Examples with IntervalWindow org.apache.beam.sdk.transforms.windowing.IntervalWindow used on opensource projects

Example 6 with IntervalWindow

use of org.apache.beam.sdk.transforms.windowing.IntervalWindow in project beam by apache.

the class DoFnOperatorTest method testStateGCForStatefulFn.

@Test
public void testStateGCForStatefulFn() throws Exception {
    WindowingStrategy<Object, IntervalWindow> windowingStrategy = WindowingStrategy.of(FixedWindows.of(new Duration(10))).withAllowedLateness(Duration.ZERO);
    final String timerId = "boo";
    final String stateId = "dazzle";
    final int offset = 5000;
    final int timerOutput = 4093;
    DoFn<KV<String, Integer>, KV<String, Integer>> fn = new DoFn<KV<String, Integer>, KV<String, Integer>>() {

        @TimerId(timerId)
        private final TimerSpec spec = TimerSpecs.timer(TimeDomain.EVENT_TIME);

        @StateId(stateId)
        private final StateSpec<ValueState<String>> stateSpec = StateSpecs.value(StringUtf8Coder.of());

        @ProcessElement
        public void processElement(ProcessContext context, @TimerId(timerId) Timer timer, @StateId(stateId) ValueState<String> state, BoundedWindow window) {
            timer.set(window.maxTimestamp());
            state.write(context.element().getKey());
            context.output(KV.of(context.element().getKey(), context.element().getValue() + offset));
        }

        @OnTimer(timerId)
        public void onTimer(OnTimerContext context, @StateId(stateId) ValueState<String> state) {
            context.output(KV.of(state.read(), timerOutput));
        }
    };
    WindowedValue.FullWindowedValueCoder<KV<String, Integer>> windowedValueCoder = WindowedValue.getFullCoder(KvCoder.of(StringUtf8Coder.of(), VarIntCoder.of()), windowingStrategy.getWindowFn().windowCoder());
    TupleTag<KV<String, Integer>> outputTag = new TupleTag<>("main-output");
    DoFnOperator<KV<String, Integer>, KV<String, Integer>, WindowedValue<KV<String, Integer>>> doFnOperator = new DoFnOperator<>(fn, "stepName", windowedValueCoder, outputTag, Collections.<TupleTag<?>>emptyList(), new DoFnOperator.DefaultOutputManagerFactory<WindowedValue<KV<String, Integer>>>(), windowingStrategy, new HashMap<Integer, PCollectionView<?>>(), /* side-input mapping */
    Collections.<PCollectionView<?>>emptyList(), /* side inputs */
    PipelineOptionsFactory.as(FlinkPipelineOptions.class), StringUtf8Coder.of());
    KeyedOneInputStreamOperatorTestHarness<String, WindowedValue<KV<String, Integer>>, WindowedValue<KV<String, Integer>>> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(doFnOperator, new KeySelector<WindowedValue<KV<String, Integer>>, String>() {

        @Override
        public String getKey(WindowedValue<KV<String, Integer>> kvWindowedValue) throws Exception {
            return kvWindowedValue.getValue().getKey();
        }
    }, new CoderTypeInformation<>(StringUtf8Coder.of()));
    testHarness.open();
    testHarness.processWatermark(0);
    assertEquals(0, testHarness.numKeyedStateEntries());
    IntervalWindow window1 = new IntervalWindow(new Instant(0), Duration.millis(10));
    testHarness.processElement(new StreamRecord<>(WindowedValue.of(KV.of("key1", 5), new Instant(1), window1, PaneInfo.NO_FIRING)));
    testHarness.processElement(new StreamRecord<>(WindowedValue.of(KV.of("key2", 7), new Instant(3), window1, PaneInfo.NO_FIRING)));
    assertThat(this.<KV<String, Integer>>stripStreamRecordFromWindowedValue(testHarness.getOutput()), contains(WindowedValue.of(KV.of("key1", 5 + offset), new Instant(1), window1, PaneInfo.NO_FIRING), WindowedValue.of(KV.of("key2", 7 + offset), new Instant(3), window1, PaneInfo.NO_FIRING)));
    assertEquals(2, testHarness.numKeyedStateEntries());
    testHarness.getOutput().clear();
    // this should trigger both the window.maxTimestamp() timer and the GC timer
    // this tests that the GC timer fires after the user timer
    testHarness.processWatermark(window1.maxTimestamp().plus(windowingStrategy.getAllowedLateness()).plus(StatefulDoFnRunner.TimeInternalsCleanupTimer.GC_DELAY_MS).getMillis());
    assertThat(this.<KV<String, Integer>>stripStreamRecordFromWindowedValue(testHarness.getOutput()), contains(WindowedValue.of(KV.of("key1", timerOutput), new Instant(9), window1, PaneInfo.NO_FIRING), WindowedValue.of(KV.of("key2", timerOutput), new Instant(9), window1, PaneInfo.NO_FIRING)));
    // ensure the state was garbage collected
    assertEquals(0, testHarness.numKeyedStateEntries());
    testHarness.close();
}

Example 7 with IntervalWindow

use of org.apache.beam.sdk.transforms.windowing.IntervalWindow in project beam by apache.

the class SparkGlobalCombineFn method createAccumulator.

private Iterable<WindowedValue<AccumT>> createAccumulator(WindowedValue<InputT> input) {
    // sort exploded inputs.
    Iterable<WindowedValue<InputT>> sortedInputs = sortByWindows(input.explodeWindows());
    TimestampCombiner timestampCombiner = windowingStrategy.getTimestampCombiner();
    WindowFn<?, BoundedWindow> windowFn = windowingStrategy.getWindowFn();
    //--- inputs iterator, by window order.
    final Iterator<WindowedValue<InputT>> iterator = sortedInputs.iterator();
    WindowedValue<InputT> currentInput = iterator.next();
    BoundedWindow currentWindow = Iterables.getFirst(currentInput.getWindows(), null);
    // first create the accumulator and accumulate first input.
    AccumT accumulator = combineFn.createAccumulator(ctxtForInput(currentInput));
    accumulator = combineFn.addInput(accumulator, currentInput.getValue(), ctxtForInput(currentInput));
    // keep track of the timestamps assigned by the TimestampCombiner.
    Instant windowTimestamp = timestampCombiner.assign(currentWindow, windowingStrategy.getWindowFn().getOutputTime(currentInput.getTimestamp(), currentWindow));
    // accumulate the next windows, or output.
    List<WindowedValue<AccumT>> output = Lists.newArrayList();
    // if merging, merge overlapping windows, e.g. Sessions.
    final boolean merging = !windowingStrategy.getWindowFn().isNonMerging();
    while (iterator.hasNext()) {
        WindowedValue<InputT> nextValue = iterator.next();
        BoundedWindow nextWindow = Iterables.getOnlyElement(nextValue.getWindows());
        boolean mergingAndIntersecting = merging && isIntersecting((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
        if (mergingAndIntersecting || nextWindow.equals(currentWindow)) {
            if (mergingAndIntersecting) {
                // merge intersecting windows.
                currentWindow = merge((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
            }
            // keep accumulating and carry on ;-)
            accumulator = combineFn.addInput(accumulator, nextValue.getValue(), ctxtForInput(nextValue));
            windowTimestamp = timestampCombiner.merge(currentWindow, windowTimestamp, windowingStrategy.getWindowFn().getOutputTime(nextValue.getTimestamp(), currentWindow));
        } else {
            // moving to the next window, first add the current accumulation to output
            // and initialize the accumulator.
            output.add(WindowedValue.of(accumulator, windowTimestamp, currentWindow, PaneInfo.NO_FIRING));
            // re-init accumulator, window and timestamp.
            accumulator = combineFn.createAccumulator(ctxtForInput(nextValue));
            accumulator = combineFn.addInput(accumulator, nextValue.getValue(), ctxtForInput(nextValue));
            currentWindow = nextWindow;
            windowTimestamp = timestampCombiner.assign(currentWindow, windowFn.getOutputTime(nextValue.getTimestamp(), currentWindow));
        }
    }
    // add last accumulator to the output.
    output.add(WindowedValue.of(accumulator, windowTimestamp, currentWindow, PaneInfo.NO_FIRING));
    return output;
}

Example 8 with IntervalWindow

use of org.apache.beam.sdk.transforms.windowing.IntervalWindow in project beam by apache.

the class SparkGlobalCombineFn method combOp.

/**
   * Implement Spark's combOp function in:
   * <p>
   * {@link org.apache.spark.api.java.JavaRDD#aggregate}.
   * </p>
   */
Iterable<WindowedValue<AccumT>> combOp(Iterable<WindowedValue<AccumT>> a1, Iterable<WindowedValue<AccumT>> a2) {
    // concatenate accumulators.
    Iterable<WindowedValue<AccumT>> accumulators = Iterables.concat(a1, a2);
    // if empty, return an empty accumulators iterable.
    if (!accumulators.iterator().hasNext()) {
        return Lists.newArrayList();
    }
    // sort accumulators, no need to explode since inputs were exploded.
    Iterable<WindowedValue<AccumT>> sortedAccumulators = sortByWindows(accumulators);
    @SuppressWarnings("unchecked") TimestampCombiner timestampCombiner = windowingStrategy.getTimestampCombiner();
    //--- accumulators iterator, by window order.
    final Iterator<WindowedValue<AccumT>> iterator = sortedAccumulators.iterator();
    // get the first accumulator and assign it to the current window's accumulators.
    WindowedValue<AccumT> currentValue = iterator.next();
    BoundedWindow currentWindow = Iterables.getFirst(currentValue.getWindows(), null);
    List<AccumT> currentWindowAccumulators = Lists.newArrayList();
    currentWindowAccumulators.add(currentValue.getValue());
    // keep track of the timestamps assigned by the TimestampCombiner,
    // in createCombiner we already merge the timestamps assigned
    // to individual elements, here we will just merge them.
    List<Instant> windowTimestamps = Lists.newArrayList();
    windowTimestamps.add(currentValue.getTimestamp());
    // accumulate the next windows, or output.
    List<WindowedValue<AccumT>> output = Lists.newArrayList();
    // if merging, merge overlapping windows, e.g. Sessions.
    final boolean merging = !windowingStrategy.getWindowFn().isNonMerging();
    while (iterator.hasNext()) {
        WindowedValue<AccumT> nextValue = iterator.next();
        BoundedWindow nextWindow = Iterables.getOnlyElement(nextValue.getWindows());
        boolean mergingAndIntersecting = merging && isIntersecting((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
        if (mergingAndIntersecting || nextWindow.equals(currentWindow)) {
            if (mergingAndIntersecting) {
                // merge intersecting windows.
                currentWindow = merge((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
            }
            // add to window accumulators.
            currentWindowAccumulators.add(nextValue.getValue());
            windowTimestamps.add(nextValue.getTimestamp());
        } else {
            // before moving to the next window,
            // add the current accumulation to the output and initialize the accumulation.
            // merge the timestamps of all accumulators to merge.
            Instant mergedTimestamp = timestampCombiner.merge(currentWindow, windowTimestamps);
            // merge accumulators.
            // transforming a KV<K, Iterable<AccumT>> into a KV<K, Iterable<AccumT>>.
            // for the (possibly merged) window.
            Iterable<AccumT> accumsToMerge = Iterables.unmodifiableIterable(currentWindowAccumulators);
            WindowedValue<Iterable<AccumT>> preMergeWindowedValue = WindowedValue.of(accumsToMerge, mergedTimestamp, currentWindow, PaneInfo.NO_FIRING);
            // applying the actual combiner onto the accumulators.
            AccumT accumulated = combineFn.mergeAccumulators(accumsToMerge, ctxtForInput(preMergeWindowedValue));
            WindowedValue<AccumT> postMergeWindowedValue = preMergeWindowedValue.withValue(accumulated);
            // emit the accumulated output.
            output.add(postMergeWindowedValue);
            // re-init accumulator, window and timestamps.
            currentWindowAccumulators.clear();
            currentWindowAccumulators.add(nextValue.getValue());
            currentWindow = nextWindow;
            windowTimestamps.clear();
            windowTimestamps.add(nextValue.getTimestamp());
        }
    }
    // merge the last chunk of accumulators.
    Instant mergedTimestamp = timestampCombiner.merge(currentWindow, windowTimestamps);
    Iterable<AccumT> accumsToMerge = Iterables.unmodifiableIterable(currentWindowAccumulators);
    WindowedValue<Iterable<AccumT>> preMergeWindowedValue = WindowedValue.of(accumsToMerge, mergedTimestamp, currentWindow, PaneInfo.NO_FIRING);
    AccumT accumulated = combineFn.mergeAccumulators(accumsToMerge, ctxtForInput(preMergeWindowedValue));
    WindowedValue<AccumT> postMergeWindowedValue = preMergeWindowedValue.withValue(accumulated);
    output.add(postMergeWindowedValue);
    return output;
}

Example 9 with IntervalWindow

use of org.apache.beam.sdk.transforms.windowing.IntervalWindow in project beam by apache.

the class SparkKeyedCombineFn method mergeCombiners.

/**
   * Implements Spark's mergeCombiners function in:
   * <p>
   * {@link org.apache.spark.rdd.PairRDDFunctions#combineByKey}.
   * </p>
   */
Iterable<WindowedValue<KV<K, AccumT>>> mergeCombiners(Iterable<WindowedValue<KV<K, AccumT>>> a1, Iterable<WindowedValue<KV<K, AccumT>>> a2) {
    // concatenate accumulators.
    Iterable<WindowedValue<KV<K, AccumT>>> accumulators = Iterables.concat(a1, a2);
    // sort accumulators, no need to explode since inputs were exploded.
    Iterable<WindowedValue<KV<K, AccumT>>> sortedAccumulators = sortByWindows(accumulators);
    @SuppressWarnings("unchecked") TimestampCombiner timestampCombiner = windowingStrategy.getTimestampCombiner();
    //--- accumulators iterator, by window order.
    final Iterator<WindowedValue<KV<K, AccumT>>> iterator = sortedAccumulators.iterator();
    // get the first accumulator and assign it to the current window's accumulators.
    WindowedValue<KV<K, AccumT>> currentValue = iterator.next();
    K key = currentValue.getValue().getKey();
    BoundedWindow currentWindow = Iterables.getFirst(currentValue.getWindows(), null);
    List<AccumT> currentWindowAccumulators = Lists.newArrayList();
    currentWindowAccumulators.add(currentValue.getValue().getValue());
    // keep track of the timestamps assigned by the TimestampCombiner,
    // in createCombiner we already merge the timestamps assigned
    // to individual elements, here we will just merge them.
    List<Instant> windowTimestamps = Lists.newArrayList();
    windowTimestamps.add(currentValue.getTimestamp());
    // accumulate the next windows, or output.
    List<WindowedValue<KV<K, AccumT>>> output = Lists.newArrayList();
    // if merging, merge overlapping windows, e.g. Sessions.
    final boolean merging = !windowingStrategy.getWindowFn().isNonMerging();
    while (iterator.hasNext()) {
        WindowedValue<KV<K, AccumT>> nextValue = iterator.next();
        BoundedWindow nextWindow = Iterables.getOnlyElement(nextValue.getWindows());
        boolean mergingAndIntersecting = merging && isIntersecting((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
        if (mergingAndIntersecting || nextWindow.equals(currentWindow)) {
            if (mergingAndIntersecting) {
                // merge intersecting windows.
                currentWindow = merge((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
            }
            // add to window accumulators.
            currentWindowAccumulators.add(nextValue.getValue().getValue());
            windowTimestamps.add(nextValue.getTimestamp());
        } else {
            // before moving to the next window,
            // add the current accumulation to the output and initialize the accumulation.
            // merge the timestamps of all accumulators to merge.
            Instant mergedTimestamp = timestampCombiner.merge(currentWindow, windowTimestamps);
            // merge accumulators.
            // transforming a KV<K, Iterable<AccumT>> into a KV<K, Iterable<AccumT>>.
            // for the (possibly merged) window.
            Iterable<AccumT> accumsToMerge = Iterables.unmodifiableIterable(currentWindowAccumulators);
            WindowedValue<KV<K, Iterable<AccumT>>> preMergeWindowedValue = WindowedValue.of(KV.of(key, accumsToMerge), mergedTimestamp, currentWindow, PaneInfo.NO_FIRING);
            // applying the actual combiner onto the accumulators.
            AccumT accumulated = combineFn.mergeAccumulators(accumsToMerge, ctxtForInput(preMergeWindowedValue));
            WindowedValue<KV<K, AccumT>> postMergeWindowedValue = preMergeWindowedValue.withValue(KV.of(key, accumulated));
            // emit the accumulated output.
            output.add(postMergeWindowedValue);
            // re-init accumulator, window and timestamps.
            currentWindowAccumulators.clear();
            currentWindowAccumulators.add(nextValue.getValue().getValue());
            currentWindow = nextWindow;
            windowTimestamps.clear();
            windowTimestamps.add(nextValue.getTimestamp());
        }
    }
    // merge the last chunk of accumulators.
    Instant mergedTimestamp = timestampCombiner.merge(currentWindow, windowTimestamps);
    Iterable<AccumT> accumsToMerge = Iterables.unmodifiableIterable(currentWindowAccumulators);
    WindowedValue<KV<K, Iterable<AccumT>>> preMergeWindowedValue = WindowedValue.of(KV.of(key, accumsToMerge), mergedTimestamp, currentWindow, PaneInfo.NO_FIRING);
    AccumT accumulated = combineFn.mergeAccumulators(accumsToMerge, ctxtForInput(preMergeWindowedValue));
    WindowedValue<KV<K, AccumT>> postMergeWindowedValue = preMergeWindowedValue.withValue(KV.of(key, accumulated));
    output.add(postMergeWindowedValue);
    return output;
}

Example 10 with IntervalWindow

use of org.apache.beam.sdk.transforms.windowing.IntervalWindow in project beam by apache.

the class SparkKeyedCombineFn method createCombiner.

/**
   * Implements Spark's createCombiner function in:
   * <p>
   * {@link org.apache.spark.rdd.PairRDDFunctions#combineByKey}.
   * </p>
   */
Iterable<WindowedValue<KV<K, AccumT>>> createCombiner(WindowedValue<KV<K, InputT>> wkvi) {
    // sort exploded inputs.
    Iterable<WindowedValue<KV<K, InputT>>> sortedInputs = sortByWindows(wkvi.explodeWindows());
    TimestampCombiner timestampCombiner = windowingStrategy.getTimestampCombiner();
    WindowFn<?, BoundedWindow> windowFn = windowingStrategy.getWindowFn();
    //--- inputs iterator, by window order.
    final Iterator<WindowedValue<KV<K, InputT>>> iterator = sortedInputs.iterator();
    WindowedValue<KV<K, InputT>> currentInput = iterator.next();
    BoundedWindow currentWindow = Iterables.getFirst(currentInput.getWindows(), null);
    // first create the accumulator and accumulate first input.
    K key = currentInput.getValue().getKey();
    AccumT accumulator = combineFn.createAccumulator(ctxtForInput(currentInput));
    accumulator = combineFn.addInput(accumulator, currentInput.getValue().getValue(), ctxtForInput(currentInput));
    // keep track of the timestamps assigned by the TimestampCombiner.
    Instant windowTimestamp = timestampCombiner.assign(currentWindow, windowingStrategy.getWindowFn().getOutputTime(currentInput.getTimestamp(), currentWindow));
    // accumulate the next windows, or output.
    List<WindowedValue<KV<K, AccumT>>> output = Lists.newArrayList();
    // if merging, merge overlapping windows, e.g. Sessions.
    final boolean merging = !windowingStrategy.getWindowFn().isNonMerging();
    while (iterator.hasNext()) {
        WindowedValue<KV<K, InputT>> nextValue = iterator.next();
        BoundedWindow nextWindow = Iterables.getOnlyElement(nextValue.getWindows());
        boolean mergingAndIntersecting = merging && isIntersecting((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
        if (mergingAndIntersecting || nextWindow.equals(currentWindow)) {
            if (mergingAndIntersecting) {
                // merge intersecting windows.
                currentWindow = merge((IntervalWindow) currentWindow, (IntervalWindow) nextWindow);
            }
            // keep accumulating and carry on ;-)
            accumulator = combineFn.addInput(accumulator, nextValue.getValue().getValue(), ctxtForInput(nextValue));
            windowTimestamp = timestampCombiner.combine(windowTimestamp, timestampCombiner.assign(currentWindow, windowFn.getOutputTime(nextValue.getTimestamp(), currentWindow)));
        } else {
            // moving to the next window, first add the current accumulation to output
            // and initialize the accumulator.
            output.add(WindowedValue.of(KV.of(key, accumulator), windowTimestamp, currentWindow, PaneInfo.NO_FIRING));
            // re-init accumulator, window and timestamp.
            accumulator = combineFn.createAccumulator(ctxtForInput(nextValue));
            accumulator = combineFn.addInput(accumulator, nextValue.getValue().getValue(), ctxtForInput(nextValue));
            currentWindow = nextWindow;
            windowTimestamp = timestampCombiner.assign(currentWindow, windowFn.getOutputTime(nextValue.getTimestamp(), currentWindow));
        }
    }
    // add last accumulator to the output.
    output.add(WindowedValue.of(KV.of(key, accumulator), windowTimestamp, currentWindow, PaneInfo.NO_FIRING));
    return output;
}