This paper investigates the Web data aggregation issues in multidimensional on-line analytical processing (MOLAP) and presents a rule-driven aggregation approach. The core of the approach is defining aggregate rules. To define the rules for reading warehouse data and computing aggregates, a rule definition language - array aggregation language (AAL) is developed. This language treats an array as a function from indexes to values and provides syntax and semantics based on monads. External functions can be called in aggregation rules to specify array reading, writing, and aggregating. Based on the features of AAL, array operations are unified as function operations, which can be easily expressed and automatically evaluated. To implement the aggregation approach, a processor for computing aggregates over the base cube and for materializing them in the data warehouse is built, and the component structure and working principle of the aggregation processor are introduced.