Java Code Examples for org.apache.flink.api.common.operators.base.MapOperatorBase#setInput()

The following examples show how to use org.apache.flink.api.common.operators.base.MapOperatorBase#setInput() . 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: MapOperator.java    From Flink-CEPplus with Apache License 2.0 6 votes vote down vote up 
@Override
protected MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> translateToDataFlow(Operator<IN> input) {

	String name = getName() != null ? getName() : "Map at " + defaultName;
	// create operator
	MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> po = new MapOperatorBase<IN, OUT, MapFunction<IN, OUT>>(function,
			new UnaryOperatorInformation<IN, OUT>(getInputType(), getResultType()), name);
	// set input
	po.setInput(input);
	// set parallelism
	if (this.getParallelism() > 0) {
		// use specified parallelism
		po.setParallelism(this.getParallelism());
	} else {
		// if no parallelism has been specified, use parallelism of input operator to enable chaining
		po.setParallelism(input.getParallelism());
	}

	return po;
}
Example 2
Source File: KeyFunctions.java    From Flink-CEPplus with Apache License 2.0 6 votes vote down vote up 
public static <T, K> org.apache.flink.api.common.operators.SingleInputOperator<?, T, ?> appendKeyRemover(
		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> inputWithKey,
		SelectorFunctionKeys<T, K> key) {

	TypeInformation<T> inputType = key.getInputType();
	TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);

	MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>> mapper =
			new MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>>(
					new KeyRemovingMapper<T, K>(),
					new UnaryOperatorInformation<>(typeInfoWithKey, inputType),
					"Key Remover"
			);
	mapper.setInput(inputWithKey);
	mapper.setParallelism(inputWithKey.getParallelism());

	return mapper;
}
Example 3
Source File: MapOperator.java    From flink with Apache License 2.0 6 votes vote down vote up 
@Override
protected MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> translateToDataFlow(Operator<IN> input) {

	String name = getName() != null ? getName() : "Map at " + defaultName;
	// create operator
	MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> po = new MapOperatorBase<IN, OUT, MapFunction<IN, OUT>>(function,
			new UnaryOperatorInformation<IN, OUT>(getInputType(), getResultType()), name);
	// set input
	po.setInput(input);
	// set parallelism
	if (this.getParallelism() > 0) {
		// use specified parallelism
		po.setParallelism(this.getParallelism());
	} else {
		// if no parallelism has been specified, use parallelism of input operator to enable chaining
		po.setParallelism(input.getParallelism());
	}

	return po;
}
Example 4
Source File: KeyFunctions.java    From flink with Apache License 2.0 6 votes vote down vote up 
public static <T, K> org.apache.flink.api.common.operators.SingleInputOperator<?, T, ?> appendKeyRemover(
		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> inputWithKey,
		SelectorFunctionKeys<T, K> key) {

	TypeInformation<T> inputType = key.getInputType();
	TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);

	MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>> mapper =
			new MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>>(
					new KeyRemovingMapper<T, K>(),
					new UnaryOperatorInformation<>(typeInfoWithKey, inputType),
					"Key Remover"
			);
	mapper.setInput(inputWithKey);
	mapper.setParallelism(inputWithKey.getParallelism());

	return mapper;
}
Example 5
Source File: MapOperator.java    From flink with Apache License 2.0 6 votes vote down vote up 
@Override
protected MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> translateToDataFlow(Operator<IN> input) {

	String name = getName() != null ? getName() : "Map at " + defaultName;
	// create operator
	MapOperatorBase<IN, OUT, MapFunction<IN, OUT>> po = new MapOperatorBase<IN, OUT, MapFunction<IN, OUT>>(function,
			new UnaryOperatorInformation<IN, OUT>(getInputType(), getResultType()), name);
	// set input
	po.setInput(input);
	// set parallelism
	if (this.getParallelism() > 0) {
		// use specified parallelism
		po.setParallelism(this.getParallelism());
	} else {
		// if no parallelism has been specified, use parallelism of input operator to enable chaining
		po.setParallelism(input.getParallelism());
	}

	return po;
}
Example 6
Source File: KeyFunctions.java    From flink with Apache License 2.0 6 votes vote down vote up 
public static <T, K> org.apache.flink.api.common.operators.SingleInputOperator<?, T, ?> appendKeyRemover(
		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> inputWithKey,
		SelectorFunctionKeys<T, K> key) {

	TypeInformation<T> inputType = key.getInputType();
	TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);

	MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>> mapper =
			new MapOperatorBase<Tuple2<K, T>, T, MapFunction<Tuple2<K, T>, T>>(
					new KeyRemovingMapper<T, K>(),
					new UnaryOperatorInformation<>(typeInfoWithKey, inputType),
					"Key Remover"
			);
	mapper.setInput(inputWithKey);
	mapper.setParallelism(inputWithKey.getParallelism());

	return mapper;
}
Example 7
Source File: KeyFunctions.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up 
@SuppressWarnings("unchecked")
public static <T, K> org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> appendKeyExtractor(
		org.apache.flink.api.common.operators.Operator<T> input,
		SelectorFunctionKeys<T, K> key) {

	if (input instanceof Union) {
		// if input is a union, we apply the key extractors recursively to all inputs
		org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
		org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();

		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> firstInputWithKey =
				appendKeyExtractor(firstInput, key);
		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> secondInputWithKey =
				appendKeyExtractor(secondInput, key);

		return new Union(firstInputWithKey, secondInputWithKey, input.getName());
	}

	TypeInformation<T> inputType = key.getInputType();
	TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);
	KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper(key.getKeyExtractor());

	MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> mapper =
			new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(
					extractor,
					new UnaryOperatorInformation(inputType, typeInfoWithKey),
					"Key Extractor"
			);

	mapper.setInput(input);
	mapper.setParallelism(input.getParallelism());

	return mapper;
}
Example 8
Source File: KeyFunctions.java    From Flink-CEPplus with Apache License 2.0 5 votes vote down vote up 
@SuppressWarnings("unchecked")
public static <T, K1, K2> org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> appendKeyExtractor(
		org.apache.flink.api.common.operators.Operator<T> input,
		SelectorFunctionKeys<T, K1> key1,
		SelectorFunctionKeys<T, K2> key2) {

	if (input instanceof Union) {
		// if input is a union, we apply the key extractors recursively to all inputs
		org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
		org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();

		org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> firstInputWithKey =
				appendKeyExtractor(firstInput, key1, key2);
		org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> secondInputWithKey =
				appendKeyExtractor(secondInput, key1, key2);

		return new Union(firstInputWithKey, secondInputWithKey, input.getName());
	}

	TypeInformation<T> inputType = key1.getInputType();
	TypeInformation<Tuple3<K1, K2, T>> typeInfoWithKey = createTypeWithKey(key1, key2);
	TwoKeyExtractingMapper<T, K1, K2> extractor =
			new TwoKeyExtractingMapper<>(key1.getKeyExtractor(), key2.getKeyExtractor());

	MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>> mapper =
			new MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>>(
					extractor,
					new UnaryOperatorInformation<>(inputType, typeInfoWithKey),
					"Key Extractor"
			);

	mapper.setInput(input);
	mapper.setParallelism(input.getParallelism());

	return mapper;
}
Example 9
Source File: KeyFunctions.java    From flink with Apache License 2.0 5 votes vote down vote up 
@SuppressWarnings("unchecked")
public static <T, K> org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> appendKeyExtractor(
		org.apache.flink.api.common.operators.Operator<T> input,
		SelectorFunctionKeys<T, K> key) {

	if (input instanceof Union) {
		// if input is a union, we apply the key extractors recursively to all inputs
		org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
		org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();

		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> firstInputWithKey =
				appendKeyExtractor(firstInput, key);
		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> secondInputWithKey =
				appendKeyExtractor(secondInput, key);

		return new Union(firstInputWithKey, secondInputWithKey, input.getName());
	}

	TypeInformation<T> inputType = key.getInputType();
	TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);
	KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper(key.getKeyExtractor());

	MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> mapper =
			new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(
					extractor,
					new UnaryOperatorInformation(inputType, typeInfoWithKey),
					"Key Extractor"
			);

	mapper.setInput(input);
	mapper.setParallelism(input.getParallelism());

	return mapper;
}
Example 10
Source File: KeyFunctions.java    From flink with Apache License 2.0 5 votes vote down vote up 
@SuppressWarnings("unchecked")
public static <T, K1, K2> org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> appendKeyExtractor(
		org.apache.flink.api.common.operators.Operator<T> input,
		SelectorFunctionKeys<T, K1> key1,
		SelectorFunctionKeys<T, K2> key2) {

	if (input instanceof Union) {
		// if input is a union, we apply the key extractors recursively to all inputs
		org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
		org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();

		org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> firstInputWithKey =
				appendKeyExtractor(firstInput, key1, key2);
		org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> secondInputWithKey =
				appendKeyExtractor(secondInput, key1, key2);

		return new Union(firstInputWithKey, secondInputWithKey, input.getName());
	}

	TypeInformation<T> inputType = key1.getInputType();
	TypeInformation<Tuple3<K1, K2, T>> typeInfoWithKey = createTypeWithKey(key1, key2);
	TwoKeyExtractingMapper<T, K1, K2> extractor =
			new TwoKeyExtractingMapper<>(key1.getKeyExtractor(), key2.getKeyExtractor());

	MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>> mapper =
			new MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>>(
					extractor,
					new UnaryOperatorInformation<>(inputType, typeInfoWithKey),
					"Key Extractor"
			);

	mapper.setInput(input);
	mapper.setParallelism(input.getParallelism());

	return mapper;
}
Example 11
Source File: KeyFunctions.java    From flink with Apache License 2.0 5 votes vote down vote up 
@SuppressWarnings("unchecked")
public static <T, K> org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> appendKeyExtractor(
		org.apache.flink.api.common.operators.Operator<T> input,
		SelectorFunctionKeys<T, K> key) {

	if (input instanceof Union) {
		// if input is a union, we apply the key extractors recursively to all inputs
		org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
		org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();

		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> firstInputWithKey =
				appendKeyExtractor(firstInput, key);
		org.apache.flink.api.common.operators.Operator<Tuple2<K, T>> secondInputWithKey =
				appendKeyExtractor(secondInput, key);

		return new Union(firstInputWithKey, secondInputWithKey, input.getName());
	}

	TypeInformation<T> inputType = key.getInputType();
	TypeInformation<Tuple2<K, T>> typeInfoWithKey = createTypeWithKey(key);
	KeyExtractingMapper<T, K> extractor = new KeyExtractingMapper(key.getKeyExtractor());

	MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>> mapper =
			new MapOperatorBase<T, Tuple2<K, T>, MapFunction<T, Tuple2<K, T>>>(
					extractor,
					new UnaryOperatorInformation(inputType, typeInfoWithKey),
					"Key Extractor"
			);

	mapper.setInput(input);
	mapper.setParallelism(input.getParallelism());

	return mapper;
}
Example 12
Source File: KeyFunctions.java    From flink with Apache License 2.0 5 votes vote down vote up 
@SuppressWarnings("unchecked")
public static <T, K1, K2> org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> appendKeyExtractor(
		org.apache.flink.api.common.operators.Operator<T> input,
		SelectorFunctionKeys<T, K1> key1,
		SelectorFunctionKeys<T, K2> key2) {

	if (input instanceof Union) {
		// if input is a union, we apply the key extractors recursively to all inputs
		org.apache.flink.api.common.operators.Operator<T> firstInput = ((Union) input).getFirstInput();
		org.apache.flink.api.common.operators.Operator<T> secondInput = ((Union) input).getSecondInput();

		org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> firstInputWithKey =
				appendKeyExtractor(firstInput, key1, key2);
		org.apache.flink.api.common.operators.Operator<Tuple3<K1, K2, T>> secondInputWithKey =
				appendKeyExtractor(secondInput, key1, key2);

		return new Union(firstInputWithKey, secondInputWithKey, input.getName());
	}

	TypeInformation<T> inputType = key1.getInputType();
	TypeInformation<Tuple3<K1, K2, T>> typeInfoWithKey = createTypeWithKey(key1, key2);
	TwoKeyExtractingMapper<T, K1, K2> extractor =
			new TwoKeyExtractingMapper<>(key1.getKeyExtractor(), key2.getKeyExtractor());

	MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>> mapper =
			new MapOperatorBase<T, Tuple3<K1, K2, T>, MapFunction<T, Tuple3<K1, K2, T>>>(
					extractor,
					new UnaryOperatorInformation<>(inputType, typeInfoWithKey),
					"Key Extractor"
			);

	mapper.setInput(input);
	mapper.setParallelism(input.getParallelism());

	return mapper;
}