* [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
This change adds two new cluster privileges:
* manage_data_frame_transforms
* monitor_data_frame_transforms
And two new built-in roles:
* data_frame_transforms_admin
* data_frame_transforms_user
These permit access to the data frame transform endpoints.
(Index privileges are also required on the source and
destination indices for each data frame transform, but
since these indices are configurable they it is not
appropriate to grant them via built-in roles.)
fix a couple of odd behaviors of data frame transforms REST API's:
- check if id from body and id from URL match if both are specified
- do not allow a body for delete
- allow get and stats without specifying an id
The SchedulerEngine is used in several places in our code and not all
of these usages properly stopped the SchedulerEngine, which could lead
to test failures due to leaked threads from the SchedulerEngine. This
change adds stopping to these usages in order to avoid the thread leaks
that cause CI failures and noise.
Closes#38875
The data frame plugin allows users to create feature indexes by pivoting a source index. In a
nutshell this can be understood as reindex supporting aggregations or similar to the so called entity
centric indexing.
Full history is provided in: feature/data-frame-transforms
Hendrik Muhs
Benjamin Trent
David Kyle
Christoph Büscher
Julie Tibshirani
Luca Cavanna
Yogesh Gaikwad
David Roberts
Jay Modi