安装hadoop集群(Multi Cluster)
配置环境本文档安装hadoop集群环境，一个master作为namenode节点，一个slave作为datanode节点：
(1) master：
os: CentOS> ip: 172.16.101.58
user：root
hadoop-2.9.0.tar.gz
(2) slave：
os: CentOS> ip: 172.16.101.59
user：root
hadoop-2.9.0.tar.gz
前提条件
(1) master和slave都安装好java环境，并配置好环境变量；
(2)master节点解压好hadoop-2.9.0.tar.gz，并配置好环境变量；
(3)本篇文档使用的是root用户安装，所以需要master上的root用户可以ssh无密码使用root用户登录slave节点；
配置集群文件
在 master节点上执行（本文档先在master节点上配置文件，然后通过scp拷贝到其他slave节点）
（1）slaves文件：将作为 DataNode 的主机名或者ip写入该文件，每行一个，默认为 localhost，所以在伪分布式配置时，节点既作为 NameNode 也作为 DataNode。
# cat slaves
172.16.101.59
（2）文件core-site.xml
#cat /usr/local/hadoop-2.9.0/etc/hadoop/core-site.xml
fs.defaultFS
hdfs://172.16.101.58:9000
hadoop.tmp.dir
/usr/local/hadoop-2.9.0/tmp
Abase for other temporary directories.
（3）文件hdfs-site.xml
# cat /usr/local/hadoop-2.9.0/etc/hadoop/hdfs-site.xml
dfs.namenode.secondary.http-address
172.16.101.58:50090
dfs.replication
1
dfs.namenode.name.dir
file:/usr/local/hadoop-2.9.0/tmp/dfs/name
dfs.datanode.data.dir
file:/usr/local/hadoop-2.9.0/tmp/dfs/data
（4）文件mapred-site.xml
# cat /usr/local/hadoop-2.9.0/etc/hadoop/mapred-site.xml
mapreduce.framework.name
yarn
mapreduce.jobhistory.address
172.16.101.58:10020
mapreduce.jobhistory.webapp.address
172.16.101.58:19888
（5）文件yarn-site.xml
# cat /usr/local/hadoop-2.9.0/etc/yarn-site.xml
yarn.resourcemanager.hostname
172.16.101.58
yarn.nodemanager.aux-services
mapreduce_shuffle
配置好后，将 Master上的 /usr/local/hadoop-2.9.0文件复制到各个节点上。因为之前有跑过伪分布式模式，建议在切换到集群模式前先删除之前的临时文件。
# rm -rf ./hadoop-2.9.0/tmp
# rm -rf ./hadoop-2.9.0/logs
# tar -zcfhadoop-2.9.0.master.tar.gz /usr/local/hadoop-2.9.0
# scp hadoop-2.9.0.master.tar.gz sht-sgmhadoopdn-02:/usr/local/
在 Slave节点上执行
# tar -zxf hadoop-2.9.0.master.tar.gz
启动hadoop集群
在 master节点上执行：
#第一次启动需要格式化HDFS,以后再启动不需要
# hdfs namenode -format
# start-dfs.sh
# start-yarn.sh
# mr-jobhistory-daemon.sh start historyserver
# jps
20289 JobHistoryServer
19730 ResourceManager
18934 NameNode
19163 SecondaryNameNode
20366 Jps
在 Slave节点上执行：
# jps
32147 DataNode
535 Jps
32559 NodeManager
在 master节点上执行：
# hdfs dfsadmin -report
Configured Capacity: 75831140352 (70.62 GB)
Present Capacity: 21246287872 (19.79 GB)
DFS Remaining: 21246263296 (19.79 GB)
DFS Used: 24576 (24 KB)
DFS Used%: 0.00%
Under replicated blocks: 0
Blocks with corrupt replicas: 0
Missing blocks: 0
Missing blocks (with replication factor 1): 0
Pending deletion blocks: 0
-------------------------------------------------
Live datanodes (1): #存活的slave数量
Name: 172.16.101.59:50010 (sht-sgmhadoopdn-02)
Hostname: sht-sgmhadoopdn-02
Decommission Status : Normal
Configured Capacity: 75831140352 (70.62 GB)
DFS Used: 24576 (24 KB)
Non DFS Used: 50732867584 (47.25 GB)
DFS Remaining: 21246263296 (19.79 GB)
DFS Used%: 0.00%
DFS Remaining%: 28.02%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Wed Dec 27 11:08:46 CST 2017
Last Block Report: Wed Dec 27 11:02:01 CST 2017
Console管理平台
NameNodehttp://172.16.101.58:50070
执行分布式实例MapReduce Job
# hdfs dfs -mkdir -p /user/root/input
# hdfs dfs -put /usr/local/hadoop-2.9.0/etc/hadoop/*.xmlinput
# hadoop jar /usr/local/hadoop-2.9.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.9.0.jar grep input output 'dfs+'
17/12/27 11:25:33 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java> 17/12/27 11:25:34 INFO client.RMProxy: Connecting to ResourceManager at /172.16.101.58:8032
17/12/27 11:25:36 INFO input.FileInputFormat: Total input files to process : 9
17/12/27 11:25:36 INFO mapreduce.JobSubmitter: number of splits:9
17/12/27 11:25:37 INFO Configuration.deprecation: yarn.resourcemanager.system-metrics-publisher.enabled is deprecated. Instead, use yarn.system-metrics-publisher.enabled
17/12/27 11:25:37 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1514343869308_0001
17/12/27 11:25:38 INFO impl.YarnClientImpl: Submitted application application_1514343869308_0001
17/12/27 11:25:38 INFO mapreduce.Job: The url to track the job:http://sht-sgmhadoopdn-01:8088/proxy/application_1514343869308_0001/
17/12/27 11:25:38 INFO mapreduce.Job: Running job: job_1514343869308_0001
17/12/27 11:25:51 INFO mapreduce.Job: Job job_1514343869308_0001 running in uber mode : false
17/12/27 11:25:51 INFO mapreduce.Job:map 0% reduce 0%
17/12/27 11:26:14 INFO mapreduce.Job:map 11% reduce 0%
17/12/27 11:26:15 INFO mapreduce.Job:map 67% reduce 0%
17/12/27 11:26:29 INFO mapreduce.Job:map 100% reduce 0%
17/12/27 11:26:32 INFO mapreduce.Job:map 100% reduce 100%
17/12/27 11:26:34 INFO mapreduce.Job: Job job_1514343869308_0001 completed successfully
17/12/27 11:26:34 INFO mapreduce.Job: Counters: 50
......
# hdfs dfs -cat output/*
17/12/27 11:30:08 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java> 1 dfsadmin
1 dfs.replication
1 dfs.namenode.secondary.http
1 dfs.namenode.name.dir
1 dfs.datanode.data.dir
也可以通过浏览器访问console，查看详细的分析信息：
ResourceManager -http://172.16.101.58:8088
停止hadoop集群
在 master节点上执行：
#stop-yarn.sh
#stop-dfs.sh
#mr-jobhistory-daemon.sh stop historyserver
参考链接：
http://www.powerxing.com/install-hadoop-cluster/
http://hadoop.apache.org/docs/r2.9.0/hadoop-project-dist/hadoop-common/ClusterSetup.html
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