* [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
* [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 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 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
Benjamin Trent
Hendrik Muhs
David Roberts
David Kyle