hadoop2.6.0版本集群环境搭建
问题导读
1.安装hadoop需要做哪些准备？
2.如何验证hadoop是否成功？
3.如何运行wordcout?
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一、环境说明
1、机器：一台物理机 和一台虚拟机
2、linux版本：$ cat /etc/issue
Red Hat Enterprise Linux Server release 5.4 (Tikanga)
3、JDK: $ 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
2、ssh免密码验证
3、下载Hadoop版本
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：$ mv hadoop-2.6.0 ~/opt/
3、进入hadoop目前$ cd hadoop-2.6.0/
$ ls
bindfsetcincludeinputliblibexecLICENSE.txtlogsNOTICE.txtREADME.txtsbinsharetmp
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
$ cd etc/hadoop/
$ ls
capacity-scheduler.xmlhadoop-env.sh httpfs-env.sh kms-env.sh mapred-env.sh ssl-client.xml.example
configuration.xsl hadoop-metrics2.propertieshttpfs-log4j.propertieskms-log4j.propertiesmapred-queues.xml.templatessl-server.xml.example
container-executor.cfghadoop-metrics.properties httpfs-signature.secretkms-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
$ scp -r hadoop-2.6.0/ spark@10.126.34.43:~/opt/
四、验证
1、格式化namenode:
$ cd hadoop-2.6.0/
$ ls
bindfsetcincludeinputliblibexecLICENSE.txtlogsNOTICE.txtREADME.txtsbinsharetmp
$ ./bin/hdfs namenode -format
$ cd ~/opt/hadoop-2.6.0
$ ./bin/hdfsnamenode -format
2、启动hdfs:
$ ./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: 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: 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
$ jps
22230 Master
30889 Jps
22478 Worker
30498 NameNode
30733 SecondaryNameNode
19781 ResourceManager
3、停止hdfs:
$./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: stopping namenode
S1PA222: stopping datanode
Stopping secondary namenodes
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
$ jps
30336 Jps
22230 Master
22478 Worker
19781 ResourceManager
4、启动yarn:
$./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
$ jps
31233 ResourceManager
22230 Master
22478 Worker
30498 NameNode
30733 SecondaryNameNode
31503 Jps
5、停止yarn:
$ ./sbin/stop-yarn.sh
stopping yarn daemons
stopping resourcemanager
S1PA222: stopping nodemanager
no proxyserver to stop
$ jps
31167 Jps
22230 Master
22478 Worker
30498 NameNode
30733 SecondaryNameNode
6、查看集群状态：
$ ./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：$ mkdir input
9.2、在input创建f1、f2并写内容
$ cat input/f1
Hello worldbye jj
$ cat input/f2
Hello Hadoopbye Hadoop
9.3、在hdfs创建/tmp/input目录
$ ./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
$ ./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
$ ./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
$ ./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
$ ./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
$ ./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
好资料多谢分享！
很好的配置文件 很好的配置文件 谢谢分享，赞 多谢分享 我的hadoop 启动后 9000端口访问不了 提示 It looks like you are making an HTTP request to a Hadoop IPC port. This is not the correct port for the web interface on this daemon. 但是 8088 和 50070 都可以打开 请问楼主 遇到过这种问题吗？ About_haoran 发表于 2016-6-1 13:51
我的hadoop 启动后 9000端口访问不了 提示 It looks like you are making an HTTP request to a Hadoop IPC ...
这个提示表示访问的端口不对，core-site.xml中的hdfs端口不是web访问端口，是namerode RPC交互访问端口，web访问端口是在hdfs-site.xml中定义的，在configuration中添加dfs.http.address字段，然后定义web访问的端口和地址，如果不加这个定义默认是50070端口访问。
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