写在前面
本系列文章索引以及一些默认好的条件在传送门
step1 eclipse访问hadoop
首先需要明确eclipse安装目录，然后将hadoop-eclipse-plugin_版本号.jar插件放在安装目录的dropins下
关于插件，可以通过博主上传到csdn的免费资源获取，链接
具体版本可以自己选择：
step2 重启并配置eclipse
在eclipse界面中依次选择：Window→show view→other→MapReduce Tools/Map/Reduce Locations
然后在界面上会显示一个大象符号，如下图：
点击大象符号，然后就会配置一个DFS Location
配置参数为：
配置好后点击finish
然后会出现：
step3 新建Map/Reduce项目
在Eclipse中依次选择File→New→Other…→Map/Reduce Project→Next，
输入项目名TestWordCount，浏览并选择Hadoop路径/usr/local/hadoop，单击“Finish”按钮，则新建项目TestWordCount成功
新建包并在包下创建相应的类，具体项目结构如下：
step4 复制粘贴代码
package wordCount; 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.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; public class WordCount { public static class WordCountMapper extends Mapper<Object, Text, Text, IntWritable> { /** * 定义final 静态变量one,用来标示键值对<String,One> * 然后定义Text类型的变量来存储字符串 */ 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 { StringTokenizer itr = new StringTokenizer(value.toString()); while (itr.hasMoreTokens()) {// word.set(itr.nextToken()); /** * 写入键值对 */ context.write(word, one); } } } public static class WordCountReducer 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(); if (args.length != 2) { System.err.println("Usage: <in> <out>"); System.exit(2); } Job job = Job.getInstance(conf, "word count"); job.setJarByClass(WordCount.class); job.setMapperClass(WordCountMapper.class); job.setCombinerClass(WordCountReducer.class); job.setReducerClass(WordCountReducer.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(IntWritable.class); FileInputFormat.addInputPath(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); System.exit(job.waitForCompletion(true) ? 0 : 1); } }
step5 配置运行参数
启动hadoop集群后在终端写入：
hadoop fs -mkdir /tmp hadoop fs -chmod -R 777 /tmp
Run→Run Configurations选项，以配置输入输出参数
大致为：
点击run直接跑
然后在左侧的目录下会显示文件夹：
点进去看下part-r-00000文件就会发现，该文件存储结果：
其中输入为：
结果与预期一致，项目成功~
