Rounding dates on a shard that contains a daylight savings time transition
is currently something like 1400% slower than when a shard contains dates
only on one side of the DST transition. And it makes a ton of short lived
garbage. This replaces that implementation with one that benchmarks to
having around 30% overhead instead of the 1400%. And it doesn't generate
any garbage per search hit.
Some background:
There are two ways to round in ES:
* Round to the nearest time unit (Day/Hour/Week/Month/etc)
* Round to the nearest time *interval* (3 days/2 weeks/etc)
I'm only optimizing the first one in this change and plan to do the second
in a follow up. It turns out that rounding to the nearest unit really *is*
two problems: when the unit rounds to midnight (day/week/month/year) and
when it doesn't (hour/minute/second). Rounding to midnight is consistently
about 25% faster and rounding to individual hour or minutes.
This optimization relies on being able to *usually* figure out what the
minimum and maximum dates are on the shard. This is similar to an existing
optimization where we rewrite time zones that aren't fixed
(think America/New_York and its daylight savings time transitions) into
fixed time zones so long as there isn't a daylight savings time transition
on the shard (UTC-5 or UTC-4 for America/New_York). Once I implement
time interval rounding the time zone rewriting optimization *should* no
longer be needed.
This optimization doesn't come into play for `composite` or
`auto_date_histogram` aggs because neither have been migrated to the new
`DATE` `ValuesSourceType` which is where that range lookup happens. When
they are they will be able to pick up the optimization without much work.
I expect this to be substantial for `auto_date_histogram` but less so for
`composite` because it deals with fewer values.
Note: My 30% overhead figure comes from small numbers of daylight savings
time transitions. That overhead gets higher when there are more
transitions in logarithmic fashion. When there are two thousand years
worth of transitions my algorithm ends up being 250% slower than rounding
without a time zone, but java time is 47000% slower at that point,
allocating memory as fast as it possibly can.
While we use `== false` as a more visible form of boolean negation
(instead of `!`), the true case is implied and the true value does not
need to explicitly checked. This commit converts cases that have slipped
into the code checking for `== true`.
We added a new rounding in #50609 that handles offsets to the start and
end of the rounding so that we could support `offset` in the `composite`
aggregation. This starts moving `date_histogram` to that new offset.
This is a redo of #50873 with more integration tests.
This reverts commit d114c9db3e1d1a766f9f48f846eed0466125ce83.
We added a new rounding in #50609 that handles offsets to the start and
end of the rounding so that we could support `offset` in the `composite`
aggregation. This starts moving `date_histogram` to that new offset.
When deserializing time zones in the Rounding classes we used to include a tiny
normalization step via `DateUtils.of(in.readString())` that was lost in #50609.
Its at least necessary for some tests, e.g. the cause of #50827 is that when
sending the default time zone ZoneOffset.UTC on a stream pre 7.0 we convert it
to a "UTC" string id via `DateUtils.zoneIdToDateTimeZone`. This gets then read
back as a UTC ZoneRegion, which should behave the same but fails the equality
tests in our serialization tests. Reverting to the previous behaviour with an
additional normalization step on 7.x.
Co-authored-by: Nik Everett <nik9000@gmail.com>
Closes#50827
Adds support for the `offset` parameter to the `date_histogram` source
of composite aggs. The `offset` parameter is supported by the normal
`date_histogram` aggregation and is useful for folks that need to
measure things from, say, 6am one day to 6am the next day.
This is implemented by creating a new `Rounding` that knows how to
handle offsets and delegates to other rounding implementations. That
implementation doesn't fully implement the `Rounding` contract, namely
`nextRoundingValue`. That method isn't used by composite aggs so I can't
be sure that any implementation that I add will be correct. I propose to
leave it throwing `UnsupportedOperationException` until I need it.
Closes#48757
The benchmarks showed a sharp decrease in aggregation performance for
the UTC case.
This commit uses the same calculation as joda time, which requires no
conversion into any java time object, also, the check for an fixedoffset
has been put into the ctor to reduce the need for runtime calculations.
The same goes for the amount of the used unit in milliseconds.
Closes#37826
This reduces objects creations in the rounding class (used by aggs) by properly
creating the objects only once. Furthermore a few unneeded ZonedDateTime objects
were created in order to create other objects out of them. This was
changed as well.
Running the benchmarks shows a much faster performance for all of the
java time based Rounding classes.
This commit moves the aggregation and mapping code from joda time to
java time. This includes field mappers, root object mappers, aggregations with date
histograms, query builders and a lot of changes within tests.
The cut-over to java time is a requirement so that we can support nanoseconds
properly in a future field mapper.
Relates #27330
This commit adds a java time version of the existing rounding classes, which features the same test suite and a small test class to check if serialization works as expected.
