1. WordCount程序
1.1 WordCount源程序
- import java.io.IOException;
- import java.util.Iterator;
- 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;
- import org.apache.hadoop.util.GenericOptionsParser;
- public class WordCount {
- public WordCount() {
- }
- 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> [<in>...] <out>");
- System.exit(2);
- }
- Job job = Job.getInstance(conf, "word count");
- job.setJarByClass(WordCount.class);
- job.setMapperClass(WordCount.TokenizerMapper.class);
- job.setCombinerClass(WordCount.IntSumReducer.class);
- job.setReducerClass(WordCount.IntSumReducer.class);
- job.setOutputKeyClass(Text.class);
- job.setOutputValueClass(IntWritable.class);
- for(int i = 0; i < otherArgs.length - 1; ++i) {
- FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
- }
- FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1]));
- System.exit(job.waitForCompletion(true)?0:1);
- }
- public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {
- private static final IntWritable one = new IntWritable(1);
- private Text word = new Text();
- public TokenizerMapper() {
- }
- public void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context) throws IOException, InterruptedException {
- StringTokenizer itr = new StringTokenizer(value.toString());
- while(itr.hasMoreTokens()) {
- this.word.set(itr.nextToken());
- context.write(this.word, one);
- }
- }
- }
- public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
- private IntWritable result = new IntWritable();
- public IntSumReducer() {
- }
- public void reduce(Text key, Iterable<IntWritable> values, Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {
- int sum = 0;
- IntWritable val;
- for(Iterator i$ = values.iterator(); i$.hasNext(); sum += val.get()) {
- val = (IntWritable)i$.next();
- }
- this.result.set(sum);
- context.write(key, this.result);
- }
- }
- }
1.2 运行程序,Run As->Java Applicatiion
1.3 编译打包程序,产生Jar文件

2 运行程序
2.1 建立要统计词频的文本文件
wordfile1.txt
Spark Hadoop
Big Data
wordfile2.txt
Spark Hadoop
Big Cloud
2.2 启动hdfs,新建input文件夹,上传词频文件
cd /usr/local/hadoop/
./sbin/start-dfs.sh
./bin/hadoop fs -mkdir input
./bin/hadoop fs -put /home/hadoop/wordfile1.txt input
./bin/hadoop fs -put /home/hadoop/wordfile2.txt input
2.3 查看已上传的词频文件:
hadoop@dblab-VirtualBox:/usr/local/hadoop$ ./bin/hadoop fs -ls .
Found 2 items
drwxr-xr-x - hadoop supergroup 0 2019-02-11 15:40 input
-rw-r--r-- 1 hadoop supergroup 5 2019-02-10 20:22 test.txt
hadoop@dblab-VirtualBox:/usr/local/hadoop$ ./bin/hadoop fs -ls ./input
Found 2 items
-rw-r--r-- 1 hadoop supergroup 27 2019-02-11 15:40 input/wordfile1.txt
-rw-r--r-- 1 hadoop supergroup 29 2019-02-11 15:40 input/wordfile2.txt
2.4 运行WordCount
./bin/hadoop jar /home/hadoop/WordCount.jar input output
屏幕上会输入大段信息
然后可以查看运行结果:
hadoop@dblab-VirtualBox:/usr/local/hadoop$ ./bin/hadoop fs -cat output/*
Hadoop 2
Spark 2
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