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arXiv · 2204.07102

Synthesizing Analytical SQL Queries from Computation Demonstration

Xiangyu Zhou·Rastislav Bodik·Alvin Cheung·Chenglong Wang
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Abstract

Analytical SQL is widely used in modern database applications and data analysis. However, its partitioning and grouping operators are challenging for novice users. Unfortunately, programming by example, shown effective on standard SQL, are less attractive because examples for analytical queries are more laborious to solve by hand. To make demonstrations easier to create, we designed a new end-user specification, programming by computation demonstration, that allows the user to demonstrate the task using a (possibly incomplete) cell-level computation trace. This specification is exploited in a new abstraction-based synthesis algorithm to prove that a partially formed query cannot be completed to satisfy the specification, allowing us to prune the search space. We implemented our approach in a tool named Sickle and tested it on 80 real-world analytical SQL tasks. Results show that even from small demonstrations, Sickle can solve 76 tasks, in 12.8 seconds on average, while the prior approaches can solve only 60 tasks and are on average 22.5x slower. Our user study with 13 participants reveals that our specification increases user efficiency and confidence on challenging tasks.

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Xiangyu Zhou, Rastislav Bodik, Alvin Cheung, Chenglong Wang. 2022-04-22. Synthesizing Analytical SQL Queries from Computation Demonstration. https://doi.org/10.1145/3519939.3523712

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