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 Overview

Window Transformation Overview

Use the Window transformation when you want to accumulate streamed data into data groups and then process the data sets. The Window transformation is a passive transformation.
When you read from unbounded sources, you might want to accumulate the data into bounded data groups for further processing. To introduce bounded intervals to unbounded data, use a Window transformation.
When you configure a Window transformation, define the type of window and the data boundaries by time. To specify data boundaries, configure the window size and window slide interval. The window size defines the time interval for which data is accumulated as a data group. The slide interval defines the time interval after which the accumulated data group is processed further. The watermark delay defines the threshold time for a delayed event to be accumulated into a data group.


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