初学Hadoop之WordCount分词统计
1、WordCount源码
将源码文件WordCount.java放到Hadoop2.6.0文件夹中。
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 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 { StringTokenizer itr = new StringTokenizer(value.toString()); while (itr.hasMoreTokens()) { word.set(itr.nextToken()); 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(); Job job = Job.getInstance(conf, "word count"); job.setJarByClass(WordCount.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(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); System.exit(job.waitForCompletion(true) ? 0 : 1); } }
2、编译源码
$ bin/hadoop com.sun.tools.javac.Main WordCount.java #将WordCount.java编译成三个.class文件 $ jar cf wc.jar WordCount*.class #将三个.class文件打包成jar文件 
3、运行
新建input文件夹，用于存放需要统计的文本。
cd /opt/hadoop-2.6.0 mkdir input 复制hadoop-2.6.0文件夹下的txt文件到input文件夹下。
cp *.txt /opt/hadoop-2.6.0/input
运行命令。
bin/hadoop jar wc.jar WordCount /opt/hadoop-2.6.0/input /opt/hadoop-2.6.0/output #自动生成output文件夹，用于存放分词统计结果。
4、查看结果
bin/hdfs dfs -cat /opt/hadoop-2.6.0/output/part-r-00000
至此， WordCount分词统计 运行成功，Hadoop环境搭建成功。
正文到此结束
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文章和留言都翻到11页了 没有OOM
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朋友，翻页到11页，及以后，会出现OOM，无法访问
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搞个gitee的项目
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版本号是多少，你可以下载哪个代码仓库，jdk选1.8 直接跑就行
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