Package storm.trident

Examples of storm.trident.TridentTopology.build()

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    topology.newDRPCStream("reach", drpc).stateQuery(urlToTweeters, new Fields("args"), new MapGet(), new Fields(
        "tweeters")).each(new Fields("tweeters"), new ExpandList(), new Fields("tweeter")).shuffle().stateQuery(
        tweetersToFollowers, new Fields("tweeter"), new MapGet(), new Fields("followers")).each(new Fields("followers"),
        new ExpandList(), new Fields("follower")).groupBy(new Fields("follower")).aggregate(new One(), new Fields(
        "one")).aggregate(new Fields("one"), new Sum(), new Fields("reach"));
    return topology.build();
  }

  public static void main(String[] args) throws Exception {
    LocalDRPC drpc = new LocalDRPC();
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        stream.partitionPersist(factory, fields,  new HBaseUpdater(), new Fields());

        TridentState state = topology.newStaticState(factory);
        stream = stream.stateQuery(state, new Fields("word"), new HBaseQuery(), new Fields("columnName","columnValue"));
        stream.each(new Fields("word","columnValue"), new PrintFunction(), new Fields());
        return topology.build();
    }

    public static void main(String[] args) throws Exception {
        Config conf = new Config();
        conf.setMaxSpoutPending(5);
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            new Fields("resultbatch"))
        .each(new Fields("hashtag", "resultrt", "resultbatch"), new LambdaMerge(), new Fields("result"))
        // Project allows us to keep only the interesting results
        .project(new Fields("result"));

    return topology.build();
  }

  public static void main(String[] args) throws Exception {
    Config conf = new Config();
    conf.setMaxSpoutPending(20);
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        new Count(), new Fields("count")).parallelismHint(16);

    topology.newDRPCStream("words", drpc).each(new Fields("args"), new Split(), new Fields("word")).groupBy(new Fields(
        "word")).stateQuery(wordCounts, new Fields("word"), new MapGet(), new Fields("count")).each(new Fields("count"),
        new FilterNull()).aggregate(new Fields("count"), new Sum(), new Fields("sum"));
    return topology.build();
  }

  public static void main(String[] args) throws Exception {
    Config conf = new Config();
    conf.setMaxSpoutPending(20);
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    topology.newDRPCStream("reach", drpc).stateQuery(urlToTweeters, new Fields("args"), new MapGet(), new Fields(
        "tweeters")).each(new Fields("tweeters"), new ExpandList(), new Fields("tweeter")).shuffle().stateQuery(
        tweetersToFollowers, new Fields("tweeter"), new MapGet(), new Fields("followers")).each(new Fields("followers"),
        new ExpandList(), new Fields("follower")).groupBy(new Fields("follower")).aggregate(new One(), new Fields(
        "one")).aggregate(new Fields("one"), new Sum(), new Fields("reach"));
    return topology.build();
  }

  public static void main(String[] args) throws Exception {
    LocalDRPC drpc = new LocalDRPC();
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      // Classification stream
      toppology.newDRPCStream("classify", localDRPC)
        // Query classifier with text instance
        .each(new Fields("args"), new TwitterSentimentClassifier(), new Fields("sentiment")).project(new Fields("sentiment"));

      cluster.submitTopology(this.getClass().getSimpleName(), new Config(), toppology.build());
      Thread.sleep(4000);

      // Query with DRPC
      test(false, "RT @JazminBianca: I hate Windows 8. I hate Windows 8. I hate Windows 8.", localDRPC);
      test(false, "I don't like Windows 8, I think it's overrated =))", localDRPC);
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          .each(new Fields("args"), new TextInstanceCreator<Integer>(false), new Fields("instance"))

          // Query classifier with text instance
          .stateQuery(classifierState, new Fields("instance"), new ClassifyTextQuery<Integer>("newsClassifier"), new Fields("prediction")).project(new Fields("prediction"));

      cluster.submitTopology(this.getClass().getSimpleName(), new Config(), toppology.build());
      Thread.sleep(4000);

      // Query with DRPC
      for (Integer realClass : ReutersBatchSpout.REUTEURS_EVAL_SAMPLES.keySet()) {
        Integer prediction = extractPrediction(localDRPC.execute("classify", ReutersBatchSpout.REUTEURS_EVAL_SAMPLES.get(realClass)));
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        // Query kmeans to classify instance
        .stateQuery(kmeansState, new Fields("instance"), new ClusterQuery("kmeans"), new Fields("prediction"))
         
        .project(new Fields("prediction"));

      cluster.submitTopology(this.getClass().getSimpleName(), new Config(), toppology.build());

      Thread.sleep(10000);

      Integer result11 = extractPrediction(localDRPC.execute("predict", "1.0 1.0 1.0"));
      Integer result12 = extractPrediction(localDRPC.execute("predict", "0.8 1.1 0.9"));
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      // Evaluation stream
      toppology.newDRPCStream("evaluate", localDRPC) //
          .stateQuery(perceptronEvaluation, new EvaluationQuery<Boolean>(), new Fields("eval")) //
          .project(new Fields("eval"));

      cluster.submitTopology(this.getClass().getSimpleName(), new Config(), toppology.build());
      Thread.sleep(4000);

      assertEquals(Boolean.TRUE, extractPrediction(localDRPC.execute("predict", "1.0 0.0 0.0")));
      assertEquals(Boolean.TRUE, extractPrediction(localDRPC.execute("predict", "1.0 0.0 1.0")));
      assertEquals(Boolean.TRUE, extractPrediction(localDRPC.execute("predict", "1.0 1.0 0.0")));
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          // Query scaled stream statistics
          .stateQuery(scaledStreamStatistics, new Fields("featureIndex", "queryType"), new StreamFeatureStatisticsQuery("scaledStreamStats"), new Fields("stats"))
          .project(new Fields("stats"));

      cluster.submitTopology("testStandardScaler", new Config(), toppology.build());

      Thread.sleep(8000);

      double mean0 = extractDouble(localDRPC.execute("queryStats", "[[0, \"MEAN\"]]"));
      double mean1 = extractDouble(localDRPC.execute("queryStats", "[[1, \"MEAN\"]]"));
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