Sample-Based Cardinality Estimation in Full Outer Join Queries

Uriy Grigorev, Andrey Ploutenko, Aleksey Burdakov, Olga Pluzhnikova, Evgeny Detkov

2024

Abstract

Efficient query planning is crucial in large smart databases, where the complexity of joining tables can exceed a hundred. This paper addresses the pivotal role of cardinality estimation in generating effective query plans within a Database Management System (DBMS). Over the past decade, various estimation methods have been developed, yet their accuracy tends to decrease as the number of joined tables increases due to specific constraints and prerequisites. This paper introduces EVACAR, a novel cardinality estimation method rooted in the theory of approximate aggregate calculations. Unlike existing methods, EVACAR is designed to alleviate limitations associated with increasing table joins. Our method not only matches but often surpasses the accuracy of machine learning methods, achieving superior results for 75-88% of the evaluated queries (subplans). This advancement signifies a promising step towards optimizing query performance in large-scale smart databases.

Paper Citation

in Harvard Style

Grigorev U., Ploutenko A., Burdakov A., Pluzhnikova O. and Detkov E. (2024). Sample-Based Cardinality Estimation in Full Outer Join Queries. In Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS; ISBN 978-989-758-699-6, SciTePress, pages 235-244. DOI: 10.5220/0012682000003705

in Bibtex Style

@conference{iotbds24,
author={Uriy Grigorev and Andrey Ploutenko and Aleksey Burdakov and Olga Pluzhnikova and Evgeny Detkov},
title={Sample-Based Cardinality Estimation in Full Outer Join Queries},
booktitle={Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS},
year={2024},
pages={235-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012682000003705},
isbn={978-989-758-699-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS
TI - Sample-Based Cardinality Estimation in Full Outer Join Queries
SN - 978-989-758-699-6
AU - Grigorev U.
AU - Ploutenko A.
AU - Burdakov A.
AU - Pluzhnikova O.
AU - Detkov E.
PY - 2024
SP - 235
EP - 244
DO - 10.5220/0012682000003705
PB - SciTePress