Continuous queries are used to monitor changes to time varying data and to provide results useful for online decision making. Typically a user desires to obtain the value of some aggregation function over distributed data items, for example, to know (a) the average of temperatures sensed by a set of sensors (b) the value of index of mid-cap stocks. In these queries a client specifies a coherency requirement as part of the query. In this paper we present a low-cost, scalable technique to answer continuous aggregation queries using a content distribution network of dynamic data items. In such a network of data aggregators, each data aggregator serves a set of data items at specific coherencies. Just as various fragments of a dynamic web-page are served by one or more nodes of a content distribution network, our technique involves decomposing a client query into sub-queries and executing sub-queries on judiciously chosen data aggregators with their individual sub-query incoherency bounds...