log-dirs</name> <value>file:///data0/yarn/container-logs</value> </property> <property> <name>yarn.nodemanager.remote-app-log-dir</name> <value>/tmp/logs</value> </property> <property> <name>yarn.application.classpath</name> <value>$HADOOP_CONF_DIR,$HADOOP_COMMON_HOME/*,$HADOOP_COMMON_HOME/lib/*,$HADOOP_HDFS_HOME/*,$HADOOP_HDFS_HOME/lib/*,$HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,$HADOOP_YARN_HOME/*,$HADOOP_YARN_HOME/lib/*</value> </property> <property> <name>yarn.resourcemanager.address</name> <value>cdh178.macro.com:8032</value> </property> <property> <name>yarn.resourcemanager.admin.address</name> <value>cdh178.macro.com:8033</value> </property> <property> <name>yarn.resourcemanager.scheduler.address</name> <value>cdh178.macro.com:8030</value> </property> <property> <name>yarn.resourcemanager.resource-tracker.address</name> <value>cdh178.macro.com:8031</value> </property> <property> <name>yarn.resourcemanager.webapp.address</name> <value>cdh178.macro.com:8088</value> </property> <property> <name>yarn.resourcemanager.webapp.https.address</name> <value>cdh178.macro.com:8090</value> </property> </configuration> ?
/etc/hadoop/conf/mapred-site.xml
<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.jobhistory.address</name> <value>cdh178.macro.com:10020</value> </property> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>cdh178.macro.com:19888</value> </property> <property> <name>mapreduce.jobhistory.webapp.https.address</name> <value>cdh178.macro.com:19890</value> </property> <property> <name>mapreduce.jobhistory.admin.address</name> <value>cdh178.macro.com:10033</value> </property> <property> <name>yarn.app.mapreduce.am.staging-dir</name> <value>/user</value> </property> </configuration> ?
/etc/hadoop/conf/core-site.xml，下面只贴出修改的部分配置
<property> <name>hadoop.proxyuser.mapred.groups</name> <value>*</value> </property> <property> <name>hadoop.proxyuser.mapred.hosts</name> <value>*</value> </property> ?
4.将配置文件保存后同步到所有节点
5.启动Yarn服务
在JobHistoryServer节点上启动mapred-historyserver
/etc/init.d/hadoop-mapreduce-historyserver start
在RM节点启动ResourceManager
systemctl start hadoop-yarn-resourcemanager systemctl status hadoop-yarn-resourcemanager ?
在NM节点启动NodeManager
systemctl start hadoop-yarn-nodemanager systemctl status hadoop-yarn-nodemanager ?
6.访问Yarn服务的Web UI
Yarn的管理页面
JobHistory的管理页面
查看在线的节点
7.运行MR示例程序
使用root用户运行示例程序，所以要先创建root用户的目录
sudo -u hdfs hdfs dfs -mkdir /user/root sudo -u hdfs hdfs dfs -chown root:root /user/root
运行MR示例程序，运行成功
hadoop jar /usr/lib/hadoop-mapreduce/hadoop-mapreduce-examples.jar pi 5 5
至此Yarn服务安装完成
3.4 Spark
1.安装Spark所需的包
yum install spark-core spark-master spark-worker spark-history-server spark-python
2.创建目录并修改属主和权限
sudo -u hdfs hadoop fs -mkdir /user/spark sudo -u hdfs hadoop fs -mkdir /user/spark/applicationHistory sudo -u hdfs hadoop fs -chown -R spark:spark /user/spark sudo -u hdfs hadoop fs -chmod 1777 /user/spark/applicationHistory ?
3.修改配置文件/etc/spark/conf/spark-defaults.conf
spark.eventLog.enabled=true spark.eventLog.dir=hdfs://cdh178.macro.com:8020/user/spark/applicationHistory spark.yarn.historyServer.address=http://cdh178.macro.com:18088 ?
4.启动spark-history-server
systemctl start spark-history-server systemctl status spark-history-server ?
访问Web UI
5.修改配置文件并同步到所有节点
6.启动Spark
在Master节点启动spark-master
systemctl start spark-master systemctl status spark-master ?
在所有节点启动spark-worker
systemctl start spark-worker systemctl status spark-worker ?
7.测试Spark使用
至此Spark安装完成