Java – Hadoop MapReduce: driver for linking mapper in MapReduce job
•
Java
I have a MapReduce job:
public static class MapClass extends Mapper<Text,Text,LongWritable> {
@Override
public void map(Text key,Text value,Context context)
throws IOException,InterruptedException {
}
}
I want to use chainmapper:
1. Job job = new Job(conf,"Job with chained tasks");
2. job.setJarByClass(MapReduce.class);
3. job.setInputFormatClass(TextInputFormat.class);
4. job.setOutputFormatClass(TextOutputFormat.class);
5. FileInputFormat.setInputPaths(job,new Path(InputFile));
6. FileOutputFormat.setOutputPath(job,new Path(OutputFile));
7. JobConf map1 = new JobConf(false);
8. ChainMapper.addMapper(
job,MapClass.class,Text.class,true,map1
);
But its report has an error on line 8:
Solution
After a lot of "effort", I can use chainmapper / chainreducer Thanks for your last comment user864846
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package myPKG;
/*
* Ajitsen: Sample program for ChainMapper/ChainReducer. This program is modified version of WordCount example available in Hadoop-0.18.0. Added ChainMapper/ChainReducer and made to works in Hadoop 1.0.2.
*/
import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.*;
import org.apache.hadoop.mapred.lib.ChainMapper;
import org.apache.hadoop.mapred.lib.ChainReducer;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
public class ChainWordCount extends Configured implements Tool {
public static class Tokenizer extends MapReduceBase
implements Mapper<LongWritable,IntWritable> {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(LongWritable key,OutputCollector<Text,IntWritable> output,Reporter reporter) throws IOException {
String line = value.toString();
System.out.println("Line:"+line);
StringTokenizer itr = new StringTokenizer(line);
while (itr.hasMoreTokens()) {
word.set(itr.nextToken());
output.collect(word,one);
}
}
}
public static class UpperCaser extends MapReduceBase
implements Mapper<Text,IntWritable,IntWritable> {
public void map(Text key,IntWritable value,Reporter reporter) throws IOException {
String word = key.toString().toUpperCase();
System.out.println("Upper Case:"+word);
output.collect(new Text(word),value);
}
}
public static class Reduce extends MapReduceBase
implements Reducer<Text,IntWritable> {
public void reduce(Text key,Iterator<IntWritable> values,Reporter reporter) throws IOException {
int sum = 0;
while (values.hasNext()) {
sum += values.next().get();
}
System.out.println("Word:"+key.toString()+"\tCount:"+sum);
output.collect(key,new IntWritable(sum));
}
}
static int printUsage() {
System.out.println("wordcount <input> <output>");
ToolRunner.printGenericCommandUsage(System.out);
return -1;
}
public int run(String[] args) throws Exception {
JobConf conf = new JobConf(getConf(),ChainWordCount.class);
conf.setJobName("wordcount");
if (args.length != 2) {
System.out.println("ERROR: Wrong number of parameters: " +
args.length + " instead of 2.");
return printUsage();
}
FileInputFormat.setInputPaths(conf,args[0]);
FileOutputFormat.setOutputPath(conf,new Path(args[1]));
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
JobConf mapAConf = new JobConf(false);
ChainMapper.addMapper(conf,Tokenizer.class,LongWritable.class,IntWritable.class,mapAConf);
JobConf mapBConf = new JobConf(false);
ChainMapper.addMapper(conf,UpperCaser.class,mapBConf);
JobConf reduceConf = new JobConf(false);
ChainReducer.setReducer(conf,Reduce.class,reduceConf);
JobClient.runJob(conf);
return 0;
}
public static void main(String[] args) throws Exception {
int res = ToolRunner.run(new Configuration(),new ChainWordCount(),args);
System.exit(res);
}
}
Edit the latest version (at least from Hadoop 2.6) without the real flag in addmapper In fact, there is a change in the signature to suppress it
So it will be fair
JobConf mapAConf = new JobConf(false); ChainMapper.addMapper(conf,mapAConf);
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