Content-Based Filtering for Efficient Online Materialized View Maintenance

Real-time materialized view maintenance has become increasingly popular, especially in real-time data warehousing and data streaming environments. Upon updates to base relations, maintaining the corresponding materialized views can bring a heavy burden to the RDBMS. A traditional method to mitigate this problem is to use the where clause condition in the materialized view definition to detect whether an update to a base relation is relevant and can affect the materialized view. However, this detection method does not consider the content in the base relations and hence misses a large number of filtering opportunities. In this paper, we propose a content-based method for detecting irrelevant updates to base relations of a materialized view. At the cost of using more space, this method increases the probability of catching irrelevant updates by judiciously designing filtering relations to capture the content in the base relations. Based on the content-based method, a prototype real-time data warehouse has been implemented on top of IBM’s Stream Processing Core middleware using IBM DB2. Using an analytical model and our prototype, we show that the content-based method can catch most (or all) irrelevant updates to base relations that are missed by the traditional method. Thus, when the fraction of irrelevant updates is non-negligible, the load on the RDBMS due to materialized view maintenance can be significantly reduced.