Based On Materialized Views Of Olap Query Performance Optimization Research And Application

With the development of enterprises, business data from different business systemhave increased, however the enterprise can’t make use of these business data.Fortunately, Data Warehouse technology solves the problem. Company can build asubject-oriented Data Warehouse where they may apply OLAP (On Line AnalysisProcessing) on. OLAP is a fast decision-making system, it can help leader to make aclear judgment on the future development of enterprises. But a new problem comes outin the application process. Vast amounts of data force OLAP queries need more timeand their performance become slower which make company discard their OLAP system.The Data Warehouse performance issues become a important problem. MaterializedView technology which enhances the performance of Data Warehouse has been appliedon major commercial database company. However Materialize View technology facestwo problems: Materialized View selection problem and Query Rewriting problem.This thesis made the following contributions: First, we show a brief analysis aboutMaterialized View which enhances the performance. Second, we talk about a detailedanalysis of the existing materialized view selection algorithm, including their viewmodel, cost model, the description of algorithm and their advantages and disadvantages.Third, an improvement algorithm based on greedy algorithm was proposed. Fourth, weestablished some rules of the query rewriting which allow user use materialized view toanswer their queries transparently. Finally, we implement a digital campus OLAPsystem which was used for performance improvement testing by materialized views.