This commit reuses the same state processor that is used for autodetect
to parse state output from data frame analytics jobs. We then index the
state document into the state index.
Backport of #46804
* [ML][Transforms] remove `force` flag from _start (#46414)
* [ML][Transforms] remove `force` flag from _start
* fixing expected error message
* adjusting bwc version
* Give kibana user reserved role privileges on .apm-* to create APM agent configuration index.
* fixed test to include checking all .apm-* permissions
* changed pattern from ".apm-*" to the more specific ".apm-agent-configuration"
* Write metadata during snapshot finalization after segment files to prevent outdated metadata in case of dynamic mapping updates as explained in #41581
* Keep the old behavior of writing the metadata beforehand in the case of mixed version clusters for BwC reasons
* Still overwrite the metadata in the end, so even a mixed version cluster is fixed by this change if a newer version master does the finalization
* Fixes#41581
* [ILM] Add date setting to calculate index age
Add the `index.lifecycle.origination_date` to allow users to configure a
custom date that'll be used to calculate the index age for the phase
transmissions (as opposed to the default index creation date).
This could be useful for users to create an index with an "older"
origination date when indexing old data.
Relates to #42449.
* [ILM] Don't override creation date on policy init
The initial approach we took was to override the lifecycle creation date
if the `index.lifecycle.origination_date` setting was set. This had the
disadvantage of the user not being able to update the `origination_date`
anymore once set.
This commit changes the way we makes use of the
`index.lifecycle.origination_date` setting by checking its value when
we calculate the index age (ie. at "read time") and, in case it's not
set, default to the index creation date.
* Make origination date setting index scope dynamic
* Document orignation date setting in ilm settings
(cherry picked from commit d5bd2bb77ee28c1978ab6679f941d7c02e389d32)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
Since the `IndicesSegmentsRequest` scatters to all shards for the index,
it's possible that some of the shards may fail. This adds failure
handling and logging (since this is a best-effort step in the first
place) for this case.
This commit replaces the `SearchContext` with the `QueryShardContext` when building aggregator factories. Aggregator factories are part of the `SearchContext` so they shouldn't require a `SearchContext` to create them.
The main changes here are the signatures of `AggregationBuilder#build` that now takes a `QueryShardContext` and `AggregatorFactory#createInternal` that passes the `SearchContext` to build the `Aggregator`.
Relates #46523
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
* More Efficient Ordering of Shard Upload Execution (#42791)
* Change the upload order of of snapshots to work file by file in parallel on the snapshot pool instead of merely shard-by-shard
* Inspired by #39657
* Cleanup BlobStoreRepository Abort and Failure Handling (#46208)
This change adds an IndexSearcher and the node's BigArrays in the QueryShardContext.
It's a spin off of #46527 as this change is required to allow aggregation builder to solely use the
query shard context.
Relates #46523
* 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
As per #45852 comment we no longer need to log stack-traces in
SecurityTransportExceptionHandler and SecurityHttpExceptionHandler even
if trace logging is enabled.
(cherry picked from commit c99224a32d26db985053b7b36e2049036e438f97)
* [ML][Transforms] fixing stop on changes check bug
* Adding new method finishAndCheckState to cover race conditions in early terminations
* changing stopping conditions in `onStart`
* allow indexer to finish when exiting early
Fixes a problem where operations_behind would be one less than
expected per shard in a new index matched by the data frame
transform source pattern.
For example, if a data frame transform had a source of foo*
and a new index foo-new was created with 2 shards and 7 documents
indexed in it then operations_behind would be 5 prior to this
change.
The problem was that an empty index has a global checkpoint
number of -1 and the sequence number of the first document that
is indexed into an index is 0, not 1. This doesn't matter for
indices included in both the last and next checkpoints, as the
off-by-one errors cancelled, but for a new index it affected
the observed result.
Though we allow CCS within datafeeds, users could prevent nodes from accessing remote clusters. This can cause mysterious errors and difficult to troubleshoot.
This commit adds a check to verify that `cluster.remote.connect` is enabled on the current node when a datafeed is configured with a remote index pattern.
* [ML] Regression dependent variable must be numeric
This adds a validation that the dependent variable of a regression
analysis must be numeric.
* Address review comments and fix some problems
In addition to addressing the review comments, this
commit fixes a few issues I found during testing.
In particular:
- if there were mappings for required fields but they were
not included we were not reporting the error
- if explicitly included fields had unsupported types we were
not reporting the error
Unfortunately, I couldn't get those fixed without refactoring
the code in `ExtractedFieldsDetector`.
This commit adds the `rollover_alias` setting required for ILM to work
correctly to the SLM history index template and adds assertions to the
SLM integration tests to ensure that it works correctly.
Prior to this commit the foreach action execution had a hard coded
limit to 100 iterations. This commit allows the max number of
iterations to be a configuration ('max_iterations') on the foreach
action. The default remains 100.
Adds a parameter `training_percent` to regression. The default
value is `100`. When the parameter is set to a value less than `100`,
from the rows that can be used for training (ie. those that have a
value for the dependent variable) we randomly choose whether to actually
use for training. This enables splitting the data into a training set and
the rest, usually called testing, validation or holdout set, which allows
for validating the model on data that have not been used for training.
Technically, the analytics process considers as training the data that
have a value for the dependent variable. Thus, when we decide a training
row is not going to be used for training, we simply clear the row's
dependent variable.
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 adds a pipeline aggregation that calculates the cumulative
cardinality of a field. It does this by iteratively merging in the
HLL sketch from consecutive buckets and emitting the cardinality up
to that point.
This is useful for things like finding the total "new" users that have
visited a website (as opposed to "repeat" visitors).
This is a Basic+ aggregation and adds a new Data Science plugin
to house it and future advanced analytics/data science aggregations.
Today if non-TLS record is received on TLS port generic exception will
be logged with the stack-trace.
SSLExceptionHelper.isNotSslRecordException method does not work because
it's assuming that NonSslRecordException would be top-level.
This commit addresses the issue and the log would be more concise.
(cherry picked from commit 6b83527bf0c23d4d5b97fab7f290c43432945d4f)
This commit allows the Transport Actions for the SSO realms to
indicate the realm that should be used to authenticate the
constructed AuthenticationToken. This is useful in the case that
many authentication realms of the same type have been configured
and where the caller of the API(Kibana or a custom web app) already
know which realm should be used so there is no need to iterate all
the realms of the same type.
The realm parameter is added in the relevant REST APIs as optional
so as not to introduce any breaking change.
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).
The security indices were being created without specifying the
refresh interval, which means it would inherit a value from any
templates that exists.
However, certain security functionality depends on being able to
wait_for refresh, and causes errors (e.g. in Kibana) if that time
exceeds 30s.
This commit changes the security indices configuration to always be
created with a 1s refresh interval. This prevents any templates from
inadvertantly interfering with the proper functioning of security.
It is possible for an administrator to explicitly change the refresh
interval after the indices have been created.
Backport of: #45434
This change adds a new SSL context
xpack.notification.email.ssl.*
that supports the standard SSL configuration settings (truststore,
verification_mode, etc). This SSL context is used when configuring
outbound SMTP properties for watcher email notifications.
Backport of: #45272
* [ML] Adding data frame analytics stats to _usage API (#45820)
* [ML] Adding data frame analytics stats to _usage API
* making the size of analytics stats 10k
* adjusting backport
Adds index versioning for the internal data frame transform index. Allows for new indices to be created and referenced, `GET` requests now query over the index pattern and takes the latest doc (based on INDEX name).
Following our own guidelines, SLM should use rollover instead of purely
time-based indices to keep shard counts low. This commit implements lazy
index creation for SLM's history indices, indexing via an alias, and
rollover in the built-in ILM policy.
Regression analysis support missing fields. Even more, it is expected
that the dependent variable has missing fields to the part of the
data frame that is not for training.
This commit allows to declare that an analysis supports missing values.
For such analysis, rows with missing values are not skipped. Instead,
they are written as normal with empty strings used for the missing values.
This also contains a fix to the integration test.
Closes#45425
* [ML] better handle empty results when evaluating regression
* adding new failure test to ml_security black list
* fixing equality check for regression results
Hendrik Muhs
Dimitris Athanasiou
Benjamin Trent
Lee Hinman
Oliver Gupte
Armin Braun
Przemysław Witek
Andrei Dan
Luca Cavanna
James Rodewig
Jim Ferenczi
Andrey Ershov
David Roberts
Zachary Tong
Gordon Brown
Jake Landis
Yogesh Gaikwad
Albert Zaharovits
Ioannis Kakavas
markharwood
Tim Vernum