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 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.
Elastic cloud has a concept of a cloud Id. This Id is a base64 encoded
url, split up into a few parts. This commit allows the user to pass in a
cloud id now, which is translated to a HttpHost that is defined by the
encoded parts therein.
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
Currently there are two issues with serializing BulkByScrollResponse.
First, when deserializing from XContent, indexing exceptions and search
exceptions are switched. Additionally, search exceptions do no retain
the appropriate RestStatus code, so you must evaluate the status code
from the exception. However, the exception class is not always correctly
retained when serialized.
This commit adds tests in the failure case. Additionally, fixes the
swapping of failure types and adds the rest status code to the search
failure.
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.
This commit adds support to retrieve all API keys if the authenticated
user is authorized to do so.
This removes the restriction of specifying one of the
parameters (like id, name, username and/or realm name)
when the `owner` is set to `false`.
Closes#46887
* Remove eclipse conditionals
We used to have some meta projects with a `-test` prefix because
historically eclipse could not distinguish between test and main
source-sets and could only use a single classpath.
This is no longer the case for the past few Eclipse versions.
This PR adds the necessary configuration to correctly categorize source
folders and libraries.
With this change eclipse can import projects, and the visibility rules
are correct e.x. auto compete doesn't offer classes from test code or
`testCompile` dependencies when editing classes in `main`.
Unfortunately the cyclic dependency detection in Eclipse doesn't seem to
take the difference between test and non test source sets into account,
but since we are checking this in Gradle anyhow, it's safe to set to
`warning` in the settings. Unfortunately there is no setting to ignore
it.
This might cause problems when building since Eclipse will probably not
know the right order to build things in so more wirk might be necesarry.
* 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
* [ML][Inference] adding .ml-inference* index and storage (#47267)
* [ML][Inference] adding .ml-inference* index and storage
* Addressing PR comments
* Allowing null definition, adding validation tests for model config
* fixing line length
* adjusting for backport
Currently the policy config is placed directly in the json object
of the toplevel `policies` array field. For example:
```
{
"policies": [
{
"match": {
"name" : "my-policy",
"indices" : ["users"],
"match_field" : "email",
"enrich_fields" : [
"first_name",
"last_name",
"city",
"zip",
"state"
]
}
}
]
}
```
This change adds a `config` field in each policy json object:
```
{
"policies": [
{
"config": {
"match": {
"name" : "my-policy",
"indices" : ["users"],
"match_field" : "email",
"enrich_fields" : [
"first_name",
"last_name",
"city",
"zip",
"state"
]
}
}
}
]
}
```
This allows us in the future to add other information about policies
in the get policy api response.
The UI will consume this API to build an overview of all policies.
The UI may in the future include additional information about a policy
and the plan is to include that in the get policy api, so that this
information can be gathered in a single api call.
An example of the information that is likely to be added is:
* Last policy execution time
* The status of a policy (executing, executed, unexecuted)
* Information about the last failure if exists
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
In the current implementation, the validation of the role query
occurs at runtime when the query is being executed.
This commit adds validation for the role query when creating a role
but not for the template query as we do not have the runtime
information required for evaluating the template query (eg. authenticated user's
information). This is similar to the scripts that we
store but do not evaluate or parse if they are valid queries or not.
For validation, the query is evaluated (if not a template), parsed to build the
QueryBuilder and verify if the query type is allowed.
Closes#34252
This commit adds support for POST requests to the SLM `_execute` API,
because POST is a more appropriate HTTP verb for this action as it is
not idempotent. The docs are also changed to favor POST over PUT,
although PUT is not removed or officially deprecated.
Using arrays of objects with embedded IDs is preferred for new APIs over
using entity IDs as JSON keys. This commit changes the SLM stats API to
use the preferred format.
* [ML][Inference] Feature pre-processing objects and functions (#46777)
To support inference on pre-trained machine learning models, some basic feature encoding will be necessary. I am using a named object serialization approach so new encodings/pre-processing steps could be added in the future.
This PR lays down the ground work for 3 basic encodings:
* HotOne
* Target Mean
* Frequency
More feature encodings or pre-processings could be added in the future:
* Handling missing columns
* Standardization
* Label encoding
* etc....
* fixing compilation for namedxcontent tests
The HLRC has a method for reindex, that allows to trigger an async reindex by running RestHighLevelClient.submitReindexTask and RestHighLevelClient.reindex. The delete by query however only has an RestHighLevelClient.deleteByQuery method (and its async counterpart), but no RestHighLevelClient.submitDeleteByQueryTask. So add RestHighLevelClient.submitDeleteByQueryTask
Closes#46395
Currently the CountRequest accepts a search source builder, while the
RestCountAction only accepts a top level query object. This can lead
to confusion if another element (e.g. aggregations) is specified,
because that will be ignored on the server side in RestCountAction.
By deprecating the current setter & constructor that accept a
SearchSourceBuilder and adding replacement that accepts a QueryBuilder
it is clear what the count api can handle from HLRC side.
Follow up from #46829
* addSnapshotLifecyclePolicy drop version assertion
This drops the assertion on the policy version (which was pinned to 1L)
as we want to execute both put policy apis (sync and async) for
documentation purposes. This will sometimes (depending on the async
call) yield a version of 2L. Waiting for the async call to always
complete could be an option but the test is already rather slow and it's
a bit of an overkill as we're already verifying the policy was created.
(cherry picked from commit af4864c39129bcdbf98d00223f445346a62075e4)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
Martijn van Groningen
David Roberts
Gordon Brown
Michael Basnight
Tanguy Leroux
Yogesh Gaikwad
Przemysław Witek
Hendrik Muhs
Tim Brooks
Benjamin Trent
Dimitris Athanasiou
Alpar Torok
Lee Hinman
Yannick Welsch
Rory Hunter
maidoo
Lisa Cawley
Andrei Dan
James Rodewig