Challenges for Efficient Query Evaluation on Structured Probabilistic Data

TL;DR

This paper discusses the challenges and potential solutions for efficient query evaluation on structured probabilistic data, emphasizing the use of structural decompositions like tree decompositions in database management systems.

Contribution

It presents a vision for a probabilistic database system leveraging structural decompositions and reviews ongoing work and challenges in this approach.

Findings

Structural decompositions can improve query efficiency.

Many theoretical and practical challenges remain.

A new vision for probabilistic database management systems.

Abstract

Query answering over probabilistic data is an important task but is generally intractable. However, a new approach for this problem has recently been proposed, based on structural decompositions of input databases, following, e.g., tree decompositions. This paper presents a vision for a database management system for probabilistic data built following this structural approach. We review our existing and ongoing work on this topic and highlight many theoretical and practical challenges that remain to be addressed.