This new API provides a way for users to upgrade their own anomaly job
model snapshots.
To upgrade a snapshot the following is done:
- Open a native process given the job id and the desired snapshot id
- load the snapshot to the process
- write the snapshot again from the native task (now updated via the
native process)
relates #64154
This adds a new flag `exclude_generated` for GET transform API.
This flag is useful for when a transform needs to be cloned within a cluster or exported/imported between clusters.
It removes certain fields that are not able to be set via the PUT api (e.g. version, create_time).
relates https://github.com/elastic/elasticsearch/issues/63055
* Adding authentication information to access token create APIs
Adding authentication object to following APIs:
/_security/oauth2/token
/_security/delegate_pki
/_security/saml/authenticate
/_security/oidc/authenticate
Resolves: #59685
(cherry picked from commit 51dbd9e584)
* Addressing PR commends, fixing tests
* Returning tokenGroups attribute as SID string instead of byte array (AD metadata)
Addressing PR comments
* Returning tokenGroups attribute as SID string instead of byte array (AD metadata)
Update version check
* Returning tokenGroups attribute as SID string instead of byte array (AD metadata)
Update version check
* Addressing more PR comments
* Adding more to integration tests + some small fixes
Getting the API key document form the security index is the most time consuing part
of the API Key authentication flow (>60% if index is local and >90% if index is remote).
This traffic is now avoided by caching added with this PR.
Additionally, we add a cache invalidator registry so that clearing of different caches will
be managed in a single place (requires follow-up PRs).
This adds the new `for_export` flag to the following APIs:
- GET _ml/anomaly_detection/<job_id>
- GET _ml/datafeeds/<datafeed_id>
- GET _ml/data_frame/analytics/<analytics_id>
The flag is designed for cloning or exporting configuration objects to later be put into the same cluster or a separate cluster.
The following fields are not returned in the objects:
- any field that is not user settable (e.g. version, create_time)
- any field that is a calculated default value (e.g. datafeed chunking_config)
- any field that would effectively require changing to be of use (e.g. datafeed job_id)
- any field that is automatically set via another Elastic stack process (e.g. anomaly job custom_settings.created_by)
closes https://github.com/elastic/elasticsearch/issues/63055
Adds new flag include to the get trained models API
The flag initially has two valid values: definition, total_feature_importance.
Consequently, the old include_model_definition flag is now deprecated.
When total_feature_importance is included, the total_feature_importance field is included in the model metadata object.
Including definition is the same as previously setting include_model_definition=true.
Adds HLRC and some docs for the new feature_processors field in Data frame analytics.
Co-authored-by: Przemysław Witek <przemyslaw.witek@elastic.co>
Co-authored-by: Lisa Cawley <lcawley@elastic.co>
Changes:
* Removes narrative around URI searches. These aren't commonly used in production. The `q` param is already covered in the search API docs: https://www.elastic.co/guide/en/elasticsearch/reference/master/search-search.html#search-api-query-params-q
* Adds a common options section that highlights narrative docs for query DSL, aggregations, multi-index search, search fields, pagination, sorting, and async search.
* Adds a `Search shard routing` page. Moves narrative docs for adaptive replica selection, preference, routing , and shard limits to that section.
* Moves search timeout and cancellation content to the `Search your data` page.
* Creates a `Search multiple data streams and indices` page. Moves related narrative docs for multi-target syntax searches and `indices_boost` to that page.
* Removes narrative examples for the `search_type` parameters. Moves documentation for this parameter to the search API docs.
Plugin discovery documentation contained information about installing
Elasticsearch 2.0 and installing an oracle JDK, both of which is no
longer valid.
While noticing that the instructions used cleartext HTTP to install
packages, this commit replaces HTTPs links instead of HTTP where possible.
In addition a few community links have been removed, as they do not seem
to exist anymore.
This adds a setting to data frame analytics jobs called
`max_number_threads`. The setting expects a positive integer.
When used the user specifies the max number of threads that may
be used by the analysis. Note that the actual number of threads
used is limited by the number of processors on the node where
the job is assigned. Also, the process may use a couple more threads
for operational functionality that is not the analysis itself.
This setting may also be updated for a stopped job.
More threads may reduce the time it takes to complete the job at the cost
of using more CPU.
Different kinds of requests may need different request options from the client
default. Users can optionally set RequestConfig on a single request's
RequestOptions to override the default. Without this, socketTimeout can only
set at RestClient initialization.
Add caching support for application privileges to reduce number of round-trips to security index when building application privilege descriptors.
Privilege retrieving in NativePrivilegeStore is changed to always fetching all privilege documents for a given application. The caching is applied to all places including "get privilege", "has privileges" APIs and CompositeRolesStore (for authentication).
Today when creating a follower index via the put follow API, or via an
auto-follow pattern, it is not possible to specify settings overrides
for the follower index. Instead, we copy all of the leader index
settings to the follower. Yet, there are cases where a user would want
some different settings on the follower index such as the number of
replicas, or allocation settings. This commit addresses this by allowing
the user to specify settings overrides when creating follower index via
manual put follower calls, or via auto-follow patterns. Note that not
all settings can be overrode (e.g., index.number_of_shards) so we also
have detection that prevents attempting to override settings that must
be equal between the leader and follow index. Note that we do not even
allow specifying such settings in the overrides, even if they are
specified to be equal between the leader and the follower
index. Instead, the must be implicitly copied from the leader index, not
explicitly set by the user.
When we force delete a DF analytics job, we currently first force
stop it and then we proceed with deleting the job config.
This may result in logging errors if the job config is deleted
before it is retrieved while the job is starting.
Instead of force stopping the job, it would make more sense to
try to stop the job gracefully first. So we now try that out first.
If normal stop fails, then we resort to force stopping the job to
ensure we can go through with the delete.
In addition, this commit introduces `timeout` for the delete action
and makes use of it in the child requests.
This adds a max_model_memory setting to forecast requests.
This setting can take a string value that is formatted according to byte sizes (i.e. "50mb", "150mb").
The default value is `20mb`.
There is a HARD limit at `500mb` which will throw an error if used.
If the limit is larger than 40% the anomaly job's configured model limit, the forecast limit is reduced to be strictly lower than that value. This reduction is logged and audited.
related native change: https://github.com/elastic/ml-cpp/pull/1238
closes: https://github.com/elastic/elasticsearch/issues/56420
This PR changes the name of the Index Template V2 classes to "Composable Templates", it also ensures there are no mentions of "V2" in the documentation or error/warning messages. V1 templates are referred to as "legacy" templates.
Resolves#56609
Throttling nightly cleanup as much as we do has been over cautious.
Night cleanup should be more lenient in its throttling. We still
keep the same batch size, but now the requests per second scale
with the number of data nodes. If we have more than 5 data nodes,
we don't throttle at all.
Additionally, the API now has `requests_per_second` and `timeout` set.
So users calling the API directly can set the throttling.
This commit also adds a new setting `xpack.ml.nightly_maintenance_requests_per_second`.
This will allow users to adjust throttling of the nightly maintenance.
Adds a "node" field to the response from the following endpoints:
1. Open anomaly detection job
2. Start datafeed
3. Start data frame analytics job
If the job or datafeed is assigned to a node immediately then
this field will return the ID of that node.
In the case where a job or datafeed is opened or started lazily
the node field will contain an empty string. Clients that want
to test whether a job or datafeed was opened or started lazily
can therefore check for this.
Fixes#54067
The usage of local parameter for GetFieldMappingRequest has been removed from the underlying transport action since v2.0.
This PR deprecates the parameter from rest layer. It will be removed in next major version.
A new field called `inference_config` is now added to the trained model config object. This new field allows for default inference settings from analytics or some external model builder.
The inference processor can still override whatever is set as the default in the trained model config.
Today when canceling a task we broadcast ban/unban requests to all nodes
in the cluster. This strategy does not scale well for hierarchical
cancellation. With this change, we will track outstanding child requests
and broadcast the cancellation to only nodes that have outstanding child
tasks. This change also prevents a parent task from sending child
requests once it got canceled.
Relates #50990
Supersedes #51157
Co-authored-by: Igor Motov <igor@motovs.org>
Co-authored-by: Yannick Welsch <yannick@welsch.lu>
Adds a new parameter for classification that enables choosing whether to assign labels to
maximise accuracy or to maximise the minimum class recall.
Fixes#52427.
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.
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.
This commit adds examples in our documentation for
- An HLRC instance authenticating to an elasticsearch cluster using
an elasticsearch token service access token or an API key
- An HLRC instance connecting to an elasticsearch cluster that is
setup for TLS on the HTTP layer when the CA certificate of the
cluster is available either as a PEM file or a keystore
- An HLRC instance connecting to an elasticsearch cluster that
requires client authentication where the client key and certificate
are available in a keystore
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
Adds a new URL parameter, `tags` to the GET _ml/inference/<model_id> endpoint.
This parameter allows the list of models to be further reduced to those who contain all the provided tags.
Synced flush was a brilliant idea. It supports instant recoveries with a
quite small implementation. However, with the presence of sequence
numbers and retention leases, it is no longer needed. This change
removes it from 8.0.
Relates #5077
Adds a new parameter to regression and classification that enables computation
of importance for the top most important features. The computation of the importance
is based on SHAP (SHapley Additive exPlanations) method.
This adds the `PUT` API for creating trained models that support our format.
This includes
* HLRC change for the API
* API creation
* Validations of model format and call
Adds a `force` parameter to the delete data frame analytics
request. When `force` is `true`, the action force-stops the
jobs and then proceeds to the deletion. This can be used in
order to delete a non-stopped job with a single request.
Closes#48124
Unreverts the commit that added the remote info api to HLRC (#49657).
The additional change to the original PR, is that `org.elasticsearch.client.cluster.RemoteConnectionInfo` now parses the initial_connect_timeout field as a string instead of a TimeValue instance.
The reason that this is needed is because that the initial_connect_timeout field in the remote connection api is serialized for human consumption, but not for parsing purposes.
Therefore the HLRC can't parse it correctly (which caused test failures in CI, but not in the PR CI
:( ). The way this field is serialized needs to be changed in the remote connection api, but that is a breaking change. We should wait making this change until rest api versioning is introduced.
Co-Authored-By: j-bean anton.shuvaev91@gmail.com
This adds a new `randomize_seed` for regression and classification.
When not explicitly set, the seed is randomly generated. One can
reuse the seed in a similar job in order to ensure the same docs
are picked for training.
Reindex sort never gave a guarantee about the order of documents being
indexed into the destination, though it could give a sense of locality
of source data.
It prevents us from doing resilient reindex and other optimizations and
it has therefore been deprecated.
Related to #47567
This adds a `_source` setting under the `source` setting of a data
frame analytics config. The new `_source` is reusing the structure
of a `FetchSourceContext` like `analyzed_fields` does. Specifying
includes and excludes for source allows selecting which fields
will get reindexed and will be available in the destination index.
Closes#49531
This commit replaces the _estimate_memory_usage API with
a new API, the _explain API.
The API consolidates information that is useful before
creating a data frame analytics job.
It includes:
- memory estimation
- field selection explanation
Memory estimation is moved here from what was previously
calculated in the _estimate_memory_usage API.
Field selection is a new feature that explains to the user
whether each available field was selected to be included or
not in the analysis. In the case it was not included, it also
explains the reason why.
PR #25543 removed the `_uid` field in favor of the `_id` field,
including for use in slicing.
This removes an outdated reference to `_uid` in our reindex docs.
This commit adds HLRC support and documentation for the SLM Start and
Stop APIs, as well as updating existing documentation where appropriate.
This commit also ensures that the SLM APIs are properly included in the
HLRC documentation.
David Kyle
James Rodewig
Benjamin Trent
Jake Landis
István Zoltán Szabó
Lyudmila Fokina
Przemysław Witek
Lisa Cawley
Yang Wang
Manabu Matsuzaki
bumjin
Mark Tozzi
Alexander Reelsen
Dimitris Athanasiou
weizijun
Jason Tedor
Lee Hinman
Samidh
Kamyar Ghajar
Andrei Dan
Hendrik Muhs
David Roberts
Nhat Nguyen
Christoph Büscher
Tom Veasey
Maxim
OriGlassman
Nik Everett
Raidok
Ioannis Kakavas
Jake
Martijn van Groningen
j-bean
Henning Andersen
Michael Basnight
James Rodewig
Alexandre Fonseca
debadair
Gordon Brown
Tanguy Leroux