Examples with TimeWindow org.apache.flink.streaming.api.windowing.windows.TimeWindow used on opensource projects

Example 1 with TimeWindow

use of org.apache.flink.streaming.api.windowing.windows.TimeWindow in project flink by apache.

the class WindowOperatorTest method testCleanupTimerWithEmptyFoldingStateForSessionWindows.

// TODO this test seems invalid, as it uses the unsupported combination of merging windows and folding window state
@Test
public void testCleanupTimerWithEmptyFoldingStateForSessionWindows() throws Exception {
    final int GAP_SIZE = 3;
    final long LATENESS = 10;
    TypeInformation<Tuple2<String, Integer>> inputType = TypeInfoParser.parse("Tuple2<String, Integer>");
    FoldingStateDescriptor<Tuple2<String, Integer>, Tuple2<String, Integer>> windowStateDesc = new FoldingStateDescriptor<>("window-contents", new Tuple2<>((String) null, 0), new FoldFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>() {

        private static final long serialVersionUID = 1L;

        @Override
        public Tuple2<String, Integer> fold(Tuple2<String, Integer> accumulator, Tuple2<String, Integer> value) throws Exception {
            return new Tuple2<>(value.f0, accumulator.f1 + value.f1);
        }
    }, inputType);
    windowStateDesc.initializeSerializerUnlessSet(new ExecutionConfig());
    WindowOperator<String, Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple2<String, Integer>, TimeWindow> operator = new WindowOperator<>(EventTimeSessionWindows.withGap(Time.seconds(GAP_SIZE)), new TimeWindow.Serializer(), new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO.createSerializer(new ExecutionConfig()), windowStateDesc, new InternalSingleValueWindowFunction<>(new PassThroughFunction()), 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<>();
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1000));
    testHarness.processWatermark(new Watermark(4998));
    expected.add(new StreamRecord<>(new Tuple2<>("key2", 1), 3999));
    expected.add(new Watermark(4998));
    testHarness.processWatermark(new Watermark(14600));
    expected.add(new Watermark(14600));
    ConcurrentLinkedQueue<Object> actual = testHarness.getOutput();
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expected, actual, new Tuple2ResultSortComparator());
    testHarness.close();
}

Example 2 with TimeWindow

use of org.apache.flink.streaming.api.windowing.windows.TimeWindow 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 3 with TimeWindow

use of org.apache.flink.streaming.api.windowing.windows.TimeWindow 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 4 with TimeWindow

use of org.apache.flink.streaming.api.windowing.windows.TimeWindow in project flink by apache.

the class WindowOperatorMigrationTest method testRestoreApplyEventTimeWindowsFromFlink11.

@Test
@SuppressWarnings("unchecked")
public void testRestoreApplyEventTimeWindowsFromFlink11() throws Exception {
    final int WINDOW_SIZE = 3;
    TypeInformation<Tuple2<String, Integer>> inputType = TypeInfoParser.parse("Tuple2<String, Integer>");
    ListStateDescriptor<Tuple2<String, Integer>> stateDesc = new ListStateDescriptor<>("window-contents", inputType.createSerializer(new ExecutionConfig()));
    WindowOperator<String, Tuple2<String, Integer>, Iterable<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 InternalIterableWindowFunction<>(new RichSumReducer<TimeWindow>()), EventTimeTrigger.create(), 0, null);
    ConcurrentLinkedQueue<Object> expectedOutput = new ConcurrentLinkedQueue<>();
    /*

		operator.setInputType(TypeInfoParser.<Tuple2<String, Integer>>parse("Tuple2<String, Integer>"), new ExecutionConfig());

		OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple2<String, Integer>> testHarness =
				new OneInputStreamOperatorTestHarness<>(operator);

		testHarness.configureForKeyedStream(new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);

		testHarness.setup();
		testHarness.open();

		// add elements out-of-order
		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 3999));
		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 3000));

		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), 20));
		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), 0));
		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), 999));

		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1998));
		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1999));
		testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), 1000));

		testHarness.processWatermark(new Watermark(999));
		expectedOutput.add(new Watermark(999));
		TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());

		testHarness.processWatermark(new Watermark(1999));
		expectedOutput.add(new Watermark(1999));
		TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());

		// do snapshot and save to file
		StreamTaskState snapshot = testHarness.snapshot(0L, 0L);
		testHarness.snaphotToFile(snapshot, "src/test/resources/win-op-migration-test-apply-event-time-flink1.1-snapshot");
		testHarness.close();

		*/
    OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple2<String, Integer>> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(operator, new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);
    testHarness.setup();
    testHarness.initializeStateFromLegacyCheckpoint(getResourceFilename("win-op-migration-test-apply-event-time-flink1.1-snapshot"));
    testHarness.open();
    testHarness.processWatermark(new Watermark(2999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key1", 3), 2999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 3), 2999));
    expectedOutput.add(new Watermark(2999));
    testHarness.processWatermark(new Watermark(3999));
    expectedOutput.add(new Watermark(3999));
    testHarness.processWatermark(new Watermark(4999));
    expectedOutput.add(new Watermark(4999));
    testHarness.processWatermark(new Watermark(5999));
    expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 2), 5999));
    expectedOutput.add(new Watermark(5999));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expectedOutput, testHarness.getOutput(), new Tuple2ResultSortComparator());
    testHarness.close();
}

Example 5 with TimeWindow

use of org.apache.flink.streaming.api.windowing.windows.TimeWindow in project flink by apache.

the class WindowTranslationTest method testSessionWithFoldFails.

// ------------------------------------------------------------------------
//  Merging Windows Support
// ------------------------------------------------------------------------
@Test
public void testSessionWithFoldFails() throws Exception {
    // verify that fold does not work with merging windows
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    WindowedStream<String, String, TimeWindow> windowedStream = env.fromElements("Hello", "Ciao").keyBy(new KeySelector<String, String>() {

        @Override
        public String getKey(String value) throws Exception {
            return value;
        }
    }).window(EventTimeSessionWindows.withGap(Time.seconds(5)));
    try {
        windowedStream.fold("", new FoldFunction<String, String>() {

            private static final long serialVersionUID = -4567902917104921706L;

            @Override
            public String fold(String accumulator, String value) throws Exception {
                return accumulator;
            }
        });
    } catch (UnsupportedOperationException e) {
        // use a catch to ensure that the exception is thrown by the fold
        return;
    }
    fail("The fold call should fail.");
}