/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * 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 * with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, * software distributed under the License is distributed on an * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY * KIND, either express or implied. See the License for the * specific language governing permissions and limitations * under the License. */ 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); } }