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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 ×.

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Metadaten
Author of HS ReutlingenPetrov, 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
Year of Publication:2022
Page Number:5
First Page:1
Last Page:5
Article Number:12
DDC classes:004 Informatik
Open Access?:Nein
Licence (English):License Logo  Lizenzbedingungen ACM