org.apache.flink.state.api

Class WindowedStateTransformation<T,K,W extends Window>

java.lang.Object

org.apache.flink.state.api.WindowedStateTransformation<T,K,W>

Type Parameters:

K - The type of the key in the window.

T - The type of the elements in the window.

W - The type of the window.

@PublicEvolving
public class WindowedStateTransformation<T,K,W extends Window>
extends Object

A WindowedStateTransformation represents a OneInputStateTransformation for bootstrapping window state.

Method Summary

Modifier and Type	Method and Description
<ACC,R> StateBootstrapTransformation<T>	aggregate(AggregateFunction<T,ACC,R> function) Applies the given aggregation function to each window.
<ACC,R> StateBootstrapTransformation<T>	aggregate(AggregateFunction<T,ACC,R> function, TypeInformation<ACC> accumulatorType) Applies the given aggregation function to each window.
<ACC,V,R> StateBootstrapTransformation<T>	aggregate(AggregateFunction<T,ACC,V> aggFunction, ProcessWindowFunction<V,R,K,W> windowFunction) Applies the given window function to each window.
<ACC,V,R> StateBootstrapTransformation<T>	aggregate(AggregateFunction<T,ACC,V> aggregateFunction, ProcessWindowFunction<V,R,K,W> windowFunction, TypeInformation<ACC> accumulatorType) Applies the given window function to each window.
<ACC,V,R> StateBootstrapTransformation<T>	aggregate(AggregateFunction<T,ACC,V> aggFunction, WindowFunction<V,R,K,W> windowFunction) Applies the given window function to each window.
<ACC,V,R> StateBootstrapTransformation<T>	aggregate(AggregateFunction<T,ACC,V> aggregateFunction, WindowFunction<V,R,K,W> windowFunction, TypeInformation<ACC> accumulatorType) Applies the given window function to each window.
<R> StateBootstrapTransformation<T>	apply(WindowFunction<T,R,K,W> function) Applies the given window function to each window.
<R> StateBootstrapTransformation<T>	apply(WindowFunction<T,R,K,W> function, TypeInformation<R> resultType) Applies the given window function to each window.
WindowedStateTransformation<T,K,W>	evictor(Evictor<? super T,? super W> evictor) Sets the Evictor that should be used to evict elements from a window before emission.
<R> StateBootstrapTransformation<T>	process(ProcessWindowFunction<T,R,K,W> function) Applies the given window function to each window.
StateBootstrapTransformation<T>	reduce(ReduceFunction<T> function) Applies a reduce function to the window.
<R> StateBootstrapTransformation<T>	reduce(ReduceFunction<T> reduceFunction, ProcessWindowFunction<T,R,K,W> function) Applies the given window function to each window.
<R> StateBootstrapTransformation<T>	reduce(ReduceFunction<T> reduceFunction, WindowFunction<T,R,K,W> function) Applies the given window function to each window.
WindowedStateTransformation<T,K,W>	trigger(Trigger<? super T,? super W> trigger) Sets the Trigger that should be used to trigger window emission.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

trigger

@PublicEvolving
public WindowedStateTransformation<T,K,W> trigger(Trigger<? super T,? super W> trigger)

Sets the Trigger that should be used to trigger window emission.

evictor

@PublicEvolving
public WindowedStateTransformation<T,K,W> evictor(Evictor<? super T,? super W> evictor)

Sets the Evictor that should be used to evict elements from a window before emission.

Note: When using an evictor window performance will degrade significantly, since incremental aggregation of window results cannot be used.

reduce

public StateBootstrapTransformation<T> reduce(ReduceFunction<T> function)

Applies a reduce function to the window. The window function is called for each evaluation of the window for each key individually. The output of the reduce function is interpreted as a regular non-windowed stream.

This window will try and incrementally aggregate data as much as the window policies permit. For example, tumbling time windows can aggregate the data, meaning that only one element per key is stored. Sliding time windows will aggregate on the granularity of the slide interval, so a few elements are stored per key (one per slide interval). Custom windows may not be able to incrementally aggregate, or may need to store extra values in an aggregation tree.

Parameters:

function - The reduce function.

Returns:

The data stream that is the result of applying the reduce function to the window.

reduce

public <R> StateBootstrapTransformation<T> reduce(ReduceFunction<T> reduceFunction,
                                                  WindowFunction<T,R,K,W> function)

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.

Arriving data is incrementally aggregated using the given reducer.

Parameters:

reduceFunction - The reduce function that is used for incremental aggregation.

function - The window function.

Returns:

The data stream that is the result of applying the window function to the window.

reduce

@Internal
public <R> StateBootstrapTransformation<T> reduce(ReduceFunction<T> reduceFunction,
                                                            ProcessWindowFunction<T,R,K,W> function)

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.

Arriving data is incrementally aggregated using the given reducer.

Parameters:

reduceFunction - The reduce function that is used for incremental aggregation.

function - The window function.

Returns:

The data stream that is the result of applying the window function to the window.

aggregate

@PublicEvolving
public <ACC,R> StateBootstrapTransformation<T> aggregate(AggregateFunction<T,ACC,R> function)

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.

Type Parameters:

ACC - The type of the AggregateFunction's accumulator

R - The type of the elements in the resulting stream, equal to the AggregateFunction's result type

Parameters:

function - The aggregation function.

Returns:

The data stream that is the result of applying the fold function to the window.

aggregate

@PublicEvolving
public <ACC,R> StateBootstrapTransformation<T> aggregate(AggregateFunction<T,ACC,R> function,
                                                                         TypeInformation<ACC> accumulatorType)

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.

Type Parameters:

ACC - The type of the AggregateFunction's accumulator

R - The type of the elements in the resulting stream, equal to the AggregateFunction's result type

Parameters:

function - The aggregation function.

Returns:

The data stream that is the result of applying the aggregation function to the window.

aggregate

@PublicEvolving
public <ACC,V,R> StateBootstrapTransformation<T> aggregate(AggregateFunction<T,ACC,V> aggFunction,
                                                                           WindowFunction<V,R,K,W> windowFunction)

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.

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.

Type Parameters:

ACC - The type of the AggregateFunction's accumulator

V - The type of AggregateFunction's result, and the WindowFunction's input

R - The type of the elements in the resulting stream, equal to the WindowFunction's result type

Parameters:

aggFunction - The aggregate function that is used for incremental aggregation.

windowFunction - The window function.

Returns:

The data stream that is the result of applying the window function to the window.

aggregate

@PublicEvolving
public <ACC,V,R> StateBootstrapTransformation<T> aggregate(AggregateFunction<T,ACC,V> aggregateFunction,
                                                                           WindowFunction<V,R,K,W> windowFunction,
                                                                           TypeInformation<ACC> accumulatorType)

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.

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.

Type Parameters:

ACC - The type of the AggregateFunction's accumulator

V - The type of AggregateFunction's result, and the WindowFunction's input

R - The type of the elements in the resulting stream, equal to the WindowFunction's result type

Parameters:

aggregateFunction - The aggregation function that is used for incremental aggregation.

windowFunction - The window function.

accumulatorType - Type information for the internal accumulator type of the aggregation function

Returns:

The data stream that is the result of applying the window function to the window.

aggregate

@PublicEvolving
public <ACC,V,R> StateBootstrapTransformation<T> aggregate(AggregateFunction<T,ACC,V> aggFunction,
                                                                           ProcessWindowFunction<V,R,K,W> windowFunction)

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.

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.

Type Parameters:

ACC - The type of the AggregateFunction's accumulator

V - The type of AggregateFunction's result, and the WindowFunction's input

R - The type of the elements in the resulting stream, equal to the WindowFunction's result type

Parameters:

aggFunction - The aggregate function that is used for incremental aggregation.

windowFunction - The window function.

Returns:

The data stream that is the result of applying the window function to the window.

aggregate

@PublicEvolving
public <ACC,V,R> StateBootstrapTransformation<T> aggregate(AggregateFunction<T,ACC,V> aggregateFunction,
                                                                           ProcessWindowFunction<V,R,K,W> windowFunction,
                                                                           TypeInformation<ACC> accumulatorType)

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.

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.

Type Parameters:

ACC - The type of the AggregateFunction's accumulator

V - The type of AggregateFunction's result, and the WindowFunction's input

R - The type of the elements in the resulting stream, equal to the WindowFunction's result type

Parameters:

aggregateFunction - The aggregation function that is used for incremental aggregation.

windowFunction - The window function.

accumulatorType - Type information for the internal accumulator type of the aggregation function

Returns:

The data stream that is the result of applying the window function to the window.

apply

public <R> StateBootstrapTransformation<T> apply(WindowFunction<T,R,K,W> function)

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.

Note that this function requires that all data in the windows is buffered until the window is evaluated, as the function provides no means of incremental aggregation.

Parameters:

function - The window function.

Returns:

The data stream that is the result of applying the window function to the window.

apply

public <R> StateBootstrapTransformation<T> apply(WindowFunction<T,R,K,W> function,
                                                 TypeInformation<R> resultType)

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.

Note that this function requires that all data in the windows is buffered until the window is evaluated, as the function provides no means of incremental aggregation.

Parameters:

function - The window function.

resultType - Type information for the result type of the window function

Returns:

The data stream that is the result of applying the window function to the window.

process

@PublicEvolving
public <R> StateBootstrapTransformation<T> process(ProcessWindowFunction<T,R,K,W> function)

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.

Note that this function requires that all data in the windows is buffered until the window is evaluated, as the function provides no means of incremental aggregation.

Parameters:

function - The window function.

Returns:

The data stream that is the result of applying the window function to the window.