Parallel join algorithms based on parallel B/sup +/-trees

Within the last several years, a number of parallel algorithms for the join operation have been proposed. However, almost all of these algorithms do not take advantage of the underlying parallel storage structures or data declustering methods of the operand relations. The paper introduces the concept of parallel storage structure or declustering aware parallel join algorithm. Two classes of parallel join algorithms, which take advantage of the underlying parallel B/sup +/-tree index, are proposed and analyzed. One class is based on the range-partition strategy. The other is based on the hash-partition strategy. The parallel execution times of the algorithms are linearly proportional to max{N/P, M/P}, where N and M are the numbers of tuples of the operand relations and P is the number of processing nodes. The proposed parallel join algorithms are compared with well known parallel join algorithms in practice. Theoretical and experimental results show that the proposed algorithms are more efficient than others in case of at least one operand relation having a parallel B/sup +/-tree index on the join attributes.