- Titel
- BUZZARD
- Untertitel
- A NUMA-Aware In-Memory Indexing System
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-794631
- Konferenz
- SIGMOD/PODS'13: International Conference on Management of Data. New York, 22. - 27. Juni 2013
- Quellenangabe
- SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Herausgeber: Kenneth Ross
Herausgeber: Divesh Srivastava
Herausgeber: Dimitris Papadias
Erscheinungsort: New York
Verlag: ACM
Erscheinungsjahr: 2013
Seiten: 1285-1286
ISBN: 978-1-4503-2037-5 - Erstveröffentlichung
- 2013
- Abstract (EN)
- With the availability of large main memory capacities, in-memory index structures have become an important component of modern data management platforms. Current research even suggests index-based query processing as an alternative or supplement for traditional tuple-at-a-time processing models. However, while simple sequential scan operations can fully exploit the high bandwidth provided by main memory, indexes are mainly latency bound and spend most of their time waiting for memory accesses. Considering current hardware trends, the problem of high memory latency is further exacerbated as modern shared-memory multiprocessors with non-uniform memory access (NUMA) become increasingly common. On those NUMA platforms, the execution time of index operations is dominated by memory access latency that increases dramatically when accessing memory on remote sockets. Therefore, good index performance can only be achieved through careful optimization of the index structure to the given topology. BUZZARD is a NUMA-aware in-memory indexing system. Using adaptive data partitioning techniques, BUZZARD distributes a prefix-tree-based index across the NUMA system and hands off incoming requests to worker threads located on each partition's respective NUMA node. This approach reduces the number of remote memory accesses to a minimum and improves cache utilization. In addition, all indexes inside BUZZARD are only accessed by their respective owner, eliminating the need for synchronization primitives like compare-and-swap.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der ACM Digital Library erschienen ist.
DOI: 10.1145/2463676.2465342 - Freie Schlagwörter (DE)
- NUMA, In-Memory-Indizierung, Präfixbäume
- Freie Schlagwörter (EN)
- NUMA, in-memory indexing, prefix trees
- Klassifikation (DDC)
- 004
- Verlag
- ACM, New York
- Förder- / Projektangaben
- Deutsche Forschungsgemeinschaft (DFG)
Sonderforschungsbereiche
HAEC - Highly Adaptive Energy-Efficient Computing
(SFB 912)
ID: 164481002 - Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-794631
- Veröffentlichungsdatum Qucosa
- 14.06.2022
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
