Study On Historical Data Archiving And Reconstructing Strategy In Data Warehouse

hi a Data Warehouse system, with the time passing and subject changing, large numbers of detail data became the overdue data, but these data are not useless. For the quality of applications on OLAP and DM, overdue and substantive detail data must be archived to be historical data, stored into the storage equipment which is off line or at lower level. Archiving data have some characteristic such as low access frequency, even zero access frequency during a long time, the quantity is very large and the storage time is very long, even some data have to be kept about ten years, data must be available and valid.XML (eXtend Markup Language) serves as an significant foundation of the research in this thesis. This thesis applies the technology of XML into the archiving of historical data in Data Warehouse, changing the storage mode of Relational Database for archiving of historical data, in the mean time, to ensure that the data are accessible, available and valid, and to avoid the inefficacy of data caused by differences of systems and platforms. Furthermore, we prove by experiments that the method can save storage space for archiving historical data.This thesis discusses particularly the method of transforming between relational schema and XML schema, realized the schema mapping and data transferring. The mapping ensured the consistency of metadata, the transferring ensure the accessibility, availability and validity.Furthermore, this thesis researches the code problem of historical data archiving and reconstructing. Considering the data structure differences between current system and archiving system, this thesis analyzes the data differences, points out it is pivotal for data access to solve code differences, and proposes concrete method for it. Mainly applies code recovery technology into the transferring from database to XML document, in order to load practical meaning into XML document for the later access. Through technology of code pick-up, code resetting and code expansion in the reconstructing XML document into analytical data in Data Warehouses system, ensures the consistency between reconstructing analytical and current analytical data.