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arXiv · 1507.00552

I/O-Efficient Similarity Join

Rasmus Pagh·Ninh Pham·Francesco Silvestri·Morten Stöckel
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Abstract

We present an I/O-efficient algorithm for computing similarity joins based on locality-sensitive hashing (LSH). In contrast to the filtering methods commonly suggested our method has provable sub-quadratic dependency on the data size. Further, in contrast to straightforward implementations of known LSH-based algorithms on external memory, our approach is able to take significant advantage of the available internal memory: Whereas the time complexity of classical algorithms includes a factor of $N^\rho$, where $\rho$ is a parameter of the LSH used, the I/O complexity of our algorithm merely includes a factor $(N/M)^\rho$, where $N$ is the data size and $M$ is the size of internal memory. Our algorithm is randomized and outputs the correct result with high probability. It is a simple, recursive, cache-oblivious procedure, and we believe that it will be useful also in other computational settings such as parallel computation.

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Rasmus Pagh, Ninh Pham, Francesco Silvestri, Morten Stöckel. 2015-07-02. I/O-Efficient Similarity Join. https://arxiv.org/abs/1507.00552

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