Execution of multidatabase queries differs from that of traditional queries in that sort merge and hash joins are more often favored, as nested loop join requires repeated accesses to external data sources. As a consequence, left deep join trees obtained by traditional (e.g., System-R style) optimizers for multi-database queries are often suboptimal, with respect to response time, due to the long delay for a sort merge (or hash) join node to produce its last result after the subordinate join node did. In this paper, we present an optimization strategy that first produces an optimal left deep join tree and then reduces the response time using simple tree transformations. This strategy has the advantages of guaranteed minimum total resource usage, improved response time, and low optimization overhead. We describe a class of basic transformations that is the cornerstone of our approach. Then we present algorithms that effectively apply basic transformations to balance a left deep join tree, and discuss how the technique can be incorporated into existing query optimizers. © 1995, ACM. All rights reserved.
CITATION STYLE
Du, W., Shan, M. C., & Dayal, U. (1995). Reducing Multidatabase Query Response Time By Tree Balancing. ACM SIGMOD Record, 24(2), 293–303. https://doi.org/10.1145/568271.223846
Mendeley helps you to discover research relevant for your work.