Hadoop文件切分的源码

Hadoop文件的切分原则：
一 按每个文件切分
二 文件大小/分片大小《=1.1则划分为一个文件，否则切分为2个文件
三 一个切片一个Maptask,一个Maptask代表一个并行度
分片默认设置

分片切分的核心源码

public List getSplits(JobContext job) throws IOException {
  StopWatch sw = new StopWatch().start();
  long minSize = Math.max(getFormatMinSplitSize(), getMinSplitSize(job));
  long maxSize = getMaxSplitSize(job);

  // generate splits
  List splits = new ArrayList();
  List files = listStatus(job);

  boolean ignoreDirs = !getInputDirRecursive(job)
    && job.getConfiguration().getBoolean(INPUT_DIR_NONRECURSIVE_IGNORE_SUBDIRS, false);
    //循环文件
  for (FileStatus file: files) {
    if (ignoreDirs && file.isDirectory()) {
      continue;
    }
    //获取文件的长度值
    Path path = file.getPath();
    long length = file.getLen();
    if (length != 0) {
      BlockLocation[] blkLocations;
      if (file instanceof LocatedFileStatus) {
        blkLocations = ((LocatedFileStatus) file).getBlockLocations();
      } else {
        FileSystem fs = path.getFileSystem(job.getConfiguration());
        blkLocations = fs.getFileBlockLocations(file, 0, length);
      }
      //是否支持切割
      if (isSplitable(job, path)) {
        long blockSize = file.getBlockSize();
        //由集群指定的块大小，最小和最大 下面对切片大小有描述
        long splitSize = computeSplitSize(blockSize, minSize, maxSize);

        long bytesRemaining = length;
        //判断是否可以切成一块，如果大于1.1切成两片，如果小于1.1形成一片
        while (((double) bytesRemaining)/splitSize > SPLIT_SLOP) {
          int blkIndex = getBlockIndex(blkLocations, length-bytesRemaining);
          splits.add(makeSplit(path, length-bytesRemaining, splitSize,
                      blkLocations[blkIndex].getHosts(),
                      blkLocations[blkIndex].getCachedHosts()));
          bytesRemaining -= splitSize;
        }

        if (bytesRemaining != 0) {
          int blkIndex = getBlockIndex(blkLocations, length-bytesRemaining);
          splits.add(makeSplit(path, length-bytesRemaining, bytesRemaining,
                     blkLocations[blkIndex].getHosts(),
                     blkLocations[blkIndex].getCachedHosts()));
        }
      } else { // not splitable
        if (LOG.isDebugEnabled()) {
          // Log only if the file is big enough to be splitted
          if (length > Math.min(file.getBlockSize(), minSize)) {
            LOG.debug("File is not splittable so no parallelization "
                + "is possible: " + file.getPath());
          }
        }
        splits.add(makeSplit(path, 0, length, blkLocations[0].getHosts(),
                    blkLocations[0].getCachedHosts()));
      }
    } else { 
      //Create empty hosts array for zero length files
      splits.add(makeSplit(path, 0, length, new String[0]));
    }
  }
  // Save the number of input files for metrics/loadgen
  job.getConfiguration().setLong(NUM_INPUT_FILES, files.size());
  sw.stop();
  if (LOG.isDebugEnabled()) {
    LOG.debug("Total # of splits generated by getSplits: " + splits.size()
        + ", Timetaken: " + sw.now(TimeUnit.MILLISECONDS));
  }
  return splits;
}

修改分片规则

//取maxsize和blocksize的最小值
//可以控制minsize和maxsize来控制切片大小
protected long computeSplitSize(long blockSize, long minSize,
                                long maxSize) {
  return Math.max(minSize, Math.min(maxSize, blockSize));
}

流程的总结