Before boost in script_score query was wrongly applied only to the subquery.
This commit makes sure that the boost is applied to the whole score
that comes out of script.
Closes#48465
Explicitly notes the Elasticsearch API endpoints that support CCS.
This should deter users from attempting to use CCS with other API
endpoints, such as `GET <index>/_doc/<_id>`.
* Adds an example request to the top of the page.
* Relocates several parameters erroneously listed under "Request body"
to the appropriate "Query parameters" section.
* Updates the "Request body" section to better document the NDJSON
structure of msearch requests.
Add default value to each one of the usages of `allow_no_indices`
since it differs between different APIs.
Relates to: #52534
(cherry picked from commit 2eb986488ac326d6da6ab8ad0203a94e08684a36)
This adds machine learning model feature importance calculations to the inference processor.
The new flag in the configuration matches the analytics parameter name: `num_top_feature_importance_values`
Example:
```
"inference": {
"field_mappings": {},
"model_id": "my_model",
"inference_config": {
"regression": {
"num_top_feature_importance_values": 3
}
}
}
```
This will write to the document as follows:
```
"inference" : {
"feature_importance" : {
"FlightTimeMin" : -76.90955548511226,
"FlightDelayType" : 114.13514762158526,
"DistanceMiles" : 13.731580450792187
},
"predicted_value" : 108.33165831875137,
"model_id" : "my_model"
}
```
This is done through calculating the [SHAP values](https://arxiv.org/abs/1802.03888).
It requires that models have populated `number_samples` for each tree node. This is not available to models that were created before 7.7.
Additionally, if the inference config is requesting feature_importance, and not all nodes have been upgraded yet, it will not allow the pipeline to be created. This is to safe-guard in a mixed-version environment where only some ingest nodes have been upgraded.
NOTE: the algorithm is a Java port of the one laid out in ml-cpp: https://github.com/elastic/ml-cpp/blob/master/lib/maths/CTreeShapFeatureImportance.cc
usability blocked by: https://github.com/elastic/ml-cpp/pull/991
Re-adds several redirects removed with #50510.
These redirects were related to the relocation of several API docs to
new pages under the 'REST APIs' chapter.
We've since decided to only remove such redirects with major releases.
When `PUT` is called to store a trained model, it is useful to return the newly create model config. But, it is NOT useful to return the inflated definition.
These definitions can be large and returning the inflated definition causes undo work on the server and client side.
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
This commit updates the enrich.get_policy API to specify name
as a list, in line with other URL parts that accept a comma-separated
list of values.
In addition, update the get enrich policy API docs
to align the URL part name in the documentation with
the name used in the REST API specs.
(cherry picked from commit 94f6f946ef283dc93040e052b4676c5bc37f4bde)
* Refresh snapshots with latest look
Add new snapshots with the connection editor to reflect the latest UI.
* Document the effect of the late added params
Add details about the Cloud ID setting, as well as those on the Misc
tab.
(cherry picked from commit afa67625e847e99a22264f5dd6fa0daa37786c6f)
Updates the cross-cluster search (CCS) documentation to note how
cluster-level settings are applied.
When `ccs_minimize_roundtrips` is `true`, each cluster applies its own
cluster-level settings to the request.
When `ccs_minimize_roundtrips` is `false`, cluster-level settings for
the local cluster is used. This includes shard limit settings, such as
`action.search.shard_count.limit`, `pre_filter_shard_size`, and
`max_concurrent_shard_requests`. If these limits are set too low, the
request could be rejected.
* Fix "Description"s for various sections in the functions pages.
* Added a TIP for searching using a routing key.
* Other small polishings
(cherry picked from commit 9fad0b1ac4409a42c435ed040f41cbaea18930a3)
The `top_metrics` agg is kind of like `top_hits` but it only works on
doc values so it *should* be faster.
At this point it is fairly limited in that it only supports a single,
numeric sort and a single, numeric metric. And it only fetches the "very
topest" document worth of metric. We plan to support returning a
configurable number of top metrics, requesting more than one metric and
more than one sort. And, eventually, non-numeric sorts and metrics. The
trick is doing those things fairly efficiently.
Co-Authored by: Zachary Tong <zach@elastic.co>
This adds a builder and parsed results for the `string_stats`
aggregation directly to the high level rest client. Without this the
HLRC can't access the `string_stats` API without the elastic licensed
`analytics` module.
While I'm in there this adds a few of our usual unit tests and
modernizes the parsing.
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)
I plan to add additional sections to this page with future PRs:
* Specify timestamp and event type fields
* Specify a join key field
* Filter using query DSL
* Paginate a large response
See #51057.
Add a section to point out that when ordering by an aggregate
only plain aggregate functions are allowed, no scalars/operators
can be used on top of them.
Fixes: #52204
(cherry picked from commit 78a1185549ff7f3229fd2d036567eb2a4f2cf230)
7.x backport of #52201
Provides a path to set register the EQL feature flag in release builds.
This enables EQL in release builds so that release docs tests pass.
Release docs tests do not have infrastructure in place to only register
snippets from included portions of the docs, they instead include all
docs snippets.
Since EQL can not be enabled in release builds, this meant that the EQL
snippets fail in the release docs tests.
This adds the ability to enable EQL in the release docs tests. This
system property will be removed when EQL is ready for release.
Adds the ability to display docs on permanently unreleased branches,
such as `master` and `7.x`.
Also updates how the autoscaling and EQL docs are included.
Currently, these feature-flag docs would display on any unreleased
branches that contain the changes, such as 7.7.
Today we use `cluster.join.timeout` to prevent nodes from waiting indefinitely
if joining a faulty master that is too slow to respond, and
`cluster.publish.timeout` to allow a faulty master to detect that it is unable
to publish its cluster state updates in a timely fashion. If these timeouts
occur then the node restarts the discovery process in an attempt to find a
healthier master.
In the special case of `discovery.type: single-node` there is no point in
looking for another healthier master since the single node in the cluster is
all we've got. This commit suppresses these timeouts and instead lets the node
wait for joins and publications to succeed no matter how long this might take.
Andrei Stefan
Julie Tibshirani
lcawl
Mayya Sharipova
Przemko Robakowski
James Rodewig
Ignacio Vera
Marios Trivyzas
Benjamin Trent
Nik Richers
Sean Story
Armin Braun
István Zoltán Szabó
Yannick Welsch
Russ Cam
Lee Hinman
Valentin Crettaz
Bogdan Pintea
debadair
OriGlassman
Nik Everett
bellengao
Igor Motov
Ryan Ernst
Marios Trivyzas
David Turner