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What is Exploring Learned Cardinality Estimation about?
This paper explores learned cardinality estimation methods for database query optimization, highlighting their advantages over traditional histogram and sampling techniques. It categorizes various learned solutions, evaluates their performance, and provides a testbed for further research. The findings indicate that learned methods, particularly those utilizing neural networks, significantly outperform non-learned methods in accuracy and efficiency for complex queries.
- Author
- Yanjing Wang
- Language
- EN