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
Backport of #49690
* Make BlobStoreRepository Aware of ClusterState (#49639)
This is a preliminary to #49060.
It does not introduce any substantial behavior change to how the blob store repository
operates. What it does is to add all the infrastructure changes around passing the cluster service to the blob store, associated test changes and a best effort approach to tracking the latest repository generation on all nodes from cluster state updates. This brings a slight improvement to the consistency
by which non-master nodes (or master directly after a failover) will be able to determine the latest repository generation. It does not however do any tricky checks for the situation after a repository operation
(create, delete or cleanup) that could theoretically be used to get even greater accuracy to keep this change simple.
This change does not in any way alter the behavior of the blobstore repository other than adding a better "guess" for the value of the latest repo generation and is mainly intended to isolate the actual logical change to how the
repository operates in #49060
- Improves HTTP client hostname verification failure messages
- Adds "DiagnosticTrustManager" which logs certificate information
when trust cannot be established (hostname failure, CA path failure,
etc)
These diagnostic messages are designed so that many common TLS
problems can be diagnosed based solely (or primarily) on the
elasticsearch logs.
These diagnostics can be disabled by setting
xpack.security.ssl.diagnose.trust: false
Backport of: #48911
Authentication has grown more complex with the addition of new realm
types and authentication methods. When user authentication does not
behave as expected it can be difficult to determine where and why it
failed.
This commit adds DEBUG and TRACE logging at key points in the
authentication flow so that it is possible to gain addition insight
into the operation of the system.
Backport of: #49575
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.
The categorization job wizard in the ML UI will use this
information when showing the effect of the chosen categorization
analyzer on a sample of input.
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
This is a pure code rearrangement refactor. Logic for what specific ValuesSource instance to use for a given type (e.g. script or field) moved out of ValuesSourceConfig and into CoreValuesSourceType (previously just ValueSourceType; we extract an interface for future extensibility). ValueSourceConfig still selects which case to use, and then the ValuesSourceType instance knows how to construct the ValuesSource for that case.
This API call in most implementations is fairly IO heavy and slow
so it is more natural to be async in the first place.
Concretely though, this change is a prerequisite of #49060 since
determining the repository generation from the cluster state
introduces situations where this call would have to wait for other
operations to finish. Doing so in a blocking manner would break
`SnapshotResiliencyTests` and waste a thread.
Also, this sets up the possibility to in the future make use of async IO
where provided by the underlying Repository implementation.
In a follow-up `SnapshotsService#getRepositoryData` will be made async
as well (did not do it here, since it's another huge change to do so).
Note: This change for now does not alter the threading behaviour in any way (since `Repository#getRepositoryData` isn't forking) and is purely mechanical.
The following edge cases were fixed:
1. A request to force-stop a stopping datafeed is no longer
ignored. Force-stop is an important recovery mechanism
if normal stop doesn't work for some reason, and needs
to operate on a datafeed in any state other than stopped.
2. If the node that a datafeed is running on is removed from
the cluster during a normal stop then the stop request is
retried (and will likely succeed on this retry by simply
cancelling the persistent task for the affected datafeed).
3. If there are multiple simultaneous force-stop requests for
the same datafeed we no longer fail the one that is
processed second. The previous behaviour was wrong as
stopping a stopped datafeed is not an error, so stopping
a datafeed twice simultaneously should not be either.
Backport of #49191
* [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
improve error handling for script errors, treating it as irrecoverable errors which puts the task
immediately into failed state, also improves the error extraction to properly report the script
error.
fixes#48467
This commit fixes a NPE problem as reported in #49150.
But this problem uncovered that we never added proper handling
of state for data frame analytics tasks.
In this commit we improve the `MlTasks.getDataFrameAnalyticsState`
method to handle null tasks and state tasks properly.
Closes#49150
Backport of #49186
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.
We can have a race here where `scheduleNextRun` executes concurrently to `stop`
and so we run into a `RejectedExecutionException` that we don't catch and thus it
fails tests.
=> Fixed by ignoring these so long as they coincide with a scheduler shutdown
When using the move-to-step API, we should reread the phase JSON from
the latest version of the ILM policy. This allows a user to move to the
same step while re-reading the policy's latest version. For example,
when changing rollover criteria.
While manually messing around with some other things I discovered that
we only reread the policy when using the retry API, not the move-to-step
API. This commit changes the move-to-step API to always read the latest
version of the policy.
* [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
decouple TransformTask and ClientTransformIndexer. Interaction between the 2 classes are
now moved into a context class which holds shared information.
relates #45369
Previous behavior while copying HTTP headers to the ThreadContext,
would allow multiple HTTP headers with the same name, handling only
the first occurrence and disregarding the rest of the values. This
can be confusing when dealing with multiple Headers as it is not
obvious which value is read and which ones are silently dropped.
According to RFC-7230, a client must not send multiple header fields
with the same field name in a HTTP message, unless the entire field
value for this header is defined as a comma separated list or this
specific header is a well-known exception.
This commits changes the behavior in order to be more compliant to
the aforementioned RFC by requiring the classes that implement
ActionPlugin to declare if a header can be multi-valued or not when
registering this header to be copied over to the ThreadContext in
ActionPlugin#getRestHeaders.
If the header is allowed to be multivalued, then all such headers
are read from the HTTP request and their values get concatenated in
a comma-separated string.
If the header is not allowed to be multivalued, and the HTTP
request contains multiple such Headers with different values, the
request is rejected with a 400 status.
This adds the infrastructure to be able to retry the execution of retryable
steps and makes the `check-rollover-ready` retryable as an initial step to
make the rollover action more resilient to transient errors.
(cherry picked from commit 454020ac8acb147eae97acb4ccd6fb470d1e5f48)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
* Un-AwaitsFix and enhance logging for testPolicyCRUD
This removes the `AwaitsFix` and increases the test logging for
`SnapshotLifecycleServiceTests.testPolicyCRUD` in an effort to track
down the cause of #44997.
* Remove unused import
* [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.
The open and close follower steps didn't check if the index is open,
closed respectively, before executing the open/close request.
This changes the steps to check the index state and only perform the
open/close operation if the index is not already open/closed.
This commit ensures that the creation of a DocumentSubsetReader does not
eagerly resolve the role query and the number of docs that match.
We want to delay this expensive operation in order to ensure that we really
need this information when we build it. For this reason the role query and the
number of docs are now resolved on demand. This commit also depends on
https://issues.apache.org/jira/browse/LUCENE-9003 that will also compute the global
number of docs lazily.
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
7.5+ for SLM requires [stats] object to exist in the cluster state.
When doing an in-place upgrade from 7.4 to 7.5+ [stats] does not exist
in cluster state, result in an exception on startup [1].
This commit moves the [stats] to be an optional object in the parser
and if not found will default to an empty stats object.
[1] Caused by: java.lang.IllegalArgumentException: Required [stats]
Reverting the change introducing IsoLocal.ROOT and introducing IsoCalendarDataProvider that defaults start of the week to Monday and requires minimum 4 days in first week of a year. This extension is using java SPI mechanism and defaults for Locale.ROOT only.
It require jvm property java.locale.providers to be set with SPI,COMPAT
closes#41670
backport #48209
This change adds a new field `"shards"` to `RepositoryData` that contains a mapping of `IndexId` to a `String[]`. This string array can be accessed by shard id to get the generation of a shard's shard folder (i.e. the `N` in the name of the currently valid `/indices/${indexId}/${shardId}/index-${N}` for the shard in question).
This allows for creating a new snapshot in the shard without doing any LIST operations on the shard's folder. In the case of AWS S3, this saves about 1/3 of the cost for updating an empty shard (see #45736) and removes one out of two remaining potential issues with eventually consistent blob stores (see #38941 ... now only the root `index-${N}` is determined by listing).
Also and equally if not more important, a number of possible failure modes on eventually consistent blob stores like AWS S3 are eliminated by moving all delete operations to the `master` node and moving from incremental naming of shard level index-N to uuid suffixes for these blobs.
This change moves the deleting of the previous shard level `index-${uuid}` blob to the master node instead of the data node allowing for a safe and consistent update of the shard's generation in the `RepositoryData` by first updating `RepositoryData` and then deleting the now unreferenced `index-${newUUID}` blob.
__No deletes are executed on the data nodes at all for any operation with this change.__
Note also: Previous issues with hanging data nodes interfering with master nodes are completely impossible, even on S3 (see next section for details).
This change changes the naming of the shard level `index-${N}` blobs to a uuid suffix `index-${UUID}`. The reason for this is the fact that writing a new shard-level `index-` generation blob is not atomic anymore in its effect. Not only does the blob have to be written to have an effect, it must also be referenced by the root level `index-N` (`RepositoryData`) to become an effective part of the snapshot repository.
This leads to a problem if we were to use incrementing names like we did before. If a blob `index-${N+1}` is written but due to the node/network/cluster/... crashes the root level `RepositoryData` has not been updated then a future operation will determine the shard's generation to be `N` and try to write a new `index-${N+1}` to the already existing path. Updates like that are problematic on S3 for consistency reasons, but also create numerous issues when thinking about stuck data nodes.
Previously stuck data nodes that were tasked to write `index-${N+1}` but got stuck and tried to do so after some other node had already written `index-${N+1}` were prevented form doing so (except for on S3) by us not allowing overwrites for that blob and thus no corruption could occur.
Were we to continue using incrementing names, we could not do this. The stuck node scenario would either allow for overwriting the `N+1` generation or force us to continue using a `LIST` operation to figure out the next `N` (which would make this change pointless).
With uuid naming and moving all deletes to `master` this becomes a non-issue. Data nodes write updated shard generation `index-${uuid}` and `master` makes those `index-${uuid}` part of the `RepositoryData` that it deems correct and cleans up all those `index-` that are unused.
Co-authored-by: Yannick Welsch <yannick@welsch.lu>
Co-authored-by: Tanguy Leroux <tlrx.dev@gmail.com>
FIPS 140 bootstrap checks should not be bootstrap checks as they
are always enforced. This commit moves the validation logic within
the security plugin.
The FIPS140SecureSettingsBootstrapCheck was not applicable as the
keystore was being loaded on init, before the Bootstrap checks
were checked, so an elasticsearch keystore of version < 3 would
cause the node to fail in a FIPS 140 JVM before the bootstrap check
kicked in, and as such hasn't been migrated.
Resolves: #34772
The enrich stats api picked the wrong task to be displayed
in the executing stats section.
In case `wait_for_completion` was set to `false` then no task
was being displayed and if that param was set to `true` then
the wrong task was being displayed (transport action task instead
of enrich policy executor task).
Testing executing policies in enrich stats api is tricky.
I have verified locally that this commit fixes the bug.
This PR adds an origin for the Enrich feature, and modifies the background
maintenance task to use the origin when executing client operations.
Without this fix, the maintenance task fails to execute when security is
enabled.
There is no reason to still resolve the
fallback `IndexId` here. It only applies to
`2.x` repos and those we can't read anymore
anyway because they use an `/index` instead of
an `/index-N` blob at the repo root for which
at least 7.x+ does not contain the logic to find
it.
* Add SLM support to xpack usage and info APIs
This is a backport of #48096
This adds the missing xpack usage and info information into the
`/_xpack` and `/_xpack/usage` APIs. The output now looks like:
```
GET /_xpack/usage
{
...
"slm" : {
"available" : true,
"enabled" : true,
"policy_count" : 1,
"policy_stats" : {
"retention_runs" : 0,
...
}
}
```
and
```
GET /_xpack
{
...
"features" : {
...
"slm" : {
"available" : true,
"enabled" : true
},
...
}
}
```
Relates to #43663
* Fix missing license
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
max_empty_searches = -1 in a datafeed update implies
max_empty_searches will be unset on the datafeed when
the update is applied. The isNoop() method needs to
take this -1 to null equivalence into account.
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 PR adds the ability to run the enrich policy execution task in the background,
returning a task id instead of waiting for the completed operation.
Currently, partial snapshots will eventually build up unless they are
manually deleted. Partial snapshots may be useful if there is not a more
recent successful snapshot, but should eventually be deleted if they are
no longer useful.
With this change, partial snapshots are deleted using the following
strategy: PARTIAL snapshots will be kept until the configured
expire_after period has passed, if present, and then be deleted. If
there is no configured expire_after in the retention policy, then they
will be deleted if there is at least one more recent successful snapshot
from this policy (as they may otherwise be useful for troubleshooting
purposes). Partial snapshots are not counted towards either min_count or
max_count.
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
Joda was using ResolverStyle.STRICT when parsing. This means that date will be validated to be a correct year, year-of-month, day-of-month
However, we also want to make it works with Year-Of-Era as Joda used to, hence custom temporalquery.localdate in DateFormatters.from
Within DateFormatters we use the correct uuuu year instead of yyyy year of era
worth noting: if yyyy(without an era) is used in code, the parsing result will be a TemporalAccessor which will fail to be converted into LocalDate. We mostly use DateFormatters.from so this takes care of this. If possible the uuuu format should be used.
Changes the execution logic to create a new task using the execute request,
and attaches the new task to the policy runner to be updated. Also, a new
response is now returned from the execute api, which contains either the task
id of the execution, or the completed status of the run. The fields are mutually
exclusive to make it easier to discern what type of response it is.
rename internal indexes of transform plugin
- rename audit index and create an alias for accessing it, BWC: add an alias for old indexes to
keep them working, kibana UI will switch to use the read alias
- rename config index and provide BWC to read from old and new ones
* Separate SLM stop/start/status API from ILM
This separates a start/stop/status API for SLM from being tied to ILM's
operation mode. These APIs look like:
```
POST /_slm/stop
POST /_slm/start
GET /_slm/status
```
This allows administrators to have fine-grained control over preventing
periodic snapshots and deletions while performing cluster maintenance.
Relates to #43663
* Allow going from RUNNING to STOPPED
* Align with the OperationMode rules
* Fix slmStopping method
* Make OperationModeUpdateTask constructor private
* Wipe snapshots better in test
Failed snapshots will eventually build up unless they are deleted. While
failures may not take up much space, they add noise to the list of
snapshots and it's desirable to remove them when they are no longer
useful.
With this change, failed snapshots are deleted using the following
strategy: `FAILED` snapshots will be kept until the configured
`expire_after` period has passed, if present, and then be deleted. If
there is no configured `expire_after` in the retention policy, then they
will be deleted if there is at least one more recent successful snapshot
from this policy (as they may otherwise be useful for troubleshooting
purposes). Failed snapshots are not counted towards either `min_count`
or `max_count`.
When exceptions could be returned from another node, the exception
might be wrapped in a `RemoteTransportException`. In places where
we handled specific exceptions using `instanceof` we ought to unwrap
the cause first.
This commit attempts to fix this issue after searching code in the ML
plugin.
Backport of #47676
this commit introduces a geo-match enrich processor that looks up a specific
`geo_point` field in the enrich-index for all entries that have a geo_shape match field
that meets some specific relation criteria with the input field.
For example, the enrich index may contain documents with zipcodes and their respective
geo_shape. Ingesting documents with a geo_point field can be enriched with which zipcode
they associate according to which shape they are contained within.
this commit also refactors some of the MatchProcessor by moving a lot of the shared code to
AbstractEnrichProcessor.
Closes#42639.
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
An index with an ILM policy that has a rollover action in one of the
phases was rolled over when the ILM conditions dictated regardless if
it was already rolled over (eg. manually after modifying an index
template in order to force the creation of a new index that uses the new
mappings).
This changes this behaviour and has ILM check if the index it's about to
roll has not been rolled over in the meantime.
(cherry picked from commit 37d6106feeb9f9369519117c88a9e7e30f3ac797)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This adds a default for the `slm.retention_schedule` setting, setting it
to `0 30 1 * * ?` which is 1:30am every day.
Having retention unset meant that it would never be invoked and clean up
snapshots. We determined it would be better to have a default than never
to be run. When coming to a decision, we weighed the option of an
absolute time (such as 1:30am) versus a periodic invocation (like every
12 hours). In the end we decided on the absolute time because it has
better predictability and consistency than a periodic invocation, which
would rely on when the master node were elected or restarted.
Relates to #43663
When an ML job runs the memory required can be
broken down into:
1. Memory required to load the executable code
2. Instrumented model memory
3. Other memory used by the job's main process or
ancilliary processes that is not instrumented
Previously we added a simple fixed overhead to
account for 1 and 3. This was 100MB for anomaly
detection jobs (large because of the completely
uninstrumented categorization function and
normalize process), and 20MB for data frame
analytics jobs.
However, this was an oversimplification because
the executable code only needs to be loaded once
per machine. Also the 100MB overhead for anomaly
detection jobs was probably too high in most cases
because categorization and normalization don't use
_that_ much memory.
This PR therefore changes the calculation of memory
requirements as follows:
1. A per-node overhead of 30MB for _only_ the first
job of any type to be run on a given node - this
is to account for loading the executable code
2. The established model memory (if applicable) or
model memory limit of the job
3. A per-job overhead of 10MB for anomaly detection
jobs and 5MB for data frame analytics jobs, to
account for the uninstrumented memory usage
This change will enable more jobs to be run on the
same node. It will be particularly beneficial when
there are a large number of small jobs. It will
have less of an effect when there are a small number
of large jobs.
* 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
* Fix AllocationRoutedStepTests.testConditionMetOnlyOneCopyAllocated
These tests were using randomly generated includes/excludes/requires for
routing, however, it was possible to generate mutually exclusive
allocation settings (about 1 out of 50,000 times for my runs).
This splits the test into three different tests, and removes the
randomization (it doesn't add anything to the testing here) to fix the
issue.
Resolves#47142
While it seemed like the PUT data frame analytics action did not
have to be a master node action as the config is stored in an index
rather than the cluster state, there are other subtle nuances which
make it worthwhile to convert it. In particular, it helps maintain
order of execution for put actions which are anyhow user driven and
are expected to have low volume.
This commit converts `TransportPutDataFrameAnalyticsAction` from
a handled transport action to a master node action.
Note this means that the action might fail in a mixed cluster
but as the API is still experimental and not widely used there will
be few moments more suitable to make this change than now.
Bulk requests currently do not allow adding "create" actions with auto-generated IDs.
This commit allows using the optype CREATE for append-only indexing operations. This is
mainly the user facing aspect of it.
Due to #47003 many clusters will have built up a
large backlog of expired results. On upgrading to
a version where that bug is fixed users could find
that the first ML daily maintenance task deletes
a very large amount of documents.
This change introduces throttling to the
delete-by-query that the ML daily maintenance uses
to delete expired results to limit it to deleting an
average 200 documents per second. (There is no
throttling for state/forecast documents as these
are expected to be lower volume.)
Additionally a rough time limit of 8 hours is applied
to the whole delete expired data action. (This is only
rough as it won't stop part way through a single
operation - it only checks the timeout between
operations.)
Relates #47103
This commit restores the model state if available in data
frame analytics jobs.
In addition, this changes the start API so that a stopped job
can be restarted. As we now store the progress in the state index
when the task is stopped, we can use it to determine what state
the job was in when it got stopped.
Note that in order to be able to distinguish between a job
that runs for the first time and another that is restarting,
we ensure reindexing progress is reported to be at least 1
for a running task.
Due to a regression bug the metadata Active Directory realm
setting is ignored (it works correctly for the LDAP realm type).
This commit redresses it.
Closes#45848
* [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
As a result of #45689 snapshot finalization started to
take significantly longer than before. This may be a
little unfortunate since it increases the likelihood
of failing to finalize after having written out all
the segment blobs.
This change parallelizes all the metadata writes that
can safely run in parallel in the finalization step to
speed the finalization step up again. Also, this will
generally speed up the snapshot process overall in case
of large number of indices.
This is also a nice to have for #46250 since we add yet
another step (deleting of old index- blobs in the shards
to the finalization.
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
These settings were using get raw to fallback to whether or not SSL is
enabled. Yet, we have a formal mechanism for falling back to a
setting. This commit cuts over to that formal mechanism.
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
Drop the usage of `SimpleDateFormat` and use the `DateFormatter` instead
(cherry picked from commit 7cf509a7a11ecf6c40c44c18e8f03b8e81fcd1c2)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This change also slightly modifies the stats response,
so that is can easier consumer by monitoring and other
users. (coordinators stats are now in a list instead of
a map and has an additional field for the node id)
Relates to #32789
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
* ILM: parse origination date from index name (#46755)
Introduce the `index.lifecycle.parse_origination_date` setting that
indicates if the origination date should be parsed from the index name.
If set to true an index which doesn't match the expected format (namely
`indexName-{dateFormat}-optional_digits` will fail before being created.
The origination date will be parsed when initialising a lifecycle for an
index and it will be set as the `index.lifecycle.origination_date` for
that index.
A user set value for `index.lifecycle.origination_date` will always
override a possible parsable date from the index name.
(cherry picked from commit c363d27f0210733dad0c307d54fa224a92ddb569)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
* Drop usage of Map.of to be java 8 compliant
* Wait for snapshot completion in SLM snapshot invocation
This changes the snapshots internally invoked by SLM to wait for
completion. This allows us to capture more snapshotting failure
scenarios.
For example, previously a snapshot would be created and then registered
as a "success", however, the snapshot may have been aborted, or it may
have had a subset of its shards fail. These cases are now handled by
inspecting the response to the `CreateSnapshotRequest` and ensuring that
there are no failures. If any failures are present, the history store
now stores the action as a failure instead of a success.
Relates to #38461 and #43663
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
This change allows for the caller of the `saml/prepare` API to pass
a `relay_state` parameter that will then be part of the redirect
URL in the response as the `RelayState` query parameter.
The SAML IdP is required to reflect back the value of that relay
state when sending a SAML Response. The caller of the APIs can
then, when receiving the SAML Response, read and consume the value
as it see fit.
Previously, queries on the _index field were not able to specify index aliases.
This was a regression in functionality compared to the 'indices' query that was
deprecated and removed in 6.0.
Now queries on _index can specify an alias, which is resolved to the concrete
index names when we check whether an index matches. To match a remote shard
target, the pattern needs to be of the form 'cluster:index' to match the
fully-qualified index name. Index aliases can be specified in the following query
types: term, terms, prefix, and wildcard.
This commit changes the GET REST api so it will accept an optional comma
separated list of enrich policy ids. This change also modifies the
behavior of the GET API in that it will not error if it is passed a bad
enrich id anymore, but will instead just return an empty list.
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)
The enrich api returns enrich coordinator stats and
information about currently executing enrich policies.
The coordinator stats include per ingest node:
* The current number of search requests in the queue.
* The total number of outstanding remote requests that
have been executed since node startup. Each remote
request is likely to include multiple search requests.
This depends on how much search requests are in the
queue at the time when the remote request is performed.
* The number of current outstanding remote requests.
* The total number of search requests that `enrich`
processors have executed since node startup.
The current execution policies stats include:
* The name of policy that is executing
* A full blow task info object that is executing the policy.
Relates to #32789
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
The previous transport action was a read action, which under the right
set of circumstances can execute on a coordinating node. This commit
ensures that cannot happen.
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
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).
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
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
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.
* [ML][Data frame] fixing failure state transitions and race condition (#45627)
There is a small window for a race condition while we are flagging a task as failed.
Here are the steps where the race condition occurs:
1. A failure occurs
2. Before `AsyncTwoPhaseIndexer` calls the `onFailure` handler it does the following:
a. `finishAndSetState()` which sets the IndexerState to STARTED
b. `doSaveState(...)` which attempts to save the current state of the indexer
3. Another trigger is fired BEFORE `onFailure` can fire, but AFTER `finishAndSetState()` occurs.
The trick here is that we will eventually set the indexer to failed, but possibly not before another trigger had the opportunity to fire. This could obviously cause some weird state interactions. To combat this, I have put in some predicates to verify the state before taking actions. This is so if state is indeed marked failed, the "second trigger" stops ASAP.
Additionally, I move the task state checks INTO the `start` and `stop` methods, which will now require a `force` parameter. `start`, `stop`, `trigger` and `markAsFailed` are all `synchronized`. This should gives us some guarantees that one will not switch states out from underneath another.
I also flag the task as `failed` BEFORE we successfully write it to cluster state, this is to allow us to make the task fail more quickly. But, this does add the behavior where the task is "failed" but the cluster state does not indicate as much. Adding the checks in `start` and `stop` will handle this "real state vs cluster state" race condition. This has always been a problem for `_stop` as it is not a master node action and doesn’t always have the latest cluster state.
closes#45609
Relates to #45562
* [ML][Data Frame] moves failure state transition for MT safety (#45676)
* [ML][Data Frame] moves failure state transition for MT safety
* removing unused imports
* Introduce Spatial Plugin (#44389)
Introduce a skeleton Spatial plugin that holds new licensed features coming to
Geo/Spatial land!
* [GEO] Refactor DeprecatedParameters in AbstractGeometryFieldMapper (#44923)
Refactor DeprecatedParameters specific to legacy geo_shape out of
AbstractGeometryFieldMapper.TypeParser#parse.
* [SPATIAL] New ShapeFieldMapper for indexing cartesian geometries (#44980)
Add a new ShapeFieldMapper to the xpack spatial module for
indexing arbitrary cartesian geometries using a new field type called shape.
The indexing approach leverages lucene's new XYShape field type which is
backed by BKD in the same manner as LatLonShape but without the WGS84
latitude longitude restrictions. The new field mapper builds on and
extends the refactoring effort in AbstractGeometryFieldMapper and accepts
shapes in either GeoJSON or WKT format (both of which support non geospatial
geometries).
Tests are provided in the ShapeFieldMapperTest class in the same manner
as GeoShapeFieldMapperTests and LegacyGeoShapeFieldMapperTests.
Documentation for how to use the new field type and what parameters are
accepted is included. The QueryBuilder for searching indexed shapes is
provided in a separate commit.
* [SPATIAL] New ShapeQueryBuilder for querying indexed cartesian geometry (#45108)
Add a new ShapeQueryBuilder to the xpack spatial module for
querying arbitrary Cartesian geometries indexed using the new shape field
type.
The query builder extends AbstractGeometryQueryBuilder and leverages the
ShapeQueryProcessor added in the previous field mapper commit.
Tests are provided in ShapeQueryTests in the same manner as
GeoShapeQueryTests and docs are updated to explain how the query works.
Dimitris Athanasiou
Armin Braun
Ioannis Kakavas
Tim Vernum
Przemysław Witek
Przemyslaw Gomulka
j-bean
Tim Brooks
David Roberts
Benjamin Trent
Mark Tozzi
Julie Tibshirani
Hendrik Muhs
Rory Hunter
Lee Hinman
Andrei Dan
Jim Ferenczi
Michael Basnight
Jake Landis
Martijn van Groningen
James Baiera
rsarawgi
Gordon Brown
Tanguy Leroux
Yogesh Gaikwad
Chris Roberson
Tal Levy
Alpar Torok
Yannick Welsch
Albert Zaharovits
Jason Tedor
Oliver Gupte
Luca Cavanna
James Rodewig
Andrey Ershov
Zachary Tong
Albert Zaharovits
markharwood
Tim Vernum
Nick Knize