Selection of Views for Materialization Using Size and Query Frequency

View selection is concerned with selecting a set of views that improves the query response time while fitting within the available space for materialization. The most fundamental view selection algorithm HRUA uses the view size, and ignores the query answering ability of the view, while selecting views for materialization. As a consequence, the view selected may not account for large numbers of queries. This problem is addressed by the proposed algorithm, which aims to select views by considering query frequency along with the size of the view. The proposed algorithm, in each iteration, computes the profit of each view, using the query frequency and size of views, and then selects from amongst them, the most profitable view for materialization. The views so selected would be able to answer a greater number of queries resulting in improvement in the average query response time. Further, experimental based comparison of the proposed algorithm with HRUA showed that the proposed algorithm was able to select views capable of answering significantly greater number of queries at the cost of a slight increase in the total cost of evaluating all the views.