use of org.apache.flink.streaming.api.transformations.OneInputTransformation in project flink by apache.
the class AllWindowTranslationTest method testFoldWithEvictor.
@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));
}
use of org.apache.flink.streaming.api.transformations.OneInputTransformation in project flink by apache.
the class AllWindowTranslationTest method testReduceFastProcessingTime.
/**
* Ignored because we currently don't have the fast processing-time window operator.
*/
@Test
@SuppressWarnings("rawtypes")
@Ignore
public void testReduceFastProcessingTime() 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(SlidingProcessingTimeWindows.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>>) window.getTransformation();
OneInputStreamOperator<Tuple2<String, Integer>, Tuple2<String, Integer>> operator = transform.getOperator();
Assert.assertTrue(operator instanceof AggregatingProcessingTimeWindowOperator);
processElementAndEnsureOutput(operator, null, BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
use of org.apache.flink.streaming.api.transformations.OneInputTransformation in project flink by apache.
the class AllWindowTranslationTest method testFoldWithProcessAllWindowFunctionProcessingTime.
@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));
}
use of org.apache.flink.streaming.api.transformations.OneInputTransformation in project flink by apache.
the class AllWindowTranslationTest method testApplyWithPreFolderEventTime.
@Test
@SuppressWarnings("rawtypes")
public void testApplyWithPreFolderEventTime() 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))).apply(new Tuple3<>("", "", 0), new DummyFolder(), new AllWindowFunction<Tuple3<String, String, Integer>, Tuple3<String, String, Integer>, TimeWindow>() {
private static final long serialVersionUID = 1L;
@Override
public void apply(TimeWindow window, Iterable<Tuple3<String, String, Integer>> values, Collector<Tuple3<String, String, Integer>> out) throws Exception {
for (Tuple3<String, String, Integer> in : values) {
out.collect(new Tuple3<>(in.f0, in.f1, in.f2));
}
}
});
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 FoldingStateDescriptor);
processElementAndEnsureOutput(winOperator, winOperator.getKeySelector(), BasicTypeInfo.STRING_TYPE_INFO, new Tuple2<>("hello", 1));
}
use of org.apache.flink.streaming.api.transformations.OneInputTransformation in project flink by apache.
the class AllWindowTranslationTest method testFoldEventTime.
// ------------------------------------------------------------------------
// fold() translation tests
// ------------------------------------------------------------------------
@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));
}
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