Superoptimizing SQL Queries using Program Synthesis


In the big data era, SQL is used by data scientists and software engineers on a daily basis. SQL queries, if written poorly, are slow on large databases, even using state-of-the-art query optimizers. This project aims to develop a super optimizer for SQL queries, which is able to maximally boost the performance of a poorly written query.

People

Xinyu
Wang

ECE, ME
Engineering

Barzan
Mozafari

CSE
Engineering

Funding: $30K (2022)

Goal: We aim to develop a new SQL query optimizer that can speed up poorly written queries by at least two orders of magnitude.

Token Investors: Xinyu Wang, Barzan Mozafari


Project ID: 1002