首页 > 代码库 > 【原】centos6.5下hadoop cdh4.6 安装
【原】centos6.5下hadoop cdh4.6 安装
1、架构准备:
sudo service hadoop-hdfs-journalnode start
namenode 10.0.0.2
secondnamenode 10.0.0.3
datanode1 10.0.0.4
datanode2 10.0.0.6
datanode3 10.0.0.11
2、安装用户:cloud-user
3、[namenode]namenode到其他节点ssh无密码登录:
ssh-keygen (一路回车)
ssh-copy-id cloud-user@10.0.0.3
ssh-copy-id cloud-user@10.0.0.4
ssh-copy-id cloud-user@10.0.0.6
ssh-copy-id cloud-user@10.0.0.11
4、[ALL]cdh源的准备:
wget
http://archive.cloudera.com/cdh4/redhat/5/x86_64/cdh/RPM-GPG-KEY-cloudera sudo rpm --import RPM-GPG-KEY-cloudera
cd /etc/yum.repos.d/ && sudo wget http://archive.cloudera.com/cdh4/one-click-install/redhat/6/x86_64/cloudera-cdh-4-0.x86_64.rpm
sudo yum --nogpgcheck localinstall cloudera-cdh-4-0.x86_64.rpm
cd /etc/yum.repos.d/ && sudo wget http://archive.cloudera.com/gplextras/redhat/6/x86_64/gplextras/cloudera-gplextras4.repo
sudo yum clean all && sudo yum makecache
5、[ALL]java的安装:这里用的是jdk-6u45-linux-x64-rpm.bin
chmod +x jdk-6u45-linux-x64-rpm.bin && sudo ./jdk-6u45-linux-x64-rpm.bin
6、 [ALL]添加java的环境变量:
/etc/profile中添加:
?
1 2 3 4 5 6 | <span style= ‘font-family: "courier new", courier;‘ >export JAVA_HOME=/usr/java/jdk1.6.0_45 export JRE_HOME=$JAVA_HOME/jre export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib:$CLASSPATH export PATH=$JAVA_HOME/bin:$JRE_HOME/bin:$PATH export HADOOP_MAPRED_HOME=/usr/lib/hadoop-mapreduce </span> |
使之生效:source /etc/profile
7、安装cdh包:
sudo yum install -y hadoop-yarn-resourcemanager hadoop-mapreduce-historyserver hadoop-yarn-proxyserver hadoop-hdfs-namenode //仅在namenode上安装
sudo yum install -y hadoop-hdfs-namenode //仅在secondnamenode上安装
sudo yum install -y hadoop-yarn-nodemanager hadoop-hdfs-datanode hadoop-mapreduce //在datanode1,datanode2,datanode3上安装
sudo yum install -y hadoop-lzo-cdh4 //在所有节点上安装
8、[ALL]配置hadoop:
sudo service iptables stop && sudo service ip6tables stop
sudo echo -e "namenode\nsecondnamenode" >> /etc/hadoop/conf/masters && sudo echo -e "datanode1\ndatanode2\ndatanode3" >> /etc/hadoop/conf/slaves
sudo cp -r /etc/hadoop/conf.dist /etc/hadoop/conf.my_cluster && sudo alternatives --verbose --install /etc/hadoop/conf hadoop-conf /etc/hadoop/conf.my_cluster 50 && sudo alternatives --set hadoop-conf /etc/hadoop/conf.my_cluster
core-site.xml:
<property>
<name>fs.defaultFS</name>
<value>hdfs://sdc</value>
</property>
<property>
<name>ha.zookeeper.quorum</name>
<value>datanode1:2181,datanode2:2181,datanode3:2181</value>
</property>
<property>
<name>fs.trash.interval</name>
<value>10080</value>
</property>
<property>
<name>fs.trash.checkpoint.interval</name>
<value>10080</value>
</property>
<property>
<name>hadoop.native.lib</name>
<value>true</value>
</property>
<property>
<name>hadoop.proxyuser.mapred.groups</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.mapred.hosts</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.oozie.hosts</name>
<value>10.0.0.2</value>
</property>
<property>
<name>hadoop.proxyuser.oozie.groups</name>
<value>*</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,com.hadoop.compression.lzo.LzoCodec,com.hadoop.compression.lzo.LzopCodec,org.apache.hadoop.io.compress.SnappyCodec</value>
</property>
hdfs-site.xml:
<property>
<name>dfs.replication</name>
<value>3</value>
</property>
<property>
<name>dfs.nameservices</name>
<value>sdc</value>
</property>
<property>
<name>dfs.ha.namenodes.sdc</name>
<value>nn1,nn2</value>
</property>
<!--配置rpc通信地址:dfs.namenode.rpc-address.[nameservice ID].-->
<property>
<name>dfs.namenode.rpc-address.sdc.nn1</name>
<value>namenode:8020</value>
</property>
<property>
<name>dfs.namenode.rpc-address.sdc.nn2</name>
<value>secondnamenode:8020</value>
</property>
<!--配置http通信地址:dfs.namenode.http-address.[nameservice ID] -->
<property>
<name>dfs.namenode.http-address.sdc.nn1</name>
<value>namenode:50070</value>
</property>
<property>
<name>dfs.namenode.http-address.sdc.nn2</name>
<value>secondnamenode:50070</value>
</property>
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://datanode1:8485;datanode2:8485;datanode3:8485/sdc</value>
</property>
<property>
<name>dfs.permissions.superusergroup</name>
<value>hadoop</value>
</property>
<property>
<name>dfs.permissions</name>
<value>false</value>
</property>
<property>
<name>dfs.permissions.enabled</name>
<value>false</value>
</property>
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/data/1/dfs/jn</value>
</property>
<!--配置客户端failover,解决客户端故障转移-->
<property>
<name>dfs.client.failover.proxy.provider.sdc</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:///data/1/dfs/nn,/nfsmount/dfs/nn</value>
</property>
<!--配置:Fencing,
这里dfs.ha.fencing.methods实现的方法有两种sshfence和shell,我下面实现的是sshfence,dfs.ha.fencing.ssh.private-key-files这个是ssh的key file ,于在Active 节点切换期间的安全机制,确保在任何时间都只有一个NameNode 处于活跃状态。在故障切换期间,haadmin 命令确保在将其它NameNode 转换为Active 状态之前Active 节点处在Standby 状态,或其进程已被终止。
至少应该配置一个,因为没有默认配置,因此如果配置则HA 机制将会失效。
如果要实现自定义的安全机制,参照org.apache.hadoop.ha.NodeFencer
-->
<property>
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/home/cloud-user/.ssh/id_rsa</value>
</property>
<!--启用失败自动切换-->
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<!--配置zk集群信息-->
<property>
<name>ha.zookeeper.quorum</name>
<value>datanode1:2181,datanode2:2181,datanode3:2181</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:///data/1/dfs/dn,/data/2/dfs/dn,/data/3/dfs/dn</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
<property>
<name>dfs.ha.fencing.ssh.connect-timeout</name>
<value>10000</value>
</property>
mapred-site.xml:
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>yarn.app.mapreduce.am.staging-dir</name>
<value>/user</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>namenode:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>namenode:19888</value>
</property>
yarn-site.xml:
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>namenode:8031</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>namenode:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>namenode:8030</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>namenode:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>namenode:8088</value>
</property>
<property>
<name>yarn.web-proxy.address</name>
<value>namenode:8100</value>
</property>
<property>
<description>Classpath for typical applications.</description>
<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/*,
$YARN_HOME/*,$YARN_HOME/lib/*
</value>
</property>
<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.nodemanager.local-dirs</name>
<value>file:///data/1/yarn/local,file:///data/2/yarn/local,file:///data/3/yarn/local</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>file:///data/1/yarn/logs,file:///data/2/yarn/logs,file:///data/3/yarn/logs</value>
</property>
<property>
<description>Where to aggregate logs</description>
<name>yarn.nodemanager.remote-app-log-dir</name>
<value>hdfs://var/log/hadoop-yarn/apps</value>
</property>
9、建立配置所需文件目录:
[ALL]:sudo mkdir -p /data/1/yarn/local /data/2/yarn/local /data/3/yarn/local /data/4/yarn/local && sudo mkdir -p /data/1/yarn/logs /data/2/yarn/logs /data/3/yarn/logs /data/4/yarn/logs && sudo chown -R yarn:yarn /data/1/yarn/local /data/2/yarn/local /data/3/yarn/local /data/4/yarn/local && sudo chown -R yarn:yarn /data/1/yarn/logs /data/2/yarn/logs /data/3/yarn/logs /data/4/yarn/logs
datanode:
sudo mkdir -p /data/1/dfs/jn && sudo chown -R hdfs:hdfs /data/1/dfs/jn
Namenode:
sudo mkdir -p /data/1/dfs/nn /nfsmount/dfs/nn && sudo chown -R hdfs:hdfs /data/1/dfs/nn /nfsmount/dfs/nn &&sudo chmod 700 /data/1/dfs/nn /nfsmount/dfs/nn
Datanode:
sudo mkdir -p /data/1/dfs/dn /data/2/dfs/dn /data/3/dfs/dn /data/4/dfs/dn && sudo chown -R hdfs:hdfs /data/1/dfs/dn /data/2/dfs/dn /data/3/dfs/dn /data/4/dfs/dn
10、[datanode]在datanode上安装zookeeper:
sudo yum install -y zookeeper
配置/etc/zookeeper/conf/zoo.cfg:
tickTime=2000
dataDir=/var/lib/zookeeper/
clientPort=2181
initLimit=5
syncLimit=2
server.1=datanode1:2888:3888
server.2=datanode2:2888:3888
server.3=datanode3:2888:3888
配置id:
sudo echo 1 > /var/lib/zookeeper/myid //仅在namenode1上执行
sudo echo 2 > /var/lib/zookeeper/myid //仅namenode2上执行
sudo echo 3 > /var/lib/zookeeper/myid //namenode3上执行
sudo chown -R zookeeper:zookeeper /var/lib/zookeeper //在所有datanode上
启动zookeeper:
sudo /usr/lib/zookeeper/bin/zkServer.sh start
查看状态:
sudo /usr/lib/zookeeper/bin/zkServer.sh start
11、namenode上格式化ZooKeeper集群:
sudo -u hdfs hdfs zkfc -formatZK
12、[datanode]安装并启动JournalNode集群:
sudo yum install -y hadoop-hdfs-journalnodesudo service hadoop-hdfs-journalnode start
13、[namenode]namenode上格式化namenode并启动:
sudo -u hdfs hdfs namenode -format sudo service hadoop-hdfs-namenode start
14、[secondnamenode]同步数据到secondnamenode上并启动:
sudo -u hdfs hdfs namenode -bootstrapStandby
sudo service hadoop-hdfs-namenode start
sudo service hadoop-mapreduce-historyserver start
sudo service hadoop-yarn-proxyserver start
sudo -u hdfs hdfs namenode -bootstrapStandby
sudo service hadoop-hdfs-namenode start
15、[datanode]启动所有的datanode:
sudo service hadoop-hdfs-datanode start 16、[namenode]启动yarn服务:
sudo service hadoop-yarn-resourcemanager startsudo service hadoop-mapreduce-historyserver start
sudo service hadoop-yarn-proxyserver start
17、[datanode]datanode上启动yarn:
sudo service hadoop-yarn-nodemanager start
sudo service hadoop-hdfs-zkfc start
sudo -u hdfs hadoop fs -chown mapred:hadoop /user/history
sudo -u hdfs hadoop fs -mkdir /var/log/hadoop-yarn
sudo -u hdfs hadoop fs -chown yarn:mapred /var/log/hadoop-yarn
sudo -u hdfs hadoop fs -mkdir /tmp
sudo -u hdfs hadoop fs -chmod -R 1777 /tmp
sudo -u hdfs hadoop fs -mkdir /user/hive
sudo -u hdfs hadoop fs -mkdir /user/hive/warehouse
sudo -u hdfs hadoop fs -chown -R hive /user/hive
sudo -u hdfs hadoop fs -chmod -R 1777 /user/hive/warehouse
sudo -u hdfs hadoop fs -mkdir /tmp/hadoop-mapred
sudo -u hdfs hadoop fs -mkdir /tmp/hive-hive
sudo -u hdfs hadoop fs -chmod -R 777 /tmp/hadoop-mapred
sudo -u hdfs hadoop fs -chmod -R 777 /tmp/hive-hive
sudo -u hdfs hadoop fs -mkdir /user/cloud-user
sudo -u hdfs hadoop fs -chown cloud-user:cloud-user /user/cloud-user
18、[namenode + secondnamenode]安装并启动ZooKeeperFailoverCotroller:
sudo yum install -y hadoop-hdfs-zkfcsudo service hadoop-hdfs-zkfc start
19、[ALL]检测状态:
sudo /usr/java/jdk1.6.0_45/bin/jps
20、建立hdfs文件目录(有些是以后用到的):
sudo -u hdfs hadoop fs -mkdir /user/history
sudo -u hdfs hadoop fs -chmod -R 1777 /user/historysudo -u hdfs hadoop fs -chown mapred:hadoop /user/history
sudo -u hdfs hadoop fs -mkdir /var/log/hadoop-yarn
sudo -u hdfs hadoop fs -chown yarn:mapred /var/log/hadoop-yarn
sudo -u hdfs hadoop fs -mkdir /tmp
sudo -u hdfs hadoop fs -chmod -R 1777 /tmp
sudo -u hdfs hadoop fs -mkdir /user/hive
sudo -u hdfs hadoop fs -mkdir /user/hive/warehouse
sudo -u hdfs hadoop fs -chown -R hive /user/hive
sudo -u hdfs hadoop fs -chmod -R 1777 /user/hive/warehouse
sudo -u hdfs hadoop fs -mkdir /tmp/hadoop-mapred
sudo -u hdfs hadoop fs -mkdir /tmp/hive-hive
sudo -u hdfs hadoop fs -chmod -R 777 /tmp/hadoop-mapred
sudo -u hdfs hadoop fs -chmod -R 777 /tmp/hive-hive
sudo -u hdfs hadoop fs -mkdir /user/cloud-user
sudo -u hdfs hadoop fs -chown cloud-user:cloud-user /user/cloud-user
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