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.
Fixes#54067
The usage of local parameter for GetFieldMappingRequest has been removed from the underlying transport action since v2.0.
This PR deprecates the parameter from rest layer. It will be removed in next major version.
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.
Today when canceling a task we broadcast ban/unban requests to all nodes
in the cluster. This strategy does not scale well for hierarchical
cancellation. With this change, we will track outstanding child requests
and broadcast the cancellation to only nodes that have outstanding child
tasks. This change also prevents a parent task from sending child
requests once it got canceled.
Relates #50990
Supersedes #51157
Co-authored-by: Igor Motov <igor@motovs.org>
Co-authored-by: Yannick Welsch <yannick@welsch.lu>
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.
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.
The `top_metrics` agg is kind of like `top_hits` but it only works on
doc values so it *should* be faster.
At this point it is fairly limited in that it only supports a single,
numeric sort and a single, numeric metric. And it only fetches the "very
topest" document worth of metric. We plan to support returning a
configurable number of top metrics, requesting more than one metric and
more than one sort. And, eventually, non-numeric sorts and metrics. The
trick is doing those things fairly efficiently.
Co-Authored by: Zachary Tong <zach@elastic.co>
This adds a builder and parsed results for the `string_stats`
aggregation directly to the high level rest client. Without this the
HLRC can't access the `string_stats` API without the elastic licensed
`analytics` module.
While I'm in there this adds a few of our usual unit tests and
modernizes the parsing.
This commit adds examples in our documentation for
- An HLRC instance authenticating to an elasticsearch cluster using
an elasticsearch token service access token or an API key
- An HLRC instance connecting to an elasticsearch cluster that is
setup for TLS on the HTTP layer when the CA certificate of the
cluster is available either as a PEM file or a keystore
- An HLRC instance connecting to an elasticsearch cluster that
requires client authentication where the client key and certificate
are available in a keystore
Co-Authored-By: Lisa Cawley <lcawley@elastic.co>
Adds a new URL parameter, `tags` to the GET _ml/inference/<model_id> endpoint.
This parameter allows the list of models to be further reduced to those who contain all the provided tags.
Synced flush was a brilliant idea. It supports instant recoveries with a
quite small implementation. However, with the presence of sequence
numbers and retention leases, it is no longer needed. This change
removes it from 8.0.
Relates #5077
Adds a new parameter to regression and classification that enables computation
of importance for the top most important features. The computation of the importance
is based on SHAP (SHapley Additive exPlanations) method.
This adds the `PUT` API for creating trained models that support our format.
This includes
* HLRC change for the API
* API creation
* Validations of model format and call
Adds a `force` parameter to the delete data frame analytics
request. When `force` is `true`, the action force-stops the
jobs and then proceeds to the deletion. This can be used in
order to delete a non-stopped job with a single request.
Closes#48124
Unreverts the commit that added the remote info api to HLRC (#49657).
The additional change to the original PR, is that `org.elasticsearch.client.cluster.RemoteConnectionInfo` now parses the initial_connect_timeout field as a string instead of a TimeValue instance.
The reason that this is needed is because that the initial_connect_timeout field in the remote connection api is serialized for human consumption, but not for parsing purposes.
Therefore the HLRC can't parse it correctly (which caused test failures in CI, but not in the PR CI
:( ). The way this field is serialized needs to be changed in the remote connection api, but that is a breaking change. We should wait making this change until rest api versioning is introduced.
Co-Authored-By: j-bean anton.shuvaev91@gmail.com
This adds a new `randomize_seed` for regression and classification.
When not explicitly set, the seed is randomly generated. One can
reuse the seed in a similar job in order to ensure the same docs
are picked for training.
Reindex sort never gave a guarantee about the order of documents being
indexed into the destination, though it could give a sense of locality
of source data.
It prevents us from doing resilient reindex and other optimizations and
it has therefore been deprecated.
Related to #47567
This adds a `_source` setting under the `source` setting of a data
frame analytics config. The new `_source` is reusing the structure
of a `FetchSourceContext` like `analyzed_fields` does. Specifying
includes and excludes for source allows selecting which fields
will get reindexed and will be available in the destination index.
Closes#49531
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.
PR #25543 removed the `_uid` field in favor of the `_id` field,
including for use in slicing.
This removes an outdated reference to `_uid` in our reindex docs.
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.
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
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
* Add API to execute SLM retention on-demand
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
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
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
Add a section to both the low level and high level client documentation on asynchronous usage and `Cancellable` added for #44802
Co-Authored-By: Lee Hinman <dakrone@users.noreply.github.com>
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
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
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
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
Closes#45201
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
Adds an API to clone an index. This is similar to the index split and shrink APIs, just with the
difference that the number of primary shards is kept the same. In case where the filesystem
provides hard-linking capabilities, this is a very cheap operation.
Indexing cloning can be done by running `POST my_source_index/_clone/my_target_index` and it
supports the same options as the split and shrink APIs.
Closes#44128
This change adjusts the data frame transforms stats
endpoint to return a structure that is easier to
understand.
This is a breaking change for clients of the data frame
transforms stats endpoint, but the feature is in beta so
stability is not guaranteed.
Closes#43767
* Add SnapshotLifecycleService and related CRUD APIs
This commit adds `SnapshotLifecycleService` as a new service under the ilm
plugin. This service handles snapshot lifecycle policies by scheduling based on
the policies defined schedule.
This also includes the get, put, and delete APIs for these policies
Relates to #38461
* Make scheduledJobIds return an immutable set
* Use Object.equals for SnapshotLifecyclePolicy
* Remove unneeded TODO
* Implement ToXContentFragment on SnapshotLifecyclePolicyItem
* Copy contents of the scheduledJobIds
* Handle snapshot lifecycle policy updates and deletions (#40062)
(Note this is a PR against the `snapshot-lifecycle-management` feature branch)
This adds logic to `SnapshotLifecycleService` to handle updates and deletes for
snapshot policies. Policies with incremented versions have the old policy
cancelled and the new one scheduled. Deleted policies have their schedules
cancelled when they are no longer present in the cluster state metadata.
Relates to #38461
* Take a snapshot for the policy when the SLM policy is triggered (#40383)
(This is a PR for the `snapshot-lifecycle-management` branch)
This commit fills in `SnapshotLifecycleTask` to actually perform the
snapshotting when the policy is triggered. Currently there is no handling of the
results (other than logging) as that will be added in subsequent work.
This also adds unit tests and an integration test that schedules a policy and
ensures that a snapshot is correctly taken.
Relates to #38461
* Record most recent snapshot policy success/failure (#40619)
Keeping a record of the results of the successes and failures will aid
troubleshooting of policies and make users more confident that their
snapshots are being taken as expected.
This is the first step toward writing history in a more permanent
fashion.
* Validate snapshot lifecycle policies (#40654)
(This is a PR against the `snapshot-lifecycle-management` branch)
With the commit, we now validate the content of snapshot lifecycle policies when
the policy is being created or updated. This checks for the validity of the id,
name, schedule, and repository. Additionally, cluster state is checked to ensure
that the repository exists prior to the lifecycle being added to the cluster
state.
Part of #38461
* Hook SLM into ILM's start and stop APIs (#40871)
(This pull request is for the `snapshot-lifecycle-management` branch)
This change allows the existing `/_ilm/stop` and `/_ilm/start` APIs to also
manage snapshot lifecycle scheduling. When ILM is stopped all scheduled jobs are
cancelled.
Relates to #38461
* Add tests for SnapshotLifecyclePolicyItem (#40912)
Adds serialization tests for SnapshotLifecyclePolicyItem.
* Fix improper import in build.gradle after master merge
* Add human readable version of modified date for snapshot lifecycle policy (#41035)
* Add human readable version of modified date for snapshot lifecycle policy
This small change changes it from:
```
...
"modified_date": 1554843903242,
...
```
To
```
...
"modified_date" : "2019-04-09T21:05:03.242Z",
"modified_date_millis" : 1554843903242,
...
```
Including the `"modified_date"` field when the `?human` field is used.
Relates to #38461
* Fix test
* Add API to execute SLM policy on demand (#41038)
This commit adds the ability to perform a snapshot on demand for a policy. This
can be useful to take a snapshot immediately prior to performing some sort of
maintenance.
```json
PUT /_ilm/snapshot/<policy>/_execute
```
And it returns the response with the generated snapshot name:
```json
{
"snapshot_name" : "production-snap-2019.04.09-rfyv3j9qreixkdbnfuw0ug"
}
```
Note that this does not allow waiting for the snapshot, and the snapshot could
still fail. It *does* record this information into the cluster state similar to
a regularly trigged SLM job.
Relates to #38461
* Add next_execution to SLM policy metadata (#41221)
* Add next_execution to SLM policy metadata
This adds the next time a snapshot lifecycle policy will be executed when
retriving a policy's metadata, for example:
```json
GET /_ilm/snapshot?human
{
"production" : {
"version" : 1,
"modified_date" : "2019-04-15T21:16:21.865Z",
"modified_date_millis" : 1555362981865,
"policy" : {
"name" : "<production-snap-{now/d}>",
"schedule" : "*/30 * * * * ?",
"repository" : "repo",
"config" : {
"indices" : [
"foo-*",
"important"
],
"ignore_unavailable" : true,
"include_global_state" : false
}
},
"next_execution" : "2019-04-15T21:16:30.000Z",
"next_execution_millis" : 1555362990000
},
"other" : {
"version" : 1,
"modified_date" : "2019-04-15T21:12:19.959Z",
"modified_date_millis" : 1555362739959,
"policy" : {
"name" : "<other-snap-{now/d}>",
"schedule" : "0 30 2 * * ?",
"repository" : "repo",
"config" : {
"indices" : [
"other"
],
"ignore_unavailable" : false,
"include_global_state" : true
}
},
"next_execution" : "2019-04-16T02:30:00.000Z",
"next_execution_millis" : 1555381800000
}
}
```
Relates to #38461
* Fix and enhance tests
* Figured out how to Cron
* Change SLM endpoint from /_ilm/* to /_slm/* (#41320)
This commit changes the endpoint for snapshot lifecycle management from:
```
GET /_ilm/snapshot/<policy>
```
to:
```
GET /_slm/policy/<policy>
```
It mimics the ILM path only using `slm` instead of `ilm`.
Relates to #38461
* Add initial documentation for SLM (#41510)
* Add initial documentation for SLM
This adds the initial documentation for snapshot lifecycle management.
It also includes the REST spec API json files since they're sort of
documentation.
Relates to #38461
* Add `manage_slm` and `read_slm` roles (#41607)
* Add `manage_slm` and `read_slm` roles
This adds two more built in roles -
`manage_slm` which has permission to perform any of the SLM actions, as well as
stopping, starting, and retrieving the operation status of ILM.
`read_slm` which has permission to retrieve snapshot lifecycle policies as well
as retrieving the operation status of ILM.
Relates to #38461
* Add execute to the test
* Fix ilm -> slm typo in test
* Record SLM history into an index (#41707)
It is useful to have a record of the actions that Snapshot Lifecycle
Management takes, especially for the purposes of alerting when a
snapshot fails or has not been taken successfully for a certain amount of
time.
This adds the infrastructure to record SLM actions into an index that
can be queried at leisure, along with a lifecycle policy so that this
history does not grow without bound.
Additionally,
SLM automatically setting up an index + lifecycle policy leads to
`index_lifecycle` custom metadata in the cluster state, which some of
the ML tests don't know how to deal with due to setting up custom
`NamedXContentRegistry`s. Watcher would cause the same problem, but it
is already disabled (for the same reason).
* High Level Rest Client support for SLM (#41767)
* High Level Rest Client support for SLM
This commit add HLRC support for SLM.
Relates to #38461
* Fill out documentation tests with tags
* Add more callouts and asciidoc for HLRC
* Update javadoc links to real locations
* Add security test testing SLM cluster privileges (#42678)
* Add security test testing SLM cluster privileges
This adds a test to `PermissionsIT` that uses the `manage_slm` and `read_slm`
cluster privileges.
Relates to #38461
* Don't redefine vars
* Add Getting Started Guide for SLM (#42878)
This commit adds a basic Getting Started Guide for SLM.
* Include SLM policy name in Snapshot metadata (#43132)
Keep track of which SLM policy in the metadata field of the Snapshots
taken by SLM. This allows users to more easily understand where the
snapshot came from, and will enable future SLM features such as
retention policies.
* Fix compilation after master merge
* [TEST] Move exception wrapping for devious exception throwing
Fixes an issue where an exception was created from one line and thrown in another.
* Fix SLM for the change to AcknowledgedResponse
* Add Snapshot Lifecycle Management Package Docs (#43535)
* Fix compilation for transport actions now that task is required
* Add a note mentioning the privileges needed for SLM (#43708)
* Add a note mentioning the privileges needed for SLM
This adds a note to the top of the "getting started with SLM"
documentation mentioning that there are two built-in privileges to
assist with creating roles for SLM users and administrators.
Relates to #38461
* Mention that you can create snapshots for indices you can't read
* Fix REST tests for new number of cluster privileges
* Mute testThatNonExistingTemplatesAreAddedImmediately (#43951)
* Fix SnapshotHistoryStoreTests after merge
* Remove overridden newResponse functions that have been removed
Previously a data frame transform would check whether the
source index was changed every 10 seconds. Sometimes it
may be desirable for the check to be done less frequently.
This commit increases the default to 60 seconds but also
allows the frequency to be overridden by a setting in the
data frame transform config.
This introduces a `failed` state to which the data frame analytics
persistent task is set to when something unexpected fails. It could
be the process crashing, the results processor hitting some error,
etc. The failure message is then captured and set on the task state.
From there, it becomes available via the _stats API as `failure_reason`.
The df-analytics stop API now has a `force` boolean parameter. This allows
the user to call it for a failed task in order to reset it to `stopped` after
we have ensured the failure has been communicated to the user.
This commit also adds the analytics version in the persistent task
params as this allows us to prevent tasks to run on unsuitable nodes in
the future.
This merges the initial work that adds a framework for performing
machine learning analytics on data frames. The feature is currently experimental
and requires a platinum license. Note that the original commits can be
found in the `feature-ml-data-frame-analytics` branch.
A new set of APIs is added which allows the creation of data frame analytics
jobs. Configuration allows specifying different types of analysis to be performed
on a data frame. At first there is support for outlier detection.
The APIs are:
- PUT _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}/_stats
- POST _ml/data_frame/analysis/{id}/_start
- POST _ml/data_frame/analysis/{id}/_stop
- DELETE _ml/data_frame/analysis/{id}
When a data frame analytics job is started a persistent task is created and started.
The main steps of the task are:
1. reindex the source index into the dest index
2. analyze the data through the data_frame_analyzer c++ process
3. merge the results of the process back into the destination index
In addition, an evaluation API is added which packages commonly used metrics
that provide evaluation of various analysis:
- POST _ml/data_frame/_evaluate
* [ML][Data Frame] adds new pipeline field to dest config
* Adding pipeline support to _preview
* removing unused import
* moving towards extracting _source from pipeline simulation
* fixing permission requirement, adding _index entry to doc
Previously, a reindex request had two different size specifications in the body:
* Outer level, determining the maximum documents to process
* Inside the source element, determining the scroll/batch size.
The outer level size has now been renamed to max_docs to
avoid confusion and clarify its semantics, with backwards compatibility and
deprecation warnings for using size.
Similarly, the size parameter has been renamed to max_docs for
update/delete-by-query to keep the 3 interfaces consistent.
Finally, all 3 endpoints now support max_docs in both body and URL.
Relates #24344
This commit clones the existing AnalyzeRequest/AnalyzeResponse classes
to the high-level rest client, and adjusts request converters to use these new
classes.
This is a prerequisite to removing the Streamable interface from the internal
server version of these classes.
Remove `common` query and `cutoff_frequency` parameter of
`match` and `multi_match` queries. Both have already been
deprecated for the next 7.x version.
Closes: #37096
Removes all deprecated type-related methods from the QueryBuilders helper class
and from tests using them. Also removing related docs tests and doc pages
refering to the `type` query. All removed methods have been deprecated since
version 7.0.
* [ML] adding pivot.size option for setting paging size
* Changing field name to address PR comments
* fixing ctor usage
* adjust hlrc for field name change
The date_histogram accepts an interval which can be either a calendar
interval (DST-aware, leap seconds, arbitrary length of months, etc) or
fixed interval (strict multiples of SI units). Unfortunately this is inferred
by first trying to parse as a calendar interval, then falling back to fixed
if that fails.
This leads to confusing arrangement where `1d` == calendar, but
`2d` == fixed. And if you want a day of fixed time, you have to
specify `24h` (e.g. the next smallest unit). This arrangement is very
error-prone for users.
This PR adds `calendar_interval` and `fixed_interval` parameters to any
code that uses intervals (date_histogram, rollup, composite, datafeed, etc).
Calendar only accepts calendar intervals, fixed accepts any combination of
units (meaning `1d` can be used to specify `24h` in fixed time), and both
are mutually exclusive.
The old interval behavior is deprecated and will throw a deprecation warning.
It is also mutually exclusive with the two new parameters. In the future the
old dual-purpose interval will be removed.
The change applies to both REST and java clients.
As a follow-up to #38540 we can use lambda functions and method
references where convenient in the low-level REST client.
Also, we need to update the docs to state that the minimum java version
required is 1.8.
* [ML] Adds progress reporting for transforms
* fixing after master merge
* Addressing PR comments
* removing unused imports
* Adjusting afterKey handling and percentage to be 100*
* Making sure it is a linked hashmap for serialization
* removing unused import
* addressing PR comments
* removing unused import
* simplifying code, only storing total docs and decrementing
* adjusting for rewrite
* removing initial progress gathering from executor
We generate two pages with "funny" names:
* _changing_the_client_8217_s_initialization_code.html
* _changing_the_application_8217_s_code.html
The leading `_` comes from us not specifying the name of the page. The
`8217` comes about because of the single quote character. This is a
funny name, but it is the name that we have so we shouldn't change it
without putting in a redirect.
We're looking at switching these docs from being built with the
no-longer-maintained AsciiDoc project to being built with the
actively-maintained Asciidoctor project. Asciidoctor Doesn't include the
`8217`s in the generated ids. That is *better*, but we don't really want
to change the pages. Ultimately we'd prefer none of our pages start with
`_`, but that is a problem for a different time.
Anyway, this pins the ids to their "funny" id so it won't change when we
switch to Asciidoctor. We'll remove it later, when we have more fine
control of our redirects.
This commit fixes a problem with BWC that was brought up in #40511. A
newer version of the code was emitting a new value for an enum to an
older version, and the older version could not handle that. It caused
the response to error. The MainResponse is now relaxed, and will accept
whatever values the server expose, and holds most of them as Strings
instead of complex objects.
Fixes#40511
* [ML] Add data frame task state object and field
* A new state item is added so that the overall task state can be
accoutned for
* A new FAILED state and reason have been added as well so that failures
can be shown to the user for optional correction
* Addressing PR comments
* adjusting after master merge
* addressing pr comment
* Adjusting auditor usage with failure state
* Refactor, renamed state items to task_state and indexer_state
* Adding todo and removing redundant auditor call
* Address HLRC changes and PR comment
* adjusting hlrc IT test
* [ML] make source and dest objects in the transform config
* addressing PR comments
* Fixing compilation post merge
* adding comment for Arrays.hashCode
* addressing changes for moving dest to object
* fixing data_frame yml tests
* fixing API test
The Migration Assistance API has been functionally replaced by the
Deprecation Info API, and the Migration Upgrade API is not used for the
transition from ES 6.x to 7.x, and does not need to be kept around to
repair indices that were not properly upgraded before upgrading the
cluster, as was the case in 6.
Andrei Dan
Dimitris Athanasiou
Hendrik Muhs
David Roberts
Yang Wang
Benjamin Trent
Nhat Nguyen
Christoph Büscher
Tom Veasey
Maxim
OriGlassman
Nik Everett
Raidok
Ioannis Kakavas
Jake
Martijn van Groningen
j-bean
Przemysław Witek
Henning Andersen
Lisa Cawley
Michael Basnight
James Rodewig
Alexandre Fonseca
debadair
Gordon Brown
Tanguy Leroux
Yogesh Gaikwad
Tal Levy
Lee Hinman
István Zoltán Szabó
Jilles van Gurp
Albert Zaharovits
markharwood
Jim Ferenczi
Luca Cavanna
Yannick Welsch
Tim Vernum
Colin Goodheart-Smithe
Alan Woodward
Marios Trivyzas
Jason Tedor
Zachary Tong
David Kyle