use of org.apache.flink.util.OutputTag in project flink by apache.
the class SideOutputITCase method testSideOutputWithMultipleConsumers.
@Test
public void testSideOutputWithMultipleConsumers() throws Exception {
final OutputTag<String> sideOutputTag = new OutputTag<String>("side") {
};
TestListResultSink<String> sideOutputResultSink1 = new TestListResultSink<>();
TestListResultSink<String> sideOutputResultSink2 = new TestListResultSink<>();
TestListResultSink<Integer> resultSink = new TestListResultSink<>();
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(3);
DataStream<Integer> dataStream = env.fromCollection(elements);
SingleOutputStreamOperator<Integer> passThroughtStream = dataStream.process(new ProcessFunction<Integer, Integer>() {
private static final long serialVersionUID = 1L;
@Override
public void processElement(Integer value, Context ctx, Collector<Integer> out) throws Exception {
out.collect(value);
ctx.output(sideOutputTag, "sideout-" + String.valueOf(value));
}
});
passThroughtStream.getSideOutput(sideOutputTag).addSink(sideOutputResultSink1);
passThroughtStream.getSideOutput(sideOutputTag).addSink(sideOutputResultSink2);
passThroughtStream.addSink(resultSink);
env.execute();
assertEquals(Arrays.asList("sideout-1", "sideout-2", "sideout-3", "sideout-4", "sideout-5"), sideOutputResultSink1.getSortedResult());
assertEquals(Arrays.asList("sideout-1", "sideout-2", "sideout-3", "sideout-4", "sideout-5"), sideOutputResultSink2.getSortedResult());
assertEquals(Arrays.asList(1, 2, 3, 4, 5), resultSink.getSortedResult());
}
use of org.apache.flink.util.OutputTag in project flink by apache.
the class SideOutputITCase method testCoProcessFunctionSideOutput.
/**
* Test CoProcessFunction side output.
*/
@Test
public void testCoProcessFunctionSideOutput() throws Exception {
final OutputTag<String> sideOutputTag = new OutputTag<String>("side") {
};
TestListResultSink<String> sideOutputResultSink = new TestListResultSink<>();
TestListResultSink<Integer> resultSink = new TestListResultSink<>();
StreamExecutionEnvironment see = StreamExecutionEnvironment.getExecutionEnvironment();
see.setParallelism(3);
DataStream<Integer> ds1 = see.fromCollection(elements);
DataStream<Integer> ds2 = see.fromCollection(elements);
SingleOutputStreamOperator<Integer> passThroughtStream = ds1.connect(ds2).process(new CoProcessFunction<Integer, Integer, Integer>() {
@Override
public void processElement1(Integer value, Context ctx, Collector<Integer> out) throws Exception {
if (value < 3) {
out.collect(value);
ctx.output(sideOutputTag, "sideout1-" + String.valueOf(value));
}
}
@Override
public void processElement2(Integer value, Context ctx, Collector<Integer> out) throws Exception {
if (value >= 3) {
out.collect(value);
ctx.output(sideOutputTag, "sideout2-" + String.valueOf(value));
}
}
});
passThroughtStream.getSideOutput(sideOutputTag).addSink(sideOutputResultSink);
passThroughtStream.addSink(resultSink);
see.execute();
assertEquals(Arrays.asList("sideout1-1", "sideout1-2", "sideout2-3", "sideout2-4", "sideout2-5"), sideOutputResultSink.getSortedResult());
assertEquals(Arrays.asList(1, 2, 3, 4, 5), resultSink.getSortedResult());
}
use of org.apache.flink.util.OutputTag in project flink by apache.
the class SideOutputITCase method testSideOutputWithMultipleConsumersWithObjectReuse.
@Test
public void testSideOutputWithMultipleConsumersWithObjectReuse() throws Exception {
final OutputTag<String> sideOutputTag = new OutputTag<String>("side") {
};
TestListResultSink<String> sideOutputResultSink1 = new TestListResultSink<>();
TestListResultSink<String> sideOutputResultSink2 = new TestListResultSink<>();
TestListResultSink<Integer> resultSink = new TestListResultSink<>();
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.getConfig().enableObjectReuse();
env.setParallelism(3);
DataStream<Integer> dataStream = env.fromCollection(elements);
SingleOutputStreamOperator<Integer> passThroughtStream = dataStream.process(new ProcessFunction<Integer, Integer>() {
private static final long serialVersionUID = 1L;
@Override
public void processElement(Integer value, Context ctx, Collector<Integer> out) throws Exception {
out.collect(value);
ctx.output(sideOutputTag, "sideout-" + String.valueOf(value));
}
});
passThroughtStream.getSideOutput(sideOutputTag).addSink(sideOutputResultSink1);
passThroughtStream.getSideOutput(sideOutputTag).addSink(sideOutputResultSink2);
passThroughtStream.addSink(resultSink);
env.execute();
assertEquals(Arrays.asList("sideout-1", "sideout-2", "sideout-3", "sideout-4", "sideout-5"), sideOutputResultSink1.getSortedResult());
assertEquals(Arrays.asList("sideout-1", "sideout-2", "sideout-3", "sideout-4", "sideout-5"), sideOutputResultSink2.getSortedResult());
assertEquals(Arrays.asList(1, 2, 3, 4, 5), resultSink.getSortedResult());
}
use of org.apache.flink.util.OutputTag in project flink by apache.
the class SortingBoundedInputITCase method testBatchExecutionWithTimersOneInput.
@Test
public void testBatchExecutionWithTimersOneInput() {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// set parallelism to 1 to have consistent order of results
env.setParallelism(1);
Configuration config = new Configuration();
config.set(ExecutionOptions.RUNTIME_MODE, RuntimeExecutionMode.BATCH);
env.configure(config, this.getClass().getClassLoader());
WatermarkStrategy<Tuple2<Integer, Integer>> watermarkStrategy = WatermarkStrategy.forGenerator(ctx -> GENERATE_WATERMARK_AFTER_4_14_TIMESTAMP).withTimestampAssigner((r, previousTimestamp) -> r.f1);
SingleOutputStreamOperator<Tuple2<Integer, Integer>> elements = env.fromElements(Tuple2.of(1, 3), Tuple2.of(1, 1), Tuple2.of(2, 1), Tuple2.of(1, 4), // late element
Tuple2.of(2, 3), // late element
Tuple2.of(1, 2), Tuple2.of(1, 13), Tuple2.of(1, 11), Tuple2.of(2, 14), // late element
Tuple2.of(1, 11)).assignTimestampsAndWatermarks(watermarkStrategy);
OutputTag<Integer> lateElements = new OutputTag<>("late_elements", BasicTypeInfo.INT_TYPE_INFO);
SingleOutputStreamOperator<Tuple3<Long, Integer, Integer>> sums = elements.map(element -> element.f0).keyBy(element -> element).process(new KeyedProcessFunction<Integer, Integer, Tuple3<Long, Integer, Integer>>() {
private MapState<Long, Integer> countState;
private ValueState<Long> previousTimestampState;
@Override
public void open(Configuration parameters) {
countState = getRuntimeContext().getMapState(new MapStateDescriptor<>("sum", BasicTypeInfo.LONG_TYPE_INFO, BasicTypeInfo.INT_TYPE_INFO));
previousTimestampState = getRuntimeContext().getState(new ValueStateDescriptor<>("previousTimestamp", BasicTypeInfo.LONG_TYPE_INFO));
}
@Override
public void processElement(Integer value, Context ctx, Collector<Tuple3<Long, Integer, Integer>> out) throws Exception {
Long elementTimestamp = ctx.timestamp();
long nextTen = ((elementTimestamp + 10) / 10) * 10;
ctx.timerService().registerEventTimeTimer(nextTen);
if (elementTimestamp < ctx.timerService().currentWatermark()) {
ctx.output(lateElements, value);
} else {
Long previousTimestamp = Optional.ofNullable(previousTimestampState.value()).orElse(0L);
assertThat(elementTimestamp, greaterThanOrEqualTo(previousTimestamp));
previousTimestampState.update(elementTimestamp);
Integer currentCount = Optional.ofNullable(countState.get(nextTen)).orElse(0);
countState.put(nextTen, currentCount + 1);
}
}
@Override
public void onTimer(long timestamp, OnTimerContext ctx, Collector<Tuple3<Long, Integer, Integer>> out) throws Exception {
out.collect(Tuple3.of(timestamp, ctx.getCurrentKey(), countState.get(timestamp)));
countState.remove(timestamp);
// this would go in infinite loop if we did not quiesce the
// timer service.
ctx.timerService().registerEventTimeTimer(timestamp + 1);
}
});
DataStream<Integer> lateStream = sums.getSideOutput(lateElements);
List<Integer> lateRecordsCollected = CollectionUtil.iteratorToList(DataStreamUtils.collect(lateStream));
List<Tuple3<Long, Integer, Integer>> sumsCollected = CollectionUtil.iteratorToList(DataStreamUtils.collect(sums));
assertTrue(lateRecordsCollected.isEmpty());
assertThat(sumsCollected, equalTo(Arrays.asList(Tuple3.of(10L, 1, 4), Tuple3.of(20L, 1, 3), Tuple3.of(10L, 2, 2), Tuple3.of(20L, 2, 1))));
}
use of org.apache.flink.util.OutputTag in project flink by apache.
the class SortingBoundedInputITCase method testBatchExecutionWithTimersTwoInput.
@Test
public void testBatchExecutionWithTimersTwoInput() {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// set parallelism to 1 to have consistent order of results
env.setParallelism(1);
Configuration config = new Configuration();
config.set(ExecutionOptions.RUNTIME_MODE, RuntimeExecutionMode.BATCH);
env.configure(config, this.getClass().getClassLoader());
WatermarkStrategy<Tuple2<Integer, Integer>> watermarkStrategy = WatermarkStrategy.forGenerator(ctx -> GENERATE_WATERMARK_AFTER_4_14_TIMESTAMP).withTimestampAssigner((r, previousTimestamp) -> r.f1);
SingleOutputStreamOperator<Integer> elements1 = env.fromElements(Tuple2.of(1, 3), Tuple2.of(1, 1), Tuple2.of(2, 1), Tuple2.of(1, 4), // late element
Tuple2.of(2, 3), // late element
Tuple2.of(1, 2), Tuple2.of(1, 13), Tuple2.of(1, 11), Tuple2.of(2, 14), // late element
Tuple2.of(1, 11)).assignTimestampsAndWatermarks(watermarkStrategy).map(element -> element.f0);
SingleOutputStreamOperator<Integer> elements2 = env.fromElements(Tuple2.of(1, 3), Tuple2.of(1, 1), Tuple2.of(2, 1), Tuple2.of(1, 4), // late element
Tuple2.of(2, 3), // late element
Tuple2.of(1, 2), Tuple2.of(1, 13), Tuple2.of(1, 11), Tuple2.of(2, 14), // late element
Tuple2.of(1, 11)).assignTimestampsAndWatermarks(watermarkStrategy).map(element -> element.f0);
OutputTag<Integer> lateElements = new OutputTag<>("late_elements", BasicTypeInfo.INT_TYPE_INFO);
SingleOutputStreamOperator<Tuple3<Long, Integer, Integer>> sums = elements1.connect(elements2).keyBy(element -> element, element -> element).process(new KeyedCoProcessFunction<Integer, Integer, Integer, Tuple3<Long, Integer, Integer>>() {
private MapState<Long, Integer> countState;
private ValueState<Long> previousTimestampState;
@Override
public void open(Configuration parameters) {
countState = getRuntimeContext().getMapState(new MapStateDescriptor<>("sum", BasicTypeInfo.LONG_TYPE_INFO, BasicTypeInfo.INT_TYPE_INFO));
previousTimestampState = getRuntimeContext().getState(new ValueStateDescriptor<>("previousTimestamp", BasicTypeInfo.LONG_TYPE_INFO));
}
@Override
public void processElement1(Integer value, Context ctx, Collector<Tuple3<Long, Integer, Integer>> out) throws Exception {
processElement(value, ctx);
}
@Override
public void processElement2(Integer value, Context ctx, Collector<Tuple3<Long, Integer, Integer>> out) throws Exception {
processElement(value, ctx);
}
private void processElement(Integer value, Context ctx) throws Exception {
Long elementTimestamp = ctx.timestamp();
long nextTen = ((elementTimestamp + 10) / 10) * 10;
ctx.timerService().registerEventTimeTimer(nextTen);
if (elementTimestamp < ctx.timerService().currentWatermark()) {
ctx.output(lateElements, value);
} else {
Long previousTimestamp = Optional.ofNullable(previousTimestampState.value()).orElse(0L);
assertThat(elementTimestamp, greaterThanOrEqualTo(previousTimestamp));
previousTimestampState.update(elementTimestamp);
Integer currentCount = Optional.ofNullable(countState.get(nextTen)).orElse(0);
countState.put(nextTen, currentCount + 1);
}
}
@Override
public void onTimer(long timestamp, OnTimerContext ctx, Collector<Tuple3<Long, Integer, Integer>> out) throws Exception {
out.collect(Tuple3.of(timestamp, ctx.getCurrentKey(), countState.get(timestamp)));
countState.remove(timestamp);
// this would go in infinite loop if we did not quiesce the
// timer service.
ctx.timerService().registerEventTimeTimer(timestamp + 1);
}
});
DataStream<Integer> lateStream = sums.getSideOutput(lateElements);
List<Integer> lateRecordsCollected = CollectionUtil.iteratorToList(DataStreamUtils.collect(lateStream));
List<Tuple3<Long, Integer, Integer>> sumsCollected = CollectionUtil.iteratorToList(DataStreamUtils.collect(sums));
assertTrue(lateRecordsCollected.isEmpty());
assertThat(sumsCollected, equalTo(Arrays.asList(Tuple3.of(10L, 1, 8), Tuple3.of(20L, 1, 6), Tuple3.of(10L, 2, 4), Tuple3.of(20L, 2, 2))));
}
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