package com.hadoopilluminated.examples;

/**
 * The example below is taken from org.apache.hadoop.examples It is then
 * commented and modified for the purposes of the book
 */

/**
 * 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.
 */
import java.io.IOException;
import java.util.ArrayList;
import java.util.Map.Entry;
import java.util.StringTokenizer;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.lib.aggregate.ValueAggregatorBaseDescriptor;
import org.apache.hadoop.mapred.lib.aggregate.ValueAggregatorJob;

/**
 * This is an example Aggregated Hadoop Map/Reduce application. It reads the
 * text input files, breaks each line into words and counts them. The output is
 * a locally sorted list of words and the count of how often they occurred.
 *
 * To run: bin/hadoop jar hadoop-examples-*.jar aggregatewordcount <i>in-dir</i>
 * <i>out-dir</i> <i>numOfReducers</i> textinputformat
 *
 */
public class AggregateWordCount {

    public static class WordCountPlugInClass extends ValueAggregatorBaseDescriptor {

        @Override
        public ArrayList<Entry<Text, Text>> generateKeyValPairs(Object key,
                Object val) {
            String countType = LONG_VALUE_SUM;
            ArrayList<Entry<Text, Text>> retv = new ArrayList<Entry<Text, Text>>();
            String line = val.toString();
            StringTokenizer itr = new StringTokenizer(line);
            while (itr.hasMoreTokens()) {
                Entry<Text, Text> e = generateEntry(countType, itr.nextToken(), ONE);
                if (e != null) {
                    retv.add(e);
                }
            }
            return retv;
        }
    }

    /**
     * The main driver for word count map/reduce program. Invoke this method to
     * submit the map/reduce job.
     *
     * @throws IOException When there is communication problems with the job
     * tracker.
     */
    @SuppressWarnings("unchecked")
    public static void main(String[] args) throws IOException {
        JobConf conf = ValueAggregatorJob.createValueAggregatorJob(args, new Class[]{WordCountPlugInClass.class});

        JobClient.runJob(conf);
    }
}
