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The examples module provides glue code implementation for extracting common phrases, key word distributions and more from tweets stored on HDFS/HBase. It builds on Mahout for more sophisticated analysis.

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/**
 * Copyright (C) 2010, 2011 Neofonie GmbH
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of 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 eu.dicodeproject.analysis.generic;

import java.io.IOException;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

/**
 * Sums up counts for words and writes the counts *-1 to HDFS.
 The counts are multiplied with -1 to get a descending sort
 * order.
 */

public class GenericReducer extends Reducer {

  private IntWritable totalCount = new IntWritable();

  public void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException {

    int wordCount = 0;
    for (IntWritable val : values) {
      wordCount += val.get();
    }
    
    totalCount.set(-1 * wordCount);
    context.write(totalCount, key);
  }
}