Introduce shift field to MovingFunction aggregation.
By default, shift = 0. Behavior, in this case, is the same as before.
Increasing shift by 1 moves starting window position by 1 to the right.
To simply include current bucket to the window, use shift = 1
For center alignment (n/2 values before and after the current bucket), use shift = window / 2
For right alignment (n values after the current bucket), use shift = window.
Introduce shift field to MovingFunction aggregation.
By default, shift = 0. Behavior, in this case, is the same as before.
Increasing shift by 1 moves starting window position by 1 to the right.
To simply include current bucket to the window, use shift = 1
For center alignment (n/2 values before and after the current bucket), use shift = window / 2
For right alignment (n values after the current bucket), use shift = window.
The date_histogram accepts an interval which can be either a calendar
interval (DST-aware, leap seconds, arbitrary length of months, etc) or
fixed interval (strict multiples of SI units). Unfortunately this is inferred
by first trying to parse as a calendar interval, then falling back to fixed
if that fails.
This leads to confusing arrangement where `1d` == calendar, but
`2d` == fixed. And if you want a day of fixed time, you have to
specify `24h` (e.g. the next smallest unit). This arrangement is very
error-prone for users.
This PR adds `calendar_interval` and `fixed_interval` parameters to any
code that uses intervals (date_histogram, rollup, composite, datafeed, etc).
Calendar only accepts calendar intervals, fixed accepts any combination of
units (meaning `1d` can be used to specify `24h` in fixed time), and both
are mutually exclusive.
The old interval behavior is deprecated and will throw a deprecation warning.
It is also mutually exclusive with the two new parameters. In the future the
old dual-purpose interval will be removed.
The change applies to both REST and java clients.
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.