Performance Verification of IDL Architecture for Partitioned Database
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F24%3A39922408" target="_blank" >RIV/00216275:25530/24:39922408 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.23919/FRUCT64283.2024.10749911" target="_blank" >http://dx.doi.org/10.23919/FRUCT64283.2024.10749911</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/FRUCT64283.2024.10749911" target="_blank" >10.23919/FRUCT64283.2024.10749911</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Performance Verification of IDL Architecture for Partitioned Database
Popis výsledku v původním jazyce
With the increasing popularity of ORM frameworks and the need to efficiently manage large volumes of data, optimization of these approaches is becoming an increasingly common subject of research. This paper focuses on analyzing the impact of partitioning of database tables on the performance of the Intelligent Data Layer (IDL), which was introduced in our previous study "Design of Data Access Architecture Using an ORM Framework". IDL enables the implementation of ORM frameworks with loaded data prediction, which overall improves and accelerates access to database data. This work extends previous experiments by optimizing IDL through database table partitioning and thoroughly analyzes the impact of this technique on system behavior and performance. We experimentally verify the applicability of this optimization technique in a practical environment and quantify the achieved performance improvements of IDL. The results show that properly designed partitioning can significantly contribute to the overall system efficiency while maintaining its flexibility and scalability.
Název v anglickém jazyce
Performance Verification of IDL Architecture for Partitioned Database
Popis výsledku anglicky
With the increasing popularity of ORM frameworks and the need to efficiently manage large volumes of data, optimization of these approaches is becoming an increasingly common subject of research. This paper focuses on analyzing the impact of partitioning of database tables on the performance of the Intelligent Data Layer (IDL), which was introduced in our previous study "Design of Data Access Architecture Using an ORM Framework". IDL enables the implementation of ORM frameworks with loaded data prediction, which overall improves and accelerates access to database data. This work extends previous experiments by optimizing IDL through database table partitioning and thoroughly analyzes the impact of this technique on system behavior and performance. We experimentally verify the applicability of this optimization technique in a practical environment and quantify the achieved performance improvements of IDL. The results show that properly designed partitioning can significantly contribute to the overall system efficiency while maintaining its flexibility and scalability.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10200 - Computer and information sciences
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of the 36th Conference of Open Innovations Association FRUCT
ISBN
978-952-65-2462-7
ISSN
2305-7254
e-ISSN
2343-0737
Počet stran výsledku
6
Strana od-do
469-474
Název nakladatele
IEEE (Institute of Electrical and Electronics Engineers)
Místo vydání
New York
Místo konání akce
Helsinky
Datum konání akce
30. 10. 2024
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—