On the optimal nesting order for computing N-relational joins
ACM Transactions on Database Systems (TODS)
Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Approximating the minimum-degree Steiner tree to within one of optimal
SODA selected papers from the third annual ACM-SIAM symposium on Discrete algorithms
An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Optimal edge ranking of trees in linear time
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
On minimum edge ranking spanning trees
Journal of Algorithms
Minimum Edge Ranking Spanning Trees of Threshold Graphs
ISAAC '02 Proceedings of the 13th International Symposium on Algorithms and Computation
Advanced Database Systems
Parallel query processing and edge ranking of graphs
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
Edge ranking of weighted trees
Discrete Applied Mathematics
Edge ranking and searching in partial orders
Discrete Applied Mathematics
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
Edge ranking of weighted trees
Discrete Applied Mathematics
Parallel query processing and edge ranking of graphs
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
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In this paper we deal with the problem of finding an optimal query execution plan in database systems. We improve the analysis of a polynomial-time approximation algorithm due to Makino et al. for designing query execution plans with almost optimal number of parallel steps. This algorithm is based on the concept of edge ranking of graphs. We use a new upper bound for the edge ranking number of a tree to derive a better worst-case performance guarantee for this algorithm. We also present some experimental results obtained during the tests of the algorithm on random graphs in order to compare the quality of both approximation ratios on average. Both theoretical analysis and experimental results indicate the superiority of our approach.