Maintaining Queries under Updates Using Heavy-Light Partitioning of the Input Relations
Abstract
We study the classical incremental view maintenance problem: Given a query and a database, maintain the query output under single-tuple updates (inserts or deletes) to the database such that the tuples in the query output can be enumerated with constant delay after any update. We introduce a maintenance approach whose update time matches or improves the best update time reported in prior work. Whereas prior approaches are manually tailored to each of a handful of queries, our approach generalizes to arbitrary join queries. It combines three techniques: delta queries, trees of materialized views, and heavy-light data partitioning. The overall update time incurred by our approach for a given join query is characterized by the maintenance width, a new measure that is parameterized by the heavy-light threshold for data partitioning. We show how to find the threshold that minimizes the maintenance width.
Keywords
Cite
@article{arxiv.2605.08397,
title = {Maintaining Queries under Updates Using Heavy-Light Partitioning of the Input Relations},
author = {Mahmoud Abo-Khamis and Eden Chmielewski and Andrei Draghici and Ahmet Kara and Dan Olteanu},
journal= {arXiv preprint arXiv:2605.08397},
year = {2026}
}