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Optimized method for operations of data warehouse

Wang Ming-ting, Jiangtao Sun

Abstract

Data cube has been playing an important role in the multidimensional OLAP operations.However,the situation is quite different when it comes to many applications of high-dimensional data warehouse.For instance,it has over 100 dimensions and about 106 tuples.Under this circumstance,it is unfeasible to construct materialized data cube.OLAP operations are done on high-dimensional data set by using minimal cubing approach.But every times OLAP operations are connected with several dimensions that have stable distribution,so there are many overlapped computation on that and increase the times of input and output disk operations.OLAP operations are done very efficiently by using pre-computed materialized data cube when we materialize the concerned dimensions that are related to many given OLAP operations.

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Key concepts: Online analytical processing, Data warehouse, Computer science, Data cube, Materialized view, Cube (algebra), Construct (python library), Set (abstract data type)