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
Currently when a document misses a vector value, vector function
returns 0 as a score for this document. We think this is incorrect
behaviour.
With this change, an error will be thrown if vector functions are
used with docs that are missing vector doc values.
Also VectorScriptDocValues is modified to allow size() function,
which can be used to check if a document has a value for the
vector field.
Typically, dense vectors of both documents and queries must have the same
number of dimensions. Different number of dimensions among documents
or query vector indicate an error. This PR enforces that all vectors
for the same field have the same number of dimensions. It also enforces
that query vectors have the same number of dimensions.
This commit adds a wildcard intervals source, similar to the prefix. It
also changes the term parameter in prefix to read prefix, to bring it
in to line with the pattern parameter in wildcard.
Closes#43198
This commit adds a prefix intervals source, allowing you to search
for intervals that contain terms starting with a given prefix. The source
can make use of the index_prefixes mapping option.
Relates to #43198
the geo-bounding-box and phrase-suggest docs were susceptible to
failing due to other indices in the cluster. This change restricts
the queries to the index that is set up for the test.
relates to #43271.
Now emphasises the test is for indexed values.
Previous documentation only mentioned the state of the input JSON doc (null values) but this is only one of several reasons why an indexed value may not exist.
Closes#24256
The `replace` option in the phonetic token filter can have suprising side
effects, e.g. such as described in #26921. This PR adds a note to be mindful
about such scenarios and offers alternatives to using the `replace` option.
Closes#26921
For `multi_match` query: link `boost` param to the generic reference
for query usage and `slop` to the `match_phrase` query where its usage
is documented.
Fixes: #40091
Remove `common` query and `cutoff_frequency` parameter of
`match` and `multi_match` queries. Both have already been
deprecated for the next 7.x version.
Closes: #37096
* Deprecate CommonTermsQuery and cutoff_frequency
Since the max_score optimization landed in Elasticsearch 7,
the CommonTermsQuery is redundant and slower. Moreover the
cutoff_frequency parameter for MatchQuery and MultiMatchQuery
is redundant.
Relates to #27096
Removes all deprecated type-related methods from the QueryBuilders helper class
and from tests using them. Also removing related docs tests and doc pages
refering to the `type` query. All removed methods have been deprecated since
version 7.0.
As negative scores will now cause an error, and it is easy to
accidentally produce negative scores with some of the built-in modifiers
(especially `ln` and `log`), this adjusts the documentation to more
strongly recommend the use of `ln1p` and `log1p` instead.
Also corrects some awkward formatting on the note sections following the
table.
Currently, the docs correctly state that using `now` in range queries will not
be affected by the `time_zone` parameter. However, using date math roundings
like e.g. `now\d` will be affected by the `time_zone`. Adding this example
because it seems to be a frequently asked question and source of confusion.
Relates to #40581
Negative scores are no longer allowed, but the cosine similarity between two
vectors lies in the range [-1, 1], and dot products can also be negative. This commit
updates the documentation with an example of how to avoid negative scores.
To make script_score query to have the same features
as function_score query, we need to add randomScore
function.
This function produces different
random scores on different index shards.
It is also able to produce random scores
based on the internal Lucene Document Ids.
Adds the search_as_you_type field type that acts like a text field optimized
for as-you-type search completion. It creates a couple subfields that analyze
the indexed terms as shingles, against which full terms are queried, and a
prefix subfield that analyze terms as the largest shingle size used and
edge-ngrams, against which partial terms are queried
Adds a match_bool_prefix query type that creates a boolean clause of a term
query for each term except the last, for which a boolean clause with a prefix
query is created.
The match_bool_prefix query is the recommended way of querying a search as you
type field, which will boil down to term queries for each shingle of the input
text on the appropriate shingle field, and the final (possibly partial) term
as a term query on the prefix field. This field type also supports phrase and
phrase prefix queries however
This is the equivalent of the `field_masking_span` query, allowing users to
merge intervals from multiple fields - for example, to search for stemmed tokens
near unstemmed tokens.
`document_type` is the type to use for parsing the document to percolate, which
is already optional and deprecated. However `percotale` queries also have the
ability to percolate existing documents, identified by an index, an id and a
type. This change makes the latter optional and deprecated.
Closes#39963
The example in the Fuzziness section was actually relevant to the section above it, so I moved it there. I replaced it with an example of how to use the `fuzziness` parameter
This commit changes the default for the `track_total_hits` option of the search request
to `10,000`. This means that by default search requests will accurately track the total hit count
up to `10,000` documents, requests that match more than this value will set the `"total.relation"`
to `"gte"` (e.g. greater than or equals) and the `"total.value"` to `10,000` in the search response.
Scroll queries are not impacted, they will continue to count the total hits accurately.
The default is set back to `true` (accurate hit count) if `rest_total_hits_as_int` is set in the search request.
I choose `10,000` as the default because that's also the number we use to limit pagination. This means that users will be able to know how far they can jump (up to 10,000) even if the total number of hits is not accurate.
Closes#33028
Ranaming as follows:
feature -> rank_feature
feature_vector -> rank_features
feature query -> rank_feature query
Ranaming is done to distinguish from other vector types.
Closes#36723
The "include_type_name" parameter was temporarily introduced in #37285 to facilitate
moving the default parameter setting to "false" in many places in the documentation
code snippets. Most of the places can simply be reverted without causing errors.
In this change I looked for asciidoc files that contained the
"include_type_name=true" addition when creating new indices but didn't look
likey they made use of the "_doc" type for mappings. This is mostly the case
e.g. in the analysis docs where index creating often only contains settings. I
manually corrected the use of types in some places where the docs still used an
explicit type name and not the dummy "_doc" type.
* Default include_type_name to false for get and put mappings.
* Default include_type_name to false for get field mappings.
* Add a constant for the default include_type_name value.
* Default include_type_name to false for get and put index templates.
* Default include_type_name to false for create index.
* Update create index calls in REST documentation to use include_type_name=true.
* Some minor clean-ups around the get index API.
* In REST tests, use include_type_name=true by default for index creation.
* Make sure to use 'expression == false'.
* Clarify the different IndexTemplateMetaData toXContent methods.
* Fix FullClusterRestartIT#testSnapshotRestore.
* Fix the ml_anomalies_default_mappings test.
* Fix GetFieldMappingsResponseTests and GetIndexTemplateResponseTests.
We make sure to specify include_type_name=true during xContent parsing,
so we continue to test the legacy typed responses. XContent generation
for the typeless responses is currently only covered by REST tests,
but we will be adding unit test coverage for these as we implement
each typeless API in the Java HLRC.
This commit also refactors GetMappingsResponse to follow the same appraoch
as the other mappings-related responses, where we read include_type_name
out of the xContent params, instead of creating a second toXContent method.
This gives better consistency in the response parsing code.
* Fix more REST tests.
* Improve some wording in the create index documentation.
* Add a note about types removal in the create index docs.
* Fix SmokeTestMonitoringWithSecurityIT#testHTTPExporterWithSSL.
* Make sure to mention include_type_name in the REST docs for affected APIs.
* Make sure to use 'expression == false' in FullClusterRestartIT.
* Mention include_type_name in the REST templates docs.
Peter Johnson
James Rodewig
Christoph Büscher
markharwood
Anton
David Woods
Alan Woodward
Ryan Ernst
Andrew Naguib
rikardbakkehaug
Suhel Khan
Nick Knize
Mayya Sharipova
Alan Woodward
rbayet
Tal Levy
Shubham Vipul Majmudar
Marios Trivyzas
Gordon Brown
Andy Bristol
Julie Tibshirani
avshiav
Adrien Grand
MK Swanson
Alexander Reelsen
Jim Ferenczi