一种OLAP海量数据载入技术的研究

在数据仓库、数据挖掘和联机分析处理系统中,海量数据的载入虽然不是时时发生,但是海量数据的载入效率直接影响着系统性能,如何高效地进行海量数据的载入十分重要.提出了两种技术,即基于UB-Tree的海量数据的初始化载入技术以及海量数据的增量载入技术,阐述了基于UB-Tree的海量数据载入的技术及其算法,提出了海量数据载入模型,建立基于UB-Tree的初始化载人,以及如何在已有的UB-Tree上做增量载入.经过性能分析,算法减少了I/O和CPU代价,为一种有效的海量数据载入方法.

Study on OLAP Mass Data Loading Technology

In data warehouse, data mining and OLAP large data sets loading occurs not continuously, but the loading efficiency influences the performance of the system. It is necessary to have efficient mass data loading techniques. In this paper, proposes two techniques, one for initial loading based on one new UB- Tree, and one for incremental loading, which adds data to an existing UB - Tree. Proposes a model of mass data loading and two techniques, one for initial loading,whlch creates a new UB- Tree, and one for incremental loading, which adds data to an existing LIB- Tree. Both teehniques try to minimize I/O and CPU cost. Analysis demonstrates that the algorithms are efficient and able to handle large data sets.