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Abstract : |
Data warehouses (DW) are built by gathering information from several information sources and integrating it into one repository customized to users ' needs. Recently proposed view maintenance algorithms tackle the problem of (concurrent) data updates happening at di erent autonomous ISs, whereas the EVE system addresses the maintenance of a data warehouse after schema changes of ISs. The concurrency of schema changes and data updates performed by di erent ISs still remains an unexplored problem however. This paper now provides a solution to this problem that guarantees the concurrent view de nition evolution and view extent maintenance of a DW de ned over distributed ISs. To solve that problem, we introduce a framework called SDCC (Schema change and Data update Concurrency Control) system. SDCC integrates existing algorithms designed to address view maintenance subproblems, such asview extent maintenance after IS data updates, view de nition evolution after IS schema changes, and view extent adaptation after view de nition changes, into one system by providing protocols that enable them to correctly co-exist and collaborate. SDCC tracks any potential faulty updates of the DW caused by con icting concurrent ISchanges using a global message labeling scheme. An algorithm that is able to compensate for such con icting updates by a local correction strategy, called Local Compensation (LC), is incorporated into SDCC. The correctness of LC is proven. Lastly, the overhead of the SDCC solution beyond the costs of the known view maintenance algorithms it incorporates is shown to be neglectable., |
