最小方方法的一种优化方法

An optimized method for minimal cubing approach

数据立方体在许多多维数据的数据仓库的高速OLAP操作中扮演着重要的角色.但在许多高维的数据仓库的应用中,查询分析效率是个关键的问题.例如超过100维,大约106个元组.在这样高维情况下建立全物化数据立方体来减少分析时间是不可行的.利用最小方的方法可以在高维数据集上进行有效OLAP操作的方法.如果能根据查询分析的历史记录合理地为立方体的维分片,就能在相同空间复杂度的情况下提高OLAP操作的效率.

Data cube has been playing an important role in the high dimensional OLAP operations. However, when it comes to many applications of high-dimensional data warehouse, the efficiency of querying analysis is a critical issue. For instance, some applications are over one hundred dimension about 10^6 tuples. Under this circumstance, it is unfeasible to reduce analyzed time by constructing materialized data cube wholly. OLAP operations on high-dimensional data set can be done by using minimal cubing approach. The high dimensions can be partitioned properly to accelerate querying analysis by studying the historical records of OLAP operations, By doing this the efficiency of OLAF＇ operations can be improved with the similar space complexity.