com.daleway.training.hadoop.condprob.ConditionalProbabilityPairsSecondarySort.java Source code

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Here is the source code for com.daleway.training.hadoop.condprob.ConditionalProbabilityPairsSecondarySort.java

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/**
 * 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.
 */
/*
 * I initially thought I had to do the Secondary Sort within the same MapReduce. 
 * The only reason we need the reducer here is for stripping out the composite key. 
 * (Don't think this can be achieved in the mapper)
 */
package com.daleway.training.hadoop.condprob;

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.io.WritableComparator;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/**
 * THis Map Reduce implements the secondary sort to sort by the Value, as Map Reduce sorts only the keys
 * @author vikram
 *
 */
public class ConditionalProbabilityPairsSecondarySort {

    public static class TokenizerMapper extends Mapper<Object, Text, Text, Text> {

        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            StringTokenizer s = new StringTokenizer(value.toString());
            String newKey = s.nextToken();
            String newValue = s.nextToken();
            String log = s.nextToken();
            double val = 0;
            try {
                val = Double.parseDouble(newValue.toString());
            } catch (NumberFormatException e) {
            }
            context.write(new Text(newKey + ":" + val), new Text(val + "\t" + log));
        }
    }

    public static class IntSumReducer extends Reducer<Text, Text, Text, Text> {

        public void reduce(Text key, Iterable<Text> values, Context context)
                throws IOException, InterruptedException {
            for (Text text : values) {
                context.write(new Text(new String(key.getBytes()).split(":")[0]), text);
            }
        }
    }

    public static class KeyComparator extends WritableComparator {

        @Override
        public int compare(WritableComparable w1, WritableComparable w2) {
            Text t1 = (Text) w1;
            Text t2 = (Text) w2;
            String[] s1 = t1.toString().split(":");
            String[] s2 = t2.toString().split(":");
            String s1key = s1[0].toString().substring(0, s1[0].toString().indexOf(","));
            String s2key = s2[0].toString().substring(0, s2[0].toString().indexOf(","));
            int comparison = s1key.compareTo(s2key);
            if (comparison == 0) {
                return new Double(Double.parseDouble(s2[1])).compareTo(new Double(Double.parseDouble(s1[1])));
            }
            return comparison;
        }

        protected KeyComparator() {
            super(Text.class, true);
        }
    }

    public static class GroupComparator extends WritableComparator {

        protected GroupComparator() {
            super(Text.class, true);
        }

        @Override
        public int compare(WritableComparable w1, WritableComparable w2) {
            Text t1 = (Text) w1;
            Text t2 = (Text) w2;
            String s1 = t1.toString().substring(0, t1.toString().indexOf(","));
            String s2 = t2.toString().substring(0, t2.toString().indexOf(","));
            return s1.compareTo(s2);
        }
    }

    public static class ProbDistPartitioner extends Partitioner<Text, Text> {

        @Override
        public int getPartition(Text arg0, Text arg1, int arg2) {
            String x = arg0.toString().substring(0, arg0.toString().indexOf(","));
            System.out.println("going to reducer : " + x.hashCode() % arg2);
            return Math.abs(x.hashCode()) % arg2;
        }

    }

    public static Job createJob(Configuration conf, String inputPath, String outputPath) throws IOException {
        Job job = new Job(conf, "pair wise count");
        job.setJarByClass(ConditionalProbabilityPairsSecondarySort.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setSortComparatorClass(KeyComparator.class);
        job.setGroupingComparatorClass(GroupComparator.class);
        //job.setCombinerClass(IntSumReducer.class);
        job.setPartitionerClass(ProbDistPartitioner.class);
        job.setReducerClass(IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        //Is the output value class for Map or Reduce ?
        job.setOutputValueClass(Text.class);
        //job.setNumReduceTasks(5);
        FileInputFormat.addInputPath(job, new Path(inputPath));
        FileOutputFormat.setOutputPath(job, new Path(outputPath));
        return job;
    }

}