DeQL: A Decision Query Language for Prescriptive Analytics over Relational Data

2026-06-17

AI Summary

This work addresses the challenge of efficiently expressing and solving constrained optimization problems over relational data, bridging the gap from descriptive to prescriptive analytics. To this end, the authors propose an extension to SQL that introduces two declarative constructs—CREATE CANDIDATES and DECIDE—enabling users to naturally specify candidate solutions, constraints, and optimization objectives, with the system automatically computing optimal decisions. This approach represents the first seamless integration of combinatorial optimization logic into the SQL framework, preserving relational algebra semantics while supporting canonical scenarios such as subset selection, resource allocation, and task scheduling. Furthermore, it provides extensible mechanisms for handling uncertainty-aware optimization and model scoring, thereby laying a foundation for the evolution of declarative decision-making languages.

Abstract

DeQL (Decision Query Language) extends SQL to express decision queries: given options drawn from relational data, constraints from policy, and a measurable objective, a DeQL query computes the best course of action. Two constructs carry the extension: CREATE CANDIDATES, which defines the space of options from relational sources, and DECIDE, which declares decision variables, named constraints, and an objective over them. The design follows SQL's principles: the user states what to optimize while the engine chooses how to solve it, every query consumes and produces relations, and the structure of a problem stays visible to the engine. This document specifies the language (its design principles, syntax, formal grammar, and execution model) with examples spanning subset selection, allocation, assignment, scheduling, and decisions at multiple levels of aggregation, and extensions for optimization under uncertainty, inline model scoring, and time- and quality-bounded solving. It is the first version of the specification; the language is under active development, and this version fixes the core constructs on which later revisions will build.

Problem

• prescriptive analytics
• decision query
• relational data
• optimization
• SQL extension

Innovation

• Decision Query Language
• Prescriptive Analytics
• Relational Optimization
• SQL Extension
• Declarative Decision Making