Psweep: Parallel View Maintenance under Concurrent Data Updates of Distributed Sources Psweep: Parallel View Maintenance under Concurrent Data Updates of Distributed Sources

Data warehouses (DW) are built by gathering information from several information sources (ISs) and integrating it into one repository customized to users' needs. Recent work has begun to address the problem of view maintenance of DWs under concurrent data updates of diierent ISs. SWEEP proposed by Agrawal et al. AAS97] is one of the more popular solutions; even though its performance is limited due to enforcing a sequential ordering on the handling of data updates from ISs by the view maintenance module. We have overcome this limitation by developing a parallel algorithm for view maintenance, called PSWEEP, that still incorporates all beneets of SWEEP while ooering substantially improved performance. In order to perform parallel view maintenance, we solve two issues: detecting maintenance-concurrent data updates in a parallel mode, and correcting the problem that the DW commit order may not correspond to the DW update processing order due to parallel maintenance handling. By decomposing SWEEP into an architecture of modular components, we then can insert a local timestamp assignment module for detecting maintenance-concurrent data updates without requiring any global clock synchronization. We introduce the negative counter concept as a simple yet suucient solution to solve the Variant-DW-Commit problem of variant orders of committing eeects of data updates to the DW. We have proven the correctness of PSWEEP to guarantee that our strategy indeed generates the correct nal DW state. An evaluation of both SWEEP and PSWEEP is given that shows that PSWEEP has the potential of multi-fold performance improvement over SWEEP depending on the number of threads supportable in the given DW system implementation.