Example usage for org.apache.hadoop.mapreduce Reducer subclass-usage

Introduction

In this page you can find the example usage for org.apache.hadoop.mapreduce Reducer subclass-usage.

Usage

From source file mapreducemaxstock.StockPriceReducer.java

/**
 *
 * @author luisf
 */
public class StockPriceReducer extends Reducer<Text, FloatWritable, Text, FloatWritable> {
    public void reduce(Text key, Iterable<FloatWritable> values, Context context)

From source file mapreducesentiment.SentimentReducer.java

/**
 *
 * @author camila
 */
public class SentimentReducer extends
        Reducer<SentimentKeyWritableComparable, LongWritable, SentimentKeyWritableComparable, DoubleWritable> {

From source file minor_MapReduce.SummarizeReducer.java

public class SummarizeReducer extends Reducer<TextArrayWritable, IntWritable, TextArrayWritable, IntWritable> {

    public void reduce(TextArrayWritable key, Iterable<IntWritable> values, Context context)
            throws IOException, InterruptedException {

        int count = 0;

From source file ml.shifu.shifu.core.autotype.AutoTypeDistinctCountReducer.java

/**
 * To merge all mapper {@link HyperLogLogPlus} statistics together according to variable id.
 */
public class AutoTypeDistinctCountReducer extends Reducer<IntWritable, BytesWritable, IntWritable, LongWritable> {

    private LongWritable outputValue = new LongWritable();

From source file ml.shifu.shifu.core.binning.UpdateBinningInfoReducer.java

/**
 * Collect all statistics together in reducer.
 * 
 * <p>
 * The same format with previous output to make sure consistent with output processing functions.
 *

From source file ml.shifu.shifu.core.correlation.CorrelationReducer.java

/**
 * {@link CorrelationReducer} is used to merge all {@link CorrelationWritable}s together to compute pearson correlation
 * between two variables.
 * 
 * @author Zhang David (pengzhang@paypal.com)
 */

From source file ml.shifu.shifu.core.posttrain.FeatureImportanceReducer.java

/**
 * {@link FeatureImportanceReducer} is to aggregate feature importance statistics and compute the top important
 * variables.
 * 
 * @author Zhang David (pengzhang@paypal.com)
 */

From source file ml.shifu.shifu.core.posttrain.PostTrainReducer.java

/**
 * {@link PostTrainReducer} is to aggregate sum of score per each bin of each variable together to compute average score
 * value.
 * 
 * <p>
 * Only 1 reducer is OK, since all mappers are feature-wised and 1 reducer is enough to process all variables.

From source file ml.shifu.shifu.core.varselect.VarSelectReducer.java

/**
 * {@link VarSelectReducer} is used to accumulate all mapper column-MSE values together.
 * 
 * <p>
 * This is a global accumulation, reducer number in current MapReduce job should be set to 1.
 *

From source file msc.fall2015.stock.kmeans.hbase.mapreduce.pwd.SWGReduce.java

/**
 * @author Thilina Gunarathne (tgunarat@cs.indiana.edu)
 */

public class SWGReduce extends Reducer<LongWritable, SWGWritable, LongWritable, SWGWritable> {