期刊名称：International Journal of Computer Science and Network
印刷版ISSN：2277-5420
出版年度：2014
卷号：3
期号：5
页码：292-297
出版社：IJCSN publisher
摘要：Due to vast use of Internet data grows explosively. A query that is fired on table may require a complete table scan which can take a long time as it has to inspect every row in table. Since, there is no way to identify this problem, becomes more sever for historical tables for which many queries concentrate, access on rows that were generated recently. Partition helps to solve this problem. Partition divide table into partitions. A query that only requires rows that correspond to a single partition or range of partitions can be executed using a partition scan rather than a table scan. Here, proposed Partition Algorithm, based on Rank Partition Tree structure, (PARPT) will map rows to partitions for optimizing the query performance of Max/Min type with mass data. We will compare amount of time required to execute queries on existing Range partition method and proposed partitioning method. The experimental result shows that the implemented method to solve the specific type of queries is much more effective than Range partitioning method
关键词：Rank Decision Tree (RDT);Join;Range Partition Method;Query processing;Relational databases
