A Join Algorithm for Large Databases: A Quadtrees Structure Approach

Abstract

Enhancing the performance of large database systems depends heavily on the cost of performing join operations. When two very large tables are joined, optimizing such operation is considered one of the interesting research topics to many researchers, especially when both tables, to be joined, are very large to fit in main memory. In such case, join is usually performed by any other method than hash join algorithms. In this paper, a novel join algorithm that is based on the use of quadtrees, is introduced. Applying the proposed algorithm on two very large tables, that are too large to fit in main memory, is proven to be fast and efficient. In the proposed new algorithm, both tables are represented by a storage efficient quadtree that is designed to handle one-dimensional arrays (1-D arrays). The algorithm works on the two 1-D arrays of the two tables to perform join operations. For the new algorithm, time and space complexities are studied. Experimental studies show the efficiency and superiority of this algorithm. The proposed join algorithm requires a minimum number of I/O operations and operates in main memory with O(n log (n/k)) time complexity, where k is the number of key groups with the same first letter, and (n/k) is much smaller than n.