Java Code Examples for org.apache.flink.streaming.api.TimeCharacteristic

The following examples show how to use org.apache.flink.streaming.api.TimeCharacteristic. These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source Project: flink   Source File: KeyedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Specifies the time boundaries over which the join operation works, so that
 * <pre>leftElement.timestamp + lowerBound <= rightElement.timestamp <= leftElement.timestamp + upperBound</pre>
 * By default both the lower and the upper bound are inclusive. This can be configured
 * with {@link IntervalJoined#lowerBoundExclusive()} and
 * {@link IntervalJoined#upperBoundExclusive()}
 *
 * @param lowerBound The lower bound. Needs to be smaller than or equal to the upperBound
 * @param upperBound The upper bound. Needs to be bigger than or equal to the lowerBound
 */
@PublicEvolving
public IntervalJoined<T1, T2, KEY> between(Time lowerBound, Time upperBound) {

	TimeCharacteristic timeCharacteristic =
		streamOne.getExecutionEnvironment().getStreamTimeCharacteristic();

	if (timeCharacteristic != TimeCharacteristic.EventTime) {
		throw new UnsupportedTimeCharacteristicException("Time-bounded stream joins are only supported in event time");
	}

	checkNotNull(lowerBound, "A lower bound needs to be provided for a time-bounded join");
	checkNotNull(upperBound, "An upper bound needs to be provided for a time-bounded join");

	return new IntervalJoined<>(
		streamOne,
		streamTwo,
		lowerBound.toMilliseconds(),
		upperBound.toMilliseconds(),
		true,
		true
	);
}
 
Example 2
Source Project: flink-connectors   Source File: FlinkPravegaReaderTest.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Tests the cancellation support.
 */
@Test
public void testCancellation() throws Exception {
    TestableFlinkPravegaReader<Integer> reader = createReader();

    try (StreamSourceOperatorTestHarness<Integer, TestableFlinkPravegaReader<Integer>> testHarness =
                 createTestHarness(reader, 1, 1, 0, TimeCharacteristic.ProcessingTime)) {
        testHarness.open();

        // prepare a sequence of events
        TestEventGenerator<Integer> evts = new TestEventGenerator<>();
        when(reader.eventStreamReader.readNextEvent(anyLong()))
                .thenAnswer(i -> {
                    testHarness.cancel();
                    return evts.idle();
                });

        // run the source, which should return upon cancellation
        testHarness.run();
        assertFalse(reader.running);
    }
}
 
Example 3
@Test
public void testLifeCycleCancel() throws Exception {
	ACTUAL_ORDER_TRACKING.clear();

	Configuration taskManagerConfig = new Configuration();
	StreamConfig cfg = new StreamConfig(new Configuration());
	MockSourceFunction srcFun = new MockSourceFunction();
	cfg.setStreamOperator(new LifecycleTrackingStreamSource<>(srcFun, false));
	cfg.setOperatorID(new OperatorID());
	cfg.setTimeCharacteristic(TimeCharacteristic.ProcessingTime);

	Task task = StreamTaskTest.createTask(SourceStreamTask.class, cfg, taskManagerConfig);

	task.startTaskThread();
	LifecycleTrackingStreamSource.runStarted.await();

	// this should cancel the task even though it is blocked on runFinished
	task.cancelExecution();

	// wait for clean termination
	task.getExecutingThread().join();
	assertEquals(ExecutionState.CANCELED, task.getExecutionState());
	assertEquals(EXPECTED_CALL_ORDER_CANCEL_RUNNING, ACTUAL_ORDER_TRACKING);
}
 
Example 4
Source Project: Flink-CEPplus   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 6 votes vote down vote up
@Test
@SuppressWarnings({"rawtypes", "unchecked"})
public void testFoldWithEvictor() 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<Tuple3<String, String, Integer>> window1 = source
			.windowAll(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.evictor(CountEvictor.of(100))
			.fold(new Tuple3<>("", "", 1), new DummyFolder());

	OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>> transform =
			(OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>>) window1.getTransformation();
	OneInputStreamOperator<Tuple2<String, Integer>, Tuple3<String, String, Integer>> operator = transform.getOperator();
	Assert.assertTrue(operator instanceof EvictingWindowOperator);
	EvictingWindowOperator<String, Tuple2<String, Integer>, ?, ?> winOperator = (EvictingWindowOperator<String, Tuple2<String, Integer>, ?, ?>) operator;
	Assert.assertTrue(winOperator.getTrigger() instanceof EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getEvictor() instanceof CountEvictor);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ListStateDescriptor);

	winOperator.setOutputType((TypeInformation) window1.getType(), new ExecutionConfig());
	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
 
Example 5
Source Project: flink   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 6 votes vote down vote up
@Test
@SuppressWarnings("rawtypes")
public void testReduceEventTime() 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>> window1 = source
			.windowAll(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.reduce(new DummyReducer());

	OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform = (OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window1.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 SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ReducingStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
 
Example 6
Source Project: flink   Source File: ExecutionContext.java    License: Apache License 2.0 6 votes vote down vote up
private TableConfig createTableConfig() {
	final TableConfig config = new TableConfig();
	config.addConfiguration(flinkConfig);
	Configuration conf = config.getConfiguration();
	environment.getConfiguration().asMap().forEach(conf::setString);
	ExecutionEntry execution = environment.getExecution();
	config.setIdleStateRetentionTime(
			Time.milliseconds(execution.getMinStateRetention()),
			Time.milliseconds(execution.getMaxStateRetention()));

	conf.set(CoreOptions.DEFAULT_PARALLELISM, execution.getParallelism());
	conf.set(PipelineOptions.MAX_PARALLELISM, execution.getMaxParallelism());
	conf.set(StreamPipelineOptions.TIME_CHARACTERISTIC, execution.getTimeCharacteristic());
	if (execution.getTimeCharacteristic() == TimeCharacteristic.EventTime) {
		conf.set(PipelineOptions.AUTO_WATERMARK_INTERVAL,
				Duration.ofMillis(execution.getPeriodicWatermarksInterval()));
	}

	setRestartStrategy(conf);
	return config;
}
 
Example 7
Source Project: flink   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 6 votes vote down vote up
@Test
@SuppressWarnings({"rawtypes", "unchecked"})
public void testFoldWithEvictor() 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<Tuple3<String, String, Integer>> window1 = source
			.windowAll(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.evictor(CountEvictor.of(100))
			.fold(new Tuple3<>("", "", 1), new DummyFolder());

	OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>> transform =
			(OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>>) window1.getTransformation();
	OneInputStreamOperator<Tuple2<String, Integer>, Tuple3<String, String, Integer>> operator = transform.getOperator();
	Assert.assertTrue(operator instanceof EvictingWindowOperator);
	EvictingWindowOperator<String, Tuple2<String, Integer>, ?, ?> winOperator = (EvictingWindowOperator<String, Tuple2<String, Integer>, ?, ?>) operator;
	Assert.assertTrue(winOperator.getTrigger() instanceof EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getEvictor() instanceof CountEvictor);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ListStateDescriptor);

	winOperator.setOutputType((TypeInformation) window1.getType(), new ExecutionConfig());
	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
 
Example 8
@Test
public void testNoMaxWatermarkOnImmediateStop() throws Exception {

	final List<StreamElement> output = new ArrayList<>();

	// regular stream source operator
	final StoppableStreamSource<String, InfiniteSource<String>> operator =
			new StoppableStreamSource<>(new InfiniteSource<String>());

	setupSourceOperator(operator, TimeCharacteristic.EventTime, 0);
	operator.stop();

	// run and stop
	operator.run(new Object(), mock(StreamStatusMaintainer.class), new CollectorOutput<String>(output));

	assertTrue(output.isEmpty());
}
 
Example 9
Source Project: Flink-CEPplus   Source File: IntervalJoinITCase.java    License: Apache License 2.0 6 votes vote down vote up
@Test(expected = UnsupportedTimeCharacteristicException.class)
public void testExecutionFailsInProcessingTime() throws Exception {
	final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);
	env.setParallelism(1);

	DataStream<Tuple2<String, Integer>> streamOne = env.fromElements(Tuple2.of("1", 1));
	DataStream<Tuple2<String, Integer>> streamTwo = env.fromElements(Tuple2.of("1", 1));

	streamOne.keyBy(new Tuple2KeyExtractor())
		.intervalJoin(streamTwo.keyBy(new Tuple2KeyExtractor()))
		.between(Time.milliseconds(0), Time.milliseconds(0))
		.process(new ProcessJoinFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, String>() {
			@Override
			public void processElement(Tuple2<String, Integer> left,
				Tuple2<String, Integer> right, Context ctx,
				Collector<String> out) throws Exception {
				out.collect(left + ":" + right);
			}
		});
}
 
Example 10
Source Project: flink   Source File: KeyedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Specifies the time boundaries over which the join operation works, so that
 * <pre>leftElement.timestamp + lowerBound <= rightElement.timestamp <= leftElement.timestamp + upperBound</pre>
 * By default both the lower and the upper bound are inclusive. This can be configured
 * with {@link IntervalJoined#lowerBoundExclusive()} and
 * {@link IntervalJoined#upperBoundExclusive()}
 *
 * @param lowerBound The lower bound. Needs to be smaller than or equal to the upperBound
 * @param upperBound The upper bound. Needs to be bigger than or equal to the lowerBound
 */
@PublicEvolving
public IntervalJoined<T1, T2, KEY> between(Time lowerBound, Time upperBound) {

	TimeCharacteristic timeCharacteristic =
		streamOne.getExecutionEnvironment().getStreamTimeCharacteristic();

	if (timeCharacteristic != TimeCharacteristic.EventTime) {
		throw new UnsupportedTimeCharacteristicException("Time-bounded stream joins are only supported in event time");
	}

	checkNotNull(lowerBound, "A lower bound needs to be provided for a time-bounded join");
	checkNotNull(upperBound, "An upper bound needs to be provided for a time-bounded join");

	return new IntervalJoined<>(
		streamOne,
		streamTwo,
		lowerBound.toMilliseconds(),
		upperBound.toMilliseconds(),
		true,
		true
	);
}
 
Example 11
Source Project: flink   Source File: ExecutionEntry.java    License: Apache License 2.0 6 votes vote down vote up
public TimeCharacteristic getTimeCharacteristic() {
	return properties.getOptionalString(EXECUTION_TIME_CHARACTERISTIC)
		.flatMap((v) -> {
			switch (v) {
				case EXECUTION_TIME_CHARACTERISTIC_VALUE_EVENT_TIME:
					return Optional.of(TimeCharacteristic.EventTime);
				case EXECUTION_TIME_CHARACTERISTIC_VALUE_PROCESSING_TIME:
					return Optional.of(TimeCharacteristic.ProcessingTime);
				default:
					return Optional.empty();
			}
		})
		.orElseGet(() ->
			useDefaultValue(
				EXECUTION_TIME_CHARACTERISTIC,
				TimeCharacteristic.EventTime,
				EXECUTION_TIME_CHARACTERISTIC_VALUE_EVENT_TIME));
}
 
Example 12
Source Project: Flink-CEPplus   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 6 votes vote down vote up
@Test
@SuppressWarnings("rawtypes")
public void testFoldWithCustomTrigger() 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<Tuple3<String, String, Integer>> window1 = source
			.windowAll(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.trigger(CountTrigger.of(1))
			.fold(new Tuple3<>("", "", 1), new DummyFolder());

	OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>> transform =
			(OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>>) window1.getTransformation();
	OneInputStreamOperator<Tuple2<String, Integer>, Tuple3<String, 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 CountTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof FoldingStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
 
Example 13
Source Project: flink   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 6 votes vote down vote up
@Test
@SuppressWarnings("rawtypes")
public void testReduceWithEvictor() 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));

	DummyReducer reducer = new DummyReducer();

	DataStream<Tuple2<String, Integer>> window1 = source
			.windowAll(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.evictor(CountEvictor.of(100))
			.reduce(reducer);

	OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform = (OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window1.getTransformation();
	OneInputStreamOperator<Tuple2<String, Integer>, Tuple2<String, Integer>> operator = transform.getOperator();
	Assert.assertTrue(operator instanceof EvictingWindowOperator);
	EvictingWindowOperator<String, Tuple2<String, Integer>, ?, ?> winOperator = (EvictingWindowOperator<String, Tuple2<String, Integer>, ?, ?>) operator;
	Assert.assertTrue(winOperator.getTrigger() instanceof EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getEvictor() instanceof CountEvictor);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ListStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
 
Example 14
Source Project: Flink-CEPplus   Source File: StateDescriptorPassingTest.java    License: Apache License 2.0 6 votes vote down vote up
@Test
public void testReduceWindowState() throws Exception {
	final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);
	env.registerTypeWithKryoSerializer(File.class, JavaSerializer.class);

	DataStream<File> src = env.fromElements(new File("/"));

	SingleOutputStreamOperator<?> result = src
			.keyBy(new KeySelector<File, String>() {
				@Override
				public String getKey(File value) {
					return null;
				}
			})
			.timeWindow(Time.milliseconds(1000))
			.reduce(new ReduceFunction<File>() {

				@Override
				public File reduce(File value1, File value2) {
					return null;
				}
			});

	validateStateDescriptorConfigured(result);
}
 
Example 15
Source Project: flink   Source File: StreamTaskMailboxTestHarnessBuilder.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Users of the test harness can call this utility method to setup the stream config
 * if there will only be a single operator to be tested. The method will setup the
 * outgoing network connection for the operator.
 *
 * <p>For more advanced test cases such as testing chains of multiple operators with the harness,
 * please manually configure the stream config.
 */
public StreamTaskMailboxTestHarnessBuilder<OUT> setupOutputForSingletonOperatorChain(
		StreamOperatorFactory<?> factory,
		OperatorID operatorID) {
	checkState(!setupCalled, "This harness was already setup.");
	setupCalled = true;
	streamConfig.setChainStart();
	streamConfig.setTimeCharacteristic(TimeCharacteristic.EventTime);
	streamConfig.setOutputSelectors(Collections.<OutputSelector<?>>emptyList());
	streamConfig.setNumberOfOutputs(1);
	streamConfig.setTypeSerializerOut(outputSerializer);
	streamConfig.setVertexID(0);

	StreamOperator<OUT> dummyOperator = new AbstractStreamOperator<OUT>() {
		private static final long serialVersionUID = 1L;
	};

	List<StreamEdge> outEdgesInOrder = new LinkedList<StreamEdge>();
	StreamNode sourceVertexDummy = new StreamNode(0, "group", null, dummyOperator, "source dummy", new LinkedList<OutputSelector<?>>(), SourceStreamTask.class);
	StreamNode targetVertexDummy = new StreamNode(1, "group", null, dummyOperator, "target dummy", new LinkedList<OutputSelector<?>>(), SourceStreamTask.class);

	outEdgesInOrder.add(new StreamEdge(sourceVertexDummy, targetVertexDummy, 0, new LinkedList<String>(), new BroadcastPartitioner<Object>(), null /* output tag */));

	streamConfig.setOutEdgesInOrder(outEdgesInOrder);
	streamConfig.setNonChainedOutputs(outEdgesInOrder);

	streamConfig.setStreamOperatorFactory(factory);
	streamConfig.setOperatorID(operatorID);

	return this;
}
 
Example 16
Source Project: Flink-CEPplus   Source File: WindowTranslationTest.java    License: Apache License 2.0 5 votes vote down vote up
@Test
public void testAggregateWithEvictor() throws Exception {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);

	DataStream<Tuple3<String, String, Integer>> source = env.fromElements(
		Tuple3.of("hello", "hallo", 1),
		Tuple3.of("hello", "hallo", 2));

	DataStream<Integer> window1 = source
			.keyBy(new Tuple3KeySelector())
			.window(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.evictor(CountEvictor.of(100))
			.aggregate(new DummyAggregationFunction());

	final OneInputTransformation<Tuple3<String, String, Integer>, Integer> transform =
		(OneInputTransformation<Tuple3<String, String, Integer>, Integer>) window1.getTransformation();

	final OneInputStreamOperator<Tuple3<String, String, Integer>, Integer> operator = transform.getOperator();

	Assert.assertTrue(operator instanceof WindowOperator);
	WindowOperator<String, Tuple3<String, String, Integer>, ?, ?, ?> winOperator =
			(WindowOperator<String, Tuple3<String, String, Integer>, ?, ?, ?>) operator;

	Assert.assertTrue(winOperator.getTrigger() instanceof EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ListStateDescriptor);

	processElementAndEnsureOutput(
			winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple3<>("hello", "hallo", 1));
}
 
Example 17
Source Project: flink   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 5 votes vote down vote up
@Test
@SuppressWarnings("rawtypes")
public void testApplyEventTime() 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>> window1 = source
			.windowAll(TumblingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.apply(new AllWindowFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, TimeWindow>() {
				private static final long serialVersionUID = 1L;

				@Override
				public void apply(
						TimeWindow window,
						Iterable<Tuple2<String, Integer>> values,
						Collector<Tuple2<String, Integer>> out) throws Exception {
					for (Tuple2<String, Integer> in : values) {
						out.collect(in);
					}
				}
			});

	OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform = (OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window1.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 ListStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
 
Example 18
Source Project: flink   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 5 votes vote down vote up
@Test
@SuppressWarnings("rawtypes")
public void testFoldWithProcessAllWindowFunctionEventTime() 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
			.windowAll(TumblingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.fold(new Tuple3<>("", "", 0), new DummyFolder(), new ProcessAllWindowFunction<Tuple3<String, String, Integer>, Tuple2<String, Integer>, TimeWindow>() {
				private static final long serialVersionUID = 1L;
				@Override
				public void process(
						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 19
Source Project: flink   Source File: FlinkKafkaConsumerBaseMigrationTest.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Test restoring from an legacy empty state, when no partitions could be found for topics.
 */
@Test
public void testRestoreFromEmptyStateNoPartitions() throws Exception {
	final DummyFlinkKafkaConsumer<String> consumerFunction =
			new DummyFlinkKafkaConsumer<>(
				Collections.singletonList("dummy-topic"),
				Collections.<KafkaTopicPartition>emptyList(),
				FlinkKafkaConsumerBase.PARTITION_DISCOVERY_DISABLED);

	StreamSource<String, DummyFlinkKafkaConsumer<String>> consumerOperator = new StreamSource<>(consumerFunction);

	final AbstractStreamOperatorTestHarness<String> testHarness =
			new AbstractStreamOperatorTestHarness<>(consumerOperator, 1, 1, 0);

	testHarness.setTimeCharacteristic(TimeCharacteristic.ProcessingTime);

	testHarness.setup();

	// restore state from binary snapshot file
	testHarness.initializeState(
		OperatorSnapshotUtil.getResourceFilename(
			"kafka-consumer-migration-test-flink" + testMigrateVersion + "-empty-state-snapshot"));

	testHarness.open();

	// assert that no partitions were found and is empty
	assertTrue(consumerFunction.getSubscribedPartitionsToStartOffsets() != null);
	assertTrue(consumerFunction.getSubscribedPartitionsToStartOffsets().isEmpty());

	// assert that no state was restored
	assertTrue(consumerFunction.getRestoredState().isEmpty());

	consumerOperator.close();
	consumerOperator.cancel();
}
 
Example 20
/**
 * Test restoring from a non-empty state taken using a previous Flink version, when some partitions could be
 * found for topics.
 */
@Test
public void testRestore() throws Exception {
	final List<KafkaTopicPartition> partitions = new ArrayList<>(PARTITION_STATE.keySet());

	final DummyFlinkKafkaConsumer<String> consumerFunction =
		new DummyFlinkKafkaConsumer<>(TOPICS, partitions, FlinkKafkaConsumerBase.PARTITION_DISCOVERY_DISABLED);

	StreamSource<String, DummyFlinkKafkaConsumer<String>> consumerOperator =
			new StreamSource<>(consumerFunction);

	final AbstractStreamOperatorTestHarness<String> testHarness =
			new AbstractStreamOperatorTestHarness<>(consumerOperator, 1, 1, 0);

	testHarness.setTimeCharacteristic(TimeCharacteristic.ProcessingTime);

	testHarness.setup();

	// restore state from binary snapshot file
	testHarness.initializeState(
		OperatorSnapshotUtil.getResourceFilename(
			"kafka-consumer-migration-test-flink" + testMigrateVersion + "-snapshot"));

	testHarness.open();

	// assert that there are partitions and is identical to expected list
	assertTrue(consumerFunction.getSubscribedPartitionsToStartOffsets() != null);
	assertTrue(!consumerFunction.getSubscribedPartitionsToStartOffsets().isEmpty());

	// on restore, subscribedPartitionsToStartOffsets should be identical to the restored state
	assertEquals(PARTITION_STATE, consumerFunction.getSubscribedPartitionsToStartOffsets());

	// assert that state is correctly restored from legacy checkpoint
	assertTrue(consumerFunction.getRestoredState() != null);
	assertEquals(PARTITION_STATE, consumerFunction.getRestoredState());

	consumerOperator.close();
	consumerOperator.cancel();
}
 
Example 21
Source Project: Flink-CEPplus   Source File: WindowTranslationTest.java    License: Apache License 2.0 5 votes vote down vote up
@Test
public void testAggregateWithProcessWindowFunctionProcessingTime() throws Exception {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);

	DataStream<Tuple3<String, String, Integer>> source = env.fromElements(
		Tuple3.of("hello", "hallo", 1),
		Tuple3.of("hello", "hallo", 2));

	DataStream<String> window = source
			.keyBy(new Tuple3KeySelector())
			.window(TumblingProcessingTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.aggregate(new DummyAggregationFunction(), new TestProcessWindowFunction());

	final OneInputTransformation<Tuple3<String, String, Integer>, String> transform =
		(OneInputTransformation<Tuple3<String, String, Integer>, String>) window.getTransformation();

	final OneInputStreamOperator<Tuple3<String, String, Integer>, String> operator = transform.getOperator();

	Assert.assertTrue(operator instanceof WindowOperator);
	WindowOperator<String, Tuple3<String, String, Integer>, ?, ?, ?> winOperator =
		(WindowOperator<String, Tuple3<String, String, Integer>, ?, ?, ?>) operator;

	Assert.assertTrue(winOperator.getTrigger() instanceof ProcessingTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingProcessingTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof AggregatingStateDescriptor);

	processElementAndEnsureOutput(
			operator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple3<>("hello", "hallo", 1));
}
 
Example 22
Source Project: Flink-CEPplus   Source File: FlinkKafkaConsumerBaseTest.java    License: Apache License 2.0 5 votes vote down vote up
private static <T> AbstractStreamOperatorTestHarness<T> createTestHarness(
	SourceFunction<T> source, int numSubtasks, int subtaskIndex) throws Exception {

	AbstractStreamOperatorTestHarness<T> testHarness =
		new AbstractStreamOperatorTestHarness<>(
			new StreamSource<>(source), maxParallelism, numSubtasks, subtaskIndex);

	testHarness.setTimeCharacteristic(TimeCharacteristic.EventTime);

	return testHarness;
}
 
Example 23
Source Project: flink   Source File: StreamSourceOperatorWatermarksTest.java    License: Apache License 2.0 5 votes vote down vote up
@SuppressWarnings("unchecked")
private static <T> void setupSourceOperator(StreamSource<T, ?> operator,
											TimeCharacteristic timeChar,
											long watermarkInterval,
											final ProcessingTimeService timeProvider) throws Exception {

	ExecutionConfig executionConfig = new ExecutionConfig();
	executionConfig.setAutoWatermarkInterval(watermarkInterval);

	StreamConfig cfg = new StreamConfig(new Configuration());
	cfg.setStateBackend(new MemoryStateBackend());

	cfg.setTimeCharacteristic(timeChar);
	cfg.setOperatorID(new OperatorID());

	Environment env = new DummyEnvironment("MockTwoInputTask", 1, 0);

	StreamStatusMaintainer streamStatusMaintainer = mock(StreamStatusMaintainer.class);
	when(streamStatusMaintainer.getStreamStatus()).thenReturn(StreamStatus.ACTIVE);

	MockStreamTask mockTask = new MockStreamTaskBuilder(env)
		.setConfig(cfg)
		.setExecutionConfig(executionConfig)
		.setStreamStatusMaintainer(streamStatusMaintainer)
		.setProcessingTimeService(timeProvider)
		.build();

	operator.setup(mockTask, cfg, (Output<StreamRecord<T>>) mock(Output.class));
}
 
Example 24
Source Project: flink   Source File: WindowTranslationTest.java    License: Apache License 2.0 5 votes vote down vote up
@Test
public void testAggregateProcessingTime() throws Exception {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);

	DataStream<Tuple3<String, String, Integer>> source = env.fromElements(
		Tuple3.of("hello", "hallo", 1),
		Tuple3.of("hello", "hallo", 2));

	DataStream<Integer> window1 = source
			.keyBy(new Tuple3KeySelector())
			.window(SlidingProcessingTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.aggregate(new DummyAggregationFunction());

	final OneInputTransformation<Tuple3<String, String, Integer>, Integer> transform =
		(OneInputTransformation<Tuple3<String, String, Integer>, Integer>) window1.getTransformation();

	final OneInputStreamOperator<Tuple3<String, String, Integer>, Integer> operator = transform.getOperator();

	Assert.assertTrue(operator instanceof WindowOperator);
	WindowOperator<String, Tuple3<String, String, Integer>, ?, ?, ?> winOperator =
			(WindowOperator<String, Tuple3<String, String, Integer>, ?, ?, ?>) operator;

	Assert.assertTrue(winOperator.getTrigger() instanceof ProcessingTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof SlidingProcessingTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof AggregatingStateDescriptor);

	processElementAndEnsureOutput(
			winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple3<>("hello", "hallo", 1));
}
 
Example 25
Source Project: Flink-CEPplus   Source File: SessionWindowITCase.java    License: Apache License 2.0 5 votes vote down vote up
private void runTest(
		SourceFunction<SessionEvent<Integer, TestEventPayload>> dataSource,
		WindowFunction<SessionEvent<Integer, TestEventPayload>,
				String, Tuple, TimeWindow> windowFunction) throws Exception {

	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
	WindowedStream<SessionEvent<Integer, TestEventPayload>, Tuple, TimeWindow> windowedStream =
			env.addSource(dataSource).keyBy("sessionKey")
			.window(EventTimeSessionWindows.withGap(Time.milliseconds(MAX_SESSION_EVENT_GAP_MS)));

	if (ALLOWED_LATENESS_MS != Long.MAX_VALUE) {
		windowedStream = windowedStream.allowedLateness(Time.milliseconds(ALLOWED_LATENESS_MS));
	}

	if (PURGE_WINDOW_ON_FIRE) {
		windowedStream = windowedStream.trigger(PurgingTrigger.of(EventTimeTrigger.create()));
	}

	windowedStream.apply(windowFunction).print();
	JobExecutionResult result = env.execute();

	// check that overall event counts match with our expectations. remember that late events within lateness will
	// each trigger a window!
	Assert.assertEquals(
		(LATE_EVENTS_PER_SESSION + 1) * NUMBER_OF_SESSIONS * EVENTS_PER_SESSION,
		(long) result.getAccumulatorResult(SESSION_COUNTER_ON_TIME_KEY));
	Assert.assertEquals(
		NUMBER_OF_SESSIONS * (LATE_EVENTS_PER_SESSION * (LATE_EVENTS_PER_SESSION + 1) / 2),
		(long) result.getAccumulatorResult(SESSION_COUNTER_LATE_KEY));
}
 
Example 26
Source Project: flink   Source File: KafkaShuffleExactlyOnceITCase.java    License: Apache License 2.0 5 votes vote down vote up
private StreamExecutionEnvironment createEnvironment(
		int producerParallelism,
		TimeCharacteristic timeCharacteristic) {
	final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setParallelism(producerParallelism);
	env.setStreamTimeCharacteristic(timeCharacteristic);
	env.setRestartStrategy(RestartStrategies.fixedDelayRestart(1, 0));
	env.setBufferTimeout(0);
	env.enableCheckpointing(500);

	return env;
}
 
Example 27
Source Project: Flink-CEPplus   Source File: ValidatingSink.java    License: Apache License 2.0 5 votes vote down vote up
public ValidatingSink(
	@Nonnull CountUpdater<T> countUpdater,
	@Nonnull ResultChecker resultChecker,
	@Nonnull TimeCharacteristic timeCharacteristic) {

	this.resultChecker = resultChecker;
	this.countUpdater = countUpdater;
	this.usingProcessingTime = TimeCharacteristic.ProcessingTime == timeCharacteristic;
	this.windowCounts = new HashMap<>();
}
 
Example 28
/**
 * This test checks that reinterpreting a data stream to a keyed stream works as expected. This test consists of
 * two jobs. The first job materializes a keyBy into files, one files per partition. The second job opens the
 * files created by the first jobs as sources (doing the correct assignment of files to partitions) and
 * reinterprets the sources as keyed, because we know they have been partitioned in a keyBy from the first job.
 */
@Test
public void testReinterpretAsKeyedStream() throws Exception {

	final int maxParallelism = 8;
	final int numEventsPerInstance = 100;
	final int parallelism = 3;
	final int numTotalEvents = numEventsPerInstance * parallelism;
	final int numUniqueKeys = 100;

	final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);
	env.setMaxParallelism(maxParallelism);
	env.setParallelism(parallelism);
	env.enableCheckpointing(100);
	env.setRestartStrategy(RestartStrategies.fixedDelayRestart(1, 0L));

	final List<File> partitionFiles = new ArrayList<>(parallelism);
	for (int i = 0; i < parallelism; ++i) {
		File partitionFile = temporaryFolder.newFile();
		partitionFiles.add(i, partitionFile);
	}

	env.addSource(new RandomTupleSource(numEventsPerInstance, numUniqueKeys))
		.keyBy(0)
		.addSink(new ToPartitionFileSink(partitionFiles));

	env.execute();

	DataStreamUtils.reinterpretAsKeyedStream(
		env.addSource(new FromPartitionFileSource(partitionFiles)),
		(KeySelector<Tuple2<Integer, Integer>, Integer>) value -> value.f0,
		TypeInformation.of(Integer.class))
		.timeWindow(Time.seconds(1)) // test that also timers and aggregated state work as expected
		.reduce((ReduceFunction<Tuple2<Integer, Integer>>) (value1, value2) ->
			new Tuple2<>(value1.f0, value1.f1 + value2.f1))
		.addSink(new ValidatingSink(numTotalEvents)).setParallelism(1);

	env.execute();
}
 
Example 29
Source Project: flink   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 5 votes vote down vote up
@Test
@SuppressWarnings("rawtypes")
public void testApplyEventTime() 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>> window1 = source
			.windowAll(TumblingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.apply(new AllWindowFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, TimeWindow>() {
				private static final long serialVersionUID = 1L;

				@Override
				public void apply(
						TimeWindow window,
						Iterable<Tuple2<String, Integer>> values,
						Collector<Tuple2<String, Integer>> out) throws Exception {
					for (Tuple2<String, Integer> in : values) {
						out.collect(in);
					}
				}
			});

	OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform = (OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window1.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 ListStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
 
Example 30
Source Project: flink   Source File: AllWindowTranslationTest.java    License: Apache License 2.0 5 votes vote down vote up
@Test
public void testAggregateWithEvictor() 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>> window1 = source
			.windowAll(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.evictor(CountEvictor.of(100))
			.aggregate(new DummyAggregationFunction());

	OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform =
			(OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window1.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 SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ListStateDescriptor);

	processElementAndEnsureOutput(
			winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}