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Qiushi Bai: QueryBooster-Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting + Demo
October 14 @ 12:30 pm - 2:00 pm
QueryBooster: Improving SQL Performance Using Middleware Services for Human-Centered Query Rewriting
Query latency is critical in many database-backed applications where users need answers quickly to gain timely insights and make mission-critical decisions. “Query rewriting” is one of the query optimization techniques which transforms SQL queries to more efficient formats based on pre-defined rewriting rules. However, with the emergence of different domain-specific applications such as visualization and business intelligence, existing database optimizers lack support for developers to leverage their domain knowledge to rewrite queries.
We propose QueryBooster, a middleware query rewriting service that sits between the application and the database. It requires few or no modifications to the application or the database and allows developers to introduce their own rewriting rules to optimize their SQL queries. We call this rewriting “human-centered.” QueryBooster aims to provide a powerful interface for users to either compose rewriting rules using a rule language or show their rewriting intentions by providing examples. Furthermore, with the wisdom accumulated from the crowd, QueryBooster can also automatically recommend rewritings for new queries to the user.
In this talk, I will first show a demo where QueryBooster can accelerate Tableau queries on top of the PostgreSQL database up to 100 times faster. I then discuss the research questions we are working on in QueryBooster, such as how to develop a rule language, how to generate rewriting rules automatically from user-given examples, and how to leverage crowdsources to recommend rewriting rules.
Qiushi Bai is a Ph.D. candidate in the Computer Science Department at UC Irvine. He received his Master’s and Bachelor’s degrees in CS from Northeastern University in China. His research interests have focused on improving query performance for big data analytics and visualizations.