Are We Ready For Learned Cardinality Estimation?

Understand

Cardinality estimation is a fundamental but long unresolved problem in query optimization.

• Recently, multiple papers from different research groups consistently report that learned models have the potential to replace existing cardinality estimators.
• In this paper, we ask a forward-thinking question: Are we ready to deploy these learned cardinality models in production? Our study consists of three main parts.
• Firstly, we focus on the static environment (i.e., no data updates) and compare five new learned methods with eight traditional methods on four real-world datasets under a unified workload setting.