Examples with Tuple2 org.apache.flink.api.java.tuple.Tuple2 used on opensource projects

Example 41 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowOperatorTest method testCleanupTimerWithEmptyReduceStateForTumblingWindows.

@Test
public void testCleanupTimerWithEmptyReduceStateForTumblingWindows() throws Exception {
    final int WINDOW_SIZE = 2;
    final long LATENESS = 1;
    TypeInformation<Tuple2<String, Integer>> inputType = TypeInfoParser.parse("Tuple2<String, Integer>");
    ReducingStateDescriptor<Tuple2<String, Integer>> stateDesc = new ReducingStateDescriptor<>("window-contents", new SumReducer(), inputType.createSerializer(new ExecutionConfig()));
    WindowOperator<String, Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple2<String, Integer>, TimeWindow> operator = new WindowOperator<>(TumblingEventTimeWindows.of(Time.of(WINDOW_SIZE, TimeUnit.SECONDS)), new TimeWindow.Serializer(), new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO.createSerializer(new ExecutionConfig()), stateDesc, new InternalSingleValueWindowFunction<>(new PassThroughWindowFunction<String, TimeWindow, Tuple2<String, Integer>>()), EventTimeTrigger.create(), LATENESS, null);
    OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple2<String, Integer>> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(operator, new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);
    testHarness.open();
    ConcurrentLinkedQueue<Object> expected = new ConcurrentLinkedQueue<>();
    // normal element
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1000));
    testHarness.processWatermark(new Watermark(1599));
    testHarness.processWatermark(new Watermark(1999));
    testHarness.processWatermark(new Watermark(2000));
    testHarness.processWatermark(new Watermark(5000));
    expected.add(new Watermark(1599));
    expected.add(new StreamRecord<>(new Tuple2<>("key2", 1), 1999));
    // here it fires and purges
    expected.add(new Watermark(1999));
    // here is the cleanup timer
    expected.add(new Watermark(2000));
    expected.add(new Watermark(5000));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expected, testHarness.getOutput(), new Tuple2ResultSortComparator());
    testHarness.close();
}

Example 42 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class TimeWindowTranslationTest method testApplyAlignedTimeWindows.

/**
	 * These tests ensure that the fast aligned time windows operator is used if the
	 * conditions are right.
	 */
@Test
public void testApplyAlignedTimeWindows() throws Exception {
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);
    DataStream<Tuple2<String, Integer>> source = env.fromElements(Tuple2.of("hello", 1), Tuple2.of("hello", 2));
    DataStream<Tuple2<String, Integer>> window1 = source.keyBy(0).window(TumblingAlignedProcessingTimeWindows.of(Time.of(1000, TimeUnit.MILLISECONDS))).apply(new WindowFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple, TimeWindow>() {

        private static final long serialVersionUID = 1L;

        @Override
        public void apply(Tuple tuple, TimeWindow window, Iterable<Tuple2<String, Integer>> values, Collector<Tuple2<String, Integer>> out) throws Exception {
        }
    });
    OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform1 = (OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window1.getTransformation();
    OneInputStreamOperator<Tuple2<String, Integer>, Tuple2<String, Integer>> operator1 = transform1.getOperator();
    Assert.assertTrue(operator1 instanceof AccumulatingProcessingTimeWindowOperator);
}

Example 43 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class TriggerTestHarness method advanceWatermark.

/**
	 * Advanced the watermark and processes any timers that fire because of this. The
	 * window and {@link TriggerResult} for each firing are returned.
	 */
public Collection<Tuple2<W, TriggerResult>> advanceWatermark(long time) throws Exception {
    Collection<TestInternalTimerService.Timer<Integer, W>> firedTimers = internalTimerService.advanceWatermark(time);
    Collection<Tuple2<W, TriggerResult>> result = new ArrayList<>();
    for (TestInternalTimerService.Timer<Integer, W> timer : firedTimers) {
        TriggerResult triggerResult = invokeOnEventTime(timer);
        result.add(new Tuple2<>(timer.getNamespace(), triggerResult));
    }
    return result;
}

Example 44 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowTranslationTest method testFoldWithProcessWindowFunctionEventTime.

@Test
@SuppressWarnings("rawtypes")
public void testFoldWithProcessWindowFunctionEventTime() throws Exception {
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);
    DataStream<Tuple2<String, Integer>> source = env.fromElements(Tuple2.of("hello", 1), Tuple2.of("hello", 2));
    DataStream<Tuple2<String, Integer>> window = source.keyBy(new TupleKeySelector()).window(TumblingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS))).fold(new Tuple3<>("", "", 0), new DummyFolder(), new ProcessWindowFunction<Tuple3<String, String, Integer>, Tuple2<String, Integer>, String, TimeWindow>() {

        private static final long serialVersionUID = 1L;

        @Override
        public void process(String key, Context ctx, Iterable<Tuple3<String, String, Integer>> values, Collector<Tuple2<String, Integer>> out) throws Exception {
            for (Tuple3<String, String, Integer> in : values) {
                out.collect(new Tuple2<>(in.f0, in.f2));
            }
        }
    });
    OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform = (OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window.getTransformation();
    OneInputStreamOperator<Tuple2<String, Integer>, Tuple2<String, Integer>> operator = transform.getOperator();
    Assert.assertTrue(operator instanceof WindowOperator);
    WindowOperator<String, Tuple2<String, Integer>, ?, ?, ?> winOperator = (WindowOperator<String, Tuple2<String, Integer>, ?, ?, ?>) operator;
    Assert.assertTrue(winOperator.getTrigger() instanceof EventTimeTrigger);
    Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingEventTimeWindows);
    Assert.assertTrue(winOperator.getStateDescriptor() instanceof FoldingStateDescriptor);
    processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}

Example 45 with Tuple2

use of org.apache.flink.api.java.tuple.Tuple2 in project flink by apache.

the class WindowTranslationTest method testFoldWithRichFolderFails.

/**
	 * .fold() does not support RichFoldFunction, since the fold function is used internally
	 * in a {@code FoldingState}.
	 */
@Test(expected = UnsupportedOperationException.class)
public void testFoldWithRichFolderFails() throws Exception {
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    DataStream<Tuple2<String, Integer>> source = env.fromElements(Tuple2.of("hello", 1), Tuple2.of("hello", 2));
    env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);
    source.keyBy(0).window(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS))).fold(new Tuple2<>("", 0), new RichFoldFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>() {

        @Override
        public Tuple2<String, Integer> fold(Tuple2<String, Integer> value1, Tuple2<String, Integer> value2) throws Exception {
            return null;
        }
    });
    fail("exception was not thrown");
}