org.apache.hadoop.mapred.JobConf#getMapOutputKeyClass ( )源码实例Demo

private void combineAndSpill(
    RawKeyValueIterator kvIter,
    Counters.Counter inCounter) throws IOException {
  JobConf job = jobConf;
  Reducer combiner = ReflectionUtils.newInstance(combinerClass, job);
  Class<K> keyClass = (Class<K>) job.getMapOutputKeyClass();
  Class<V> valClass = (Class<V>) job.getMapOutputValueClass();
  RawComparator<K> comparator = 
    (RawComparator<K>)job.getCombinerKeyGroupingComparator();
  try {
    CombineValuesIterator values = new CombineValuesIterator(
        kvIter, comparator, keyClass, valClass, job, Reporter.NULL,
        inCounter);
    while (values.more()) {
      combiner.reduce(values.getKey(), values, combineCollector,
                      Reporter.NULL);
      values.nextKey();
    }
  } finally {
    combiner.close();
  }
}
 

private void combineAndSpill(
    RawKeyValueIterator kvIter,
    Counters.Counter inCounter) throws IOException {
  JobConf job = jobConf;
  Reducer combiner = ReflectionUtils.newInstance(combinerClass, job);
  Class<K> keyClass = (Class<K>) job.getMapOutputKeyClass();
  Class<V> valClass = (Class<V>) job.getMapOutputValueClass();
  RawComparator<K> comparator = 
    (RawComparator<K>)job.getCombinerKeyGroupingComparator();
  try {
    CombineValuesIterator values = new CombineValuesIterator(
        kvIter, comparator, keyClass, valClass, job, Reporter.NULL,
        inCounter);
    while (values.more()) {
      combiner.reduce(values.getKey(), values, combineCollector,
                      Reporter.NULL);
      values.nextKey();
    }
  } finally {
    combiner.close();
  }
}
 

/**
 * Try initializing partially raw comparator for job.
 *
 * @param conf Configuration.
 */
private void initializePartiallyRawComparator(JobConf conf) {
    String clsName = conf.get(HadoopJobProperty.JOB_PARTIALLY_RAW_COMPARATOR.propertyName(), null);

    if (clsName == null) {
        Class keyCls = conf.getMapOutputKeyClass();

        while (keyCls != null) {
            clsName = PARTIAL_COMPARATORS.get(keyCls.getName());

            if (clsName != null) {
                conf.set(HadoopJobProperty.JOB_PARTIALLY_RAW_COMPARATOR.propertyName(), clsName);

                break;
            }

            keyCls = keyCls.getSuperclass();
        }
    }
}
 

/**
 * Read in the partition file and build indexing data structures.
 * If the keytype is {@link org.apache.hadoop.io.BinaryComparable} and
 * <tt>total.order.partitioner.natural.order</tt> is not false, a trie
 * of the first <tt>total.order.partitioner.max.trie.depth</tt>(2) + 1 bytes
 * will be built. Otherwise, keys will be located using a binary search of
 * the partition keyset using the {@link org.apache.hadoop.io.RawComparator}
 * defined for this job. The input file must be sorted with the same
 * comparator and contain {@link
   org.apache.hadoop.mapred.JobConf#getNumReduceTasks} - 1 keys.
 */
@SuppressWarnings("unchecked") // keytype from conf not static
public void configure(JobConf job) {
  try {
    String parts = getPartitionFile(job);
    final Path partFile = new Path(parts);
    final FileSystem fs = (DEFAULT_PATH.equals(parts))
      ? FileSystem.getLocal(job)     // assume in DistributedCache
      : partFile.getFileSystem(job);

    Class<K> keyClass = (Class<K>)job.getMapOutputKeyClass();
    K[] splitPoints = readPartitions(fs, partFile, keyClass, job);
    if (splitPoints.length != job.getNumReduceTasks() - 1) {
      throw new IOException("Wrong number of partitions in keyset");
    }
    RawComparator<K> comparator =
      (RawComparator<K>) job.getOutputKeyComparator();
    for (int i = 0; i < splitPoints.length - 1; ++i) {
      if (comparator.compare(splitPoints[i], splitPoints[i+1]) >= 0) {
        throw new IOException("Split points are out of order");
      }
    }
    boolean natOrder =
      job.getBoolean("total.order.partitioner.natural.order", true);
    if (natOrder && BinaryComparable.class.isAssignableFrom(keyClass)) {
      partitions = buildTrie((BinaryComparable[])splitPoints, 0,
          splitPoints.length, new byte[0],
          job.getInt("total.order.partitioner.max.trie.depth", 2));
    } else {
      partitions = new BinarySearchNode(splitPoints, comparator);
    }
  } catch (IOException e) {
    throw new IllegalArgumentException("Can't read partitions file", e);
  }
}
 

/**
 * Read in the partition file and build indexing data structures.
 * If the keytype is {@link org.apache.hadoop.io.BinaryComparable} and
 * <tt>total.order.partitioner.natural.order</tt> is not false, a trie
 * of the first <tt>total.order.partitioner.max.trie.depth</tt>(2) + 1 bytes
 * will be built. Otherwise, keys will be located using a binary search of
 * the partition keyset using the {@link org.apache.hadoop.io.RawComparator}
 * defined for this job. The input file must be sorted with the same
 * comparator and contain {@link
   org.apache.hadoop.mapred.JobConf#getNumReduceTasks} - 1 keys.
 */
@SuppressWarnings("unchecked") // keytype from conf not static
public void configure(JobConf job) {
  try {
    String parts = getPartitionFile(job);
    final Path partFile = new Path(parts);
    final FileSystem fs = (DEFAULT_PATH.equals(parts))
      ? FileSystem.getLocal(job)     // assume in DistributedCache
      : partFile.getFileSystem(job);

    Class<K> keyClass = (Class<K>)job.getMapOutputKeyClass();
    K[] splitPoints = readPartitions(fs, partFile, keyClass, job);
    if (splitPoints.length != job.getNumReduceTasks() - 1) {
      throw new IOException("Wrong number of partitions in keyset");
    }
    RawComparator<K> comparator =
      (RawComparator<K>) job.getOutputKeyComparator();
    for (int i = 0; i < splitPoints.length - 1; ++i) {
      if (comparator.compare(splitPoints[i], splitPoints[i+1]) >= 0) {
        throw new IOException("Split points are out of order");
      }
    }
    boolean natOrder =
      job.getBoolean("total.order.partitioner.natural.order", true);
    if (natOrder && BinaryComparable.class.isAssignableFrom(keyClass)) {
      partitions = buildTrie((BinaryComparable[])splitPoints, 0,
          splitPoints.length, new byte[0],
          job.getInt("total.order.partitioner.max.trie.depth", 2));
    } else {
      partitions = new BinarySearchNode(splitPoints, comparator);
    }
  } catch (IOException e) {
    throw new IllegalArgumentException("Can't read partitions file", e);
  }
}