Abstract
Compact representation of Web and social graphs can be made efficiently with the K 2-tree as it achieves compression ratios about 5 bits per link for web graphs and about 20 bits per link for social graphs. The K 2-tree also enables fast processing of relevant queries such as direct and reverse neighbours in the compressed graph. These two properties make the K 2-tree suitable for inclusion in Web search engines where it is necessary to maintain very large graphs and to process on-line queries on them. Typically these search engines are deployed on dedicated clusters of distributed memory processors wherein the data set is partitioned and replicated to enable low query response time and high query throughput. In this context a practical strategy is simply to distribute the data on the processors and build local data structures for efficient retrieval in each processor. However, the way the data set is distributed on the processors can have a significant impact in performance. In this paper, we evaluate a number of data distribution strategies which are suitable for the K 2-tree and identify the alternative with the best general performance. In our study we consider different data sets and focus on metrics such as overall compression ratio and parallel response time for retrieving direct and reverse neighbours.
SAG and NB were founded by MICIN (PGE and FEDER) grants TIN2009-14560-C03-02, TIN2010-21246-C02-01, and CDTI CEN-20091048 and Xunta de Galicia (co-funded with FEDER) ref. 2010/17. MM was partially funded by research grant FONDEF IDeA CA12I10314.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02432-5_33
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Álvarez-García, S., Brisaboa, N.R., Gómez-Pantoja, C., Marin, M. (2013). Distributed Query Processing on Compressed Graphs Using K2-Trees. In: Kurland, O., Lewenstein, M., Porat, E. (eds) String Processing and Information Retrieval. SPIRE 2013. Lecture Notes in Computer Science, vol 8214. Springer, Cham. https://doi.org/10.1007/978-3-319-02432-5_32
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DOI: https://doi.org/10.1007/978-3-319-02432-5_32
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