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Adaptive Multi-Grained Buffer Management for Database Systems

Author

Listed:
  • Xiaoliang Wang

    (School of Computer Science and Technology, University of Science and Technology of China, Hefei 230026, China)

  • Peiquan Jin

    (School of Computer Science and Technology, University of Science and Technology of China, Hefei 230026, China
    Key Laboratory of Electromagnetic Space Information, China Academy of Sciences, Hefei 230027, China)

Abstract

The traditional page-grained buffer manager in database systems has a low hit ratio when only a few tuples within a page are frequently accessed. To handle this issue, this paper proposes a new buffering scheme called the AMG-Buffer (Adaptive Multi-Grained Buffer). AMG-Buffer proposes to use two page buffers and a tuple buffer to organize the whole buffer. In this way, the AMG-Buffer can hold more hot tuples than a single page-grained buffer. Further, we notice that the tuple buffer may cause additional read I/Os when writing dirty tuples into disks. Thus, we introduce a new metric named clustering rate to quantify the hot-tuple rate in a page. The use of the tuple buffer is determined by the clustering rate, allowing the AMG-Buffer to adapt to different workloads. We conduct experiments on various workloads to compare the AMG-Buffer with several existing schemes, including LRU, LIRS, CFLRU, CFDC, and MG-Buffer. The results show that AMG-Buffer can significantly improve the hit ratio and reduce I/Os compared to its competitors. Moreover, the AMG-Buffer achieves the best performance on a dynamic workload as well as on a large data set, suggesting its adaptivity and scalability to changing workloads.

Suggested Citation

  • Xiaoliang Wang & Peiquan Jin, 2021. "Adaptive Multi-Grained Buffer Management for Database Systems," Future Internet, MDPI, vol. 13(12), pages 1-16, November.
  • Handle: RePEc:gam:jftint:v:13:y:2021:i:12:p:303-:d:688788
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