Understanding Queries by Conditional Instances

TL;DR

This paper introduces a method for generating simple, representative data instances that illustrate how relational queries are satisfied, aiding understanding and debugging of complex queries.

Contribution

It formalizes the concept of representative instances for relational queries, proposes algorithms to compute minimal collections of such instances, and demonstrates their practical effectiveness.

Findings

Algorithms efficiently generate representative instances.

User study shows improved query debugging.

Method effectively summarizes all query satisfaction ways.

Abstract

A powerful way to understand a complex query is by observing how it operates on data instances. However, specific database instances are not ideal for such observations: they often include large amounts of superfluous details that are not only irrelevant to understanding the query but also cause cognitive overload; and one specific database may not be enough. Given a relational query, is it possible to provide a simple and generic "representative" instance that (1) illustrates how the query can be satisfied, (2) summarizes all specific instances that would satisfy the query in the same way by abstracting away unnecessary details? Furthermore, is it possible to find a collection of such representative instances that together completely characterize all possible ways in which the query can be satisfied? This paper takes initial steps towards answering these questions. We design what these representative instances look like, define what they stand for, and formalize what it means for them to satisfy a query in "all possible ways." We argue that this problem is undecidable for general domain relational calculus queries, and develop practical algorithms for computing a minimum collection of such instances subject to other constraints. We evaluate the efficiency of our approach experimentally, and show its effectiveness in helping users debug relational queries through a user study.