Renames the GET, PUT and DELETE inference APIs removing the model parts:
inference.delete_model -> inference.delete
inference.get_model -> inference.get
inference.put -> inference.put
The GET response now has a endpoints field instead of models
* Track synthetic source for disabled objects
* Update docs/changelog/108051.yaml
* minor refactor
* remove redundant method
* no need to skipChildren
* add mixed test
* add mixed yaml test
* remove extra line
* Implement synthetic source support for range fields
This PR adds basic synthetic source support for range fields. There are
following notable properties of synthetic source produced:
* Ranges are always normalized to be inclusive on both ends (this is how
they are stored).
* Original order of ranges is not preserved.
* Date ranges are always expressed in epoch millis, format is not
preserved.
* IP ranges are always expressed as a range of IPs while it could
have been originally provided as a CIDR.
This PR only implements retrieval of data for source reconstruction from
doc values.
Resolves#106254
This PR introduces `_name` support for top-level kNN queries, enabling named query functionality consistent with other query types. Changes include serialization/deserialization of the `_name` field within `KnnSearchBuilder` and handling within `KnnScoreDocQueryBuilder`.
Key Changes:
- Added `_name` field to `KnnSearchBuilder`.
- Modified serialization to include `_name`.
- Ensured `_name` is processed during query execution and included in the response.
Tests:
- Updated existing tests to cover `_name` functionality.
- Added new tests to ensure correct serialization/deserialization and response behavior.
During the fetch phase, there's a number of stored fields that are requested explicitly or loaded by default. That information is included in `StoredFieldsSpec` that each fetch sub phase exposes.
We attempt to provide stored fields that are already loaded to the fields lookup that scripts as well as value fetchers use to load field values (via `SearchLookup`). This is done in `PreloadedFieldLookupProvider.` The current logic makes available values for fields that have been found, so that scripts or value fetchers that request them don't load them again ad-hoc. What happens though for stored fields that don't have a value for a specific doc, is that they are treated like any other field that was not requested, and loaded again, although they will not be found, which causes overhead.
This change makes available to `PreloadedFieldLookupProvider` the list of required stored fields, so that it can better distinguish between fields that we already attempted to load (although we may not have found a value for them) and those that need to be loaded ad-hoc (for instance because a script is requesting them for the first time).
This is an existing issue, that has become evident as we moved fetching of metadata fields to `FetchFieldsPhase`, that relies on value fetchers, and hence on `SearchLookup`. We end up attempting to load default metadata fields (`_ignored` and `_routing`) twice when they are not present in a document, which makes us call `LeafReader#storedFields` additional times for the same document providing a `SingleFieldVisitor` that will never find a value.
Another existing issue that this PR fixes is for the `FetchFieldsPhase` to extend the `StoredFieldsSpec` that it exposes to include the metadata fields that the phase is now responsible for loading. That results in `_ignored` being included in the output of the debug stored fields section when profiling is enabled. The fact that it was previously missing is an existing bug (it was missing in `StoredFieldLoader#fieldsToLoad`).
Yet another existing issues that this PR fixes is that `_id` has been until now always loaded on demand when requested via fetch fields or script. That is because it is not part of the preloaded stored fields that the fetch phase passes over to the `PreloadedFieldLookupProvider`. That causes overhead as the field has already been loaded, and should not be loaded once again when explicitly requested.
* Adding confidence_interval to one of the tests
* Fixing mapper testKnnQuantizedHNSWVectorsFormat
* Adding deterministic confidence interval for int8 flat
Here we extract the logic to populate metadata fields such as _ignored, _routing, _size and the deprecated _type into FetchFieldsPhase so that we can use the ValueFetcher interface to retrieve field values. This allows us to fetch values no matter if the Mapper uses stored or doc values.
This commit adds an optimised int8 vector distance implementation for aarch64. Additional platforms like, say, x64, will be added as a follow-up.
The vector distance implementation outperforms Lucene's Pamana Vector implementation for binary comparisons by approx 5x (depending on the number of dimensions). It does so by means of compiler intrinsics built into a separate native library and link by Panama's FFI. Comparisons are performed on off-heap mmap'ed vector data.
The implementation is currently only used during merging of scalar quantized segments, through a custom format ES814HnswScalarQuantizedVectorsFormat, but its usage will likely be expanded over time.
Co-authored-by: Benjamin Trent <ben.w.trent@gmail.com>
Co-authored-by: Lorenzo Dematté <lorenzo.dematte@elastic.co>
Co-authored-by: Mark Vieira <portugee@gmail.com>
Co-authored-by: Ryan Ernst <ryan@iernst.net>
To simplify the migration away from version based skip checks in YAML specs,
this PR adds a synthetic version feature `gte_vX.Y.Z` for any version at or before 8.14.0.
New test specs for 8.14 or later are expected to use respective new cluster features,
or a test-only feature supplied via ESRestTestCase#createAdditionalFeatureSpecifications
if sufficient.
When an alias action list is posted with must_exist==false, and succeeds only partially, a list of results for each action are now returned. The results contain information about the requested action, indices, and aliases. If must_exist==true, or all actions fail, the call will return a 400 status along with the associated exception.
