Method line, but the code is 2.0 please modify
preparatory work
Install Eclipse and search for installation directly in Ubuntu Software Center.
On the left-hand taskbar, click Ubuntu Software Center.
Ubuntu Software Center
Search for Eclipse in the search bar in the upper-right corner, click Eclipse in the search results, and click Install.
Install Eclipse
This completes the installation of Eclipse. The default installation directory for Eclipse is:/usr/lib/eclipse. Installing Hadoop-eclipse-plugin
Download Hadoop2x-eclipse-plugin, will release in the Hadoop-eclipse-kepler-plugin-2.2.0.jar (although labeled 2.2.0, but under the 2.6.0 is not a problem, should be in the 2.x version Can be copied to the plugin folder in the Eclipse installation directory and run Eclipse-clean to restart Eclipse.
CD ~/download/unzip./hadoop2x-eclipse-plugin-master.zip cd/usr/lib/eclipse sudo cp ~/download/hadoop2x-eclipse-plugin-master/ Release/hadoop-eclipse-kepler-plugin-2.2.0.jar./plugins/./eclipse-clean
Configure Hadoop-eclipse-plugin
After you start Eclipse, you can see DFS Locations in Project Explorer on the left (if you see the Welcome interface, click the x close in the upper left corner to see it).
After installing the Hadoop-eclipse-plugin plug-in effect
The plugin requires further configuration.
First step: Select Preference under the Window menu.
Open preference
A form will pop up with the Hadoop map/reduce option on the left side of the form, click this option to select the installation directory for Hadoop (for example,/usr/local/hadoop,ubuntu is not a good choice for the directory, just enter the line).
Select the installation directory for Hadoop
The second step: switch map/reduce working directory, choose the Window menu under Open perspective and other, pop up a form, select the Map/reduce option to switch.
Switch map/reduce working directory
Step three: Establish a connection to the Hadoop cluster, click the Map/reduce Locations panel in the lower right corner of the Eclipse software, right-click in the panel and select New Hadoop location.
Establishing a connection to a Hadoop cluster
In the pop-up General Options panel for Master settings, set the configuration to be consistent with Hadoop, such as the Hadoop pseudo-distributed configuration I used, set Fs.defaultfs to hdfs://localhost:9000, then DFS maste The Post for R should also be changed to 9000.
Location Name is free to fill in, Map/reduce Master Host will fill in your native IP (localhost also line), Port default is 50020. The final settings are as follows:
Settings for Hadoop location
Then switch to the Advanced Parameters Options panel, which has a detailed configuration, remembering that it needs to be consistent with the configuration of Hadoop (configuration files in/usr/local/hadoop/etc/hadoop), as I configured the Hadoop.tmp.dir , you need to make changes.
Settings for Hadoop location
Finally click on Finish,map/reduce location to create it.
The configuration is complete. View the contents of a file in HDFs in Eclipse
Once configured, clicking on the MapReduce location in Project Explorer on the left allows you to view the contents of the file directly in HDFS (as shown in the WordCount output) without having to go through the cumbersome HDFS dfs-ls command. If you are unable to view it, try restarting Eclipse.
Use Eclipse to view file contents in HDFs Tips
After the content changes in HDFS, Eclipse does not synchronize refreshes, you need to right click on the MapReduce location in Project Explorer and select Refresh to see the changed files. Create a MapReduce project in Eclipse
Click the File menu and choose New Project ...:
Create Project
Select Map/reduce Project and click Next.
Create a MapReduce project
Fill out project name as WordCount, and click Finish to create the item.
Fill in the project name
At this point, Project Explorer on the left will be able to see the projects you have just created.
Project Creation Complete
Then right-click on the WordCount project you just created and choose New Class
New class
Two places to fill in: Fill in the Org.apache.hadoop.examples at the package and fill in the WordCount in Name.
Fill in the class information
Once you have created the Class, you will see the Wordcount.java file in src in Project. Copy the following WordCount code into the file.
Package org.apache.hadoop.examples; Import java.io.IOException; Import Java.util.StringTokenizer; Import org.apache.hadoop.conf.Configuration; Import Org.apache.hadoop.fs.Path; Import org.apache.hadoop.io.IntWritable; Import Org.apache.hadoop.io.Text; Import Org.apache