/**
* 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.DataInputStream;
import java.io.IOException;
import java.io.PrintStream;
import java.net.URI;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.conf.Configurable;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.MRJobConfig;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
/**
* Generates the sampled split points, launches the job, and waits for it to
* finish.
* <p>
* To run the program:
* <b>bin/hadoop jar hadoop-*-examples.jar terasort in-dir out-dir</b>
*/
public class TeraSort extends Configured implements Tool {
private static final Log LOG = LogFactory.getLog(TeraSort.class);
static String SIMPLE_PARTITIONER = "mapreduce.terasort.simplepartitioner";
static String OUTPUT_REPLICATION = "mapreduce.terasort.output.replication";
/**
* A partitioner that splits text keys into roughly equal partitions
* in a global sorted order.
*/
static class TotalOrderPartitioner extends Partitioner<Text,Text>
implements Configurable {
private TrieNode trie;
private Text[] splitPoints;
private Configuration conf;
/**
* A generic trie node
*/
static abstract class TrieNode {
private int level;
TrieNode(int level) {
this.level = level;
}
abstract int findPartition(Text key);
abstract void print(PrintStream strm) throws IOException;
int getLevel() {
return level;
}
}
/**
* An inner trie node that contains 256 children based on the next
* character.
*/
static class InnerTrieNode extends TrieNode {
private TrieNode[] child = new TrieNode[256];
InnerTrieNode(int level) {
super(level);
}
int findPartition(Text key) {
int level = getLevel();
if (key.getLength() <= level) {
return child[0].findPartition(key);
}
return child[key.getBytes()[level] & 0xff].findPartition(key);
}
void setChild(int idx, TrieNode child) {
this.child[idx] = child;
}
void print(PrintStream strm) throws IOException {
for(int ch=0; ch < 256; ++ch) {
for(int i = 0; i < 2*getLevel(); ++i) {
strm.print(' ');
}
strm.print(ch);
strm.println(" ->");
if (child[ch] != null) {
child[ch].print(strm);
}
}
}
}
/**
* A leaf trie node that does string compares to figure out where the given
* key belongs between lower..upper.
*/
static class LeafTrieNode extends TrieNode {
int lower;
int upper;
Text[] splitPoints;
LeafTrieNode(int level, Text[] splitPoints, int lower, int upper) {
super(level);
this.splitPoints = splitPoints;
this.lower = lower;
this.upper = upper;
}
int findPartition(Text key) {
for(int i=lower; i<upper; ++i) {
if (splitPoints[i].compareTo(key) > 0) {
return i;
}
}
return upper;
}
void print(PrintStream strm) throws IOException {
for(int i = 0; i < 2*getLevel(); ++i) {
strm.print(' ');
}
strm.print(lower);
strm.print(", ");
strm.println(upper);
}
}
/**
* Read the cut points from the given sequence file.
* @param fs the file system
* @param p the path to read
* @param job the job config
* @return the strings to split the partitions on
* @throws IOException
*/
private static Text[] readPartitions(FileSystem fs, Path p,
Configuration conf) throws IOException {
int reduces = conf.getInt(MRJobConfig.NUM_REDUCES, 1);
Text[] result = new Text[reduces - 1];
DataInputStream reader = fs.open(p);
for(int i=0; i < reduces - 1; ++i) {
result[i] = new Text();
result[i].readFields(reader);
}
reader.close();
return result;
}
/**
* Given a sorted set of cut points, build a trie that will find the correct
* partition quickly.
* @param splits the list of cut points
* @param lower the lower bound of partitions 0..numPartitions-1
* @param upper the upper bound of partitions 0..numPartitions-1
* @param prefix the prefix that we have already checked against
* @param maxDepth the maximum depth we will build a trie for
* @return the trie node that will divide the splits correctly
*/
private static TrieNode buildTrie(Text[] splits, int lower, int upper,
Text prefix, int maxDepth) {
int depth = prefix.getLength();
if (depth >= maxDepth || lower == upper) {
return new LeafTrieNode(depth, splits, lower, upper);
}
InnerTrieNode result = new InnerTrieNode(depth);
Text trial = new Text(prefix);
// append an extra byte on to the prefix
trial.append(new byte[1], 0, 1);
int currentBound = lower;
for(int ch = 0; ch < 255; ++ch) {
trial.getBytes()[depth] = (byte) (ch + 1);
lower = currentBound;
while (currentBound < upper) {
if (splits[currentBound].compareTo(trial) >= 0) {
break;
}
currentBound += 1;
}
trial.getBytes()[depth] = (byte) ch;
result.child[ch] = buildTrie(splits, lower, currentBound, trial,
maxDepth);
}
// pick up the rest
trial.getBytes()[depth] = (byte) 255;
result.child[255] = buildTrie(splits, currentBound, upper, trial,
maxDepth);
return result;
}
public void setConf(Configuration conf) {
try {
FileSystem fs = FileSystem.getLocal(conf);
this.conf = conf;
Path partFile = new Path(TeraInputFormat.PARTITION_FILENAME);
splitPoints = readPartitions(fs, partFile, conf);
trie = buildTrie(splitPoints, 0, splitPoints.length, new Text(), 2);
} catch (IOException ie) {
throw new IllegalArgumentException("can't read paritions file", ie);
}
}
public Configuration getConf() {
return conf;
}
public TotalOrderPartitioner() {
}
public int getPartition(Text key, Text value, int numPartitions) {
return trie.findPartition(key);
}
}
/**
* A total order partitioner that assigns keys based on their first
* PREFIX_LENGTH bytes, assuming a flat distribution.
*/
public static class SimplePartitioner extends Partitioner<Text, Text>
implements Configurable {
int prefixesPerReduce;
private static final int PREFIX_LENGTH = 3;
private Configuration conf = null;
public void setConf(Configuration conf) {
this.conf = conf;
prefixesPerReduce = (int) Math.ceil((1 << (8 * PREFIX_LENGTH)) /
(float) conf.getInt(MRJobConfig.NUM_REDUCES, 1));
}
public Configuration getConf() {
return conf;
}
@Override
public int getPartition(Text key, Text value, int numPartitions) {
byte[] bytes = key.getBytes();
int len = Math.min(PREFIX_LENGTH, key.getLength());
int prefix = 0;
for(int i=0; i < len; ++i) {
prefix = (prefix << 8) | (0xff & bytes[i]);
}
return prefix / prefixesPerReduce;
}
}
public static boolean getUseSimplePartitioner(JobContext job) {
return job.getConfiguration().getBoolean(SIMPLE_PARTITIONER, false);
}
public static void setUseSimplePartitioner(Job job, boolean value) {
job.getConfiguration().setBoolean(SIMPLE_PARTITIONER, value);
}
public static int getOutputReplication(JobContext job) {
return job.getConfiguration().getInt(OUTPUT_REPLICATION, 1);
}
public static void setOutputReplication(Job job, int value) {
job.getConfiguration().setInt(OUTPUT_REPLICATION, value);
}
public int run(String[] args) throws Exception {
LOG.info("starting");
Job job = Job.getInstance(getConf());
Path inputDir = new Path(args[0]);
Path outputDir = new Path(args[1]);
boolean useSimplePartitioner = getUseSimplePartitioner(job);
TeraInputFormat.setInputPaths(job, inputDir);
FileOutputFormat.setOutputPath(job, outputDir);
job.setJobName("TeraSort");
job.setJarByClass(TeraSort.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(Text.class);
job.setInputFormatClass(TeraInputFormat.class);
job.setOutputFormatClass(TeraOutputFormat.class);
if (useSimplePartitioner) {
job.setPartitionerClass(SimplePartitioner.class);
} else {
long start = System.currentTimeMillis();
Path partitionFile = new Path(outputDir,
TeraInputFormat.PARTITION_FILENAME);
URI partitionUri = new URI(partitionFile.toString() +
"#" + TeraInputFormat.PARTITION_FILENAME);
try {
TeraInputFormat.writePartitionFile(job, partitionFile);
} catch (Throwable e) {
LOG.error(e.getMessage());
return -1;
}
job.addCacheFile(partitionUri);
long end = System.currentTimeMillis();
System.out.println("Spent " + (end - start) + "ms computing partitions.");
job.setPartitionerClass(TotalOrderPartitioner.class);
}
job.getConfiguration().setInt("dfs.replication", getOutputReplication(job));
TeraOutputFormat.setFinalSync(job, true);
int ret = job.waitForCompletion(true) ? 0 : 1;
LOG.info("done");
return ret;
}
/**
* @param args
*/
public static void main(String[] args) throws Exception {
int res = ToolRunner.run(new Configuration(), new TeraSort(), args);
System.exit(res);
}
}