1 常用输入格式

InputFormat层级.JPG

2 自定义InputFormat的流程

1）如果是文本格式的数据，那么实现一个XXInputForamt继承FileInputFormat
2）重写 FileInputFormat 里面的 isSplitable() 方法。如果文件是压缩文件的话则不能切割，一般都是支持切割
3）重写 FileInputFormat 里面的 createRecordReader()方法
4）自定义XXRecordReader，来读取特定的格式

XXRecordReader中需要重点实现以下两个的方法
        @Override
        public void initialize(InputSplit input, TaskAttemptContext context)
                throws IOException, InterruptedException {
            FileSplit split=(FileSplit)input;
            Configuration job=context.getConfiguration();
            Path file=split.getPath();
            FileSystem fs=file.getFileSystem(job);
           
            FSDataInputStream fileIn=fs.open(file);
            //红色标记这部分对于文本型数据来说基本是一样的
            in=new LineReader(fileIn,job);
            line=new Text();
            lineKey=new Text();
            lineValue = new Text();
        }

        //此方法读取每行数据，完成自定义的key和value
        @Override
        public boolean nextKeyValue() throws IOException, InterruptedException {
            int linesize=in.readLine(line);//每行数据
            if(linesize==0) return false;
            String[] pieces = line.toString().split("\\s+");//解析每行数据
            ...
            lineKey.set(“key”);//完成自定义key数据
            lineValue.set(“value”);//封装自定义value数据
            return true;
        }       

3 多个输入

1）如果输入格式存在多种，可以设置不同Mapper处理不同的数据源

MultipleInputs.addInputPath(job,ncdcInputPath,TextInputFormat.class,NCDCTemperatureMapper.class);

2）存在多种输入格式，而只有一个Mapper则可使用

public static void addInputPath(Job job,Path path,class< ? extends InputFormat> inputFormatClass);
使用job.setMapperClass();

4. InputFormat及其子类解决的是针对不同的数据格式分片和读取问题

4.1 getSplits方法中实现如何分片?

1）根据不同的数据来源采取不同的切片方式
例子1：文本格式的数据来源
通过计算确认splitSize的大小，假如输入文件为100M，那么splitSize则为64M，那么文件会被切分为64M和36M两个分片输出。

public List<InputSplit> getSplits(JobContext job) throws IOException {
    StopWatch sw = new StopWatch().start();
    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();
      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);
        }
        if (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(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;
  }

例子2：数据来源为数据库
通过查询需要读取的条数，然后再除以map_task数，得出每个map_task需要处理的条数，进行切分

public List<InputSplit> getSplits(JobContext job) throws IOException {

    ResultSet results = null;  
    Statement statement = null;
    try {
      statement = connection.createStatement();

      results = statement.executeQuery(getCountQuery());//查询总条数
      results.next();

      long count = results.getLong(1);
      int chunks = job.getConfiguration().getInt(MRJobConfig.NUM_MAPS, 1);
      long chunkSize = (count / chunks);

      results.close();
      statement.close();

      List<InputSplit> splits = new ArrayList<InputSplit>();

      // Split the rows into n-number of chunks and adjust the last chunk
      // accordingly
      for (int i = 0; i < chunks; i++) {
        DBInputSplit split;

        if ((i + 1) == chunks)
          split = new DBInputSplit(i * chunkSize, count);
        else
          split = new DBInputSplit(i * chunkSize, (i * chunkSize)
              + chunkSize);

        splits.add(split);
      }

      connection.commit();
      return splits;
    } catch (SQLException e) {
      throw new IOException("Got SQLException", e);
    } finally {
      try {
        if (results != null) { results.close(); }
      } catch (SQLException e1) {}
      try {
        if (statement != null) { statement.close(); }
      } catch (SQLException e1) {}

      closeConnection();
    }
  }

2）RecordReader类实现如何读取数据
一般的文本格式一般使用LineRecordReader进行读取，然后根据需求进行处理