Efficient temporal counting with bounded error

Efficient temporal counting with bounded error This paper studies aggregate search in transaction time databases. Specifically, each object in such a database can be modeled as a horizontal segment, whose y -projection is its search key, and its x -projection represents the period when the key was valid in history. Given a query timestamp q t and a key range $$\vec{q_k}$$ , a count-query retrieves the number of objects that are alive at q t , and their keys fall in $$\vec{q_k}$$ . We provide a method that accurately answers such queries, with error less than $$\frac{1}{\varepsilon} + \varepsilon \cdot N_{\rm alive}(q_t)$$ , where N alive ( q t ) is the number of objects alive at time q t , and ɛ is any constant in (0, 1). Denoting the disk page size as B , and n = N / B , our technique requires O ( n ) space, processes any query in O (log B n ) time, and supports each update in O (log B n ) amortized I/Os. As demonstrated by extensive experiments, the proposed solutions guarantee query results with extremely high precision (median relative error below 5%), while consuming only a fraction of the space occupied by the existing approaches that promise precise results. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Efficient temporal counting with bounded error

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Copyright © 2008 by Springer-Verlag
Computer Science; Database Management
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