本文整理汇总了Java中org.apache.flink.streaming.api.datastream.DataStream.getTransformation方法的典型用法代码示例。如果您正苦于以下问题：Java DataStream.getTransformation方法的具体用法？Java DataStream.getTransformation怎么用？Java DataStream.getTransformation使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类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个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: testReduceEventTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例2: testFoldEventTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例3: testFoldWithEvictor
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例4: testFoldWithProcessAllWindowFunctionEventTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例5: testFoldWithProcessAllWindowFunctionProcessingTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例6: testReduceWithCustomTrigger
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例7: testFoldWithCustomTrigger
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例8: testCoGroupOperatorWithCheckpoint
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
/**
* 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);
}
示例9: testAggregateWithWindowFunctionEventTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例10: testAlignedWindowDeprecation
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
/**
* 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);
}
示例11: testReduceWithProcesWindowFunctionEventTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例12: testApplyProcessingTimeTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例13: testAggregateWithWindowFunctionEventTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例14: testAggregateWithWindowFunctionProcessingTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}
示例15: testAggregateWithProcessWindowFunctionEventTime
import org.apache.flink.streaming.api.datastream.DataStream; //导入方法依赖的package包/类
@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));
}