HINT on Steroids

HINT on Steroids: Batch Query Processing for Interval Data

Bouros, Panagiotis (University of Mainz)
Titkov, Artur (University of Mainz)
Christodoulou, G.C. (TU Delft Web Information Systems)
Rauch, Christian (University of Mainz)
Mamoulis, Nikos (University of Ioannina)

2024

A wide range of applications manage interval data. HINT was recently proposed to hierarchically index intervals in main memory. The index outperforms competitive structures by a wide margin, but under its current setup, HINT is able to service only single query requests. In practice however, real systems receive a large number of queries at the same time and so, our focus in this paper is on batch query processing. We propose two novel evaluation strategies termed level-based and partition-based, which both work in a per-level fashion, i.e., all queries for an index level are computed before moving to the next level. The new strategies operate in a cache-aware fashion to reduce the cache misses caused by climbing the index hierarchy or accessing multiple partitions per level, and to decrease the total execution time for a query batch. Our experimental analysis with both real and synthetic datasets showed that our batch processing strategies always outperform a baseline that executes queries in a serial fashion, and that partition-based is overall the most efficient strategy.

http://resolver.tudelft.nl/uuid:fa44c311-afdc-4795-a5ab-462f1b708afc

https://doi.org/10.48786/edbt.2024.38

OpenProceedings.org

9783893180912

Advances in Database Technology - EDBT (3)

27th International Conference on Extending Database Technology, EDBT 2024, 2024-03-25 → 2024-03-28, Paestum, Italy

Advances in Database Technology - EDBT, 2367-2005, 27 (3)

Institutional Repository

conference paper

© 2024 Panagiotis Bouros, Artur Titkov, G.C. Christodoulou, Christian Rauch, Nikos Mamoulis