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Approximate Query Processing over Static Sets and Sliding Windows

Authors Ran Ben Basat, Seungbum Jo , Srinivasa Rao Satti , Shubham Ugare

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Author Details

Ran Ben Basat
  • Harvard University, Cambridge, USA
Seungbum Jo
  • University of Siegen, Germany
Srinivasa Rao Satti
  • Seoul National University, South Korea
Shubham Ugare
  • IIT Guwahati, Guwahati, India

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Ran Ben Basat, Seungbum Jo, Srinivasa Rao Satti, and Shubham Ugare. Approximate Query Processing over Static Sets and Sliding Windows. In 29th International Symposium on Algorithms and Computation (ISAAC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 123, pp. 54:1-54:12, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


Indexing of static and dynamic sets is fundamental to a large set of applications such as information retrieval and caching. Denoting the characteristic vector of the set by B, we consider the problem of encoding sets and multisets to support approximate versions of the operations rank(i) (i.e., computing sum_{j <= i} B[j]) and select(i) (i.e., finding min{p|rank(p) >= i}) queries. We study multiple types of approximations (allowing an error in the query or the result) and present lower bounds and succinct data structures for several variants of the problem. We also extend our model to sliding windows, in which we process a stream of elements and compute suffix sums. This is a generalization of the window summation problem that allows the user to specify the window size at query time. Here, we provide an algorithm that supports updates and queries in constant time while requiring just (1+o(1)) factor more space than the fixed-window summation algorithms.

Subject Classification

ACM Subject Classification
  • Theory of computation → Data compression
  • Streaming
  • Algorithms
  • Sliding window
  • Lower bounds


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