The example of how to access the nano value of a date_nanos field has
been broken since it was created. This commit fixes it to use the
correct scripting methods.
closes#51931
Add a new cluster setting `search.allow_expensive_queries` which by
default is `true`. If set to `false`, certain queries that have
usually slow performance cannot be executed and an error message
is returned.
- Queries that need to do linear scans to identify matches:
- Script queries
- Queries that have a high up-front cost:
- Fuzzy queries
- Regexp queries
- Prefix queries (without index_prefixes enabled
- Wildcard queries
- Range queries on text and keyword fields
- Joining queries
- HasParent queries
- HasChild queries
- ParentId queries
- Nested queries
- Queries on deprecated 6.x geo shapes (using PrefixTree implementation)
- Queries that may have a high per-document cost:
- Script score queries
- Percolate queries
Closes: #29050
(cherry picked from commit a8b39ed842c7770bd9275958c9f747502fd9a3ea)
The way it was originally written, it sounds like
we are boosting at query time.
Of course, the effect is at query time,
but the point here is that boosting is done at index time
This PR adds per-field metadata that can be set in the mappings and is later
returned by the field capabilities API. This metadata is completely opaque to
Elasticsearch but may be used by tools that index data in Elasticsearch to
communicate metadata about fields with tools that then search this data. A
typical example that has been requested in the past is the ability to attach
a unit to a numeric field.
In order to not bloat the cluster state, Elasticsearch requires that this
metadata be small:
- keys can't be longer than 20 chars,
- values can only be numbers or strings of no more than 50 chars - no inner
arrays or objects,
- the metadata can't have more than 5 keys in total.
Given that metadata is opaque to Elasticsearch, field capabilities don't try to
do anything smart when merging metadata about multiple indices, the union of
all field metadatas is returned.
Here is how the meta might look like in mappings:
```json
{
"properties": {
"latency": {
"type": "long",
"meta": {
"unit": "ms"
}
}
}
}
```
And then in the field capabilities response:
```json
{
"latency": {
"long": {
"searchable": true,
"aggreggatable": true,
"meta": {
"unit": [ "ms" ]
}
}
}
}
```
When there are no conflicts, values are arrays of size 1, but when there are
conflicts, Elasticsearch includes all unique values in this array, without
giving ways to know which index has which metadata value:
```json
{
"latency": {
"long": {
"searchable": true,
"aggreggatable": true,
"meta": {
"unit": [ "ms", "ns" ]
}
}
}
}
```
Closes#33267
The docs/reference/redirects.asciidoc file stores a list of relocated or
deleted pages for the Elasticsearch Reference documentation.
This prunes several older redirects that are no longer needed and
don't require work to fix broken links in other repositories.
Users often mistakenly map numeric IDs to numeric datatypes. However,
this is often slow for the `term` and other term-level queries.
The "Tune for search speed" docs includes advice for mapping numeric
IDs to `keyword` fields. However, this tip is not included in the
`numeric` or `keyword` field datatype doc pages.
This rewords the tip in the "Tune for search speed" docs, relocates it
to the `numeric` field docs, and reuses it using tagged regions.
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.
This change adds a dynamic cluster setting named `indices.id_field_data.enabled`.
When set to `false` any attempt to load the fielddata for the `_id` field will fail
with an exception. The default value in this change is set to `false` in order to prevent
fielddata usage on this field for future versions but it will be set to `true` when backporting
to 7x. When the setting is set to true (manually or by default in 7x) the loading will also issue
a deprecation warning since we want to disallow fielddata entirely when https://github.com/elastic/elasticsearch/issues/26472
is implemented.
Closes#43599
The `string` type (with option `analyzed`) has been replaced by `text` after `6.0`,
also the `annonated_text` field do not support doc values and should be mentioned.
This PR makes the following two fixes around updating flattened fields:
* Make sure that the new value for ignore_above is immediately taken into
affect. Previously we recorded the new value but did not use it when parsing
documents.
* Allow depth_limit to be updated dynamically. It seems plausible that a user
might want to tweak this setting as they encounter more data.
This PR makes the following updates:
* Update the supported query types to include `prefix` and `wildcard`.
* Specify that queries accept index aliases.
* Clarify that when querying on a remote index name, the separator `:` must be
present.
We have not seen much adoption of this experimental field type, and don't see a
clear use case as it's currently designed. This PR deprecates the field type in
7.x. It will be removed from 8.0 in a follow-up PR.
The `ignore_malformed` setting only works on selected mapping types, otherwise
we throw an mapper_parsing_exception. We should add a list of all the mapping
types that support it, since the number of types not supporting it seems larger.
Closes#47166
Although they do not support eager_global_ordinals, ip fields use global
ordinals for certain aggregations like 'terms'.
This commit also corrects a reference to the sampler aggregation.
Currently we allow `_field_names` fields to be disabled explicitely, but since
the overhead is negligible now we decided to keep it turned on by default and
deprecate the `enable` option on the field type. This change adds a deprecation
warning whenever this setting is used, going forward we want to ignore and finally
remove it.
Closes#27239
This commit updates the eager_global_ordinals documentation to give more
background on what global ordinals are and when they are used. The docs also now
mention that global ordinal loading may be expensive, and describes the cases
where in which loading them can be avoided.
This PR merges the `vectors-optimize-brute-force` feature branch, which makes
the following changes to how vector functions are computed:
* Precompute the L2 norm of each vector at indexing time. (#45390)
* Switch to ByteBuffer for vector encoding. (#45936)
* Decode vectors and while computing the vector function. (#46103)
* Use an array instead of a List for the query vector. (#46155)
* Precompute the normalized query vector when using cosine similarity. (#46190)
Co-authored-by: Mayya Sharipova <mayya.sharipova@elastic.co>
* 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.
Previously, the reindex examples did not include `_doc` as the destination type.
This would result in the reindex failing with the error "Rejecting mapping
update to [users] as the final mapping would have more than 1 type: [_doc,
user]".
Relates to #43100.
Some small clarifications about force-merging and global ordinals, particularly
that global ordinals are cheap on a single-segment index and how this relates
to frozen indices.
Fixes#41687
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.
Ignacio Vera
Valentin Crettaz
James Rodewig
Igor Motov
Ryan Ernst
Marios Trivyzas
Yannick Welsch
Mayya Sharipova
Jonas F. Henriksen
junmuz
Adrien Grand
arkel-s
Nik Everett
Ignacio Vera
Jim Ferenczi
Julie Tibshirani
Antoine Garcia
lgypro
Christoph Büscher
Anton
Nick Knize
David Turner
Mark Walkom
Nikita Glashenko