Result-set management for NDP operations on smart storage
- Current data-intensive systems suffer from scalability as they transfer massive amounts of data to the host DBMS to process it there. Novel near-data processing (NDP) DBMS architectures and smart storage can provably reduce the impact of raw data movement. However, transferring the result-set of an NDP operation may increase the data movement, and thus, the performance overhead. In this paper, we introduce a set of in-situ NDP result-set management techniques, such as spilling, materialization, and reuse. Our evaluation indicates a performance improvement of 1.13 × to 400 ×.
| Author of HS Reutlingen | Petrov, Ilia |
|---|---|
| DOI: | https://doi.org/10.1145/3533737.3535097 |
| ISBN: | 978-1-4503-9378-2 |
| Erschienen in: | DaMoN '22 : proceedings of the 18th International Workshop on Data Management on New Hardware, Philadelphia, PA, June 2022 |
| Publisher: | ACM |
| Place of publication: | New York |
| Document Type: | Conference proceeding |
| Language: | English |
| Publication year: | 2022 |
| Page Number: | 5 |
| First Page: | 1 |
| Last Page: | 5 |
| Article Number: | 12 |
| DDC classes: | 004 Informatik |
| Open access?: | Nein |
| Licence (German): |  In Copyright - Urheberrechtlich geschützt |
