KeyValueTextInputFormat用法

数据是以空格为分隔符的。

[root@baolibin hadoop]# hadoop fs -text /input/hehe
Warning: $HADOOP_HOME is deprecated.

hello you
hello me
hello you
hello me

代码如下：

package hadoop_2_6_0;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
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.Reducer;
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;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;

public class KeyValueTextInputFormatTest {
	
	public static class MyMapper extends
			Mapper<Text, Text, Text, LongWritable> {
		final Text k2 = new Text();
		final LongWritable v2 = new LongWritable();

		protected void map(Text key, Text value,
				Mapper<Text, Text, Text, LongWritable>.Context context)
				throws InterruptedException, IOException {
		//	final String line = value.toString();
		//	final String[] splited = line.split("o");
		//	for (String word : splited) {
		//		k2.set(word);
				k2.set(key);
				v2.set(1);
				context.write(k2, v2);
		//	}
		}
	}

	public static class MyReducer extends
			Reducer<Text, LongWritable, Text, LongWritable> {
		LongWritable v3 = new LongWritable();

		protected void reduce(Text k2, Iterable<LongWritable> v2s,
				Reducer<Text, LongWritable, Text, LongWritable>.Context context)
				throws IOException, InterruptedException {
			long count = 0L;
			for (LongWritable v2 : v2s) {
				count += v2.get();
			}
			v3.set(count);
			context.write(k2, v3);
		}
	}

	public static void main(String[] args) throws Exception {
		final Configuration conf = new Configuration();
		
		conf.set(KeyValueLineRecordReader.KEY_VALUE_SEPERATOR, " "); 
		
		final Job job = Job.getInstance(conf, KeyValueTextInputFormatTest.class.getSimpleName());		
		// 1.1
		FileInputFormat.setInputPaths(job,"hdfs://192.168.1.100:9000/input/hehe");
		
		//
		job.setInputFormatClass(KeyValueTextInputFormat.class);
		
		
		// 1.2
		job.setMapperClass(MyMapper.class);
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(LongWritable.class);
		// 1.3 
		job.setPartitionerClass(HashPartitioner.class);
		job.setNumReduceTasks(1);
		// 1.4
		// 1.5

		// 2.2
		job.setReducerClass(MyReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(LongWritable.class);
		// 2.3
		FileOutputFormat.setOutputPath(job, new Path("hdfs://192.168.1.100:9000/out5"));
		job.setOutputFormatClass(TextOutputFormat.class);
		// 
		job.setJarByClass(KeyValueTextInputFormatTest.class);
		job.waitForCompletion(true);
	}
}

结果如下：

</pre><pre name="code" class="java">[root@baolibin hadoop]# hadoop fs -text /out5/part-r*
Warning: $HADOOP_HOME is deprecated.

hello   4

解析：

下面这行代码说明每行数据以空格为分隔符，空格前面为key，空格后面为value

conf.set(KeyValueLineRecordReader.KEY_VALUE_SEPERATOR, " "); 

如果不指定分隔符，则整行为key，value为空值。

指明使用的是KeyValueTextInputFormat。

job.setInputFormatClass(KeyValueTextInputFormat.class);

map函数里面可以直接调用set方法：

k2.set(key);
v2.set(1);
context.write(k2, v2);

这里的key和value值都已经分割好了，我这里只用了分割好的key值，value并没有用。

我把map函数里面写成这样，调用value的值：

k2.set(value);
v2.set(1);
context.write(k2, v2);

结果如下：

[root@baolibin hadoop]# hadoop fs -text /out6/part-r*
Warning: $HADOOP_HOME is deprecated.

me      2
you     2