| /** |
| * 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 java.util.ArrayList; |
| import java.util.List; |
| import java.util.zip.Checksum; |
| |
| import org.apache.commons.logging.Log; |
| import org.apache.commons.logging.LogFactory; |
| import org.apache.hadoop.conf.Configuration; |
| 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.Writable; |
| import org.apache.hadoop.io.WritableUtils; |
| import org.apache.hadoop.mapreduce.Cluster; |
| import org.apache.hadoop.mapreduce.Counter; |
| import org.apache.hadoop.mapreduce.InputFormat; |
| import org.apache.hadoop.mapreduce.InputSplit; |
| import org.apache.hadoop.mapreduce.Job; |
| import org.apache.hadoop.mapreduce.JobContext; |
| import org.apache.hadoop.mapreduce.MRJobConfig; |
| import org.apache.hadoop.mapreduce.Mapper; |
| import org.apache.hadoop.mapreduce.RecordReader; |
| import org.apache.hadoop.mapreduce.TaskAttemptContext; |
| import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; |
| import org.apache.hadoop.util.PureJavaCrc32; |
| import org.apache.hadoop.util.Tool; |
| import org.apache.hadoop.util.ToolRunner; |
| |
| /** |
| * Generate the official GraySort 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) (constant 2 bytes) (32 bytes rowid) |
| * (constant 4 bytes) (48 bytes filler) (constant 4 bytes) |
| * <li>The rowid is the right justified row id as a hex number. |
| * </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 { |
| private static final Log LOG = LogFactory.getLog(TeraSort.class); |
| |
| public static enum Counters {CHECKSUM} |
| |
| public static final String NUM_ROWS = "mapreduce.terasort.num-rows"; |
| /** |
| * An input format that assigns ranges of longs to each mapper. |
| */ |
| static class RangeInputFormat |
| extends InputFormat<LongWritable, NullWritable> { |
| |
| /** |
| * An input split consisting of a range on numbers. |
| */ |
| static class RangeInputSplit extends InputSplit implements Writable { |
| 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 |
| extends RecordReader<LongWritable, NullWritable> { |
| long startRow; |
| long finishedRows; |
| long totalRows; |
| LongWritable key = null; |
| |
| public RangeRecordReader() { |
| } |
| |
| public void initialize(InputSplit split, TaskAttemptContext context) |
| throws IOException, InterruptedException { |
| startRow = ((RangeInputSplit)split).firstRow; |
| finishedRows = 0; |
| totalRows = ((RangeInputSplit)split).rowCount; |
| } |
| |
| public void close() throws IOException { |
| // NOTHING |
| } |
| |
| public LongWritable getCurrentKey() { |
| return key; |
| } |
| |
| public NullWritable getCurrentValue() { |
| return NullWritable.get(); |
| } |
| |
| public float getProgress() throws IOException { |
| return finishedRows / (float) totalRows; |
| } |
| |
| public boolean nextKeyValue() { |
| if (key == null) { |
| key = new LongWritable(); |
| } |
| if (finishedRows < totalRows) { |
| key.set(startRow + finishedRows); |
| finishedRows += 1; |
| return true; |
| } else { |
| return false; |
| } |
| } |
| |
| } |
| |
| public RecordReader<LongWritable, NullWritable> |
| createRecordReader(InputSplit split, TaskAttemptContext context) |
| throws IOException { |
| return new RangeRecordReader(); |
| } |
| |
| /** |
| * Create the desired number of splits, dividing the number of rows |
| * between the mappers. |
| */ |
| public List<InputSplit> getSplits(JobContext job) { |
| long totalRows = getNumberOfRows(job); |
| int numSplits = job.getConfiguration().getInt(MRJobConfig.NUM_MAPS, 1); |
| LOG.info("Generating " + totalRows + " using " + numSplits); |
| List<InputSplit> splits = new ArrayList<InputSplit>(); |
| long currentRow = 0; |
| for(int split = 0; split < numSplits; ++split) { |
| long goal = |
| (long) Math.ceil(totalRows * (double)(split + 1) / numSplits); |
| splits.add(new RangeInputSplit(currentRow, goal - currentRow)); |
| currentRow = goal; |
| } |
| return splits; |
| } |
| |
| } |
| |
| static long getNumberOfRows(JobContext job) { |
| return job.getConfiguration().getLong(NUM_ROWS, 0); |
| } |
| |
| static void setNumberOfRows(Job job, long numRows) { |
| job.getConfiguration().setLong(NUM_ROWS, numRows); |
| } |
| |
| /** |
| * The Mapper class that given a row number, will generate the appropriate |
| * output line. |
| */ |
| public static class SortGenMapper |
| extends Mapper<LongWritable, NullWritable, Text, Text> { |
| |
| private Text key = new Text(); |
| private Text value = new Text(); |
| private Unsigned16 rand = null; |
| private Unsigned16 rowId = null; |
| private Unsigned16 checksum = new Unsigned16(); |
| private Checksum crc32 = new PureJavaCrc32(); |
| private Unsigned16 total = new Unsigned16(); |
| private static final Unsigned16 ONE = new Unsigned16(1); |
| private byte[] buffer = new byte[TeraInputFormat.KEY_LENGTH + |
| TeraInputFormat.VALUE_LENGTH]; |
| private Counter checksumCounter; |
| |
| public void map(LongWritable row, NullWritable ignored, |
| Context context) throws IOException, InterruptedException { |
| if (rand == null) { |
| rowId = new Unsigned16(row.get()); |
| rand = Random16.skipAhead(rowId); |
| checksumCounter = context.getCounter(Counters.CHECKSUM); |
| } |
| Random16.nextRand(rand); |
| GenSort.generateRecord(buffer, rand, rowId); |
| key.set(buffer, 0, TeraInputFormat.KEY_LENGTH); |
| value.set(buffer, TeraInputFormat.KEY_LENGTH, |
| TeraInputFormat.VALUE_LENGTH); |
| context.write(key, value); |
| crc32.reset(); |
| crc32.update(buffer, 0, |
| TeraInputFormat.KEY_LENGTH + TeraInputFormat.VALUE_LENGTH); |
| checksum.set(crc32.getValue()); |
| total.add(checksum); |
| rowId.add(ONE); |
| } |
| |
| @Override |
| public void cleanup(Context context) { |
| if (checksumCounter != null) { |
| checksumCounter.increment(total.getLow8()); |
| } |
| } |
| } |
| |
| private static void usage() throws IOException { |
| System.err.println("teragen <num rows> <output dir>"); |
| } |
| |
| /** |
| * Parse a number that optionally has a postfix that denotes a base. |
| * @param str an string integer with an option base {k,m,b,t}. |
| * @return the expanded value |
| */ |
| private static long parseHumanLong(String str) { |
| char tail = str.charAt(str.length() - 1); |
| long base = 1; |
| switch (tail) { |
| case 't': |
| base *= 1000 * 1000 * 1000 * 1000; |
| break; |
| case 'b': |
| base *= 1000 * 1000 * 1000; |
| break; |
| case 'm': |
| base *= 1000 * 1000; |
| break; |
| case 'k': |
| base *= 1000; |
| break; |
| default: |
| } |
| if (base != 1) { |
| str = str.substring(0, str.length() - 1); |
| } |
| return Long.parseLong(str) * base; |
| } |
| |
| /** |
| * @param args the cli arguments |
| */ |
| public int run(String[] args) |
| throws IOException, InterruptedException, ClassNotFoundException { |
| Job job = Job.getInstance(getConf()); |
| if (args.length != 2) { |
| usage(); |
| return 2; |
| } |
| setNumberOfRows(job, parseHumanLong(args[0])); |
| Path outputDir = new Path(args[1]); |
| if (outputDir.getFileSystem(getConf()).exists(outputDir)) { |
| throw new IOException("Output directory " + outputDir + |
| " already exists."); |
| } |
| FileOutputFormat.setOutputPath(job, outputDir); |
| job.setJobName("TeraGen"); |
| job.setJarByClass(TeraGen.class); |
| job.setMapperClass(SortGenMapper.class); |
| job.setNumReduceTasks(0); |
| job.setOutputKeyClass(Text.class); |
| job.setOutputValueClass(Text.class); |
| job.setInputFormatClass(RangeInputFormat.class); |
| job.setOutputFormatClass(TeraOutputFormat.class); |
| return job.waitForCompletion(true) ? 0 : 1; |
| } |
| |
| public static void main(String[] args) throws Exception { |
| int res = ToolRunner.run(new Configuration(), new TeraGen(), args); |
| System.exit(res); |
| } |
| } |