hadoop 2.7 分布式安装 + HA
hadoop 2.7 分布式安装 + HA 开始安装：
1、解压hadoop并修改环境变量（每台机器）
[hadoop@new-cdh1 soft]$ tar -zvxf hadoop-2.6.0-cdh5.7.0.tar.gz
[hadoop@new-cdh1 soft]$ vi ~/.bash_profile
# .bash_profile
# Get the aliases and functions
if [ -f ~/.bashrc ]; then
. ~/.bashrc
fi
# User specific environment and startup programs
export HADOOP_HOME=/hadoop/soft/hadoop-2.6.0-cdh5.7.0
PATH=HOME/bin:HADOOP_HOME/sbin
export PATH
[hadoop@new-cdh1 soft]$ source ~/.bash_profile
2、修改$HADOOP_HOME/etc/hadoop/slaves文件
[hadoop@new-cdh1 soft]$ vi hadoop-2.6.0-cdh5.7.0/etc/hadoop/slaves
new-cdh15
new-cdh16
new-cdh5
new-cdh6
new-cdh7
new-cdh9
new-cdh10
new-cdh11
new-cdh12
new-cdh13
3、修改HADOOP_HOME/etc/hadoop/yarn-env.sh文件
[hadoop@new-cdh1 soft]$ vi hadoop-2.6.0-cdh5.7.0/etc/hadoop/hadoop-env.sh
…
export JAVA_HOME=/opt/jdk1.7.0_79
…
[hadoop@new-cdh1 soft]$ vi hadoop-2.6.0-cdh5.7.0/etc/hadoop/yarn-env.sh
…
export JAVA_HOME=/opt/jdk1.7.0_79
…
4、修改HADOOPHOME/etc/hadoop/core−site.xml文件
5、修改HADOOPHOME/etc/hadoop/mapred−site.xml文件
6、修改HADOOP_HOME/etc/hadoop/hdfs-site.xml文件
7、修改HADOOP_HOME/etc/hadoop/yarn-site.xml文件
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<configuration>
<property>
<name>yarn.resourcemanager.ha.rm-ids</name>
<value>rm1,rm2</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm1</name>
<value>new-cdh3</value>
</property>
<property>
<name>yarn.resourcemanager.hostname.rm2</name>
<value>new-cdh4</value>
</property>
<property>
<name>yarn.resourcemanager.ha.id</name>
<value>rm1</value>
</property>
<property>
<name>yarn.resourcemanager.address.rm1</name>
<value>${yarn.resourcemanager.hostname.rm1}:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address.rm1</name>
<value>${yarn.resourcemanager.hostname.rm1}:8030</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.https.address.rm1</name>
<value>${yarn.resourcemanager.hostname.rm1}:8089</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address.rm1</name>
<value>${yarn.resourcemanager.hostname.rm1}:8088</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address.rm1</name>
<value>${yarn.resourcemanager.hostname.rm1}:8025</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address.rm1</name>
<value>${yarn.resourcemanager.hostname.rm1}:8041</value>
</property>
<property>
<name>yarn.resourcemanager.address.rm2</name>
<value>${yarn.resourcemanager.hostname.rm2}:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address.rm2</name>
<value>${yarn.resourcemanager.hostname.rm2}:8030</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.https.address.rm2</name>
<value>${yarn.resourcemanager.hostname.rm2}:8089</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address.rm2</name>
<value>${yarn.resourcemanager.hostname.rm2}:8088</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address.rm2</name>
<value>${yarn.resourcemanager.hostname.rm2}:8025</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address.rm2</name>
<value>${yarn.resourcemanager.hostname.rm2}:8041</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.resourcemanager.ha.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.nodemanager.local-dirs</name>
<value>/hadoop/data/yarn/local</value>
</property>
<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/hadoop/data/yarn/log</value>
</property>
<property>
<name>yarn.client.failover-proxy-provider</name>
<value>org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider</value>
</property>
<property>
<name>yarn.resourcemanager.zk-state-store.address</name>
<value>new-cdh12:2181,new-cdh13:2181,new-cdh15:2181,new-cdh16:2181,new-cdh17:2181</value>
</property>
<property>
<name>yarn.resourcemanager.zk-address</name>
<value>new-cdh12:2181,new-cdh13:2181,new-cdh15:2181,new-cdh16:2181,new-cdh17:2181</value>
</property>
<property>
<name>yarn.resourcemanager.store.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
</property>
<property>
<name>yarn.resourcemanager.cluster-id</name>
<value>cluster</value>
</property>
<property>
<name>yarn.resourcemanager.recovery.enabled</name>
<value>true</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
</property>
<property>
<name>yarn.scheduler.fair.allocation.file</name>
<value>/hadoop/soft/hadoop-2.6.0-cdh5.7.0/etc/hadoop/fairscheduler.xml</value>
</property>
</configuration>
8、添加$HADOOP_HOME/etc/hadoop/fairscheduler.xml文件
9、创建相关文件夹
在相关的机器上创建文件夹
mkdir -p /hadoop/data/journal;
mkdir -p /hadoop/data/dfs/name;
mkdir -p /hadoop/data/dfs/data;
mkdir -p /hadoop/data/yarn/local;
mkdir -p /hadoop/data/yarn/log
10、复制集群到其他机器
[hadoop@new-cdh1 soft]$ scp -r hadoop-2.6.0-cdh5.7.0 new-cdh2:~/soft/
[hadoop@new-cdh1 soft]$ scp -r hadoop-2.6.0-cdh5.7.0 new-cdh3:~/soft/
…
…
…
11、修改new-cdh4配置文件
<property>
<name>yarn.resourcemanager.ha.id</name>
<value>rm2</value>
</property>
12、第一次启动
1、启动zookeeper（略）
2、格式化ZooKeeper集群
在new-cdh1 执行
[hadoop@new-cdh1 soft]$ hdfs zkfc -formatZK
…
…
16/06/22 17:51:37 INFO zookeeper.ClientCnxn: Session establishment complete on server new-cdh15/192.168.36.15:2181, sessionid = 0xf5576a58dc00004, negotiated timeout = 5000
16/06/22 17:51:37 INFO ha.ActiveStandbyElector: Session connected.
16/06/22 17:51:37 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/familyha in ZK.
16/06/22 17:51:37 INFO zookeeper.ZooKeeper: Session: 0xf5576a58dc00004 closed
16/06/22 17:51:37 INFO zookeeper.ClientCnxn: EventThread shut down
zookeeper 查看格式化效果
[hadoop@new-cdh12 ~]$ zkCli.sh
Connecting to localhost:2181
[zk: localhost:2181(CONNECTED) 1] ls /hadoop-ha
[familyha]
3、启动journalnode进程
在new-cdh5、new-cdh6、new-cdh7 上分别启动并查看
[hadoop@new-cdh5 ~]$ hadoop-daemon.sh start journalnode
starting journalnode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-journalnode-new-cdh5.out
[hadoop@new-cdh5 ~]$ jps
3697 Jps
3653 JournalNode
4、格式化new-cdh1 上的 namenode
[hadoop@new-cdh1 ~]$ hdfs namenode -format
16/06/22 18:10:12 INFO namenode.NameNode: STARTUP_MSG:
/************************************************************
STARTUP_MSG: Starting NameNode
STARTUP_MSG: host = new-cdh1/192.168.36.1
STARTUP_MSG: args = [-format]
STARTUP_MSG: version = 2.6.0-cdh5.7.0
…
…
…
16/06/22 18:10:18 INFO namenode.FSImage: Allocated new BlockPoolId: BP-996370904-192.168.36.1-1466590218912
16/06/22 18:10:19 INFO common.Storage: Storage directory /hadoop/data/dfs/name has been successfully formatted.
16/06/22 18:10:19 INFO namenode.NNStorageRetentionManager: Going to retain 1 images with txid >= 0
16/06/22 18:10:19 INFO util.ExitUtil: Exiting with status 0
16/06/22 18:10:19 INFO namenode.NameNode: SHUTDOWN_MSG:
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at new-cdh1/192.168.36.1
************************************************************/
5、启动并查看new-cdh1上的namenode
[hadoop@new-cdh1 ~]$ hadoop-daemon.sh start namenode
starting namenode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-namenode-new-cdh1.out
[hadoop@new-cdh1 ~]$ jps
5486 NameNode
5577 Jps
6、将刚才格式化的new-cdh1 上的 namenode信息同步到备用new-cdh2 的namenode
[hadoop@new-cdh2 ~]$ hdfs namenode -bootstrapStandby
16/06/22 18:17:56 INFO namenode.NameNode: STARTUP_MSG:
/************************************************************
STARTUP_MSG: Starting NameNode
STARTUP_MSG: host = new-cdh2/192.168.36.2
STARTUP_MSG: args = [-bootstrapStandby]
STARTUP_MSG: version = 2.6.0-cdh5.7.0
STARTUP_MSG: classpath =
…
…
About to bootstrap Standby ID family2 from:
Nameservice ID: familyha
Other Namenode ID: family1
Other NN’s HTTP address: http://new-cdh1:50070
Other NN’s IPC address: new-cdh1/192.168.36.1:53333
Namespace ID: 1800644275
Block pool ID: BP-996370904-192.168.36.1-1466590218912
Cluster ID: CID-753f5b34-21e6-4305-9672-50607ce8d630
Layout version: -60
isUpgradeFinalized: true
16/06/22 18:17:58 INFO common.Storage: Storage directory /hadoop/data/dfs/name has been successfully formatted.
16/06/22 18:17:59 INFO namenode.TransferFsImage: Opening connection to http://new-cdh1:50070/imagetransfer?getimage=1&txid=0&storageInfo=-60:1800644275:0:CID-753f5b34-21e6-4305-9672-50607ce8d630&bootstrapstandby=true
16/06/22 18:17:59 INFO namenode.TransferFsImage: Image Transfer timeout configured to 60000 milliseconds
16/06/22 18:17:59 INFO namenode.TransferFsImage: Transfer took 0.05s at 0.00 KB/s
16/06/22 18:17:59 INFO namenode.TransferFsImage: Downloaded file fsimage.ckpt_0000000000000000000 size 353 bytes.
16/06/22 18:17:59 INFO util.ExitUtil: Exiting with status 0
16/06/22 18:17:59 INFO namenode.NameNode: SHUTDOWN_MSG:
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at new-cdh2/192.168.36.2
************************************************************/
7、启动并查看new-cdh2上的namenode
[hadoop@new-cdh2 ~]$ hadoop-daemon.sh start namenode
starting namenode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-namenode-new-cdh2.out
[hadoop@new-cdh2 ~]$ jps
4178 Jps
4087 NameNode
8、启动并查看所有datanode
[hadoop@new-cdh2 ~]$ hadoop-daemons.sh start datanode
new-cdh5: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh5.out
new-cdh6: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh6.out
new-cdh12: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh12.out
new-cdh7: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh7.out
new-cdh13: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh13.out
new-cdh11: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh11.out
new-cdh9: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh9.out
new-cdh10: starting datanode, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-datanode-new-cdh10.out
[hadoop@new-cdh5 ~]$ jps
3766 DataNode
3865 Jps
3653 JournalNode
9、在new-cdh3上启动并查看yarn
[hadoop@new-cdh3 ~]$ start-yarn.sh
starting yarn daemons
starting resourcemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-resourcemanager-new-cdh3.out
new-cdh13: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh13.out
new-cdh6: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh6.out
new-cdh7: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh7.out
new-cdh12: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh12.out
new-cdh5: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh5.out
new-cdh10: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh10.out
new-cdh11: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh11.out
new-cdh9: starting nodemanager, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/yarn-hadoop-nodemanager-new-cdh9.out
[hadoop@new-cdh3 ~]$ jps
4016 ResourceManager
4295 Jps
9、在new-cdh1、new-cdh2上分别启动并查看zkfc
[hadoop@new-cdh2 ~]$ hadoop-daemon.sh start zkfc
starting zkfc, logging to /hadoop/soft/hadoop-2.6.0-cdh5.7.0/logs/hadoop-hadoop-zkfc-new-cdh2.out
[hadoop@new-cdh2 ~]$ jps
4087 NameNode
4407 DFSZKFailoverController
4459 Jps
10、在网页查看安装效果 
以后启动就可以在 hdfs 和 yarn 的主节点上直接运行 start-dfs.sh或start-yarn.sh来启动
