Abstract
We design and develop an SQL-based approach for querying and mining large graphs within a relational database management system (RDBMS). We propose a simple lightweight framework to integrate graph applications with the RDBMS through a tightly-coupled network layer, thereby leveraging efficient features of modern databases. Comparisons with straight-up main memory implementations of two kernels - breadth-first search and quasi clique detection - reveal that SQL implementations offer an attractive option in terms of productivity and performance.
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Srihari, S., Chandrashekar, S., Parthasarathy, S. (2010). A Framework for SQL-Based Mining of Large Graphs on Relational Databases. In: Zaki, M.J., Yu, J.X., Ravindran, B., Pudi, V. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2010. Lecture Notes in Computer Science(), vol 6119. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13672-6_16
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DOI: https://doi.org/10.1007/978-3-642-13672-6_16
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