Resiliency-aware data compression for in-memory database systems
Gespeichert in:
| Titel: | Resiliency-aware data compression for in-memory database systems |
|---|---|
| Autoren: | Kolditz, Till, Habich, Dirk, Damme, Patrick, Lehner, Wolfgang, Kuvaiskii, Dmitrii, Oleksenko, Oleksii, Fetzer, Christof |
| Weitere Verfasser: | Helfert, Markus, Holzinger, Andreas, Belo, Orlando, Francalanci, Chiara |
| Quelle: | Kolditz, T, Habich, D, Damme, P, Lehner, W, Kuvaiskii, D, Oleksenko, O & Fetzer, C 2015, Resiliency-aware data compression for in-memory database systems. in M Helfert, A Holzinger, O Belo & C Francalanci (eds), DATA 2015 - 4th International Conference on Data Management Technologies and Applications, Proceedings. SciTePress, DATA 2015 - 4th International Conference on Data Management Technologies and Applications, Proceedings, pp. 326-331, 4th International Conference on Data Management Technologies and Applications, DATA 2015, Colmar, Alsace, France, 20/07/2015. https://doi.org/10.5220/0005557303260331 |
| Verlagsinformationen: | SciTePress |
| Publikationsjahr: | 2015 |
| Bestand: | Aalborg University (AAU): Publications / Aalborg Universitet: Publikationer |
| Schlagwörter: | AN encoding, Data integrity, In-memory database systems, Lightweight data compression |
| Beschreibung: | Nowadays, database systems pursuit a main memory-centric architecture, where the entire business-related data is stored and processed in a compressed form in main memory. In this case, the performance gain is massive because database operations can benefit from its higher bandwidth and lower latency. However, current main memory-centric database systems utilize general-purpose error detection and correction solutions to address the emerging problem of increasing dynamic error rate of main memory. The costs of these general-purpose methods dramatically increases with increasing error rates. To reduce these costs, we have to exploit context knowledge of database systems for resiliency. Therefore, we introduce our vision of resiliency-aware data compression in this paper, where we want to exploit the benefits of both fields in an integrated approach with low performance and memory overhead. In detail, we present and evaluate a first approach using AN encoding and two different compression schemes to show the potentials and challenges of our vision. |
| Publikationsart: | article in journal/newspaper |
| Sprache: | English |
| ISBN: | 978-989-758-103-8 989-758-103-0 |
| Relation: | urn:ISBN:9789897581038 |
| DOI: | 10.5220/0005557303260331 |
| Verfügbarkeit: | https://vbn.aau.dk/da/publications/f7dafa21-1c52-4bbb-af1d-2432d5e5fc81 https://doi.org/10.5220/0005557303260331 http://www.scopus.com/inward/record.url?scp=84964923583&partnerID=8YFLogxK |
| Rights: | info:eu-repo/semantics/openAccess |
| Dokumentencode: | edsbas.1B62B74B |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | Nowadays, database systems pursuit a main memory-centric architecture, where the entire business-related data is stored and processed in a compressed form in main memory. In this case, the performance gain is massive because database operations can benefit from its higher bandwidth and lower latency. However, current main memory-centric database systems utilize general-purpose error detection and correction solutions to address the emerging problem of increasing dynamic error rate of main memory. The costs of these general-purpose methods dramatically increases with increasing error rates. To reduce these costs, we have to exploit context knowledge of database systems for resiliency. Therefore, we introduce our vision of resiliency-aware data compression in this paper, where we want to exploit the benefits of both fields in an integrated approach with low performance and memory overhead. In detail, we present and evaluate a first approach using AN encoding and two different compression schemes to show the potentials and challenges of our vision. |
|---|---|
| ISBN: | 9789897581038 9897581030 |
| DOI: | 10.5220/0005557303260331 |