org.apache.flink.api.common.functions.CoGroupFunction Java Examples

The following examples show how to use org.apache.flink.api.common.functions.CoGroupFunction. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example #1
Source File: TypeExtractor.java    From flink with Apache License 2.0 6 votes vote down vote up
@PublicEvolving
public static <IN1, IN2, OUT> TypeInformation<OUT> getCoGroupReturnTypes(CoGroupFunction<IN1, IN2, OUT> coGroupInterface,
		TypeInformation<IN1> in1Type, TypeInformation<IN2> in2Type, String functionName, boolean allowMissing)
{
	return getBinaryOperatorReturnType(
		(Function) coGroupInterface,
		CoGroupFunction.class,
		0,
		1,
		2,
		new int[]{2, 0},
		in1Type,
		in2Type,
		functionName,
		allowMissing);
}
 
Example #2
Source File: PlanBothUnwrappingCoGroupOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
public PlanBothUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		Keys.SelectorFunctionKeys<I1, K> key1,
		Keys.SelectorFunctionKeys<I2, K> key2,
		String name,
		TypeInformation<OUT> type,
		TypeInformation<Tuple2<K, I1>> typeInfoWithKey1,
		TypeInformation<Tuple2<K, I2>> typeInfoWithKey2) {

	super(
			new TupleBothUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<Tuple2<K, I1>, Tuple2<K, I2>, OUT>(
					typeInfoWithKey1,
					typeInfoWithKey2,
					type),
			key1.computeLogicalKeyPositions(),
			key2.computeLogicalKeyPositions(),
			name);
}
 
Example #3
Source File: PlanLeftUnwrappingCoGroupOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
public PlanLeftUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		Keys.SelectorFunctionKeys<I1, K> key1,
		int[] key2,
		String name,
		TypeInformation<OUT> resultType,
		TypeInformation<Tuple2<K, I1>> typeInfoWithKey1,
		TypeInformation<I2> typeInfo2) {

	super(
			new TupleLeftUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<Tuple2<K, I1>, I2, OUT>(
					typeInfoWithKey1,
					typeInfo2,
					resultType),
			key1.computeLogicalKeyPositions(),
			key2,
			name);
}
 
Example #4
Source File: TypeExtractor.java    From Flink-CEPplus with Apache License 2.0 6 votes vote down vote up
@PublicEvolving
public static <IN1, IN2, OUT> TypeInformation<OUT> getCoGroupReturnTypes(CoGroupFunction<IN1, IN2, OUT> coGroupInterface,
		TypeInformation<IN1> in1Type, TypeInformation<IN2> in2Type, String functionName, boolean allowMissing)
{
	return getBinaryOperatorReturnType(
		(Function) coGroupInterface,
		CoGroupFunction.class,
		0,
		1,
		2,
		new int[]{2, 0},
		in1Type,
		in2Type,
		functionName,
		allowMissing);
}
 
Example #5
Source File: CoGroupOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
private static <I1, I2, K, OUT> PlanBothUnwrappingCoGroupOperator<I1, I2, OUT, K> translateSelectorFunctionCoGroup(
		SelectorFunctionKeys<I1, ?> rawKeys1, SelectorFunctionKeys<I2, ?> rawKeys2,
		CoGroupFunction<I1, I2, OUT> function,
		TypeInformation<OUT> outputType, String name,
		Operator<I1> input1, Operator<I2> input2) {
	@SuppressWarnings("unchecked")
	final SelectorFunctionKeys<I1, K> keys1 = (SelectorFunctionKeys<I1, K>) rawKeys1;
	@SuppressWarnings("unchecked")
	final SelectorFunctionKeys<I2, K> keys2 = (SelectorFunctionKeys<I2, K>) rawKeys2;

	final TypeInformation<Tuple2<K, I1>> typeInfoWithKey1 = KeyFunctions.createTypeWithKey(keys1);
	final TypeInformation<Tuple2<K, I2>> typeInfoWithKey2 = KeyFunctions.createTypeWithKey(keys2);

	final Operator<Tuple2<K, I1>> keyedInput1 = KeyFunctions.appendKeyExtractor(input1, keys1);
	final Operator<Tuple2<K, I2>> keyedInput2 = KeyFunctions.appendKeyExtractor(input2, keys2);

	final PlanBothUnwrappingCoGroupOperator<I1, I2, OUT, K> cogroup =
		new PlanBothUnwrappingCoGroupOperator<>(function, keys1, keys2, name, outputType, typeInfoWithKey1, typeInfoWithKey2);

	cogroup.setFirstInput(keyedInput1);
	cogroup.setSecondInput(keyedInput2);

	return cogroup;
}
 
Example #6
Source File: PlanBothUnwrappingCoGroupOperator.java    From Flink-CEPplus with Apache License 2.0 6 votes vote down vote up
public PlanBothUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		Keys.SelectorFunctionKeys<I1, K> key1,
		Keys.SelectorFunctionKeys<I2, K> key2,
		String name,
		TypeInformation<OUT> type,
		TypeInformation<Tuple2<K, I1>> typeInfoWithKey1,
		TypeInformation<Tuple2<K, I2>> typeInfoWithKey2) {

	super(
			new TupleBothUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<Tuple2<K, I1>, Tuple2<K, I2>, OUT>(
					typeInfoWithKey1,
					typeInfoWithKey2,
					type),
			key1.computeLogicalKeyPositions(),
			key2.computeLogicalKeyPositions(),
			name);
}
 
Example #7
Source File: CoGroupRawOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
public CoGroupRawOperator(DataSet<I1> input1, DataSet<I2> input2,
		Keys<I1> keys1, Keys<I2> keys2,
		CoGroupFunction<I1, I2, OUT> function,
		TypeInformation<OUT> returnType,
		String defaultName) {
	super(input1, input2, returnType);
	this.function = function;
	this.defaultName = defaultName;
	this.name = defaultName;

	if (keys1 == null || keys2 == null) {
		throw new NullPointerException();
	}

	this.keys1 = keys1;
	this.keys2 = keys2;

	extractSemanticAnnotationsFromUdf(function.getClass());
}
 
Example #8
Source File: PlanRightUnwrappingCoGroupOperator.java    From Flink-CEPplus with Apache License 2.0 6 votes vote down vote up
public PlanRightUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		int[] key1,
		Keys.SelectorFunctionKeys<I2, K> key2,
		String name,
		TypeInformation<OUT> resultType,
		TypeInformation<I1> typeInfo1,
		TypeInformation<Tuple2<K, I2>> typeInfoWithKey2) {

	super(
			new TupleRightUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<I1, Tuple2<K, I2>, OUT>(
					typeInfo1,
					typeInfoWithKey2,
					resultType),
			key1,
			key2.computeLogicalKeyPositions(),
			name);
}
 
Example #9
Source File: CoGroupRawOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
public CoGroupRawOperator(DataSet<I1> input1, DataSet<I2> input2,
		Keys<I1> keys1, Keys<I2> keys2,
		CoGroupFunction<I1, I2, OUT> function,
		TypeInformation<OUT> returnType,
		String defaultName) {
	super(input1, input2, returnType);
	this.function = function;
	this.defaultName = defaultName;
	this.name = defaultName;

	if (keys1 == null || keys2 == null) {
		throw new NullPointerException();
	}

	this.keys1 = keys1;
	this.keys2 = keys2;

	extractSemanticAnnotationsFromUdf(function.getClass());
}
 
Example #10
Source File: CoGroupRawOperator.java    From Flink-CEPplus with Apache License 2.0 6 votes vote down vote up
public CoGroupRawOperator(DataSet<I1> input1, DataSet<I2> input2,
		Keys<I1> keys1, Keys<I2> keys2,
		CoGroupFunction<I1, I2, OUT> function,
		TypeInformation<OUT> returnType,
		String defaultName) {
	super(input1, input2, returnType);
	this.function = function;
	this.defaultName = defaultName;
	this.name = defaultName;

	if (keys1 == null || keys2 == null) {
		throw new NullPointerException();
	}

	this.keys1 = keys1;
	this.keys2 = keys2;

	extractSemanticAnnotationsFromUdf(function.getClass());
}
 
Example #11
Source File: CoGroupOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
private static <I1, I2, K, OUT> PlanBothUnwrappingCoGroupOperator<I1, I2, OUT, K> translateSelectorFunctionCoGroup(
		SelectorFunctionKeys<I1, ?> rawKeys1, SelectorFunctionKeys<I2, ?> rawKeys2,
		CoGroupFunction<I1, I2, OUT> function,
		TypeInformation<OUT> outputType, String name,
		Operator<I1> input1, Operator<I2> input2) {
	@SuppressWarnings("unchecked")
	final SelectorFunctionKeys<I1, K> keys1 = (SelectorFunctionKeys<I1, K>) rawKeys1;
	@SuppressWarnings("unchecked")
	final SelectorFunctionKeys<I2, K> keys2 = (SelectorFunctionKeys<I2, K>) rawKeys2;

	final TypeInformation<Tuple2<K, I1>> typeInfoWithKey1 = KeyFunctions.createTypeWithKey(keys1);
	final TypeInformation<Tuple2<K, I2>> typeInfoWithKey2 = KeyFunctions.createTypeWithKey(keys2);

	final Operator<Tuple2<K, I1>> keyedInput1 = KeyFunctions.appendKeyExtractor(input1, keys1);
	final Operator<Tuple2<K, I2>> keyedInput2 = KeyFunctions.appendKeyExtractor(input2, keys2);

	final PlanBothUnwrappingCoGroupOperator<I1, I2, OUT, K> cogroup =
		new PlanBothUnwrappingCoGroupOperator<>(function, keys1, keys2, name, outputType, typeInfoWithKey1, typeInfoWithKey2);

	cogroup.setFirstInput(keyedInput1);
	cogroup.setSecondInput(keyedInput2);

	return cogroup;
}
 
Example #12
Source File: PlanBothUnwrappingCoGroupOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
public PlanBothUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		Keys.SelectorFunctionKeys<I1, K> key1,
		Keys.SelectorFunctionKeys<I2, K> key2,
		String name,
		TypeInformation<OUT> type,
		TypeInformation<Tuple2<K, I1>> typeInfoWithKey1,
		TypeInformation<Tuple2<K, I2>> typeInfoWithKey2) {

	super(
			new TupleBothUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<Tuple2<K, I1>, Tuple2<K, I2>, OUT>(
					typeInfoWithKey1,
					typeInfoWithKey2,
					type),
			key1.computeLogicalKeyPositions(),
			key2.computeLogicalKeyPositions(),
			name);
}
 
Example #13
Source File: TypeExtractor.java    From flink with Apache License 2.0 6 votes vote down vote up
@PublicEvolving
public static <IN1, IN2, OUT> TypeInformation<OUT> getCoGroupReturnTypes(CoGroupFunction<IN1, IN2, OUT> coGroupInterface,
		TypeInformation<IN1> in1Type, TypeInformation<IN2> in2Type, String functionName, boolean allowMissing)
{
	return getBinaryOperatorReturnType(
		(Function) coGroupInterface,
		CoGroupFunction.class,
		0,
		1,
		2,
		new int[]{2, 0},
		in1Type,
		in2Type,
		functionName,
		allowMissing);
}
 
Example #14
Source File: PlanRightUnwrappingCoGroupOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
public PlanRightUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		int[] key1,
		Keys.SelectorFunctionKeys<I2, K> key2,
		String name,
		TypeInformation<OUT> resultType,
		TypeInformation<I1> typeInfo1,
		TypeInformation<Tuple2<K, I2>> typeInfoWithKey2) {

	super(
			new TupleRightUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<I1, Tuple2<K, I2>, OUT>(
					typeInfo1,
					typeInfoWithKey2,
					resultType),
			key1,
			key2.computeLogicalKeyPositions(),
			name);
}
 
Example #15
Source File: PlanLeftUnwrappingCoGroupOperator.java    From flink with Apache License 2.0 6 votes vote down vote up
public PlanLeftUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		Keys.SelectorFunctionKeys<I1, K> key1,
		int[] key2,
		String name,
		TypeInformation<OUT> resultType,
		TypeInformation<Tuple2<K, I1>> typeInfoWithKey1,
		TypeInformation<I2> typeInfo2) {

	super(
			new TupleLeftUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<Tuple2<K, I1>, I2, OUT>(
					typeInfoWithKey1,
					typeInfo2,
					resultType),
			key1.computeLogicalKeyPositions(),
			key2,
			name);
}
 
Example #16
Source File: PlanLeftUnwrappingCoGroupOperator.java    From Flink-CEPplus with Apache License 2.0 6 votes vote down vote up
public PlanLeftUnwrappingCoGroupOperator(
		CoGroupFunction<I1, I2, OUT> udf,
		Keys.SelectorFunctionKeys<I1, K> key1,
		int[] key2,
		String name,
		TypeInformation<OUT> resultType,
		TypeInformation<Tuple2<K, I1>> typeInfoWithKey1,
		TypeInformation<I2> typeInfo2) {

	super(
			new TupleLeftUnwrappingCoGrouper<I1, I2, OUT, K>(udf),
			new BinaryOperatorInformation<Tuple2<K, I1>, I2, OUT>(
					typeInfoWithKey1,
					typeInfo2,
					resultType),
			key1.computeLogicalKeyPositions(),
			key2,
			name);
}
 
Example #17
Source File: CoGroupedStreams.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up
/**
 * Completes the co-group operation with the user function that is executed
 * for windowed groups.
 *
 * <p>Note: This method's return type does not support setting an operator-specific parallelism.
 * Due to binary backwards compatibility, this cannot be altered. Use the
 * {@link #with(CoGroupFunction, TypeInformation)} method to set an operator-specific parallelism.
 */
public <T> DataStream<T> apply(CoGroupFunction<T1, T2, T> function, TypeInformation<T> resultType) {
	//clean the closure
	function = input1.getExecutionEnvironment().clean(function);

	UnionTypeInfo<T1, T2> unionType = new UnionTypeInfo<>(input1.getType(), input2.getType());
	UnionKeySelector<T1, T2, KEY> unionKeySelector = new UnionKeySelector<>(keySelector1, keySelector2);

	DataStream<TaggedUnion<T1, T2>> taggedInput1 = input1
			.map(new Input1Tagger<T1, T2>())
			.setParallelism(input1.getParallelism())
			.returns(unionType);
	DataStream<TaggedUnion<T1, T2>> taggedInput2 = input2
			.map(new Input2Tagger<T1, T2>())
			.setParallelism(input2.getParallelism())
			.returns(unionType);

	DataStream<TaggedUnion<T1, T2>> unionStream = taggedInput1.union(taggedInput2);

	// we explicitly create the keyed stream to manually pass the key type information in
	windowedStream =
			new KeyedStream<TaggedUnion<T1, T2>, KEY>(unionStream, unionKeySelector, keyType)
			.window(windowAssigner);

	if (trigger != null) {
		windowedStream.trigger(trigger);
	}
	if (evictor != null) {
		windowedStream.evictor(evictor);
	}
	if (allowedLateness != null) {
		windowedStream.allowedLateness(allowedLateness);
	}

	return windowedStream.apply(new CoGroupWindowFunction<T1, T2, T, KEY, W>(function), resultType);
}
 
Example #18
Source File: CoGroupJoinITCase.java    From flink with Apache License 2.0 5 votes vote down vote up
/**
 * 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);
}
 
Example #19
Source File: CoGroupedStreamsTest.java    From flink with Apache License 2.0 5 votes vote down vote up
@Before
public void setUp() {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	dataStream1 = env.fromElements("a1", "a2", "a3");
	dataStream2 = env.fromElements("a1", "a2");
	keySelector = element -> element;
	tsAssigner = TumblingEventTimeWindows.of(Time.milliseconds(1L));
	coGroupFunction = (CoGroupFunction<String, String, String>) (first, second, out) -> out.collect("");
}
 
Example #20
Source File: UdfAnalyzerExamplesTest.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up
@Test
public void testWebLogAnalysisExamplesAntiJoinVisits() {
	compareAnalyzerResultWithAnnotationsDualInputWithKeys(CoGroupFunction.class, AntiJoinVisits.class,
			TypeInformation.of(new TypeHint<Tuple3<Integer, String, Integer>>(){}),
			TypeInformation.of(new TypeHint<Tuple1<String>>(){}),
			TypeInformation.of(new TypeHint<Tuple3<Integer, String, Integer>>(){}),
			new String[] { "1" }, new String[] { "0" });
}
 
Example #21
Source File: CoGroupDriver.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up
@Override
public void run() throws Exception
{
	final Counter numRecordsOut = this.taskContext.getMetricGroup().getIOMetricGroup().getNumRecordsOutCounter();

	final CoGroupFunction<IT1, IT2, OT> coGroupStub = this.taskContext.getStub();
	final Collector<OT> collector = new CountingCollector<>(this.taskContext.getOutputCollector(), numRecordsOut);
	final CoGroupTaskIterator<IT1, IT2> coGroupIterator = this.coGroupIterator;
	
	while (this.running && coGroupIterator.next()) {
		coGroupStub.coGroup(coGroupIterator.getValues1(), coGroupIterator.getValues2(), collector);
	}
}
 
Example #22
Source File: CoGroupedStreamsTest.java    From flink with Apache License 2.0 5 votes vote down vote up
@Before
public void setUp() {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	dataStream1 = env.fromElements("a1", "a2", "a3");
	dataStream2 = env.fromElements("a1", "a2");
	keySelector = element -> element;
	tsAssigner = TumblingEventTimeWindows.of(Time.milliseconds(1L));
	coGroupFunction = (CoGroupFunction<String, String, String>) (first, second, out) -> out.collect("");
}
 
Example #23
Source File: CoGroupRawDriver.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up
@Override
public void run() throws Exception {
	final CoGroupFunction<IT1, IT2, OT> coGroupStub = this.taskContext.getStub();
	final Collector<OT> collector = this.taskContext.getOutputCollector();
	final SimpleIterable<IT1> i1 = this.coGroupIterator1;
	final SimpleIterable<IT2> i2 = this.coGroupIterator2;

	coGroupStub.coGroup(i1, i2, collector);
}
 
Example #24
Source File: CoGroupDriver.java    From flink with Apache License 2.0 5 votes vote down vote up
@Override
public void run() throws Exception
{
	final Counter numRecordsOut = this.taskContext.getMetricGroup().getIOMetricGroup().getNumRecordsOutCounter();

	final CoGroupFunction<IT1, IT2, OT> coGroupStub = this.taskContext.getStub();
	final Collector<OT> collector = new CountingCollector<>(this.taskContext.getOutputCollector(), numRecordsOut);
	final CoGroupTaskIterator<IT1, IT2> coGroupIterator = this.coGroupIterator;
	
	while (this.running && coGroupIterator.next()) {
		coGroupStub.coGroup(coGroupIterator.getValues1(), coGroupIterator.getValues2(), collector);
	}
}
 
Example #25
Source File: CoGroupedStreams.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up
/**
 * Completes the co-group operation with the user function that is executed
 * for windowed groups.
 *
 * <p>Note: This method's return type does not support setting an operator-specific parallelism.
 * Due to binary backwards compatibility, this cannot be altered. Use the {@link #with(CoGroupFunction)}
 * method to set an operator-specific parallelism.
 */
public <T> DataStream<T> apply(CoGroupFunction<T1, T2, T> function) {

	TypeInformation<T> resultType = TypeExtractor.getCoGroupReturnTypes(
		function,
		input1.getType(),
		input2.getType(),
		"CoGroup",
		false);

	return apply(function, resultType);
}
 
Example #26
Source File: CoGroupOperator.java    From flink with Apache License 2.0 5 votes vote down vote up
private static <I1, I2, K, OUT> PlanLeftUnwrappingCoGroupOperator<I1, I2, OUT, K> translateSelectorFunctionCoGroupLeft(
		SelectorFunctionKeys<I1, ?> rawKeys1, int[] logicalKeyPositions2,
		CoGroupFunction<I1, I2, OUT> function,
		TypeInformation<I2> inputType2, TypeInformation<OUT> outputType, String name,
		Operator<I1> input1, Operator<I2> input2) {
	if (!inputType2.isTupleType()) {
		throw new InvalidParameterException("Should not happen.");
	}

	@SuppressWarnings("unchecked")
	final SelectorFunctionKeys<I1, K> keys1 = (SelectorFunctionKeys<I1, K>) rawKeys1;
	final TypeInformation<Tuple2<K, I1>> typeInfoWithKey1 = KeyFunctions.createTypeWithKey(keys1);
	final Operator<Tuple2<K, I1>> keyedInput1 = KeyFunctions.appendKeyExtractor(input1, keys1);

	final PlanLeftUnwrappingCoGroupOperator<I1, I2, OUT, K> cogroup =
			new PlanLeftUnwrappingCoGroupOperator<>(
					function,
					keys1,
					logicalKeyPositions2,
					name,
					outputType,
					typeInfoWithKey1,
					inputType2);

	cogroup.setFirstInput(keyedInput1);
	cogroup.setSecondInput(input2);

	return cogroup;
}
 
Example #27
Source File: CoGroupedStreamsTest.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up
@Before
public void setUp() {
	StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
	dataStream1 = env.fromElements("a1", "a2", "a3");
	dataStream2 = env.fromElements("a1", "a2");
	keySelector = element -> element;
	tsAssigner = TumblingEventTimeWindows.of(Time.milliseconds(1L));
	coGroupFunction = (CoGroupFunction<String, String, String>) (first, second, out) -> out.collect("");
}
 
Example #28
Source File: CoGroupOperatorCollectionTest.java    From flink with Apache License 2.0 5 votes vote down vote up
private CoGroupOperatorBase<Tuple2<String, Integer>, Tuple2<String, Integer>,
		Tuple2<String, Integer>, CoGroupFunction<Tuple2<String, Integer>, Tuple2<String, Integer>,
		Tuple2<String, Integer>>> getCoGroupOperator(
		RichCoGroupFunction<Tuple2<String, Integer>, Tuple2<String, Integer>, Tuple2<String, Integer>> udf) {

	TypeInformation<Tuple2<String, Integer>> tuple2Info = TypeInformation.of(new TypeHint<Tuple2<String, Integer>>(){});

	return new CoGroupOperatorBase<>(
			udf,
			new BinaryOperatorInformation<>(tuple2Info, tuple2Info, tuple2Info),
			new int[]{0},
			new int[]{0},
			"coGroup on Collections"
	);
}
 
Example #29
Source File: LambdaExtractionTest.java    From flink with Apache License 2.0 5 votes vote down vote up
@Test
public void testCoGroupLambda() {
	CoGroupFunction<Tuple2<Tuple1<Integer>, Boolean>, Tuple2<Tuple1<Integer>, Double>, Tuple2<Tuple1<Integer>, String>> f = (i1, i2, o) -> {};

	TypeInformation<?> ti = TypeExtractor.getCoGroupReturnTypes(f, NESTED_TUPLE_BOOLEAN_TYPE, NESTED_TUPLE_DOUBLE_TYPE, null, true);
	if (!(ti instanceof MissingTypeInfo)) {
		assertTrue(ti.isTupleType());
		assertEquals(2, ti.getArity());
		assertTrue(((TupleTypeInfo<?>) ti).getTypeAt(0).isTupleType());
		assertEquals(((TupleTypeInfo<?>) ti).getTypeAt(1), BasicTypeInfo.STRING_TYPE_INFO);
	}
}
 
Example #30
Source File: LambdaExtractionTest.java    From flink with Apache License 2.0 5 votes vote down vote up
@Test
public void testCoGroupLambda() {
	CoGroupFunction<Tuple2<Tuple1<Integer>, Boolean>, Tuple2<Tuple1<Integer>, Double>, Tuple2<Tuple1<Integer>, String>> f = (i1, i2, o) -> {};

	TypeInformation<?> ti = TypeExtractor.getCoGroupReturnTypes(f, NESTED_TUPLE_BOOLEAN_TYPE, NESTED_TUPLE_DOUBLE_TYPE, null, true);
	if (!(ti instanceof MissingTypeInfo)) {
		assertTrue(ti.isTupleType());
		assertEquals(2, ti.getArity());
		assertTrue(((TupleTypeInfo<?>) ti).getTypeAt(0).isTupleType());
		assertEquals(((TupleTypeInfo<?>) ti).getTypeAt(1), BasicTypeInfo.STRING_TYPE_INFO);
	}
}