Package org.apache.hadoop.mapreduce.lib.input

Examples of org.apache.hadoop.mapreduce.lib.input.TextInputFormat

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    FileInputFormat.setInputPaths(job, dataPath);

    setMaxSplitSize(job.getConfiguration(), dataPath, numMaps);

    // retrieve the splits
    TextInputFormat input = new TextInputFormat();
    List<InputSplit> splits = input.getSplits(job);
    assertEquals(numMaps, splits.size());

    InputSplit[] sorted = new InputSplit[numMaps];
    splits.toArray(sorted);
    Builder.sortSplits(sorted);

    Step0Context context = new Step0Context(new Step0Mapper(), job.getConfiguration(),
                                            new TaskAttemptID(), numMaps);

    for (int p = 0; p < numMaps; p++) {
      InputSplit split = sorted[p];

      RecordReader<LongWritable, Text> reader = input.createRecordReader(split,
                                                                         context);
      reader.initialize(split, context);

      Step0Mapper mapper = new Step0Mapper();
      mapper.configure(p);
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    FileInputFormat.setInputPaths(job, dataPath);

    setMaxSplitSize(job.getConfiguration(), dataPath, numMaps);

    // retrieve the splits
    TextInputFormat input = new TextInputFormat();
    List<InputSplit> splits = input.getSplits(job);
    assertEquals(numMaps, splits.size());

    InputSplit[] sorted = new InputSplit[numMaps];
    splits.toArray(sorted);
    Builder.sortSplits(sorted);

    List<Integer> keys = new ArrayList<Integer>();
    List<Step0Output> values = new ArrayList<Step0Output>();

    int[] expectedIds = new int[numMaps];

    TaskAttemptContext context = new TaskAttemptContext(job.getConfiguration(),
        new TaskAttemptID());

    for (int p = 0; p < numMaps; p++) {
      InputSplit split = sorted[p];
      RecordReader<LongWritable, Text> reader = input.createRecordReader(split,
          context);
      reader.initialize(split, context);

      Long firstKey = null;
      int size = 0;
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        InputFormat result = null;
        if(inputAvroSchema != null) {
            result = new PigAvroInputFormat(
            inputAvroSchema, ignoreBadFiles, schemaToMergedSchemaMap, useMultipleSchemas);
        } else {
            result = new TextInputFormat();
        }
        return result;
    }
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    FileInputFormat.setInputPaths(job, location);
  }
 
  @Override
  public InputFormat getInputFormat() {
    return new TextInputFormat();
  }
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    @SuppressWarnings("unchecked")
    public InputFormat getInputFormat() throws IOException {
        // We will use TextInputFormat, the default Hadoop input format for
        // text.  It has a LongWritable key that we will ignore, and the value
        // is a Text (a string writable) that the JSON data is in.
        return new TextInputFormat();
    }
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    @SuppressWarnings("unchecked")
    public InputFormat getInputFormat() throws IOException {
        // We will use TextInputFormat, the default Hadoop input format for
        // text.  It has a LongWritable key that we will ignore, and the value
        // is a Text (a string writable) that the JSON data is in.
        return new TextInputFormat();
    }
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        InputFormat result = null;
        if(inputAvroSchema != null) {
            result = new PigAvroInputFormat(
            inputAvroSchema, ignoreBadFiles, schemaToMergedSchemaMap, useMultipleSchemas);
        } else {
            result = new TextInputFormat();
        }
        return result;
    }
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     * Methods called on the frontend
     */

    @Override
    public InputFormat getInputFormat() throws IOException {
        return new TextInputFormat();
    }
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  }
 
  @SuppressWarnings("unchecked")
  @Override
  public InputFormat getInputFormat() throws IOException {
      return new TextInputFormat();
  }
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        }
    }
   
    @Override
    public InputFormat getInputFormat() {
        return new TextInputFormat();
    }
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