| The frustration of broken links from the early Web has been replaced today by the frustration of web servers stalling or crashing under the heavy load of dynamically generated content. Even seemingly static web pages are usually generated dynamically in order to include personalization and advertising features. Such dynamic content has high resource demands and poses a scalability problem for both web and database servers.; In our work, we have used view materialization techniques to ameliorate this scalability problem. We introduced WebViews to identify frequently accessed web page fragments which are dynamically generated. With materialization, these WebViews are constantly refreshed in the background in anticipation of future requests.; WebView materialization drastically improves performance, but poses new challenges: (1) the selection of WebViews to materialize has to be performed in real-time, with limited knowledge of the access and update patterns, and must adapt rapidly to changing web workloads, (2) the freshness of the data served (Quality of Data) must be considered during the selection process, and, (3) scheduling the updates in the background concurrently with user requests has a significant impact on data freshness.; Our work has recognized the importance of both performance and data freshness in scalable, database-driven internet servers. Specifically, we have extended a real web server to support WebView materialization and shown its advantages. We have designed an adaptive algorithm for selecting which WebViews to materialize under changing workloads. Finally, we have designed an online algorithm to determine the order to refresh materialized WebViews so that the overall data freshness is maximized. |
