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%

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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