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* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
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*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
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package com.aliyun.odps.mapred.example;
import java.io.IOException;
import java.util.Iterator;
import com.aliyun.odps.Column;
import com.aliyun.odps.OdpsException;
import com.aliyun.odps.OdpsType;
import com.aliyun.odps.data.Record;
import com.aliyun.odps.data.TableInfo;
import com.aliyun.odps.mapred.JobClient;
import com.aliyun.odps.mapred.MapperBase;
import com.aliyun.odps.mapred.ReducerBase;
import com.aliyun.odps.mapred.conf.JobConf;
import com.aliyun.odps.mapred.utils.InputUtils;
import com.aliyun.odps.mapred.utils.OutputUtils;
/**
* This is an example ODPS Map/Reduce application. It reads the input table, map
* each column into words and counts them. The output is a locally sorted list
* of words and the count of how often they occurred.
* <p>
* To run: mapreduce -libjars mapreduce-examples.jar
* com.aliyun.odps.mapreduce.examples.WordCount <i>in-tbl</i> <i>out-tbl</i>
*/
public class WordCount {
/**
* Counts the words in each record. For each record, emit each column as
* (<b>word</b>, <b>1</b>).
*/
public static class TokenizerMapper extends MapperBase {
Record word;
Record one;
@Override
public void setup(TaskContext context) throws IOException {
word = context.createMapOutputKeyRecord();
one = context.createMapOutputValueRecord();
one.setBigint(0, 1L);
}
@Override
public void map(long recordNum, Record record, TaskContext context)
throws IOException {
for (int i = 0; i < record.getColumnCount(); i++) {
String[] words = record.get(i).toString().split("\\s+");
for (String w : words) {
word.setString(0, w);
context.write(word, one);
}
}
}
}
/**
* A combiner class that combines map output by sum them.
*/
public static class SumCombiner extends ReducerBase {
private Record count;
@Override
public void setup(TaskContext context) throws IOException {
count = context.createMapOutputValueRecord();
}
@Override
public void reduce(Record key, Iterator<Record> values, TaskContext context)
throws IOException {
long c = 0;
while (values.hasNext()) {
Record val = values.next();
c += (Long) val.get(0);
}
count.set(0, c);
context.write(key, count);
}
}
/**
* A reducer class that just emits the sum of the input values.
*/
public static class SumReducer extends ReducerBase {
private Record result;
@Override
public void setup(TaskContext context) throws IOException {
result = context.createOutputRecord();
}
@Override
public void reduce(Record key, Iterator<Record> values, TaskContext context)
throws IOException {
long count = 0;
while (values.hasNext()) {
Record val = values.next();
count += (Long) val.get(0);
}
result.set(0, key.get(0));
result.set(1, count);
context.write(result);
}
}
public static void main(String[] args) throws OdpsException {
if (args.length != 2) {
System.err.println("Usage: wordcount <in_table> <out_table>");
System.exit(2);
}
JobConf job = new JobConf();
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(SumCombiner.class);
job.setReducerClass(SumReducer.class);
job.setMapOutputKeySchema(new Column[]{new Column("word", OdpsType.STRING)});
job.setMapOutputValueSchema(new Column[]{new Column("count",
OdpsType.BIGINT)});
InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
OutputUtils.addTable(TableInfo.builder().tableName(args[1]).build(), job);
JobClient.runJob(job);
}
}