Backport of #55548
Adds equivalence for keyword field to the wildcard field. Regex, fuzzy, wildcard and prefix queries are all supported.
All queries use an approximation query backed by an automaton-based verification queries.
Closes#54275
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.
* [Transform] add support for terms agg in transforms (#56696)
This adds support for `terms` and `rare_terms` aggs in transforms.
The default behavior is that the results are collapsed in the following manner:
`<AGG_NAME>.<BUCKET_NAME>.<SUBAGGS...>...`
Or if no sub aggs exist
`<AGG_NAME>.<BUCKET_NAME>.<_doc_count>`
The mapping is also defined as `flattened` by default. This is to avoid field explosion while still providing (limited) search and aggregation capabilities.
This aggregation will perform normalizations of metrics
for a given series of data in the form of bucket values.
The aggregations supports the following normalizations
- rescale 0-1
- rescale 0-100
- percentage of sum
- mean normalization
- z-score normalization
- softmax normalization
To specify which normalization is to be used, it can be specified
in the normalize agg's `normalizer` field.
For example:
```
{
"normalize": {
"buckets_path": <>,
"normalizer": "percent"
}
}
```
This commit allows the JSON schema's documentation.url property to have a null value.
This can useful for cases where a feature is under development, and does not have
documentation published yet.
This commit also adds a documentation.url for two ml resources.
Backport: #55377
This commit adds the ability to auto create data streams using index templates v2.
Index templates (v2) now have a data_steam field that includes a timestamp field,
if provided and index name matches with that template then a data stream
(plus first backing index) is auto created.
Relates to #53100
Backport of: #56569
A data stream test, which tests data stream resolvability in xpack apis failed in release builds.
A invocation of a searchable snapshot api failed, because the corresponding feature flag
wasn't enabled for xpack rest tests.
Closes#56531
Similar to what the moving function aggregation does, except merging windows of percentiles
sketches together instead of cumulatively merging final metrics
Change TransportBroadcastByNodeAction and TransportBroadcastReplicationAction
to be able to resolve data streams by default. Implementations can change this ability.
This change allows to following APIs to resolve data streams: flush,
refresh (already supported data streams), force merge, clear indices cache,
indices stats (already supported data streams), segments, upgrade stats,
upgrade, validate query, searchable snapshots stats, clear searchable snapshots cache and
reload analyzers APIs.
Relates to #53100
Transforms should propagate up the search execution exception if one is returned when it does the test query.
this allows transforms to return a `4xx` when the aggs are malformed but parseable.
closes https://github.com/elastic/elasticsearch/issues/55994
This PR implements the following changes to make ML model snapshot
retention more flexible in advance of adding a UI for the feature in
an upcoming release.
- The default for `model_snapshot_retention_days` for new jobs is now
10 instead of 1
- There is a new job setting, `daily_model_snapshot_retention_after_days`,
that defaults to 1 for new jobs and `model_snapshot_retention_days`
for pre-7.8 jobs
- For days that are older than `model_snapshot_retention_days`, all
model snapshots are deleted as before
- For days that are in between `daily_model_snapshot_retention_after_days`
and `model_snapshot_retention_days` all but the first model snapshot
for that day are deleted
- The `retain` setting of model snapshots is still respected to allow
selected model snapshots to be retained indefinitely
Backport of #56125
As of elastic/ml-cpp#1179, the analytics process reports phases
depending on the analysis type. This commit adjusts the phases
of current analyses from `analyzing` to the following:
- outlier_detection: [`computing_outlier`]
- regression/classification: [`feature_selection`, `coarse_parameter_search`, `fine_tuning_parameters`, `final_training`]
Backport of #56107
Backport of #55858 to 7.x branch.
Currently the TransportBulkAction detects whether an index is missing and
then decides whether it should be auto created. The coordination of the
index creation also happens in the TransportBulkAction on the coordinating node.
This change adds a new transport action that the TransportBulkAction delegates to
if missing indices need to be created. The reasons for this change:
* Auto creation of data streams can't occur on the coordinating node.
Based on the index template (v2) either a regular index or a data stream should be created.
However if the coordinating node is slow in processing cluster state updates then it may be
unaware of the existence of certain index templates, which then can load to the
TransportBulkAction creating an index instead of a data stream. Therefor the coordination of
creating an index or data stream should occur on the master node. See #55377
* From a security perspective it is useful to know whether index creation originates from the
create index api or from auto creating a new index via the bulk or index api. For example
a user would be allowed to auto create an index, but not to use the create index api. The
auto create action will allow security to distinguish these two different patterns of
index creation.
This change adds the following new transport actions:
AutoCreateAction, the TransportBulkAction redirects to this action and this action will actually create the index (instead of the TransportCreateIndexAction). Later via #55377, can improve the AutoCreateAction to also determine whether an index or data stream should be created.
The create_index index privilege is also modified, so that if this permission is granted then a user is also allowed to auto create indices. This change does not yet add an auto_create index privilege. A future change can introduce this new index privilege or modify an existing index / write index privilege.
Relates to #53100
Backports #55933 to 7.x
Implements value_count and avg aggregations over Histogram fields as discussed in #53285
- value_count returns the sum of all counts array of the histograms
- avg computes a weighted average of the values array of the histogram by multiplying each value with its associated element in the counts array
* Emit deprecation warning if multiple v1 templates match with a new index (#55558)
* Emit deprecation warning if multiple v1 templates match with a new index
* DEPRECATION_LOGGER rename
Implements Sum aggregation over Histogram fields by summing the value of each bucket multiplied by their count as requested in #53285
Backports #55681 to 7.x
We were previously checking at least one supported field existed
when the _explain API was called. However, in the case of analyses
with required fields (e.g. regression) we were not accounting that
the dependent variable is not a feature and thus if the source index
only contains the dependent variable field there are no features to
train a model on.
This commit adds a validation that at least one feature is available
for analysis. Note that we also move that validation away from
`ExtractedFieldsDetector` and the _explain API and straight into
the _start API. The reason for doing this is to allow the user to use
the _explain API in order to understand why they would be seeing an
error like this one.
For example, the user might be using an index that has fields but
they are of unsupported types. If they start the job and get
an error that there are no features, they will wonder why that is.
Calling the _explain API will show them that all their fields are
unsupported. If the _explain API was failing instead, there would
be no way for the user to understand why all those fields are
ignored.
Closes#55593
Backport of #55876
The failed_category_count statistic records the number of times
categorization wanted to create a new category but couldn't
because the job had reached its model_memory_limit.
Backport of #55716
The ML info endpoint returns the max_model_memory_limit setting
if one is configured. However, it is still possible to create
a job that cannot run anywhere in the current cluster because
no node in the cluster has enough memory to accommodate it.
This change adds an extra piece of information,
limits.effective_max_model_memory_limit, to the ML info
response that returns the biggest model memory limit that could
be run in the current cluster assuming no other jobs were
running.
The idea is that the ML UI will be able to warn users who try to
create jobs with higher model memory limits that their jobs will
not be able to start unless they add a bigger ML node to their
cluster.
Backport of #55529
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.
Backport of #55473
This commit fixes our behavior regarding the responses we
return in various cases for the use of token related APIs.
More concretely:
- In the Get Token API with the `refresh` grant, when an invalid
(already deleted, malformed, unknown) refresh token is used in the
body of the request, we respond with `400` HTTP status code
and an `error_description` header with the message "could not
refresh the requested token".
Previously we would return erroneously return a `401` with "token
malformed" message.
- In the Invalidate Token API, when using an invalid (already
deleted, malformed, unknown) access or refresh token, we respond
with `404` and a body that shows that no tokens were invalidated:
```
{
"invalidated_tokens":0,
"previously_invalidated_tokens":0,
"error_count":0
}
```
The previous behavior would be to erroneously return
a `400` or `401` ( depending on the case ).
- In the Invalidate Token API, when the tokens index doesn't
exist or is closed, we return `400` because we assume this is
a user issue either because they tried to invalidate a token
when there is no tokens index yet ( i.e. no tokens have
been created yet or the tokens index has been deleted ) or the
index is closed.
- In the Invalidate Token API, when the tokens index is
unavailable, we return a `503` status code because
we want to signal to the caller of the API that the token they
tried to invalidate was not invalidated and we can't be sure
if it is still valid or not, and that they should try the request
again.
Resolves: #53323
Provides basic repository-level stats that will allow us to get some insight into how many
requests are actually being made by the underlying SDK. Currently only tracks GET and LIST
calls for S3 repositories. Most of the code is unfortunately boiler plate to add a new endpoint
that will help us better understand some of the low-level dynamics of searchable snapshots.
Adds support for filters to T-Test aggregation. The filters can be used to
select populations based on some criteria and use values from the same or
different fields.
Closes#53692
This is a backport of #54803 for 7.x.
This pull request cherry picks the squashed commit from #54803 with the additional commits:
6f50c92 which adjusts master code to 7.x
a114549 to mute a failing ILM test (#54818)
48cbca1 and 50186b2 that cleans up and fixes the previous test
aae12bb that adds a missing feature flag (#54861)
6f330e3 that adds missing serialization bits (#54864)
bf72c02 that adjust the version in YAML tests
a51955f that adds some plumbing for the transport client used in integration tests
Co-authored-by: David Turner <david.turner@elastic.co>
Co-authored-by: Yannick Welsch <yannick@welsch.lu>
Co-authored-by: Lee Hinman <dakrone@users.noreply.github.com>
Co-authored-by: Andrei Dan <andrei.dan@elastic.co>
* [ML] add new inference_config field to trained model config (#54421)
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.
* fixing for backport
* Rename cat.transform => cat.transforms
To match the url.
We typically prefer singular url nouns but _cat tends to use plural and
this API does in fact uses `/_cat/transforms`
* also rename the api in the spec and tests
(cherry picked from commit c495d220ac8fedba7f70f82387cd6d6a672b8b14)
This commit updates the rest API specs to validate against a
JSON schema for the specifications. Most updates are to add
a description, whilst others fix typos and unify conventions
e.g. deprecations, descriptions, urls starting with /. The schema
conforms to draft-07 JSON schema.
(cherry picked from commit da37e01d32f9764c3937736ef0c7d3ab40af9a77)
This commit is the first in a series of commits that introduces
autoscaling policies, and APIs for working with them. For now, we
introduce the basic infrastructure, and a single API for putting an
autoscaling policy. We will follow in rapid succession with APIs for
getting, and deleting autoscaling policies.
This is a simple naming change PR, to fix the fact that "metadata" is a
single English word, and for too long we have not followed general
naming conventions for it. We are also not consistent about it, for
example, METADATA instead of META_DATA if we were trying to be
consistent with MetaData (although METADATA is correct when considered
in the context of "metadata"). This was a simple find and replace across
the code base, only taking a few minutes to fix this naming issue
forever.
This PR:
1. Fixes the bug where a cardinality estimate of zero could cause
a 500 status
2. Adds tests for that scenario and a few others
3. Adds sensible estimates for the cases that were previously TODO
Backport of #54462
Fixing the naming of the HLRC values to match the ToXContent field names (i.e. the field names returned from an API call).
Also fixes the names in the _cat API as well.
closes#53946
This commit populates the _stats API response with sensible "empty"
`data_counts` and `memory_usage` objects when the job itself
has not started reporting them.
Backport of #54210
When get filters is called without setting the `size`
paramter only up to 10 filters are returned. However,
100 filters should be returned. This commit fixes this
and adds an integ test to guard it.
It seems this was accidentally broken in #39976.
Closes#54206
Backport of #54207
This commit renames wait_for_completion to wait_for_completion_timeout in submit async search and get async search.
Also it renames clean_on_completion to keep_on_completion and turns around its behaviour.
Closes#54069
* transform.cat should live in the cat namespace.
Similarly to to ml cat API's also living in the `cat` namespace.
Clients treat the `cat` namespace differently then other API's (return
types, content types). This introduces an exception to this rule.
* rename the specification file as well
(cherry picked from commit 0a98904b1a73a30bbaebc32bd16a238c8d03c329)
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
markharwood
Benjamin Trent
Tal Levy
Jake Landis
Martijn van Groningen
Ignacio Vera
David Roberts
Dimitris Athanasiou
Christos Soulios
Przemko Robakowski
Yang Wang
James Rodewig
Ioannis Kakavas
Igor Motov
Yannick Welsch
Przemysław Witek
Tanguy Leroux
Jason Tedor
Martijn Laarman
Russ Cam
Christoph Büscher
David Turner
Luca Cavanna
Hendrik Muhs
Tim Vernum
Gordon Brown
Jim Ferenczi
Tom Veasey
Adrien Grand
Nik Everett
Lisa Cawley
István Zoltán Szabó
Ryan Ernst
David Kyle