SQLRec

Introduction

A recommendation engine that supports SQL development, aiming to enable data science practitioners, including data analysts, data engineers, and backend developers, to quickly build production-ready recommendation systems. The system architecture is shown in the figure below. SQLRec encapsulates underlying component access, model training, inference, and other processes using SQL, allowing upper-level recommendation business logic to be described using only SQL.

SQLRec has the following features:

• Cloud native, with built-in minikube-based deployment scripts for one-click deployment of SQLRec system and related dependency services
• Extended SQL syntax, making it possible to describe recommendation system business logic using SQL
• Implemented an efficient SQL execution engine based on Calcite, meeting the real-time requirements of recommendation systems
• Based on existing big data ecosystem, easy to integrate
• Easy to extend, supporting custom UDFs, Table types, and Model types

Roadmap

When will version 1.0 be released?

Versions before 1.0 are beta versions, not recommended for production use, and do not guarantee interface compatibility. There is no planned release date yet; it will be released after the following features are completed:

• Comprehensive unit test, integration test, and effectiveness test coverage
• Code quality optimization, many details still need refinement
• Support for degradation and timeout configuration
• Complete version management methods for easy rollback to previous versions
• Optimize metric monitoring system
• C++ model serving

Future Feature Plans

• Frontend UI for viewing current execution DAG, SQL code, statistics, etc.
• Further optimize SQL syntax compatibility and runtime performance
• More ready-to-use UDFs, models, etc.
• Support for more external data sources, such as JDBC, MongoDB, etc.
• Tensorboard visualization of model training process
• GPU training and inference support
• Support for authentication and authorization
• Best practice tutorials, including search, recommendation, etc.