Research On Multi-Dimensional Data Update And Query Based On P2P

Due to four features of quickness,analytical,multidimensionality and informative, Online Analytical Processing(OLAP) has been widely used in modern society.With the fast development of P2P technology,P2P technology combine with OLAP technology becomes a tendency. Recently,the research on OLAP technology under P2P is mainly about querying speed improvement, such as the introduction of the object buffer pool mechanism and a simple semantic query matching mechanism. But the OLAP efficiency did not significantly increase.Especially,the study of update strategy is still scarce.The data update of multi-dimension does not only need to update OLAP server ,but also needs to update each node in the network, which is determined by the characteristics of P2P.This paper focused on improving the query efficiency of OLAP which is rare in current research. The mainly researches are as follows:(1)Discussing the classification of P2P network model and the characteristics of OLAP ,?then constructing a OLAP network model which based on multi-dimension data frequency division.There are a lot of clusters in this OLAP network model,in order to management resource we established Cluster Head Node and Deputy Node in a cluster.This model can effectively avoid node isolated for single point failure and enhance the robustness of this network.(2)Analyzing the latest research of Data Cube storage on P2P,combining with existing simple semantic dimension storage strategy, a storage solution based on the real-time Data Cube semantic dynamic compression has been proposed in this paper.According to construct a update node Flag to judge whether Data has been updated,then ensuring the Data is real.(3)The OLAP network model based on the multi-dimension data frequency division can be used to guarantee the stability of network,the storage scheme based on real-time semantic dimension hierarchies has realized the Data Cube sharing among different nodes on P2P environment.Therefore, a OLAP inquires algorithm based on real-time semantic was given. Experimental results show that this RTOS algorithm can improve the efficiency of OLAP decision analysis and balance the OLAP server load.