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arXiv · 1808.02546

Parallel and Streaming Algorithms for K-Core Decomposition

Hossein Esfandiari·Silvio Lattanzi·Vahab Mirrokni
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Abstract

The $k$-core decomposition is a fundamental primitive in many machine learning and data mining applications. We present the first distributed and the first streaming algorithms to compute and maintain an approximate $k$-core decomposition with provable guarantees. Our algorithms achieve rigorous bounds on space complexity while bounding the number of passes or number of rounds of computation. We do so by presenting a new powerful sketching technique for $k$-core decomposition, and then by showing it can be computed efficiently in both streaming and MapReduce models. Finally, we confirm the effectiveness of our sketching technique empirically on a number of publicly available graphs.

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BibTeXRIS

Hossein Esfandiari, Silvio Lattanzi, Vahab Mirrokni. 2018-08-07. Parallel and Streaming Algorithms for K-Core Decomposition. https://arxiv.org/abs/1808.02546

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