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Database Tuning Using Trade-Off Elimination

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Encyclopedia of Database Systems

Definition

Database systems need to be prepared to cope with trade-offs arising from different kinds of workloads that different deployments of the same system need to support. To this end, systems offer tuning parameters that allow experienced system administrators to tune the system to the workload characteristics of the application(s) at hand. As part of the self-management capabilities of a database system, it is desirable to eliminate these tuning parameters and rather provide an algorithm for parameter settings such that near-optimal performance is achieved across a very wide range of workload properties. This is the trade-off elimination paradigm. The nature of the solution for trade-off elimination depends on specific tuning problems; its principal feasibility has been successfully demonstrated on issues such as file striping and cache management.

Historical Background

To cope with applications that exhibit a wide variety of workload characteristics, database systems have...

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Recommended Reading

  1. Cao P, Irani S. Cost-aware WWW proxy caching algorithms. In: Proceedings of the 1st USENIX Symposium on Internet Technologies and Systems; 1997.

    Google Scholar 

  2. Chen PM, Lee EL, Gibson GA, Katz RH, Patterson DA. RAID: high-performance, reliable secondary storage. ACM Comput Surv. 1994;26(2):145–85.

    Article  Google Scholar 

  3. Coffman Jr EG, Denning PJ. Operating systems theory. Englewood Cliffs: Prentice-Hall; 1973.

    Google Scholar 

  4. Gray J, Graefe G. The five-minute rule ten years later, and other computer storage rules of thumb. ACM SIGMOD Rec. 1997;26(4):63–8.

    Article  Google Scholar 

  5. Johnson T, Shasha D. 2Q: a low overhead high performance buffer management replacement algorithm. In: Proceedings of the 20th International Conference on Very Large Data Bases; 1994. p. 439–50.

    Google Scholar 

  6. Lee D, Choi J, Kim JH, Noh SH, Min SL, Cho Y, Kim CS. LRFU: a spectrum of policies that subsumes the least recently used and least frequently used policies. IEEE Trans Comput. 2001;50(12):1352–61.

    Article  MathSciNet  MATH  Google Scholar 

  7. Megiddo N, Modha DS. Outperforming LRU with an adaptive replacement cache algorithm. IEEE Comput. 2004;37(4):58–65.

    Article  Google Scholar 

  8. O’Neil EJ, O’Neil PE, Weikum G. The LRU-K page replacement algorithm for database disk buffering. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1993. p. 297–306.

    Google Scholar 

  9. Scheuermann P, Weikum G, Zabback P. Data partitioning and load balancing in parallel disk systems. VLDB J. 1998;7(1):48–66.

    Article  Google Scholar 

  10. Young NE. On-line file caching. Algorithmica. 2002;33(3):371–83.

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Surajit Chaudhuri .

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Chaudhuri, S., Weikum, G. (2018). Database Tuning Using Trade-Off Elimination. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_44

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