A two-tier index architecture for fast processing large RDF data over distributed memory

Cheng, L.; Kotoulas, S.; Ward, T.; Theodoropoulos, G.

Abstract

We propose an efficient method for fast processing large RDF data over distributed memory. Our approach adopts a two-tier index architecture on each computation node: (1) a light-weight primary index, to keep loading times low, and (2) a dynamic, multi-level secondary index, calculated as a by-product of query execution, to decrease or remove inter-machine data movement for subsequent queries that contain the same graph patterns. Experimental results on a commodity cluster show that we can load large RDF data very quickly in memory while remaining within an interactive range for query processing with the secondary index.

Citation

Cheng, L., Kotoulas, S., Ward, T., & Theodoropoulos, G. (2014, September). A two-tier index architecture for fast processing large RDF data over distributed memory. Presented at 25th ACM conference on Hypertext and social media - HT '14, Santiago, Chile

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 25th ACM conference on Hypertext and social media - HT '14
• Start Date: Sep 1, 2014
• End Date: Sep 4, 2014
• Online Publication Date: Sep 1, 2014
• Publication Date: Sep 1, 2014
• Deposit Date: Apr 21, 2016
• Publicly Available Date: Apr 28, 2016
• Pages: 300-302
• Book Title: HT'14 : proceedings of the 25th ACM Conference on Hypertext and Social Media : September 1-4, 2014, Santiago, Chile.
• DOI: https://doi.org/10.1145/2631775.2631789
• Public URL: https://durham-repository.worktribe.com/output/1151771