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Fig. 2 | Journal of Big Data

Fig. 2

From: GraphZIP: a clique-based sparse graph compression method

Fig. 2

Generalized CSR/CSC Data Structures (In-memory graph encoding). Cost of this particular in-memory graph encoding is 11 (or \(\mathcal {O}(|V|+|\mathcal {C}|)\)) for the ptr array (top) whereas the other is only 14, for a total of 27. This is compared to the popular CSC/CSR that requires arrays of size 9 and 34 for a total of 43. Thus, the simple encoding reduces the storage costs quite significantly (as well as IO costs, while improving algorithm performance as the computational costs of many graph primitives are also reduced using this encoding. Moreover, it is guaranteed to improve caching. Note that storing the graph to disk in a lossless fashion is even more efficient, since one can simply write “\(v_{1} \; v_{6} \; v_{10}\)” as the first line, followed by the edge \(v_5 \; v_6\)

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