Table of Contents


  1. Preface
  2. Introduction to Big Data Streaming
  3. Big Data Streaming Administration
  4. Sources in a Streaming Mapping
  5. Targets in a Streaming Mapping
  6. Streaming Mappings
  7. Window Transformation
  8. Connections
  9. Sample Files

Window Transformation Window Properties

Window Transformation Window Properties

A Window transformation has different window types that allow you to accumulate data groups at different time intervals.
Configure the following window properties for a Window transformation:
Window Type
The type of window transformation you want to create. You can choose tumbling or sliding.
Window Size
The window size defines the time interval for which data is accumulated as a data group. The window size should be a multiple of the batch interval. Specify the window size as a value in units of time or as a parameter of type TimeDuration.
Sliding Interval
The slide interval defines the time interval after which the accumulated data group is processed. Specify the slide interval as a value in units of time or as a parameter of type TimeDuration. Specify the sliding interval if you create a sliding window. By default, the window size and sliding interval are same for tumbling windows.
Watermark Delay
The watermark delay defines threshold time for a delayed event to be accumulated into a data group. Watermark delay is a threshold where you can specify the duration at which late arriving data can be grouped and processed.
If an event data arrives within the threshold time, the data is processed, and the data is accumulated into the corresponding data group. You can specify the watermark delay as a value in units of time or as a parameter of type TimeDuration in the window properties.
The following image shows sample window transformation properties:


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