| /** |
| * 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 org.apache.hadoop.examples.terasort; |
| |
| import java.io.DataInput; |
| import java.io.DataOutput; |
| import java.io.IOException; |
| |
| import org.apache.hadoop.conf.Configured; |
| import org.apache.hadoop.fs.Path; |
| import org.apache.hadoop.io.LongWritable; |
| import org.apache.hadoop.io.NullWritable; |
| import org.apache.hadoop.io.Text; |
| import org.apache.hadoop.io.WritableUtils; |
| import org.apache.hadoop.mapred.FileOutputFormat; |
| import org.apache.hadoop.mapred.InputFormat; |
| import org.apache.hadoop.mapred.InputSplit; |
| 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.RecordReader; |
| import org.apache.hadoop.mapred.Reporter; |
| import org.apache.hadoop.util.Tool; |
| import org.apache.hadoop.util.ToolRunner; |
| |
| /** |
| * Generate the official terasort input data set. |
| * The user specifies the number of rows and the output directory and this |
| * class runs a map/reduce program to generate the data. |
| * The format of the data is: |
| * <ul> |
| * <li>(10 bytes key) (10 bytes rowid) (78 bytes filler) \r \n |
| * <li>The keys are random characters from the set ' ' .. '~'. |
| * <li>The rowid is the right justified row id as a int. |
| * <li>The filler consists of 7 runs of 10 characters from 'A' to 'Z'. |
| * </ul> |
| * |
| * <p> |
| * To run the program: |
| * <b>bin/hadoop jar hadoop-examples-*.jar teragen 10000000000 in-dir</b> |
| */ |
| public class TeraGen extends Configured implements Tool { |
| |
| /** |
| * An input format that assigns ranges of longs to each mapper. |
| */ |
| static class RangeInputFormat |
| implements InputFormat<LongWritable, NullWritable> { |
| |
| /** |
| * An input split consisting of a range on numbers. |
| */ |
| static class RangeInputSplit implements InputSplit { |
| long firstRow; |
| long rowCount; |
| |
| public RangeInputSplit() { } |
| |
| public RangeInputSplit(long offset, long length) { |
| firstRow = offset; |
| rowCount = length; |
| } |
| |
| public long getLength() throws IOException { |
| return 0; |
| } |
| |
| public String[] getLocations() throws IOException { |
| return new String[]{}; |
| } |
| |
| public void readFields(DataInput in) throws IOException { |
| firstRow = WritableUtils.readVLong(in); |
| rowCount = WritableUtils.readVLong(in); |
| } |
| |
| public void write(DataOutput out) throws IOException { |
| WritableUtils.writeVLong(out, firstRow); |
| WritableUtils.writeVLong(out, rowCount); |
| } |
| } |
| |
| /** |
| * A record reader that will generate a range of numbers. |
| */ |
| static class RangeRecordReader |
| implements RecordReader<LongWritable, NullWritable> { |
| long startRow; |
| long finishedRows; |
| long totalRows; |
| |
| public RangeRecordReader(RangeInputSplit split) { |
| startRow = split.firstRow; |
| finishedRows = 0; |
| totalRows = split.rowCount; |
| } |
| |
| public void close() throws IOException { |
| // NOTHING |
| } |
| |
| public LongWritable createKey() { |
| return new LongWritable(); |
| } |
| |
| public NullWritable createValue() { |
| return NullWritable.get(); |
| } |
| |
| public long getPos() throws IOException { |
| return finishedRows; |
| } |
| |
| public float getProgress() throws IOException { |
| return finishedRows / (float) totalRows; |
| } |
| |
| public boolean next(LongWritable key, |
| NullWritable value) { |
| if (finishedRows < totalRows) { |
| key.set(startRow + finishedRows); |
| finishedRows += 1; |
| return true; |
| } else { |
| return false; |
| } |
| } |
| |
| } |
| |
| public RecordReader<LongWritable, NullWritable> |
| getRecordReader(InputSplit split, JobConf job, |
| Reporter reporter) throws IOException { |
| return new RangeRecordReader((RangeInputSplit) split); |
| } |
| |
| /** |
| * Create the desired number of splits, dividing the number of rows |
| * between the mappers. |
| */ |
| public InputSplit[] getSplits(JobConf job, |
| int numSplits) { |
| long totalRows = getNumberOfRows(job); |
| long rowsPerSplit = totalRows / numSplits; |
| System.out.println("Generating " + totalRows + " using " + numSplits + |
| " maps with step of " + rowsPerSplit); |
| InputSplit[] splits = new InputSplit[numSplits]; |
| long currentRow = 0; |
| for(int split=0; split < numSplits-1; ++split) { |
| splits[split] = new RangeInputSplit(currentRow, rowsPerSplit); |
| currentRow += rowsPerSplit; |
| } |
| splits[numSplits-1] = new RangeInputSplit(currentRow, |
| totalRows - currentRow); |
| return splits; |
| } |
| |
| } |
| |
| static long getNumberOfRows(JobConf job) { |
| return job.getLong("terasort.num-rows", 0); |
| } |
| |
| static void setNumberOfRows(JobConf job, long numRows) { |
| job.setLong("terasort.num-rows", numRows); |
| } |
| |
| static class RandomGenerator { |
| private long seed = 0; |
| private static final long mask32 = (1l<<32) - 1; |
| /** |
| * The number of iterations separating the precomputed seeds. |
| */ |
| private static final int seedSkip = 128 * 1024 * 1024; |
| /** |
| * The precomputed seed values after every seedSkip iterations. |
| * There should be enough values so that a 2**32 iterations are |
| * covered. |
| */ |
| private static final long[] seeds = new long[]{0L, |
| 4160749568L, |
| 4026531840L, |
| 3892314112L, |
| 3758096384L, |
| 3623878656L, |
| 3489660928L, |
| 3355443200L, |
| 3221225472L, |
| 3087007744L, |
| 2952790016L, |
| 2818572288L, |
| 2684354560L, |
| 2550136832L, |
| 2415919104L, |
| 2281701376L, |
| 2147483648L, |
| 2013265920L, |
| 1879048192L, |
| 1744830464L, |
| 1610612736L, |
| 1476395008L, |
| 1342177280L, |
| 1207959552L, |
| 1073741824L, |
| 939524096L, |
| 805306368L, |
| 671088640L, |
| 536870912L, |
| 402653184L, |
| 268435456L, |
| 134217728L, |
| }; |
| |
| /** |
| * Start the random number generator on the given iteration. |
| * @param initalIteration the iteration number to start on |
| */ |
| RandomGenerator(long initalIteration) { |
| int baseIndex = (int) ((initalIteration & mask32) / seedSkip); |
| seed = seeds[baseIndex]; |
| for(int i=0; i < initalIteration % seedSkip; ++i) { |
| next(); |
| } |
| } |
| |
| RandomGenerator() { |
| this(0); |
| } |
| |
| long next() { |
| seed = (seed * 3141592621l + 663896637) & mask32; |
| return seed; |
| } |
| } |
| |
| /** |
| * The Mapper class that given a row number, will generate the appropriate |
| * output line. |
| */ |
| public static class SortGenMapper extends MapReduceBase |
| implements Mapper<LongWritable, NullWritable, Text, Text> { |
| |
| private Text key = new Text(); |
| private Text value = new Text(); |
| private RandomGenerator rand; |
| private byte[] keyBytes = new byte[12]; |
| private byte[] spaces = " ".getBytes(); |
| private byte[][] filler = new byte[26][]; |
| { |
| for(int i=0; i < 26; ++i) { |
| filler[i] = new byte[10]; |
| for(int j=0; j<10; ++j) { |
| filler[i][j] = (byte) ('A' + i); |
| } |
| } |
| } |
| |
| /** |
| * Add a random key to the text |
| * @param rowId |
| */ |
| private void addKey() { |
| for(int i=0; i<3; i++) { |
| long temp = rand.next() / 52; |
| keyBytes[3 + 4*i] = (byte) (' ' + (temp % 95)); |
| temp /= 95; |
| keyBytes[2 + 4*i] = (byte) (' ' + (temp % 95)); |
| temp /= 95; |
| keyBytes[1 + 4*i] = (byte) (' ' + (temp % 95)); |
| temp /= 95; |
| keyBytes[4*i] = (byte) (' ' + (temp % 95)); |
| } |
| key.set(keyBytes, 0, 10); |
| } |
| |
| /** |
| * Add the rowid to the row. |
| * @param rowId |
| */ |
| private void addRowId(long rowId) { |
| byte[] rowid = Integer.toString((int) rowId).getBytes(); |
| int padSpace = 10 - rowid.length; |
| if (padSpace > 0) { |
| value.append(spaces, 0, 10 - rowid.length); |
| } |
| value.append(rowid, 0, Math.min(rowid.length, 10)); |
| } |
| |
| /** |
| * Add the required filler bytes. Each row consists of 7 blocks of |
| * 10 characters and 1 block of 8 characters. |
| * @param rowId the current row number |
| */ |
| private void addFiller(long rowId) { |
| int base = (int) ((rowId * 8) % 26); |
| for(int i=0; i<7; ++i) { |
| value.append(filler[(base+i) % 26], 0, 10); |
| } |
| value.append(filler[(base+7) % 26], 0, 8); |
| } |
| |
| public void map(LongWritable row, NullWritable ignored, |
| OutputCollector<Text, Text> output, |
| Reporter reporter) throws IOException { |
| long rowId = row.get(); |
| if (rand == null) { |
| // we use 3 random numbers per a row |
| rand = new RandomGenerator(rowId*3); |
| } |
| addKey(); |
| value.clear(); |
| addRowId(rowId); |
| addFiller(rowId); |
| output.collect(key, value); |
| } |
| |
| } |
| |
| /** |
| * @param args the cli arguments |
| */ |
| public int run(String[] args) throws IOException { |
| JobConf job = (JobConf) getConf(); |
| setNumberOfRows(job, Long.parseLong(args[0])); |
| FileOutputFormat.setOutputPath(job, new Path(args[1])); |
| job.setJobName("TeraGen"); |
| job.setJarByClass(TeraGen.class); |
| job.setMapperClass(SortGenMapper.class); |
| job.setNumReduceTasks(0); |
| job.setOutputKeyClass(Text.class); |
| job.setOutputValueClass(Text.class); |
| job.setInputFormat(RangeInputFormat.class); |
| job.setOutputFormat(TeraOutputFormat.class); |
| JobClient.runJob(job); |
| return 0; |
| } |
| |
| public static void main(String[] args) throws Exception { |
| int res = ToolRunner.run(new JobConf(), new TeraGen(), args); |
| System.exit(res); |
| } |
| |
| } |