MapReduce的KeyValueTextInputFormat

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如果行中有分隔符，那么分隔符前面的作为key，后面的作为value；如果没有分隔符，那么整行作为key，value为空

当输入数据的每一行是两列，并用tab分离的形式的时候，KeyValueTextInputformat处理这种格式的文件非常适合。

代码示例：

package com.bigdata.hadoop.mapred;import java.io.IOException;import java.net.URI;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.FileSystem;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.Mapper;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.input.KeyValueLineRecordReader;import org.apache.hadoop.mapreduce.lib.input.KeyValueTextInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;public class MyKeyValueTextInputFormatApp {private static final String INPUT_PATH = "hdfs://hadoop1:9000/dir1/hello";private static final String OUTPUT_PATH = "hdfs://hadoop1:9000/dir1/out";public static void main(String[] args) throws Exception {Configuration configuration = new Configuration();//分隔符默认是\tconfiguration.set(KeyValueLineRecordReader.KEY_VALUE_SEPERATOR, "\t");Job job = new Job(configuration,MyKeyValueTextInputFormatApp.class.getSimpleName());final FileSystem fileSystem = FileSystem.get(new URI(OUTPUT_PATH), configuration);fileSystem.delete(new Path(OUTPUT_PATH),true);job.setJarByClass(MyKeyValueTextInputFormatApp.class);FileInputFormat.setInputPaths(job, INPUT_PATH);//指定使用KeyValueTextInputFormat解析内容 分隔key和value的分隔符默认是\tjob.setInputFormatClass(KeyValueTextInputFormat.class);job.setMapperClass(MyMapper.class);job.setMapOutputKeyClass(Text.class);job.setMapOutputValueClass(LongWritable.class);job.setNumReduceTasks(0);FileOutputFormat.setOutputPath(job, new Path(OUTPUT_PATH));job.waitForCompletion(true);}//做简单输出public static class MyMapper extends Mapper<Text, Text, Text, LongWritable>{@Overrideprotected void map(Text key, Text value,Mapper<Text, Text, Text, LongWritable>.Context context)throws IOException, InterruptedException {context.write(new Text(key), new LongWritable(1));context.write(new Text(value), new LongWritable(1));}}}

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