Query execution algorithm in web environment with limited availability of statistics

Traditional static cost-based query optimization approach uses data statistics to evaluate costs of potential query execution plans for a given query. Unfortunately, this approach cannot be directly applied to Web environment due to limited availability of statistics and unpredictable delays in access to data sources. To cope with lack or limited availability of statistics we propose a novel competitive query execution strategy. The basic idea is to initiate simultaneously several equivalent query execution plans and measure dynamically their progress. Processing of the most promising plan is continued, whereas processing of remaining plans is stopped. We also present in the paper results of performance evaluation of the proposed strategy.