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This paper explores the limitations and strategies of using sample-based joins in approximate query processing (AQP), particularly focusing on offline samples. It discusses the effectiveness of various sampling techniques, such as uniform, universe, and stratified sampling, and introduces a hybrid sampling scheme called Stratified-Universe-Bernoulli Sampling (SUBS) that optimizes join approximations. The authors empirically validate their findings, demonstrating that their optimal sampling parameters yield
- Author
- Farooq Khan
- Language
- EN