Optimizing Analytical Query Processing on Disaggregated Hardware
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen
Beitragende
Abstract
In a world of ever-growing amounts of data, hardware-scalability and energy-efficiency become more important with every year. Traditional scale-up and scale-out database management systems (DBMS) struggle to scale well with their growing analytical workloads. Due to this, the emerging technology of disaggregated hardware becomes more and more popular. However, there is no free ride and specific challenges arise. In my PhD topic, I want (i) to look into these challenges for analytical query workloads on disaggregated hardware and (ii) to provide appropriate solutions. First initial results concerning data movement are promising and show the potential of adapted solutions.
Details
| Originalsprache | Englisch |
|---|---|
| Titel | EDBT/ICDT 2023 Workshops |
| Redakteure/-innen | George Fletcher, Verena Kantere |
| Seitenumfang | 4 |
| Band | 3379 |
| Publikationsstatus | Veröffentlicht - 2023 |
| Peer-Review-Status | Nein |
Publikationsreihe
| Reihe | CEUR Workshop Proceedings |
|---|---|
| Band | 3379 |
| ISSN | 1613-0073 |
Externe IDs
| Scopus | 85158928845 |
|---|
Schlagworte
Forschungsprofillinien der TU Dresden
DFG-Fachsystematik nach Fachkollegium
Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis
Ziele für nachhaltige Entwicklung
ASJC Scopus Sachgebiete
Schlagwörter
- RDMA, Disaggregated Memory, Disaggregated Hardware