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
In #55592 and #55416, we deprecated the settings for enabling and disabling
basic license features and turned those settings into no-ops. Since doing so,
we've had feedback that this change may not give users enough time to cleanly
switch from non-ILM index management tools to ILM. If two index managers
operate simultaneously, results could be strange and difficult to
reconstruct. We don't know of any cases where SLM will cause a problem, but we
are restoring that setting as well, to be on the safe side.
This PR is not a strict commit reversion. First, we are keeping the new
xpack.watcher.use_ilm_index_management setting, introduced when
xpack.ilm.enabled was made a no-op, so that users can begin migrating to using
it. Second, the SLM setting was modified in the same commit as a group of other
settings, so I have taken just the changes relating to SLM.
As the datastream information is stored in the `ClusterState.Metadata` we exposed
the `Metadata` to the `AsyncWaitStep#evaluateCondition` method in order for
the steps to be able to identify when a managed index is part of a DataStream.
If a managed index is part of a DataStream the rollover target is the DataStream
name and the highest generation index is the write index (ie. the rolled index).
(cherry picked from commit 6b410dfb78f3676fce1b7401f1628c1ca6fbd45a)
Signed-off-by: Andrei Dan <andrei.dan@elastic.co>
* [ML] mark forecasts for force closed/failed jobs as failed (#57143)
forecasts that are still running should be marked as failed/finished in the following scenarios:
- Job is force closed
- Job is re-assigned to another node.
Forecasts are not "resilient". Their execution does not continue after a node failure. Consequently, forecasts marked as STARTED or SCHEDULED should be flagged as failed. These forecasts can then be deleted.
Additionally, force closing a job kills the native task directly. This means that if a forecast was running, it is not allowed to complete and could still have the status of `STARTED` in the index.
relates to https://github.com/elastic/elasticsearch/issues/56419
* [ML] adds new for_export flag to GET _ml/inference API (#57351)
Adds a new boolean flag, `for_export` to the `GET _ml/inference/<model_id>` API.
This flag is useful for moving models between clusters.
This adds a max_model_memory setting to forecast requests.
This setting can take a string value that is formatted according to byte sizes (i.e. "50mb", "150mb").
The default value is `20mb`.
There is a HARD limit at `500mb` which will throw an error if used.
If the limit is larger than 40% the anomaly job's configured model limit, the forecast limit is reduced to be strictly lower than that value. This reduction is logged and audited.
related native change: https://github.com/elastic/ml-cpp/pull/1238
closes: https://github.com/elastic/elasticsearch/issues/56420
The ssl.trust setting for Watcher provides a list of hostnames that
should be automatically trusted for SSL hostname verification. It was
accidentally broken when we added the full ssl.* settings for email
notifications (see #45272)
This commit corrects this, so the setting is once again respected,
as long as none of the other ssl settings are configured for email
notifications.
Resolves: #52153
Backport of: #56090
Fix delete_expired_data/nightly maintenance when
many model snapshots need deleting (#57041)
The queries performed by the expired data removers pull back entire
documents when only a few fields are required. For ModelSnapshots in
particular this is a problem as they contain quantiles which may be
100s of KB and the search size is set to 10,000.
This change makes the search more efficient by only requesting the
fields needed to work out which expired data should be deleted.
The original implementation utilized `bbox` as the index mapping type. This would not work as it would have to be `envelope`. But, given that `envelope` and `polygon` are tessellated in the same way, we choose to use `polygon` as the geo_shape type. This is for easier support other places in the stack (a la kibana maps)
Throttling nightly cleanup as much as we do has been over cautious.
Night cleanup should be more lenient in its throttling. We still
keep the same batch size, but now the requests per second scale
with the number of data nodes. If we have more than 5 data nodes,
we don't throttle at all.
Additionally, the API now has `requests_per_second` and `timeout` set.
So users calling the API directly can set the throttling.
This commit also adds a new setting `xpack.ml.nightly_maintenance_requests_per_second`.
This will allow users to adjust throttling of the nightly maintenance.
WatcherIndexTemplateRegistry as of https://github.com/elastic/elasticsearch/pull/52962
requires all nodes to be on 7.7.0 before it allows the version 11 index template to be
installed.
While in a mixed cluster, nothing prevents Watcher from running on the new
host before the all of the nodes are on 7.7.0. This will result in the
.watcher-history-11* index without the proper mappings. Without the proper
mapping a single document (for a large watch) can exceed the default 1000 field
limit and cause error to show in the logs.
This commit ensures the same logic for writing to the index is applied as for
installing the template. In a mixed cluster, the `10` index template will continue
to be written. Only once all of nodes are on 7.7.0+ will the `11` index template
be installed and used.
closes#56732
This change aims to fix our setup in CI so that we can run 7.x in
FIPS 140 mode. The major issue that we have in 7.x and did not
have in master is that we can't use the diagnostic trust manager
in FIPS mode in Java 8 with SunJSSE in FIPS approved mode as it
explicitly disallows the wrapping of X509TrustManager.
Previous attempts like #56427 and #52211 focused on disabling the
setting in all of our tests when creating a Settings object or
on setting fips_mode.enabled accordingly (which implicitly disables
the diagnostic trust manager). The attempts weren't future proof
though as nothing would forbid someone to add new tests without
setting the necessary setting and forcing this would be very
inconvenient for any other case ( see
#56427 (comment) for the full argumentation).
This change introduces a runtime check in SSLService that overrides
the configuration value of xpack.security.ssl.diagnose.trust and
disables the diagnostic trust manager when we are running in Java 8
and the SunJSSE provider is set in FIPS mode.
This is another part of the breakup of the massive BuildPlugin. This PR
moves the code for configuring publications to a separate plugin. Most
of the time these publications are jar files, but this also supports the
zip publication we have for integ tests.
This aggregation will perform normalizations of metrics
for a given series of data in the form of bucket values.
The aggregations supports the following normalizations
- rescale 0-1
- rescale 0-100
- percentage of sum
- mean normalization
- z-score normalization
- softmax normalization
To specify which normalization is to be used, it can be specified
in the normalize agg's `normalizer` field.
For example:
```
{
"normalize": {
"buckets_path": <>,
"normalizer": "percent"
}
}
```
This merges the code for the `significant_terms` agg into the package
for the code for the `terms` agg. They are *super* entangled already,
this mostly just admits that to ourselves.
Precondition for the terms work in #56487
When decoding async execution ids, exceptions thrown from the decode method itself were not caught, leading to cryptic errors like "Input byte array has incorrect ending byte at 68" being returned. With this commit we return "invalid id: [abcdef]".
Added tests coverage for a couple of these scenarios and also added tests for equals/hashcode methods.
This setting was not returned in the SamlRealmSettings#getSettings
so it was not possible for users to set this in the realm config
in our configuration.
fix count in get and get stats if explicit ids are given and ids might be
duplicated when configuration are stored in different index (versions).
fixes#56196
Similar to what the moving function aggregation does, except merging windows of percentiles
sketches together instead of cumulatively merging final metrics
Currently Elasticsearch creates independent event loop groups for each
transport (http and internal) transport type. This is unnecessary and
can lead to contention when different threads access shared resources
(ex: allocators). This commit moves to a model where, by default, the
event loops are shared between the transports. The previous behavior can
be attained by specifically setting the http worker count.
Async search integration tests are subject to random failures when:
* The test index has more than one replica.
* The request cache is used.
* Some shards are empty.
* The maintenance service starts a garbage collection when node is closing.
They are also slow because the test index is created/populated on each
test method.
This change refactors these integration tests in order to:
* Create the index once for the entire test suite.
* Fix the usage of the request cache and replicas.
* Ensures that all shards have at least one document.
* Increase the delay of the maintenance service garbage collection.
Closes#55895Closes#55988
It is possible that the config document for a data frame
analytics job is deleted from the config index. If that is
the case the user is unable to stop a running job because
we attempt to retrieve the config and that will throw.
This commit changes that. When the request is forced,
we do not expand the requested ids based on the existing
configs but from the list of running tasks instead.
Backport of #56360
Due to multi-threading it is possible that phase progress
updates written from the c++ process arrive reordered.
We can address this by ensuring that progress may only increase.
Closes#56282
Backport of #56339
this commit adds aggregation support for the geo_shape field
type on geo*_grid aggregations.
it introduces a Tiler for both tiles and hashes that enables a new type of
ValuesSource to replace the GeoPoint's CellIdSource. This makes it possible
for the existing Aggregator to be re-used, so no new implementations of
the grid aggregators are added.
The following settings are now no-ops:
* xpack.flattened.enabled
* xpack.logstash.enabled
* xpack.rollup.enabled
* xpack.slm.enabled
* xpack.sql.enabled
* xpack.transform.enabled
* xpack.vectors.enabled
Since these settings no longer need to be checked, we can remove settings
parameters from a number of constructors and methods, and do so in this
commit.
We also update documentation to remove references to these settings.
This PR implements the following changes to make ML model snapshot
retention more flexible in advance of adding a UI for the feature in
an upcoming release.
- The default for `model_snapshot_retention_days` for new jobs is now
10 instead of 1
- There is a new job setting, `daily_model_snapshot_retention_after_days`,
that defaults to 1 for new jobs and `model_snapshot_retention_days`
for pre-7.8 jobs
- For days that are older than `model_snapshot_retention_days`, all
model snapshots are deleted as before
- For days that are in between `daily_model_snapshot_retention_after_days`
and `model_snapshot_retention_days` all but the first model snapshot
for that day are deleted
- The `retain` setting of model snapshots is still respected to allow
selected model snapshots to be retained indefinitely
Backport of #56125
As of elastic/ml-cpp#1179, the analytics process reports phases
depending on the analysis type. This commit adjusts the phases
of current analyses from `analyzing` to the following:
- outlier_detection: [`computing_outlier`]
- regression/classification: [`feature_selection`, `coarse_parameter_search`, `fine_tuning_parameters`, `final_training`]
Backport of #56107
Backport of #56034.
Move includeDataStream flag from an IndicesOptions to IndexNameExpressionResolver.Context
as a dedicated field that callers to IndexNameExpressionResolver can set.
Also alter indices stats api to support data streams.
The rollover api uses this api and otherwise rolling over data stream does no longer work.
Relates to #53100
Backport of #55858 to 7.x branch.
Currently the TransportBulkAction detects whether an index is missing and
then decides whether it should be auto created. The coordination of the
index creation also happens in the TransportBulkAction on the coordinating node.
This change adds a new transport action that the TransportBulkAction delegates to
if missing indices need to be created. The reasons for this change:
* Auto creation of data streams can't occur on the coordinating node.
Based on the index template (v2) either a regular index or a data stream should be created.
However if the coordinating node is slow in processing cluster state updates then it may be
unaware of the existence of certain index templates, which then can load to the
TransportBulkAction creating an index instead of a data stream. Therefor the coordination of
creating an index or data stream should occur on the master node. See #55377
* From a security perspective it is useful to know whether index creation originates from the
create index api or from auto creating a new index via the bulk or index api. For example
a user would be allowed to auto create an index, but not to use the create index api. The
auto create action will allow security to distinguish these two different patterns of
index creation.
This change adds the following new transport actions:
AutoCreateAction, the TransportBulkAction redirects to this action and this action will actually create the index (instead of the TransportCreateIndexAction). Later via #55377, can improve the AutoCreateAction to also determine whether an index or data stream should be created.
The create_index index privilege is also modified, so that if this permission is granted then a user is also allowed to auto create indices. This change does not yet add an auto_create index privilege. A future change can introduce this new index privilege or modify an existing index / write index privilege.
Relates to #53100
Martijn van Groningen
David Roberts
Rene Groeschke
Przemysław Witek
Tim Vernum
Yang Wang
Dimitris Athanasiou
Lee Hinman
Henning Andersen
Jason Tedor
Igor Motov
Benjamin Trent
Nik Everett
Chris Roberson
Armin Braun
Jim Ferenczi
Przemko Robakowski
Andrei Dan
Alan Woodward
Alejandro Fernández Haro
Shaunak Kashyap
David Kyle
Dan Hermann
Mayya Sharipova
Luca Cavanna
Hendrik Muhs
William Brafford
Ioannis Kakavas
William Brafford
Mark Vieira
Jake Landis
Ryan Ernst
Tal Levy
Ignacio Vera
Tim Brooks