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.
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
This pipeline will calculate percentiles over a set of sibling buckets. This is an exact
implementation, meaning it needs to cache a copy of the series in memory and sort it to determine
the percentiles.
This comes with a few limitations: to prevent serializing data around, only the requested percentiles
are calculated (unlike the TDigest version, which allows the java API to ask for any percentile).
It also needs to store the data in-memory, resulting in some overhead if the requested series is
very large.
James Rodewig
Zachary Tong
João Barbosa
Clinton Gormley
Alexander Kazakov
Suhas Karanth
Zachary Tong
Adrien Grand
Nik Everett
Deb Adair
Zachary Tong