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Java DataStream.getTransformation方法代碼示例

本文整理匯總了Java中org.apache.flink.streaming.api.datastream.DataStream.getTransformation方法的典型用法代碼示例。如果您正苦於以下問題：Java DataStream.getTransformation方法的具體用法？Java DataStream.getTransformation怎麽用？Java DataStream.getTransformation使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類org.apache.flink.streaming.api.datastream.DataStream的用法示例。


在下文中一共展示了DataStream.getTransformation方法的15個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Java代碼示例。

示例1: testReduceEventTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@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));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:23，代碼來源:AllWindowTranslationTest.java

示例2: testFoldEventTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
@SuppressWarnings("rawtypes")
public void testFoldEventTime() 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)))
			.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 EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof SlidingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof FoldingStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:24，代碼來源:AllWindowTranslationTest.java

示例3: testFoldWithEvictor

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@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));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:27，代碼來源:AllWindowTranslationTest.java

示例4: testFoldWithProcessAllWindowFunctionEventTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@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));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:35，代碼來源:AllWindowTranslationTest.java

示例5: testFoldWithProcessAllWindowFunctionProcessingTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
@SuppressWarnings("rawtypes")
public void testFoldWithProcessAllWindowFunctionProcessingTime() 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>> window = source
			.windowAll(TumblingProcessingTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.fold(new Tuple3<>("", "empty", 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 ProcessingTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingProcessingTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof FoldingStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:36，代碼來源:AllWindowTranslationTest.java

示例6: testReduceWithCustomTrigger

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
@SuppressWarnings("rawtypes")
public void testReduceWithCustomTrigger() 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
			.keyBy(0)
			.window(SlidingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS), Time.of(100, TimeUnit.MILLISECONDS)))
			.trigger(CountTrigger.of(1))
			.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 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 ReducingStateDescriptor);

	processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:27，代碼來源:WindowTranslationTest.java

示例7: testFoldWithCustomTrigger

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
@SuppressWarnings("rawtypes")
public void testFoldWithCustomTrigger() 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
			.keyBy(0)
			.window(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));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:26，代碼來源:WindowTranslationTest.java

示例8: testCoGroupOperatorWithCheckpoint

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
/**
 * Verifies that pipelines including {@link CoGroupedStreams} can be checkpointed properly,
 * which includes snapshotting configurations of any involved serializers.
 *
 * @see <a href="https://issues.apache.org/jira/browse/FLINK-6808">FLINK-6808</a>
 */
@Test
public void testCoGroupOperatorWithCheckpoint() throws Exception {

	// generate an operator for the co-group operation
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
	env.setParallelism(1);

	DataStream<Tuple2<String, Integer>> source1 = env.fromElements(Tuple2.of("a", 0), Tuple2.of("b", 3));
	DataStream<Tuple2<String, Integer>> source2 = env.fromElements(Tuple2.of("a", 1), Tuple2.of("b", 6));

	DataStream<String> coGroupWindow = source1.coGroup(source2)
		.where(new Tuple2KeyExtractor())
		.equalTo(new Tuple2KeyExtractor())
		.window(TumblingEventTimeWindows.of(Time.of(3, TimeUnit.MILLISECONDS)))
		.apply(new CoGroupFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, String>() {
			@Override
			public void coGroup(Iterable<Tuple2<String, Integer>> first,
								Iterable<Tuple2<String, Integer>> second,
								Collector<String> out) throws Exception {
				out.collect(first + ":" + second);
			}
		});

	OneInputTransformation<Tuple2<String, Integer>, String> transform = (OneInputTransformation<Tuple2<String, Integer>, String>) coGroupWindow.getTransformation();
	OneInputStreamOperator<Tuple2<String, Integer>, String> operator = transform.getOperator();

	// wrap the operator in the test harness, and perform a snapshot
	OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, String> testHarness =
		new KeyedOneInputStreamOperatorTestHarness<>(operator, new Tuple2KeyExtractor(), BasicTypeInfo.STRING_TYPE_INFO);

	testHarness.open();
	testHarness.snapshot(0L, 0L);
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:41，代碼來源:CoGroupJoinITCase.java

示例9: testAggregateWithWindowFunctionEventTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
public void testAggregateWithWindowFunctionEventTime() 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>> window = source
			.windowAll(TumblingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.aggregate(new DummyAggregationFunction(), new TestAllWindowFunction());

	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 EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof AggregatingStateDescriptor);

	processElementAndEnsureOutput(
			operator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:28，代碼來源:AllWindowTranslationTest.java

示例10: testAlignedWindowDeprecation

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
/**
 * Verifies that calls to timeWindow() instantiate a regular
 * windowOperator instead of an aligned one.
 */
@Test
public void testAlignedWindowDeprecation() 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));

	DummyReducer reducer = new DummyReducer();

	DataStream<Tuple2<String, Integer>> window1 = source
			.keyBy(0)
			.timeWindow(Time.of(1000, TimeUnit.MILLISECONDS), Time.of(100, TimeUnit.MILLISECONDS))
			.reduce(reducer);

	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);

	DataStream<Tuple2<String, Integer>> window2 = source
			.keyBy(0)
			.timeWindow(Time.of(1000, TimeUnit.MILLISECONDS))
			.apply(new WindowFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple, TimeWindow>() {
				private static final long serialVersionUID = 1L;

				@Override
				public void apply(Tuple tuple,
						TimeWindow window,
						Iterable<Tuple2<String, Integer>> values,
						Collector<Tuple2<String, Integer>> out) throws Exception {

				}
			});

	OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>> transform2 = (OneInputTransformation<Tuple2<String, Integer>, Tuple2<String, Integer>>) window2.getTransformation();
	OneInputStreamOperator<Tuple2<String, Integer>, Tuple2<String, Integer>> operator2 = transform2.getOperator();
	Assert.assertTrue(operator2 instanceof WindowOperator);
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:42，代碼來源:TimeWindowTranslationTest.java

示例11: testReduceWithProcesWindowFunctionEventTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
@SuppressWarnings("rawtypes")
public void testReduceWithProcesWindowFunctionEventTime() 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<Tuple3<String, String, Integer>> window = source
			.keyBy(new TupleKeySelector())
			.window(TumblingEventTimeWindows.of(Time.of(1, TimeUnit.SECONDS)))
			.reduce(reducer, new ProcessWindowFunction<Tuple2<String, Integer>, Tuple3<String, String, Integer>, String, TimeWindow>() {
				private static final long serialVersionUID = 1L;

				@Override
				public void process(String key,
						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 EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof ReducingStateDescriptor);

	processElementAndEnsureOutput(operator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:39，代碼來源:WindowTranslationTest.java

示例12: testApplyProcessingTimeTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
@SuppressWarnings("rawtypes")
public void testApplyProcessingTimeTime() 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)))
			.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 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));

}
開發者ID:axbaretto，項目名稱:flink，代碼行數:36，代碼來源:AllWindowTranslationTest.java

示例13: testAggregateWithWindowFunctionEventTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
public void testAggregateWithWindowFunctionEventTime() 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));

	DummyReducer reducer = new DummyReducer();

	DataStream<String> window = source
			.keyBy(new Tuple3KeySelector())
			.window(TumblingEventTimeWindows.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 EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof AggregatingStateDescriptor);

	processElementAndEnsureOutput(
			operator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple3<>("hello", "hallo", 1));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:33，代碼來源:WindowTranslationTest.java

示例14: testAggregateWithWindowFunctionProcessingTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@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));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:31，代碼來源:WindowTranslationTest.java

示例15: testAggregateWithProcessWindowFunctionEventTime

import org.apache.flink.streaming.api.datastream.DataStream; //導入方法依賴的package包/類
@Test
public void testAggregateWithProcessWindowFunctionEventTime() 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<String> window = source
			.keyBy(new Tuple3KeySelector())
			.window(TumblingEventTimeWindows.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 EventTimeTrigger);
	Assert.assertTrue(winOperator.getWindowAssigner() instanceof TumblingEventTimeWindows);
	Assert.assertTrue(winOperator.getStateDescriptor() instanceof AggregatingStateDescriptor);

	processElementAndEnsureOutput(
			operator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple3<>("hello", "hallo", 1));
}
開發者ID:axbaretto，項目名稱:flink，代碼行數:31，代碼來源:WindowTranslationTest.java


注：本文中的org.apache.flink.streaming.api.datastream.DataStream.getTransformation方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。