Optimization of large join queries

  • Authors:

  • Arun Swami;Anoop Gupta

  • Affiliations:

  • Stanford Univ., Stanford, CA;Stanford Univ., Stanford, CA

  • Venue:
  • SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
  • Year:
  • 1988

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Abstract

We investigate the problem of optimizing Select—Project—Join queries with large numbers of joins. Taking advantage of commonly used heuristics, the problem is reduced to that of determining the optimal join order. This is a hard combinatorial optimization problem. Some general techniques, such as iterative improvement and simulated annealing, have often proved effective in attacking a wide variety of combinatorial optimization problems. In this paper, we apply these general algorithms to the large join query optimization problem. We use the statistical techniques of factorial experiments and analysis of variance (ANOVA) to obtain reliable values for the parameters of these algorithms and to compare these algorithms. One interesting result of our experiments is that the relatively simple iterative improvement proves to be better than all the other algorithms (included the more complex simulated annealing). We also find that the general algorithms do quite well at the maximum time limit.