src/java/org/apache/hadoop/mapred/MapTask.java

/**
 * 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.mapred;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.DataOutputStream;
import java.io.IOException;
import java.io.OutputStream;
import java.lang.reflect.Constructor;
import java.lang.reflect.InvocationTargetException;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.ReentrantLock;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocalDirAllocator;
import org.apache.hadoop.fs.LocalFileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.BytesWritable;
import org.apache.hadoop.io.DataInputBuffer;
import org.apache.hadoop.io.RawComparator;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.SequenceFile.CompressionType;
import org.apache.hadoop.io.compress.CompressionCodec;
import org.apache.hadoop.io.compress.DefaultCodec;
import org.apache.hadoop.io.serializer.Deserializer;
import org.apache.hadoop.io.serializer.SerializationFactory;
import org.apache.hadoop.io.serializer.Serializer;
import org.apache.hadoop.mapred.IFile.Writer;
import org.apache.hadoop.mapred.Merger.Segment;
import org.apache.hadoop.mapred.SortedRanges.SkipRangeIterator;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.map.WrappedMapper;
import org.apache.hadoop.mapreduce.task.MapContextImpl;
import org.apache.hadoop.mapreduce.MRConfig;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.mapreduce.TaskCounter;
import org.apache.hadoop.util.IndexedSortable;
import org.apache.hadoop.util.IndexedSorter;
import org.apache.hadoop.util.Progress;
import org.apache.hadoop.util.QuickSort;
import org.apache.hadoop.util.ReflectionUtils;
import org.apache.hadoop.util.StringUtils;

/** A Map task. */
class MapTask extends Task {
  /**
   * The size of each record in the index file for the map-outputs.
   */
  public static final int MAP_OUTPUT_INDEX_RECORD_LENGTH = 24;

  private BytesWritable split = new BytesWritable();
  private String splitClass;
  private final static int APPROX_HEADER_LENGTH = 150;

  private static final Log LOG = LogFactory.getLog(MapTask.class.getName());

  private Progress mapPhase;
  private Progress sortPhase;
  
  
  {   // set phase for this task
    setPhase(TaskStatus.Phase.MAP); 
    getProgress().setStatus("map");
  }

  public MapTask() {
    super();
  }

  public MapTask(String jobFile, TaskAttemptID taskId, 
                 int partition, String splitClass, BytesWritable split,
                 int numSlotsRequired) {
    super(jobFile, taskId, partition, numSlotsRequired);
    this.splitClass = splitClass;
    this.split = split;
  }

  @Override
  public boolean isMapTask() {
    return true;
  }

  @Override
  public void localizeConfiguration(JobConf conf)
      throws IOException {
    super.localizeConfiguration(conf);
    // split.dta file is used only by IsolationRunner.
    // Write the split file to the local disk if it is a normal map task (not a
    // job-setup or a job-cleanup task) and if the user wishes to run
    // IsolationRunner either by setting keep.failed.tasks.files to true or by
    // using keep.tasks.files.pattern
    if (isMapOrReduce()
        && (conf.getKeepTaskFilesPattern() != null || conf
            .getKeepFailedTaskFiles())) {
      Path localSplit =
          new LocalDirAllocator(MRConfig.LOCAL_DIR).getLocalPathForWrite(
              TaskTracker.getLocalSplitFile(conf.getUser(), getJobID()
                  .toString(), getTaskID().toString()), conf);
      LOG.debug("Writing local split to " + localSplit);
      DataOutputStream out = FileSystem.getLocal(conf).create(localSplit);
      Text.writeString(out, splitClass);
      split.write(out);
      out.close();
    }
  }
  
  @Override
  public TaskRunner createRunner(TaskTracker tracker, 
      TaskTracker.TaskInProgress tip) {
    return new MapTaskRunner(tip, tracker, this.conf);
  }

  @Override
  public void write(DataOutput out) throws IOException {
    super.write(out);
    if (isMapOrReduce()) {
      Text.writeString(out, splitClass);
      split.write(out);
      split = null;
    }
  }
  
  @Override
  public void readFields(DataInput in) throws IOException {
    super.readFields(in);
    if (isMapOrReduce()) {
      splitClass = Text.readString(in);
      split.readFields(in);
    }
  }

  /**
   * This class wraps the user's record reader to update the counters and progress
   * as records are read.
   * @param <K>
   * @param <V>
   */
  class TrackedRecordReader<K, V> 
      implements RecordReader<K,V> {
    private RecordReader<K,V> rawIn;
    private Counters.Counter inputByteCounter;
    private Counters.Counter inputRecordCounter;
    private TaskReporter reporter;
    private long beforePos = -1;
    private long afterPos = -1;
    
    TrackedRecordReader(RecordReader<K,V> raw, TaskReporter reporter) 
      throws IOException{
      rawIn = raw;
      inputRecordCounter = reporter.getCounter(TaskCounter.MAP_INPUT_RECORDS);
      inputByteCounter = reporter.getCounter(
                           FileInputFormat.COUNTER_GROUP,
                           FileInputFormat.BYTES_READ);
      this.reporter = reporter;
    }

    public K createKey() {
      return rawIn.createKey();
    }
      
    public V createValue() {
      return rawIn.createValue();
    }
     
    public synchronized boolean next(K key, V value)
    throws IOException {
      boolean ret = moveToNext(key, value);
      if (ret) {
        incrCounters();
      }
      return ret;
    }
    
    protected void incrCounters() {
      inputRecordCounter.increment(1);
      inputByteCounter.increment(afterPos - beforePos);
    }
     
    protected synchronized boolean moveToNext(K key, V value)
      throws IOException {
      beforePos = getPos();
      boolean ret = rawIn.next(key, value);
      afterPos = getPos();
      reporter.setProgress(getProgress());
      return ret;
    }
    
    public long getPos() throws IOException { return rawIn.getPos(); }
    public void close() throws IOException { rawIn.close(); }
    public float getProgress() throws IOException {
      return rawIn.getProgress();
    }
    TaskReporter getTaskReporter() {
      return reporter;
    }
  }

  /**
   * This class skips the records based on the failed ranges from previous 
   * attempts.
   */
  class SkippingRecordReader<K, V> extends TrackedRecordReader<K,V> {
    private SkipRangeIterator skipIt;
    private SequenceFile.Writer skipWriter;
    private boolean toWriteSkipRecs;
    private TaskUmbilicalProtocol umbilical;
    private Counters.Counter skipRecCounter;
    private long recIndex = -1;
    
    SkippingRecordReader(RecordReader<K,V> raw, TaskUmbilicalProtocol umbilical,
                         TaskReporter reporter) throws IOException{
      super(raw, reporter);
      this.umbilical = umbilical;
      this.skipRecCounter = reporter.getCounter(TaskCounter.MAP_SKIPPED_RECORDS);
      this.toWriteSkipRecs = toWriteSkipRecs() &&  
        SkipBadRecords.getSkipOutputPath(conf)!=null;
      skipIt = getSkipRanges().skipRangeIterator();
    }
    
    public synchronized boolean next(K key, V value)
    throws IOException {
      if(!skipIt.hasNext()) {
        LOG.warn("Further records got skipped.");
        return false;
      }
      boolean ret = moveToNext(key, value);
      long nextRecIndex = skipIt.next();
      long skip = 0;
      while(recIndex<nextRecIndex && ret) {
        if(toWriteSkipRecs) {
          writeSkippedRec(key, value);
        }
      	ret = moveToNext(key, value);
        skip++;
      }
      //close the skip writer once all the ranges are skipped
      if(skip>0 && skipIt.skippedAllRanges() && skipWriter!=null) {
        skipWriter.close();
      }
      skipRecCounter.increment(skip);
      reportNextRecordRange(umbilical, recIndex);
      if (ret) {
        incrCounters();
      }
      return ret;
    }
    
    protected synchronized boolean moveToNext(K key, V value)
    throws IOException {
	    recIndex++;
      return super.moveToNext(key, value);
    }
    
    @SuppressWarnings("unchecked")
    private void writeSkippedRec(K key, V value) throws IOException{
      if(skipWriter==null) {
        Path skipDir = SkipBadRecords.getSkipOutputPath(conf);
        Path skipFile = new Path(skipDir, getTaskID().toString());
        skipWriter = 
          SequenceFile.createWriter(
              skipFile.getFileSystem(conf), conf, skipFile,
              (Class<K>) createKey().getClass(),
              (Class<V>) createValue().getClass(), 
              CompressionType.BLOCK, getTaskReporter());
      }
      skipWriter.append(key, value);
    }
  }

  @Override
  public void run(final JobConf job, final TaskUmbilicalProtocol umbilical)
    throws IOException, ClassNotFoundException, InterruptedException {
    this.umbilical = umbilical;

    if (isMapTask()) {
      mapPhase = getProgress().addPhase("map", 0.667f);
      sortPhase  = getProgress().addPhase("sort", 0.333f);
    }
    TaskReporter reporter = startReporter(umbilical);
 
    boolean useNewApi = job.getUseNewMapper();
    initialize(job, getJobID(), reporter, useNewApi);

    // check if it is a cleanupJobTask
    if (jobCleanup) {
      runJobCleanupTask(umbilical, reporter);
      return;
    }
    if (jobSetup) {
      runJobSetupTask(umbilical, reporter);
      return;
    }
    if (taskCleanup) {
      runTaskCleanupTask(umbilical, reporter);
      return;
    }

    if (useNewApi) {
      runNewMapper(job, split, umbilical, reporter);
    } else {
      runOldMapper(job, split, umbilical, reporter);
    }
    done(umbilical, reporter);
  }

  @SuppressWarnings("unchecked")
  private <INKEY,INVALUE,OUTKEY,OUTVALUE>
  void runOldMapper(final JobConf job,
                    final BytesWritable rawSplit,
                    final TaskUmbilicalProtocol umbilical,
                    TaskReporter reporter
                    ) throws IOException, InterruptedException,
                             ClassNotFoundException {
    InputSplit inputSplit = null;
    // reinstantiate the split
    try {
      inputSplit = (InputSplit) 
        ReflectionUtils.newInstance(job.getClassByName(splitClass), job);
    } catch (ClassNotFoundException exp) {
      IOException wrap = new IOException("Split class " + splitClass + 
                                         " not found");
      wrap.initCause(exp);
      throw wrap;
    }
    DataInputBuffer splitBuffer = new DataInputBuffer();
    splitBuffer.reset(split.getBytes(), 0, split.getLength());
    inputSplit.readFields(splitBuffer);
    
    updateJobWithSplit(job, inputSplit);
    reporter.setInputSplit(inputSplit);

    RecordReader<INKEY,INVALUE> rawIn =                  // open input
      job.getInputFormat().getRecordReader(inputSplit, job, reporter);
    RecordReader<INKEY,INVALUE> in = isSkipping() ? 
        new SkippingRecordReader<INKEY,INVALUE>(rawIn, umbilical, reporter) :
        new TrackedRecordReader<INKEY,INVALUE>(rawIn, reporter);
    job.setBoolean(JobContext.SKIP_RECORDS, isSkipping());


    int numReduceTasks = conf.getNumReduceTasks();
    LOG.info("numReduceTasks: " + numReduceTasks);
    MapOutputCollector collector = null;
    if (numReduceTasks > 0) {
      collector = new MapOutputBuffer(umbilical, job, reporter);
    } else { 
      collector = new DirectMapOutputCollector(umbilical, job, reporter);
    }
    MapRunnable<INKEY,INVALUE,OUTKEY,OUTVALUE> runner =
      ReflectionUtils.newInstance(job.getMapRunnerClass(), job);

    try {
      runner.run(in, new OldOutputCollector(collector, conf), reporter);
      mapPhase.complete();
      setPhase(TaskStatus.Phase.SORT);
      statusUpdate(umbilical);
      collector.flush();
    } finally {
      //close
      in.close();                               // close input
      collector.close();
    }
  }

  /**
   * Update the job with details about the file split
   * @param job the job configuration to update
   * @param inputSplit the file split
   */
  private void updateJobWithSplit(final JobConf job, InputSplit inputSplit) {
    if (inputSplit instanceof FileSplit) {
      FileSplit fileSplit = (FileSplit) inputSplit;
      job.set(JobContext.MAP_INPUT_FILE, fileSplit.getPath().toString());
      job.setLong(JobContext.MAP_INPUT_START, fileSplit.getStart());
      job.setLong(JobContext.MAP_INPUT_PATH, fileSplit.getLength());
    }
  }

  static class NewTrackingRecordReader<K,V> 
    extends org.apache.hadoop.mapreduce.RecordReader<K,V> {
    private final org.apache.hadoop.mapreduce.RecordReader<K,V> real;
    private final org.apache.hadoop.mapreduce.Counter inputRecordCounter;
    private final TaskReporter reporter;
    
    NewTrackingRecordReader(org.apache.hadoop.mapreduce.RecordReader<K,V> real,
                            TaskReporter reporter) {
      this.real = real;
      this.reporter = reporter;
      this.inputRecordCounter = reporter.getCounter(TaskCounter.MAP_INPUT_RECORDS);
    }

    @Override
    public void close() throws IOException {
      real.close();
    }

    @Override
    public K getCurrentKey() throws IOException, InterruptedException {
      return real.getCurrentKey();
    }

    @Override
    public V getCurrentValue() throws IOException, InterruptedException {
      return real.getCurrentValue();
    }

    @Override
    public float getProgress() throws IOException, InterruptedException {
      return real.getProgress();
    }

    @Override
    public void initialize(org.apache.hadoop.mapreduce.InputSplit split,
                           org.apache.hadoop.mapreduce.TaskAttemptContext context
                           ) throws IOException, InterruptedException {
      real.initialize(split, context);
    }

    @Override
    public boolean nextKeyValue() throws IOException, InterruptedException {
      boolean result = real.nextKeyValue();
      if (result) {
        inputRecordCounter.increment(1);
      }
      reporter.setProgress(getProgress());
      return result;
    }
  }

  /**
   * Since the mapred and mapreduce Partitioners don't share a common interface
   * (JobConfigurable is deprecated and a subtype of mapred.Partitioner), the
   * partitioner lives in Old/NewOutputCollector. Note that, for map-only jobs,
   * the configured partitioner should not be called. It's common for
   * partitioners to compute a result mod numReduces, which causes a div0 error
   */
  private static class OldOutputCollector<K,V> implements OutputCollector<K,V> {
    private final Partitioner<K,V> partitioner;
    private final MapOutputCollector<K,V> collector;
    private final int numPartitions;

    @SuppressWarnings("unchecked")
    OldOutputCollector(MapOutputCollector<K,V> collector, JobConf conf) {
      numPartitions = conf.getNumReduceTasks();
      if (numPartitions > 0) {
        partitioner = (Partitioner<K,V>)
          ReflectionUtils.newInstance(conf.getPartitionerClass(), conf);
      } else {
        partitioner = new Partitioner<K,V>() {
          @Override
          public void configure(JobConf job) { }
          @Override
          public int getPartition(K key, V value, int numPartitions) {
            return -1;
          }
        };
      }
      this.collector = collector;
    }

    @Override
    public void collect(K key, V value) throws IOException {
      try {
        collector.collect(key, value,
                          partitioner.getPartition(key, value, numPartitions));
      } catch (InterruptedException ie) {
        Thread.currentThread().interrupt();
        throw new IOException("interrupt exception", ie);
      }
    }
  }

  private class NewDirectOutputCollector<K,V>
  extends org.apache.hadoop.mapreduce.RecordWriter<K,V> {
    private final org.apache.hadoop.mapreduce.RecordWriter out;

    private final TaskReporter reporter;

    private final Counters.Counter mapOutputRecordCounter;
    
    @SuppressWarnings("unchecked")
    NewDirectOutputCollector(org.apache.hadoop.mapreduce.JobContext jobContext,
        JobConf job, TaskUmbilicalProtocol umbilical, TaskReporter reporter) 
    throws IOException, ClassNotFoundException, InterruptedException {
      this.reporter = reporter;
      out = outputFormat.getRecordWriter(taskContext);
      mapOutputRecordCounter = 
        reporter.getCounter(TaskCounter.MAP_OUTPUT_RECORDS);
    }

    @Override
    @SuppressWarnings("unchecked")
    public void write(K key, V value) 
    throws IOException, InterruptedException {
      reporter.progress();
      out.write(key, value);
      mapOutputRecordCounter.increment(1);
    }

    @Override
    public void close(TaskAttemptContext context) 
    throws IOException,InterruptedException {
      reporter.progress();
      if (out != null) {
        out.close(context);
      }
    }
  }
  
  private class NewOutputCollector<K,V>
    extends org.apache.hadoop.mapreduce.RecordWriter<K,V> {
    private final MapOutputCollector<K,V> collector;
    private final org.apache.hadoop.mapreduce.Partitioner<K,V> partitioner;
    private final int partitions;

    @SuppressWarnings("unchecked")
    NewOutputCollector(org.apache.hadoop.mapreduce.JobContext jobContext,
                       JobConf job,
                       TaskUmbilicalProtocol umbilical,
                       TaskReporter reporter
                       ) throws IOException, ClassNotFoundException {
      collector = new MapOutputBuffer<K,V>(umbilical, job, reporter);
      partitions = jobContext.getNumReduceTasks();
      if (partitions > 0) {
        partitioner = (org.apache.hadoop.mapreduce.Partitioner<K,V>)
          ReflectionUtils.newInstance(jobContext.getPartitionerClass(), job);
      } else {
        partitioner = new org.apache.hadoop.mapreduce.Partitioner<K,V>() {
          @Override
          public int getPartition(K key, V value, int numPartitions) {
            return -1;
          }
        };
      }
    }

    @Override
    public void write(K key, V value) throws IOException, InterruptedException {
      collector.collect(key, value,
                        partitioner.getPartition(key, value, partitions));
    }

    @Override
    public void close(TaskAttemptContext context
                      ) throws IOException,InterruptedException {
      try {
        collector.flush();
      } catch (ClassNotFoundException cnf) {
        throw new IOException("can't find class ", cnf);
      }
      collector.close();
    }
  }

  @SuppressWarnings("unchecked")
  private <INKEY,INVALUE,OUTKEY,OUTVALUE>
  void runNewMapper(final JobConf job,
                    final BytesWritable rawSplit,
                    final TaskUmbilicalProtocol umbilical,
                    TaskReporter reporter
                    ) throws IOException, ClassNotFoundException,
                             InterruptedException {
    // make a task context so we can get the classes
    org.apache.hadoop.mapreduce.TaskAttemptContext taskContext =
      new org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl(job, 
                                                                  getTaskID());
    // make a mapper
    org.apache.hadoop.mapreduce.Mapper<INKEY,INVALUE,OUTKEY,OUTVALUE> mapper =
      (org.apache.hadoop.mapreduce.Mapper<INKEY,INVALUE,OUTKEY,OUTVALUE>)
        ReflectionUtils.newInstance(taskContext.getMapperClass(), job);
    // make the input format
    org.apache.hadoop.mapreduce.InputFormat<INKEY,INVALUE> inputFormat =
      (org.apache.hadoop.mapreduce.InputFormat<INKEY,INVALUE>)
        ReflectionUtils.newInstance(taskContext.getInputFormatClass(), job);
    // rebuild the input split
    org.apache.hadoop.mapreduce.InputSplit split = null;
    DataInputBuffer splitBuffer = new DataInputBuffer();
    splitBuffer.reset(rawSplit.getBytes(), 0, rawSplit.getLength());
    SerializationFactory factory = new SerializationFactory(job);
    Deserializer<? extends org.apache.hadoop.mapreduce.InputSplit>
      deserializer = 
        (Deserializer<? extends org.apache.hadoop.mapreduce.InputSplit>) 
        factory.getDeserializer(job.getClassByName(splitClass));
    deserializer.open(splitBuffer);
    split = deserializer.deserialize(null);

    org.apache.hadoop.mapreduce.RecordReader<INKEY,INVALUE> input =
      new NewTrackingRecordReader<INKEY,INVALUE>
          (inputFormat.createRecordReader(split, taskContext), reporter);
    
    job.setBoolean(JobContext.SKIP_RECORDS, isSkipping());
    org.apache.hadoop.mapreduce.RecordWriter output = null;
    
    // get an output object
    if (job.getNumReduceTasks() == 0) {
      output = 
        new NewDirectOutputCollector(taskContext, job, umbilical, reporter);
    } else {
      output = new NewOutputCollector(taskContext, job, umbilical, reporter);
    }

    org.apache.hadoop.mapreduce.MapContext<INKEY, INVALUE, OUTKEY, OUTVALUE> 
    mapContext = 
      new MapContextImpl<INKEY, INVALUE, OUTKEY, OUTVALUE>(job, getTaskID(), 
          input, output, 
          committer, 
          reporter, split);

    org.apache.hadoop.mapreduce.Mapper<INKEY,INVALUE,OUTKEY,OUTVALUE>.Context 
        mapperContext = 
          new WrappedMapper<INKEY, INVALUE, OUTKEY, OUTVALUE>().getMapContext(
              mapContext);

    input.initialize(split, mapperContext);
    mapper.run(mapperContext);
    mapPhase.complete();
    setPhase(TaskStatus.Phase.SORT);
    statusUpdate(umbilical);
    input.close();
    output.close(mapperContext);
  }

  interface MapOutputCollector<K, V> {

    public void collect(K key, V value, int partition
                        ) throws IOException, InterruptedException;
    public void close() throws IOException, InterruptedException;
    
    public void flush() throws IOException, InterruptedException, 
                               ClassNotFoundException;
        
  }

  class DirectMapOutputCollector<K, V>
    implements MapOutputCollector<K, V> {
 
    private RecordWriter<K, V> out = null;

    private TaskReporter reporter = null;

    private final Counters.Counter mapOutputRecordCounter;

    @SuppressWarnings("unchecked")
    public DirectMapOutputCollector(TaskUmbilicalProtocol umbilical,
        JobConf job, TaskReporter reporter) throws IOException {
      this.reporter = reporter;
      String finalName = getOutputName(getPartition());
      FileSystem fs = FileSystem.get(job);

      out = job.getOutputFormat().getRecordWriter(fs, job, finalName, reporter);

      mapOutputRecordCounter = reporter.getCounter(TaskCounter.MAP_OUTPUT_RECORDS);
    }

    public void close() throws IOException {
      if (this.out != null) {
        out.close(this.reporter);
      }

    }

    public void flush() throws IOException, InterruptedException, 
                               ClassNotFoundException {
    }

    public void collect(K key, V value, int partition) throws IOException {
      reporter.progress();
      out.write(key, value);
      mapOutputRecordCounter.increment(1);
    }
    
  }

  class MapOutputBuffer<K extends Object, V extends Object>
      implements MapOutputCollector<K, V>, IndexedSortable {
    private final int partitions;
    private final JobConf job;
    private final TaskReporter reporter;
    private final Class<K> keyClass;
    private final Class<V> valClass;
    private final RawComparator<K> comparator;
    private final SerializationFactory serializationFactory;
    private final Serializer<K> keySerializer;
    private final Serializer<V> valSerializer;
    private final CombinerRunner<K,V> combinerRunner;
    private final CombineOutputCollector<K, V> combineCollector;
    
    // Compression for map-outputs
    private CompressionCodec codec = null;

    // k/v accounting
    private volatile int kvstart = 0;  // marks beginning of spill
    private volatile int kvend = 0;    // marks beginning of collectable
    private int kvindex = 0;           // marks end of collected
    private final int[] kvoffsets;     // indices into kvindices
    private final int[] kvindices;     // partition, k/v offsets into kvbuffer
    private volatile int bufstart = 0; // marks beginning of spill
    private volatile int bufend = 0;   // marks beginning of collectable
    private volatile int bufvoid = 0;  // marks the point where we should stop
                                       // reading at the end of the buffer
    private int bufindex = 0;          // marks end of collected
    private int bufmark = 0;           // marks end of record
    private byte[] kvbuffer;           // main output buffer
    private static final int PARTITION = 0; // partition offset in acct
    private static final int KEYSTART = 1;  // key offset in acct
    private static final int VALSTART = 2;  // val offset in acct
    private static final int ACCTSIZE = 3;  // total #fields in acct
    private static final int RECSIZE =
                       (ACCTSIZE + 1) * 4;  // acct bytes per record

    // spill accounting
    private volatile int numSpills = 0;
    private volatile Throwable sortSpillException = null;
    private final int softRecordLimit;
    private final int softBufferLimit;
    private int recordRemaining;
    private int bufferRemaining;
    private final int minSpillsForCombine;
    private final IndexedSorter sorter;
    private final ReentrantLock spillLock = new ReentrantLock();
    private final Condition spillDone = spillLock.newCondition();
    private final Condition spillReady = spillLock.newCondition();
    private final BlockingBuffer bb = new BlockingBuffer();
    private volatile boolean spillThreadRunning = false;
    private final SpillThread spillThread = new SpillThread();

    private final FileSystem localFs;
    private final FileSystem rfs;
   
    private final Counters.Counter mapOutputByteCounter;
    private final Counters.Counter mapOutputRecordCounter;
    private final Counters.Counter combineOutputCounter;
    
    private ArrayList<SpillRecord> indexCacheList;
    private int totalIndexCacheMemory;
    private static final int INDEX_CACHE_MEMORY_LIMIT = 1024 * 1024;

    @SuppressWarnings("unchecked")
    public MapOutputBuffer(TaskUmbilicalProtocol umbilical, JobConf job,
                           TaskReporter reporter
                           ) throws IOException, ClassNotFoundException {
      this.job = job;
      this.reporter = reporter;
      localFs = FileSystem.getLocal(job);
      partitions = job.getNumReduceTasks();
       
      rfs = ((LocalFileSystem)localFs).getRaw();

      indexCacheList = new ArrayList<SpillRecord>();
      
      //sanity checks
      final float spillper = job.getFloat(JobContext.MAP_SORT_SPILL_PERCENT,(float)0.8);
      final float recper = job.getFloat(JobContext.MAP_SORT_RECORD_PERCENT,(float)0.05);
      final int sortmb = job.getInt(JobContext.IO_SORT_MB, 100);
      if (spillper > (float)1.0 || spillper < (float)0.0) {
        throw new IOException("Invalid \"mapreduce.map.sort.spill.percent\": " + spillper);
      }
      if (recper > (float)1.0 || recper < (float)0.01) {
        throw new IOException("Invalid \"mapreduce.map.sort.record.percent\": " + recper);
      }
      if ((sortmb & 0x7FF) != sortmb) {
        throw new IOException("Invalid \"mapreduce.task.mapreduce.task.io.sort.mb\": " + sortmb);
      }
      sorter = ReflectionUtils.newInstance(job.getClass("map.sort.class",
            QuickSort.class, IndexedSorter.class), job);
      LOG.info("mapreduce.task.mapreduce.task.io.sort.mb = " + sortmb);
      // buffers and accounting
      int maxMemUsage = sortmb << 20;
      int recordCapacity = (int)(maxMemUsage * recper);
      recordCapacity -= recordCapacity % RECSIZE;
      kvbuffer = new byte[maxMemUsage - recordCapacity];
      bufvoid = kvbuffer.length;
      recordCapacity /= RECSIZE;
      kvoffsets = new int[recordCapacity];
      kvindices = new int[recordCapacity * ACCTSIZE];
      softBufferLimit = (int)(kvbuffer.length * spillper);
      softRecordLimit = (int)(kvoffsets.length * spillper);
      recordRemaining = softRecordLimit;
      bufferRemaining = softBufferLimit;
      LOG.info("data buffer = " + softBufferLimit + "/" + kvbuffer.length);
      LOG.info("record buffer = " + softRecordLimit + "/" + kvoffsets.length);
      // k/v serialization
      comparator = job.getOutputKeyComparator();
      keyClass = (Class<K>)job.getMapOutputKeyClass();
      valClass = (Class<V>)job.getMapOutputValueClass();
      serializationFactory = new SerializationFactory(job);
      keySerializer = serializationFactory.getSerializer(keyClass);
      keySerializer.open(bb);
      valSerializer = serializationFactory.getSerializer(valClass);
      valSerializer.open(bb);
      // counters
      mapOutputByteCounter = reporter.getCounter(TaskCounter.MAP_OUTPUT_BYTES);
      mapOutputRecordCounter = reporter.getCounter(TaskCounter.MAP_OUTPUT_RECORDS);
      Counters.Counter combineInputCounter = 
        reporter.getCounter(TaskCounter.COMBINE_INPUT_RECORDS);
      combineOutputCounter = reporter.getCounter(TaskCounter.COMBINE_OUTPUT_RECORDS);
      // compression
      if (job.getCompressMapOutput()) {
        Class<? extends CompressionCodec> codecClass =
          job.getMapOutputCompressorClass(DefaultCodec.class);
        codec = ReflectionUtils.newInstance(codecClass, job);
      }
      // combiner
      combinerRunner = CombinerRunner.create(job, getTaskID(), 
                                             combineInputCounter,
                                             reporter, null);
      if (combinerRunner != null) {
        combineCollector= new CombineOutputCollector<K,V>(combineOutputCounter);
      } else {
        combineCollector = null;
      }
      minSpillsForCombine = job.getInt(JobContext.MAP_COMBINE_MIN_SPISS, 3);
      spillThread.setDaemon(true);
      spillThread.setName("SpillThread");
      spillLock.lock();
      try {
        spillThread.start();
        while (!spillThreadRunning) {
          spillDone.await();
        }
      } catch (InterruptedException e) {
        throw (IOException)new IOException("Spill thread failed to initialize"
            ).initCause(sortSpillException);
      } finally {
        spillLock.unlock();
      }
      if (sortSpillException != null) {
        throw (IOException)new IOException("Spill thread failed to initialize"
            ).initCause(sortSpillException);
      }
    }

    public synchronized void collect(K key, V value, int partition
                                     ) throws IOException {
      reporter.progress();
      if (key.getClass() != keyClass) {
        throw new IOException("Type mismatch in key from map: expected "
                              + keyClass.getName() + ", recieved "
                              + key.getClass().getName());
      }
      if (value.getClass() != valClass) {
        throw new IOException("Type mismatch in value from map: expected "
                              + valClass.getName() + ", recieved "
                              + value.getClass().getName());
      }
      final int kvnext = (kvindex + 1) % kvoffsets.length;
      if (--recordRemaining <= 0) {
        // Possible for check to remain < zero, if soft limit remains
        // in force but unsatisfiable because spill is in progress
        spillLock.lock();
        try {
          boolean kvfull;
          do {
            if (sortSpillException != null) {
              throw (IOException)new IOException("Spill failed"
                  ).initCause(sortSpillException);
            }
            // sufficient acct space
            kvfull = kvnext == kvstart;
            final boolean kvsoftlimit = ((kvnext > kvend)
                ? kvnext - kvend > softRecordLimit
                : kvend - kvnext <= kvoffsets.length - softRecordLimit);
            if (kvstart == kvend && kvsoftlimit) {
              LOG.info("Spilling map output: record full = " + kvfull);
              startSpill();
            }
            if (kvfull) {
              try {
                while (kvstart != kvend) {
                  reporter.progress();
                  spillDone.await();
                }
              } catch (InterruptedException e) {
                throw (IOException)new IOException(
                    "Collector interrupted while waiting for the writer"
                    ).initCause(e);
              }
            }
          } while (kvfull);
          final int softOff = kvend + softRecordLimit;
          recordRemaining = Math.min(
              // out of acct space
              (kvnext < kvstart
                 ? kvstart - kvnext
                 : kvoffsets.length - kvnext + kvstart),
              // soft limit
              (kvend < kvnext
                 ? softOff - kvnext
                 : kvnext + (softOff - kvoffsets.length)));
        } finally {
          spillLock.unlock();
        }
      }

      try {
        // serialize key bytes into buffer
        int keystart = bufindex;
        keySerializer.serialize(key);
        if (bufindex < keystart) {
          // wrapped the key; reset required
          bb.reset();
          keystart = 0;
        }
        // serialize value bytes into buffer
        final int valstart = bufindex;
        valSerializer.serialize(value);
        int valend = bb.markRecord();

        if (partition < 0 || partition >= partitions) {
          throw new IOException("Illegal partition for " + key + " (" +
              partition + ")");
        }

        mapOutputRecordCounter.increment(1);
        mapOutputByteCounter.increment(valend >= keystart
            ? valend - keystart
            : (bufvoid - keystart) + valend);

        // update accounting info
        int ind = kvindex * ACCTSIZE;
        kvoffsets[kvindex] = ind;
        kvindices[ind + PARTITION] = partition;
        kvindices[ind + KEYSTART] = keystart;
        kvindices[ind + VALSTART] = valstart;
        kvindex = kvnext;
      } catch (MapBufferTooSmallException e) {
        LOG.info("Record too large for in-memory buffer: " + e.getMessage());
        spillSingleRecord(key, value, partition);
        mapOutputRecordCounter.increment(1);
        return;
      }

    }

    /**
     * Compare logical range, st i, j MOD offset capacity.
     * Compare by partition, then by key.
     * @see IndexedSortable#compare
     */
    public int compare(int i, int j) {
      final int ii = kvoffsets[i % kvoffsets.length];
      final int ij = kvoffsets[j % kvoffsets.length];
      // sort by partition
      if (kvindices[ii + PARTITION] != kvindices[ij + PARTITION]) {
        return kvindices[ii + PARTITION] - kvindices[ij + PARTITION];
      }
      // sort by key
      return comparator.compare(kvbuffer,
          kvindices[ii + KEYSTART],
          kvindices[ii + VALSTART] - kvindices[ii + KEYSTART],
          kvbuffer,
          kvindices[ij + KEYSTART],
          kvindices[ij + VALSTART] - kvindices[ij + KEYSTART]);
    }

    /**
     * Swap logical indices st i, j MOD offset capacity.
     * @see IndexedSortable#swap
     */
    public void swap(int i, int j) {
      i %= kvoffsets.length;
      j %= kvoffsets.length;
      int tmp = kvoffsets[i];
      kvoffsets[i] = kvoffsets[j];
      kvoffsets[j] = tmp;
    }

    /**
     * Inner class managing the spill of serialized records to disk.
     */
    protected class BlockingBuffer extends DataOutputStream {

      public BlockingBuffer() {
        this(new Buffer());
      }

      private BlockingBuffer(OutputStream out) {
        super(out);
      }

      /**
       * Mark end of record. Note that this is required if the buffer is to
       * cut the spill in the proper place.
       */
      public int markRecord() {
        bufmark = bufindex;
        return bufindex;
      }

      /**
       * Set position from last mark to end of writable buffer, then rewrite
       * the data between last mark and kvindex.
       * This handles a special case where the key wraps around the buffer.
       * If the key is to be passed to a RawComparator, then it must be
       * contiguous in the buffer. This recopies the data in the buffer back
       * into itself, but starting at the beginning of the buffer. Note that
       * reset() should <b>only</b> be called immediately after detecting
       * this condition. To call it at any other time is undefined and would
       * likely result in data loss or corruption.
       * @see #markRecord()
       */
      protected void reset() throws IOException {
        // spillLock unnecessary; If spill wraps, then
        // bufindex < bufstart < bufend so contention is impossible
        // a stale value for bufstart does not affect correctness, since
        // we can only get false negatives that force the more
        // conservative path
        int headbytelen = bufvoid - bufmark;
        bufvoid = bufmark;
        if (bufindex + headbytelen < bufstart) {
          System.arraycopy(kvbuffer, 0, kvbuffer, headbytelen, bufindex);
          System.arraycopy(kvbuffer, bufvoid, kvbuffer, 0, headbytelen);
          bufindex += headbytelen;
        } else {
          byte[] keytmp = new byte[bufindex];
          System.arraycopy(kvbuffer, 0, keytmp, 0, bufindex);
          bufindex = 0;
          out.write(kvbuffer, bufmark, headbytelen);
          out.write(keytmp);
        }
      }
    }

    public class Buffer extends OutputStream {
      private final byte[] scratch = new byte[1];

      @Override
      public void write(int v)
          throws IOException {
        scratch[0] = (byte)v;
        write(scratch, 0, 1);
      }

      /**
       * Attempt to write a sequence of bytes to the collection buffer.
       * This method will block if the spill thread is running and it
       * cannot write.
       * @throws MapBufferTooSmallException if record is too large to
       *    deserialize into the collection buffer.
       */
      @Override
      public void write(byte b[], int off, int len)
          throws IOException {
        boolean buffull = false;
        boolean wrap = false;
        bufferRemaining -= len;
        if (bufferRemaining <= 0) {
          // writing these bytes could exhaust available buffer space
          // check if spill or blocking is necessary
          spillLock.lock();
          try {
            do {
              if (sortSpillException != null) {
                throw (IOException)new IOException("Spill failed"
                    ).initCause(sortSpillException);
              }

              // sufficient buffer space?
              if (bufstart <= bufend && bufend <= bufindex) {
                buffull = bufindex + len > bufvoid;
                wrap = (bufvoid - bufindex) + bufstart > len;
              } else {
                // bufindex <= bufstart <= bufend
                // bufend <= bufindex <= bufstart
                wrap = false;
                buffull = bufindex + len > bufstart;
              }

              if (kvstart == kvend) {
                // spill thread not running
                if (kvend != kvindex) {
                  // we have records we can spill
                  final boolean bufsoftlimit = (bufindex > bufend)
                    ? bufindex - bufend > softBufferLimit
                    : bufend - bufindex < bufvoid - softBufferLimit;
                  if (bufsoftlimit || (buffull && !wrap)) {
                    LOG.info("Spilling map output: buffer full= " + (buffull && !wrap));
                    startSpill();
                  }
                } else if (buffull && !wrap) {
                  // We have no buffered records, and this record is too large
                  // to write into kvbuffer. We must spill it directly from
                  // collect
                  final int size = ((bufend <= bufindex)
                    ? bufindex - bufend
                    : (bufvoid - bufend) + bufindex) + len;
                  bufstart = bufend = bufindex = bufmark = 0;
                  kvstart = kvend = kvindex = 0;
                  bufvoid = kvbuffer.length;
                  throw new MapBufferTooSmallException(size + " bytes");
                }
              }

              if (buffull && !wrap) {
                try {
                  while (kvstart != kvend) {
                    reporter.progress();
                    spillDone.await();
                  }
                } catch (InterruptedException e) {
                    throw (IOException)new IOException(
                        "Buffer interrupted while waiting for the writer"
                        ).initCause(e);
                }
              }
            } while (buffull && !wrap);
            final int softOff = bufend + softBufferLimit;
            bufferRemaining = Math.min(
                // out of buffer space
                (bufindex < bufstart
                   ? bufstart - bufindex
                   : kvbuffer.length - bufindex + bufstart),
                // soft limit
                (bufend < bufindex
                   ? softOff - bufindex
                   : bufindex + (softOff - kvbuffer.length)));
          } finally {
            spillLock.unlock();
          }
        } else {
          buffull = bufindex + len > bufvoid;
        }
        // here, we know that we have sufficient space to write
        if (buffull) {
          final int gaplen = bufvoid - bufindex;
          System.arraycopy(b, off, kvbuffer, bufindex, gaplen);
          len -= gaplen;
          off += gaplen;
          bufindex = 0;
        }
        System.arraycopy(b, off, kvbuffer, bufindex, len);
        bufindex += len;
        bufferRemaining -= len;
      }
    }

    public void flush() throws IOException, ClassNotFoundException,
           InterruptedException {
      LOG.info("Starting flush of map output");
      spillLock.lock();
      try {
        while (kvstart != kvend) {
          reporter.progress();
          spillDone.await();
        }
        if (sortSpillException != null) {
          throw (IOException)new IOException("Spill failed"
              ).initCause(sortSpillException);
        }
        if (kvend != kvindex) {
          kvend = kvindex;
          bufend = bufmark;
          sortAndSpill();
        }
      } catch (InterruptedException e) {
        throw (IOException)new IOException(
            "Buffer interrupted while waiting for the writer"
            ).initCause(e);
      } finally {
        spillLock.unlock();
      }
      assert !spillLock.isHeldByCurrentThread();
      // shut down spill thread and wait for it to exit. Since the preceding
      // ensures that it is finished with its work (and sortAndSpill did not
      // throw), we elect to use an interrupt instead of setting a flag.
      // Spilling simultaneously from this thread while the spill thread
      // finishes its work might be both a useful way to extend this and also
      // sufficient motivation for the latter approach.
      try {
        spillThread.interrupt();
        spillThread.join();
      } catch (InterruptedException e) {
        throw (IOException)new IOException("Spill failed"
            ).initCause(e);
      }
      // release sort buffer before the merge
      kvbuffer = null;
      mergeParts();
    }

    public void close() { }

    protected class SpillThread extends Thread {

      @Override
      public void run() {
        spillLock.lock();
        spillThreadRunning = true;
        try {
          while (true) {
            spillDone.signal();
            while (kvstart == kvend) {
              spillReady.await();
            }
            try {
              spillLock.unlock();
              sortAndSpill();
            } catch (Exception e) {
              sortSpillException = e;
            } catch (Throwable t) {
              sortSpillException = t;
              String logMsg = "Task " + getTaskID() + " failed : " 
                              + StringUtils.stringifyException(t);
              reportFatalError(getTaskID(), t, logMsg);
            } finally {
              spillLock.lock();
              if (bufend < bufindex && bufindex < bufstart) {
                bufvoid = kvbuffer.length;
              }
              kvstart = kvend;
              bufstart = bufend;
            }
          }
        } catch (InterruptedException e) {
          Thread.currentThread().interrupt();
        } finally {
          spillLock.unlock();
          spillThreadRunning = false;
        }
      }
    }

    private void startSpill() {
      LOG.info("bufstart = " + bufstart + "; bufend = " + bufmark +
               "; bufvoid = " + bufvoid);
      LOG.info("kvstart = " + kvstart + "; kvend = " + kvindex +
               "; length = " + kvoffsets.length);
      kvend = kvindex;
      bufend = bufmark;
      spillReady.signal();
    }

    private void sortAndSpill() throws IOException, ClassNotFoundException,
                                       InterruptedException {
      //approximate the length of the output file to be the length of the
      //buffer + header lengths for the partitions
      long size = (bufend >= bufstart
          ? bufend - bufstart
          : (bufvoid - bufend) + bufstart) +
                  partitions * APPROX_HEADER_LENGTH;
      FSDataOutputStream out = null;
      try {
        // create spill file
        final SpillRecord spillRec = new SpillRecord(partitions);
        final Path filename =
            mapOutputFile.getSpillFileForWrite(numSpills, size);
        out = rfs.create(filename);

        final int endPosition = (kvend > kvstart)
          ? kvend
          : kvoffsets.length + kvend;
        sorter.sort(MapOutputBuffer.this, kvstart, endPosition, reporter);
        int spindex = kvstart;
        IndexRecord rec = new IndexRecord();
        InMemValBytes value = new InMemValBytes();
        for (int i = 0; i < partitions; ++i) {
          IFile.Writer<K, V> writer = null;
          try {
            long segmentStart = out.getPos();
            writer = new Writer<K, V>(job, out, keyClass, valClass, codec,
                                      spilledRecordsCounter);
            if (combinerRunner == null) {
              // spill directly
              DataInputBuffer key = new DataInputBuffer();
              while (spindex < endPosition &&
                  kvindices[kvoffsets[spindex % kvoffsets.length]
                            + PARTITION] == i) {
                final int kvoff = kvoffsets[spindex % kvoffsets.length];
                getVBytesForOffset(kvoff, value);
                key.reset(kvbuffer, kvindices[kvoff + KEYSTART],
                          (kvindices[kvoff + VALSTART] - 
                           kvindices[kvoff + KEYSTART]));
                writer.append(key, value);
                ++spindex;
              }
            } else {
              int spstart = spindex;
              while (spindex < endPosition &&
                  kvindices[kvoffsets[spindex % kvoffsets.length]
                            + PARTITION] == i) {
                ++spindex;
              }
              // Note: we would like to avoid the combiner if we've fewer
              // than some threshold of records for a partition
              if (spstart != spindex) {
                combineCollector.setWriter(writer);
                RawKeyValueIterator kvIter =
                  new MRResultIterator(spstart, spindex);
                combinerRunner.combine(kvIter, combineCollector);
              }
            }

            // close the writer
            writer.close();

            // record offsets
            rec.startOffset = segmentStart;
            rec.rawLength = writer.getRawLength();
            rec.partLength = writer.getCompressedLength();
            spillRec.putIndex(rec, i);

            writer = null;
          } finally {
            if (null != writer) writer.close();
          }
        }

        if (totalIndexCacheMemory >= INDEX_CACHE_MEMORY_LIMIT) {
          // create spill index file
          Path indexFilename =
              mapOutputFile.getSpillIndexFileForWrite(numSpills, partitions
                  * MAP_OUTPUT_INDEX_RECORD_LENGTH);
          spillRec.writeToFile(indexFilename, job);
        } else {
          indexCacheList.add(spillRec);
          totalIndexCacheMemory +=
            spillRec.size() * MAP_OUTPUT_INDEX_RECORD_LENGTH;
        }
        LOG.info("Finished spill " + numSpills);
        ++numSpills;
      } finally {
        if (out != null) out.close();
      }
    }

    /**
     * Handles the degenerate case where serialization fails to fit in
     * the in-memory buffer, so we must spill the record from collect
     * directly to a spill file. Consider this "losing".
     */
    private void spillSingleRecord(final K key, final V value,
                                   int partition) throws IOException {
      long size = kvbuffer.length + partitions * APPROX_HEADER_LENGTH;
      FSDataOutputStream out = null;
      try {
        // create spill file
        final SpillRecord spillRec = new SpillRecord(partitions);
        final Path filename =
            mapOutputFile.getSpillFileForWrite(numSpills, size);
        out = rfs.create(filename);
        
        // we don't run the combiner for a single record
        IndexRecord rec = new IndexRecord();
        for (int i = 0; i < partitions; ++i) {
          IFile.Writer<K, V> writer = null;
          try {
            long segmentStart = out.getPos();
            // Create a new codec, don't care!
            writer = new IFile.Writer<K,V>(job, out, keyClass, valClass, codec,
                                            spilledRecordsCounter);

            if (i == partition) {
              final long recordStart = out.getPos();
              writer.append(key, value);
              // Note that our map byte count will not be accurate with
              // compression
              mapOutputByteCounter.increment(out.getPos() - recordStart);
            }
            writer.close();

            // record offsets
            rec.startOffset = segmentStart;
            rec.rawLength = writer.getRawLength();
            rec.partLength = writer.getCompressedLength();
            spillRec.putIndex(rec, i);

            writer = null;
          } catch (IOException e) {
            if (null != writer) writer.close();
            throw e;
          }
        }
        if (totalIndexCacheMemory >= INDEX_CACHE_MEMORY_LIMIT) {
          // create spill index file
          Path indexFilename =
              mapOutputFile.getSpillIndexFileForWrite(numSpills, partitions
                  * MAP_OUTPUT_INDEX_RECORD_LENGTH);
          spillRec.writeToFile(indexFilename, job);
        } else {
          indexCacheList.add(spillRec);
          totalIndexCacheMemory +=
            spillRec.size() * MAP_OUTPUT_INDEX_RECORD_LENGTH;
        }
        ++numSpills;
      } finally {
        if (out != null) out.close();
      }
    }

    /**
     * Given an offset, populate vbytes with the associated set of
     * deserialized value bytes. Should only be called during a spill.
     */
    private void getVBytesForOffset(int kvoff, InMemValBytes vbytes) {
      final int nextindex = (kvoff / ACCTSIZE ==
                            (kvend - 1 + kvoffsets.length) % kvoffsets.length)
        ? bufend
        : kvindices[(kvoff + ACCTSIZE + KEYSTART) % kvindices.length];
      int vallen = (nextindex >= kvindices[kvoff + VALSTART])
        ? nextindex - kvindices[kvoff + VALSTART]
        : (bufvoid - kvindices[kvoff + VALSTART]) + nextindex;
      vbytes.reset(kvbuffer, kvindices[kvoff + VALSTART], vallen);
    }

    /**
     * Inner class wrapping valuebytes, used for appendRaw.
     */
    protected class InMemValBytes extends DataInputBuffer {
      private byte[] buffer;
      private int start;
      private int length;
            
      public void reset(byte[] buffer, int start, int length) {
        this.buffer = buffer;
        this.start = start;
        this.length = length;
        
        if (start + length > bufvoid) {
          this.buffer = new byte[this.length];
          final int taillen = bufvoid - start;
          System.arraycopy(buffer, start, this.buffer, 0, taillen);
          System.arraycopy(buffer, 0, this.buffer, taillen, length-taillen);
          this.start = 0;
        }
        
        super.reset(this.buffer, this.start, this.length);
      }
    }

    protected class MRResultIterator implements RawKeyValueIterator {
      private final DataInputBuffer keybuf = new DataInputBuffer();
      private final InMemValBytes vbytes = new InMemValBytes();
      private final int end;
      private int current;
      public MRResultIterator(int start, int end) {
        this.end = end;
        current = start - 1;
      }
      public boolean next() throws IOException {
        return ++current < end;
      }
      public DataInputBuffer getKey() throws IOException {
        final int kvoff = kvoffsets[current % kvoffsets.length];
        keybuf.reset(kvbuffer, kvindices[kvoff + KEYSTART],
                     kvindices[kvoff + VALSTART] - kvindices[kvoff + KEYSTART]);
        return keybuf;
      }
      public DataInputBuffer getValue() throws IOException {
        getVBytesForOffset(kvoffsets[current % kvoffsets.length], vbytes);
        return vbytes;
      }
      public Progress getProgress() {
        return null;
      }
      public void close() { }
    }

    private void mergeParts() throws IOException, InterruptedException, 
                                     ClassNotFoundException {
      // get the approximate size of the final output/index files
      long finalOutFileSize = 0;
      long finalIndexFileSize = 0;
      final Path[] filename = new Path[numSpills];
      final TaskAttemptID mapId = getTaskID();

      for(int i = 0; i < numSpills; i++) {
        filename[i] = mapOutputFile.getSpillFile(i);
        finalOutFileSize += rfs.getFileStatus(filename[i]).getLen();
      }
      if (numSpills == 1) { //the spill is the final output
        rfs.rename(filename[0],
            new Path(filename[0].getParent(), "file.out"));
        if (indexCacheList.size() == 0) {
          rfs.rename(mapOutputFile.getSpillIndexFile(0),
              new Path(filename[0].getParent(),"file.out.index"));
        } else {
          indexCacheList.get(0).writeToFile(
                new Path(filename[0].getParent(),"file.out.index"), job);
        }
        return;
      }

      // read in paged indices
      for (int i = indexCacheList.size(); i < numSpills; ++i) {
        Path indexFileName = mapOutputFile.getSpillIndexFile(i);
        indexCacheList.add(new SpillRecord(indexFileName, job));
      }

      //make correction in the length to include the sequence file header
      //lengths for each partition
      finalOutFileSize += partitions * APPROX_HEADER_LENGTH;
      finalIndexFileSize = partitions * MAP_OUTPUT_INDEX_RECORD_LENGTH;
      Path finalOutputFile =
          mapOutputFile.getOutputFileForWrite(finalOutFileSize);
      Path finalIndexFile =
          mapOutputFile.getOutputIndexFileForWrite(finalIndexFileSize);

      //The output stream for the final single output file
      FSDataOutputStream finalOut = rfs.create(finalOutputFile, true, 4096);

      if (numSpills == 0) {
        //create dummy files
        IndexRecord rec = new IndexRecord();
        SpillRecord sr = new SpillRecord(partitions);
        try {
          for (int i = 0; i < partitions; i++) {
            long segmentStart = finalOut.getPos();
            Writer<K, V> writer =
              new Writer<K, V>(job, finalOut, keyClass, valClass, codec, null);
            writer.close();
            rec.startOffset = segmentStart;
            rec.rawLength = writer.getRawLength();
            rec.partLength = writer.getCompressedLength();
            sr.putIndex(rec, i);
          }
          sr.writeToFile(finalIndexFile, job);
        } finally {
          finalOut.close();
        }
        return;
      }
      {
        sortPhase.addPhases(partitions); // Divide sort phase into sub-phases
        Merger.considerFinalMergeForProgress();
        
        IndexRecord rec = new IndexRecord();
        final SpillRecord spillRec = new SpillRecord(partitions);
        for (int parts = 0; parts < partitions; parts++) {
          //create the segments to be merged
          List<Segment<K,V>> segmentList =
            new ArrayList<Segment<K, V>>(numSpills);
          for(int i = 0; i < numSpills; i++) {
            IndexRecord indexRecord = indexCacheList.get(i).getIndex(parts);

            Segment<K,V> s =
              new Segment<K,V>(job, rfs, filename[i], indexRecord.startOffset,
                               indexRecord.partLength, codec, true);
            segmentList.add(i, s);

            if (LOG.isDebugEnabled()) {
              LOG.debug("MapId=" + mapId + " Reducer=" + parts +
                  "Spill =" + i + "(" + indexRecord.startOffset + "," +
                  indexRecord.rawLength + ", " + indexRecord.partLength + ")");
            }
          }

          int mergeFactor = job.getInt(JobContext.IO_SORT_FACTOR, 100);
          // sort the segments only if there are intermediate merges
          boolean sortSegments = segmentList.size() > mergeFactor;
          //merge
          @SuppressWarnings("unchecked")
          RawKeyValueIterator kvIter = Merger.merge(job, rfs,
                         keyClass, valClass, codec,
                         segmentList, mergeFactor,
                         new Path(mapId.toString()),
                         job.getOutputKeyComparator(), reporter, sortSegments,
                         null, spilledRecordsCounter, sortPhase.phase());

          //write merged output to disk
          long segmentStart = finalOut.getPos();
          Writer<K, V> writer =
              new Writer<K, V>(job, finalOut, keyClass, valClass, codec,
                               spilledRecordsCounter);
          if (combinerRunner == null || numSpills < minSpillsForCombine) {
            Merger.writeFile(kvIter, writer, reporter, job);
          } else {
            combineCollector.setWriter(writer);
            combinerRunner.combine(kvIter, combineCollector);
          }

          //close
          writer.close();

          sortPhase.startNextPhase();
          
          // record offsets
          rec.startOffset = segmentStart;
          rec.rawLength = writer.getRawLength();
          rec.partLength = writer.getCompressedLength();
          spillRec.putIndex(rec, parts);
        }
        spillRec.writeToFile(finalIndexFile, job);
        finalOut.close();
        for(int i = 0; i < numSpills; i++) {
          rfs.delete(filename[i],true);
        }
      }
    }

  } // MapOutputBuffer
  
  /**
   * Exception indicating that the allocated sort buffer is insufficient
   * to hold the current record.
   */
  @SuppressWarnings("serial")
  private static class MapBufferTooSmallException extends IOException {
    public MapBufferTooSmallException(String s) {
      super(s);
    }
  }

}