Deductive optimization of relational data storage
Name
3428238.pdf
Description
Published version
Size
628.9 KB
Format
Adobe PDF
Checksum (MD5)
bee99cb2fbe0f838a1ab55197511c904
Author(s)
Feser, John
Madden, Sam
Tang, Nan
Solar-Lezama, Armando
Date Issued
2020
Journal
Proceedings of the ACM on Programming Languages
Publisher
Association for Computing Machinery (ACM)
Version
Final published version
Abstract
© 2020 Owner/Author. Optimizing the physical data storage and retrieval of data are two key database management problems. In this paper, we propose a language that can express both a relational query and the layout of its data. Our language can express a wide range of physical database layouts, going well beyond the row- and column-based methods that are widely used in database management systems. We use deductive program synthesis to turn a high-level relational representation of a database query into a highly optimized low-level implementation which operates on a specialized layout of the dataset. We build an optimizing compiler for this language and conduct experiments using a popular database benchmark, which shows that the performance of our specialized queries is better than a state-of-the-art in memory compiled database system while achieving an order-of-magnitude reduction in memory use.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3428238
