@Test
public void testTypeInfo() {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStream<Long> src1 = env.generateSequence(0, 0);
assertEquals(TypeExtractor.getForClass(Long.class), src1.getType());
DataStream<Tuple2<Integer, String>> map =
src1.map(
new MapFunction<Long, Tuple2<Integer, String>>() {
@Override
public Tuple2<Integer, String> map(Long value) throws Exception {
return null;
}
});
assertEquals(TypeExtractor.getForObject(new Tuple2<>(0, "")), map.getType());
DataStream<String> window =
map.windowAll(GlobalWindows.create())
.trigger(PurgingTrigger.of(CountTrigger.of(5)))
.apply(
new AllWindowFunction<Tuple2<Integer, String>, String, GlobalWindow>() {
@Override
public void apply(
GlobalWindow window,
Iterable<Tuple2<Integer, String>> values,
Collector<String> out)
throws Exception {}
});
assertEquals(TypeExtractor.getForClass(String.class), window.getType());
DataStream<CustomPOJO> flatten =
window
.windowAll(GlobalWindows.create())
.trigger(PurgingTrigger.of(CountTrigger.of(5)))
.fold(
new CustomPOJO(),
new FoldFunction<String, CustomPOJO>() {
private static final long serialVersionUID = 1L;
@Override
public CustomPOJO fold(CustomPOJO accumulator, String value) throws Exception {
return null;
}
});
assertEquals(TypeExtractor.getForClass(CustomPOJO.class), flatten.getType());
}
/**
* Windows this {@code DataStream} into tumbling count windows.
*
* <p>Note: This operation can be inherently non-parallel since all elements have to pass through
* the same operator instance. (Only for special cases, such as aligned time windows is it
* possible to perform this operation in parallel).
*
* @param size The size of the windows in number of elements.
*/
public AllWindowedStream<T, GlobalWindow> countWindowAll(long size) {
return windowAll(GlobalWindows.create()).trigger(PurgingTrigger.of(CountTrigger.of(size)));
}
@Test
@SuppressWarnings("unchecked")
public void testCountTrigger() throws Exception {
closeCalled.set(0);
final int WINDOW_SIZE = 4;
TypeInformation<Tuple2<String, Integer>> inputType =
TypeInfoParser.parse("Tuple2<String, Integer>");
ReducingStateDescriptor<Tuple2<String, Integer>> stateDesc =
new ReducingStateDescriptor<>(
"window-contents", new SumReducer(), inputType.createSerializer(new ExecutionConfig()));
WindowOperator<
String,
Tuple2<String, Integer>,
Tuple2<String, Integer>,
Tuple2<String, Integer>,
GlobalWindow>
operator =
new WindowOperator<>(
GlobalWindows.create(),
new GlobalWindow.Serializer(),
new TupleKeySelector(),
BasicTypeInfo.STRING_TYPE_INFO.createSerializer(new ExecutionConfig()),
stateDesc,
new InternalSingleValueWindowFunction<>(
new PassThroughWindowFunction<String, GlobalWindow, Tuple2<String, Integer>>()),
PurgingTrigger.of(CountTrigger.of(WINDOW_SIZE)));
operator.setInputType(
TypeInfoParser.<Tuple2<String, Integer>>parse("Tuple2<String, Integer>"),
new ExecutionConfig());
OneInputStreamOperatorTestHarness<Tuple2<String, Integer>, Tuple2<String, Integer>>
testHarness = new OneInputStreamOperatorTestHarness<>(operator);
testHarness.configureForKeyedStream(new TupleKeySelector(), BasicTypeInfo.STRING_TYPE_INFO);
long initialTime = 0L;
ConcurrentLinkedQueue<Object> expectedOutput = new ConcurrentLinkedQueue<>();
testHarness.open();
// The global window actually ignores these timestamps...
// add elements out-of-order
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 3000));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 3999));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), initialTime + 20));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), initialTime));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), initialTime + 999));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 1998));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 1999));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 1000));
expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 4), Long.MAX_VALUE));
TestHarnessUtil.assertOutputEqualsSorted(
"Output was not correct.",
expectedOutput,
testHarness.getOutput(),
new ResultSortComparator());
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key1", 1), initialTime + 10999));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 1000));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 1000));
testHarness.processElement(new StreamRecord<>(new Tuple2<>("key2", 1), initialTime + 1000));
expectedOutput.add(new StreamRecord<>(new Tuple2<>("key1", 4), Long.MAX_VALUE));
expectedOutput.add(new StreamRecord<>(new Tuple2<>("key2", 4), Long.MAX_VALUE));
TestHarnessUtil.assertOutputEqualsSorted(
"Output was not correct.",
expectedOutput,
testHarness.getOutput(),
new ResultSortComparator());
testHarness.close();
}
/**
* Tests {@link SingleOutputStreamOperator#name(String)} functionality.
*
* @throws Exception
*/
@Test
public void testNaming() throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStream<Long> dataStream1 =
env.generateSequence(0, 0)
.name("testSource1")
.map(
new MapFunction<Long, Long>() {
@Override
public Long map(Long value) throws Exception {
return null;
}
})
.name("testMap");
DataStream<Long> dataStream2 =
env.generateSequence(0, 0)
.name("testSource2")
.map(
new MapFunction<Long, Long>() {
@Override
public Long map(Long value) throws Exception {
return null;
}
})
.name("testMap");
DataStreamSink<Long> connected =
dataStream1
.connect(dataStream2)
.flatMap(
new CoFlatMapFunction<Long, Long, Long>() {
private static final long serialVersionUID = 1L;
@Override
public void flatMap1(Long value, Collector<Long> out) throws Exception {}
@Override
public void flatMap2(Long value, Collector<Long> out) throws Exception {}
})
.name("testCoFlatMap")
.windowAll(GlobalWindows.create())
.trigger(PurgingTrigger.of(CountTrigger.of(10)))
.fold(
0L,
new FoldFunction<Long, Long>() {
private static final long serialVersionUID = 1L;
@Override
public Long fold(Long accumulator, Long value) throws Exception {
return null;
}
})
.name("testWindowFold")
.print();
// test functionality through the operator names in the execution plan
String plan = env.getExecutionPlan();
assertTrue(plan.contains("testSource1"));
assertTrue(plan.contains("testSource2"));
assertTrue(plan.contains("testMap"));
assertTrue(plan.contains("testMap"));
assertTrue(plan.contains("testCoFlatMap"));
assertTrue(plan.contains("testWindowFold"));
}
/** Tests whether parallelism gets set. */
@Test
public void testParallelism() {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<Tuple2<Long, Long>> src = env.fromElements(new Tuple2<>(0L, 0L));
env.setParallelism(10);
SingleOutputStreamOperator<Long, ?> map =
src.map(
new MapFunction<Tuple2<Long, Long>, Long>() {
@Override
public Long map(Tuple2<Long, Long> value) throws Exception {
return null;
}
})
.name("MyMap");
DataStream<Long> windowed =
map.windowAll(GlobalWindows.create())
.trigger(PurgingTrigger.of(CountTrigger.of(10)))
.fold(
0L,
new FoldFunction<Long, Long>() {
@Override
public Long fold(Long accumulator, Long value) throws Exception {
return null;
}
});
windowed.addSink(new NoOpSink<Long>());
DataStreamSink<Long> sink =
map.addSink(
new SinkFunction<Long>() {
private static final long serialVersionUID = 1L;
@Override
public void invoke(Long value) throws Exception {}
});
assertEquals(1, env.getStreamGraph().getStreamNode(src.getId()).getParallelism());
assertEquals(10, env.getStreamGraph().getStreamNode(map.getId()).getParallelism());
assertEquals(1, env.getStreamGraph().getStreamNode(windowed.getId()).getParallelism());
assertEquals(
10, env.getStreamGraph().getStreamNode(sink.getTransformation().getId()).getParallelism());
env.setParallelism(7);
// Some parts, such as windowing rely on the fact that previous operators have a parallelism
// set when instantiating the Discretizer. This would break if we dynamically changed
// the parallelism of operations when changing the setting on the Execution Environment.
assertEquals(1, env.getStreamGraph().getStreamNode(src.getId()).getParallelism());
assertEquals(10, env.getStreamGraph().getStreamNode(map.getId()).getParallelism());
assertEquals(1, env.getStreamGraph().getStreamNode(windowed.getId()).getParallelism());
assertEquals(
10, env.getStreamGraph().getStreamNode(sink.getTransformation().getId()).getParallelism());
try {
src.setParallelism(3);
fail();
} catch (IllegalArgumentException success) {
// do nothing
}
DataStreamSource<Long> parallelSource = env.generateSequence(0, 0);
parallelSource.addSink(new NoOpSink<Long>());
assertEquals(7, env.getStreamGraph().getStreamNode(parallelSource.getId()).getParallelism());
parallelSource.setParallelism(3);
assertEquals(3, env.getStreamGraph().getStreamNode(parallelSource.getId()).getParallelism());
map.setParallelism(2);
assertEquals(2, env.getStreamGraph().getStreamNode(map.getId()).getParallelism());
sink.setParallelism(4);
assertEquals(
4, env.getStreamGraph().getStreamNode(sink.getTransformation().getId()).getParallelism());
}
