This repository has been archived by the owner on Apr 15, 2022. It is now read-only.
What's new?
This release has 40 commits and a number of major enhancements.
Major Enhancements
- Airflow Support - Feature Statistics calculations, backfill, and pipeline support for feature sets (@myles-novick, #157 #171 #173)
- JWT Support for the feature store and mlmanager (@myles-novick, #126)
- MLflow 1.15 upgrade (@Ben-Epstein, #129)
- Support for deploying fastai, statsmodels, and spacy models to kubernetes natively (@Ben-Epstein, #131)
- New HTTP artifact store for mlflow (@Ben-Epstein, #155)
- New, cleaner documentation! See it here
Other Changes
- Support returning training sets as pandas dataframes (@Ben-Epstein, #158)
- feature_exists, feature_set_exists, and training_view_exists functions (@Ben-Epstein, #132 #161 #159 #164)
- Enabling custom CORS support via environment variable (@Ben-Epstein, #136)
- Versioning for training sets (@Ben-Epstein, #138)
- Advanced feature search (@Ben-Epstein, #145)
- Database deployed models now propagate errors to the user instead of throwing Unexpected Exceptions (@Ben-Epstein, #166)
Bug Fixes
- Fix to the feature store VTI function for TimeSnap was missing the schema name (@Ben-Epstein, #128)
- Database model deployment via new VTI was failing when executing via OLAP (@Ben-Epstein, #130)
- Various bug fixes for the new Feature Store UI (@Ben-Epstein, #135)
- Missing validation on aggregation feature sets (@Ben-Epstein, #147 #148 #156)
- TimestampSnap function was sometimes 12 hours off (@sergioferragut, #174)
Breaking Changes
- You must run the upgrade script moving from 2.7.0 to 2.8.0 in order for the feature store to function properly
This release is in tandem with the pysplice release