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 This method was using an outdated static list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 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
Dan Hermann
Przemysław Witek
Mayya Sharipova
Andrei Dan
David Kyle
Luca Cavanna
David Roberts
Benjamin Trent
Dimitris Athanasiou
Hendrik Muhs
William Brafford
Ioannis Kakavas
William Brafford
Mark Vieira
Tim Vernum
Jake Landis
Tal Levy
Nik Everett
Ignacio Vera
Ryan Ernst
Tim Brooks
Jim Ferenczi