DeprecationLogger's constructor should not create two loggers. It was
taking parent logger instance, changing its name with a .deprecation
prefix and creating a new logger.
Most of the time parent logger was not needed. It was causing Log4j to
unnecessarily cache the unused parent logger instance.
depends on #61515
backports #58435
Splitting DeprecationLogger into two. HeaderWarningLogger - responsible for adding a response warning headers and ThrottlingLogger - responsible for limiting the duplicated log entries for the same key (previously deprecateAndMaybeLog).
Introducing A ThrottlingAndHeaderWarningLogger which is a base for other common logging usages where both response warning header and logging throttling was needed.
relates #55699
relates #52369
backports #55941
The API key document currently doesn't include the user's full_name or email attributes,
and as a result, when those attributes return `null` when hitting `GET`ing `/_security/_authenticate`,
and in the SAML response from the [IdP Plugin](https://github.com/elastic/elasticsearch/pull/54046).
This changeset adds those fields to the document and extracts them to fill in the User when
authenticating. They're effectively going to be a snapshot of the User from when the key was
created, but this is in line with roles and metadata as well.
Signed-off-by: lloydmeta <lloydmeta@gmail.com>
feature_processors allow users to create custom features from
individual document fields.
These `feature_processors` are the same object as the trained model's pre_processors.
They are passed to the native process and the native process then appends them to the
pre_processor array in the inference model.
closes https://github.com/elastic/elasticsearch/issues/59327
When the ML annotations index was first added, only the
ML UI wrote to it, so the code to create it was designed
with this in mind. Now the ML backend also creates
annotations, and those mappings can change between
versions.
In this change:
1. The code that runs on the master node to create the
annotations index if it doesn't exist but another ML
index does also now ensures the mappings are up-to-date.
This is good enough for the ML UI's use of the
annotations index, because the upgrade order rules say
that the whole Elasticsearch cluster must be upgraded
prior to Kibana, so the master node should be on the
newer version before Kibana tries to write an
annotation with the new fields.
2. We now also check whether the annotations index exists
with the correct mappings before starting an autodetect
process on a node. This is necessary because ML nodes
can be upgraded before the master node, so could write
an annotation with the new fields before the master node
knows about the new fields.
Backport of #61107
This commit adds the `data_hot`, `data_warm`, `data_cold`, and `data_frozen` node roles to the
x-pack plugin. These roles are intended to be the base for the formalization of data tiers in
Elasticsearch.
These roles all act as data nodes (meaning shards can be allocated to them). Nodes with the existing
`data` role acts as though they have all of the roles configured (it is a hot, warm, cold, and
frozen node).
This also includes a custom `AllocationDecider` that allows the user to configure the following
settings on a cluster level:
- `cluster.routing.allocation.require._tier`
- `cluster.routing.allocation.include._tier`
- `cluster.routing.allocation.exclude._tier`
And in index settings:
- `index.routing.allocation.require._tier`
- `index.routing.allocation.include._tier`
- `index.routing.allocation.exclude._tier`
Relates to #60848
This adds a frozen phase to ILM that will allow the execution of the
set_priority, unfollow, allocate, freeze and searchable_snapshot actions.
The frozen phase will be executed after the cold and before the delete phase.
(cherry picked from commit 6d0148001c3481290ed7e60dab588e0191346864)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
`foreach` processors store information within the `_ingest` metadata object.
This commit adds the contents of the `_ingest` metadata (if it is not empty).
And will append new inference results if the result field already exists.
This allows a `foreach` to execute and multiple inference results being written to the same result field.
closes https://github.com/elastic/elasticsearch/issues/60867
Use thread-local buffers and deflater and inflater instances to speed up
compressing and decompressing from in-memory bytes.
Not manually invoking `end()` on these should be safe since their off-heap memory
will eventually be reclaimed by the finalizer thread which should not be an issue for thread-locals
that are not instantiated at a high frequency.
This significantly reduces the amount of byte copying and object creation relative to the previous approach
which had to create a fresh temporary buffer (that was then resized multiple times during operations), copied
bytes out of that buffer to a freshly allocated `byte[]`, used 4k stream buffers needlessly when working with
bytes that are already in arrays (`writeTo` handles efficient writing to the compression logic now) etc.
Relates #57284 which should be helped by this change to some degree.
Also, I expect this change to speed up mapping/template updates a little as those make heavy use of these
code paths.
This adds a force-merge step to the searchable snapshot action, enabled by default,
but parameterizable using the `force_merge-index" optional boolean.
eg.
```
PUT _ilm/policy/my_policy
{
"policy": {
"phases": {
"cold": {
"actions": {
"searchable_snapshot" : {
"snapshot_repository" : "backing_repo",
"force_merge_index": true
}
}
}
}
}
}
```
(cherry picked from commit d0a17b2d35f1b083b574246bdbf3e1929471a4a9)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
remove test, scripts are excluded in the change collector, the test is a leftover from a previous
solution of #57332, which has been discarded
relates #60724fixes#60794
This pull request adds recovery state tracking for Searchable Snapshots.
In order to track recoveries for searchable snapshot backed indices, this pull
request adds a new type of RecoveryState.
This newRecoveryState instance is able to deal with the
small differences that arise during Searchable snapshots recoveries.
Those differences can be summarized as follows:
- The Directory implementation that's provided by SearchableSnapshots mark the
snapshot files as reused during recovery. In order to keep track of the
recovery process as the cache is pre-warmed, those files shouldn't be marked
as reused.
- Once the shard is created, the cache starts its pre-warming phase, meaning that
we should keep track of those downloads during that process and tie the recovery
to this pre-warming phase. The shard is considered recovered once this pre-warming
phase has finished.
Backport of #60505
disable optimizations when using scripts in group_by, when scripts using scripts we can not predict
the outcome and we have no query counterpart. Other optimizations for other group_by's are not
affected.
fixes#57332
Implements license degradation behavior for searchable snapshots. Snapshot-backed shards are failed when the license becomes invalid, and shards won't be reallocated. After valid license is put in place again, shards are allocated again.
We have various ways of copying between two streams and handling thread-local
buffers throughout the codebase. This commit unifies a number of them and
removes buffer allocations in many spots.
- Replace immediate task creations by using task avoidance api
- One step closer to #56610
- Still many tasks are created during configuration phase. Tackled in separate steps
In order to unify model inference and analytics results we
need to write the same fields.
prediction_probability and prediction_score are now written
for inference calls against classification models.
If a feature is created via a custom pre-processor,
we should return the importance for that feature.
This means we will not return the importance for the
original document field for custom processed features.
closes https://github.com/elastic/elasticsearch/issues/59330
Putting an ingest pipeline used to require that the user calling
it had permission to get nodes info as well as permission to
manage ingest. This was due to an internal implementaton detail
that was not visible to the end user.
This change alters the behaviour so that a user with the
manage_pipeline cluster privilege can put an ingest pipeline
regardless of whether they have the separate privilege to get
nodes info. The internal implementation detail now runs as
the internal _xpack user when security is enabled.
Backport of #60106
This PR removes the expand_wildcards and forbid_closed_indices parameters from the Data
Streams Stats REST endpoint. These options are required for broadcast requests, but are not
needed for anything in terms of resolving data streams. Instead, we just set a default set of
IndicesOptions on the transport request.
* Adding new `require_alias` option to indexing requests (#58917)
This commit adds the `require_alias` flag to requests that create new documents.
This flag, when `true` prevents the request from automatically creating an index. Instead, the destination of the request MUST be an alias.
When the flag is not set, or `false`, the behavior defaults to the `action.auto_create_index` settings.
This is useful when an alias is required instead of a concrete index.
closes https://github.com/elastic/elasticsearch/issues/55267
* [ML] add new `custom` field to trained model processors (#59542)
This commit adds the new configurable field `custom`.
`custom` indicates if the preprocessor was submitted by a user or automatically created by the analytics job.
Eventually, this field will be used in calculating feature importance. When `custom` is true, the feature importance for
the processed fields is calculated. When `false` the current behavior is the same (we calculate the importance for the originating field/feature).
This also adds new required methods to the preprocessor interface. If users are to supply their own preprocessors
in the analytics job configuration, we need to know the input and output field names.
Backport of #59525 to 7.x branch.
* Actions are moved to xpack core.
* Transport and rest actions are moved the data-streams module.
* Removed data streams methods from Client interface.
* Adjusted tests to use client.execute(...) instead of data stream specific methods.
* only attempt to delete all data streams if xpack is installed in rest tests
* Now that ds apis are in xpack and ESIntegTestCase
no longers deletes all ds, do that in the MlNativeIntegTestCase
class for ml tests.
Since #58728 writing operations on searchable snapshot directory cache files
are executed in an asynchronous manner using a dedicated thread pool. The
thread pool used is searchable_snapshots which has been created to execute
prewarming tasks.
Reusing the same thread pool wasn't a good idea as it can lead to deadlock
situations. One of these situation arose in a test failure where the thread pool
was full of prewarming tasks, all waiting for a cache file to be accessible, while
the cache file was being evicted by the cache service. But such an eviction
can only be processed when all read/write operations on the cache file are
completed and in this case the deadlock occurred because the cache file was
actively being read by a concurrent search which also won the privilege to
write the range of bytes in cache... and this writing operation could never have
been completed because of the prewarming tasks making no progress and
filling up the thread pool.
This commit renames the searchable_snapshots thread pool to
searchable_snapshots_cache_fetch_async. Assertions are added to assert
that cache writes are executed using this thread pool and to assert that read
on cached index inputs are executed using a different thread pool to avoid
potential deadlock situations.
This commit also adds a searchable_snapshots_cache_prewarming that is
used to execute prewarming tasks. It also converts the existing cache prewarming
test into a more complte integration test that creates multiple searchable
snapshot indices concurrently with randomized thread pool sizes, and verifies
that all files have been correctly prewarmed.
Many of the parameters we pass into this method were only used to
build the `SnapshotInfo` instance to write.
This change simplifies the signature. Also, it seems less error prone to build
`SnapshotInfo` in `SnapshotsService` isntead of relying on the fact that each repository
implementation will build the correct `SnapshotInfo`.
This commit adds a new api to track when gold+ features are used within
x-pack. The tracking is done internally whenever a feature is checked
against the current license. The output of the api is a list of each
used feature, which includes the name, license level, and last time it
was used. In addition to a unit test for the tracking, a rest test is
added which ensures starting up a default configured node does not
result in any features registering as used.
There are a couple features which currently do not work well with the
tracking, as they are checked in a manner that makes them look always
used. Those features will be fixed in followups, and in this PR they are
omitted from the feature usage output.
The `create_doc`, `create`, `write` and `index` privileges do not grant
the PutMapping action anymore. Apart from the `write` privilege, the other
three privileges also do NOT grant (auto) updating the mapping when ingesting
a document with unmapped fields, according to the templates.
In order to maintain the BWC in the 7.x releases, the above privileges will still grant
the Put and AutoPutMapping actions, but only when the "index" entity is an alias
or a concrete index, but not a data stream or a backing index of a data stream.
This PR introduces two new fields in to `RepositoryData` (index-N) to track the blob name of `IndexMetaData` blobs and their content via setting generations and uuids. This is used to deduplicate the `IndexMetaData` blobs (`meta-{uuid}.dat` in the indices folders under `/indices` so that new metadata for an index is only written to the repository during a snapshot if that same metadata can't be found in another snapshot.
This saves one write per index in the common case of unchanged metadata thus saving cost and making snapshot finalization drastically faster if many indices are being snapshotted at the same time.
The implementation is mostly analogous to that for shard generations in #46250 and piggy backs on the BwC mechanism introduced in that PR (which means this PR needs adjustments if it doesn't go into `7.6`).
Relates to #45736 as it improves the efficiency of snapshotting unchanged indices
Relates to #49800 as it has the potential of loading the index metadata for multiple snapshots of the same index concurrently much more efficient speeding up future concurrent snapshot delete
The primary shards of follower indices during the bootstrap need to be
on nodes with the remote cluster client role as those nodes reach out to
the corresponding leader shards on the remote cluster to copy Lucene
segment files and renew the retention leases. This commit introduces a
new allocation decider that ensures bootstrapping follower primaries are
allocated to nodes with the remote cluster client role.
Co-authored-by: Jason Tedor <jason@tedor.me>
This makes the data_stream timestamp field specification optional when
defining a composable template.
When there isn't one specified it will default to `@timestamp`.
(cherry picked from commit 5609353c5d164e15a636c22019c9c17fa98aac30)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
separate pivot from the indexer and introduce an abstraction layer, pivot becomes a function.
Foundation to add more functions to transform.
piggy backed fixes:
- when running geo tile group_by it could fail due to query clause limit (unreleased)
- new style page size using settings was not validating limit of 10k (7.8)
This commit adds data stream info to the `/_xpack` and `/_xpack/usage` APIs. Currently the usage is
pretty minimal, returning only the number of data streams and the number of indices currently
abstracted by a data stream:
```
...
"data_streams" : {
"available" : true,
"enabled" : true,
"data_streams" : 3,
"indices_count" : 17
}
...
```
With the introduction of per-partition categorization the old
logic for creating a job notification for categorization status
"warn" does not work. However, the C++ code is already writing
annotations for categorization status "warn" that take into
account whether per-partition categorization is being used and
which partition(s) the warnings relate to. Therefore, this
change alters the Java results processor to create notifications
based on the annotations the C++ writes. (It is arguable that
we don't need both annotations and notifications, but they show
up in different ways in the UI: only annotations are visible in
results and only notifications set the warning symbol in the
jobs list. This means it's best to have both.)
Backport of #59377
This PR ensure that same roles are cached only once even when they are from different API keys.
API key role descriptors and limited role descriptors are now saved in Authentication#metadata
as raw bytes instead of deserialised Map<String, Object>.
Hashes of these bytes are used as keys for API key roles. Only when the required role is not found
in the cache, they will be deserialised to build the RoleDescriptors. The deserialisation is directly
from raw bytes to RoleDescriptors without going through the current detour of
"bytes -> Map -> bytes -> RoleDescriptors".
This adds a setting to data frame analytics jobs called
`max_number_threads`. The setting expects a positive integer.
When used the user specifies the max number of threads that may
be used by the analysis. Note that the actual number of threads
used is limited by the number of processors on the node where
the job is assigned. Also, the process may use a couple more threads
for operational functionality that is not the analysis itself.
This setting may also be updated for a stopped job.
More threads may reduce the time it takes to complete the job at the cost
of using more CPU.
Backport of #59254 and #57274
Since we are able to load the inference model
and perform inference in java, we no longer need
to rely on the analytics process to be performing
test inference on the docs that were not used for
training. The benefit is that we do not need to
send test docs and fit them in memory of the c++
process.
Backport of #58877
Co-authored-by: Dimitris Athanasiou <dimitris@elastic.co>
Co-authored-by: Benjamin Trent <ben.w.trent@gmail.com>
1. Add the `apikey.id`, `apikey.name` and `authentication.type` fields
to the `access_granted`, `access_denied`, `authentication_success`, and
(some) `tampered_request` audit events. The `apikey.id` and `apikey.name`
are present only when authn using an API Key.
2. When authn with an API Key, the `user.realm` field now contains the effective
realm name of the user that created the key, instead of the synthetic value of
`_es_api_key`.
Backport of #59076 to 7.x branch.
The commit makes the following changes:
* The timestamp field of a data stream definition in a composable
index template can only be set to '@timestamp'.
* Removed custom data stream timestamp field validation and reuse the validation from `TimestampFieldMapper` and
instead only check that the _timestamp field mapping has been defined on a backing index of a data stream.
* Moved code that injects _timestamp meta field mapping from `MetadataCreateIndexService#applyCreateIndexRequestWithV2Template58956(...)` method
to `MetadataIndexTemplateService#collectMappings(...)` method.
* Fixed a bug (#58956) that cases timestamp field validation to be performed
for each template and instead of the final mappings that is created.
* only apply _timestamp meta field if index is created as part of a data stream or data stream rollover,
this fixes a docs test, where a regular index creation matches (logs-*) with a template with a data stream definition.
Relates to #58642
Relates to #53100Closes#58956Closes#58583
Today we empty the searchable snapshots cache when cleanly closing a
shard, but leak cache files in some cases involving an unclean shutdown.
Such leaks are not permanent, they are cleaned up on shard relocation or
deletion, but they still might last for arbitrarily long until that
happens. This commit introduces a cleanup process that runs during node
startup to catch such leaks sooner.
Also, today we permit searchable snapshots to be held on custom data
paths, and store the corresponding cache files within the custom
location. Supporting this feature would make the cleanup process
significantly more complicated since it would require each node to parse
the index metadata for the shards it held before shutdown. Yet, this
feature is undocumented and offers minimal benefits to searchable
snapshots. Therefore with this commit we forbid custom data paths for
searchable snapshot shards.
The composite role that is used for authz, following the authn with an API key,
is an intersection of the privileges from the owner role and the key privileges defined
when the key has been created.
This change ensures that the `#names` property of such a role equals the `#names`
property of the key owner role, thereby rectifying the value for the `user.roles`
audit event field.
There have been a few test failures that are likely caused by tests
performing actions that use ML indices immediately after the actions
that create those ML indices. Currently this can result in attempts
to search the newly created index before its shards have initialized.
This change makes the method that creates the internal ML indices
that have been affected by this problem (state and stats) wait for
the shards to be initialized before returning.
Backport of #59027
- The exception that we caught when failing to schedule a thread was incorrect.
- We may have failures when reducing the response before returning it, which were not handled correctly and may have caused get or submit async search task to not be properly unregistered from the task manager
- when the completion listener onFailure method is invoked, the search task has to be unregistered. Not doing so may cause the search task to be stuck in the task manager although it has completed.
Closes#58995
Add caching support for application privileges to reduce number of round-trips to security index when building application privilege descriptors.
Privilege retrieving in NativePrivilegeStore is changed to always fetching all privilege documents for a given application. The caching is applied to all places including "get privilege", "has privileges" APIs and CompositeRolesStore (for authentication).
* [ML] handles compressed model stream from native process (#58009)
This moves model storage from handling the fully parsed JSON string to handling two separate types of documents.
1. ModelSizeInfo which contains model size information
2. TrainedModelDefinitionChunk which contains a particular chunk of the compressed model definition string.
`model_size_info` is assumed to be handled first. This will generate the model_id and store the initial trained model config object. Then each chunk is assumed to be in correct order for concatenating the chunks to get a compressed definition.
Native side change: https://github.com/elastic/ml-cpp/pull/1349
The checks on the license state have a singular method, isAllowed, that
returns whether the given feature is allowed by the current license.
However, there are two classes of usages, one which intends to actually
use a feature, and another that intends to return in telemetry whether
the feature is allowed. When feature usage tracking is added, the latter
case should not count as a "usage", so this commit reworks the calls to
isAllowed into 2 methods, checkFeature, which will (eventually) both
check whether a feature is allowed, and keep track of the last usage
time, and isAllowed, which simply determines whether the feature is
allowed.
Note that I considered having a boolean flag on the current method, but
wanted the additional clarity that a different method name provides,
versus a boolean flag which is more easily copied without realizing what
the flag means since it is nameless in call sites.
Restoring from a snapshot (which is a particular form of recovery) does not currently take recovery throttling into account
(i.e. the `indices.recovery.max_bytes_per_sec` setting). While restores are subject to their own throttling (repository
setting `max_restore_bytes_per_sec`), this repository setting does not allow for values to be configured differently on a
per-node basis. As restores are very similar in nature to peer recoveries (streaming bytes to the node), it makes sense to
configure throttling in a single place.
The `max_restore_bytes_per_sec` setting is also changed to default to unlimited now, whereas previously it was set to
`40mb`, which is the current default of `indices.recovery.max_bytes_per_sec`). This means that no behavioral change
will be observed by clusters where the recovery and restore settings were not adapted.
Relates https://github.com/elastic/elasticsearch/issues/57023
Co-authored-by: James Rodewig <james.rodewig@elastic.co>
SAML idP sends back a LogoutResponse at the end of the logout workflow. It can be sent via either HTTP-Redirect binding or HTTP-POST binding. Currently, the HTTP-Redirect request is simply ignored by Kibana and never reaches ES. It does not cause any obvious issue and the workflow is completed normally from user's perspective.
The HTTP-POST request results in a 404 error because POST request is not accepted by Kibana's logout end-point. This causes a non-trivial issue because it renders an error page in user's browser. In addition, some resources do not seem to be fully cleaned up due to the error, e.g. the username will be pre-filled when trying to login again after the 404 error.
This PR solves both of the above issues from ES side with a new /_security/saml/complete_logout end-point. Changes are still needed on Kibana side to relay the messages.
Backport of #58419
Mapping updates that originate from indexing a document with unmapped fields will use this new action
instead of the current put mapping action. This way on the security side, authorization logic
can easily determine whether a mapping update is automatically generated or a mapping update originates
from the put mapping api.
The new auto put mapping action is only used if all nodes are on the version that supports it.
When per_partition_categorization.stop_on_warn is set for an analysis
config it is now passed through to the autodetect C++ process.
Also adds some end-to-end tests that exercise the functionality
added in elastic/ml-cpp#1356
Backport of #58632
* Replace compile configuration usage with api (#58451)
- Use java-library instead of plugin to allow api configuration usage
- Remove explicit references to runtime configurations in dependency declarations
- Make test runtime classpath input for testing convention
- required as java library will by default not have build jar file
- jar file is now explicit input of the task and gradle will ensure its properly build
* Fix compile usages in 7.x branch
The GET /_license endpoint displays "enterprise" licenses as
"platinum" by default so that old clients (including beats, kibana and
logstash) know to interpret this new license type as if it were a
platinum license.
However, this compatibility layer was not applied to the GET /_xpack/
endpoint which also displays a license type & mode.
This commit causes the _xpack API to mimic the _license API and treat
enterprise as platinum by default, with a new accept_enterprise
parameter that will cause the API to return the correct "enterprise"
value.
This BWC layer exists only for the 7.x branch.
This is a breaking change because, since 7.6, the _xpack API has
returned "enterprise" for enterprise licenses, but this has been found
to break old versions of beats and logstash so needs to be corrected.
The remote_monitoring_user user needs to access the enrich stats API.
But the request is denied because the API is categorized under admin.
The correct privilege should be monitor.
Adds parsing of `status` and `memory_reestimate_bytes`
to data frame analytics `memory_usage`. When the training surpasses
the model memory limit, the status will be set to `hard_limit` and
`memory_reestimate_bytes` can be used to update the job's
limit in order to restart the job.
Backport of #58588
In SLM retention, when a minimum number of snapshots is required for retention, we prefer to remove
the oldest snapshots first. To perform this, we limit one of the streams, in a rare case this can
cause:
```
[mynode] error during snapshot retention task
java.lang.IllegalArgumentException: -5
at java.util.stream.ReferencePipeline.limit(ReferencePipeline.java:469) ~[?:?]
at org.elasticsearch.xpack.core.slm.SnapshotRetentionConfiguration.lambda$getSnapshotDeletionPredicate$6(SnapshotRetentionConfiguration.java:195) ~[?:?]
at org.elasticsearch.xpack.slm.SnapshotRetentionTask.snapshotEligibleForDeletion(SnapshotRetentionTask.java:245) ~[?:?]
at org.elasticsearch.xpack.slm.SnapshotRetentionTask$1.lambda$onResponse$0(SnapshotRetentionTask.java:163) ~[?:?]
at java.util.stream.ReferencePipeline$2$1.accept(ReferencePipeline.java:176) ~[?:?]
at java.util.ArrayList$ArrayListSpliterator.forEachRemaining(ArrayList.java:1624) ~[?:?]
at java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:484) ~[?:?]
at java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:474) ~[?:?]
at java.util.stream.ReduceOps$ReduceOp.evaluateSequential(ReduceOps.java:913) ~[?:?]
```
When certain criteria are met. This commit fixes the negative limiting with `Math.max(0, ...)` and
adds a unit test for the behavior.
Resolves#58515
Rather than let ExtensiblePlugins know extending plugins' classloaders,
we now pass along an explicit ExtensionLoader that loads the extensions
asked for. Extensions constructed that way can optionally receive their
own Plugin instance in the constructor.
Today we have individual settings for configuring node roles such as
node.data and node.master. Additionally, roles are pluggable and we have
used this to introduce roles such as node.ml and node.voting_only. As
the number of roles is growing, managing these becomes harder for the
user. For example, to create a master-only node, today a user has to
configure:
- node.data: false
- node.ingest: false
- node.remote_cluster_client: false
- node.ml: false
at a minimum if they are relying on defaults, but also add:
- node.master: true
- node.transform: false
- node.voting_only: false
If they want to be explicit. This is also challenging in cases where a
user wants to have configure a coordinating-only node which requires
disabling all roles, a list which we are adding to, requiring the user
to keep checking whether a node has acquired any of these roles.
This commit addresses this by adding a list setting node.roles for which
a user has explicit control over the list of roles that a node has. If
the setting is configured, the node has exactly the roles in the list,
and not any additional roles. This means to configure a master-only
node, the setting is merely 'node.roles: [master]', and to configure a
coordinating-only node, the setting is merely: 'node.roles: []'.
With this change we deprecate the existing 'node.*' settings such as
'node.data'.
* [ML] make waiting for renormalization optional for internally flushing job (#58537)
When flushing, datafeeds only need the guaruntee that the latest bucket has been handled.
But, in addition to this, the typical call to flush waits for renormalization to complete. For large jobs, this can take a fair bit of time (even longer than a bucket length). This causes unnecessary delays in handling data.
This commit adds a new internal only flag that allows datafeeds (and forecasting) to skip waiting on renormalization.
closes#58395
The main changes are:
1. Catch the `NamedObjectNotFoundException` when parsing aggregation
type, and then throw a `ParsingException` with clear error message with hint.
2. Add a unit test method: AggregatorFactoriesTests#testInvalidType().
Closes#58146.
Co-authored-by: bellengao <gbl_long@163.com>
It is possible for the source document to have an empty string value
for a field that is mapped as numeric. We should treat those as missing
values and avoid throwing an assertion error.
Backport of #58541
This changes the default value for the results field of inference
applied on models that are trained via a data frame analytics job.
Previously, the results field default was `predicted_value`. This
commit makes it the same as in the training job itself. The new
default field is `<dependent_variable>_prediction`. Apart from
making inference consistent with the training job the model came
from, it is helpful to preserve the dependent variable name
by default as it provides some context to the user that may
avoid confusion as to which model results came from.
Backport of #58538
* Add acm mapping to APM for beats
* Add root mapping for APM
* Add sourcemap mapping to APM
* Fix missing properties
* Fix a second missing properties
* Add request property to acm
* Remove root and sourcemap per review
Co-authored-by: Mike Place <mike.place@elastic.co>
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
Add the ability to get a custom value while specifying a default and use it throughout the
codebase to get rid of the `null` edge case and shorten the code a little.
This change allows the submit async search task to cancel children
and removes the manual indirection that cancels the search task when the submit
task is cancelled. This is now handled by the task cancellation, which can cancel
grand-children since #54757.
This commits allows data streams to be a valid source for analytics and transforms.
Data streams are fairly transparent and our `_search` and `_reindex` actions work without error.
For `_transforms` the check-pointing works as desired as well. Data streams are effectively treated as an `alias` and the backing index values are stored within checkpointing information.
There was a discrepancy in the implementation of flush
acknowledgements: most of the class was designed on the
basis that the "last finalized bucket time" could be null
but the wire serialization assumed that it was never
null. This works because, the C++ sends zero "last
finalized bucket time" when it is not known or not
relevant. But then the Java code will print that to
XContent as it is assuming null represents not known or
not relevant.
This change corrects the discrepancies. Internally within
the class null represents not known or not relevant, but
this is translated from/to 0 for communications from the
C++ and old nodes that have the bug.
Additionally I switched from Date to Instant for this
class and made the member variables final to modernise it
a bit.
Backport of #58413
Adds a new value to the "event" enum of ML annotations, namely
"categorization_status_change".
This will allow users to see when categorization was found to
be performing poorly. Once per-partition categorization is
available, it will allow users to see when categorization is
performing poorly for a specific partition.
It does not make sense to reuse the "model_change" event that
annotations already have, because categorizer state is separate
to model state ("model" state is really anomaly detector state),
and is not reverted by the revert model snapshot API.
Therefore annotations related to categorization need to be
treated differently to annotations related to anomaly detection.
Backporting #58096 to 7.x branch.
Relates to #53100
* use mapping source direcly instead of using mapper service to extract the relevant mapping details
* moved assertion to TimestampField class and added helper method for tests
* Improved logic that inserts timestamp field mapping into an mapping.
If the timestamp field path consisted out of object fields and
if the final mapping did not contain the parent field then an error
occurred, because the prior logic assumed that the object field existed.
* Add support for snapshot and restore to data streams (#57675)
This change adds support for including data streams in snapshots.
Names are provided in indices field (the same way as in other APIs), wildcards are supported.
If rename pattern is specified it renames both data streams and backing indices.
It also adds test to make sure SLM works correctly.
Closes#57127
Relates to #53100
* version fix
* compilation fix
* compilation fix
* remove unused changes
* compilation fix
* test fix
When a local model is constructed, the cache hit miss count is incremented.
When a user calls _stats, we will include the sum cache hit miss count across ALL nodes. This statistic is important to in comparing against the inference_count. If the cache hit miss count is near the inference_count it indicates that the cache is overburdened, or inappropriately configured.
Today when creating a follower index via the put follow API, or via an
auto-follow pattern, it is not possible to specify settings overrides
for the follower index. Instead, we copy all of the leader index
settings to the follower. Yet, there are cases where a user would want
some different settings on the follower index such as the number of
replicas, or allocation settings. This commit addresses this by allowing
the user to specify settings overrides when creating follower index via
manual put follower calls, or via auto-follow patterns. Note that not
all settings can be overrode (e.g., index.number_of_shards) so we also
have detection that prevents attempting to override settings that must
be equal between the leader and follow index. Note that we do not even
allow specifying such settings in the overrides, even if they are
specified to be equal between the leader and the follower
index. Instead, the must be implicitly copied from the leader index, not
explicitly set by the user.
This changes the actions that would attempt to make the managed index read only to
check if the managed index is the write index of a data stream before proceeding.
The updated actions are shrink, readonly, freeze and forcemerge.
(cherry picked from commit c906f631833fee8628f898917a8613a1f436c6b1)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
As part of the "ML in Spaces" project, access to the ML UI in
Kibana is migrating to being controlled by Kibana privileges.
The ML UI will check whether the logged-in user has permission
to do something ML-related using Kibana privileges, and if they
do will call the relevant ML Elasticsearch API using the Kibana
system user. In order for this to work the kibana_system role
needs to have administrative access to ML.
Backport of #58061
We don't allow converting a data stream's writeable index into a searchable
snapshot. We are currently preventing swapping a data stream's write index
with the restored index.
This adds another step that will not proceed with the searchable snapshot action
until the managed index is not the write index of a data stream anymore.
(cherry picked from commit ccd618ead7cf7f5a74b9fb34524d00024de1479a)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
MappedFieldType is a combination of two concerns:
* an extension of lucene's FieldType, defining how a field should be indexed
* a set of query factory methods, defining how a field should be searched
We want to break these two concerns apart. This commit is a first step to doing this, breaking
the inheritance relationship between MappedFieldType and FieldType. MappedFieldType
instead has a series of boolean flags defining whether or not the field is searchable or
aggregatable, and FieldMapper has a separate FieldType passed to its constructor defining
how indexing should be done.
Relates to #56814
Allows the kibana user to collect data telemetry in a background
task by giving the kibana_system built-in role the view_index_metadata
and monitoring privileges over all indices (*).
Without this fix, users who try to use Metricbeat for Stack Monitoring today
see the following error repeatedly in their Metricbeat log. Due to this error
Metricbeat is unwilling to proceed further and, thus, no Stack Monitoring
data is indexed into the Elasticsearch cluster.
Co-authored-by: Albert Zaharovits <albert.zaharovits@elastic.co>
* Remove usage of deprecated testCompile configuration
* Replace testCompile usage by testImplementation
* Make testImplementation non transitive by default (as we did for testCompile)
* Update CONTRIBUTING about using testImplementation for test dependencies
* Fail on testCompile configuration usage
This has `EnsembleInferenceModel` not parse feature_names from the XContent.
Instead, it will rely on `rewriteFeatureIndices` to be called ahead time.
Consequently, protections are made for a fail fast path if `rewriteFeatureIndices` has not been called before `infer`.
This type of result will store stats about how well categorization
is performing. When per-partition categorization is in use, separate
documents will be written for every partition so that it is possible
to see if categorization is working well for some partitions but not
others.
This PR is a minimal implementation to allow the C++ side changes to
be made. More Java side changes related to per-partition
categorization will be in followup PRs. However, even in the long
term I do not see a major benefit in introducing dedicated APIs for
querying categorizer stats. Like forecast request stats the
categorizer stats can be read directly from the job's results alias.
Backport of #57978
Adds support for reading in `model_size_info` objects.
These objects contain numeric values indicating the model definition size and complexity.
Additionally, these objects are not stored or serialized to any other node. They are to be used for calculating and storing model metadata. They are much smaller on heap than the true model definition and should help prevent the analytics process from using too much memory.
Co-authored-by: Elastic Machine <elasticmachine@users.noreply.github.com>
The shrink action creates a shrunken index with the target number of shards.
This makes the shrink action data stream aware. If the ILM managed index is
part of a data stream the shrink action will make sure to swap the original
managed index with the shrunken one as part of the data stream's backing
indices and then delete the original index.
(cherry picked from commit 99aeed6acf4ae7cbdd97a3bcfe54c5d37ab7a574)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
This deprecates `Rounding#round` and `Rounding#nextRoundingValue` in
favor of calling
```
Rounding.Prepared prepared = rounding.prepare(min, max);
...
prepared.round(val)
```
because it is always going to be faster to prepare once. There
are going to be some cases where we won't know what to prepare *for*
and in those cases you can call `prepareForUnknown` and stil be faster
than calling the deprecated method over and over and over again.
Ultimately, this is important because it doesn't look like there is an
easy way to cache `Rounding.Prepared` or any of its precursors like
`LocalTimeOffset.Lookup`. Instead, we can just build it at most once per
request.
Relates to #56124
Before to determine if a field is meta-field, a static method of MapperService
isMetadataField was used. This method was using an outdated static list
of meta-fields.
This PR instead changes this method to the instance method that
is also aware of meta-fields in all registered plugins.
Related #38373, #41656Closes#24422
We want to validate the DataStreams on creation to make sure the future backing
indices would not clash with existing indices in the system (so we can
always rollover the data stream).
This changes the validation logic to allow for a DataStream to be created
with a backing index that has a prefix (eg. `shrink-foo-000001`) even if the
former backing index (`foo-000001`) exists in the system.
The new validation logic will look for potential index conflicts with indices
in the system that have the counter in the name greater than the data stream's
generation.
This ensures that the `DataStream`'s future rollovers are safe because for a
`DataStream` `foo` of generation 4, we will look for standalone indices in the
form of `foo-%06d` with the counter greater than 4 (ie. validation will fail if
`foo-000006` exists in the system), but will also allow replacing a
backing index with an index named by prefixing the backing index it replaces.
(cherry picked from commit 695b242d69f0dc017e732b63737625adb01fe595)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
Deleting expired data can take a long time leading to timeouts if there
are many jobs. Often the problem is due to a few large jobs which
prevent the regular maintenance of the remaining jobs. This change adds
a job_id parameter to the delete expired data endpoint to help clean up
those problematic jobs.
This makes it easier to debug where such tasks come from in case they are returned from the get tasks API.
Also renamed the last occurrence of waitForCompletion to waitForCompletionTimeout in get async search request.
This PR adds the initial Java side changes to enable
use of the per-partition categorization functionality
added in elastic/ml-cpp#1293.
There will be a followup change to complete the work,
as there cannot be any end-to-end integration tests
until elastic/ml-cpp#1293 is merged, and also
elastic/ml-cpp#1293 does not implement some of the
more peripheral functionality, like stop_on_warn and
per-partition stats documents.
The changes so far cover REST APIs, results object
formats, HLRC and docs.
Backport of #57683
This is a major refactor of the underlying inference logic.
The main refactor is now we are separating the model configuration and
the inference interfaces.
This has the following benefits:
- we can store extra things with the model that are not
necessary for inference (i.e. treenode split information gain)
- we can optimize inference separate from model serialization and storage.
- The user is oblivious to the optimizations (other than seeing the benefits).
A major part of this commit is removing all inference related methods from the
trained model configurations (ensemble, tree, etc.) and moving them to a new class.
This new class satisfies a new interface that is ONLY for inference.
The optimizations applied currently are:
- feature maps are flattened once
- feature extraction only happens once at the highest level
(improves inference + feature importance through put)
- Only storing what we need for inference + feature importance on heap
When we force delete a DF analytics job, we currently first force
stop it and then we proceed with deleting the job config.
This may result in logging errors if the job config is deleted
before it is retrieved while the job is starting.
Instead of force stopping the job, it would make more sense to
try to stop the job gracefully first. So we now try that out first.
If normal stop fails, then we resort to force stopping the job to
ensure we can go through with the delete.
In addition, this commit introduces `timeout` for the delete action
and makes use of it in the child requests.
Backport of #57680
rewrite config on update if either version is outdated, credentials change,
the update changes the config or deprecated settings are found. Deprecated
settings get migrated to the new format. The upgrade can be easily extended to
do any necessary re-writes.
fixes#56499
backport #57648
Przemyslaw Gomulka
Igor Motov
David Kyle
Yang Wang
Lloyd
Mark Tozzi
Benjamin Trent
David Roberts
Lee Hinman
Andrei Dan
Armin Braun
Dimitris Athanasiou
Hendrik Muhs
Ryan Ernst
Francisco Fernández Castaño
Przemysław Witek
Yannick Welsch
Adrien Grand
Rene Groeschke
Jim Ferenczi
Dan Hermann
Larry Gregory
James Baiera
Martijn van Groningen
Tanguy Leroux
Tal Levy
Ryan Ernst
Albert Zaharovits
Nhat Nguyen
Andrei Stefan
David Turner
Luca Cavanna
Dario Gieselaar
Tim Vernum
Henning Andersen
Jason Tedor
Nik Everett
Chris Roberson
Przemko Robakowski
Alan Woodward
Alejandro Fernández Haro
Shaunak Kashyap
Mayya Sharipova