大数据学习(6)MapReduce应用

倒排索引

/**
*
*
* <pre>
*file1.txt:
*hello ketty
*hello tomcat
*
*file2.txt:
*hello hadoop
*
*map1:
*hello:file1.txt 1
*hello:file1.txt 1
*ketty:file1.txt 1
*tomcat:file1.txt 1
*hello:file2.txt 1
*hadoop:file2.txt 1
*
*reduce1:
*hello:file1.txt 2
*ketty:file1.txt 1
*tomcat:file1.txt 1
*hello:file2.txt 1
*hadoop:file2.txt 1
*
*reduce2:
*hello file1.txt 2,file2.txt 1
*ketty file1.txt 1
*tomcat file1.txt 1
*hadoop file2.txt 1
*</pre>
* @author huqiao
*/
public class InvertedIndex { /**
* input:files to be inverted index<br/>
* output: someword:filename count
* @author huqiao
*/
static class WordInFileCountMapper extends Mapper<LongWritable,Text,Text,LongWritable>{ @Override
protected void map(LongWritable key, Text value,Context ctx)
throws IOException, InterruptedException {
String line = value.toString();
String[] words = line.split(" "); FileSplit fileSplit = (FileSplit)ctx.getInputSplit();
String fileName = fileSplit.getPath().getName();
for(String word : words) {
ctx.write(new Text(word + ":" + fileName), new LongWritable(1));
}
} } /**
* output:
* <pre>
*hello:file1.txt 2
*ketty:file1.txt 1
*tomcat:file1.txt 1
*hello:file2.txt 1
*hadoop:file2.txt 1
*</pre>
* @author huqiao
*/
static class WordInFileCountReducer extends Reducer<Text,LongWritable,Text,LongWritable>{ @Override
protected void reduce(Text key, Iterable<LongWritable> values, Context ctx) throws IOException, InterruptedException {
int total = 0;
for(LongWritable value : values) {
total += value.get();
}
ctx.write(key, new LongWritable(total));
} } /**
* output:
* <pre>
* hello-->WordCountRecord{fileName:file1.txt,count:2}
* ...
* </pre>
* @author huqiao
*/
static class InvertedIndexMapper extends Mapper<LongWritable,Text,Text,WordCountRecord>{ @Override
protected void map(LongWritable key, Text value,Context ctx)
throws IOException, InterruptedException {
String line = value.toString();
String[] lineArray = line.split("\t");
String[] wordAndFileName = lineArray[0].split(":");
String word = wordAndFileName[0];
String fileName = wordAndFileName[1];
Long count = Long.parseLong(lineArray[1]); ctx.write(new Text(word), new WordCountRecord(fileName, count)); } } /**
* output:
* <pre>
* hello-->file1.txt 2,file2.txt 1
* ...
* </pre>
* @author huqiao
*/
static class InvertedIndexReducer extends Reducer<Text,WordCountRecord,Text,Text>{ @Override
protected void reduce(Text key, Iterable<WordCountRecord> values, Context ctx) throws IOException, InterruptedException {
StringBuffer output = new StringBuffer();
for(WordCountRecord value : values) {
output.append(value.getFileName() + " " + value.getCount()+",");
}
ctx.write(key, new Text(output.toString()));
} } public static void main(String[] args) throws Exception{ String inputPath = args[0];
String outputPath = args[1];
String phase = args[2]; FileSystem fs = FileSystem.get(new URI("hdfs://vcentos1:9000"),new Configuration(),"root"); //delete output path when it existed
Path output = new Path(outputPath);
if(fs.exists(output)) {
fs.delete(output,true);
} if("phase1".equals(phase)) {
doPhase1(inputPath,outputPath);
}else {
doPhase2(inputPath,outputPath);
} } private static void doPhase1(String inputPath,String outputPath)throws Exception {
Job job = Job.getInstance(); job.setJarByClass(InvertedIndex.class); job.setMapperClass(WordInFileCountMapper.class);
job.setReducerClass(WordInFileCountReducer.class); job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(LongWritable.class); job.setOutputKeyClass(Text.class);
job.setOutputValueClass(LongWritable.class); FileInputFormat.setInputPaths(job, new Path(inputPath));
FileOutputFormat.setOutputPath(job, new Path(outputPath)); boolean success = job.waitForCompletion(true); System.exit(success ? 0 : 1);
} private static void doPhase2(String inputPath,String outputPath)throws Exception {
Job job = Job.getInstance(); job.setJarByClass(InvertedIndex.class); job.setMapperClass(InvertedIndexMapper.class);
job.setReducerClass(InvertedIndexReducer.class); job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(WordCountRecord.class); job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class); FileInputFormat.setInputPaths(job, new Path(inputPath));
FileOutputFormat.setOutputPath(job, new Path(outputPath)); boolean success = job.waitForCompletion(true); System.exit(success ? 0 : 1);
} }

执行时分两个阶段:

 hadoop jar mr.jar me.huqiao.hadoop.demo_code.invertedsort.InvertedIndex /invertedindex/input /invertedindex/phase-a-output/ phase1

然后以第一个阶段的输出作为第二个阶段的输入:

hadoop jar mr.jar me.huqiao.hadoop.demo_code.invertedsort.InvertedIndex /invertedindex/phase-a-output /invertedindex/phase-b-output/ phase2

最终效果类似于:

about   logs.txt ,
are text.txt ,
hadoop file1.txt ,
hdfs file1.txt ,
hello text.txt ,logs.txt ,file1.txt ,
how logs.txt ,text.txt ,
kitty logs.txt ,
today logs.txt ,
tom text.txt ,
you text.txt ,

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