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GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables

Authors:

Alexander K. Lew,

Ulrich Schaechtle,

Cameron E. Freer,

Martin C. Rinard,

Vikash K. MansinghkaAuthors Info & Claims

Proceedings of the ACM on Programming Languages, Volume 8, Issue PLDI

Article No.: 179, Pages 790 - 815

https://doi.org/10.1145/3656409

Published: 20 June 2024 Publication History

Abstract

This article presents GenSQL, a probabilistic programming system for querying probabilistic generative models of database tables. By augmenting SQL with only a few key primitives for querying probabilistic models, GenSQL enables complex Bayesian inference workflows to be concisely implemented. GenSQL’s query planner rests on a unified programmatic interface for interacting with probabilistic models of tabular data, which makes it possible to use models written in a variety of probabilistic programming languages that are tailored to specific workflows. Probabilistic models may be automatically learned via probabilistic program synthesis, hand-designed, or a combination of both. GenSQL is formalized using a novel type system and denotational semantics, which together enable us to establish proofs that precisely characterize its soundness guarantees. We evaluate our system on two case real-world studies—an anomaly detection in clinical trials and conditional synthetic data generation for a virtual wet lab—and show that GenSQL more accurately captures the complexity of the data as compared to common baselines. We also show that the declarative syntax in GenSQL is more concise and less error-prone as compared to several alternatives. Finally, GenSQL delivers a 1.7-6.8x speedup compared to its closest competitor on a representative benchmark set and runs in comparable time to hand-written code, in part due to its reusable optimizations and code specialization.

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Cited By

Collins KSucholutsky IBhatt UChandra KWong LLee MZhang CZhi-Xuan THo MMansinghka VWeller ATenenbaum JGriffiths T(2024)Building machines that learn and think with peopleNature Human Behaviour10.1038/s41562-024-01991-98:10(1851-1863)Online publication date: 22-Oct-2024
https://doi.org/10.1038/s41562-024-01991-9

Index Terms

GenSQL: A Probabilistic Programming System for Querying Generative Models of Database Tables
1. Mathematics of computing
  1. Mathematical software
    1. Statistical software
  2. Probability and statistics
    1. Probabilistic inference problems
      1. Bayesian computation
2. Software and its engineering
  1. Software notations and tools
    1. Formal language definitions
      1. Semantics

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cover image Proceedings of the ACM on Programming Languages

Proceedings of the ACM on Programming Languages Volume 8, Issue PLDI

June 2024

2198 pages

EISSN:2475-1421

DOI:10.1145/3554317

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Cited By

Collins KSucholutsky IBhatt UChandra KWong LLee MZhang CZhi-Xuan THo MMansinghka VWeller ATenenbaum JGriffiths T(2024)Building machines that learn and think with peopleNature Human Behaviour10.1038/s41562-024-01991-98:10(1851-1863)Online publication date: 22-Oct-2024
https://doi.org/10.1038/s41562-024-01991-9

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