(i), install eclipse
1, download eclipse, click here
2, upload the file to Centos7, you can use WINSCP
3. Unzip and install eclipse
[Email protected] opt]# tar zxvf '/home/s/eclipse-jee-neon-1a-linux-gtk-x86_64.tar.gz '-c/opt---------------> Build file: [[email protected] opt]# mkdir/usr/bin/eclipse------------------Add link, shortcut: [[email protected] opt]# ln-s/opt /eclipse/eclipse/usr/bin/eclipse-----------"Click Eclipse to launch the
(ii) Creation of Hadoop projects
1, download Hadoop plugin 2.7.3 link: http://pan.baidu.com/s/1i5yRyuh Password: ms91
2, unzip the jar package plug-in, put it into Eclipse plugins, and restart Eclipse
2. Load the DFS library in eclipse, click on the Windows toolbar--------> select Show view
2. Open Resource Click Window----->perspective----------->open Perspective Select resource:
3. Configure the connection port, click Mapresource Location under Eclipse, click Add: Where port number is filled in by Hdfs-site.xml and Core-site.xml.
4. Upload the input file: use HDFs Dfs-put/home/file1/data to see the following in eclipse: (to ensure that each machine's firewall is closed, the exception can be temporarily off, run the following example is all gone, hehe)
(iii) test the WordCount procedure
1, New project: Click New------------Project----------->map Reduce,
2, configure the local Hadoop file for the project, and write the path to the local Hadoop at the circle:
3, create a new Mappert class, write the following code:
1 package word; 2 3 Import java.io.IOException; 4 Import Java.util.StringTokenizer; 5 6 Import Org.apache.hadoop.conf.Configuration; 7 Import Org.apache.hadoop.fs.Path; 8 Import org.apache.hadoop.io.IntWritable; 9 Import org.apache.hadoop.io.text;10 Import org.apache.hadoop.mapreduce.job;11 Import ORG.APACHE.HADOOP.MAPREDUCE.MAPPER;12 Import org.apache.hadoop.mapreduce.reducer;13 Import ORG.APACHE.HADOOP.MAPREDUCE.LIB.INPUT.FILEINPUTFORMAT;14 Import ORG.APACHE.HADOOP.MAPREDUCE.LIB.OUTPUT.FILEOUTPUTFORMAT;15 Import org.apache.hadoop.util.genericoptionsparser;16 public class Mapper {Tokenizermapper extends Mapper<object, text, text, intwritable> {The private final static intwritable one = new intwritable (1), and the. Text Word = new text (); public void Map (O Bject key, Text value, Context context26) throws IOException, interruptedexception {stringtokenizer ITR = new Stringto Kenizer (Value.tostring ()); while (Itr.hasmoretokens ()) {WORD.set (Itr.nexttoken ()); Context.write (Word, one),}32}33}34 public static class Intsumreducer extends reducer& Lt text,intwritable,text,intwritable> {PNS Private intwritable result = new intwritable (); , iterable<intwritable> values, context41) throws IOException, interruptedexception {int sum = 0;43 F or (intwritable val:values) {Sum of $ + = Val.get ();}46 result.set (sum); Context.write (key, result);}49}50 Wuyi Publ IC static void Main (string[] args) throws Exception {string[configuration conf = new Configuration (); = new Genericoptionsparser (conf, args). Getremainingargs (); if (otherargs.length! = 2) {System.err.println ( Otherargs.length), System.err.println ("Usage:wordcount <in> <out>"), System.exit (2),}60 job Job = New Job (conf, "word count"); Job.setjarbyclass (Mapper.class); Job.setmapperclass (Tokenizermapper.class); 63 Job.setcombinerclass (Intsumreducer.class);B.setreducerclass (Intsumreducer.class), Job.setoutputkeyclass (Text.class), Job.setoutputvalueclass ( Intwritable.class); Fileinputformat.addinputpath (Job, New Path (otherargs[0)); Fileoutputformat.setoutputpath ( Job, New Path (Otherargs[1]); System.out.print ("OK"); System.exit (Job.waitforcompletion (true)? 0:1); 71}72}
2. Click Run as------------>runconfigurations----------> Set input and output file parameters
3, click Run to view the results
The contents of the file:
CentOS under install Eclipse test Hadoop