In the example we show an `exists` query inside a constant score query. While this is possible, it can mislead users to think it is necessary so we should remove it.
At the time of geo_shape query conception, CONTAINS was not yet a supported spatial operation in Lucene. Since it is now available this commit adds ShapeRelation.CONTAINS to GeoShapeQuery. Randomized testing is included and documentation is updated.
We already introduced the MatchNoneQueryBuilder query that does not
return any documents, mainly because we needed it for internal
representation of the NONE option in the IndicesQueryBuilder.
However, the query was requested at least once also for the query dsl,
and since we can parser it already we should document it as
`match_none` query in the relevant reference docs as well.
The NotQueryBuilder has been deprecated on the 2.x branches
and can be removed with the next major version. It can be
replaced by boolean query with added mustNot() clause.
Closes#13761
* Dropped ScoreType in favour of Lucene's ScoreMode
* Removed `score_type` option from `has_child` and `has_parent` queries in favour for the already existing `score_mode` option.
* Removed the score mode `sum` in favour for the already existing `total` score mode. (`sum` doesn't exist in Lucene's ScoreMode class)
* If `max_children` is set to `0` it now really means that zero children are allowed to match.
This commit splits HasParentQueryParser into toQuery and fromXContent.
This change also deprecates several keys in favor of simplified settings
and adds basic unittests for HasParentQueryParser.
Relates to #10217
The `multi_match` query groups terms that have the same analyzer together and
then applies the boost of the first query in each group. This is not necessary
given that boosts for each term are already applied another way.
Fixed documentation since the default rewrite method for fuzzy queries is to
select top terms, fixed usage of the fuzzy rewrite method, and removed unused
`rewrite` parameter.
Close#6932
This rewrite method is interesting because it computes scores as if all terms
had the same frequencies, which avoids disappointments with ranking when a fuzzy
query ranks typos first given that they are less frequent than the correct term.
This changes the parameter name `ignore_like` to the more user friendly name
`unlike`. This later feature generates a query from the terms in `A` but not
from the terms in `B`. This translates to a result set which is like `A` but
unlike `B`. We could have further negatively boosted any documents that have
some `B`, but these documents already do not receive any contribution from
having `B`, and would therefore negatively compete with documents having `A`.
Closes#11117