com.neu.cs6240.AvgTimeToAnswer.AvgTimeToAnsPerHashTag.java Source code

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Here is the source code for com.neu.cs6240.AvgTimeToAnswer.AvgTimeToAnsPerHashTag.java

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/**
 *  Licensed 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.
 */

package com.neu.cs6240.AvgTimeToAnswer;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
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;
import org.apache.hadoop.util.GenericOptionsParser;

import au.com.bytecode.opencsv.CSVParser;

public class AvgTimeToAnsPerHashTag {

    private static final int TAGS = 1;
    private static final int MINS = 2;
    private static final String HASH_SEPERATOR = "=";

    public static class AvgTimeToAnsPerHashTagMapper extends Mapper<Object, Text, Text, IntWritable> {
        // initialize CSVParser as comma separated values
        private CSVParser csvParser = new CSVParser(',', '"');

        public void map(Object offset, Text line, Context context) throws IOException, InterruptedException {

            // Parse the input line
            String[] parsedData = this.csvParser.parseLine(line.toString());
            IntWritable value = null;
            Text key = null;

            if (!isValid(parsedData)) {
                return;
            }

            // Just in case some minutes values cannot be parsed
            try {
                int minutes = Integer.parseInt(parsedData[MINS]);
                value = new IntWritable(minutes);
            } catch (NumberFormatException ex) {
                // Ignore the record 
                return;
            }

            String[] hashTags = parsedData[TAGS].replaceAll("><", HASH_SEPERATOR).replaceAll("<", "")
                    .replaceAll(">", "").split(HASH_SEPERATOR);

            for (String hashTag : hashTags) {
                key = new Text(hashTag);
                context.write(key, value);
            }
        }

        /**
         * remove invalid entries
         * 
         * @param parsedData
         * @return
         */
        private boolean isValid(String[] parsedData) {
            // We must have TAGS & MINS
            if (parsedData[TAGS].isEmpty() || parsedData[MINS].isEmpty()) {
                return false;
            }
            return true;
        }
    }

    public static class AvgTimeToAnsPerHashTagReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

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

            int totalMinutes = 0;
            int totalEntries = 0;

            for (IntWritable value : values) {
                totalEntries++;
                totalMinutes += value.get();
            }

            context.write(key, new IntWritable(totalMinutes / totalEntries));
        }
    }

    public static class AvgTimeToAnsPerHashTagPartitioner extends Partitioner<Text, IntWritable> {
        /**
         * Based on the configured number of reducer, this will partition the
         * data approximately evenly based on number of unique hash Tags
         */
        @Override
        public int getPartition(Text key, IntWritable value, int numPartitions) {
            // multiply by 127 to perform some mixing
            return Math.abs(key.hashCode() * 127) % numPartitions;
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        conf.set("mapred.textoutputformat.separator", ",");
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
        if (otherArgs.length != 2) {
            System.err.println("Usage: AvgTimeToAnsPerHashTag <in> <out>");
            System.exit(2);
        }
        Job job = new Job(conf, "AvgTimeToAnsPerHashTag");
        job.setJarByClass(AvgTimeToAnsPerHashTag.class);
        job.setMapperClass(AvgTimeToAnsPerHashTagMapper.class);
        job.setReducerClass(AvgTimeToAnsPerHashTagReducer.class);
        job.setCombinerClass(AvgTimeToAnsPerHashTagReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        job.setPartitionerClass(AvgTimeToAnsPerHashTagPartitioner.class);
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}