暑假总结7
MapReduce 主要是依靠开发者通过编程来实现功能的,开发者可以通过实现 Map 和 Reduce 相关的方法来进行数据处理。
package com.runoob.hadoop;
import java.io.IOException;
import java.util.*;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.*;
/**
* 与 `Map` 相关的方法
*/
class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(LongWritable key,
Text value,
OutputCollector<Text, IntWritable> output,
Reporter reporter)
throws IOException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
output.collect(word, one);
}
}
}
/**
* 与 `Reduce` 相关的方法
*/
class Reduce extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key,
Iterator<IntWritable> values,
OutputCollector<Text, IntWritable> output,
Reporter reporter)
throws IOException {
int sum = 0;
while (values.hasNext()) {
sum += values.next().get();
}
output.collect(key, new IntWritable(sum));
}
}
public class MyWordCount {
public static void main(String[] args) throws Exception {
JobConf conf = new JobConf(MyWordCount.class);
conf.setJobName("my_word_count");
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(IntWritable.class);
conf.setMapperClass(Map.class);
conf.setCombinerClass(Reduce.class);
conf.setReducerClass(Reduce.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
// 第一个参数表示输入
FileInputFormat.setInputPaths(conf, new Path(args[0]));
// 第二个输入参数表示输出
FileOutputFormat.setOutputPath(conf, new Path(args[1]));
JobClient.runJob(conf);
}
}

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