Prior to this change ML memory estimation processes for a
given job would always use the same named pipe names. This
would often cause one of the processes to fail.
This change avoids this risk by adding an incrementing counter
value into the named pipe names used for memory estimation
processes.
Backport of #60395
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.
This sets up all indexing to one of our write aliases to require it actually be an alias.
This allows failures scenarios to be captured quickly, loudly, and then potentially recovered.
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
Previously the test was asserting the prediction on each document
was close 10.0 from the expected. It turned out that was not enough
as we occasionally saw the test failing by little.
Instead of relaxing that assertion, this commit changes it to
assert the mean prediction error is less than 10.0. This should
reduce the chances of the test failing significantly.
Fixes#60212
Backport of #60221
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
In #58877, when we switched test inference on java, we just
use the doc's `_source` as features. However, this could be
missing out on features that were used during training,
e.g. alias fields, etc.
This commit addresses this by extracting fields to use as
features during inference the same way they are extracted
in `DataFrameDataExtractor` when they are used for training.
Backport of #59963
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.
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 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>
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>
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
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
This commit creates a new Gradle plugin to provide a separate task name
and source set for running YAML based REST tests. The only project
converted to use the new plugin in this PR is distribution/archives/integ-test-zip.
For which the testing has been moved to :rest-api-spec since it makes the most
sense and it avoids a small but awkward change to the distribution plugin.
The remaining cases in modules, plugins, and x-pack will be handled in followups.
This plugin is distinctly different from the plugin introduced in #55896 since
the YAML REST tests are intended to be black box tests over HTTP. As such they
should not (by default) have access to the classpath for that which they are testing.
The YAML based REST tests will be moved to separate source sets (yamlRestTest).
The which source is the target for the test resources is dependent on if this
new plugin is applied. If it is not applied, it will default to the test source
set.
Further, this introduces a breaking change for plugin developers that
use the YAML testing framework. They will now need to either use the new source set
and matching task, or configure the rest resources to use the old "test" source set that
matches the old integTest task. (The former should be preferred).
As part of this change (which is also breaking for plugin developers) the
rest resources plugin has been removed from the build plugin and now requires
either explicit application or application via the new YAML REST test plugin.
Plugin developers should be able to fix the breaking changes to the YAML tests
by adding apply plugin: 'elasticsearch.yaml-rest-test' and moving the YAML tests
under a yamlRestTest folder (instead of test)
Backport of #58582 to 7.x branch.
This commit adds a new metadata field mapper that validates,
that a document has exactly a single timestamp value in the data stream timestamp field and
that the timestamp field mapping only has `type`, `meta` or `format` attributes configured.
Other attributes can affect the guarantee that an index with this meta field mapper has a
useable timestamp field.
The MetadataCreateIndexService inserts a data stream timestamp field mapper whenever
a new backing index of a data stream is created.
Relates to #53100
* [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
This PR implements recursive mapping merging for composable index templates.
When creating an index, we perform the following:
* Add each component template mapping in order, merging each one in after the
last.
* Merge in the index template mappings (if present).
* Merge in the mappings on the index request itself (if present).
Some principles:
* All 'structural' changes are disallowed (but everything else is fine). An
object mapper can never be changed between `type: object` and `type: nested`. A
field mapper can never be changed to an object mapper, and vice versa.
* Generally, each section is merged recursively. This includes `object`
mappings, as well as root options like `dynamic_templates` and `meta`. Once we
reach 'leaf components' like field definitions, they always overwrite an
existing one instead of being merged.
Relates to #53101.
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
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
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.
This commit bumps our JNA dependency from 4.5.1 to 5.5.0, so that we are
now on the latest maintained line, and pick up a large collection of bug
fixes that have accumulated.
* 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
Since we change the memory estimates for data frame analytics jobs from worst case to a realistic case, the strict less-than assertion in the test does not hold anymore. I replaced it with a less-or-equal-than assertion.
Backport or #57882
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
* [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.
Przemysław Witek
David Roberts
Benjamin Trent
Dimitris Athanasiou
David Kyle
Martijn van Groningen
Albert Zaharovits
Andrei Dan
Jake Landis
Julie Tibshirani
Rene Groeschke
Luca Cavanna
Jason Tedor
Valeriy Khakhutskyy