This commit refactors the following:
* GeoPointFieldMapper and PointFieldMapper to
AbstractPointGeometryFieldMapper derived from AbstractGeometryFieldMapper.
* .setupFieldType moved up to AbstractGeometryFieldMapper
* lucene indexing moved up to AbstractGeometryFieldMapper.parse
* new addStoredFields, addDocValuesFields abstract methods for implementing
stored field and doc values field indexing in the concrete field mappers
This refactor is the next phase for setting up a framework for extending
spatial field mapper functionality in x-pack.
Right now all implementations of the `terms` agg allocate a new
`Aggregator` per bucket. This uses a bunch of memory. Exactly how much
isn't clear but each `Aggregator` ends up making its own objects to read
doc values which have non-trivial buffers. And it forces all of it
sub-aggregations to do the same. We allocate a new `Aggregator` per
bucket for two reasons:
1. We didn't have an appropriate data structure to track the
sub-ordinals of each parent bucket.
2. You can only make a single call to `runDeferredCollections(long...)`
per `Aggregator` which was the only way to delay collection of
sub-aggregations.
This change switches the method that builds aggregation results from
building them one at a time to building all of the results for the
entire aggregator at the same time.
It also adds a fairly simplistic data structure to track the sub-ordinals
for `long`-keyed buckets.
It uses both of those to power numeric `terms` aggregations and removes
the per-bucket allocation of their `Aggregator`. This fairly
substantially reduces memory consumption of numeric `terms` aggregations
that are not the "top level", especially when those aggregations contain
many sub-aggregations. It also is a pretty big speed up, especially when
the aggregation is under a non-selective aggregation like
the `date_histogram`.
I picked numeric `terms` aggregations because those have the simplest
implementation. At least, I could kind of fit it in my head. And I
haven't fully understood the "bytes"-based terms aggregations, but I
imagine I'll be able to make similar optimizations to them in follow up
changes.
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.
`FieldMapper#parseCreateField` accepts the parse context, plus a list of fields
as an output parameter. These fields are immediately added to the document
through `ParseContext#doc()`.
This commit simplifies the signature by removing the list of fields, and having
the mappers add the fields directly to `ParseContext#doc()`. I think this is
nicer for implementors, because previously fields could be added either through
the list, or the context (through `add`, `addWithKey`, etc.)
this commit adds aggregation support for the geo_shape field
type on geo*_grid aggregations.
it introduces a Tiler for both tiles and hashes that enables a new type of
ValuesSource to replace the GeoPoint's CellIdSource. This makes it possible
for the existing Aggregator to be re-used, so no new implementations of
the grid aggregators are added.
This commit converts the remaining isXXXAllowed methods to instead of
use isAllowed with a Feature value. There are a couple other methods
that are static, as well as some licensed features that check the
license directly, but those will be dealt with in other followups.
This commit refactors all spatial Field Mappers to a common
AbstractGeometryFieldMapper that implements shared parameter functionality
(e.g., ignore_malformed, ignore_z_value) and provides a common framework for
overriding type parsing, and building in xpack. Common shape functionality is
implemented in a new AbstractShapeGeometryFieldMapper that is reused and
overridden in GeoShapeFieldMapper, GeoShapeFieldMapperWithDocValues,
LegacyGeoShapeFieldMapper, and ShapeFieldMapper. This abstraction provides a
reusable foundation for adding new xpack features; such as coordinate reference
system support.
This commit refactors geo_shape doc values, fielddata, and utility classes from
the single mapper package in x-pack spatial plugin to a package structure that
is consistent with the server module.
This commit adds a new GeoShapeBoundsAggregator to the spatial plugin and registers it with the GeoShapeValuesSourceType. This enables geo_bounds aggregations on geo_shape fields
After #53562, the `geo_shape` field mapper is registered within
a module. This opens the door for introducing a new `geo_shape`
field mapper into the Spatial Plugin that has doc-values support.
This is very much an extension of server's GeoShapeFieldMapper,
but with the addition of the doc values implementation.
This commit introduces a new `geo` module that is intended
to be contain all the geo-spatial-specific features in server.
As a first step, the responsibility of registering the geo_shape
field mapper is moved to this module.
Co-authored-by: Nicholas Knize <nknize@gmail.com>
This commit adds a new point field that is able to index arbitrary pair of values (x/y)
in the cartesian space. It only supports filtering using shape queries at the moment.
Some field name constants were not updaten when we moved from "string" to "text"
and "keyword" fields. Renaming them makes it easier and faster to know which
field type is used in test subclassing this base test case.
Backport to 7x
Enable geo_shape query to work on geo_point fields for shapes: circle, polygon, multipolygon, rectangle see: #48928
Co-Authored-By: @iverase
Lucene 8.4 added support for "CONTAINS", therefore in this commit those
changes are integrated in Elasticsearch. This commit contains as well a
bug fix when querying with a geometry collection with "DISJOINT" relation.
Backport of #48849. Update `.editorconfig` to make the Java settings the
default for all files, and then apply a 2-space indent to all `*.gradle`
files. Then reformat all the files.
* Remove eclipse conditionals
We used to have some meta projects with a `-test` prefix because
historically eclipse could not distinguish between test and main
source-sets and could only use a single classpath.
This is no longer the case for the past few Eclipse versions.
This PR adds the necessary configuration to correctly categorize source
folders and libraries.
With this change eclipse can import projects, and the visibility rules
are correct e.x. auto compete doesn't offer classes from test code or
`testCompile` dependencies when editing classes in `main`.
Unfortunately the cyclic dependency detection in Eclipse doesn't seem to
take the difference between test and non test source sets into account,
but since we are checking this in Gradle anyhow, it's safe to set to
`warning` in the settings. Unfortunately there is no setting to ignore
it.
This might cause problems when building since Eclipse will probably not
know the right order to build things in so more wirk might be necesarry.
XPackPlugin holds data in statics and can only be initialized once. This
caused tests to fail primarily when running with a low max-workers.
Replaced usages with the LocalStateCompositeXPackPlugin, which handles
this properly for testing.
This commit replaces the SearchContext used in AbstractQueryTestCase with
a QueryShardContext in order to reduce the visibility of search contexts.
Relates #46523
Changes the order of parameters in Geometries from lat, lon to lon, lat
and moves all Geometry classes are moved to the
org.elasticsearch.geomtery package.
Backport of #45332Closes#45048
* Introduce Spatial Plugin (#44389)
Introduce a skeleton Spatial plugin that holds new licensed features coming to
Geo/Spatial land!
* [GEO] Refactor DeprecatedParameters in AbstractGeometryFieldMapper (#44923)
Refactor DeprecatedParameters specific to legacy geo_shape out of
AbstractGeometryFieldMapper.TypeParser#parse.
* [SPATIAL] New ShapeFieldMapper for indexing cartesian geometries (#44980)
Add a new ShapeFieldMapper to the xpack spatial module for
indexing arbitrary cartesian geometries using a new field type called shape.
The indexing approach leverages lucene's new XYShape field type which is
backed by BKD in the same manner as LatLonShape but without the WGS84
latitude longitude restrictions. The new field mapper builds on and
extends the refactoring effort in AbstractGeometryFieldMapper and accepts
shapes in either GeoJSON or WKT format (both of which support non geospatial
geometries).
Tests are provided in the ShapeFieldMapperTest class in the same manner
as GeoShapeFieldMapperTests and LegacyGeoShapeFieldMapperTests.
Documentation for how to use the new field type and what parameters are
accepted is included. The QueryBuilder for searching indexed shapes is
provided in a separate commit.
* [SPATIAL] New ShapeQueryBuilder for querying indexed cartesian geometry (#45108)
Add a new ShapeQueryBuilder to the xpack spatial module for
querying arbitrary Cartesian geometries indexed using the new shape field
type.
The query builder extends AbstractGeometryQueryBuilder and leverages the
ShapeQueryProcessor added in the previous field mapper commit.
Tests are provided in ShapeQueryTests in the same manner as
GeoShapeQueryTests and docs are updated to explain how the query works.
Nick Knize
Nik Everett
Julie Tibshirani
Tal Levy
Ryan Ernst
Igor Motov
Christos Soulios
Mark Tozzi
Ignacio Vera
Christoph Büscher
Dominic Page
markharwood
Ignacio Vera
Rory Hunter
Alpar Torok
Henning Andersen
Jim Ferenczi
Zachary Tong