Query Optimization for Parallel Relational Databases

本研究针对关系查询的问题 通用并行机的优化。 的 本项目的主要目标是开发查询优化器 这将为并行机生成高效的查询计划。 数据库查询优化器的三个主要组件是其 查询计划表示、其成本模型及其搜索 算法 本项目涉及制定计划的问题 包含运算符内和运算符间的表示 并行性，以及流水线。 此外，成本模型 将被开发，区分总的工作， 即，它在单处理器上所花费的（顺序）时间， 多处理器上的总（并行）时间。 成本模式 取决于查询和数据库参数，以及 体系结构参数。 基于成本的搜索算法选择 高效（低成本）查询计划。 由于搜索空间很大， 比在单处理器查询优化中发现的要大， 研究将开发新的算法来修剪搜索空间。 此外，由于多处理器是可用的， 还将研究并行处理对 优化过程本身。 这项研究的结果将 影响并行查询处理的效率 关系数据库

This research address the problem of relational query optimization for general purpose parallel machines. The principle objective of this project to develop query optimizer that will generate efficient query plans for parallel machines. The three main components of a database query optimizer are its query plan representation, its cost model, and its search algorithm. This project addresses the issue of developing a plan representation that incorporates intra- and inter-operator parallelism, as well as pipelining. Furthermore, cost models will be developed which distinguish between the total work done, i.e. the (sequential) time it would take on a uni-processor and total (parallel) time taken on a multi-processor. The cost model depends on the query and database parameters, as well as architecture parameters. A cost-based search algorithm selects efficient (low cost) query plans. Since the search space is much larger than that found in uni-processor query optimization, this research will develop new heuristics to prune the search space. Furthermore, since a multiprocessor is available, the research will also investigate applicability of parallel processing to the optimization process itself. The results of this research will have an impact on efficient query processing in parallel relational databases.