hadoop如何查看wordcount代码（初学Hadoop之中文词频统计）

1、安装eclipse

准备

eclipse-dsl-luna-SR2-linux-gtk-x86_64.tar.gz

安装

1、解压文件。

hadoop如何查看wordcount代码（初学Hadoop之中文词频统计）(1)

hadoop如何查看wordcount代码（初学Hadoop之中文词频统计）(2)

2、创建图标。

ln -s /opt/eclipse/eclipse /usr/bin/eclipse #使符号链接目录

vim /usr/share/applications/eclipse.desktop #创建一个 Gnome 启动

添加如下代码：

[Desktop Entry] Encoding=UTF-8 Name=Eclipse 4.4.2 Comment=Eclipse Luna Exec=/usr/bin/eclipse Icon=/opt/eclipse/icon.xpm Categories=Application;Development;Java;IDE Version=1.0 Type=Application Terminal=0

hadoop如何查看wordcount代码（初学Hadoop之中文词频统计）(3)

完成以后则会出现下图中的图标。

hadoop如何查看wordcount代码（初学Hadoop之中文词频统计）(4)

至此，eclipse安装完成。

2、安装hadoop插件

1、下载插件http:///s/1ydUEy 。

2、将插件放到/opt/eclipse/plugins文件夹下。

hadoop如何查看wordcount代码（初学Hadoop之中文词频统计）(5)

3、在eclipse->Windows->preferences设置Hadoop路径。

hadoop如何查看wordcount代码（初学Hadoop之中文词频统计）(6)

至此，插件安装完成。

3、ChineseWordCount源码

package com.example.test; import java.io.IOException; import java.io.InputStream; import java.io.InputStreamReader; import java.io.Reader; import java.io.ByteArrayInputStream; import org.wltea.analyzer.core.IKSegmenter; import org.wltea.analyzer.core.Lexeme; 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.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.Reducer; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.GenericOptionsParser; public class ChineseWordCount { public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> { private final static IntWritable one = new IntWritable(1); private Text word = new Text; public void map(Object key, Text value, Context context) throws IOException, InterruptedException { byte bt = value.getBytes; InputStream ip = new ByteArrayInputStream(bt); Reader read = new InputStreamReader(ip); IKSegmenter iks = new IKSegmenter(read, true); Lexeme t; while ((t = iks.next) != null) { word.set(t.getLexemeText); context.write(word, one); } } } public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> { private IntWritable result = new IntWritable; public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException { int sum = 0; for (IntWritable val : values) { sum = val.get; } result.set(sum); context.write(key, result); } } public static void main(String[] args) throws Exception { Configuration conf = new Configuration; String otherArgs = new GenericOptionsParser(conf, args) .getRemainingArgs; if (otherArgs.length != 2) { System.err.println("Usage: wordcount <in> <out>"); System.exit(2); } Job job = new Job(conf, "word count"); job.setJarByClass(ChineseWordCount.class); job.setMapperClass(TokenizerMapper.class); job.setCombinerClass(IntSumReducer.class); job.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.exit(job.waitForCompletion(true) ? 0 : 1); } }