Package com.datasalt.pangool.examples.topicalwordcount.TopicalWordCount

Examples of com.datasalt.pangool.examples.topicalwordcount.TopicalWordCount.CountReducer


    // Note that we don't need to use the DistributedCache for that becasuse mappers, reducers, etc themselves are instantiable
    StopWordMapper mapper = new StopWordMapper(stopWords);
    cg.addInput(new Path(args[0]), new HadoopInputFormat(TextInputFormat.class), mapper);
    // We'll use a TupleOutputFormat with the same schema than the intermediate schema
    cg.setTupleOutput(new Path(args[1]), TopicalWordCount.getSchema());
    cg.setTupleReducer(new CountReducer());
    cg.setTupleCombiner(new CountReducer());

    cg.createJob().waitForCompletion(true);

    return 1;
  }
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    // Note that we don't need to use the DistributedCache for that becasuse mappers, reducers, etc themselves are instantiable
    StopWordMapper mapper = new StopWordMapper(stopWords);
    cg.addInput(new Path(args[0]), new HadoopInputFormat(TextInputFormat.class), mapper);
    // We'll use a TupleOutputFormat with the same schema than the intermediate schema
    cg.setTupleOutput(new Path(args[1]), TopicalWordCount.getSchema());
    cg.setTupleReducer(new CountReducer());
    cg.setTupleCombiner(new CountReducer());

    cg.createJob().waitForCompletion(true);

    return 1;
  }
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    // instantiable
    StopWordMapper mapper = new StopWordMapper(stopWords);
    cg.addInput(new Path(args[0]), new HadoopInputFormat(TextInputFormat.class), mapper);
    // We'll use a TupleOutputFormat with the same schema than the intermediate schema
    cg.setTupleOutput(new Path(args[1]), TopicalWordCount.getSchema());
    cg.setTupleReducer(new CountReducer());
    cg.setTupleCombiner(new CountReducer());

    try {
      cg.createJob().waitForCompletion(true);
    } finally {
      cg.cleanUpInstanceFiles();
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