Examples with WindowAssigner org.apache.flink.streaming.api.windowing.assigners.WindowAssigner used on opensource projects

Example 1 with WindowAssigner

use of org.apache.flink.streaming.api.windowing.assigners.WindowAssigner in project flink by apache.

the class WindowOperatorTest method testCleanupTimeOverflow.

@Test
public void testCleanupTimeOverflow() throws Exception {
    final int WINDOW_SIZE = 1000;
    final long LATENESS = 2000;
    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()));
    TumblingEventTimeWindows windowAssigner = TumblingEventTimeWindows.of(Time.milliseconds(WINDOW_SIZE));
    final WindowOperator<String, Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple2<String, Integer>, TimeWindow> operator = new WindowOperator<>(windowAssigner, 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<>();
    long timestamp = Long.MAX_VALUE - 1750;
    Collection<TimeWindow> windows = windowAssigner.assignWindows(new Tuple2<>("key2", 1), timestamp, new WindowAssigner.WindowAssignerContext() {

        @Override
        public long getCurrentProcessingTime() {
            return operator.windowAssignerContext.getCurrentProcessingTime();
        }
    });
    TimeWindow window = Iterables.getOnlyElement(windows);
    testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), timestamp));
    // the garbage collection timer would wrap-around
    Assert.assertTrue(window.maxTimestamp() + LATENESS < window.maxTimestamp());
    // and it would prematurely fire with watermark (Long.MAX_VALUE - 1500)
    Assert.assertTrue(window.maxTimestamp() + LATENESS < Long.MAX_VALUE - 1500);
    // if we don't correctly prevent wrap-around in the garbage collection
    // timers this watermark will clean our window state for the just-added
    // element/window
    testHarness.processWatermark(new Watermark(Long.MAX_VALUE - 1500));
    // this watermark is before the end timestamp of our only window
    Assert.assertTrue(Long.MAX_VALUE - 1500 < window.maxTimestamp());
    Assert.assertTrue(window.maxTimestamp() < Long.MAX_VALUE);
    // push in a watermark that will trigger computation of our window
    testHarness.processWatermark(new Watermark(window.maxTimestamp()));
    expected.add(new Watermark(Long.MAX_VALUE - 1500));
    expected.add(new StreamRecord<>(new Tuple2<>("key2", 1), window.maxTimestamp()));
    expected.add(new Watermark(window.maxTimestamp()));
    TestHarnessUtil.assertOutputEqualsSorted("Output was not correct.", expected, testHarness.getOutput(), new Tuple2ResultSortComparator());
    testHarness.close();
}