hadoop1.2.1中使用MultipleOutputs将结果输出到多个文件或文件夹
使用步骤主要有三步:
1、在reduce或map类中创建MultipleOutputs对象,将结果输出
- class reduceStatistics extends Reducer<Text, IntWritable, Text, IntWritable>{
- //将结果输出到多个文件或多个文件夹
- private MultipleOutputs<Text,IntWritable> mos;
- //创建对象
- protected void setup(Context context) throws IOException,InterruptedException {
- mos = new MultipleOutputs<Text, IntWritable>(context);
- }
- //关闭对象
- protected void cleanup(Context context) throws IOException,InterruptedException {
- mos.close();
- }
- }
2、在map或reduce方法中使用MultipleOutputs对象输出数据,代替congtext.write()
- protected void reduce(Text key, Iterable<IntWritable> values, Context context)
- throws IOException, InterruptedException {
- IntWritable V = new IntWritable();
- int sum = 0;
- for(IntWritable value : values){
- sum = sum + value.get();
- }
- System.out.println("word:" + key.toString() + " sum = " + sum);
- V.set(sum);
- //使用MultipleOutputs对象输出数据
- if(key.toString().equals("hello")){
- mos.write("hello", key, V);
- }else if(key.toString().equals("world")){
- mos.write("world", key, V);
- }else if(key.toString().equals("hadoop")){
- //输出到hadoop/hadoopfile-r-00000文件
- mos.write("hadoopfile", key, V, "hadoop/");
- }
- }
3、在创建job时,定义附加的输出文件,这里的文件名称与第二步设置的文件名相同
- //定义附加的输出文件
- MultipleOutputs.addNamedOutput(job,"hello",TextOutputFormat.class,Text.class,IntWritable.class);
- MultipleOutputs.addNamedOutput(job,"world",TextOutputFormat.class,Text.class,IntWritable.class);
- MultipleOutputs.addNamedOutput(job,"hadoopfile",TextOutputFormat.class,Text.class,IntWritable.class);
完整代码:
- package com.ru.hadoop.wordcount;
- import java.io.IOException;
- import java.net.URI;
- import java.net.URISyntaxException;
- import java.util.regex.Pattern;
- import org.apache.hadoop.conf.Configuration;
- import org.apache.hadoop.conf.Configured;
- import org.apache.hadoop.fs.FileSystem;
- import org.apache.hadoop.fs.Path;
- import org.apache.hadoop.io.IntWritable;
- import org.apache.hadoop.io.LongWritable;
- import org.apache.hadoop.io.NullWritable;
- import org.apache.hadoop.io.Text;
- import org.apache.hadoop.mapred.JobConf;
- import org.apache.hadoop.mapred.RecordWriter;
- import org.apache.hadoop.mapred.lib.MultipleOutputFormat;
- import org.apache.hadoop.mapred.lib.MultipleTextOutputFormat;
- 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.mapreduce.lib.output.MultipleOutputs;
- import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
- import org.apache.hadoop.util.Progressable;
- public class WordCount2 extends Configured{
- public static void main(String[] args) {
- String in = "/home/nange/work/test/word/";
- String out = "hdfs://localhost:9000/hdfs/test/wordcount/out/";
- Job job;
- try {
- //删除hdfs目录
- WordCount2 wc2 = new WordCount2();
- wc2.removeDir(out);
- job = new Job(new Configuration(), "wordcount Job");
- job.setOutputKeyClass(Text.class);
- job.setOutputValueClass(IntWritable.class);
- job.setMapperClass(mapperString.class);
- // job.setCombinerClass(reduceStatistics.class);
- job.setReducerClass(reduceStatistics.class);
- //定义附加的输出文件
- MultipleOutputs.addNamedOutput(job,"hello",TextOutputFormat.class,Text.class,IntWritable.class);
- MultipleOutputs.addNamedOutput(job,"world",TextOutputFormat.class,Text.class,IntWritable.class);
- MultipleOutputs.addNamedOutput(job,"hadoopfile",TextOutputFormat.class,Text.class,IntWritable.class);
- FileInputFormat.addInputPath(job, new Path(in));
- FileOutputFormat.setOutputPath(job, new Path(out));
- job.waitForCompletion(true);
- } catch (IOException e) {
- e.printStackTrace();
- } catch (URISyntaxException e) {
- e.printStackTrace();
- } catch (ClassNotFoundException e) {
- e.printStackTrace();
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
- public void removeDir(String filePath) throws IOException, URISyntaxException{
- String url = "hdfs://localhost:9000";
- FileSystem fs = FileSystem.get(new URI(url), new Configuration());
- fs.delete(new Path(filePath));
- }
- }
- /**
- * 重写maptask使用的map方法
- * @author nange
- *
- */
- class mapperString extends Mapper<LongWritable, Text, Text, IntWritable>{
- //设置正则表达式的编译表达形式
- public static Pattern PATTERN = Pattern.compile(" ");
- Text K = new Text();
- IntWritable V = new IntWritable(1);
- @Override
- protected void map(LongWritable key, Text value, Context context)
- throws IOException, InterruptedException {
- String[] words = PATTERN.split(value.toString());
- System.out.println("********" + value.toString());
- for(String word : words){
- K.set(word);
- context.write(K, V);
- }
- }
- }
- /**
- * 对单词做统计
- * @author nange
- *
- */
- class reduceStatistics extends Reducer<Text, IntWritable, Text, IntWritable>{
- //将结果输出到多个文件或多个文件夹
- private MultipleOutputs<Text,IntWritable> mos;
- //创建MultipleOutputs对象
- protected void setup(Context context) throws IOException,InterruptedException {
- mos = new MultipleOutputs<Text, IntWritable>(context);
- }
- @Override
- protected void reduce(Text key, Iterable<IntWritable> values, Context context)
- throws IOException, InterruptedException {
- IntWritable V = new IntWritable();
- int sum = 0;
- for(IntWritable value : values){
- sum = sum + value.get();
- }
- System.out.println("word:" + key.toString() + " sum = " + sum);
- V.set(sum);
- //使用MultipleOutputs对象输出数据
- if(key.toString().equals("hello")){
- mos.write("hello", key, V);
- }else if(key.toString().equals("world")){
- mos.write("world", key, V);
- }else if(key.toString().equals("hadoop")){
- //输出到hadoop/hadoopfile-r-00000文件
- mos.write("hadoopfile", key, V, "hadoop/");
- }
- }
- //关闭MultipleOutputs对象
- protected void cleanup(Context context) throws IOException,InterruptedException {
- mos.close();
- }
- }