Java Code Examples for org.apache.flink.api.java.typeutils.TypeExtractor#getAggregateFunctionReturnType()

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Example 1
Source Project: Flink-CEPplus   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given aggregation function to each window. The aggregation function is called for
 * each element, aggregating values incrementally and keeping the state to one accumulator
 * per key and window.
 *
 * @param function The aggregation function.
 * @return The data stream that is the result of applying the fold function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            AggregateFunction's result type
 */
@PublicEvolving
public <ACC, R> SingleOutputStreamOperator<R> aggregate(AggregateFunction<T, ACC, R> function) {
	checkNotNull(function, "function");

	if (function instanceof RichFunction) {
		throw new UnsupportedOperationException("This aggregation function cannot be a RichFunction.");
	}

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			function, input.getType(), null, false);

	TypeInformation<R> resultType = TypeExtractor.getAggregateFunctionReturnType(
			function, input.getType(), null, false);

	return aggregate(function, accumulatorType, resultType);
}
 
Example 2
Source Project: Flink-CEPplus   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		WindowFunction<V, R, K, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, resultType);
}
 
Example 3
Source Project: Flink-CEPplus   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		ProcessWindowFunction<V, R, K, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getProcessWindowFunctionReturnType(windowFunction, aggResultType, null);

	return aggregate(aggFunction, windowFunction, accumulatorType, aggResultType, resultType);
}
 
Example 4
Source Project: Flink-CEPplus   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given {@code AggregateFunction} to each window. The AggregateFunction
 * aggregates all elements of a window into a single result element. The stream of these
 * result elements (one per window) is interpreted as a regular non-windowed stream.
 *
 * @param function The aggregation function.
 * @return The data stream that is the result of applying the fold function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            AggregateFunction's result type
 */
@PublicEvolving
public <ACC, R> SingleOutputStreamOperator<R> aggregate(AggregateFunction<T, ACC, R> function) {
	checkNotNull(function, "function");

	if (function instanceof RichFunction) {
		throw new UnsupportedOperationException("This aggregation function cannot be a RichFunction.");
	}

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			function, input.getType(), null, false);

	TypeInformation<R> resultType = TypeExtractor.getAggregateFunctionReturnType(
			function, input.getType(), null, false);

	return aggregate(function, accumulatorType, resultType);
}
 
Example 5
Source Project: Flink-CEPplus   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		AllWindowFunction<V, R, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getAllWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, resultType);
}
 
Example 6
Source Project: Flink-CEPplus   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The process window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		ProcessAllWindowFunction<V, R, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, aggResultType, resultType);
}
 
Example 7
Source Project: flink   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given aggregation function to each window. The aggregation function is called for
 * each element, aggregating values incrementally and keeping the state to one accumulator
 * per key and window.
 *
 * @param function The aggregation function.
 * @return The data stream that is the result of applying the fold function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            AggregateFunction's result type
 */
@PublicEvolving
public <ACC, R> SingleOutputStreamOperator<R> aggregate(AggregateFunction<T, ACC, R> function) {
	checkNotNull(function, "function");

	if (function instanceof RichFunction) {
		throw new UnsupportedOperationException("This aggregation function cannot be a RichFunction.");
	}

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			function, input.getType(), null, false);

	TypeInformation<R> resultType = TypeExtractor.getAggregateFunctionReturnType(
			function, input.getType(), null, false);

	return aggregate(function, accumulatorType, resultType);
}
 
Example 8
Source Project: flink   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		WindowFunction<V, R, K, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, resultType);
}
 
Example 9
Source Project: flink   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		ProcessWindowFunction<V, R, K, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getProcessWindowFunctionReturnType(windowFunction, aggResultType, null);

	return aggregate(aggFunction, windowFunction, accumulatorType, aggResultType, resultType);
}
 
Example 10
Source Project: flink   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given {@code AggregateFunction} to each window. The AggregateFunction
 * aggregates all elements of a window into a single result element. The stream of these
 * result elements (one per window) is interpreted as a regular non-windowed stream.
 *
 * @param function The aggregation function.
 * @return The data stream that is the result of applying the fold function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            AggregateFunction's result type
 */
@PublicEvolving
public <ACC, R> SingleOutputStreamOperator<R> aggregate(AggregateFunction<T, ACC, R> function) {
	checkNotNull(function, "function");

	if (function instanceof RichFunction) {
		throw new UnsupportedOperationException("This aggregation function cannot be a RichFunction.");
	}

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			function, input.getType(), null, false);

	TypeInformation<R> resultType = TypeExtractor.getAggregateFunctionReturnType(
			function, input.getType(), null, false);

	return aggregate(function, accumulatorType, resultType);
}
 
Example 11
Source Project: flink   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		AllWindowFunction<V, R, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getAllWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, resultType);
}
 
Example 12
Source Project: flink   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The process window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		ProcessAllWindowFunction<V, R, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, aggResultType, resultType);
}
 
Example 13
Source Project: flink   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given aggregation function to each window. The aggregation function is called for
 * each element, aggregating values incrementally and keeping the state to one accumulator
 * per key and window.
 *
 * @param function The aggregation function.
 * @return The data stream that is the result of applying the fold function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            AggregateFunction's result type
 */
@PublicEvolving
public <ACC, R> SingleOutputStreamOperator<R> aggregate(AggregateFunction<T, ACC, R> function) {
	checkNotNull(function, "function");

	if (function instanceof RichFunction) {
		throw new UnsupportedOperationException("This aggregation function cannot be a RichFunction.");
	}

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			function, input.getType(), null, false);

	TypeInformation<R> resultType = TypeExtractor.getAggregateFunctionReturnType(
			function, input.getType(), null, false);

	return aggregate(function, accumulatorType, resultType);
}
 
Example 14
Source Project: flink   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		WindowFunction<V, R, K, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, resultType);
}
 
Example 15
Source Project: flink   File: WindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		ProcessWindowFunction<V, R, K, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getProcessWindowFunctionReturnType(windowFunction, aggResultType, null);

	return aggregate(aggFunction, windowFunction, accumulatorType, aggResultType, resultType);
}
 
Example 16
Source Project: flink   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given {@code AggregateFunction} to each window. The AggregateFunction
 * aggregates all elements of a window into a single result element. The stream of these
 * result elements (one per window) is interpreted as a regular non-windowed stream.
 *
 * @param function The aggregation function.
 * @return The data stream that is the result of applying the fold function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            AggregateFunction's result type
 */
@PublicEvolving
public <ACC, R> SingleOutputStreamOperator<R> aggregate(AggregateFunction<T, ACC, R> function) {
	checkNotNull(function, "function");

	if (function instanceof RichFunction) {
		throw new UnsupportedOperationException("This aggregation function cannot be a RichFunction.");
	}

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			function, input.getType(), null, false);

	TypeInformation<R> resultType = TypeExtractor.getAggregateFunctionReturnType(
			function, input.getType(), null, false);

	return aggregate(function, accumulatorType, resultType);
}
 
Example 17
Source Project: flink   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		AllWindowFunction<V, R, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getAllWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, resultType);
}
 
Example 18
Source Project: flink   File: AllWindowedStream.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Applies the given window function to each window. The window function is called for each
 * evaluation of the window for each key individually. The output of the window function is
 * interpreted as a regular non-windowed stream.
 *
 * <p>Arriving data is incrementally aggregated using the given aggregate function. This means
 * that the window function typically has only a single value to process when called.
 *
 * @param aggFunction The aggregate function that is used for incremental aggregation.
 * @param windowFunction The process window function.
 *
 * @return The data stream that is the result of applying the window function to the window.
 *
 * @param <ACC> The type of the AggregateFunction's accumulator
 * @param <V> The type of AggregateFunction's result, and the WindowFunction's input
 * @param <R> The type of the elements in the resulting stream, equal to the
 *            WindowFunction's result type
 */
@PublicEvolving
public <ACC, V, R> SingleOutputStreamOperator<R> aggregate(
		AggregateFunction<T, ACC, V> aggFunction,
		ProcessAllWindowFunction<V, R, W> windowFunction) {

	checkNotNull(aggFunction, "aggFunction");
	checkNotNull(windowFunction, "windowFunction");

	TypeInformation<ACC> accumulatorType = TypeExtractor.getAggregateFunctionAccumulatorType(
			aggFunction, input.getType(), null, false);

	TypeInformation<V> aggResultType = TypeExtractor.getAggregateFunctionReturnType(
			aggFunction, input.getType(), null, false);

	TypeInformation<R> resultType = getProcessAllWindowFunctionReturnType(windowFunction, aggResultType);

	return aggregate(aggFunction, windowFunction, accumulatorType, aggResultType, resultType);
}