com.ricemap.spateDB.operations.LineRandomizer.java Source code

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Here is the source code for com.ricemap.spateDB.operations.LineRandomizer.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.
 */
package com.ricemap.spateDB.operations;

import java.io.IOException;
import java.util.Collections;
import java.util.Iterator;
import java.util.Vector;

import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.ClusterStatus;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;

import com.ricemap.spateDB.core.CellInfo;
import com.ricemap.spateDB.mapred.TextOutputFormat;
import com.ricemap.spateDB.util.CommandLineArguments;

/**
 * Calculates number of records in a file depending on its type. If the file
 * is a text file, it counts number of lines. If it's a grid file with no local
 * index, it counts number of non-empty lines. If it's a grid file with RTree
 * index, it counts total number of records stored in all RTrees.
 * @author tonyren, eldawy
 *
 */
public class LineRandomizer {

    private static final String NumOfPartitions = "com.ricemap.spateDB.operations.LineRandomizer";

    public static class Map extends MapReduceBase implements Mapper<CellInfo, Text, IntWritable, Text> {
        /**Total number of partitions to generate*/
        private int totalNumberOfPartitions;

        /**Temporary key used to generate intermediate records*/
        private IntWritable tempKey = new IntWritable();

        @Override
        public void configure(JobConf job) {
            super.configure(job);
            totalNumberOfPartitions = job.getInt(NumOfPartitions, 1);
        }

        public void map(CellInfo cell, Text line, OutputCollector<IntWritable, Text> output, Reporter reporter)
                throws IOException {
            tempKey.set((int) (Math.random() * totalNumberOfPartitions));
            output.collect(tempKey, line);
        }
    }

    public static class Reduce extends MapReduceBase implements Reducer<IntWritable, Text, NullWritable, Text> {

        private NullWritable dummy = NullWritable.get();

        @Override
        public void reduce(IntWritable key, Iterator<Text> values, OutputCollector<NullWritable, Text> output,
                Reporter reporter) throws IOException {
            // Retrieve all lines in this reduce group
            Vector<Text> all_lines = new Vector<Text>();
            while (values.hasNext()) {
                Text t = values.next();
                all_lines.add(new Text(t));
            }

            // Randomize lines within this group
            Collections.shuffle(all_lines);

            // Output lines in the randomized order
            for (Text line : all_lines) {
                output.collect(dummy, line);
            }
        }
    }

    /**
     * Counts the exact number of lines in a file by issuing a MapReduce job
     * that does the thing
     * @param conf
     * @param infs
     * @param infile
     * @return
     * @throws IOException 
     */
    public static void randomizerMapReduce(Path infile, Path outfile, boolean overwrite) throws IOException {
        JobConf job = new JobConf(LineRandomizer.class);

        FileSystem outfs = outfile.getFileSystem(job);

        if (overwrite)
            outfs.delete(outfile, true);

        job.setJobName("Randomizer");
        job.setMapOutputKeyClass(IntWritable.class);
        job.setMapOutputValueClass(Text.class);

        job.setMapperClass(Map.class);
        ClusterStatus clusterStatus = new JobClient(job).getClusterStatus();
        job.setNumMapTasks(clusterStatus.getMaxMapTasks() * 5);

        job.setReducerClass(Reduce.class);
        job.setNumReduceTasks(Math.max(1, clusterStatus.getMaxReduceTasks()));

        FileSystem infs = infile.getFileSystem(job);
        int numOfPartitions = (int) Math
                .ceil((double) infs.getFileStatus(infile).getLen() / infs.getDefaultBlockSize(outfile));
        job.setInt(NumOfPartitions, numOfPartitions);

        job.setInputFormat(TextInputFormat.class);
        TextInputFormat.setInputPaths(job, infile);

        job.setOutputFormat(TextOutputFormat.class);
        TextOutputFormat.setOutputPath(job, outfile);

        // Submit the job
        JobClient.runJob(job);
    }

    /**
     * @param args
     * @throws IOException 
     */
    public static void main(String[] args) throws IOException {
        CommandLineArguments cla = new CommandLineArguments(args);
        Path inputFile = cla.getPaths()[0];
        Path outputFile = cla.getPaths()[1];
        boolean overwrite = cla.isOverwrite();
        randomizerMapReduce(inputFile, outputFile, overwrite);
    }

}