Computation over APT Compressed Data

The Arithmetic Progressions Tree (APT) is an encoding of a monotonic sequence ℒ in [1..n]. Previous work on APT coding focused on its theoretical and experimental compression guarantees. This paper is the first to consider computations over APT compressed data. In particular: (1) We show how to perform a search for any sub-sequence of the monotone sequence ℒ in time proportional to the query sub-sequence length multiplied by the size of the APT compressed representation of ℒ. (2) We show how, given the APT compressed representation of the monotone sequence ℒ, we can find a minimum run-length of ℒ in constant time, a maximum run-length of ℒ in O(log n) time, and all runs of ℒ in constant time plus the output size. (3) Most importantly, we show how, given the APT compressed representation of the monotone sequence ℒ, we can answer whether a periodic pattern P appears in ℒ in O(log n) time and report its locations in the output size time. (4) In addition, we improve the APT construction algorithm time and space complexity.