Package org.apache.crunch.impl.mr

Examples of org.apache.crunch.impl.mr.MRPipeline.writeTextFile()

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    String outputA = tmpDir.getFileName("stringsA");
    String outputB = tmpDir.getFileName("stringsB");

    pipeline.writeTextFile(stringsA, outputA);
    pipeline.writeTextFile(stringsB, outputB);
    PipelineResult pipelineResult = pipeline.done();

    // Make sure fusing did actually occur
    assertEquals(1, pipelineResult.getStageResults().size());
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    // Calculate average response size by ip address
    PTable<String, Double> avgs = remoteAddrResponseSize.parallelDo(calulateAverage,
        Writables.tableOf(Writables.strings(), Writables.doubles()));

    // write the result to a text file
    pipeline.writeTextFile(avgs, args[1]);
    // Execute the pipeline as a MapReduce.
    PipelineResult result = pipeline.done();

    return result.succeeded() ? 0 : 1;
  }
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    // Table of (ip, sum(response size))
    PTable<String, Long> ipAddrResponseSize = lines
        .parallelDo(extractIPResponseSize, Writables.tableOf(Writables.strings(), Writables.longs())).groupByKey()
        .combineValues(agg);

    pipeline.writeTextFile(ipAddrResponseSize, args[1]);
    // Execute the pipeline as a MapReduce.
    PipelineResult result = pipeline.done();

    return result.succeeded() ? 0 : 1;
  }
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    // Best of all, the count() function doesn't need to know anything about
    // the kind of data stored in the input PCollection.
    PTable<String, Long> counts = words.count();

    // Instruct the pipeline to write the resulting counts to a text file.
    pipeline.writeTextFile(counts, args[1]);
    // Execute the pipeline as a MapReduce.
    PipelineResult result = pipeline.done();

    return result.succeeded() ? 0 : 1;
  }
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        // The count method applies a series of Crunch primitives and returns
        // a map of the unique words in the input PCollection to their counts.
        PTable<String, Long> counts = noStopWords.count();

        // Instruct the pipeline to write the resulting counts to a text file.
        pipeline.writeTextFile(counts, outputPath);

        // Execute the pipeline as a MapReduce.
        PipelineResult result = pipeline.done();

        return result.succeeded() ? 0 : 1;
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