Java Code Examples for org.apache.flink.streaming.api.environment.StreamExecutionEnvironment#setStreamTimeCharacteristic()

/**
 * .reduce() does not support RichReduceFunction, since the reduce function is used internally
 * in a {@code ReducingState}.
 */
@Test(expected = UnsupportedOperationException.class)
public void testReduceWithRichReducerFails() 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
			.windowAll(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.reduce(new RichReduceFunction<Tuple2<String, Integer>>() {
				private static final long serialVersionUID = -6448847205314995812L;

				@Override
				public Tuple2<String, Integer> reduce(Tuple2<String, Integer> value1,
						Tuple2<String, Integer> value2) throws Exception {
					return null;
				}
			});

	fail("exception was not thrown");
}
 

@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));
}
 

/**
 * .reduce() does not support RichReduceFunction, since the reduce function is used internally
 * in a {@code ReducingState}.
 */
@Test(expected = UnsupportedOperationException.class)
public void testReduceWithRichReducerFails() 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)))
		.reduce(new RichReduceFunction<Tuple2<String, Integer>>() {

			@Override
			public Tuple2<String, Integer> reduce(Tuple2<String, Integer> value1,
				Tuple2<String, Integer> value2) throws Exception {
				return null;
			}
		});

	fail("exception was not thrown");
}
 

@Test
public void testFoldWindowAllState() throws Exception {
	final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);
	env.registerTypeWithKryoSerializer(File.class, JavaSerializer.class);

	DataStream<String> src = env.fromElements("abc");

	SingleOutputStreamOperator<?> result = src
			.timeWindowAll(Time.milliseconds(1000))
			.fold(new File("/"), new FoldFunction<String, File>() {

				@Override
				public File fold(File a, String e) {
					return null;
				}
			});

	validateStateDescriptorConfigured(result);
}
 

@Test
@SuppressWarnings("rawtypes")
public void testReduceEventTimeWindows() 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
			.keyBy(0)
			.timeWindow(Time.of(1000, TimeUnit.MILLISECONDS), Time.of(100, TimeUnit.MILLISECONDS))
			.reduce(new DummyReducer());

	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 WindowOperator);
	WindowOperator winOperator1 = (WindowOperator) operator1;
	Assert.assertTrue(winOperator1.getTrigger() instanceof EventTimeTrigger);
	Assert.assertTrue(winOperator1.getWindowAssigner() instanceof SlidingEventTimeWindows);
	Assert.assertTrue(winOperator1.getStateDescriptor() instanceof ReducingStateDescriptor);
}
 

@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));
}
 

@Test
public void testAggregateEventTime() 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)))
			.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 AggregatingStateDescriptor);

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

@Test
public void testAggregateWithWindowFunctionProcessingTime() 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 TestWindowFunction());

	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));
}
 

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;
}
 

@Test
@SuppressWarnings("rawtypes")
public void testProcessProcessingTime() 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
			.windowAll(TumblingProcessingTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.process(new ProcessAllWindowFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, TimeWindow>() {
				private static final long serialVersionUID = 1L;

				@Override
				public void process(
						Context ctx,
						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 ProcessingTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingProcessingTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ListStateDescriptor);

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

}
 

@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));
}
 

@Test
@SuppressWarnings("rawtypes")
public void testReduceWithProcessWindowFunctionProcessingTime() 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>> window = source
			.windowAll(TumblingProcessingTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.reduce(new DummyReducer(), new ProcessAllWindowFunction<Tuple2<String, Integer>, Tuple3<String, String, Integer>, TimeWindow>() {
				private static final long serialVersionUID = 1L;

				@Override
				public void process(
						Context ctx,
						Iterable<Tuple2<String, Integer>> values,
						Collector<Tuple3<String, String, Integer>> out) throws Exception {
					for (Tuple2<String, Integer> in : values) {
						out.collect(new Tuple3<>(in.f0, in.f0, in.f1));
					}
				}
			});

	OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>> transform =
			(OneInputTransformation<Tuple2<String, Integer>, Tuple3<String, String, Integer>>) window.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 ProcessingTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingProcessingTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ReducingStateDescriptor);

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

public static void setupEnvironment(StreamExecutionEnvironment env, ParameterTool pt) throws Exception {

		// set checkpointing semantics
		String semantics = pt.get(TEST_SEMANTICS.key(), TEST_SEMANTICS.defaultValue());
		long checkpointInterval = pt.getLong(ENVIRONMENT_CHECKPOINT_INTERVAL.key(), ENVIRONMENT_CHECKPOINT_INTERVAL.defaultValue());
		CheckpointingMode checkpointingMode = semantics.equalsIgnoreCase("exactly-once")
			? CheckpointingMode.EXACTLY_ONCE
			: CheckpointingMode.AT_LEAST_ONCE;

		env.enableCheckpointing(checkpointInterval, checkpointingMode);

		// use event time
		env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);

		// parallelism
		env.setParallelism(pt.getInt(ENVIRONMENT_PARALLELISM.key(), ENVIRONMENT_PARALLELISM.defaultValue()));
		env.setMaxParallelism(pt.getInt(ENVIRONMENT_MAX_PARALLELISM.key(), ENVIRONMENT_MAX_PARALLELISM.defaultValue()));

		// restart strategy
		String restartStrategyConfig = pt.get(ENVIRONMENT_RESTART_STRATEGY.key());
		if (restartStrategyConfig != null) {
			RestartStrategies.RestartStrategyConfiguration restartStrategy;
			switch (restartStrategyConfig) {
				case "fixed_delay":
					restartStrategy = RestartStrategies.fixedDelayRestart(
						pt.getInt(
							ENVIRONMENT_RESTART_STRATEGY_FIXED_ATTEMPTS.key(),
							ENVIRONMENT_RESTART_STRATEGY_FIXED_ATTEMPTS.defaultValue()),
						pt.getLong(
							ENVIRONMENT_RESTART_STRATEGY_FIXED_DELAY.key(),
							ENVIRONMENT_RESTART_STRATEGY_FIXED_DELAY.defaultValue()));
					break;
				case "no_restart":
					restartStrategy = RestartStrategies.noRestart();
					break;
				default:
					throw new IllegalArgumentException("Unkown restart strategy: " + restartStrategyConfig);
			}
			env.setRestartStrategy(restartStrategy);
		}

		// state backend
		final String stateBackend = pt.get(
			STATE_BACKEND.key(),
			STATE_BACKEND.defaultValue());

		final String checkpointDir = pt.getRequired(STATE_BACKEND_CHECKPOINT_DIR.key());

		if ("file".equalsIgnoreCase(stateBackend)) {
			boolean asyncCheckpoints = pt.getBoolean(
				STATE_BACKEND_FILE_ASYNC.key(),
				STATE_BACKEND_FILE_ASYNC.defaultValue());

			env.setStateBackend((StateBackend) new FsStateBackend(checkpointDir, asyncCheckpoints));
		} else if ("rocks".equalsIgnoreCase(stateBackend)) {
			boolean incrementalCheckpoints = pt.getBoolean(
				STATE_BACKEND_ROCKS_INCREMENTAL.key(),
				STATE_BACKEND_ROCKS_INCREMENTAL.defaultValue());

			env.setStateBackend((StateBackend) new RocksDBStateBackend(checkpointDir, incrementalCheckpoints));
		} else {
			throw new IllegalArgumentException("Unknown backend requested: " + stateBackend);
		}

		boolean enableExternalizedCheckpoints = pt.getBoolean(
			ENVIRONMENT_EXTERNALIZE_CHECKPOINT.key(),
			ENVIRONMENT_EXTERNALIZE_CHECKPOINT.defaultValue());

		if (enableExternalizedCheckpoints) {
			String cleanupModeConfig = pt.get(
				ENVIRONMENT_EXTERNALIZE_CHECKPOINT_CLEANUP.key(),
				ENVIRONMENT_EXTERNALIZE_CHECKPOINT_CLEANUP.defaultValue());

			CheckpointConfig.ExternalizedCheckpointCleanup cleanupMode;
			switch (cleanupModeConfig) {
				case "retain":
					cleanupMode = CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION;
					break;
				case "delete":
					cleanupMode = CheckpointConfig.ExternalizedCheckpointCleanup.DELETE_ON_CANCELLATION;
					break;
				default:
					throw new IllegalArgumentException("Unknown clean up mode for externalized checkpoints: " + cleanupModeConfig);
			}

			env.getCheckpointConfig().enableExternalizedCheckpoints(cleanupMode);
		}

		// make parameters available in the web interface
		env.getConfig().setGlobalJobParameters(pt);
	}
 

@Test
public void testPreAggregatedSlidingTimeWindow() {
	final int numElementsPerKey = numElementsPerKey();
	final int windowSize = windowSize();
	final int windowSlide = windowSlide();
	final int numKeys = numKeys();

	try {
		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
		env.setParallelism(PARALLELISM);
		env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
		env.enableCheckpointing(100);
		env.setRestartStrategy(RestartStrategies.fixedDelayRestart(1, 0));
		env.getConfig().disableSysoutLogging();
		env.setStateBackend(this.stateBackend);
		env.getConfig().setUseSnapshotCompression(true);

		env
				.addSource(new FailingSource(new KeyedEventTimeGenerator(numKeys, windowSlide), numElementsPerKey))
				.rebalance()
				.keyBy(0)
				.timeWindow(Time.of(windowSize, MILLISECONDS), Time.of(windowSlide, MILLISECONDS))
				.reduce(
						new ReduceFunction<Tuple2<Long, IntType>>() {

							@Override
							public Tuple2<Long, IntType> reduce(
									Tuple2<Long, IntType> a,
									Tuple2<Long, IntType> b) {

								// validate that the function has been opened properly
								return new Tuple2<>(a.f0, new IntType(a.f1.value + b.f1.value));
							}
						},
						new RichWindowFunction<Tuple2<Long, IntType>, Tuple4<Long, Long, Long, IntType>, Tuple, TimeWindow>() {

					private boolean open = false;

					@Override
					public void open(Configuration parameters) {
						assertEquals(PARALLELISM, getRuntimeContext().getNumberOfParallelSubtasks());
						open = true;
					}

					@Override
					public void apply(
							Tuple tuple,
							TimeWindow window,
							Iterable<Tuple2<Long, IntType>> input,
							Collector<Tuple4<Long, Long, Long, IntType>> out) {

						// validate that the function has been opened properly
						assertTrue(open);

						for (Tuple2<Long, IntType> in: input) {
							out.collect(new Tuple4<>(in.f0,
									window.getStart(),
									window.getEnd(),
									in.f1));
						}
					}
				})
				.addSink(new ValidatingSink<>(
					new SinkValidatorUpdateFun(numElementsPerKey),
					new SinkValidatorCheckFun(numKeys, numElementsPerKey, windowSlide))).setParallelism(1);

		env.execute("Tumbling Window Test");
	}
	catch (Exception e) {
		e.printStackTrace();
		fail(e.getMessage());
	}
}
 

@Test
public void testTumblingProcessingTimeWindow() {
	final int numElements = 3000;

	try {
		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
		env.setParallelism(PARALLELISM);
		env.setStreamTimeCharacteristic(timeCharacteristic);
		env.getConfig().setAutoWatermarkInterval(10);
		env.enableCheckpointing(100);
		env.setRestartStrategy(RestartStrategies.fixedDelayRestart(1, 0));
		env.getConfig().disableSysoutLogging();

		SinkValidatorUpdaterAndChecker updaterAndChecker =
			new SinkValidatorUpdaterAndChecker(numElements, 1);

		env
				.addSource(new FailingSource(new Generator(), numElements, timeCharacteristic))
				.rebalance()
				.keyBy(0)
				.timeWindow(Time.of(100, MILLISECONDS))
				.apply(new RichWindowFunction<Tuple2<Long, IntType>, Tuple2<Long, IntType>, Tuple, TimeWindow>() {

					private boolean open = false;

					@Override
					public void open(Configuration parameters) {
						assertEquals(PARALLELISM, getRuntimeContext().getNumberOfParallelSubtasks());
						open = true;
					}

					@Override
					public void apply(
							Tuple tuple,
							TimeWindow window,
							Iterable<Tuple2<Long, IntType>> values,
							Collector<Tuple2<Long, IntType>> out) {

						// validate that the function has been opened properly
						assertTrue(open);

						for (Tuple2<Long, IntType> value : values) {
							assertEquals(value.f0.intValue(), value.f1.value);
							out.collect(new Tuple2<>(value.f0, new IntType(1)));
						}
					}
				})
			.addSink(new ValidatingSink<>(updaterAndChecker, updaterAndChecker, timeCharacteristic))
			.setParallelism(1);

		tryExecute(env, "Tumbling Window Test");
	}
	catch (Exception e) {
		e.printStackTrace();
		fail(e.getMessage());
	}
}
 

public static void main(String[] args) throws Exception {

		final ParameterTool params = ParameterTool.fromArgs(args);

		final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
		env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
		env.getConfig().setGlobalJobParameters(params);

		@SuppressWarnings({"rawtypes", "serial"})
		DataStream<Tuple4<Integer, Integer, Double, Long>> carData;
		if (params.has("input")) {
			carData = env.readTextFile(params.get("input")).map(new ParseCarData());
		} else {
			System.out.println("Executing TopSpeedWindowing example with default input data set.");
			System.out.println("Use --input to specify file input.");
			carData = env.addSource(CarSource.create(2));
		}

		int evictionSec = 10;
		double triggerMeters = 50;
		DataStream<Tuple4<Integer, Integer, Double, Long>> topSpeeds = carData
				.assignTimestampsAndWatermarks(new CarTimestamp())
				.keyBy(0)
				.window(GlobalWindows.create())
				.evictor(TimeEvictor.of(Time.of(evictionSec, TimeUnit.SECONDS)))
				.trigger(DeltaTrigger.of(triggerMeters,
						new DeltaFunction<Tuple4<Integer, Integer, Double, Long>>() {
							private static final long serialVersionUID = 1L;

							@Override
							public double getDelta(
									Tuple4<Integer, Integer, Double, Long> oldDataPoint,
									Tuple4<Integer, Integer, Double, Long> newDataPoint) {
								return newDataPoint.f2 - oldDataPoint.f2;
							}
						}, carData.getType().createSerializer(env.getConfig())))
				.maxBy(1);

		if (params.has("output")) {
			topSpeeds.writeAsText(params.get("output"));
		} else {
			System.out.println("Printing result to stdout. Use --output to specify output path.");
			topSpeeds.print();
		}

		env.execute("CarTopSpeedWindowingExample");
	}
 

private void testTableSourceStreamingDescriptor(Stream stream, PravegaConfig pravegaConfig) throws Exception {
    final StreamExecutionEnvironment execEnvRead = StreamExecutionEnvironment.getExecutionEnvironment();
    execEnvRead.setParallelism(1);
    execEnvRead.enableCheckpointing(100);
    execEnvRead.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);

    StreamTableEnvironment tableEnv = StreamTableEnvironment.create(execEnvRead,
            EnvironmentSettings.newInstance()
                    // watermark is only supported in blink planner
                    .useBlinkPlanner()
                    .inStreamingMode()
                    .build());
    RESULTS.clear();

    // read data from the stream using Table reader
    Schema schema = new Schema()
            .field("user", DataTypes.STRING())
            .field("uri", DataTypes.STRING())
            .field("accessTime", DataTypes.TIMESTAMP(3)).rowtime(
                    new Rowtime().timestampsFromField("accessTime").watermarksPeriodicBounded(30000L));

    Pravega pravega = new Pravega();
    pravega.tableSourceReaderBuilder()
            .withReaderGroupScope(stream.getScope())
            .forStream(stream)
            .withPravegaConfig(pravegaConfig);

    ConnectTableDescriptor desc = tableEnv.connect(pravega)
            .withFormat(new Json().failOnMissingField(true))
            .withSchema(schema)
            .inAppendMode();

    final Map<String, String> propertiesMap = desc.toProperties();
    final TableSource<?> source = TableFactoryService.find(StreamTableSourceFactory.class, propertiesMap)
            .createStreamTableSource(propertiesMap);

    String tableSourcePath = tableEnv.getCurrentDatabase() + "." + "MyTableRow";

    ConnectorCatalogTable<?, ?> connectorCatalogSourceTable = ConnectorCatalogTable.source(source, false);

    tableEnv.getCatalog(tableEnv.getCurrentCatalog()).get().createTable(
            ObjectPath.fromString(tableSourcePath),
            connectorCatalogSourceTable, false);

    String sqlQuery = "SELECT user, " +
            "TUMBLE_END(accessTime, INTERVAL '5' MINUTE) AS accessTime, " +
            "COUNT(uri) AS cnt " +
            "from MyTableRow GROUP BY " +
            "user, TUMBLE(accessTime, INTERVAL '5' MINUTE)";
    Table result = tableEnv.sqlQuery(sqlQuery);

    DataStream<Tuple2<Boolean, Row>> resultSet = tableEnv.toRetractStream(result, Row.class);
    StringSink2 stringSink = new StringSink2(8);
    resultSet.addSink(stringSink);

    try {
        execEnvRead.execute("ReadRowData");
    } catch (Exception e) {
        if (!(ExceptionUtils.getRootCause(e) instanceof SuccessException)) {
            throw e;
        }
    }

    log.info("results: {}", RESULTS);
    boolean compare = compare(RESULTS, getExpectedResultsAppend());
    assertTrue("Output does not match expected result", compare);
}
 

public static void main(String[] args) throws Exception {

		final ParameterTool params = ParameterTool.fromArgs(args);

		final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
		env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
		env.getConfig().setGlobalJobParameters(params);

		@SuppressWarnings({"rawtypes", "serial"})
		DataStream<Tuple4<Integer, Integer, Double, Long>> carData;
		if (params.has("input")) {
			carData = env.readTextFile(params.get("input")).map(new ParseCarData());
		} else {
			System.out.println("Executing TopSpeedWindowing example with default input data set.");
			System.out.println("Use --input to specify file input.");
			carData = env.addSource(CarSource.create(2));
		}

		int evictionSec = 10;
		double triggerMeters = 50;
		DataStream<Tuple4<Integer, Integer, Double, Long>> topSpeeds = carData
				.assignTimestampsAndWatermarks(new CarTimestamp())
				.keyBy(0)
				.window(GlobalWindows.create())
				.evictor(TimeEvictor.of(Time.of(evictionSec, TimeUnit.SECONDS)))
				.trigger(DeltaTrigger.of(triggerMeters,
						new DeltaFunction<Tuple4<Integer, Integer, Double, Long>>() {
							private static final long serialVersionUID = 1L;

							@Override
							public double getDelta(
									Tuple4<Integer, Integer, Double, Long> oldDataPoint,
									Tuple4<Integer, Integer, Double, Long> newDataPoint) {
								return newDataPoint.f2 - oldDataPoint.f2;
							}
						}, carData.getType().createSerializer(env.getConfig())))
				.maxBy(1);

		if (params.has("output")) {
			topSpeeds.writeAsText(params.get("output"));
		} else {
			System.out.println("Printing result to stdout. Use --output to specify output path.");
			topSpeeds.print();
		}

		env.execute("CarTopSpeedWindowingExample");
	}
 

public static void main(String[] args) throws Exception {
    LOG.info("Starting Event Time Average...");

    // initialize the parameter utility tool in order to retrieve input parameters
    ParameterTool params = ParameterTool.fromArgs(args);
    PravegaConfig pravegaConfig = PravegaConfig
            .fromParams(params)
            .withDefaultScope(Constants.DEFAULT_SCOPE);

    // Get or create the Pravega input/output stream
    Stream inputStream = Utils.createStream(
            pravegaConfig,
            params.get(Constants.INPUT_STREAM_PARAM, Constants.RAW_DATA_STREAM));
    Stream outputStream = Utils.createStream(
            pravegaConfig,
            params.getRequired(Constants.OUTPUT_STREAM_PARAM));

    // Get window length (in seconds) from parameters
    long windowLength = params.getInt(Constants.WINDOW_LENGTH_PARAM, 10);

    // initialize the Flink execution environment
    final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

    // Use event time characteristic
    env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
    // Set the auto watermark interval to 2 seconds
    env.getConfig().setAutoWatermarkInterval(2000);

    // create the Pravega source to read a stream of SensorData with Pravega watermark
    FlinkPravegaReader<SensorData> source = FlinkPravegaReader.<SensorData>builder()
            .withPravegaConfig(pravegaConfig)
            .forStream(inputStream)
            .withDeserializationSchema(PravegaSerialization.deserializationFor(SensorData.class))
            // provide an implementation of AssignerWithTimeWindows<T>
            .withTimestampAssigner(new LowerBoundAssigner<SensorData>() {
                @Override
                public long extractTimestamp(SensorData sensorData, long previousTimestamp) {
                    return sensorData.getTimestamp();
                }
            })
            .build();

    DataStream<SensorData> dataStream = env.addSource(source).name("Pravega Reader").uid("Pravega Reader")
            .setParallelism(Constants.PARALLELISM);

    // Calculate the average of each sensor in a 10 second period upon event-time clock.
    DataStream<SensorData> avgStream = dataStream
            .keyBy(SensorData::getSensorId)
            .timeWindow(Time.seconds(windowLength))
            .aggregate(new WindowAverage(), new WindowProcess())
            .uid("Count Event-time Average");

    // Print to stdout for verification
    avgStream.print().uid("Print to Std. Out");

    // Register a Flink Pravega writer with watermark enabled
    FlinkPravegaWriter<SensorData> writer = FlinkPravegaWriter.<SensorData>builder()
            .withPravegaConfig(pravegaConfig)
            .forStream(outputStream)
            // enable watermark propagation
            .enableWatermark(true)
            .withEventRouter(event -> String.valueOf(event.getSensorId()))
            .withSerializationSchema(PravegaSerialization.serializationFor(SensorData.class))
            .build();

    // Print to pravega sink for further usage
    avgStream.addSink(writer).name("Pravega Writer").uid("Pravega Writer");

    // execute within the Flink environment
    env.execute("Sensor Event Time Average");

    LOG.info("Ending Event Time Average...");
}
 

public static void main(String[] args) throws Exception {

        final long windowSize = 200L;
        final long rate = 3L;

        System.out.println("Using windowSize=" + windowSize + ", data rate=" + rate);
        System.out.println("To customize example, use: WindowJoin [--windowSize <window-size-in-millis>] [--rate <elements-per-second>]");

        // 获取env, 配置为"ingestion time"
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);


        // 生成 grade 和 salary 两个流 分别是 (name, grade) / (name, salary)
        DataStream<Tuple2<String, Integer>> grades = WindowJoinSampleData.GradeSource.getSource(env, rate);
        DataStream<Tuple2<String, Integer>> salaries = WindowJoinSampleData.SalarySource.getSource(env, rate);

        DataStream<Tuple3<String, Integer, Integer>> joinedStream = runWindowJoin(grades, salaries, windowSize);

        joinedStream.print().setParallelism(1);

        env.execute("Windowed Join Example");
    }