This change adds a dynamic cluster setting named `indices.id_field_data.enabled`.
When set to `false` any attempt to load the fielddata for the `_id` field will fail
with an exception. The default value in this change is set to `false` in order to prevent
fielddata usage on this field for future versions but it will be set to `true` when backporting
to 7x. When the setting is set to true (manually or by default in 7x) the loading will also issue
a deprecation warning since we want to disallow fielddata entirely when https://github.com/elastic/elasticsearch/issues/26472
is implemented.
Closes#43599
This commit back ports three commits related to enabling the simple
connection strategy.
Allow simple connection strategy to be configured (#49066)
Currently the simple connection strategy only exists in the code. It
cannot be configured. This commit moves in the direction of allowing it
to be configured. It introduces settings for the addresses and socket
count. Additionally it introduces new settings for the sniff strategy
so that the more generic number of connections and seed node settings
can be deprecated.
The simple settings are not yet registered as the registration is
dependent on follow-up work to validate the settings.
Ensure at least 1 seed configured in remote test (#49389)
This fixes#49384. Currently when we select a random subset of seed
nodes from a list, it is possible for 0 seeds to be selected. This test
depends on at least 1 seed being selected.
Add the simple strategy to cluster settings (#49414)
This is related to #49067. This commit adds the simple connection
strategy settings and strategy mode setting to the cluster settings
registry. With these changes, the simple connection mode can be used.
Additionally, it adds validation to ensure that settings cannot be
misconfigured.
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
This commit adds a deprecation warning when starting
a node where either of the server contexts
(xpack.security.transport.ssl and xpack.security.http.ssl)
meet either of these conditions:
1. The server lacks a certificate/key pair (i.e. neither
ssl.keystore.path not ssl.certificate are configured)
2. The server has some ssl configuration, but ssl.enabled is not
specified. This new validation does not care whether ssl.enabled is
true or false (though other validation might), it simply makes it
an error to configure server SSL without being explicit about
whether to enable that configuration.
Backport of: #45892
* [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
Backport of #48849. Update `.editorconfig` to make the Java settings the
default for all files, and then apply a 2-space indent to all `*.gradle`
files. Then reformat all the files.
* [ML] Add new geo_results.(actual_point|typical_point) fields for `lat_long` results (#47050)
[ML] Add new geo_results.(actual_point|typical_point) fields for `lat_long` results (#47050)
Related PR: https://github.com/elastic/ml-cpp/pull/809
* adjusting bwc version
This commit finishes cleaning up the AbstractHlrcXContentTestCase work
and removes this class. All classes that were using this are now using
the updated base class.
Ref #39745
The old graph tests were duplicated a lot and used a deprecated parent
class. This commit cleans that up and removes one of the duplicated
tests.
Ref #39745
* [ML][Inference] separating definition and config object storage (#48651)
This separates out the `definition` object from being stored within the configuration object in the index.
This allows us to gather the config object without decompressing a potentially large definition.
Additionally, `input` is moved to the TrainedModelConfig object and out of the definition. This is so the trained input fields are accessible outside the potentially large model definition.
Adding support for the `search_type` request parameter to the Ranking Evaluation
API since this parameter can impact the ranking and the metric score and should
be choosen in the same way when evaluating the search as later in the real
search.
Closes#48503
Backport of #48447. Make a number of changes so that code in the
`client` directory is more resilient to automatic formatting. This
covers:
* Literal JSON handling:
* Reformatting multiline JSON to embed whitespace in the strings
* Remove string concatenation where JSON fits on a single line
* Use `String.format` for large documents with variable content
* Remove some erroneous doc refs in `QueryDSLDocumentationTests`
* Move some comments around to they aren't auto-formatted to a strange
place
This commit simplifies and standardizes our usage of the Gradle Shadow
plugin to conform more to plugin conventions. The custom "bundle" plugin
has been removed as it's not necessary and performs the same function
as the Shadow plugin's default behavior with existing configurations.
Additionally, this removes unnecessary creation of a "nodeps" artifact,
which is unnecessary because by default project dependencies will in
fact use the non-shadowed JAR unless explicitly depending on the
"shadow" configuration.
Finally, we've cleaned up the logic used for unit testing, so we are
now correctly testing against the shadow JAR when the plugin is applied.
This better represents a real-world scenario for consumers and provides
better test coverage for incorrectly declared dependencies.
(cherry picked from commit 3698131109c7e78bdd3a3340707e1c7b4740d310)
Due to a bug, GETing a snapshot can cause a RespositoryException to be
thrown. This error is transient and should be retried, rather than
causing the test to fail. This commit converts those
RepositoryExceptions into AssertionErrors so that they will be retried
in code wrapped in assertBusy.
BytesReference is currently an abstract class which is extended by
various implementations. This makes it very difficult to use the
delegation pattern. The implication of this is that our releasable
BytesReference is a PagedBytesReference type and cannot be used as a
generic releasable bytes reference that delegates to any reference type.
This commit makes BytesReference an interface and introduces an
AbstractBytesReference for common functionality.
The AbstractHlrcWriteableXContentTestCase was replaced by a better test
case a while ago, and this is the last two instances using it. They have
been converted and the test is now deleted.
Ref #39745
This commit removes the randomization used by every execute call in the
high level rest tests. Previously every execute call, which can be many
calls per single test, would rely on a random boolean to determine if
they should use the sync or async methods provided to the execute
method. This commit runs the tests twice, using two different clusters,
both of them providing the value one time via a sysprop. This ensures
that the whole suite of tests is run using the sync and async code
paths.
Closes#39667
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
Several links from the ILM HLRC Javadoc to the online documentation were
not updated when the ILM HLRC documentation was written. This commit
fixes those links.
Adds `GET /_script_context`, returning a `contexts` object with each
available context as a key whose value is an empty object. eg.
```
{
"contexts": {
"aggregation_selector": {},
"aggs": {},
"aggs_combine": {},
...
}
}
```
refs: #47411
This adds parsing an inference model as a possible
result of the analytics process. When we do parse such a model
we persist a `TrainedModelConfig` into the inference index
that contains additional metadata derived from the running job.
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>
Prior to this commit terminate_after was sent as request body parameter
(via SearchSourceBuilder), which is not possible in the count api.
Closes#46446
This commits makes all the async methods in the high level client return the `Cancellable` object that the low level client now exposes.
Relates to #45379Closes#44802
The low-level REST client exposes a `performRequestAsync` method that
allows to send async requests, but today it does not expose the ability
to cancel such requests. That is something that the underlying apache
async http client supports, and it makes sense for us to expose.
This commit adds a return value to the `performRequestAsync` method,
which is backwards compatible. A `Cancellable` object gets returned,
which exposes a `cancel` public method. When calling `cancel`, the
on-going request associated with the returned `Cancellable` instance
will be cancelled by calling its `abort` method. This works throughout
multiple retries, though some special care was needed for the case where
`cancel` is called between different attempts (when one attempt has
failed and the consecutive one has not been sent yet).
Note that cancelling a request on the client side does not automatically
translate to cancelling the server side execution of it. That needs to be
specifically implemented, which is on the work for the search API (see #43332).
Relates to #44802
rename data frame transform plugin to transform:
- rename plugin data-frame to transform
- change all package names from o.e.*.dataframe.* to o.e.*.transform.*
- necessary changes to fix loading/testing
Changed the signature of AbstractResponseTestCase#createServerTestInstance(...)
to include the randomly selected xcontent type. This is needed for the
creating a server response instance with a query which is represented as BytesReference.
Maybe this should go into a different change?
This PR also includes HLRC docs for the get policy api.
Relates to #32789
* Add retention to Snapshot Lifecycle Management (#46407)
This commit adds retention to the existing Snapshot Lifecycle Management feature (#38461) as described in #43663. This allows a user to configure SLM to automatically delete older snapshots based on a number of criteria.
An example policy would look like:
```
PUT /_slm/policy/snapshot-every-day
{
"schedule": "0 30 2 * * ?",
"name": "<production-snap-{now/d}>",
"repository": "my-s3-repository",
"config": {
"indices": ["foo-*", "important"]
},
// Newly configured retention options
"retention": {
// Snapshots should be deleted after 14 days
"expire_after": "14d",
// Keep a maximum of thirty snapshots
"max_count": 30,
// Keep a minimum of the four most recent snapshots
"min_count": 4
}
}
```
SLM Retention is run on a scheduled configurable with the `slm.retention_schedule` setting, which supports cron expressions. Deletions are run for a configurable time bounded by the `slm.retention_duration` setting, which defaults to 1 hour.
Included in this work is a new SLM stats API endpoint available through
``` json
GET /_slm/stats
```
That returns statistics about snapshot taken and deleted, as well as successful retention runs, failures, and the time spent deleting snapshots. #45362 has more information as well as an example of the output. These stats are also included when retrieving SLM policies via the API.
* Add base framework for snapshot retention (#43605)
* Add base framework for snapshot retention
This adds a basic `SnapshotRetentionService` and `SnapshotRetentionTask`
to start as the basis for SLM's retention implementation.
Relates to #38461
* Remove extraneous 'public'
* Use a local var instead of reading class var repeatedly
* Add SnapshotRetentionConfiguration for retention configuration (#43777)
* Add SnapshotRetentionConfiguration for retention configuration
This commit adds the `SnapshotRetentionConfiguration` class and its HLRC
counterpart to encapsulate the configuration for SLM retention.
Currently only a single parameter is supported as an example (we still
need to discuss the different options we want to support and their
names) to keep the size of the PR down. It also does not yet include version serialization checks
since the original SLM branch has not yet been merged.
Relates to #43663
* Fix REST tests
* Fix more documentation
* Use Objects.equals to avoid NPE
* Put `randomSnapshotLifecyclePolicy` in only one place
* Occasionally return retention with no configuration
* Implement SnapshotRetentionTask's snapshot filtering and delet… (#44764)
* Implement SnapshotRetentionTask's snapshot filtering and deletion
This commit implements the snapshot filtering and deletion for
`SnapshotRetentionTask`. Currently only the expire-after age is used for
determining whether a snapshot is eligible for deletion.
Relates to #43663
* Fix deletes running on the wrong thread
* Handle missing or null policy in snap metadata differently
* Convert Tuple<String, List<SnapshotInfo>> to Map<String, List<SnapshotInfo>>
* Use the `OriginSettingClient` to work with security, enhance logging
* Prevent NPE in test by mocking Client
* Allow empty/missing SLM retention configuration (#45018)
Semi-related to #44465, this allows the `"retention"` configuration map
to be missing.
Relates to #43663
* Add min_count and max_count as SLM retention predicates (#44926)
This adds the configuration options for `min_count` and `max_count` as
well as the logic for determining whether a snapshot meets this criteria
to SLM's retention feature.
These options are optional and one, two, or all three can be specified
in an SLM policy.
Relates to #43663
* Time-bound deletion of snapshots in retention delete function (#45065)
* Time-bound deletion of snapshots in retention delete function
With a cluster that has a large number of snapshots, it's possible that
snapshot deletion can take a very long time (especially since deletes
currently have to happen in a serial fashion). To prevent snapshot
deletion from taking forever in a cluster and blocking other operations,
this commit adds a setting to allow configuring a maximum time to spend
deletion snapshots during retention. This dynamic setting defaults to 1
hour and is best-effort, meaning that it doesn't hard stop a deletion
at an hour mark, but ensures that once the time has passed, all
subsequent deletions are deferred until the next retention cycle.
Relates to #43663
* Wow snapshots suuuure can take a long time.
* Use a LongSupplier instead of actually sleeping
* Remove TestLogging annotation
* Remove rate limiting
* Add SLM metrics gathering and endpoint (#45362)
* Add SLM metrics gathering and endpoint
This commit adds the infrastructure to gather metrics about the different SLM actions that a cluster
takes. These actions are stored in `SnapshotLifecycleStats` and perpetuated in cluster state. The
stats stored include the number of snapshots taken, failed, deleted, the number of retention runs,
as well as per-policy counts for snapshots taken, failed, and deleted. It also includes the amount
of time spent deleting snapshots from SLM retention.
This commit also adds an endpoint for retrieving all stats (further commits will expose this in the
SLM get-policy API) that looks like:
```
GET /_slm/stats
{
"retention_runs" : 13,
"retention_failed" : 0,
"retention_timed_out" : 0,
"retention_deletion_time" : "1.4s",
"retention_deletion_time_millis" : 1404,
"policy_metrics" : {
"daily-snapshots2" : {
"snapshots_taken" : 7,
"snapshots_failed" : 0,
"snapshots_deleted" : 6,
"snapshot_deletion_failures" : 0
},
"daily-snapshots" : {
"snapshots_taken" : 12,
"snapshots_failed" : 0,
"snapshots_deleted" : 12,
"snapshot_deletion_failures" : 6
}
},
"total_snapshots_taken" : 19,
"total_snapshots_failed" : 0,
"total_snapshots_deleted" : 18,
"total_snapshot_deletion_failures" : 6
}
```
This does not yet include HLRC for this, as this commit is quite large on its own. That will be
added in a subsequent commit.
Relates to #43663
* Version qualify serialization
* Initialize counters outside constructor
* Use computeIfAbsent instead of being too verbose
* Move part of XContent generation into subclass
* Fix REST action for master merge
* Unused import
* Record history of SLM retention actions (#45513)
This commit records the deletion of snapshots by the retention component
of SLM into the SLM history index for the purposes of reviewing operations
taken by SLM and alerting.
* Retry SLM retention after currently running snapshot completes (#45802)
* Retry SLM retention after currently running snapshot completes
This commit adds a ClusterStateObserver to wait until the currently
running snapshot is complete before proceeding with snapshot deletion.
SLM retention waits for the maximum allowed deletion time for the
snapshot to complete, however, the waiting time is not factored into
the limit on actual deletions.
Relates to #43663
* Increase timeout waiting for snapshot completion
* Apply patch
From 2374316f0d.patch
* Rename test variables
* [TEST] Be less strict for stats checking
* Skip SLM retention if ILM is STOPPING or STOPPED (#45869)
This adds a check to ensure we take no action during SLM retention if
ILM is currently stopped or in the process of stopping.
Relates to #43663
* Check all actions preventing snapshot delete during retention (#45992)
* Check all actions preventing snapshot delete during retention run
Previously we only checked to see if a snapshot was currently running,
but it turns out that more things can block snapshot deletion. This
changes the check to be a check for:
- a snapshot currently running
- a deletion already in progress
- a repo cleanup in progress
- a restore currently running
This was found by CI where a third party delete in a test caused SLM
retention deletion to throw an exception.
Relates to #43663
* Add unit test for okayToDeleteSnapshots
* Fix bug where SLM retention task would be scheduled on every node
* Enhance test logging
* Ignore if snapshot is already deleted
* Missing import
* Fix SnapshotRetentionServiceTests
* Expose SLM policy stats in get SLM policy API (#45989)
This also adds support for the SLM stats endpoint to the high level rest client.
Retrieving a policy now looks like:
```json
{
"daily-snapshots" : {
"version": 1,
"modified_date": "2019-04-23T01:30:00.000Z",
"modified_date_millis": 1556048137314,
"policy" : {
"schedule": "0 30 1 * * ?",
"name": "<daily-snap-{now/d}>",
"repository": "my_repository",
"config": {
"indices": ["data-*", "important"],
"ignore_unavailable": false,
"include_global_state": false
},
"retention": {}
},
"stats": {
"snapshots_taken": 0,
"snapshots_failed": 0,
"snapshots_deleted": 0,
"snapshot_deletion_failures": 0
},
"next_execution": "2019-04-24T01:30:00.000Z",
"next_execution_millis": 1556048160000
}
}
```
Relates to #43663
* Rewrite SnapshotLifecycleIT as as ESIntegTestCase (#46356)
* Rewrite SnapshotLifecycleIT as as ESIntegTestCase
This commit splits `SnapshotLifecycleIT` into two different tests.
`SnapshotLifecycleRestIT` which includes the tests that do not require
slow repositories, and `SLMSnapshotBlockingIntegTests` which is now an
integration test using `MockRepository` to simulate a snapshot being in
progress.
Relates to #43663Resolves#46205
* Add error logging when exceptions are thrown
* Update serialization versions
* Fix type inference
* Use non-Cancellable HLRC return value
* Fix Client mocking in test
* Fix SLMSnapshotBlockingIntegTests for 7.x branch
* Update SnapshotRetentionTask for non-multi-repo snapshot retrieval
* Add serialization guards for SnapshotLifecyclePolicy
Since 7.3, the request converter for multiSearchTemplate would silently
not set the two request parameters `typed_keys` and
`max_concurrent_searches`.
Closes#46488
Besides a rename, this changes allows to processor to attach multiple
enrich docs to the document being ingested.
Also in order to control the maximum number of enrich docs to be
included in the document being ingested, the `max_matches` setting
is added to the enrich processor.
Relates #32789
Add XContentType as parameter to the
AbstractResponseTestCase#createServerTestInstance method.
In the case a server side response class serializes xcontent as
bytes then the test needs to know what xcontent type was randomily selected.
This change is needed in #45970
The existing privilege model for API keys with privileges like
`manage_api_key`, `manage_security` etc. are too permissive and
we would want finer-grained control over the cluster privileges
for API keys. Previously APIs created would also need these
privileges to get its own information.
This commit adds support for `manage_own_api_key` cluster privilege
which only allows api key cluster actions on API keys owned by the
currently authenticated user. Also adds support for retrieval of
the API key self-information when authenticating via API key
without the need for the additional API key privileges.
To support this privilege, we are introducing additional
authentication context along with the request context such that
it can be used to authorize cluster actions based on the current
user authentication.
The API key get and invalidate APIs introduce an `owner` flag
that can be set to true if the API key request (Get or Invalidate)
is for the API keys owned by the currently authenticated user only.
In that case, `realm` and `username` cannot be set as they are
assumed to be the currently authenticated ones.
The changes cover HLRC changes, documentation for the API changes.
Closes#40031
This commit introduces PKI realm delegation. This feature
supports the PKI authentication feature in Kibana.
In essence, this creates a new API endpoint which Kibana must
call to authenticate clients that use certificates in their TLS
connection to Kibana. The API call passes to Elasticsearch the client's
certificate chain. The response contains an access token to be further
used to authenticate as the client. The client's certificates are validated
by the PKI realms that have been explicitly configured to permit
certificates from the proxy (Kibana). The user calling the delegation
API must have the delegate_pki privilege.
Closes#34396
Previously, the stats API reports a progress percentage
for DF analytics tasks that are running and are in the
`reindexing` or `analyzing` state.
This means that when the task is `stopped` there is no progress
reported. Thus, one cannot distinguish between a task that never
run to one that completed.
In addition, there are blind spots in the progress reporting.
In particular, we do not account for when data is loaded into the
process. We also do not account for when results are written.
This commit addresses the above issues. It changes progress
to being a list of objects, each one describing the phase
and its progress as a percentage. We currently have 4 phases:
reindexing, loading_data, analyzing, writing_results.
When the task stops, progress is persisted as a document in the
state index. The stats API now reports progress from in-memory
if the task is running, or returns the persisted document
(if there is one).
A policy type controls how the enrich index is created and
the query executed against the match field. Currently there
is a single policy type (`exact_match`). In the near future
more policy types will be added and different policy may have
different configuration options.
For this reason type should be a json object instead of a string field:
```
{
"exact_match": {
...
}
}
```
instead of:
```
{
"type": "exact_match",
...
}
```
This will make streaming parsing of enrich policies easier as in the
new format, the parsing code can know ahead what configuration fields
to expect. In the latter format that is not possible if the type field
appears not as the first field.
Relates to #32789
* Repository Cleanup Endpoint (#43900)
* Snapshot cleanup functionality via transport/REST endpoint.
* Added all the infrastructure for this with the HLRC and node client
* Made use of it in tests and resolved relevant TODO
* Added new `Custom` CS element that tracks the cleanup logic.
Kept it similar to the delete and in progress classes and gave it
some (for now) redundant way of handling multiple cleanups but only allow one
* Use the exact same mechanism used by deletes to have the combination
of CS entry and increment in repository state ID provide some
concurrency safety (the initial approach of just an entry in the CS
was not enough, we must increment the repository state ID to be safe
against concurrent modifications, otherwise we run the risk of "cleaning up"
blobs that just got created without noticing)
* Isolated the logic to the transport action class as much as I could.
It's not ideal, but we don't need to keep any state and do the same
for other repository operations
(like getting the detailed snapshot shard status)
The get and list APIs are a single API in this commit. Whether
requesting one named policy or all policies, a list of policies is
returened. The list API code has all been removed and the GET api is
what remains, which contains much of the list response code.
Adjusts the cluster cleanup routine in ESRestTestCase to clean up SLM
test cases, and optionally wait for all snapshots to be deleted.
Waiting for all snapshots to be deleted, rather than failing if any are
in progress, is necessary for tests which use SLM policies because SLM
policies may be in the process of executing when the test ends.
This change adds the support for the RankFeatureQuery in the HLRC by
providing an extra dependency on mapper-extras-client. It also removes
the dependency on lang-painless in mapper-extras which is not needed
anymore since the move of the vector field into a dedicated module.
Closes#43634
This commit replaces task_state and indexer_state in the
data frame _stats output with a single top level state
that combines the two. It is defined as:
- failed if what's currently reported as task_state is failed
- stopped if there is no persistent task
- Otherwise what's currently reported as indexer_state
Backport of #45276
* [ML][Data Frame] Add update transform api endpoint (#45154)
This adds the ability to `_update` stored data frame transforms. All mutable fields are applied when the next checkpoint starts. The exception being `description`.
This PR contains all that is necessary for this addition:
* HLRC
* Docs
* Server side
This commit adds a deprecation warning in 7.x for the Force Merge API
when both only_expunge_deletes and max_num_segments are set in a request.
Relates #44761
introduces an abstraction for how checkpointing and synchronization works, covering
- retrieval of checkpoints
- check for updates
- retrieving stats information
This commit switches to using the full hash to build into the JAR
manifest, which is used in node startup and the REST main action to
display the build hash.
Jim Ferenczi
Benjamin Trent
Tim Brooks
jesinity
Dimitris Athanasiou
Tim Vernum
Przemysław Witek
Rory Hunter
Alan Woodward
Michael Basnight
Dan Hermann
Gordon Brown
Christoph Büscher
Mark Vieira
David Turner
Tanguy Leroux
Martijn van Groningen
Lee Hinman
Albert Zaharovits
Stuart Tettemer
David Roberts
Yogesh Gaikwad
Hendrik Muhs
Alpar Torok
Yannick Welsch
maidoo
Lisa Cawley
Andrei Dan
James Rodewig
Turaç Kangal
Henning Andersen
Luca Cavanna
Jilles van Gurp
Albert Zaharovits
markharwood
Armin Braun
Denis Derezhenets
Jason Tedor