跟我一起hadoop（1）-hadoop2.6安装与使用

伪分布式

hadoop的三种安装方式：

• ​​Local (Standalone) Mode​​
• ​​Pseudo-Distributed Mode​​
• ​​Fully-Distributed Mode​​

安装之前需要

$ sudo apt-get install ssh

     $ sudo apt-get install rsync

详见：​​http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-common/SingleCluster.html​​

伪分布式配置

Configuration

修改下边:

etc/hadoop/core-site.xml:

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

etc/hadoop/hdfs-site.xml:

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
</configuration>

配置ssh

$ ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa
  $ cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys

如果想运行在yarn上

需要执行下边的步骤：

2. Configure parameters as follows:

etc/hadoop/mapred-site.xml:

<configuration>
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
</configuration>

etc/hadoop/yarn-site.xml:

<configuration>
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
</configuration>

4. Start ResourceManager daemon and NodeManager daemon:

$ sbin/start-yarn.sh

5. Browse the web interface for the ResourceManager; by default it is available at:

• ResourceManager - http://localhost:8088/

6. Run a MapReduce job.
8. When you're done, stop the daemons with:

$ sbin/stop-yarn.sh

输入：

​​http://localhost:8088/​​

可以看到

​​​

启动yarn后

2. Format the filesystem:

$ bin/hdfs namenode -format

4. Start NameNode daemon and DataNode daemon:

$ sbin/start-dfs.sh

The hadoop daemon log output is written to the $HADOOP_LOG_DIR directory (defaults to $HADOOP_HOME/logs).

5. Browse the web interface for the NameNode; by default it is available at:

• NameNode -​​http://localhost:50070/​​

输入后得到：

​​​

然后执行测试

2. Make the HDFS directories required to execute MapReduce jobs:

$ bin/hdfs dfs -mkdir /user
  $ bin/hdfs dfs -mkdir /user/<username>

4. Copy the input files into the distributed filesystem:

$ bin/hdfs dfs -put etc/hadoop input

6. Run some of the examples provided:

$ bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.0.jar grep input output 'dfs[a-z.]+'

8. Examine the output files:

Copy the output files from the distributed filesystem to the local filesystem and examine them:

$ bin/hdfs dfs -get output output
  $ cat output/*

or

View the output files on the distributed filesystem:

$ bin/hdfs dfs -cat output/*

看运行的情况：

​​​

查看结果

​​​

测试执行成功，可以编写本地代码了。

eclipse hadoop2.6插件使用

下载源码：

git clone https://github.com/winghc/hadoop2x-eclipse-plugin.git

下载过程：

​​​

编译插件：

cd src/contrib/eclipse-plugin
ant jar -Dversion=2.6.0 -Declipse.home=/usr/local/eclipse -Dhadoop.home=/usr/local/hadoop-2.6.0  //路径根据自己的配置​​​

• 复制编译好的jar到eclipse插件目录，重启eclipse

• 配置 hadoop 安装目录

遇到异常

Exception in thread "main" org.apache.hadoop.mapred.FileAlreadyExistsException: Output directory hdfs://localhost:9000/output already exists
    at org.apache.hadoop.mapred.FileOutputFormat.checkOutputSpecs(FileOutputFormat.java:132)
    at org.apache.hadoop.mapreduce.JobSubmitter.checkSpecs(JobSubmitter.java:564)
    at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:432)
    at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1296)
    at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1293)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628)
    at org.apache.hadoop.mapreduce.Job.submit(Job.java:1293)
    at org.apache.hadoop.mapred.JobClient$1.run(JobClient.java:562)
    at org.apache.hadoop.mapred.JobClient$1.run(JobClient.java:557)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:415)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628)
    at org.apache.hadoop.mapred.JobClient.submitJobInternal(JobClient.java:557)
    at org.apache.hadoop.mapred.JobClient.submitJob(JobClient.java:548)
    at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:833)
    at com.zongtui.WordCount.main(WordCount.java:83)

1、改变输出路径。

2、删除重新建。

运行完成后看结果：

​​​

作者：​​张锋​​

本文版权归作者，欢迎转载，但未经作者同意必须在文章页面给出原文连接，否则保留追究法律责任的权利。

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