This pipeline aggregation gives the user the ability to script functions that "move" across a window
of data, instead of single data points. It is the scripted version of MovingAvg pipeline agg.
Through custom script contexts, we expose a number of convenience methods:
- MovingFunctions.max()
- MovingFunctions.min()
- MovingFunctions.sum()
- MovingFunctions.unweightedAvg()
- MovingFunctions.linearWeightedAvg()
- MovingFunctions.ewma()
- MovingFunctions.holt()
- MovingFunctions.holtWinters()
- MovingFunctions.stdDev()
The user can also define any arbitrary logic via their own scripting, or combine with the above methods.
Most of the examples in the pipeline aggregation docs use a small
"sales" test data set and I converted all of the examples that use
it to `// CONSOLE`. There are still a bunch of snippets in the pipeline
aggregation docs that aren't `// CONSOLE` so they aren't tested. Most
of them are "this is the most basic form of this aggregation" so they
are more immune to errors and bit rot then the examples that I converted.
I'd like to do something with them as well but I'm not sure what.
Also, the moving average docs and serial diff docs didn't get a lot of
love from this pass because they don't use the test data set or follow
the same general layout.
Relates to #18160
Zachary Tong
Clinton Gormley
msancho
Nik Everett
evanfreed
KangYongKyun
Zachary Tong
Colin Goodheart-Smithe