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/**
 * 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 org.apache.hadoop.mapred.lib;

import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.mapred.*;

import java.io.IOException;
import java.util.Iterator;

/**
 * The ChainReducer class allows to chain multiple Mapper classes after a
 * Reducer within the Reducer task.
 * 

* For each record output by the Reducer, the Mapper classes are invoked in a * chained (or piped) fashion, the output of the first becomes the input of the * second, and so on until the last Mapper, the output of the last Mapper will * be written to the task's output. *

* The key functionality of this feature is that the Mappers in the chain do not * need to be aware that they are executed after the Reducer or in a chain. * This enables having reusable specialized Mappers that can be combined to * perform composite operations within a single task. *

* Special care has to be taken when creating chains that the key/values output * by a Mapper are valid for the following Mapper in the chain. It is assumed * all Mappers and the Reduce in the chain use maching output and input key and * value classes as no conversion is done by the chaining code. *

* Using the ChainMapper and the ChainReducer classes is possible to compose * Map/Reduce jobs that look like [MAP+ / REDUCE MAP*]. And * immediate benefit of this pattern is a dramatic reduction in disk IO. *

* IMPORTANT: There is no need to specify the output key/value classes for the * ChainReducer, this is done by the setReducer or the addMapper for the last * element in the chain. *

* ChainReducer usage pattern: *

*

 * ...
 * conf.setJobName("chain");
 * conf.setInputFormat(TextInputFormat.class);
 * conf.setOutputFormat(TextOutputFormat.class);
 *
 * JobConf mapAConf = new JobConf(false);
 * ...
 * ChainMapper.addMapper(conf, AMap.class, LongWritable.class, Text.class,
 *   Text.class, Text.class, true, mapAConf);
 *
 * JobConf mapBConf = new JobConf(false);
 * ...
 * ChainMapper.addMapper(conf, BMap.class, Text.class, Text.class,
 *   LongWritable.class, Text.class, false, mapBConf);
 *
 * JobConf reduceConf = new JobConf(false);
 * ...
 * ChainReducer.setReducer(conf, XReduce.class, LongWritable.class, Text.class,
 *   Text.class, Text.class, true, reduceConf);
 *
 * ChainReducer.addMapper(conf, CMap.class, Text.class, Text.class,
 *   LongWritable.class, Text.class, false, null);
 *
 * ChainReducer.addMapper(conf, DMap.class, LongWritable.class, Text.class,
 *   LongWritable.class, LongWritable.class, true, null);
 *
 * FileInputFormat.setInputPaths(conf, inDir);
 * FileOutputFormat.setOutputPath(conf, outDir);
 * ...
 *
 * JobClient jc = new JobClient(conf);
 * RunningJob job = jc.submitJob(conf);
 * ...
 * 
*/ @InterfaceAudience.Public @InterfaceStability.Stable public class ChainReducer implements Reducer { /** * Sets the Reducer class to the chain job's JobConf. *

* It has to be specified how key and values are passed from one element of * the chain to the next, by value or by reference. If a Reducer leverages the * assumed semantics that the key and values are not modified by the collector * 'by value' must be used. If the Reducer does not expect this semantics, as * an optimization to avoid serialization and deserialization 'by reference' * can be used. *

* For the added Reducer the configuration given for it, * reducerConf, have precedence over the job's JobConf. This * precedence is in effect when the task is running. *

* IMPORTANT: There is no need to specify the output key/value classes for the * ChainReducer, this is done by the setReducer or the addMapper for the last * element in the chain. * * @param job job's JobConf to add the Reducer class. * @param klass the Reducer class to add. * @param inputKeyClass reducer input key class. * @param inputValueClass reducer input value class. * @param outputKeyClass reducer output key class. * @param outputValueClass reducer output value class. * @param byValue indicates if key/values should be passed by value * to the next Mapper in the chain, if any. * @param reducerConf a JobConf with the configuration for the Reducer * class. It is recommended to use a JobConf without default values using the * JobConf(boolean loadDefaults) constructor with FALSE. */ public static void setReducer(JobConf job, Class> klass, Class inputKeyClass, Class inputValueClass, Class outputKeyClass, Class outputValueClass, boolean byValue, JobConf reducerConf) { job.setReducerClass(ChainReducer.class); job.setOutputKeyClass(outputKeyClass); job.setOutputValueClass(outputValueClass); Chain.setReducer(job, klass, inputKeyClass, inputValueClass, outputKeyClass, outputValueClass, byValue, reducerConf); } /** * Adds a Mapper class to the chain job's JobConf. *

* It has to be specified how key and values are passed from one element of * the chain to the next, by value or by reference. If a Mapper leverages the * assumed semantics that the key and values are not modified by the collector * 'by value' must be used. If the Mapper does not expect this semantics, as * an optimization to avoid serialization and deserialization 'by reference' * can be used. *

* For the added Mapper the configuration given for it, * mapperConf, have precedence over the job's JobConf. This * precedence is in effect when the task is running. *

* IMPORTANT: There is no need to specify the output key/value classes for the * ChainMapper, this is done by the addMapper for the last mapper in the chain * . * * @param job chain job's JobConf to add the Mapper class. * @param klass the Mapper class to add. * @param inputKeyClass mapper input key class. * @param inputValueClass mapper input value class. * @param outputKeyClass mapper output key class. * @param outputValueClass mapper output value class. * @param byValue indicates if key/values should be passed by value * to the next Mapper in the chain, if any. * @param mapperConf a JobConf with the configuration for the Mapper * class. It is recommended to use a JobConf without default values using the * JobConf(boolean loadDefaults) constructor with FALSE. */ public static void addMapper(JobConf job, Class> klass, Class inputKeyClass, Class inputValueClass, Class outputKeyClass, Class outputValueClass, boolean byValue, JobConf mapperConf) { job.setOutputKeyClass(outputKeyClass); job.setOutputValueClass(outputValueClass); Chain.addMapper(false, job, klass, inputKeyClass, inputValueClass, outputKeyClass, outputValueClass, byValue, mapperConf); } private Chain chain; /** * Constructor. */ public ChainReducer() { chain = new Chain(false); } /** * Configures the ChainReducer, the Reducer and all the Mappers in the chain. *

* If this method is overriden super.configure(...) should be * invoked at the beginning of the overwriter method. */ public void configure(JobConf job) { chain.configure(job); } /** * Chains the reduce(...) method of the Reducer with the * map(...) methods of the Mappers in the chain. */ @SuppressWarnings({"unchecked"}) public void reduce(Object key, Iterator values, OutputCollector output, Reporter reporter) throws IOException { Reducer reducer = chain.getReducer(); if (reducer != null) { reducer.reduce(key, values, chain.getReducerCollector(output, reporter), reporter); } } /** * Closes the ChainReducer, the Reducer and all the Mappers in the chain. *

* If this method is overriden super.close() should be * invoked at the end of the overwriter method. */ public void close() throws IOException { chain.close(); } }





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