Examples of org.apache.flink.api.java.ExecutionEnvironment.fromElements()

Class org.apache.flink.api.java.ExecutionEnvironment

Examples of org.apache.flink.api.java.ExecutionEnvironment.fromElements()

org.apache.flink.api.java.ExecutionEnvironment.fromElements()
Creates a new data set that contains the given elements. The elements must all be of the same type, for example, all of the {@link String} or {@link Integer}. The sequence of elements must not be empty. Furthermore, the elements must be serializable (as defined in {@link java.io.Serializable}, because the execution environment may ship the elements into the cluster.
The framework will try and determine the exact type from the collection elements. In case of generic elements, it may be necessary to manually supply the type information via {@link #fromCollection(Collection,TypeInformation)}.
Note that this operation will result in a non-parallel data source, i.e. a data source with a degree of parallelism of one. @param data The elements to make up the data set. @return A DataSet representing the given list of elements.

    
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.setDegreeOfParallelism(DEFAULT_PARALLELISM);
    
    @SuppressWarnings("unchecked")
    DataSet<Tuple3<Long, Long, Long>> bigInput = env.fromElements(new Tuple3<Long, Long, Long>(1L, 2L, 3L),
        new Tuple3<Long, Long, Long>(1L, 2L, 3L),new Tuple3<Long, Long, Long>(1L, 2L, 3L)).name("Big");
    
    @SuppressWarnings("unchecked")
    DataSet<Tuple3<Long, Long, Long>> smallInput = env.fromElements(new Tuple3<Long, Long, Long>(1L, 2L, 3L)).name("Small");

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    @SuppressWarnings("unchecked")
    DataSet<Tuple3<Long, Long, Long>> bigInput = env.fromElements(new Tuple3<Long, Long, Long>(1L, 2L, 3L),
        new Tuple3<Long, Long, Long>(1L, 2L, 3L),new Tuple3<Long, Long, Long>(1L, 2L, 3L)).name("Big");
    
    @SuppressWarnings("unchecked")
    DataSet<Tuple3<Long, Long, Long>> smallInput = env.fromElements(new Tuple3<Long, Long, Long>(1L, 2L, 3L)).name("Small");
    
    IterativeDataSet<Tuple3<Long, Long, Long>> iteration = bigInput.iterate(10);
    
    Configuration joinStrategy = new Configuration();
    joinStrategy.setString(PactCompiler.HINT_LOCAL_STRATEGY, strategy);

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  public static void main(String[] args) throws Exception {
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    
    DataSet<Long> vertexIds = env.generateSequence(0, 10);
    DataSet<Tuple2<Long, Long>> edges = env.fromElements(new Tuple2<Long, Long>(0L, 2L), new Tuple2<Long, Long>(2L, 4L), new Tuple2<Long, Long>(4L, 8L),
                              new Tuple2<Long, Long>(1L, 5L), new Tuple2<Long, Long>(3L, 7L), new Tuple2<Long, Long>(3L, 9L));
    
    DataSet<Tuple2<Long, Long>> initialVertices = vertexIds.map(new IdAssigner());
    
    DataSet<Tuple2<Long, Long>> result = initialVertices.runOperation(VertexCentricIteration.withPlainEdges(edges, new CCUpdater(), new CCMessager(), 100));

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    // this is an artificial program, it does not compute anything sensical
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    
    @SuppressWarnings("unchecked")
    DataSet<Tuple2<Long, Double>> initialData = env.fromElements(new Tuple2<Long, Double>(1L, 1.0), new Tuple2<Long, Double>(2L, 2.0),
                              new Tuple2<Long, Double>(3L, 3.0), new Tuple2<Long, Double>(4L, 4.0),
                              new Tuple2<Long, Double>(5L, 5.0), new Tuple2<Long, Double>(6L, 6.0));
    
    DataSet<Tuple2<Long, Double>> result = MultipleJoinsWithSolutionSetCompilerTest.constructPlan(initialData, NUM_ITERS);

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  @Override
  protected void testProgram() throws Exception {
    
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    
    DataSet<Integer> data = env.fromElements(1, 2, 3, 4, 5, 6, 7, 8);
    
    IterativeDataSet<Integer> iteration = data.iterate(10);
    
    DataSet<Integer> result = data.reduceGroup(new PickOneAllReduce()).withBroadcastSet(iteration, "bc");

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  protected void testProgram() throws Exception {
    
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
    env.setDegreeOfParallelism(4);
    
    DataSet<Integer> data = env.fromElements(1, 2, 3, 4, 5, 6, 7, 8);
    
    IterativeDataSet<Integer> iteration = data.iterate(10);
    
    DataSet<Integer> result = data.reduceGroup(new PickOneAllReduce()).withBroadcastSet(iteration, "bc");

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    try {
      
      ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
      
      @SuppressWarnings("unchecked")
      DataSet<Tuple2<Long, Double>> inputData = env.fromElements(new Tuple2<Long, Double>(1L, 1.0));
      DataSet<Tuple2<Long, Double>> result = constructPlan(inputData, 10);
      
      // add two sinks, to test the case of branching after an iteration
      result.print();
      result.print();

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  public void testPageRank() {
    try {
      final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
      
      // get input data
      DataSet<Long> pagesInput = env.fromElements(1l);
      @SuppressWarnings("unchecked")
      DataSet<Tuple2<Long, Long>> linksInput =env.fromElements(new Tuple2<Long, Long>(1l, 2l));
      
      // assign initial rank to pages
      DataSet<Tuple2<Long, Double>> pagesWithRanks = pagesInput.

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      final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
      
      // get input data
      DataSet<Long> pagesInput = env.fromElements(1l);
      @SuppressWarnings("unchecked")
      DataSet<Tuple2<Long, Long>> linksInput =env.fromElements(new Tuple2<Long, Long>(1l, 2l));
      
      // assign initial rank to pages
      DataSet<Tuple2<Long, Double>> pagesWithRanks = pagesInput.
          map(new RankAssigner((1.0d / 10)));

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      // compose test program
      {
        DataSet<Long> vertexIds = env.generateSequence(1, 2);
        
        @SuppressWarnings("unchecked")
        DataSet<Tuple2<Long, Long>> edges = env.fromElements(new Tuple2<Long, Long>(1L, 2L));
        
        DataSet<Tuple2<Long, Long>> initialVertices = vertexIds.map(new IdAssigner());
        DataSet<Tuple2<Long, Long>> result = initialVertices.runOperation(VertexCentricIteration.withPlainEdges(edges, new CCUpdater(), new CCMessager(), 100));
        
        result.print();

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