Heavy hitters and frequency measurements are fundamental in many networking applications such as load balancing, QoS, and network security. This paper considers a generalized sliding window model that supports frequency and heavy hitters queries over an interval given at \emph{query time}. This enables drill-down queries, in which the behavior of the network can be examined in finer and finer granularities. For this model, we asymptotically improve the space bounds of existing work, reduce the update and query time to a constant, and provide deterministic solutions. When evaluated over real Internet packet traces, our fastest algorithm processes packets $90$--$250$ times faster, serves queries at least $730$ times quicker and consumes at least $40\%$ less space than the known method.