OnWindowedStream

class OnWindowedStream[T, K, W <: Window](stream: WindowedStream[T, K, W])

Wraps a joined data stream, allowing to use anonymous partial functions to perform extraction of items in a tuple, case class instance or collection

Type parameters:
K

The type of key

T

The type of the data stream items from the right input of the join

W

The type of the window

Value parameters:
stream

The wrapped data stream

class Object
trait Matchable
class Any

Value members

Concrete methods

@PublicEvolving
def reduceWith(function: (T, T) => T): DataStream[T]

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.

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 pre-aggregate data as much as the window policies permit. For example,tumbling time windows can perfectly pre-aggregate the data, meaning that only one element per key is stored. Sliding time windows will pre-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 pre-aggregate, or may need to store extra values in an aggregation tree.

Value parameters:
function

The reduce function.

Returns:

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