Package org.apache.flink.streaming.api.environment

Examples of org.apache.flink.streaming.api.environment.StreamExecutionEnvironment

35
36
37
38
39
40
41
42
43
44
45
46
47
48
  }

  private static final int PARALLELISM = 1;

  public static void main(String[] args) throws Exception {
    StreamExecutionEnvironment env = StreamExecutionEnvironment
        .createLocalEnvironment(PARALLELISM);

    DataStream<String> stream = env.fromElements(WordCountData.WORDS).map(new IdentityMap());

    stream.print();

    env.execute();
  }
View Full Code Here
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
    List<Tuple2<Double, Integer>> input = new ArrayList<Tuple2<Double, Integer>>();
    for (int i = 0; i < 100; i++) {
      input.add(new Tuple2<Double, Integer>(0., 0));
    }

    StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment(2)
        .setBufferTimeout(1);

    IterativeDataStream<Tuple2<Double, Integer>> it = env.fromCollection(input).iterate()
        .setMaxWaitTime(3000);
   
    SplitDataStream<Tuple2<Double,Integer>> step = it.map(new Step()).shuffle().setParallelism(2).split(new MySelector());
   
    it.closeWith(step.select("iterate"));
   
    step.select("output").project(1).types(Integer.class).print();

    env.execute();
  }
View Full Code Here
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
    } else {
      System.err.println("USAGE:\nTwitterLocal <pathToPropertiesFile>");
      return;
    }

    StreamExecutionEnvironment env = StreamExecutionEnvironment
        .createLocalEnvironment(PARALLELISM);

    DataStream<String> streamSource = env.addSource(new TwitterSource(path, NUMBEROFTWEETS),
        SOURCE_PARALLELISM);


    DataStream<Tuple2<String, Integer>> dataStream = streamSource
        .flatMap(new SelectLanguageFlatMap())
        .partitionBy(0)
        .map(new MapFunction<String, Tuple2<String, Integer>>() {

          private static final long serialVersionUID = 1L;
         
          @Override
          public Tuple2<String, Integer> map(String value) throws Exception {
            return new Tuple2<String, Integer>(value, 1);
          }
        })
        .groupBy(0)
        .sum(1);

    dataStream.print();

    env.execute();
  }
View Full Code Here
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
    } else {
      System.err.println("USAGE:\nTwitterStreaming <pathToPropertiesFile>");
      return;
    }

    StreamExecutionEnvironment env = StreamExecutionEnvironment
        .createLocalEnvironment(PARALLELISM);

    DataStream<String> streamSource = env.addSource(new TwitterSource(path, NUMBEROFTWEETS),
        SOURCE_PARALLELISM);

    DataStream<Tuple5<Long, Integer, String, String, String>> selectedDataStream = streamSource
        .flatMap(new SelectDataFlatMap());

    selectedDataStream.addSink(new TwitterSink());

    env.execute();
  }
View Full Code Here
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
  private static final int PARALLELISM = 1;
  private static final int SOURCE_PARALLELISM = 1;

  public static void main(String[] args) throws Exception {

    StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment(
        PARALLELISM).setBufferTimeout(1000);

    // Build new model on every second of new data
    DataStream<Double[]> model = env.addSource(new TrainingDataSource(), SOURCE_PARALLELISM)
        .window(5000).reduceGroup(new PartialModelBuilder());

    // Use partial model for prediction
    DataStream<Integer> prediction = env.addSource(new NewDataSource(), SOURCE_PARALLELISM)
        .connect(model).map(new Predictor());

    prediction.print();

    env.execute();
  }
View Full Code Here
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
  // This example will join two streams. One which emits people's grades and
  // one which emits people's salaries.

  public static void main(String[] args) throws Exception {

    StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment(
        PARALLELISM).setBufferTimeout(100);

    DataStream<Tuple2<String, Integer>> grades = env.addSource(new GradeSource(),
        SOURCE_PARALLELISM);
   
    DataStream<Tuple2<String, Integer>> salaries = env.addSource(new SalarySource(),
        SOURCE_PARALLELISM);

    DataStream<Tuple3<String, Integer, Integer>> joinedStream = grades.connect(salaries)
        .flatMap(new JoinTask());
   
    System.out.println("(NAME, GRADE, SALARY)");
    joinedStream.print();

    env.execute();

  }
View Full Code Here
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
    if (!parseParameters(args)) {
      return;
    }

    // set up the execution environment
    final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

    // get input data
    DataStream<String> text = getTextDataStream(env);

    DataStream<Tuple2<String, Integer>> counts =
        // split up the lines in pairs (2-tuples) containing: (word,1)
        text.flatMap(new Tokenizer())
        // group by the tuple field "0" and sum up tuple field "1"
        .groupBy(0)
        .sum(1);

    // emit result
    if (fileOutput) {
      counts.writeAsText(outputPath, 1);
    } else {
      counts.print();
    }

    // execute program
    env.execute("Streaming WordCount");
  }
View Full Code Here
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
    if (!parseParameters(args)) {
      return;
    }

    // set up the execution environment
    StreamExecutionEnvironment env = StreamExecutionEnvironment
        .createLocalEnvironment(PARALLELISM);

    env.setBufferTimeout(1000);
   
    // get input data
    DataStream<String> streamSource = getTextDataStream(env);

    DataStream<Tuple2<String, Integer>> dataStream = streamSource
        // selecting english tweets and split to words
        .flatMap(new SelectEnglishAndTokenizeFlatMap())
        .partitionBy(0)
        // returning (word, 1)
        .map(new MapFunction<String, Tuple2<String, Integer>>() {
          private static final long serialVersionUID = 1L;

          @Override
          public Tuple2<String, Integer> map(String value)
              throws Exception {
            return new Tuple2<String, Integer>(value, 1);
          }
        })
        // group by words and sum their occurence
        .groupBy(0)
        .sum(1)
        // select maximum occurenced word
        .flatMap(new SelectMaxOccurence());

    // emit result
    dataStream.print();

    // execute program
    env.execute();
  }
View Full Code Here
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
  }

  public static void main(String[] args) throws Exception {

    StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment(1);

    @SuppressWarnings("unused")
    DataStream<String> dataStream1 = env.addSource(new MyFlumeSource("localhost", 41414))
        .addSink(new MyFlumePrintSink());

    @SuppressWarnings("unused")
    DataStream<String> dataStream2 = env.fromElements("one", "two", "three", "four", "five",
        "q").addSink(new MyFlumeSink("localhost", 42424));

    env.execute();
  }
View Full Code Here
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
  }

  public static void main(String[] args) throws Exception {

    StreamExecutionEnvironment env = StreamExecutionEnvironment.createLocalEnvironment(1);

    @SuppressWarnings("unused")
    DataStream<String> dataStream1 = env
      .addSource(new MyRMQSource("localhost", "hello"))
      .addSink(new MyRMQPrintSink());

    @SuppressWarnings("unused")
    DataStream<String> dataStream2 = env
      .fromElements("one", "two", "three", "four", "five", "q")
      .addSink(new MyRMQSink("localhost", "hello"));

    env.execute();
  }
View Full Code Here
TOP

Related Classes of org.apache.flink.streaming.api.environment.StreamExecutionEnvironment

  • org.apache.flink.streaming.api.AggregationFunctionTest
  • org.apache.flink.streaming.api.function.source.FileSourceFunction
  • org.apache.flink.streaming.api.function.source.FileStreamFunction
  • org.apache.flink.streaming.api.function.source.GenSequenceFunction
  • org.apache.flink.streaming.api.JobGraphBuilder
  • org.apache.flink.streaming.connectors.flume.FlumeTopology
  • org.apache.flink.streaming.connectors.kafka.KafkaTopology
  • org.apache.flink.streaming.connectors.rabbitmq.RMQTopology
  • org.apache.flink.streaming.connectors.twitter.TwitterLocal
  • org.apache.flink.streaming.connectors.twitter.TwitterStreaming
    • Copyright © 2018 www.massapicom. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.