Package eu.stratosphere.api.java.record.operators

Examples of eu.stratosphere.api.java.record.operators.ReduceOperator

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    iteration.setInput(initialInput);
    iteration.setMaximumNumberOfIterations(5);
   
    Assert.assertTrue(iteration.getMaximumNumberOfIterations() > 1);

    ReduceOperator sumReduce = ReduceOperator.builder(new PickOneReducer())
        .input(iteration.getPartialSolution())
        .name("Compute sum (Reduce)")
        .build();
   
    iteration.setNextPartialSolution(sumReduce);
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    // construct the plan
    FileDataSource source = new FileDataSource(new DummyInputFormat(), IN_FILE, "Source");
   
    MapOperator map = MapOperator.builder(new IdentityMap()).name("Map1").input(source).build();
   
    ReduceOperator reduce1 = ReduceOperator.builder(new IdentityReduce(), IntValue.class, 0).name("Reduce1").input(map).build();
   
    CrossOperator cross1 = CrossOperator.builder(new DummyCrossStub()).name("Cross1").input1(reduce1).input2(source).build();
   
    ReduceOperator reduce2 = ReduceOperator.builder(new IdentityReduce(), IntValue.class, 0).name("Reduce2").input(cross1).build();
   
    CrossOperator cross2 = CrossOperator.builder(new DummyCrossStub()).name("Cross2").input1(reduce2).input2(source).build();
   
    ReduceOperator reduce3 = ReduceOperator.builder(new IdentityReduce(), IntValue.class, 0).name("Reduce3").input(cross2).build();
   
    FileDataSink sink = new FileDataSink(new DummyOutputFormat(), OUT_FILE, "Sink");
    sink.setInput(reduce3);
   
    Plan plan = new Plan(sink, "Test Temp Task");
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        JoinOperator.builder(JoinLiO.class, IntValue.class, 0, 0)
      .name("OrdersLineitemsJoin")
      .build();
      join.setDegreeOfParallelism(degreeOfParallelism);
   
    ReduceOperator aggregation =
        ReduceOperator.builder(CountAgg.class, StringValue.class, 0)
      .name("AggregateGroupBy")
      .build();
    aggregation.setDegreeOfParallelism(this.degreeOfParallelism);
   
    lineFilter.setInput(lineItems);
    ordersFilter.setInput(orders);
    join.setFirstInput(ordersFilter);
    join.setSecondInput(lineFilter);
    aggregation.setInput(join);
    result.setInput(aggregation);
   
     
    return new Plan(result, "TPC-H 4");
  }
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  @Test
  public void testReduce() {
    // construct the plan
    FileDataSource source = new FileDataSource(new DummyInputFormat(), IN_FILE, "Source");
    ReduceOperator reduce1 = ReduceOperator.builder(new IdentityReduce()).name("Reduce1").input(source).build();
    FileDataSink sink = new FileDataSink(new DummyOutputFormat(), OUT_FILE, "Sink");
    sink.setInput(reduce1);
    Plan plan = new Plan(sink, "AllReduce Test");
    plan.setDefaultParallelism(DEFAULT_PARALLELISM);
   
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    MapOperator projectOutCounts = MapOperator.builder(new ProjectOutCounts())
        .input(edges)
        .name("Project to vertex Ids only")
        .build();

    ReduceOperator buildTriads = ReduceOperator.builder(new BuildTriads(), IntValue.class, 0)
        .input(toLowerDegreeEdge)
        .name("Build Triads")
        .build();

    JoinOperator closeTriads = JoinOperator.builder(new CloseTriads(), IntValue.class, 1, 0)
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        .input2(edges)
        .name("Join Candidate Id With Neighbor")
        .build();

    // create ReduceOperator for finding the nearest cluster centers
    ReduceOperator minCandidateId = ReduceOperator.builder(new MinimumComponentIDReduce(), LongValue.class, 0)
        .input(joinWithNeighbors)
        .name("Find Minimum Candidate Id")
        .build();
   
    // create CrossOperator for distance computation
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  @Test
  public void testReduceWithGroupOrder() {
    // construct the plan
    FileDataSource source = new FileDataSource(new DummyInputFormat(), IN_FILE, "Source");
   
    ReduceOperator reduce = ReduceOperator.builder(new IdentityReduce()).keyField(IntValue.class, 2).name("Reduce").input(source).build();
    Ordering groupOrder = new Ordering(5, StringValue.class, Order.DESCENDING);
    reduce.setGroupOrder(groupOrder);
   
    FileDataSink sink = new FileDataSink(new DummyOutputFormat(), OUT_FILE, reduce, "Sink");
   
   
    Plan plan = new Plan(sink, "Test Temp Task");
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    // =========================== Vertex Degree ============================
   
    MapOperator projectEdge = MapOperator.builder(new ProjectEdge())
        .input(edges).name("Project Edge").build();
   
    ReduceOperator edgeCounter = ReduceOperator.builder(new CountEdges(), IntValue.class, 0)
        .input(projectEdge).name("Count Edges for Vertex").build();
   
    ReduceOperator countJoiner = ReduceOperator.builder(new JoinCountsAndUniquify(), IntValue.class, 0)
        .keyField(IntValue.class, 1)
        .input(edgeCounter).name("Join Counts").build();
   
   
    // =========================== Triangle Enumeration ============================
   
    MapOperator toLowerDegreeEdge = MapOperator.builder(new ProjectToLowerDegreeVertex())
        .input(countJoiner).name("Select lower-degree Edge").build();
   
    MapOperator projectOutCounts = MapOperator.builder(new ProjectOutCounts())
        .input(countJoiner).name("Project out Counts").build();

    ReduceOperator buildTriads = ReduceOperator.builder(new BuildTriads(), IntValue.class, 0)
        .input(toLowerDegreeEdge).name("Build Triads").build();

    JoinOperator closeTriads = JoinOperator.builder(new CloseTriads(), IntValue.class, 1, 0)
        .keyField(IntValue.class, 2, 1)
        .input1(buildTriads).input2(projectOutCounts)
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      .name("JoinCO")
      .build();
    joinCO.setDegreeOfParallelism(numSubtasks);

    // create ReduceOperator for aggregating the result
    ReduceOperator aggCO = ReduceOperator.builder(new AggCO(), StringValue.class, 1)
      .name("AggCo")
      .build();
    aggCO.setDegreeOfParallelism(numSubtasks);

    // create DataSinkContract for writing the result
    FileDataSink result = new FileDataSink(new CsvOutputFormat(), output, "Output");
    result.setDegreeOfParallelism(numSubtasks);
    CsvOutputFormat.configureRecordFormat(result)
      .recordDelimiter('\n')
      .fieldDelimiter('|')
      .field(IntValue.class, 0)
      .field(StringValue.class, 1);

    // assemble the plan
    result.setInput(aggCO);
    aggCO.setInput(joinCO);
    joinCO.setFirstInput(orders);
    joinCO.setSecondInput(customers);

    return new Plan(result, "TPCH Asterix");
  }
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      MapOperator.builder(new LineItemFilter())
      .name("LineItem Filter")
      .build();
    lineItemFilter.setDegreeOfParallelism(this.degreeOfParallelism);
   
    ReduceOperator groupByReturnFlag =
      ReduceOperator.builder(new GroupByReturnFlag(), StringValue.class, 0)
      .name("groupyBy")
      .build();
   
    lineItemFilter.setInput(lineItems);
    groupByReturnFlag.setInput(lineItemFilter);
    result.setInput(groupByReturnFlag);
   
    return new Plan(result, "TPC-H 1");
  }
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