/**
* 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; import java.io.IOException;
import java.net.URI;
import java.util.*; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.mapreduce.filecache.DistributedCache;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.mapred.ClusterStatus;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
import org.apache.hadoop.mapreduce.lib.partition.InputSampler;
import org.apache.hadoop.mapreduce.lib.partition.TotalOrderPartitioner;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner; /**
* This is the trivial map/reduce program that does absolutely nothing
* other than use the framework to fragment and sort the input values.
*
* To run: bin/hadoop jar build/hadoop-examples.jar sort
* [-r <i>reduces</i>]
* [-inFormat <i>input format class</i>]
* [-outFormat <i>output format class</i>]
* [-outKey <i>output key class</i>]
* [-outValue <i>output value class</i>]
* [-totalOrder <i>pcnt</i> <i>num samples</i> <i>max splits</i>]
* <i>in-dir</i> <i>out-dir</i>
*/
public class Sort<K,V> extends Configured implements Tool {
public static final String REDUCES_PER_HOST =
"mapreduce.sort.reducesperhost";
private Job job = null; static int printUsage() {
System.out.println("sort [-r <reduces>] " +
"[-inFormat <input format class>] " +
"[-outFormat <output format class>] " +
"[-outKey <output key class>] " +
"[-outValue <output value class>] " +
"[-totalOrder <pcnt> <num samples> <max splits>] " +
"<input> <output>");
ToolRunner.printGenericCommandUsage(System.out);
return 2;
} /**
* The main driver for sort program.
* Invoke this method to submit the map/reduce job.
* @throws IOException When there is communication problems with the
* job tracker.
*/
public int run(String[] args) throws Exception { Configuration conf = getConf();
JobClient client = new JobClient(conf);
ClusterStatus cluster = client.getClusterStatus();
int num_reduces = (int) (cluster.getMaxReduceTasks() * 0.9);
String sort_reduces = conf.get(REDUCES_PER_HOST);
if (sort_reduces != null) {
num_reduces = cluster.getTaskTrackers() *
Integer.parseInt(sort_reduces);
}
Class<? extends InputFormat> inputFormatClass =
SequenceFileInputFormat.class;
Class<? extends OutputFormat> outputFormatClass =
SequenceFileOutputFormat.class;
Class<? extends WritableComparable> outputKeyClass = BytesWritable.class;
Class<? extends Writable> outputValueClass = BytesWritable.class;
List<String> otherArgs = new ArrayList<String>();
InputSampler.Sampler<K,V> sampler = null;
for(int i=0; i < args.length; ++i) {
try {
if ("-r".equals(args[i])) {
num_reduces = Integer.parseInt(args[++i]);
} else if ("-inFormat".equals(args[i])) {
inputFormatClass =
Class.forName(args[++i]).asSubclass(InputFormat.class);
} else if ("-outFormat".equals(args[i])) {
outputFormatClass =
Class.forName(args[++i]).asSubclass(OutputFormat.class);
} else if ("-outKey".equals(args[i])) {
outputKeyClass =
Class.forName(args[++i]).asSubclass(WritableComparable.class);
} else if ("-outValue".equals(args[i])) {
outputValueClass =
Class.forName(args[++i]).asSubclass(Writable.class);
} else if ("-totalOrder".equals(args[i])) {
double pcnt = Double.parseDouble(args[++i]);
int numSamples = Integer.parseInt(args[++i]);
int maxSplits = Integer.parseInt(args[++i]);
if (0 >= maxSplits) maxSplits = Integer.MAX_VALUE;
sampler =
new InputSampler.RandomSampler<K,V>(pcnt, numSamples, maxSplits);
} else {
otherArgs.add(args[i]);
}
} catch (NumberFormatException except) {
System.out.println("ERROR: Integer expected instead of " + args[i]);
return printUsage();
} catch (ArrayIndexOutOfBoundsException except) {
System.out.println("ERROR: Required parameter missing from " +
args[i-1]);
return printUsage(); // exits
}
}
// Set user-supplied (possibly default) job configs
job = Job.getInstance(conf);
job.setJobName("sorter");
job.setJarByClass(Sort.class); job.setMapperClass(Mapper.class);
job.setReducerClass(Reducer.class); job.setNumReduceTasks(num_reduces); job.setInputFormatClass(inputFormatClass);
job.setOutputFormatClass(outputFormatClass); job.setOutputKeyClass(outputKeyClass);
job.setOutputValueClass(outputValueClass); // Make sure there are exactly 2 parameters left.
if (otherArgs.size() != 2) {
System.out.println("ERROR: Wrong number of parameters: " +
otherArgs.size() + " instead of 2.");
return printUsage();
}
FileInputFormat.setInputPaths(job, otherArgs.get(0));
FileOutputFormat.setOutputPath(job, new Path(otherArgs.get(1))); if (sampler != null) {
System.out.println("Sampling input to effect total-order sort...");
job.setPartitionerClass(TotalOrderPartitioner.class);
Path inputDir = FileInputFormat.getInputPaths(job)[0];
inputDir = inputDir.makeQualified(inputDir.getFileSystem(conf));
Path partitionFile = new Path(inputDir, "_sortPartitioning");
TotalOrderPartitioner.setPartitionFile(conf, partitionFile);
InputSampler.<K,V>writePartitionFile(job, sampler);
URI partitionUri = new URI(partitionFile.toString() +
"#" + "_sortPartitioning");
DistributedCache.addCacheFile(partitionUri, conf);
} System.out.println("Running on " +
cluster.getTaskTrackers() +
" nodes to sort from " +
FileInputFormat.getInputPaths(job)[0] + " into " +
FileOutputFormat.getOutputPath(job) +
" with " + num_reduces + " reduces.");
Date startTime = new Date();
System.out.println("Job started: " + startTime);
int ret = job.waitForCompletion(true) ? 0 : 1;
Date end_time = new Date();
System.out.println("Job ended: " + end_time);
System.out.println("The job took " +
(end_time.getTime() - startTime.getTime()) /1000 + " seconds.");
return ret;
} public static void main(String[] args) throws Exception {
int res = ToolRunner.run(new Configuration(), new Sort(), args);
System.exit(res);
} /**
* Get the last job that was run using this instance.
* @return the results of the last job that was run
*/
public Job getResult() {
return job;
}
}
看了源码的第一印象就是，我啥时候写MapReduce也这么规范，这么屌......