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Issue No.01 - February (1994 vol.6)

pp: 152-165

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/69.273034

ABSTRACT

<p>Semijoin has traditionally been relied upon to reduce the cost of data transmission for distributed query processing. However, judiciously applying join operations as reducers can lead to further reduction in the amount of data transmission required. In view of this fact, we explore the approach of using join operations as reducers in distributed query processing. We first show that the problem of determining a sequence of join operations for a query can be transformed to that of finding a specific type of set of cuts to the corresponding query graph, where a cut to a graph is a partition of nodes in that graph. Then, in light of this concept, we prove that the problem of determining the optimal sequence of join operations for a given query graph is of exponential complexity, thus justifying the necessity of applying heuristic approaches to solve this problem. By mapping the problem of determining a sequence of join reducers into the one of finding a set of cuts, we develop (for tree and general query graphs, respectively) efficient heuristic algorithms to determine a join reducer sequence for distributed query processing. The algorithms developed are based on the concept of divide and conquer and are of polynomial time complexity. Simulation is performed to evaluate these algorithms.</p>

INDEX TERMS

distributed databases; query processing; graph theory; database theory; computational complexity; graph theoretical approach; join reducer sequence; distributed query processing; semijoin; data transmission; join operations; query graph; optimal sequence; exponential complexity; heuristic approaches; heuristic algorithms; polynomial time complexity

CITATION

M.-S. Chen, P.S. Yu, "A Graph Theoretical Approach to Determine a Join Reducer Sequence in Distributed Query Processing",

*IEEE Transactions on Knowledge & Data Engineering*, vol.6, no. 1, pp. 152-165, February 1994, doi:10.1109/69.273034