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.