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Leveraging Application Data Constraints to Optimize Database-Backed Web Applications

Xiaoxuan LiuShuxian WangMengzhu Sun ...+6 Alvin Cheung
May 2022
摘要
Exploiting the relationships among data, such as primary and foreign keys, isa classical query optimization technique. As persistent data is increasinglybeing created and maintained programmatically (e.g., web applications), priorwork that focuses on inferring data relationships by tabulating statistics fromthe stored data misses an important opportunity. We present ConstrOpt, thefirst tool that identifies data relationships by analyzing the programs thatgenerate and maintain the persistent data. Once identified, ConstrOpt leveragesthe found constraints to optimize the application's physical design and queryexecution by rewriting queries. Instead of developing a fixed set of predefinedrewriting rules, ConstrOpt employs an enumerate-test-verify technique toautomatically exploit the discovered data constraints to improve queryexecution. Each resulting rewrite is provably semantically equivalent to theoriginal query. Using 14 real-world web applications, our experiments show thatConstrOpt can discover over 4306 data constraints by analyzing applicationsource code. On 3 of the evaluated applications, among queries with at leastone constrained column, 42% can benefit from data layout optimization, and 35%are optimized by changing the application code. Finally, ConstrOpt'sconstraint-driven optimizer improves the performance of 826 queries, 9.8% ofwhich has over 2x speedup.
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