Overview
Temporal data is ubiquitous, and its importance has been witnessed by the recent introduction of temporal features in the SQL standard and commercial database management systems (DBMSs). Despite such efforts, current DBMSs offer little support for query formulation and processing. This makes application code and SQL queries complex and inefficient. Temporal alignment is the first and only framework that provides comprehensive temporal query support over interval-timestamped data and allows a tight integration into existing DBMSs (see http://tpg.inf.unibz.it). While the approach minimizes the changes of the host DBMS and leverages its query optimization techniques, important aspects of the efficiency of the query processing remain as unaddressed open problems.
This project aims at boosting the efficiency and scalability of query processing in the temporal alignment framework by tackling the following challenges:
- The current approach works with two primitives to transform temporal queries into non-temporal queries, which might produce large and redundant intermediate relations. In order to avoid this, we will explore new alignment primitives that are customized for specific temporal operators.
- Since current cost estimates for intermediate relations are very conservative, we will develop more realistic cost estimates to feed into the query optimizer.
- We will invent new algebraic equivalence rules for query optimization that exploit specific properties of temporal operators.
Funding
This project is funded by the Autonomous Province of Bozen-Bolzano with research call “Research Südtirol/Alto Adige 2019“ (CUP: I52F20000250003).
Partners
