hadoop2.6.0版本集群环境搭建

一、环境说明

1、机器：一台物理机 和一台虚拟机

2、linux版本：[spark@S1PA11 ~]$ cat /etc/issue
Red Hat Enterprise Linux Server release 5.4 (Tikanga)

3、JDK: [spark@S1PA11 ~]$ java -version
java version "1.6.0_27"
Java(TM) SE Runtime Environment (build 1.6.0_27-b07)
Java HotSpot(TM) 64-Bit Server VM (build 20.2-b06, mixed mode)

4、集群节点：两个 S1PA11（Master）,S1PA222(Slave)

二、准备工作

1、安装Java jdk前一篇文章撰写了：http://blog.csdn.net/stark_summer/article/details/42391531

2、ssh免密码验证 ：http://blog.csdn.net/stark_summer/article/details/42393053

3、下载Hadoop版本：http://mirror.bit.edu.cn/apache/hadoop/common/

三、安装Hadoop

这是下载后的hadoop-2.6.0.tar.gz压缩包，   

1、解压 tar -xzvf hadoop-2.6.0.tar.gz 

2、move到指定目录下：[spark@S1PA11 software]$ mv hadoop-2.6.0 ~/opt/ 

3、进入hadoop目前  [spark@S1PA11 opt]$ cd hadoop-2.6.0/
[spark@S1PA11 hadoop-2.6.0]$ ls
bin  dfs  etc  include  input  lib  libexec  LICENSE.txt  logs  NOTICE.txt  README.txt  sbin  share  tmp

 配置之前，先在本地文件系统创建以下文件夹：~/hadoop/tmp、~/dfs/data、~/dfs/name。 主要涉及的配置文件有7个：都在/hadoop/etc/hadoop文件夹下，可以用gedit命令对其进行编辑。

~/hadoop/etc/hadoop/hadoop-env.sh
~/hadoop/etc/hadoop/yarn-env.sh
~/hadoop/etc/hadoop/slaves
~/hadoop/etc/hadoop/core-site.xml
~/hadoop/etc/hadoop/hdfs-site.xml
~/hadoop/etc/hadoop/mapred-site.xml
~/hadoop/etc/hadoop/yarn-site.xml

4、进去hadoop配置文件目录

[spark@S1PA11 hadoop-2.6.0]$ cd etc/hadoop/
[spark@S1PA11 hadoop]$ ls
capacity-scheduler.xml  hadoop-env.sh               httpfs-env.sh            kms-env.sh            mapred-env.sh               ssl-client.xml.example
configuration.xsl       hadoop-metrics2.properties  httpfs-log4j.properties  kms-log4j.properties  mapred-queues.xml.template  ssl-server.xml.example
container-executor.cfg  hadoop-metrics.properties   httpfs-signature.secret  kms-site.xml          mapred-site.xml             yarn-env.cmd
core-site.xml           hadoop-policy.xml           httpfs-site.xml          log4j.properties      mapred-site.xml.template    yarn-env.sh
hadoop-env.cmd          hdfs-site.xml               kms-acls.xml             mapred-env.cmd        slaves                      yarn-site.xml

4.1、配置 hadoop-env.sh文件-->修改JAVA_HOME

# The java implementation to use.
export JAVA_HOME=/home/spark/opt/java/jdk1.6.0_37

4.2、配置 yarn-env.sh 文件-->>修改JAVA_HOME

# some Java parameters

 export JAVA_HOME=/home/spark/opt/java/jdk1.6.0_37

4.3、配置slaves文件-->>增加slave节点 

 S1PA222

4.4、配置 core-site.xml文件-->>增加hadoop核心配置（hdfs文件端口是9000、file:/home/spark/opt/hadoop-2.6.0/tmp、）

<configuration>
 <property>
  <name>fs.defaultFS</name>
  <value>hdfs://S1PA11:9000</value>
 </property>

 <property>
  <name>io.file.buffer.size</name>
  <value>131072</value>
 </property>
 <property>
  <name>hadoop.tmp.dir</name>
  <value>file:/home/spark/opt/hadoop-2.6.0/tmp</value>
  <description>Abasefor other temporary directories.</description>
 </property>
 <property>
  <name>hadoop.proxyuser.spark.hosts</name>
  <value>*</value>
 </property>
<property>
  <name>hadoop.proxyuser.spark.groups</name>
  <value>*</value>
 </property>
</configuration>

4.5、配置  hdfs-site.xml 文件-->>增加hdfs配置信息（namenode、datanode端口和目录位置）

<configuration>
 <property>
  <name>dfs.namenode.secondary.http-address</name>
  <value>S1PA11:9001</value>
 </property>

  <property>
   <name>dfs.namenode.name.dir</name>
   <value>file:/home/spark/opt/hadoop-2.6.0/dfs/name</value>
 </property>

 <property>
  <name>dfs.datanode.data.dir</name>
  <value>file:/home/spark/opt/hadoop-2.6.0/dfs/data</value>
  </property>

 <property>
  <name>dfs.replication</name>
  <value>3</value>
 </property>

 <property>
  <name>dfs.webhdfs.enabled</name>
  <value>true</value>
 </property>

</configuration>

4.6、配置  mapred-site.xml 文件-->>增加mapreduce配置（使用yarn框架、jobhistory使用地址以及web地址）

<configuration>
  <property>
   <name>mapreduce.framework.name</name>
   <value>yarn</value>
 </property>
 <property>
  <name>mapreduce.jobhistory.address</name>
  <value>S1PA11:10020</value>
 </property>
 <property>
  <name>mapreduce.jobhistory.webapp.address</name>
  <value>S1PA11:19888</value>
 </property>
</configuration>

4.7、配置   yarn-site.xml  文件-->>增加yarn功能

<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.resourcemanager.address</name>
   <value>S1PA11:8032</value>
  </property>
  <property>
   <name>yarn.resourcemanager.scheduler.address</name>
   <value>S1PA11:8030</value>
  </property>
  <property>
   <name>yarn.resourcemanager.resource-tracker.address</name>
   <value>S1PA11:8035</value>
  </property>
  <property>
   <name>yarn.resourcemanager.admin.address</name>
   <value>S1PA11:8033</value>
  </property>
  <property>
   <name>yarn.resourcemanager.webapp.address</name>
   <value>S1PA11:8088</value>
  </property>

</configuration>

5、将配置好的hadoop文件copy到另一台slave机器上

[spark@S1PA11 opt]$ scp -r hadoop-2.6.0/ spark@10.126.34.43:~/opt/

四、验证

1、格式化namenode:

[spark@S1PA11 opt]$ cd hadoop-2.6.0/
[spark@S1PA11 hadoop-2.6.0]$ ls
bin  dfs  etc  include  input  lib  libexec  LICENSE.txt  logs  NOTICE.txt  README.txt  sbin  share  tmp
[spark@S1PA11 hadoop-2.6.0]$ ./bin/hdfs namenode -format

[spark@S1PA222 .ssh]$ cd ~/opt/hadoop-2.6.0
[spark@S1PA222 hadoop-2.6.0]$ ./bin/hdfs  namenode -format

2、启动hdfs:

[spark@S1PA11 hadoop-2.6.0]$ ./sbin/start-dfs.sh 
15/01/05 16:41:04 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Starting namenodes on [S1PA11]
S1PA11: starting namenode, logging to /home/spark/opt/hadoop-2.6.0/logs/hadoop-spark-namenode-S1PA11.out
S1PA222: starting datanode, logging to /home/spark/opt/hadoop-2.6.0/logs/hadoop-spark-datanode-S1PA222.out
Starting secondary namenodes [S1PA11]
S1PA11: starting secondarynamenode, logging to /home/spark/opt/hadoop-2.6.0/logs/hadoop-spark-secondarynamenode-S1PA11.out
15/01/05 16:41:21 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[spark@S1PA11 hadoop-2.6.0]$ jps
22230 Master
30889 Jps
22478 Worker
30498 NameNode
30733 SecondaryNameNode
19781 ResourceManager

3、停止hdfs:

[spark@S1PA11 hadoop-2.6.0]$./sbin/stop-dfs.sh 
15/01/05 16:40:28 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Stopping namenodes on [S1PA11]
S1PA11: stopping namenode
S1PA222: stopping datanode
Stopping secondary namenodes [S1PA11]
S1PA11: stopping secondarynamenode
15/01/05 16:40:48 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[spark@S1PA11 hadoop-2.6.0]$ jps
30336 Jps
22230 Master
22478 Worker
19781 ResourceManager

4、启动yarn:

[spark@S1PA11 hadoop-2.6.0]$./sbin/start-yarn.sh 
starting yarn daemons
starting resourcemanager, logging to /home/spark/opt/hadoop-2.6.0/logs/yarn-spark-resourcemanager-S1PA11.out
S1PA222: starting nodemanager, logging to /home/spark/opt/hadoop-2.6.0/logs/yarn-spark-nodemanager-S1PA222.out
[spark@S1PA11 hadoop-2.6.0]$ jps
31233 ResourceManager
22230 Master
22478 Worker
30498 NameNode
30733 SecondaryNameNode
31503 Jps

5、停止yarn:

[spark@S1PA11 hadoop-2.6.0]$ ./sbin/stop-yarn.sh 
stopping yarn daemons
stopping resourcemanager
S1PA222: stopping nodemanager
no proxyserver to stop
[spark@S1PA11 hadoop-2.6.0]$ jps
31167 Jps
22230 Master
22478 Worker
30498 NameNode
30733 SecondaryNameNode

6、查看集群状态：

[spark@S1PA11 hadoop-2.6.0]$ ./bin/hdfs dfsadmin -report
15/01/05 16:44:50 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Configured Capacity: 52101857280 (48.52 GB)
Present Capacity: 45749510144 (42.61 GB)
DFS Remaining: 45748686848 (42.61 GB)
DFS Used: 823296 (804 KB)
DFS Used%: 0.00%
Under replicated blocks: 10
Blocks with corrupt replicas: 0
Missing blocks: 0


-------------------------------------------------
Live datanodes (1):


Name: 10.126.45.56:50010 (S1PA222)
Hostname: S1PA209
Decommission Status : Normal
Configured Capacity: 52101857280 (48.52 GB)
DFS Used: 823296 (804 KB)
Non DFS Used: 6352347136 (5.92 GB)
DFS Remaining: 45748686848 (42.61 GB)
DFS Used%: 0.00%
DFS Remaining%: 87.81%
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: Mon Jan 05 16:44:50 CST 2015

7、查看hdfs：http://10.58.44.47:50070/

8、查看RM：http://10.58.44.47:8088/

9、运行wordcount程序

9.1、创建 input目录：[spark@S1PA11 hadoop-2.6.0]$ mkdir input

9.2、在input创建f1、f2并写内容

[spark@S1PA11 hadoop-2.6.0]$ cat input/f1 
Hello world  bye jj
[spark@S1PA11 hadoop-2.6.0]$ cat input/f2
Hello Hadoop  bye Hadoop

9.3、在hdfs创建/tmp/input目录

[spark@S1PA11 hadoop-2.6.0]$ ./bin/hadoop fs  -mkdir /tmp
15/01/05 16:53:57 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

[spark@S1PA11 hadoop-2.6.0]$ ./bin/hadoop fs  -mkdir /tmp/input
15/01/05 16:54:16 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

9.4、将f1、f2文件copy到hdfs /tmp/input目录

[spark@S1PA11 hadoop-2.6.0]$ ./bin/hadoop fs  -put input/ /tmp
15/01/05 16:56:01 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

9.5、查看hdfs上是否有f1、f2文件

[spark@S1PA11 hadoop-2.6.0]$ ./bin/hadoop fs -ls /tmp/input/
15/01/05 16:57:42 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Found 2 items
-rw-r--r--   3 spark supergroup         20 2015-01-04 19:09 /tmp/input/f1
-rw-r--r--   3 spark supergroup         25 2015-01-04 19:09 /tmp/input/f2

9.6、执行wordcount程序

[spark@S1PA11 hadoop-2.6.0]$ ./bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar wordcount /tmp/input /output
15/01/05 17:00:09 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/01/05 17:00:09 INFO client.RMProxy: Connecting to ResourceManager at S1PA11/10.58.44.47:8032
15/01/05 17:00:11 INFO input.FileInputFormat: Total input paths to process : 2
15/01/05 17:00:11 INFO mapreduce.JobSubmitter: number of splits:2
15/01/05 17:00:11 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1420447392452_0001
15/01/05 17:00:12 INFO impl.YarnClientImpl: Submitted application application_1420447392452_0001
15/01/05 17:00:12 INFO mapreduce.Job: The url to track the job: http://S1PA11:8088/proxy/application_1420447392452_0001/
15/01/05 17:00:12 INFO mapreduce.Job: Running job: job_1420447392452_0001

9.7、查看执行结果

[spark@S1PA11 hadoop-2.6.0]$ ./bin/hadoop fs -cat /output/part-r-0000
15/01/05 17:06:10 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

 

 

http://blog.csdn.net/stark_summer/article/details/42424279