001/**
002 * Licensed to the Apache Software Foundation (ASF) under one
003 * or more contributor license agreements.  See the NOTICE file
004 * distributed with this work for additional information
005 * regarding copyright ownership.  The ASF licenses this file
006 * to you under the Apache License, Version 2.0 (the
007 * "License"); you may not use this file except in compliance
008 * with the License.  You may obtain a copy of the License at
009 *
010 *     http://www.apache.org/licenses/LICENSE-2.0
011 *
012 * Unless required by applicable law or agreed to in writing, software
013 * distributed under the License is distributed on an "AS IS" BASIS,
014 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
015 * See the License for the specific language governing permissions and
016 * limitations under the License.
017 */
018package org.apache.hadoop.mapreduce.lib.chain;
019
020import org.apache.hadoop.classification.InterfaceAudience;
021import org.apache.hadoop.classification.InterfaceStability;
022import org.apache.hadoop.conf.Configuration;
023import org.apache.hadoop.mapreduce.Job;
024import org.apache.hadoop.mapreduce.Mapper;
025import org.apache.hadoop.mapreduce.Reducer;
026import org.apache.hadoop.mapreduce.lib.chain.Chain.ChainBlockingQueue;
027
028import java.io.IOException;
029
030/**
031 * The ChainReducer class allows to chain multiple Mapper classes after a
032 * Reducer within the Reducer task.
033 * 
034 * <p>
035 * For each record output by the Reducer, the Mapper classes are invoked in a
036 * chained (or piped) fashion. The output of the reducer becomes the input of
037 * the first mapper and output of first becomes the input of the second, and so
038 * on until the last Mapper, the output of the last Mapper will be written to
039 * the task's output.
040 * </p>
041 * <p>
042 * The key functionality of this feature is that the Mappers in the chain do not
043 * need to be aware that they are executed after the Reducer or in a chain. This
044 * enables having reusable specialized Mappers that can be combined to perform
045 * composite operations within a single task.
046 * </p>
047 * <p>
048 * Special care has to be taken when creating chains that the key/values output
049 * by a Mapper are valid for the following Mapper in the chain. It is assumed
050 * all Mappers and the Reduce in the chain use matching output and input key and
051 * value classes as no conversion is done by the chaining code.
052 * </p>
053 * <p> Using the ChainMapper and the ChainReducer classes is possible to
054 * compose Map/Reduce jobs that look like <code>[MAP+ / REDUCE MAP*]</code>. And
055 * immediate benefit of this pattern is a dramatic reduction in disk IO. </p>
056 * <p>
057 * IMPORTANT: There is no need to specify the output key/value classes for the
058 * ChainReducer, this is done by the setReducer or the addMapper for the last
059 * element in the chain.
060 * </p>
061 * ChainReducer usage pattern:
062 * <p>
063 * 
064 * <pre>
065 * ...
066 * Job = new Job(conf);
067 * ....
068 *
069 * Configuration reduceConf = new Configuration(false);
070 * ...
071 * ChainReducer.setReducer(job, XReduce.class, LongWritable.class, Text.class,
072 *   Text.class, Text.class, true, reduceConf);
073 *
074 * ChainReducer.addMapper(job, CMap.class, Text.class, Text.class,
075 *   LongWritable.class, Text.class, false, null);
076 *
077 * ChainReducer.addMapper(job, DMap.class, LongWritable.class, Text.class,
078 *   LongWritable.class, LongWritable.class, true, null);
079 *
080 * ...
081 *
082 * job.waitForCompletion(true);
083 * ...
084 * </pre>
085 */
086@InterfaceAudience.Public
087@InterfaceStability.Stable
088public class ChainReducer<KEYIN, VALUEIN, KEYOUT, VALUEOUT> extends
089    Reducer<KEYIN, VALUEIN, KEYOUT, VALUEOUT> {
090
091  /**
092   * Sets the {@link Reducer} class to the chain job.
093   * 
094   * <p>
095   * The key and values are passed from one element of the chain to the next, by
096   * value. For the added Reducer the configuration given for it,
097   * <code>reducerConf</code>, have precedence over the job's Configuration.
098   * This precedence is in effect when the task is running.
099   * </p>
100   * <p>
101   * IMPORTANT: There is no need to specify the output key/value classes for the
102   * ChainReducer, this is done by the setReducer or the addMapper for the last
103   * element in the chain.
104   * </p>
105   * 
106   * @param job
107   *          the job
108   * @param klass
109   *          the Reducer class to add.
110   * @param inputKeyClass
111   *          reducer input key class.
112   * @param inputValueClass
113   *          reducer input value class.
114   * @param outputKeyClass
115   *          reducer output key class.
116   * @param outputValueClass
117   *          reducer output value class.
118   * @param reducerConf
119   *          a configuration for the Reducer class. It is recommended to use a
120   *          Configuration without default values using the
121   *          <code>Configuration(boolean loadDefaults)</code> constructor with
122   *          FALSE.
123   */
124  public static void setReducer(Job job, Class<? extends Reducer> klass,
125      Class<?> inputKeyClass, Class<?> inputValueClass,
126      Class<?> outputKeyClass, Class<?> outputValueClass,
127      Configuration reducerConf) {
128    job.setReducerClass(ChainReducer.class);
129    job.setOutputKeyClass(outputKeyClass);
130    job.setOutputValueClass(outputValueClass);
131    Chain.setReducer(job, klass, inputKeyClass, inputValueClass,
132        outputKeyClass, outputValueClass, reducerConf);
133  }
134
135  /**
136   * Adds a {@link Mapper} class to the chain reducer.
137   * 
138   * <p>
139   * The key and values are passed from one element of the chain to the next, by
140   * value For the added Mapper the configuration given for it,
141   * <code>mapperConf</code>, have precedence over the job's Configuration. This
142   * precedence is in effect when the task is running.
143   * </p>
144   * <p>
145   * IMPORTANT: There is no need to specify the output key/value classes for the
146   * ChainMapper, this is done by the addMapper for the last mapper in the
147   * chain.
148   * </p>
149   * 
150   * @param job
151   *          The job.
152   * @param klass
153   *          the Mapper class to add.
154   * @param inputKeyClass
155   *          mapper input key class.
156   * @param inputValueClass
157   *          mapper input value class.
158   * @param outputKeyClass
159   *          mapper output key class.
160   * @param outputValueClass
161   *          mapper output value class.
162   * @param mapperConf
163   *          a configuration for the Mapper class. It is recommended to use a
164   *          Configuration without default values using the
165   *          <code>Configuration(boolean loadDefaults)</code> constructor with
166   *          FALSE.
167   */
168  public static void addMapper(Job job, Class<? extends Mapper> klass,
169      Class<?> inputKeyClass, Class<?> inputValueClass,
170      Class<?> outputKeyClass, Class<?> outputValueClass,
171      Configuration mapperConf) throws IOException {
172    job.setOutputKeyClass(outputKeyClass);
173    job.setOutputValueClass(outputValueClass);
174    Chain.addMapper(false, job, klass, inputKeyClass, inputValueClass,
175        outputKeyClass, outputValueClass, mapperConf);
176  }
177
178  private Chain chain;
179
180  protected void setup(Context context) {
181    chain = new Chain(false);
182    chain.setup(context.getConfiguration());
183  }
184
185  public void run(Context context) throws IOException, InterruptedException {
186    setup(context);
187
188    // if no reducer is set, just do nothing
189    if (chain.getReducer() == null) {
190      return;
191    }
192    int numMappers = chain.getAllMappers().size();
193    // if there are no mappers in chain, run the reducer
194    if (numMappers == 0) {
195      chain.runReducer(context);
196      return;
197    }
198
199    // add reducer and all mappers with proper context
200    ChainBlockingQueue<Chain.KeyValuePair<?, ?>> inputqueue;
201    ChainBlockingQueue<Chain.KeyValuePair<?, ?>> outputqueue;
202    // add reducer
203    outputqueue = chain.createBlockingQueue();
204    chain.addReducer(context, outputqueue);
205    // add all mappers except last one
206    for (int i = 0; i < numMappers - 1; i++) {
207      inputqueue = outputqueue;
208      outputqueue = chain.createBlockingQueue();
209      chain.addMapper(inputqueue, outputqueue, context, i);
210    }
211    // add last mapper
212    chain.addMapper(outputqueue, context, numMappers - 1);
213
214    // start all threads
215    chain.startAllThreads();
216    
217    // wait for all threads
218    chain.joinAllThreads();
219  }
220}