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Database design principles for placement of delay-sensitive data on disks

机译:用于在磁盘上放置对延迟敏感的数据的数据库设计原则

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Investigates design principles for placing striped delay-sensitive data on a number of disks in a distributed environment. The cost formulas of our performance model allow us to calculate the maximum number of users that can be supported by n disks, as well as to study the impact of other performance-tuning options. We show that, for fixed probabilities of accessing the delay-sensitive objects, partitioning the set of disks is always better than striping in all of the disks. Then, given a number n of disks and r distinct delay-sensitive objects with access probabilities p/sub 1/, p/sub 2/, ..., p/sub r/ that must be striped across r different disk partitions (i.e. nonoverlapping subsets of the n disks), we use the theory of Schur functions in order to find what is the optimal number of disks that must be allocated to each partition. For objects with different consumption rates, we provide an analytic solution to the problem of disk partitioning. We analyze the problem of grouping the more- and less-popular delay-sensitive objects together in partitions-when the partitions are less than the objects-so that the number of supported users is maximized. Finally, we analyze the trade-off of striping on all the disks versus partitioning the set of the disks when the access probabilities of the delay-sensitive objects change with time.
机译:研究将分布式延迟敏感数据放置在分布式环境中的多个磁盘上的设计原则。我们的性能模型的成本公式使我们能够计算n个磁盘可支持的最大用户数,并研究其他性能调整选项的影响。我们显示出,对于访问延迟敏感对象的固定概率而言,对磁盘集进行分区总是比对所有磁盘进行条带化更好。然后,给定n个磁盘和r个具有访问概率p / sub 1 /,p / sub 2 /,...,p / sub r /的不同的延迟敏感对象,它们必须在r个不同的磁盘分区上进行条带化(即n个磁盘的非重叠子集),我们使用Schur函数的理论来找出必须分配给每个分区的最佳磁盘数量。对于消耗率不同的对象,我们提供了磁盘分区问题的解析解决方案。我们分析了在分区少于对象的情况下,将受欢迎程度较低的对延迟敏感的对象归为一组的问题,以便使受支持的用户数量最大化。最后,当延迟敏感对象的访问概率随时间变化时,我们分析了在所有磁盘上进行条带化与对磁盘组进行分区之间的权衡取舍。

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