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Materialized Views Optimal Selection for Data Warehouse Quality

机译:物质化视图数据仓库质量的最佳选择

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摘要

For the success of any data warehouse, accurate and timely consolidated information along with quick and effective query response times is the basic fundamental requirement. The materialization of all views is practically impossible because of the materialized view storage space and maintenance cost constraint thus proper materialized views selection is one of the intelligent decisions in designing a data warehouse to get optimal efficiency. This study presents a framework for selecting best materialized view using algorithm Particle Swarm Optimization (PSO) this algorithm one of the stochastic algorithm so as to achieve the effective combination of good query response time, low query processing cost and low view maintenance cost. The results showed that the proposed method for selecting best materialized view using PSO algorithm is better than other techniques through compute the ratio of query response time and compare it to the response time of the same queries on the materialized views ratio of implementing the query on the base table takes eleven times more than time of the query implementation on the materialized views. Where the response time of queries through MVs access were found 0092 msec while through direct access queries were found 1039 msec. This show the performance of query through materialized views access is 1029.34% better than those directly access through data warehouse.
机译:对于任何数据仓库的成功,准确和及时的合并信息以及快速有效的查询响应时间是基本的基本要求。所有视图的实现实际上是不可能的,因为物化的视图存储空间和维护成本约束因此正确的实化视图选择是设计数据仓库以获得最佳效率的智能决策之一。本研究介绍了使用算法粒子群优化(PSO)选择最佳物化视图的框架本算法,即该算法之一,以实现良好查询响应时间,低查询处理成本和低视图维护成本的有效组合。结果表明,使用PSO算法选择最佳物化视图的所提出的方法优于通过计算查询响应时间的比率来优于其他技术,并将其与实现查询的物流视图比的相同查询的响应时间进行比较基本表在物化视图上占用查询实现的十一时间。如果通过直接访问查询找到通过MVS访问的查询响应时间,请通过直接访问查询,找到1039毫秒。这显示了通过物化视图访问的查询性能比通过数据仓库直接访问更好的价格为1029.34%。

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