Reduction of Materialized View Staleness Using Online Updates

Abstract

Updating the materialized views stored in data warehouses usually implies making the warehouse unavailable to users. We propose MAUVE , a new algorithm for online incremental view updates that uses timestamps and allows consistent read-only access to the warehouse while it being updated. The algorithm propagates the updates to the views more often than the typical once a day in order to reduce view staleness. We have implemented MAUVE on top of the Informix Universal Server and used a synthetic workload generator to experiment with various update workloads and different view update frequencies. Our results show that, all kinds of update streams benefit from more frequent view updates, instead of just once a day. However, there is a clear maximum for the view update frequency, for which view staleness is minimal. 1 Introduction Data warehouses contain data replicated from several external sources, collected to answer decision support queries. The replicated data is often copied in re..