A materialized-view based technique to optimize progressive queries via dependency analysis
Proceedings of the 2011 Conference of the Center for Advanced Studies on Collaborative Research
Dynamic materialized view selection algorithm: a clustering approach
ICDEM'10 Proceedings of the Second international conference on Data Engineering and Management
Dynamic View Management System for Query Prediction to View Materialization
International Journal of Data Warehousing and Mining
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With the base of proposing materialized view similarity function, the paper proposes clustering-based dynamic materialized view selection algorithm. It firstly clusters materialized views, and then dynamically adjusts materialized view set. So, it eliminates the "jitter", which dynamic materialized view selection algorithm generally has. The experimental results show that the algorithm not only improves the overall query response performance, but also reduces the computational cost which will bespent during updating materialized view.