An efficient processing of a chain join with the minimum communication cost in distributed database systems

This paper investigates the optimization problem when executing a join in a distributed database environment. The minimization of the communication cost for sending data through links has been adopted as an optimization criterion. We explore in this paper the approach of judiciously using join operations as reducers in distributed query processing. In general, this problem is computationally intractable. A restriction of the execution of a join in a pre-defined combinatorial order leads to a possible solution in polynomial time. An algorithm for a chain query computation has been proposed in [21]. The time complexity of the algorithm is O(m2n2+m3n), where n is the number of sites in the network, and m is the number of relations (fragments) involved in the join. In this paper, we firstly present a proof of the intuitively well understood fact-that the "eigenorder" of a "chain" join will be the best pre-defined combinatorial order to implement the algorithm in [21]. Secondly, we show a sufficient and necessary condition for a chain query with the eigenordering to be a "simple" query. For the process of the class of simple queries, we show a significant reduction of the time complexity from O(m2n2+m3n) to O(mn+m2). It is encouraging that, in practice, the most frequent queries belong to the category of simple queries