Hadoop map任务数量的计算

Hadoop中决定map个数的的因素有几个，由于版本的不同，决定因素也不一样，掌握这些因素对了解hadoop分片的划分有很大帮助，

并且对优化hadoop性能也很有大的益处。

旧API中getSplits方法:

public InputSplit[] getSplits(JobConf job, int numSplits)
    throws IOException {
    FileStatus[] files = listStatus(job);
    
    // Save the number of input files in the job-conf
    job.setLong(NUM_INPUT_FILES, files.length);
    long totalSize = 0;                           // compute total size
    for (FileStatus file: files) {                // check we have valid files
      if (file.isDir()) {
        throw new IOException("Not a file: "+ file.getPath());
      }
      totalSize += file.getLen();
    }

    long goalSize = totalSize / (numSplits == 0 ? 1 : numSplits);
    long minSize = Math.max(job.getLong("mapred.min.split.size", 1),
                            minSplitSize);

    // generate splits
    ArrayList<FileSplit> splits = new ArrayList<FileSplit>(numSplits);
    NetworkTopology clusterMap = new NetworkTopology();
    for (FileStatus file: files) {
      Path path = file.getPath();
      FileSystem fs = path.getFileSystem(job);
      long length = file.getLen();
      BlockLocation[] blkLocations = fs.getFileBlockLocations(file, 0, length);
      if ((length != 0) && isSplitable(fs, path)) { 
        long blockSize = file.getBlockSize();
        long splitSize = computeSplitSize(goalSize, minSize, blockSize);

        long bytesRemaining = length;
        while (((double) bytesRemaining)/splitSize > SPLIT_SLOP) {
          String[] splitHosts = getSplitHosts(blkLocations, 
              length-bytesRemaining, splitSize, clusterMap);
          splits.add(new FileSplit(path, length-bytesRemaining, splitSize, 
              splitHosts));
          bytesRemaining -= splitSize;
        }
        
        if (bytesRemaining != 0) {
          splits.add(new FileSplit(path, length-bytesRemaining, bytesRemaining, 
                     blkLocations[blkLocations.length-1].getHosts()));
        }
      } else if (length != 0) {
        String[] splitHosts = getSplitHosts(blkLocations,0,length,clusterMap);
        splits.add(new FileSplit(path, 0, length, splitHosts));
      } else { 
        //Create empty hosts array for zero length files
        splits.add(new FileSplit(path, 0, length, new String[0]));
      }
    }
    LOG.debug("Total # of splits: " + splits.size());
    return splits.toArray(new FileSplit[splits.size()]);
  }

  protected long computeSplitSize(long goalSize, long minSize,
                                       long blockSize) {
    return Math.max(minSize, Math.min(goalSize, blockSize));
  }

新API中getSplits方法：

public List<InputSplit> getSplits(JobContext job
                                    ) throws IOException {
    long minSize = Math.max(getFormatMinSplitSize(), getMinSplitSize(job));
    long maxSize = getMaxSplitSize(job);

    // generate splits
    List<InputSplit> splits = new ArrayList<InputSplit>();
    List<FileStatus>files = listStatus(job);
    for (FileStatus file: files) {
      Path path = file.getPath();
      FileSystem fs = path.getFileSystem(job.getConfiguration());
      long length = file.getLen();
      BlockLocation[] blkLocations = fs.getFileBlockLocations(file, 0, length);
      if ((length != 0) && isSplitable(job, path)) { 
        long blockSize = file.getBlockSize();
        long splitSize = computeSplitSize(blockSize, minSize, maxSize);

        long bytesRemaining = length;
        while (((double) bytesRemaining)/splitSize > SPLIT_SLOP) {
          int blkIndex = getBlockIndex(blkLocations, length-bytesRemaining);
          splits.add(new FileSplit(path, length-bytesRemaining, splitSize, 
                                   blkLocations[blkIndex].getHosts()));
          bytesRemaining -= splitSize;
        }
        
        if (bytesRemaining != 0) {
          splits.add(new FileSplit(path, length-bytesRemaining, bytesRemaining, 
                     blkLocations[blkLocations.length-1].getHosts()));
        }
      } else if (length != 0) {
        splits.add(new FileSplit(path, 0, length, blkLocations[0].getHosts()));
      } else { 
        //Create empty hosts array for zero length files
        splits.add(new FileSplit(path, 0, length, new String[0]));
      }
    }
    
    // Save the number of input files in the job-conf
    job.getConfiguration().setLong(NUM_INPUT_FILES, files.size());

    LOG.debug("Total # of splits: " + splits.size());
    return splits;
  }

  protected long computeSplitSize(long blockSize, long minSize,
                                  long maxSize) {
    return Math.max(minSize, Math.min(maxSize, blockSize));
  }

 测试一个输入文件大小为:0.52 KB 日志如下：

new :
blockSize:67108864 minSize:1 maxSize:9223372036854775807
splitSize:67108864

决定因素为 blockSize的大小.这个很容易理解

old:
blockSize:67108864 totalSize:529 numSplits:2 goalSize:264 minSplitSize:1 minSize:1
splitSize:264

numSplits为2，这个是在调用getSplits中传入的,这个地方要注意，经过查找发现这个参数为job.getNumMapTasks()的值如下

JobConf: public int getNumMapTasks() { return getInt("mapred.map.tasks", 1); }

mapred-default.xml中：

<property>
<name>mapred.map.tasks</name>
<value>2</value>
<description>The default number of map tasks per job.
Ignored when mapred.job.tracker is "local".
</description>
</property>

所以使用旧的API编写的MP程序，会产生2个map，而使用新的API则会产生1个map.