This adds a new configurable field called `indices_options`. This allows users to create or update the indices_options used when a datafeed reads from an index.
This is necessary for the following use cases:
- Reading from frozen indices
- Allowing certain indices in multiple index patterns to not exist yet
These index options are available on datafeed creation and update. Users may specify them as URL parameters or within the configuration object.
closes https://github.com/elastic/elasticsearch/issues/48056
This change adds the recall@k metric and refactors precision@k to match
the new metric.
Recall@k is an important metric to use for learning to rank (LTR)
use-cases. Candidate generation or first ranking phase ranking functions
are often optimized for high recall, in order to generate as many
relevant candidates in the top-k as possible for a second phase of
ranking. Adding this metric allows tuning that base query for LTR.
See: https://github.com/elastic/elasticsearch/issues/51676
Backports: https://github.com/elastic/elasticsearch/pull/52577
Add query execution and return actual results returned from
Elasticsearch inside the tests
(cherry picked from commit 3e039282bf991af87604a6d4f8eada19d5e33842)
The introductory sections of the reference manual contains some simplified
instructions for adding a node to the cluster. Unfortunately they are a little
too simplified and only really work for clusters running on `localhost`. If you
try and follow these instructions for a distributed cluster then the new node
will, confusingly, auto-bootstrap itself into a distinct one-node cluster.
Multiple nodes running on localhost is a valid config, of course, but we should
spell out that these instructions are really only for experimentation and that
it takes a bit more work to add nodes to a distributed cluster. This commit
does so.
Also, the "important config" instructions for discovery say that you MUST set
`discovery.seed_hosts` whereas in fact it is fine to ignore this setting and
use a dynamic discovery mechanism instead. This commit weakens this statement
and links to the docs for dynamic discovery mechanisms.
Finally, this section is also overloaded with some technical details that are
not important for this context and are adequately covered elsewhere, and
completely fails to note that the default discovery port is 9300. This commit
addresses this.
Adds the `?refresh=wait_for` query argument to an index API snippet in
the term vectors API docs.
This should ensure the document is indexed and available before a
subsequent term vectors API request executes.
Fixes#52814.
* Smarter copying of the rest specs and tests (#52114)
This PR addresses the unnecessary copying of the rest specs and allows
for better semantics for which specs and tests are copied. By default
the rest specs will get copied if the project applies
`elasticsearch.standalone-rest-test` or `esplugin` and the project
has rest tests or you configure the custom extension `restResources`.
This PR also removes the need for dozens of places where the x-pack
specs were copied by supporting copying of the x-pack rest specs too.
The plugin/task introduced here can also copy the rest tests to the
local project through a similar configuration.
The new plugin/task allows a user to minimize the surface area of
which rest specs are copied. Per project can be configured to include
only a subset of the specs (or tests). Configuring a project to only
copy the specs when actually needed should help with build cache hit
rates since we can better define what is actually in use.
However, project level optimizations for build cache hit rates are
not included with this PR.
Also, with this PR you can no longer use the includePackaged flag on
integTest task.
The following items are included in this PR:
* new plugin: `elasticsearch.rest-resources`
* new tasks: CopyRestApiTask and CopyRestTestsTask - performs the copy
* new extension 'restResources'
```
restResources {
restApi {
includeCore 'foo' , 'bar' //will include the core specs that start with foo and bar
includeXpack 'baz' //will include x-pack specs that start with baz
}
restTests {
includeCore 'foo', 'bar' //will include the core tests that start with foo and bar
includeXpack 'baz' //will include the x-pack tests that start with baz
}
}
```
Remove reference to an "SQL API" which could suggest that one needs to
treat this in a special way when configuring the ODBC driver.
(cherry picked from commit 451c341e0193b542409e8891ec2a31e62529a5e7)
Adds an explicit "important" admonition discouraging apps from using
cat APIs.
cat APIs are intended for human consumption via the command line or
Kibana console only. They are not intended for consumption by
applications.
Indices open with the `niofs` store type load much more data on-heap than
indices open with the `mmapfs` store type. This limitation is now documented
and examples have been updated to show how to update settings to use the
`mmapfs` store type rather than `niofs`.
We should be more explicit about the downsides of disabling replicas and
explain that users should be ready to re-do the entire load in case of
issues mid-way.
One architecture that we have recommended to several users to speed up
indexing involved using CCR to prevent searching from stealing resources
from indexing.
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.
The changes add more granularity for identiying the data ingestion user.
The ingest pipeline can now be configure to record authentication realm and
type. It can also record API key name and ID when one is in use.
This improves traceability when data are being ingested from multiple agents
and will become more relevant with the incoming support of required
pipelines (#46847)
Resolves: #49106
* Allow forcemerge in the hot phase for ILM policies
This commit changes the `forcemerge` action to also be allowed in the `hot` phase for policies. The
forcemerge will occur after a rollover, and allows users to take advantage of higher disk speeds for
performing the force merge (on a separate node type, for example).
On caveat with this is that a `forcemerge` in the `hot` phase *MUST* be accompanied by a `rollover`
action. ILM validates policies to ensure this is the case.
Resolves#43165
* Use anyMatch instead of findAny in validation
* Make randomTimeseriesLifecyclePolicy single-pass
This change adds support for the following new model_size_stats
fields:
- categorized_doc_count
- total_category_count
- frequent_category_count
- rare_category_count
- dead_category_count
- categorization_status
Backport of #51879
This commit introduces the ability to override JVM options by adding
custom JVM options files to a jvm.options.d directory. This simplifies
administration of Elasticsearch by not requiring administrators to keep
the root jvm.options file in sync with changes that we make to the root
jvm.options file. Instead, they are not expected to modify this file but
instead supply their own in jvm.options.d. In Docker installations, this
means they can bind mount this directory in. In future versions of
Elasticsearch, we can consider removing the root jvm.options file
(instead, providing all options there as system JVM options).
This commit provides a path to set register the autoscaling feature flag
in release builds, and therefore enabling autoscaling in release
builds. The primary reason that we add this is so that our release docs
tests can pass. Our 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 autoscaling can not be enabled
in release builds, this meant that the autoscaling snippets would fail
in the release docs tests. To address then, we need the ability to
enable autoscaling in the release docs tests which we can now do with
the system property added here. This system property will be removed
when autoscaling is ready for release.
There is some extraneous whitespace here, and every time I look at this
file my editor wants to make these changes and so my diffs end up having
this noise in it which I fight to exclude. This commit addresses this
issue by removing this extraneous whitespace.
The main purpose of this commit is to add a single autoscaling REST
endpoint skeleton, for the purpose of starting to build out the build
and testing infrastructure that will surround it. For example, rather
than commiting a fully-functioning autoscaling API, we introduce here
the skeleton so that we can start wiring up the build and testing
infrastructure, establish security roles/permissions, an so on. This
way, in a forthcoming PR that introduces actual functionality, that PR
will be smaller and have less distractions around that sort of
infrastructure.
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.
Backport of #51867.
Tweak the documentation around configuring the heap size when using
Docker, to state that:
- using `ES_JAVA_OPTS` is the preferred method
- Any `ES_JAVA_OPTS` overrides the defaults in `jvm.options`
- It's possible to bind-mount a custom `jvm.options`
* Add empty_value parameter to CSV processor
This change adds `empty_value` parameter to the CSV processor.
This value is used to fill empty fields. Fields will be skipped
if this parameter is ommited. This behavior is the same for both
quoted and unquoted fields.
* docs updated
* Fix compilation problem
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
Nik Everett
Benjamin Trent
Nattachai Suteerapongpan
Josh Devins
István Zoltán Szabó
Costin Leau
David Turner
James Rodewig
Lisa Cawley
Jake Landis
Bogdan Pintea
Andrei Stefan
Pius
bellengao
David Pilato
David Roberts
Adrien Grand
Bob Blank
Julie Tibshirani
Mayya Sharipova
Przemko Robakowski
Ignacio Vera
Marios Trivyzas
Nik Richers
Sean Story
Armin Braun
Yannick Welsch
Russ Cam
Lee Hinman
Valentin Crettaz
debadair
OriGlassman
Igor Motov
Ryan Ernst
Marios Trivyzas
Yang Wang
Jason Tedor
Zachary Tong
Raidok
David Kyle
Rory Hunter