org.apache.hadoop.examples.pi.DistSum Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of hadoop-mapreduce-examples Show documentation
Show all versions of hadoop-mapreduce-examples Show documentation
Apache Hadoop MapReduce Examples
/**
* 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.pi;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.File;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.concurrent.Callable;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.examples.pi.math.Summation;
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.Writable;
import org.apache.hadoop.mapreduce.Cluster;
import org.apache.hadoop.mapreduce.ClusterMetrics;
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.Partitioner;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.TaskInputOutputContext;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.net.NetUtils;
import org.apache.hadoop.util.Time;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* The main class for computing sums using map/reduce jobs.
* A sum is partitioned into jobs.
* A job may be executed on the map-side or on the reduce-side.
* A map-side job has multiple maps and zero reducer.
* A reduce-side job has one map and multiple reducers.
* Depending on the clusters status in runtime,
* a mix-type job may be executed on either side.
*/
public final class DistSum extends Configured implements Tool {
private static final Logger LOG = LoggerFactory.getLogger(DistSum.class);
private static final String NAME = DistSum.class.getSimpleName();
private static final String N_PARTS = "mapreduce.pi." + NAME + ".nParts";
/////////////////////////////////////////////////////////////////////////////
/** DistSum job parameters */
static class Parameters {
static final int COUNT = 6;
static final String LIST = " ";
static final String DESCRIPTION =
"\n The number of working threads."
+ "\n The number of jobs per sum."
+ "\n 'm' for map side job, 'r' for reduce side job, 'x' for mix type."
+ "\n The number of parts per job."
+ "\n Remote directory for submitting jobs."
+ "\n Local directory for storing output files.";
/** Number of worker threads */
final int nThreads;
/** Number of jobs */
final int nJobs;
/** Number of parts per job */
final int nParts;
/** The machine used in the computation */
final Machine machine;
/** The remote job directory */
final String remoteDir;
/** The local output directory */
final File localDir;
private Parameters(Machine machine, int nThreads, int nJobs, int nParts,
String remoteDir, File localDir) {
this.machine = machine;
this.nThreads = nThreads;
this.nJobs = nJobs;
this.nParts = nParts;
this.remoteDir = remoteDir;
this.localDir = localDir;
}
/** {@inheritDoc} */
public String toString() {
return "\nnThreads = " + nThreads
+ "\nnJobs = " + nJobs
+ "\nnParts = " + nParts + " (" + machine + ")"
+ "\nremoteDir = " + remoteDir
+ "\nlocalDir = " + localDir;
}
/** Parse parameters */
static Parameters parse(String[] args, int i) {
if (args.length - i < COUNT)
throw new IllegalArgumentException("args.length - i < COUNT = "
+ COUNT + ", args.length="
+ args.length + ", i=" + i + ", args=" + Arrays.asList(args));
final int nThreads = Integer.parseInt(args[i++]);
final int nJobs = Integer.parseInt(args[i++]);
final String type = args[i++];
final int nParts = Integer.parseInt(args[i++]);
final String remoteDir = args[i++];
final File localDir = new File(args[i++]);
if (!"m".equals(type) && !"r".equals(type) && !"x".equals(type)) {
throw new IllegalArgumentException("type=" + type + " is not equal to m, r or x");
} else if (nParts <= 0) {
throw new IllegalArgumentException("nParts = " + nParts + " <= 0");
} else if (nJobs <= 0) {
throw new IllegalArgumentException("nJobs = " + nJobs + " <= 0");
} else if (nThreads <= 0) {
throw new IllegalArgumentException("nThreads = " + nThreads + " <= 0");
}
Util.checkDirectory(localDir);
return new Parameters("m".equals(type)? MapSide.INSTANCE
: "r".equals(type)? ReduceSide.INSTANCE: MixMachine.INSTANCE,
nThreads, nJobs, nParts, remoteDir, localDir);
}
}
/////////////////////////////////////////////////////////////////////////////
/** Abstract machine for job execution. */
public static abstract class Machine {
/** Initialize a job */
abstract void init(Job job) throws IOException;
/** {@inheritDoc} */
public String toString() {return getClass().getSimpleName();}
/** Compute sigma */
static void compute(Summation sigma,
TaskInputOutputContext context
) throws IOException, InterruptedException {
String s;
LOG.info(s = "sigma=" + sigma);
context.setStatus(s);
final long start = Time.monotonicNow();
sigma.compute();
final long duration = Time.monotonicNow() - start;
final TaskResult result = new TaskResult(sigma, duration);
LOG.info(s = "result=" + result);
context.setStatus(s);
context.write(NullWritable.get(), result);
}
/** Split for the summations */
public static final class SummationSplit extends InputSplit implements Writable, Container {
private final static String[] EMPTY = {};
private Summation sigma;
public SummationSplit() {}
private SummationSplit(Summation sigma) {this.sigma = sigma;}
/** {@inheritDoc} */
@Override
public Summation getElement() {return sigma;}
/** {@inheritDoc} */
@Override
public long getLength() {return 1;}
/** {@inheritDoc} */
@Override
public String[] getLocations() {return EMPTY;}
/** {@inheritDoc} */
@Override
public void readFields(DataInput in) throws IOException {
sigma = SummationWritable.read(in);
}
/** {@inheritDoc} */
@Override
public void write(DataOutput out) throws IOException {
new SummationWritable(sigma).write(out);
}
}
/** An abstract InputFormat for the jobs */
public static abstract class AbstractInputFormat extends InputFormat {
/** Specify how to read the records */
@Override
public final RecordReader createRecordReader(
InputSplit generic, TaskAttemptContext context) {
final SummationSplit split = (SummationSplit)generic;
//return a record reader
return new RecordReader() {
boolean done = false;
/** {@inheritDoc} */
@Override
public void initialize(InputSplit split, TaskAttemptContext context) {}
/** {@inheritDoc} */
@Override
public boolean nextKeyValue() {return !done ? done = true : false;}
/** {@inheritDoc} */
@Override
public NullWritable getCurrentKey() {return NullWritable.get();}
/** {@inheritDoc} */
@Override
public SummationWritable getCurrentValue() {return new SummationWritable(split.getElement());}
/** {@inheritDoc} */
@Override
public float getProgress() {return done? 1f: 0f;}
/** {@inheritDoc} */
@Override
public void close() {}
};
}
}
}
/////////////////////////////////////////////////////////////////////////////
/**
* A machine which does computation on the map side.
*/
public static class MapSide extends Machine {
private static final MapSide INSTANCE = new MapSide();
/** {@inheritDoc} */
@Override
public void init(Job job) {
// setup mapper
job.setMapperClass(SummingMapper.class);
job.setMapOutputKeyClass(NullWritable.class);
job.setMapOutputValueClass(TaskResult.class);
// zero reducer
job.setNumReduceTasks(0);
// setup input
job.setInputFormatClass(PartitionInputFormat.class);
}
/** An InputFormat which partitions a summation */
public static class PartitionInputFormat extends AbstractInputFormat {
/** Partitions the summation into parts and then return them as splits */
@Override
public List getSplits(JobContext context) {
//read sigma from conf
final Configuration conf = context.getConfiguration();
final Summation sigma = SummationWritable.read(DistSum.class, conf);
final int nParts = conf.getInt(N_PARTS, 0);
//create splits
final List splits = new ArrayList(nParts);
final Summation[] parts = sigma.partition(nParts);
for(int i = 0; i < parts.length; ++i) {
splits.add(new SummationSplit(parts[i]));
//LOG.info("parts[" + i + "] = " + parts[i]);
}
return splits;
}
}
/** A mapper which computes sums */
public static class SummingMapper extends
Mapper {
@Override
protected void map(NullWritable nw, SummationWritable sigma, final Context context
) throws IOException, InterruptedException {
compute(sigma.getElement(), context);
}
}
}
/////////////////////////////////////////////////////////////////////////////
/**
* A machine which does computation on the reduce side.
*/
public static class ReduceSide extends Machine {
private static final ReduceSide INSTANCE = new ReduceSide();
/** {@inheritDoc} */
@Override
public void init(Job job) {
// setup mapper
job.setMapperClass(PartitionMapper.class);
job.setMapOutputKeyClass(IntWritable.class);
job.setMapOutputValueClass(SummationWritable.class);
// setup partitioner
job.setPartitionerClass(IndexPartitioner.class);
// setup reducer
job.setReducerClass(SummingReducer.class);
job.setOutputKeyClass(NullWritable.class);
job.setOutputValueClass(TaskResult.class);
final Configuration conf = job.getConfiguration();
final int nParts = conf.getInt(N_PARTS, 1);
job.setNumReduceTasks(nParts);
// setup input
job.setInputFormatClass(SummationInputFormat.class);
}
/** An InputFormat which returns a single summation. */
public static class SummationInputFormat extends AbstractInputFormat {
/** @return a list containing a single split of summation */
@Override
public List getSplits(JobContext context) {
//read sigma from conf
final Configuration conf = context.getConfiguration();
final Summation sigma = SummationWritable.read(DistSum.class, conf);
//create splits
final List splits = new ArrayList(1);
splits.add(new SummationSplit(sigma));
return splits;
}
}
/** A Mapper which partitions a summation */
public static class PartitionMapper extends
Mapper {
/** Partitions sigma into parts */
@Override
protected void map(NullWritable nw, SummationWritable sigma, final Context context
) throws IOException, InterruptedException {
final Configuration conf = context.getConfiguration();
final int nParts = conf.getInt(N_PARTS, 0);
final Summation[] parts = sigma.getElement().partition(nParts);
for(int i = 0; i < parts.length; ++i) {
context.write(new IntWritable(i), new SummationWritable(parts[i]));
LOG.info("parts[" + i + "] = " + parts[i]);
}
}
}
/** Use the index for partitioning. */
public static class IndexPartitioner extends Partitioner {
/** Return the index as the partition. */
@Override
public int getPartition(IntWritable index, SummationWritable value, int numPartitions) {
return index.get();
}
}
/** A Reducer which computes sums */
public static class SummingReducer extends
Reducer {
@Override
protected void reduce(IntWritable index, Iterable sums,
Context context) throws IOException, InterruptedException {
LOG.info("index=" + index);
for(SummationWritable sigma : sums)
compute(sigma.getElement(), context);
}
}
}
/////////////////////////////////////////////////////////////////////////////
/**
* A machine which chooses Machine in runtime according to the cluster status
*/
public static class MixMachine extends Machine {
private static final MixMachine INSTANCE = new MixMachine();
private Cluster cluster;
/** {@inheritDoc} */
@Override
public synchronized void init(Job job) throws IOException {
final Configuration conf = job.getConfiguration();
if (cluster == null) {
String jobTrackerStr = conf.get("mapreduce.jobtracker.address", "localhost:8012");
cluster = new Cluster(NetUtils.createSocketAddr(jobTrackerStr), conf);
}
chooseMachine(conf).init(job);
}
/**
* Choose a Machine in runtime according to the cluster status.
*/
private Machine chooseMachine(Configuration conf) throws IOException {
final int parts = conf.getInt(N_PARTS, Integer.MAX_VALUE);
try {
for(;; Thread.sleep(2000)) {
//get cluster status
final ClusterMetrics status = cluster.getClusterStatus();
final int m =
status.getMapSlotCapacity() - status.getOccupiedMapSlots();
final int r =
status.getReduceSlotCapacity() - status.getOccupiedReduceSlots();
if (m >= parts || r >= parts) {
//favor ReduceSide machine
final Machine value = r >= parts?
ReduceSide.INSTANCE: MapSide.INSTANCE;
Util.out.println(" " + this + " is " + value + " (m=" + m + ", r=" + r + ")");
return value;
}
}
} catch (InterruptedException e) {
throw new IOException(e);
}
}
}
/////////////////////////////////////////////////////////////////////////////
private final Util.Timer timer = new Util.Timer(true);
private Parameters parameters;
/** Get Parameters */
Parameters getParameters() {return parameters;}
/** Set Parameters */
void setParameters(Parameters p) {parameters = p;}
/** Create a job */
private Job createJob(String name, Summation sigma) throws IOException {
final Job job = Job.getInstance(getConf(), parameters.remoteDir + "/" +
name);
final Configuration jobconf = job.getConfiguration();
job.setJarByClass(DistSum.class);
jobconf.setInt(N_PARTS, parameters.nParts);
SummationWritable.write(sigma, DistSum.class, jobconf);
// disable task timeout
jobconf.setLong(MRJobConfig.TASK_TIMEOUT, 0);
// do not use speculative execution
jobconf.setBoolean(MRJobConfig.MAP_SPECULATIVE, false);
jobconf.setBoolean(MRJobConfig.REDUCE_SPECULATIVE, false);
return job;
}
/** Start a job to compute sigma */
private void compute(final String name, Summation sigma) throws IOException {
if (sigma.getValue() != null)
throw new IOException("sigma.getValue() != null, sigma=" + sigma);
//setup remote directory
final FileSystem fs = FileSystem.get(getConf());
final Path dir = fs.makeQualified(new Path(parameters.remoteDir, name));
if (!Util.createNonexistingDirectory(fs, dir))
return;
//setup a job
final Job job = createJob(name, sigma);
final Path outdir = new Path(dir, "out");
FileOutputFormat.setOutputPath(job, outdir);
//start a map/reduce job
final String startmessage = "steps/parts = "
+ sigma.E.getSteps() + "/" + parameters.nParts
+ " = " + Util.long2string(sigma.E.getSteps()/parameters.nParts);
Util.runJob(name, job, parameters.machine, startmessage, timer);
final List results = Util.readJobOutputs(fs, outdir);
Util.writeResults(name, results, fs, parameters.remoteDir);
fs.delete(dir, true);
//combine results
final List combined = Util.combine(results);
final PrintWriter out = Util.createWriter(parameters.localDir, name);
try {
for(TaskResult r : combined) {
final String s = taskResult2string(name, r);
out.println(s);
out.flush();
Util.out.println(s);
}
} finally {
out.close();
}
if (combined.size() == 1) {
final Summation s = combined.get(0).getElement();
if (sigma.contains(s) && s.contains(sigma))
sigma.setValue(s.getValue());
}
}
/** Convert a TaskResult to a String */
public static String taskResult2string(String name, TaskResult result) {
return NAME + " " + name + "> " + result;
}
/** Convert a String to a (String, TaskResult) pair */
public static Map.Entry string2TaskResult(final String s) {
// LOG.info("line = " + line);
int j = s.indexOf(NAME);
if (j == 0) {
int i = j + NAME.length() + 1;
j = s.indexOf("> ", i);
final String key = s.substring(i, j);
final TaskResult value = TaskResult.valueOf(s.substring(j + 2));
return new Map.Entry(){
@Override
public String getKey() {return key;}
@Override
public TaskResult getValue() {return value;}
@Override
public TaskResult setValue(TaskResult value) {
throw new UnsupportedOperationException();
}
};
}
return null;
}
/** Callable computation */
class Computation implements Callable {
private final int index;
private final String name;
private final Summation sigma;
Computation(int index, String name, Summation sigma) {
this.index = index;
this.name = name;
this.sigma = sigma;
}
/** @return The job name */
String getJobName() {return String.format("%s.job%03d", name, index);}
/** {@inheritDoc} */
@Override
public String toString() {return getJobName() + sigma;}
/** Start the computation */
@Override
public Computation call() {
if (sigma.getValue() == null)
try {
compute(getJobName(), sigma);
} catch(Exception e) {
Util.out.println("ERROR: Got an exception from " + getJobName());
e.printStackTrace(Util.out);
}
return this;
}
}
/** Partition sigma and execute the computations. */
private Summation execute(String name, Summation sigma) {
final Summation[] summations = sigma.partition(parameters.nJobs);
final List computations = new ArrayList();
for(int i = 0; i < summations.length; i++)
computations.add(new Computation(i, name, summations[i]));
try {
Util.execute(parameters.nThreads, computations);
} catch (Exception e) {
throw new RuntimeException(e);
}
final List combined = Util.combine(Arrays.asList(summations));
return combined.size() == 1? combined.get(0): null;
}
/** {@inheritDoc} */
@Override
public int run(String[] args) throws Exception {
//parse arguments
if (args.length != Parameters.COUNT + 2)
return Util.printUsage(args, getClass().getName()
+ " " + Parameters.LIST
+ "\n The name."
+ "\n The summation."
+ Parameters.DESCRIPTION);
int i = 0;
final String name = args[i++];
final Summation sigma = Summation.valueOf(args[i++]);
setParameters(DistSum.Parameters.parse(args, i));
Util.out.println();
Util.out.println("name = " + name);
Util.out.println("sigma = " + sigma);
Util.out.println(parameters);
Util.out.println();
//run jobs
final Summation result = execute(name, sigma);
if (result.equals(sigma)) {
sigma.setValue(result.getValue());
timer.tick("\n\nDONE\n\nsigma=" + sigma);
return 0;
} else {
timer.tick("\n\nDONE WITH ERROR\n\nresult=" + result);
return 1;
}
}
/** main */
public static void main(String[] args) throws Exception {
System.exit(ToolRunner.run(null, new DistSum(), args));
}
}
© 2015 - 2024 Weber Informatics LLC | Privacy Policy