It is fairly common to filter the geo point candidates in
geohash_grid and geotile_grid aggregations according to some
viewable bounding box. This change introduces the option of
specifying this filter directly in the tiling aggregation.
This is even more relevant to `geo_shape` where the bounds will restrict
the shape to be within the bounds
this optional `bounds` parameter is parsed in an equivalent fashion to
the bounds specified in the geo_bounding_box query.
This intervals source will return terms that are similar to an input term, up to
an edit distance defined by fuzziness, similar to FuzzyQuery.
Closes#49595
PR #44238 changed several links related to the Elasticsearch search request body API. This updates several places still using outdated links or anchors.
This will ultimately let us remove some redirects related to those link changes.
The `filter` rule is not allowed on the top-level of the query, so removing it
from the list of allowed rules. Where it can be nested inside other rules, those
rules already mention it.
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.
In the shape query docs, the index mapping snippet uses the "geometry"
shape field mapping. However, the doc index snippet uses the "location"
property.
This changes the "location" property to "geometry". It also adds a
comment containing the search result snippet. This should prevent
similar issues in the future.
Adds documentation for the `minimum_should_match` parameter to the `bool` query docs. Includes docs for the default values:
- `1` if the `bool` query includes at least one `should` clause and no `must` or `filter` clauses
- `0` otherwise
The default is set to Integer.MAX_VALUE but is reported to be `0` in the docs.
With the current implementation a value of 0 would mean all terms are filtered
out, which is the opposite of "unbounded".
Closes#49520
All document scores are positive 32-bit floating point numbers. However, this
wasn't previously documented.
This can result in surprising behavior, such as precision loss, for users when
customizing scores using the function score query.
This commit updates an existing admonition in the function score query docs to
document the 32-bits precision limit. It also updates the search API reference
docs to note that `_score` is a 32-bit float.
While function scores using scripts do allow explanations, they are only
creatable with an expert plugin. This commit improves the situation for
the newer script score query by adding the ability to set the
explanation from the script itself.
To set the explanation, a user would check for `explanation != null` to
indicate an explanation is needed, and then call
`explanation.set("some description")`.
Search enhancement: - new query type allows selected documents to be promoted above any "organic” search results.
This is the first feature in a new module `search-business-rules` which will house licensed (non OSS) logic for rewriting queries according to business rules.
The PinnedQueryBuilder class offers a new `pinned` query in the DSL that takes an array of promoted IDs and an “organic” query and ensures the documents with the promoted IDs rank higher than the organic matches.
Closes#44074
This commit adds 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.
* Add l1norm and l2norm distances for vectors
Add L1norm - Manhattan distance
Add L2norm - Euclidean distance
relates to #37947
* Address Christoph's feedback
- organize vector functions as a separate doc
- increase precision in tests calculations
- add a separate test when sparse doc dims
are bigger and less than query vector dims
* Made examples more realistic
