Snapshot Semantics for Temporal Multiset Relations (Extended Version)

TL;DR

This paper introduces a new temporal data model based on K-relations that correctly implements snapshot semantics for interval-timestamped multiset relations, fixing existing bugs and improving query performance.

Contribution

The authors propose a novel K-relations based model that accurately encodes snapshot semantics and provides an efficient middleware implementation.

Findings

The new model corrects bugs in existing snapshot semantics approaches.

Experimental results show the middleware outperforms native implementations on aggregation queries.

The approach is competitive with native database solutions.

Abstract

Snapshot semantics is widely used for evaluating queries over temporal data: temporal relations are seen as sequences of snapshot relations, and queries are evaluated at each snapshot. In this work, we demonstrate that current approaches for snapshot semantics over interval-timestamped multiset relations are subject to two bugs regarding snapshot aggregation and bag difference. We introduce a novel temporal data model based on K-relations that overcomes these bugs and prove it to correctly encode snapshot semantics. Furthermore, we present an efficient implementation of our model as a database middleware and demonstrate experimentally that our approach is competitive with native implementations and significantly outperforms such implementations on queries that involve aggregation.