Abstract
We investigate the use of heuristics in optimizing queries with a large number of joins. Examples of such heuristics are the augmentation and local improvement heuristics described in this paper and a heuristic proposed by Krishnamurthy et al. We also study the combination of these heuristics with two general combinatorial optimization techniques, iterative improvement and simulated annealing, that were studied in a previous paper. Several interesting combinations are experimentally compared. For completeness, we also include simple iterative improvement and simulated annealing in our experimental comparisons. We find that two combinations of the augmentation heuristic and iterative improvement perform the best under most conditions. The results are validated using two different cost models and several different synthetic benchmarks.
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