- Adaptive segmentation for scientific databases
- 2008 IEEE 24th International Conference on Data Engineering
- Book/source title
- ICDE 2008: proceedings of the 2008 IEEE 24th International Conference on Data Engineering: April 7-12, 2008, Cancun, Mexico
- Pages (from-to)
- Piscataway, NJ: IEEE
- Document type
- Conference contribution
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
In this paper we explore database segmentation in the context of a column-store DBMS targeted at a scientific database. We present a novel hardware- and scheme-oblivious segmentation algorithm, which learns and adapts to the workload immediately. The approach taken is to capitalize on (intermediate) query results, such that future queries benefit from a more appropriate data layout. The algorithm is implemented as an extension of a complete DBMS and evaluated against a real-life workload. It demonstrates significant performance gains without DBA assistance.
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