We needlessly send documents to be persisted. If there are no stats added, then we should not attempt to persist them.
Also, this PR fixes the race condition that caused issue: https://github.com/elastic/elasticsearch/issues/54786
* [ML] Start gathering and storing inference stats (#53429)
This PR enables stats on inference to be gathered and stored in the `.ml-stats-*` indices.
Each node + model_id will have its own running stats document and these will later be summed together when returning _stats to the user.
`.ml-stats-*` is ILM managed (when possible). So, at any point the underlying index could change. This means that a stats document that is read in and then later updated will actually be a new doc in a new index. This complicates matters as this means that having a running knowledge of seq_no and primary_term is complicated and almost impossible. This is because we don't know the latest index name.
We should also strive for throughput, as this code sits in the middle of an ingest pipeline (or even a query).
This change makes sure that all internal client requests spawned by the
data frame analytics persistent task executor and that use the end user
security credentials, have the parent task id assigned. The objective here
is to permit auditing (as well as tracking for debugging purposes) of all
the end-user requests executed on its behalf by persistent tasks.
Because data frame analytics taks already implements graceful shutdown
of child tasks, this change does not interfere with it by opting out of
the persistent task cancellation of child tasks.
Relates #54943#52314
We recently cleaned up the use of the word "metadata" across the
codebase. Even more additional uses have trickled in, likely from
in-progress work. This commit cleans up these last few additional
instances.
Relates #54519
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>
This change ensures that the AsyncSearchUser is correctly (de)serialized when
an action executed by this user is sent to a remote node internally (via transport client).
Adds t_test metric aggregation that can perform paired and unpaired two-sample
t-tests. In this PR support for filters in unpaired is still missing. It will
be added in a follow-up PR.
Relates to #53692
Previously, the id of the `GetDataFrameAnalyticsStatsAction.Request`
could be `null` which caused NPE on serialization as `writeString`
is used (it doesn't accept null values).
This commit ensures the id is never null.
Closes#54807
Backport of #54808
This changes a SamlServiceProvider to have a function that maps
from an "action-name" to set of role-names instead of a Map that does
so.
The on-disk representation of this mapping is a set of Java Regexp
Patterns, for which the first matching group is the role name.
For example "sso:(\w+)" would map any action that started with "sso:"
to the corresponding role name (e.g. "sso:superuser" -> "superuser").
Backport of: #54440
Force stopping a failed job used to work but it
now puts the job in `stopping` state and hangs.
In addition, force stopping a `stopping` job is
not handled.
This commit addresses those issues with force
stopping data frame analytics. It inlines the
approach with that followed for anomaly detection
jobs.
Backport of #54650
In #33933 we disallowed changing the `enabled` parameter in object mappings.
However, the fix didn't cover the root object mapper. This PR adjusts the change
to also include the root mapper and clarifies the error message.
This adds training_percent parameter to the analytics process for Classification and Regression. This parameter is then used to give more accurate memory estimations.
See native side pr: elastic/ml-cpp#1111
* [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
* [ML] add num_matches and preferred_to_categories to category defintion objects (#54214)
This adds two new fields to category definitions.
- `num_matches` indicating how many documents have been seen by this category
- `preferred_to_categories` indicating which other categories this particular category supersedes when messages are categorized.
These fields are only guaranteed to be up to date after a `_flush` or `_close`
native change: https://github.com/elastic/ml-cpp/pull/1062
* adjusting for backport
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 follow up to a previous commit that renamed MetaData to
Metadata in all of the places. In that commit in master, we renamed
META_DATA to METADATA, but lost this on the backport. This commit
addresses that.
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.
The allowTrial flag is always true, since trial licenses act as though
everything is licensed. This commit removes the allowTrial flag in
license checking helper methods.
Pipeline aggregations like `stats_bucket`, `sum_bucket`, and
`percentiles_bucket` only operate on buckets that have multiple buckets.
This adds support for those aggregations to `geo_distance`, `ip_range`,
`auto_date_histogram`, and `rare_terms`.
This all happened because we used a marker interface to mark compatible
aggs, `MultiBucketAggregationBuilder` and it was fairly easy to forget
to implement the interface.
This replaces the marker interface with an abstract method in
`AggregationBuilder`, `bucketCardinality` which makes you return `NONE`,
`ONE`, or `MANY`. The `bucket` aggregations can check for `MANY`. At
this point `ONE` and `NONE` amount to about the same thing, but I
suspect that'll be a useful distinction when validating bucket sorts.
Closes#53215
Backport of #53982
In order to prepare the `AliasOrIndex` abstraction for the introduction of data streams,
the abstraction needs to be made more flexible, because currently it really can be only
an alias or an index.
* Renamed `AliasOrIndex` to `IndexAbstraction`.
* Introduced a `IndexAbstraction.Type` enum to indicate what a `IndexAbstraction` instance is.
* Replaced the `isAlias()` method that returns a boolean with the `getType()` method that returns the new Type enum.
* Moved `getWriteIndex()` up from the `IndexAbstraction.Alias` to the `IndexAbstraction` interface.
* Moved `getAliasName()` up from the `IndexAbstraction.Alias` to the `IndexAbstraction` interface and renamed it to `getName()`.
* Removed unnecessary casting to `IndexAbstraction.Alias` by just checking the `getType()` method.
Relates to #53100
* Add REST APIs for IndexTemplateV2Metadata CRUD (#54039)
* Add REST APIs for IndexTemplateV2Metadata CRUD
This commit adds the get/put/delete APIs for interacting with the now v2 versions of index
templates.
These APIs are behind the existing `es.itv2_feature_flag_registered` system property feature flag.
Relates to #53101
* Add exceptions for HLRC tests
* Add skips for 7.x versions
* Use index_template instead of template_v2 in action names
* Add test for MetaDataIndexTemplateService.addIndexTemplateV2
* Move removal to static method and add test
* Add unit tests for request classes (implement hashCode & equals)
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
* Fix compilation
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
optimize transform for group_by on date_histogram by injecting an additional range query. This limits the number of search and index requests and avoids unnecessary updates. Only recent buckets get re-written.
fixes#54254
This commit causes negative TimeValues, other than -1 which is sometimes used as
a sentinel value, to be rejected during parsing.
Also introduces a hack to allow ILM to load policies which were written to the
cluster state with a negative min_age, treating those values as 0, which should
match the behavior of prior versions.
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
Xpack license state contains a helper method to determine whether
security is disabled due to license level defaults. Most code needs to
know whether security is enabled, not disabled, but this method exists
so that the security being explicitly disabled can be distinguished from
licence level defaulting to disabled. However, in the case that security
is explicitly disabled, the handlers in question are never registered,
so security is implicitly not disabled explicitly, and thus we can share
a single method to know whether licensing is enabled.
* Required for elastic/kibana#50757.
Allows the kibana user to collect APM telemetry in a background task.
* removed unnecessary priviledges on `.ml-anomalies-*` for the `kibana_system` reserved role
This change merges the "feature-internal-idp" branch into Elasticsearch.
This introduces a small identity-provider plugin as a child of the x-pack module.
This allows ES to act as a SAML IdP, for users who are authenticated against the
Elasticsearch cluster.
This feature is intended for internal use within Elastic Cloud environments
and is not supported for any other use case. It falls under an enterprise license tier.
The IdP is disabled by default.
Co-authored-by: Ioannis Kakavas <ioannis@elastic.co>
Co-authored-by: Tim Vernum <tim.vernum@elastic.co>
As classification now works for multiple classes, randomly
picking training/test data frame rows is not good enough.
This commit introduces a stratified cross validation splitter
that maintains the proportion of the each class in the dataset
in the sample that is used for training the model.
Backport of #54087
Fixes an issue where the elasticsearch-node command-line tools would not work correctly
because PersistentTasksCustomMetaData contains named XContent from plugins. This PR
makes it so that the parsing for all custom metadata is skipped, even if the core system would
know how to handle it.
Closes#53549
Submit async search forces pre_filter_shard_size for the underlying search that it creates.
With this commit we also prevent users from overriding such default as part of request validation.
This commit adds an explicit cancellation of the search task if
the initial async search submit task is cancelled (connection closed by the user).
This was previously done through the cancellation of the parent task but we don't
handle grand-children cancellation yet so we have to manually cancel the search task
in order to ensure that shard actions are cancelled too.
This change can be considered as a workaround until #50990 is fixed.
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
Role names are now compiled from role templates before role mapping is saved.
This serves as validation for role templates to prevent malformed and invalid scripts
to be persisted, which could later break authentication.
Resolves: #48773
This commit instruments data frame analytics
with stats for the data that are being analyzed.
In particular, we count training docs, test docs,
and skipped docs.
In order to account docs with missing values as skipped
docs for analyses that do not support missing values,
this commit changes the extractor so that it only ignores
docs with missing values when it collects the data summary,
which is used to estimate memory usage.
Backport of #53998
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.
Adds multi-class feature importance calculation.
Feature importance objects are now mapped as follows
(logistic) Regression:
```
{
"feature_name": "feature_0",
"importance": -1.3
}
```
Multi-class [class names are `foo`, `bar`, `baz`]
```
{
“feature_name”: “feature_0”,
“importance”: 2.0, // sum(abs()) of class importances
“foo”: 1.0,
“bar”: 0.5,
“baz”: -0.5
},
```
For users to get the full benefit of aggregating and searching for feature importance, they should update their index mapping as follows (before turning this option on in their pipelines)
```
"ml.inference.feature_importance": {
"type": "nested",
"dynamic": true,
"properties": {
"feature_name": {
"type": "keyword"
},
"importance": {
"type": "double"
}
}
}
```
The mapping field name is as follows
`ml.<inference.target_field>.<inference.tag>.feature_importance`
if `inference.tag` is not provided in the processor definition, it is not part of the field path.
`inference.target_field` is defaulted to `ml.inference`.
//cc @lcawl ^ Where should we document this?
If this makes it in for 7.7, there shouldn't be any feature_importance at inference BWC worries as 7.7 is the first version to have it.
