透過您的圖書館登入
IP:18.118.26.249

並列摘要


Data warehouses contain data consolidated from several operational databases and provide the historical, and summarized data. On-Line Analytical Processing (OLAP) is designed to provide aggregate information to analyze the contents of data warehouses. An increasingly popular data model for OLAP applications is the multidimensional database, also known as data cube. A range sum query applies a sum aggregation operation over all selected cells of an OLAP data cube where the selection is specified by providing ranges of values for numeric dimensions. It is very useful in finding trends and in discovering relationships between attributes in the database. For today's applications, interactive data analysis applications which provide the current information will require fast response time and have reasonable update time. Since the size of a data cube is exponential in the number of its dimensions, it costs a lot of time to rebuild the entire data cube. To solve these updating problem, we present the recursive relative prefix sum method, which provides a compromise between query and update cost. From our performance study, we show that the update cost of our method is always less than that of the prefix sum method. Our recursive relative prefix sum method has a reasonable response time for ad hoc range queries on the data cube, while at the same time, greatly reduces the update cost.

並列關鍵字

data warehouse OLAP range query range sum query update

延伸閱讀