Abstract
In the rank join problem, we are given a set of relations and a scoring function, and the goal is to return the K join results with the highest scores. It is often the case in practice that the inputs may be accessed in ranked order and the scoring function is monotonic. These conditions allow for efficient algorithms that solve the rank join problem without reading all of the input. In this chapter, we review recent efforts in the development and analysis of such rank join algorithms. First, we present some theoretical results that state the inherent complexity of the rank join problem and essentially reveal that any rank join algorithm has to trade off between I/O efficiency and computational efficiency. We then review a specific rank join algorithm that adjusts this trade-off at runtime, depending on the data and the scoring function, in order to strike a balance between I/O overhead and computation.
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© 2011 Springer-Verlag Berlin Heidelberg
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Polyzotis, N. (2011). The Rank Join Problem. In: Ceri, S., Brambilla, M. (eds) Search Computing. Lecture Notes in Computer Science, vol 6585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19668-3_10
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DOI: https://doi.org/10.1007/978-3-642-19668-3_10
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