T
 The type of elements in the stream.K
 The type of the key by which elements are grouped.W
 The type of Window
that the WindowAssigner
assigns the elements to.@Public public class WindowedStream<T,K,W extends Window> extends Object
WindowedStream
represents a data stream where elements are grouped by
key, and for each key, the stream of elements is split into windows based on a
WindowAssigner
. Window emission
is triggered based on a Trigger
.
The windows are conceptually evaluated for each key individually, meaning windows can trigger at different points for each key.
If an Evictor
is specified it will be used to evict elements from the window after
evaluation was triggered by the Trigger
but before the actual evaluation of the window.
When using an evictor window performance will degrade significantly, since
incremental aggregation of window results cannot be used.
Note that the WindowedStream
is purely and API construct, during runtime
the WindowedStream
will be collapsed together with the
KeyedStream
and the operation over the window into one single operation.
Constructor and Description 

WindowedStream(KeyedStream<T,K> input,
WindowAssigner<? super T,W> windowAssigner) 
Modifier and Type  Method and Description 

<R> SingleOutputStreamOperator<R> 
apply(ReduceFunction<T> reduceFunction,
WindowFunction<T,R,K,W> function)
Applies the given window function to each window.

<R> SingleOutputStreamOperator<R> 
apply(ReduceFunction<T> reduceFunction,
WindowFunction<T,R,K,W> function,
TypeInformation<R> resultType)
Applies the given window function to each window.

<R> SingleOutputStreamOperator<R> 
apply(R initialValue,
FoldFunction<T,R> foldFunction,
WindowFunction<R,R,K,W> function)
Applies the given window function to each window.

<R> SingleOutputStreamOperator<R> 
apply(R initialValue,
FoldFunction<T,R> foldFunction,
WindowFunction<R,R,K,W> function,
TypeInformation<R> resultType)
Applies the given window function to each window.

<R> SingleOutputStreamOperator<R> 
apply(WindowFunction<T,R,K,W> function)
Applies the given window function to each window.

<R> SingleOutputStreamOperator<R> 
apply(WindowFunction<T,R,K,W> function,
TypeInformation<R> resultType)
Applies the given window function to each window.

WindowedStream<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> SingleOutputStreamOperator<R> 
fold(R initialValue,
FoldFunction<T,R> function)
Applies the given fold function to each window.

<R> SingleOutputStreamOperator<R> 
fold(R initialValue,
FoldFunction<T,R> function,
TypeInformation<R> resultType)
Applies the given fold function to each window.

StreamExecutionEnvironment 
getExecutionEnvironment() 
TypeInformation<T> 
getInputType() 
SingleOutputStreamOperator<T> 
max(int positionToMax)
Applies an aggregation that gives the maximum value of every window of
the data stream at the given position.

SingleOutputStreamOperator<T> 
max(String field)
Applies an aggregation that that gives the maximum value of the pojo data
stream at the given field expression for every window.

SingleOutputStreamOperator<T> 
maxBy(int positionToMaxBy)
Applies an aggregation that gives the maximum element of every window of
the data stream by the given position.

SingleOutputStreamOperator<T> 
maxBy(int positionToMaxBy,
boolean first)
Applies an aggregation that gives the maximum element of every window of
the data stream by the given position.

SingleOutputStreamOperator<T> 
maxBy(String positionToMaxBy)
Applies an aggregation that gives the maximum element of every window of
the data stream by the given position.

SingleOutputStreamOperator<T> 
maxBy(String field,
boolean first)
Applies an aggregation that that gives the maximum element of the pojo
data stream by the given field expression for every window.

SingleOutputStreamOperator<T> 
min(int positionToMin)
Applies an aggregation that that gives the minimum value of every window
of the data stream at the given position.

SingleOutputStreamOperator<T> 
min(String field)
Applies an aggregation that that gives the minimum value of the pojo data
stream at the given field expression for every window.

SingleOutputStreamOperator<T> 
minBy(int positionToMinBy)
Applies an aggregation that gives the minimum element of every window of
the data stream by the given position.

SingleOutputStreamOperator<T> 
minBy(int positionToMinBy,
boolean first)
Applies an aggregation that gives the minimum element of every window of
the data stream by the given position.

SingleOutputStreamOperator<T> 
minBy(String positionToMinBy)
Applies an aggregation that gives the minimum element of every window of
the data stream by the given position.

SingleOutputStreamOperator<T> 
minBy(String field,
boolean first)
Applies an aggregation that that gives the minimum element of the pojo
data stream by the given field expression for every window.

SingleOutputStreamOperator<T> 
reduce(ReduceFunction<T> function)
Applies a reduce function to the window.

SingleOutputStreamOperator<T> 
sum(int positionToSum)
Applies an aggregation that sums every window of the data stream at the
given position.

SingleOutputStreamOperator<T> 
sum(String field)
Applies an aggregation that sums every window of the pojo data stream at
the given field for every window.

WindowedStream<T,K,W> 
trigger(Trigger<? super T,? super W> trigger)
Sets the
Trigger that should be used to trigger window emission. 
@PublicEvolving public WindowedStream(KeyedStream<T,K> input, WindowAssigner<? super T,W> windowAssigner)
@PublicEvolving public WindowedStream<T,K,W> trigger(Trigger<? super T,? super W> trigger)
Trigger
that should be used to trigger window emission.@PublicEvolving public WindowedStream<T,K,W> evictor(Evictor<? super T,? super W> evictor)
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.
public SingleOutputStreamOperator<T> reduce(ReduceFunction<T> function)
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.
function
 The reduce function.public <R> SingleOutputStreamOperator<R> fold(R initialValue, FoldFunction<T,R> function)
function
 The fold function.public <R> SingleOutputStreamOperator<R> fold(R initialValue, FoldFunction<T,R> function, TypeInformation<R> resultType)
function
 The fold function.public <R> SingleOutputStreamOperator<R> apply(WindowFunction<T,R,K,W> function)
Not 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.
function
 The window function.public <R> SingleOutputStreamOperator<R> apply(WindowFunction<T,R,K,W> function, TypeInformation<R> resultType)
Not 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.
function
 The window function.resultType
 Type information for the result type of the window functionpublic <R> SingleOutputStreamOperator<R> apply(ReduceFunction<T> reduceFunction, WindowFunction<T,R,K,W> function)
Arriving data is incrementally aggregated using the given reducer.
reduceFunction
 The reduce function that is used for incremental aggregation.function
 The window function.public <R> SingleOutputStreamOperator<R> apply(ReduceFunction<T> reduceFunction, WindowFunction<T,R,K,W> function, TypeInformation<R> resultType)
Arriving data is incrementally aggregated using the given reducer.
reduceFunction
 The reduce function that is used for incremental aggregation.function
 The window function.resultType
 Type information for the result type of the window functionpublic <R> SingleOutputStreamOperator<R> apply(R initialValue, FoldFunction<T,R> foldFunction, WindowFunction<R,R,K,W> function)
Arriving data is incrementally aggregated using the given fold function.
initialValue
 The initial value of the fold.foldFunction
 The fold function that is used for incremental aggregation.function
 The window function.public <R> SingleOutputStreamOperator<R> apply(R initialValue, FoldFunction<T,R> foldFunction, WindowFunction<R,R,K,W> function, TypeInformation<R> resultType)
Arriving data is incrementally aggregated using the given fold function.
initialValue
 The initial value of the fold.foldFunction
 The fold function that is used for incremental aggregation.function
 The window function.resultType
 Type information for the result type of the window functionpublic SingleOutputStreamOperator<T> sum(int positionToSum)
positionToSum
 The position in the tuple/array to sumpublic SingleOutputStreamOperator<T> sum(String field)
A field expression is either
the name of a public field or a getter method with parentheses of the
stream's underlying type. A dot can be used to drill down into objects,
as in "field1.getInnerField2()"
.
field
 The field to sumpublic SingleOutputStreamOperator<T> min(int positionToMin)
positionToMin
 The position to minimizepublic SingleOutputStreamOperator<T> min(String field)
A field
expression is either the name of a public field or a getter method with
parentheses of the DataStream
S underlying type. A dot can be used
to drill down into objects, as in "field1.getInnerField2()"
.
field
 The field expression based on which the aggregation will be applied.public SingleOutputStreamOperator<T> minBy(int positionToMinBy)
positionToMinBy
 The position to minimize bypublic SingleOutputStreamOperator<T> minBy(String positionToMinBy)
positionToMinBy
 The position to minimize bypublic SingleOutputStreamOperator<T> minBy(int positionToMinBy, boolean first)
positionToMinBy
 The position to minimizefirst
 If true, then the operator return the first element with the minimum value, otherwise returns the lastpublic SingleOutputStreamOperator<T> minBy(String field, boolean first)
DataStreams
underlying type. A dot can be used
to drill down into objects, as in "field1.getInnerField2()"
.field
 The field expression based on which the aggregation will be applied.first
 If True then in case of field equality the first object will be returnedpublic SingleOutputStreamOperator<T> max(int positionToMax)
positionToMax
 The position to maximizepublic SingleOutputStreamOperator<T> max(String field)
DataStreams
underlying type. A dot can be used to drill
down into objects, as in "field1.getInnerField2()"
.field
 The field expression based on which the aggregation will be applied.public SingleOutputStreamOperator<T> maxBy(int positionToMaxBy)
positionToMaxBy
 The position to maximize bypublic SingleOutputStreamOperator<T> maxBy(String positionToMaxBy)
positionToMaxBy
 The position to maximize bypublic SingleOutputStreamOperator<T> maxBy(int positionToMaxBy, boolean first)
positionToMaxBy
 The position to maximize byfirst
 If true, then the operator return the first element with the maximum value, otherwise returns the lastpublic SingleOutputStreamOperator<T> maxBy(String field, boolean first)
DataStream
S underlying type. A dot can be used
to drill down into objects, as in "field1.getInnerField2()"
.field
 The field expression based on which the aggregation will be applied.first
 If True then in case of field equality the first object will be returnedpublic StreamExecutionEnvironment getExecutionEnvironment()
public TypeInformation<T> getInputType()
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