1.圖解MapReduceMapReduce整體流程圖

並行讀取文本中的內容,然后進行MapReduce操作

Map過程:並行讀取三行,對讀取的單詞進行map操作,每個詞都以<key,value>形式生成

reduce操作是對map的結果進行排序,合並,最后得出詞頻。

2.簡單過程:
MergeSort的過程(ps:2012-10-18)Map:
<Hello,1><World,1><Bye,1><World,1><Hello,1><Hadoop,1><Bye,1><Hadoop,1><Bye,1><Hadoop,1><Hello,1><Hadoop,1>
MergeSort:
- <Hello,1><World,1><Bye,1><World,1><Hello,1><Hadoop,1> | <Bye,1><Hadoop,1><Bye,1><Hadoop,1><Hello,1><Hadoop,1>
- <Hello,1><World,1><Bye,1> || <World,1><Hello,1><Hadoop,1> | <Bye,1><Hadoop,1><Bye,1> || <Hadoop,1><Hello,1><Hadoop,1>
- <Hello,1><World,1> ||| <Bye,1> || <World,1><Hello,1> ||| <Hadoop,1> | <Bye,1><Hadoop,1> ||| <Bye,1> || <Hadoop,1><Hello,1> ||| <Hadoop,1>
- MergeArray 結果:<Hello,1><World,1> ||| <Bye,1> || <Hello,1><World,1> ||| <Hadoop,1> | <Bye,1><Hadoop,1> ||| <Bye,1> || <Hadoop,1><Hello,1> ||| <Hadoop,1> 在|||這一層級
- MergeArray 結果:<Bye,1><Hello,1><World,1> || <Hadoop,1><Hello,1><World,1> | <Bye,1><Bye,1><Hadoop,1> || <Hadoop,1><Hadoop,1><Hello,1> 在||這一層級
- MergeArray 結 果:<Bye,1><Hadoop,1><Hello,1><World,1><Hello,1><World,1> | <Bye,1><Bye,1><Hadoop,1><Hadoop,1><Hello,1><Hadoop,1> 在|這一層級
- MergeArray結 果:<Bye,1><Bye,1><Bye,1><Hadoop,1><Hadoop,1><Hadoop,1><Hadoop,1><Hello,1><Hello,1><Hello,1><World,1><World,1> 排序完成
3.代碼實例:
package cn.opensv.hadoop.ch1;
import java.io.IOException;
import java.util.StringTokenizer;
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.output.FileOutputFormat;
/**
* Hello world!
*
*/
public class WordCount1 {
public static class Map extends Mapper<LongWritable, Text, Text, LongWritable> {
private final static LongWritable one = new LongWritable(1);
private Text word = new Text();
@Override
public void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
String line = value.toString();
StringTokenizer tokenizer = new StringTokenizer(line);
while (tokenizer.hasMoreTokens()) {
word.set(tokenizer.nextToken());
context.write(word, one);
}
}
}
public static class Reduce extends Reducer<Text, LongWritable, Text, LongWritable> {
@Override
public void reduce(Text key, Iterable<LongWritable> values, Context context)
throws IOException, InterruptedException {
long sum = 0;
for (LongWritable val : values) {
sum += val.get();
}
context.write(key, new LongWritable(sum));
}
}
public static void main(String[] args) throws Exception {
Configuration cfg = new Configuration();
Job job = new Job(cfg);
job.setJarByClass(WordCount1.class);
job.setJobName("wordcount1"); // 設置一個用戶定義的job名稱
job.setOutputKeyClass(Text.class); // 為job的輸出數據設置Key類
job.setOutputValueClass(LongWritable.class); // 為job輸出設置value類
job.setMapperClass(Map.class); // 為job設置Mapper類
job.setCombinerClass(Reduce.class); // 為job設置Combiner類
job.setReducerClass(Reduce.class); // 為job設置Reduce類
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.waitForCompletion(true);
}
}
