Algorithms for the database layout problem

  • Authors:

  • Gagan Aggarwal;Tomás Feder;Rajeev Motwani;Rina Panigrahy;An Zhu

  • Affiliations:

  • Computer Science Department, Stanford University, Stanford, CA;Computer Science Department, Stanford University, Stanford, CA;Computer Science Department, Stanford University, Stanford, CA;Computer Science Department, Stanford University, Stanford, CA;Computer Science Department, Stanford University, Stanford, CA

  • Venue:
  • ICDT'05 Proceedings of the 10th international conference on Database Theory
  • Year:
  • 2005

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Abstract

We present a formal analysis of the database layout problem, i.e., the problem of determining how database objects such as tables and indexes are assigned to disk drives. Optimizing this layout has a direct impact on the I/O performance of the entire system. The traditional approach of striping each object across all available disk drives is aimed at optimizing I/O parallelism; however, it is suboptimal when queries co-access two or more database objects, e.g., during a merge join of two tables, due to the increase in random disk seeks. We adopt an existing model, which takes into account both the benefit of I/O parallelism and the overhead due to random disk accesses, in the context of a query workload which includes co-access of database objects. The resulting optimization problem is intractable in general and we employ techniques from approximation algorithms to present provable performance guarantees. We show that while optimally exploiting I/O parallelism alone suggests uniformly striping data objects (even for heterogeneous files and disks), optimizing random disk access alone would assign each data object to a single disk drive. This confirms the intuition that the two effects are in tension with each other. We provide approximation algorithms in an attempt to optimize the trade-off between the two effects. We show that our algorithm achieves the best possible approximation ratio.