Window analytics

Standard window functions are provided to perform event based analytics

Objective

Joule provides the ability to perform time or number of events window based analytics. A suite of standard window functions are provided out-of-the-box.

Developers can create custom analytic functions which are deployable as discrete components on the classpath.

Joule provides tumbling and sliding window analytics.

Tumbling

Tumbling windows are a non-overlapping events arrays ordered by time. In a tumbling window, events are grouped in to a single window based on time or count.

An event belongs to only one window. Events within a window are only processed once when a new window is presented for processing.

Tumbling windows

Sliding

Sliding windows, unlike tumbling windows, output events only for points in time when the content of the window actually changes.

In other words, when an event enters or exits the window. Every window has at least one event. Events can belong to more than one sliding window.

Sliding windows

Example

processing unit:
  pipeline:
    - time window:
        emitting type: tumblingQuoteAnalytics
        aggregate functions:
          FIRST: [ask]
          LAST: [ ask ]
          MIN: [ ask ]
          MAX: [ bid ]
          SUM: [ volume ]
          MEAN: [ volatility ]
          VARIANCE: [ volatility ]
          STDEV: [ volatility ]
        policy:
          type: tumblingTime
          window size: 5000

Attribute schema

Attribute	Description	Data Type	Required
emitting type	name of the event	String
preprocessor	Window preprocessor
window listeners	Custom window listeners which are executed on window generation. See window listener documentation below	See documentation below.
aggregate functions	Standard set of aggragation functions based over a window using group by semantics	See documentation below.
policy	Type of window processing. Supported types: Tumbling tumblingTime tumblingCount Sliding slidingTime slidingCount	String e.g. slidingCount

Available options

In the following pages you can read further how to apply the window functionalities and a list of all the aggregate functions.

Tumbling window

Sliding window

Aggregate functions