Example usage for org.apache.hadoop.mapred Partitioner interface-usage

Introduction

In this page you can find the example usage for org.apache.hadoop.mapred Partitioner interface-usage.

Usage

public class FIMPartitioner implements Partitioner<IntWritable, Text> {
    @Override
    public void configure(JobConf job) {
    }

    @Override

From source file SleepJob.java

/**
 * Dummy class for testing MR framefork. Sleeps for a defined period 
 * of time in mapper and reducer. Generates fake input for map / reduce 
 * jobs. Note that generated number of input pairs is in the order 
 * of <code>numMappers * mapSleepTime / 100</code>, so the job uses
 * some disk space.

From source file SleepJobWithArray.java

/**
 * Dummy class for testing MR framefork. Sleeps for a defined period 
 * of time in mapper and reducer. Generates fake input for map / reduce 
 * jobs. Note that generated number of input pairs is in the order 
 * of <code>numMappers * mapSleepTime / 100</code>, so the job uses
 * some disk space.

From source file cascading.tuple.hadoop.CoGroupingPartitioner.java

/** Class GroupingPartitioner is an implementation of {@link org.apache.hadoop.mapred.Partitioner}. */
public class CoGroupingPartitioner implements Partitioner<IndexTuple, Tuple> {
    public int getPartition(IndexTuple key, Tuple value, int numReduceTasks) {
        return (key.getTuple().hashCode() & Integer.MAX_VALUE) % numReduceTasks;
    }

From source file cascading.tuple.hadoop.GroupingPartitioner.java

/** Class GroupingPartitioner is an implementation of {@link Partitioner}. */
public class GroupingPartitioner implements Partitioner<TuplePair, Tuple> {
    public int getPartition(TuplePair key, Tuple value, int numReduceTasks) {
        return (key.getLhs().hashCode() & Integer.MAX_VALUE) % numReduceTasks;
    }

From source file cascading.tuple.hadoop.util.CoGroupingPartitioner.java

/** Class GroupingPartitioner is an implementation of {@link org.apache.hadoop.mapred.Partitioner}. */
public class CoGroupingPartitioner extends HasherPartitioner implements Partitioner<IndexTuple, Tuple> {
    public int getPartition(IndexTuple key, Tuple value, int numReduceTasks) {
        return (hashCode(key.getTuple()) & Integer.MAX_VALUE) % numReduceTasks;
    }

From source file cascading.tuple.hadoop.util.GroupingPartitioner.java

/** Class GroupingPartitioner is an implementation of {@link org.apache.hadoop.mapred.Partitioner}. */
public class GroupingPartitioner extends HasherPartitioner implements Partitioner<Tuple, Tuple> {
    public int getPartition(Tuple key, Tuple value, int numReduceTasks) {
        return (hashCode(key) & Integer.MAX_VALUE) % numReduceTasks;
    }

From source file cascading.tuple.hadoop.util.GroupingSortingPartitioner.java

/** Class GroupingSortingPartitioner is an implementation of {@link Partitioner}. */
public class GroupingSortingPartitioner extends HasherPartitioner implements Partitioner<TuplePair, Tuple> {
    public int getPartition(TuplePair key, Tuple value, int numReduceTasks) {
        return (hashCode(key.getLhs()) & Integer.MAX_VALUE) % numReduceTasks;
    }

From source file colossal.pipe.AvroGroupPartitioner.java

public class AvroGroupPartitioner<K, V> implements Partitioner<AvroKey<K>, AvroValue<V>> {

    private ArrayList<String> groupNames;

    @Override
    public void configure(JobConf conf) {

From source file com.benchmark.mapred.SleepJob.java

/**
 * Dummy class for testing MR framefork. Sleeps for a defined period 
 * of time in mapper and reducer. Generates fake input for map / reduce 
 * jobs. Note that generated number of input pairs is in the order 
 * of <code>numMappers * mapSleepTime / 100</code>, so the job uses
 * some disk space.