BigDL Friesian is an application framework for building optimized large-scale recommender solutions. The recommending workflows built on top of Friesian can seamlessly scale out to distributed big data clusters in the production environment.
Friesian provides end-to-end support for three typical stages in a modern recommendation system:
- Offline stage: distributed feature engineering and model training.
- Nearline stage: Feature and model updates.
- Online stage: Recall and ranking.
The overall architecture of Friesian is shown in the following diagram:
See here for the uses cases of various recommendation models implemented in Friesian.
See here for the end-to-end serving pipeline in Friesian.