* [ML][Data Frame] Adding bwc tests for pivot transform (#43506)
* [ML][Data Frame] Adding bwc tests for pivot transform
* adding continuous transforms
* adding continuous dataframes to bwc
* adding continuous data frame tests
* Adding rolling upgrade tests for continuous df
* Fixing test
* Adjusting indices used in BWC, and handling NPE for seq_no_stats
* updating and muting specific bwc test
* Adjusting bwc tests for backport
* [ML][Data Frame] add node attr to GET _stats (#43842)
* [ML][Data Frame] add node attr to GET _stats
* addressing testing issues with node.attributes
* adjusting for backport
* [ML][Data Frame] using transform creation version for node assignment (#43764)
* [ML][Data Frame] using transform creation version for node assignment
* removing unused imports
* Addressing PR comment
* adjusing for backport
Action is a class that encapsulates meta information about an action
that allows it to be called remotely, specifically the action name and
response type. With recent refactoring, the action class can now be
constructed as a static constant, instead of needing to create a
subclass. This makes the old pattern of creating a singleton INSTANCE
both misnamed and lacking a common placement.
This commit renames Action to ActionType, thus allowing the old INSTANCE
naming pattern to be TYPE on the transport action itself. ActionType
also conveys that this class is also not the action itself, although
this change does not rename any concrete classes as those will be
removed organically as they are converted to TYPE constants.
relates #34389
* [ML][Data Frame] Add support for allow_no_match for endpoints (#43490)
* [ML][Data Frame] Add support for allow_no_match parameter in endpoints
Adds support for:
* Get Transforms
* Get Transforms stats
* stop transforms
* Update DataFrameTransformDocumentationIT.java
This merges the initial work that adds a framework for performing
machine learning analytics on data frames. The feature is currently experimental
and requires a platinum license. Note that the original commits can be
found in the `feature-ml-data-frame-analytics` branch.
A new set of APIs is added which allows the creation of data frame analytics
jobs. Configuration allows specifying different types of analysis to be performed
on a data frame. At first there is support for outlier detection.
The APIs are:
- PUT _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}
- GET _ml/data_frame/analysis/{id}/_stats
- POST _ml/data_frame/analysis/{id}/_start
- POST _ml/data_frame/analysis/{id}/_stop
- DELETE _ml/data_frame/analysis/{id}
When a data frame analytics job is started a persistent task is created and started.
The main steps of the task are:
1. reindex the source index into the dest index
2. analyze the data through the data_frame_analyzer c++ process
3. merge the results of the process back into the destination index
In addition, an evaluation API is added which packages commonly used metrics
that provide evaluation of various analysis:
- POST _ml/data_frame/_evaluate
This commit replaces usages of Streamable with Writeable for the
AcknowledgedResponse and its subclasses, plus associated actions.
Note that where possible response fields were made final and default
constructors were removed.
This is a large PR, but the change is mostly mechanical.
Relates to #34389
Backport of #43414
* [ML][Data Frame] Add version and create_time to transform config (#43384)
* [ML][Data Frame] Add version and create_time to transform config
* s/transform_version/version s/Date/Instant
* fixing getter/setter for version
* adjusting for backport
* [ML][Data Frame] make response.count be total count of hits
* addressing line length check
* changing response count for filters
* adjusting serialization, variable name, and total count logic
* making count mandatory for creation
* [ML][Data Frame] adds new pipeline field to dest config (#43124)
* [ML][Data Frame] adds new pipeline field to dest config
* Adding pipeline support to _preview
* removing unused import
* moving towards extracting _source from pipeline simulation
* fixing permission requirement, adding _index entry to doc
* adjusting for java 8 compatibility
* adjusting bwc serialization version to 7.3.0
* [ML][Data Frame] only complete task after state persistence
There is a race condition where the task could be completed, but there
is still a pending document write. This change moves
the task cancellation into the actionlistener of the state persistence.
intermediate commit
intermediate commit
* removing unused import
* removing unused const
* refreshing internal index after waiting for task to complete
* adjusting test data generation
* stop data frame task after it finishes
* test auto stop
* adapt tests
* persist the state correctly and move stop into listener
* Calling `onStop` even if persistence fails, changing `stop` to rely on doSaveState
The description field of xpack featuresets is optionally part of the
xpack info api, when using the verbose flag. However, this information
is unnecessary, as it is better left for documentation (and the existing
descriptions describe anything meaningful). This commit removes the
description field from feature sets.
increases the scheduler interval to fire less frequently, namely changing it from 1s to 10s. The scheduler interval is used for retrying after an error condition.
We had this as a dependency for legacy dependencies that still needed
the Log4j 1.2 API. This appears to no longer be necessary, so this
commit removes this artifact as a dependency.
To remove this dependency, we had to fix a few places where we were
accidentally relying on Log4j 1.2 instead of Log4j 2 (easy to do, since
both APIs were on the compile-time classpath).
Finally, we can remove our custom Netty logger factory. This was needed
when we were on Log4j 1.2 and handled logging in our own unique
way. When we migrated to Log4j 2 we could have dropped this
dependency. However, even then Netty would still pick up Log4j 1.2 since
it was on the classpath, thus the advantage to removing this as a
dependency now.
This corrects what appears to have been a copy-paste error
where the logger for `MachineLearning` and `DataFrame` was wrongly
set to be that of `XPackPlugin`.
The date_histogram accepts an interval which can be either a calendar
interval (DST-aware, leap seconds, arbitrary length of months, etc) or
fixed interval (strict multiples of SI units). Unfortunately this is inferred
by first trying to parse as a calendar interval, then falling back to fixed
if that fails.
This leads to confusing arrangement where `1d` == calendar, but
`2d` == fixed. And if you want a day of fixed time, you have to
specify `24h` (e.g. the next smallest unit). This arrangement is very
error-prone for users.
This PR adds `calendar_interval` and `fixed_interval` parameters to any
code that uses intervals (date_histogram, rollup, composite, datafeed, etc).
Calendar only accepts calendar intervals, fixed accepts any combination of
units (meaning `1d` can be used to specify `24h` in fixed time), and both
are mutually exclusive.
The old interval behavior is deprecated and will throw a deprecation warning.
It is also mutually exclusive with the two new parameters. In the future the
old dual-purpose interval will be removed.
The change applies to both REST and java clients.
* [ML] adding pivot.size option for setting paging size
* Changing field name to address PR comments
* fixing ctor usage
* adjust hlrc for field name change
* [ML] properly nesting objects in document source
* Throw exception on agg extraction failure, cause it to fail df
* throwing error to stop df if unsupported agg is found
Direct the task request to the node executing the task and also refactor the task responses
so all errors are returned and set the HTTP status code based on presence of errors.
* [ML] Adds progress reporting for transforms
* fixing after master merge
* Addressing PR comments
* removing unused imports
* Adjusting afterKey handling and percentage to be 100*
* Making sure it is a linked hashmap for serialization
* removing unused import
* addressing PR comments
* removing unused import
* simplifying code, only storing total docs and decrementing
* adjusting for rewrite
* removing initial progress gathering from executor
* [ML] Add mappings, serialization, and hooks to persist stats
* Adding tests for transforms without tasks having stats persisted
* intermittent commit
* Adjusting usage stats to account for stored stats docs
* Adding tests for id expander
* Addressing PR comments
* removing unused import
* adding shard failures to the task response
* [ML] Add data frame task state object and field
* A new state item is added so that the overall task state can be
accoutned for
* A new FAILED state and reason have been added as well so that failures
can be shown to the user for optional correction
* Addressing PR comments
* adjusting after master merge
* addressing pr comment
* Adjusting auditor usage with failure state
* Refactor, renamed state items to task_state and indexer_state
* Adding todo and removing redundant auditor call
* Address HLRC changes and PR comment
* adjusting hlrc IT test
create and use unique, deterministic document ids based on the grouping values.
This is a pre-requisite for updating documents as well as preventing duplicates after a hard failure during indexing.
* [ML] make source and dest objects in the transform config
* addressing PR comments
* Fixing compilation post merge
* adding comment for Arrays.hashCode
* addressing changes for moving dest to object
* fixing data_frame yml tests
* fixing API test
Add a checkpoint service for data frame transforms, which allows to ask for a checkpoint of the
source. In future these checkpoints will be stored in the internal index to
- detect upstream changes
- updating the data frame without a full re-run
- allow data frame clients to checkpoint themselves
* [Data Frame] Refactor GET Transforms API:
* Add pagination
* comma delimited list expression support GET transforms
* Flag troublesome internal code for future refactor
* Removing `allow_no_transforms` param, ratcheting down pageparam option
* Changing DataFrameFeatureSet#usage to not get all configs
* Intermediate commit
* Writing test for batch data gatherer
* Removing unused import
* removing bad println used for debugging
* Updating BatchedDataIterator comments and query
* addressing pr comments
* disallow null scrollId to cause stackoverflow
* [Data Frame] Refactor PUT transform such that:
* POST _start creates the task and starts it
* GET transforms queries docs instead of tasks
* POST _stop verifies the stored config exists before trying to stop
the task
* Addressing PR comments
* Refactoring DataFrameFeatureSet#usage, decreasing size returned getTransformConfigurations
* fixing failing usage test
Benjamin Trent
Ryan Ernst
Przemysław Witek
David Kyle
Dimitris Athanasiou
Martijn van Groningen
Ryan Ernst
Hendrik Muhs
Jason Tedor
Zachary Tong
Christoph Büscher
Yogesh Gaikwad