It is possible for ML jobs to open lazily if the "allow_lazy_open"
option in the job config is set to true. Such jobs wait in the
"opening" state until a node has sufficient capacity to run them.
This commit fixes the bug that prevented datafeeds for jobs lazily
waiting assignment from being started. The state of such datafeeds
is "starting", and they can be stopped by the stop datafeed API
while in this state with or without force.
Backport of #53918
add 2 additional stats: processing time and processing total which capture the
time spent for processing results and how often it ran. The 2 new stats
correspond to the existing indexing and search stats. Together with indexing
and search this now allows the user to see the full picture, all 3 stages.
* Get Async Search: omit _clusters section when empty (#53907)
The _clusters section is omitted by the search API whenever no remote clusters are searched. Async search should do the same, but Get Async Search returns a deserialized response, hence a weird `_clusters` section with all values set to `0` gets returned instead. In fact the recreated Clusters object is not the same object as the EMPTY constant, yet it has the same content.
This commit addresses this by changing the comparison in the `toXContent` method to not print out the section if the number of total clusters is `0`.
* Async search: remove version from response (#53960)
The goal of the version field was to quickly show when you can expect to find something new in the search response, compared to when nothing has changed. This can also be done by looking at the `_shards` section and `num_reduce_phases` returned with the search response. In fact when there has been one or more additional reduction of the results, you can expect new results in the search response. Otherwise, the `_shards` section could notify of additional failures of shards that have completed the query, but that is not a guarantee that their results will be exposed (only when the following partial reduction is performed their results will be available).
That said this commit clarifies this in the docs and removes the version field from the async search response
* Async Search: replicas to auto expand from 0 to 1 (#53964)
This way single node clusters that are green don't go yellow once async search is used, while
all the others still have one replica.
* [DOCS] address timing issue in async search docs tests (#53910)
The docs snippets for submit async search have proven difficult to test as it is not possible to guarantee that you get a response that is not final, even when providing `wait_for_completion=0`. In the docs we want to show though a proper long-running query, and its first response should be partial rather than final.
With this commit we adapt the docs snippets to show a partial response, and replace under the hood all that's needed to make the snippets tests succeed when we get a final response. Also, increased the timeout so we always get a final response.
Closes#53887Closes#53891
Since a data frame analytics job may have associated docs
in the .ml-stats-* indices, when the job is deleted we
should delete those docs too.
Backport of #53933
Some clients have problems running this test as a numeric key is treated like an array index by default.
We can work around this by renaming the aggregation key to not be a numeric.
changes the output format of preview regarding deduced mappings and enhances
it to return all the details about auto-index creation. This allows the user
to customize the index creation. Using HLRC you can create a index request
from the output of the response.
backport #53572
Password changes are only allowed when the user is currently
authenticated by a realm (that permits the password to be changed)
and not when authenticated by a bearer token or an API key.
* Submit async search to work only with POST (#53368)
Currently the submit async search API can be called using both GET and POST at REST, but given that it submits a call and creates internal state, POST should be the only allowed method.
* Refine SearchProgressListener internal API (#53373)
The following cumulative improvements have been made:
- rename `onReduce` and `notifyReduce` to `onFinalReduce` and `notifyFinalReduce`
- add unit test for `SearchShard`
- on* methods in `SearchProgressListener` shouldn't need to be public as they should never be called directly, they only need to be overridden hence they can be made protected. They are actually called directly from a test which required some adapting, like making `AsyncSearchTask.Listener` class package private instead of private
- Instead of overriding `getProgressListener` in `AsyncSearchTask`, as it feels weird to override a getter method, added a specific method that allows to retrieve the Listener directly without needing to cast it. Made the getter and setter for the listener final in the base class.
- rename `SearchProgressListener#searchShards` methods to `buildSearchShards` and make it static given that it accesses no instance members
- make `SearchShard` and `SearchShardTask` classes final
* Move async search yaml tests to x-pack yaml test folder (#53537)
The yaml tests for async search currently sit in its qa folder. There is no reason though for them to live in a separate folder as they don't require particular setup. This commit moves them to the main folder together with the other x-pack yaml tests so that they will be run by the client test runners too.
* [DOCS] Add temporary redirect for async-search (#53454)
The following API spec files contain a link to a not-yet-created
async search docs page:
* [async_search.delete.json][0]
* [async_search.get.json][1]
* [async_search.submit.json][2]
The Elaticsearch-js client uses these spec files to create their docs.
This created a broken link in the Elaticsearch-js docs, which has broken
the docs build.
This PR adds a temporary redirect for the docs page. This redirect
should be removed when the actual API docs are added.
[0]: https://github.com/elastic/elasticsearch/blob/master/x-pack/plugin/src/test/resources/rest-api-spec/api/async_search.delete.json
[1]: https://github.com/elastic/elasticsearch/blob/master/x-pack/plugin/src/test/resources/rest-api-spec/api/async_search.get.json
[2]: https://github.com/elastic/elasticsearch/blob/master/x-pack/plugin/src/test/resources/rest-api-spec/api/async_search.submit.json
Co-authored-by: James Rodewig <james.rodewig@elastic.co>
This commit adjusts the _cat/indices and _cat/aliases APIs to allow
specifying indices options, so that these APIs can handle hidden
indices/aliases in the same way as other APIs.
Also adds the hidden option to the expand_wildcards parameter
in the YAML spec for every API that accepts it.
* New wildcard field optimised for wildcard queries (#49993)
Indexes values using size 3 ngrams and also stores the full original as a binary doc value.
Wildcard queries operate by using a cheap approximation query on the ngram field followed up by a more expensive verification query using an automaton on the binary doc values. Also supports aggregations and sorting.
This change introduces a new API in x-pack basic that allows to track the progress of a search.
Users can submit an asynchronous search through a new endpoint called `_async_search` that
works exactly the same as the `_search` endpoint but instead of blocking and returning the final response when available, it returns a response after a provided `wait_for_completion` time.
````
GET my_index_pattern*/_async_search?wait_for_completion=100ms
{
"aggs": {
"date_histogram": {
"field": "@timestamp",
"fixed_interval": "1h"
}
}
}
````
If after 100ms the final response is not available, a `partial_response` is included in the body:
````
{
"id": "9N3J1m4BgyzUDzqgC15b",
"version": 1,
"is_running": true,
"is_partial": true,
"response": {
"_shards": {
"total": 100,
"successful": 5,
"failed": 0
},
"total_hits": {
"value": 1653433,
"relation": "eq"
},
"aggs": {
...
}
}
}
````
The partial response contains the total number of requested shards, the number of shards that successfully returned and the number of shards that failed.
It also contains the total hits as well as partial aggregations computed from the successful shards.
To continue to monitor the progress of the search users can call the get `_async_search` API like the following:
````
GET _async_search/9N3J1m4BgyzUDzqgC15b/?wait_for_completion=100ms
````
That returns a new response that can contain the same partial response than the previous call if the search didn't progress, in such case the returned `version`
should be the same. If new partial results are available, the version is incremented and the `partial_response` contains the updated progress.
Finally if the response is fully available while or after waiting for completion, the `partial_response` is replaced by a `response` section that contains the usual _search response:
````
{
"id": "9N3J1m4BgyzUDzqgC15b",
"version": 10,
"is_running": false,
"response": {
"is_partial": false,
...
}
}
````
Asynchronous search are stored in a restricted index called `.async-search` if they survive (still running) after the initial submit. Each request has a keep alive that defaults to 5 days but this value can be changed/updated any time:
`````
GET my_index_pattern*/_async_search?wait_for_completion=100ms&keep_alive=10d
`````
The default can be changed when submitting the search, the example above raises the default value for the search to `10d`.
`````
GET _async_search/9N3J1m4BgyzUDzqgC15b/?wait_for_completion=100ms&keep_alive=10d
`````
The time to live for a specific search can be extended when getting the progress/result. In the example above we extend the keep alive to 10 more days.
A background service that runs only on the node that holds the first primary shard of the `async-search` index is responsible for deleting the expired results. It runs every hour but the expiration is also checked by running queries (if they take longer than the keep_alive) and when getting a result.
Like a normal `_search`, if the http channel that is used to submit a request is closed before getting a response, the search is automatically cancelled. Note that this behavior is only for the submit API, subsequent GET requests will not cancel if they are closed.
Asynchronous search are not persistent, if the coordinator node crashes or is restarted during the search, the asynchronous search will stop. To know if the search is still running or not the response contains a field called `is_running` that indicates if the task is up or not. It is the responsibility of the user to resume an asynchronous search that didn't reach a final response by re-submitting the query. However final responses and failures are persisted in a system index that allows
to retrieve a response even if the task finishes.
````
DELETE _async_search/9N3J1m4BgyzUDzqgC15b
````
The response is also not stored if the initial submit action returns a final response. This allows to not add any overhead to queries that completes within the initial `wait_for_completion`.
The `.async-search` index is a restricted index (should be migrated to a system index in +8.0) that is accessible only through the async search APIs. These APIs also ensure that only the user that submitted the initial query can retrieve or delete the running search. Note that admins/superusers would still be able to cancel the search task through the task manager like any other tasks.
Relates #49091
Co-authored-by: Luca Cavanna <javanna@users.noreply.github.com>
Prepares classification analysis to support more than just
two classes. It introduces a new parameter to the process config
which dictates the `num_classes` to the process. It also
changes the max classes limit to `30` provisionally.
Backport of #53539
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.
This is a partial implementation of an endpoint for anomaly
detector model memory estimation.
It is not complete, lacking docs, HLRC and sensible numbers
for many anomaly detector configurations. These will be
added in a followup PR in time for 7.7 feature freeze.
A skeleton endpoint is useful now because it allows work on
the UI side of the change to commence. The skeleton endpoint
handles the same cases that the old UI code used to handle,
and produces very similar estimates for these cases.
Backport of #53333
This field is a specialization of the `keyword` field for the case when all
documents have the same value. It typically performs more efficiently than
keywords at query time by figuring out whether all or none of the documents
match at rewrite time, like `term` queries on `_index`.
The name is up for discussion. I liked including `keyword` in it, so that we
still have room for a `singleton_numeric` in the future. However I'm unsure
whether to call it `singleton`, `constant` or something else, any opinions?
For this field there is a choice between
1. accepting values in `_source` when they are equal to the value configured
in mappings, but rejecting mapping updates
2. rejecting values in `_source` but then allowing updates to the value that
is configured in the mapping
This commit implements option 1, so that it is possible to reindex from/to an
index that has the field mapped as a keyword with no changes to the source.
Backport of #49713
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 PR moves the majority of the Watcher REST tests under
the Watcher x-pack plugin.
Specifically, moves the Watcher tests from:
x-pack/plugin/test
x-pack/qa/smoke-test-watcher
x-pack/qa/smoke-test-watcher-with-security
x-pack/qa/smoke-test-monitoring-with-watcher
to:
x-pack/plugin/watcher/qa/rest (/test and /qa/smoke-test-watcher)
x-pack/plugin/watcher/qa/with-security
x-pack/plugin/watcher/qa/with-monitoring
Additionally, this disables Watcher from the main
x-pack test cluster and consolidates the stop/start logic
for the tests listed.
No changes to the tests (beyond moving them) are included.
3rd party tests and doc tests (which also touch Watcher)
are not included in the changes here.
These tests didn't work properly when run against multi-shard indices.
The `_score` based sorting test expects fairly specific scores which
isn't going to happen with multiple shards so this disables multiple
shards for that test. The other tests were failing due to a fairly
sneaky race condition around `_bulk` and type inference. This fixes them
by always sending metric values as floating point numbers so
Elasticsearch always infers them to be doubles.
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)
This changes the tree validation code to ensure no node in the tree has a
feature index that is beyond the bounds of the feature_names array.
Specifically this handles the situation where the C++ emits a tree containing
a single node and an empty feature_names list. This is valid tree used to
centre the data in the ensemble but the validation code would reject this
as feature_names is empty. This meant a broken workflow as you cannot GET
the model and PUT it back
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>
ML mappings and index templates have so far been created
programmatically. While this had its merits due to static typing,
there is consensus it would be clear to maintain those in json files.
In addition, we are going to adding ILM policies to these indices
and the component for a plugin to register ILM policies is
`IndexTemplateRegistry`. It expects the templates to be in resource
json files.
For the above reasons this commit refactors ML mappings and index
templates into json resource files that are registered via
`MlIndexTemplateRegistry`.
Backport of #51765
Changes the misleading error message when attempting to open
a job while the "cluster.persistent_tasks.allocation.enable"
setting is set to "none" to a clearer message that names the
setting.
Closes#51956
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
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.
Not all clients support this e.g if the java high level rest client were
to map this it would look like `client.cat().ml().api()` which hinders
discoverability.
(cherry picked from commit 21cdabf09dc8305ce2f5e3b6cb193f67137d8bdb)
* [DOCS] Align with ILM API docs (#48705)
* [DOCS] Reconciled with Snapshot/Restore reorg
* [DOCS] Split off ILM overview to a separate topic. (#51287)
* [DOCS} Split off overview to a separate topic.
* [DOCS] Incorporated feedback from @jrodewig.
* [DOCS] Edit ILM GS tutorial (#51513)
* [DOCS] Edit ILM GS tutorial
* [DOCS] Incorporated review feedback from @andreidan.
* [DOCS] Removed test link & fixed anchor & title.
* Update docs/reference/ilm/getting-started-ilm.asciidoc
Co-Authored-By: James Rodewig <james.rodewig@elastic.co>
* Fixed glossary merge error.
Co-authored-by: James Rodewig <james.rodewig@elastic.co>
* REST: Test: Fix the `accept_enterprise` parameter for Get License API (#51527)
The Get License API specifies the `accept_enterprise` parameter as a `boolean`:
0ca5cb8cb6/x-pack/plugin/src/test/resources/rest-api-spec/api/license.get.json (L22-L27)
In the test, a `string` is passed however, which makes the test compilation fail in the Go client.
(cherry picked from commit e2a2169b3d44592057c143253bb56375ed3e4268)
* Fix the SQL API documentation in REST specification (#51534)
This patch fixes the SQL REST API documentation to conform to the current schema.
(cherry picked from commit c8b6a849852699883086a6ada42279f2f68d7e07)
* Fix the "slices" parameter for the Delete By Query API in the REST specification (#51535)
This patch updates the `type` parameter in the Delete By Query API: according to
[the documentation](https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-delete-by-query.html#docs-delete-by-query-slice),
it can be set to "auto", but the type in the documentation allows only numerical values.
This prevents people from setting the parameter to "auto" eg. in the Go client,
which generates source from the specification, and sets the corresponding Go
type as number.
The patch uses the `|` notation, which we have discussed previously for encoding
a "polymorphic" parameter like this.
Related: https://github.com/elastic/go-elasticsearch/issues/77
* Fix the Enrich API documentation in REST specification (#51528)
This patch fixes the REST API documentation for the Enrich APIs to conform to the current schema.
(cherry picked from commit 59f28f4f2feeba3f6d2f0b632410577eacb28121)
This adds logic to handle paging problems when the ID pattern + tags reference models stored as resources.
Most of the complexity comes from the issue where a model stored as a resource could be at the start, or the end of a page or when we are on the last page.
This commit creates a new index privilege named `maintenance`.
The privilege grants the following actions: `refresh`, `flush` (also synced-`flush`),
and `force-merge`. Previously the actions were only under the `manage` privilege
which in some situations was too permissive.
Co-authored-by: Amir H Movahed <arhd83@gmail.com>
This PR tries to address the intermittent vector test failures on 7.x by making
sure we create indices with one shard.
The fix is based on this theory as to what's happening:
* On 7.x, the default number of shards is 1, but in REST tests we randomly use
2 in order to cover the multiple shards case. In the failing test run, we use 2
shards and all documents end up on only one shard.
* During a search, the response from the empty shard doesn't produce
deprecation warnings because we never try to execute the script. If not all
shard responses contain the warning headers, then certain deprecation warnings
can be lost (due to the bug described in #33936).
Addresses #50716.
Relates to #50061.
This commit deprecates the creation of dot-prefixed index names (e.g.
.watches) unless they are either 1) a hidden index, or 2) registered by
a plugin that extends SystemIndexPlugin. This is the first step
towards more thorough protections for system indices.
This commit also modifies several plugins which use dot-prefixed indices
to register indices they own as system indices, and adds a plugin to
register .tasks as a system index.
* [ML][Inference] add tags url param to GET (#51330)
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.
Data frame analytics classification currently only supports 2 classes for the
dependent variable. We were checking that the field's cardinality is not higher
than 2 but we should also check it is not less than that as otherwise the process
fails.
Backport of #51232
This replaces the message we return for unknown queries with the standard
one that we use for unknown fields from `ObjectParser`. This is nice
because it includes "did you mean". One day we might convert parsing
queries to using object parser, but that looks complex. This change is
much smaller and seems useful.
Knowing about used analysis components and mapping types would be incredibly
useful in order to know which ones may be deprecated or should get more love.
Some field types also act as a proxy to know about feature usage of some APIs
like the `percolator` or `completion` fields types for percolation and the
completion suggester, respectively.
Check it out:
```
$ curl -u elastic:password -HContent-Type:application/json -XPOST localhost:9200/test/_update/foo?pretty -d'{
"dac": {}
}'
{
"error" : {
"root_cause" : [
{
"type" : "x_content_parse_exception",
"reason" : "[2:3] [UpdateRequest] unknown field [dac] did you mean [doc]?"
}
],
"type" : "x_content_parse_exception",
"reason" : "[2:3] [UpdateRequest] unknown field [dac] did you mean [doc]?"
},
"status" : 400
}
```
The tricky thing about implementing this is that x-content doesn't
depend on Lucene. So this works by creating an extension point for the
error message using SPI. Elasticsearch's server module provides the
"spell checking" implementation.
s
The enterprise license type must have "max_resource_units" and may not
have "max_nodes".
This change adds support for this new field, validation that the field
is present if-and-only-if the license is enterprise and bumps the
license version number to reflect the new field.
Includes a BWC layer to return "max_nodes: ${max_resource_units}" in
the GET license API.
Backport of: #50735
* [ML][Inference] PUT API (#50852)
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
* fixing backport
This commit removes validation logic of source and dest indices
for data frame analytics and replaces it with using the common
`SourceDestValidator` class which is already used by transforms.
This way the validations and their messages become consistent
while we reduce code.
This means that where these validations fail the error messages
will be slightly different for data frame analytics.
Backport of #50841
If a pipeline referenced by a transform does not exist, we should not allow the transform to be created.
We do allow the pipeline existence check to be skipped with defer_validations, but if the pipeline still does not exist on `_start`, the pipeline will fail to start.
relates: #50135
vector REST tests occasionally fail on 7.x because
we don't receive the expected response headers with deprecation warnings.
This happens as searchers were executed against all indices including
internal indices, whose shards did not produce expected warnings.
This PR ensures that searchers are executed only against expected
indices.
Closes#50716
This adds a new cluster privilege `monitor_snapshot` which is a restricted
version of `create_snapshot`, granting the same privileges to view
snapshot and repository info and status but not granting the actual
privilege to create a snapshot.
Co-authored-by: j-bean <anton.shuvaev91@gmail.com>
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
Backport of #50553
We are matching on the exact number of shards in this test, but may run into
snapshotting more than the single index created in it due to auto-created indices like
`.watcher`.
Fixed by making the test only take a snapshot of the single index used by this test.
Closes#50450
refactors source and dest validation, adds support for CCS, makes resolve work like reindex/search, allow aliased dest index with a single write index.
fixes#49988fixes#49851
relates #43201
This adds "enterprise" as an acceptable type for a license loaded
through the PUT _license API.
Internally an enterprise license is treated as having a "platinum"
operating mode.
The handling of License types was refactored to have a new explicit
"LicenseType" enum in addition to the existing "OperatingMode" enum.
By default (in 7.x) the GET license API will return "platinum" when an
enterprise license is active in order to be compatible with existing
consumers of that API.
A new "accept_enterprise" flag has been introduced to allow clients to
opt-in to receive the correct "enterprise" type.
Backport of: #49223
The `sparse_vector` REST tests occasionally fail on 7.x because we don't receive the expected response headers with deprecation warnings.
One theory as to what is happening is that there is an extra empty index present in addition to the test index. Since the search doesn't specify an index name, it hits both the test index and this extra empty index and shard responses from the extra index don't produce deprecation warnings. If not all shard responses contain the warning headers, then certain deprecation warnings can be lost (due to the bug described in #33936).
This PR tries to harden the `sparse_vector` tests by always specifying the index name during a search. This doesn't fix the root causes of the issue, but is good practice and can help avoid intermittent failures.
Addresses #49383.
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.
Backport of #49990
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
Backport of #49690
This commit adds a function in NodeClient that allows to track the progress
of a search request locally. Progress is tracked through a SearchProgressListener
that exposes query and fetch responses as well as partial and final reduces.
This new method can be used by modules/plugins inside a node in order to track the
progress of a local search request.
Relates #49091
The categorization job wizard in the ML UI will use this
information when showing the effect of the chosen categorization
analyzer on a sample of input.
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.
Backport of #49455
* [ML] ML Model Inference Ingest Processor (#49052)
* [ML][Inference] adds lazy model loader and inference (#47410)
This adds a couple of things:
- A model loader service that is accessible via transport calls. This service will load in models and cache them. They will stay loaded until a processor no longer references them
- A Model class and its first sub-class LocalModel. Used to cache model information and run inference.
- Transport action and handler for requests to infer against a local model
Related Feature PRs:
* [ML][Inference] Adjust inference configuration option API (#47812)
* [ML][Inference] adds logistic_regression output aggregator (#48075)
* [ML][Inference] Adding read/del trained models (#47882)
* [ML][Inference] Adding inference ingest processor (#47859)
* [ML][Inference] fixing classification inference for ensemble (#48463)
* [ML][Inference] Adding model memory estimations (#48323)
* [ML][Inference] adding more options to inference processor (#48545)
* [ML][Inference] handle string values better in feature extraction (#48584)
* [ML][Inference] Adding _stats endpoint for inference (#48492)
* [ML][Inference] add inference processors and trained models to usage (#47869)
* [ML][Inference] add new flag for optionally including model definition (#48718)
* [ML][Inference] adding license checks (#49056)
* [ML][Inference] Adding memory and compute estimates to inference (#48955)
* fixing version of indexed docs for model inference
We can't guarantee expected request failures if search request is across
many indexes, as if expected shards fail, some indexes may return 200.
closes#47743
Previously the functions accepted a doc values reference, whereas they now
accept the name of the vector field. Here's an example of how a vector function
was called before and after the change.
```
Before: cosineSimilarity(params.query_vector, doc['field'])
After: cosineSimilarity(params.query_vector, 'field')
```
This seems more intuitive, since we don't allow direct access to vector doc
values and the the meaning of `doc['field']` is unclear.
The PR makes the following changes (broken into distinct commits):
* Add new function signatures of the form `function(params.query_vector,
'field')` and deprecates the old ones. Because Painless doesn't allow two
methods with the same name and number of arguments, we allow a generic `Object`
to be passed in to the function and decide on the behavior through an
`instanceof` check.
* Refactor the class bindings so that the document field is passed to the
constructor instead of the instance method. This allows us to avoid retrieving
the vector doc values on every function invocation, which gives a tiny speed-up
in benchmarks.
Note that this PR adds new signatures for the sparse vector functions too, even
though sparse vectors are deprecated. It seemed simplest to understand (for both
us and users) to keep everything symmetric between dense and sparse vectors.
This commit changes the REST API spec slm.get_lifecycle's policy_id url part to be of type "list", in line with other REST API specs that accept a comma-separated list of values.
Closes#47765
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.
All internal searches (triggered by APIs) across the .security index
must be performed while "under the security origin". Otherwise,
the search is performed in the context of the caller which most
likely does not have privileges to search .security (hopefully).
This commit fixes this in the case of two methods in the
TokenService and corrects an overly done such context switch
in the ApiKeyService.
In addition, this makes all tests from the client/rest-high-level
module execute as an all mighty administrator,
but not a literal superuser.
Closes#47151
which is backport merge and adds a new ingest processor, named enrich processor,
that allows document being ingested to be enriched with data from other indices.
Besides a new enrich processor, this PR adds several APIs to manage an enrich policy.
An enrich policy is in charge of making the data from other indices available to the enrich processor in an efficient manner.
Related to #32789
This change adds:
- A new option, allow_lazy_open, to anomaly detection jobs
- A new option, allow_lazy_start, to data frame analytics jobs
Both work in the same way: they allow a job to be
opened/started even if no ML node exists that can
accommodate the job immediately. In this situation
the job waits in the opening/starting state until ML
node capacity is available. (The starting state for data
frame analytics jobs is new in this change.)
Additionally, the ML nightly maintenance tasks now
creates audit warnings for ML jobs that are unassigned.
This means that jobs that cannot be assigned to an ML
node for a very long time will show a yellow warning
triangle in the UI.
A final change is that it is now possible to close a job
that is not assigned to a node without using force.
This is because previously jobs that were open but
not assigned to a node were an aberration, whereas
after this change they'll be relatively common.
This PR adds the ability to run the enrich policy execution task in the background,
returning a task id instead of waiting for the completed operation.
Adds a new datafeed config option, max_empty_searches,
that tells a datafeed that has never found any data to stop
itself and close its associated job after a certain number
of real-time searches have returned no data.
Backport of #47922
This commit adds two APIs that allow to pause and resume
CCR auto-follower patterns:
// pause auto-follower
POST /_ccr/auto_follow/my_pattern/pause
// resume auto-follower
POST /_ccr/auto_follow/my_pattern/resume
The ability to pause and resume auto-follow patterns can be
useful in some situations, including the rolling upgrades of
cluster using a bi-directional cross-cluster replication scheme
(see #46665).
This commit adds a new active flag to the AutoFollowPattern
and adapts the AutoCoordinator and AutoFollower classes so
that it stops to fetch remote's cluster state when all auto-follow
patterns associate to the remote cluster are paused.
When an auto-follower is paused, remote indices that match the
pattern are just ignored: they are not added to the pattern's
followed indices uids list that is maintained in the local cluster
state. This way, when the auto-follow pattern is resumed the
indices created in the remote cluster in the meantime will be
picked up again and added as new following indices. Indices
created and then deleted in the remote cluster will be ignored
as they won't be seen at all by the auto-follower pattern at
resume time.
Backport of #47510 for 7.x
* [ML][Analytics] fix bug where regression deleted early does not delete state (#47885)
* [ML][Analytics] fix bug where regression deleted early does not delete state
* Fixing ml with security test failure
* fixing for older java
Batch transforms automatically stop after all data has processed, therefore tests can not reliable test the state. This change rewrites tests to remove the unreliable tests or use continuous transforms instead as they do not auto-stop.
fixes#47441
Adds the following parameters to `outlier_detection`:
- `compute_feature_influence` (boolean): whether to compute or not
feature influence scores
- `outlier_fraction` (double): the proportion of the data set assumed
to be outlying prior to running outlier detection
- `standardization_enabled` (boolean): whether to apply standardization
to the feature values
Backport of #47600
Use case:
User with `create_doc` index privilege will be allowed to only index new documents
either via Index API or Bulk API.
There are two cases that we need to think:
- **User indexing a new document without specifying an Id.**
For this ES auto generates an Id and now ES version 7.5.0 onwards defaults to `op_type` `create` we just need to authorize on the `op_type`.
- **User indexing a new document with an Id.**
This is problematic as we do not know whether a document with Id exists or not.
If the `op_type` is `create` then we can assume the user is trying to add a document, if it exists it is going to throw an error from the index engine.
Given these both cases, we can safely authorize based on the `op_type` value. If the value is `create` then the user with `create_doc` privilege is authorized to index new documents.
In the `AuthorizationService` when authorizing a bulk request, we check the implied action.
This code changes that to append the `:op_type/index` or `:op_type/create`
to indicate the implied index action.
* Add API to execute SLM retention on-demand (#47405)
This is a backport of #47405
This commit adds the `/_slm/_execute_retention` API endpoint. This
endpoint kicks off SLM retention and then returns immediately.
This in particular allows us to run retention without scheduling it
(for entirely manual invocation) or perform a one-off cleanup.
This commit also includes HLRC for the new API, and fixes an issue
in SLMSnapshotBlockingIntegTests where retention invoked prior to the
test completing could resurrect an index the internal test cluster
cleanup had already deleted.
Resolves#46508
Relates to #43663
When we added support for wildcard application names, we started to build
the prefix query along with the term query but we used 'filter' clause
instead of 'should', so this would not fetch the correct application
privilege descriptor thereby failing the _has_privilege checks.
This commit changes the clause to use should and with minimum_should_match
as 1.
Backport of #45794 to 7.x. Convert most `awaitBusy` calls to
`assertBusy`, and use asserts where possible. Follows on from #28548 by
@liketic.
There were a small number of places where it didn't make sense to me to
call `assertBusy`, so I kept the existing calls but renamed the method to
`waitUntil`. This was partly to better reflect its usage, and partly so
that anyone trying to add a new call to awaitBusy wouldn't be able to find
it.
I also didn't change the usage in `TransportStopRollupAction` as the
comments state that the local awaitBusy method is a temporary
copy-and-paste.
Other changes:
* Rework `waitForDocs` to scale its timeout. Instead of calling
`assertBusy` in a loop, work out a reasonable overall timeout and await
just once.
* Some tests failed after switching to `assertBusy` and had to be fixed.
* Correct the expect templates in AbstractUpgradeTestCase. The ES
Security team confirmed that they don't use templates any more, so
remove this from the expected templates. Also rewrite how the setup
code checks for templates, in order to give more information.
* Remove an expected ML template from XPackRestTestConstants The ML team
advised that the ML tests shouldn't be waiting for any
`.ml-notifications*` templates, since such checks should happen in the
production code instead.
* Also rework the template checking code in `XPackRestTestHelper` to give
more helpful failure messages.
* Fix issue in `DataFrameSurvivesUpgradeIT` when upgrading from < 7.4
David Roberts
markharwood
Hendrik Muhs
Tim Vernum
Luca Cavanna
Dimitris Athanasiou
Benjamin Trent
Przemysław Witek
Ioannis Kakavas
Gordon Brown
Jim Ferenczi
Tom Veasey
Adrien Grand
Nik Everett
Lisa Cawley
István Zoltán Szabó
Jake Landis
Yang Wang
Russ Cam
Ryan Ernst
David Kyle
Henning Andersen
Marios Trivyzas
Julie Tibshirani
James Rodewig
Igor Motov
Ignacio Vera
Jason Tedor
Martijn Laarman
debadair
Jonathan Budzenski
Karel Minarik
Albert Zaharovits
Aleksandr Maus
Tomas Della Vedova
Christoph Büscher
Mayya Sharipova
Armin Braun
Stuart Cam
Yogesh Gaikwad
Albert Zaharovits
Martijn van Groningen
James Baiera
Tanguy Leroux
Lee Hinman
Rory Hunter