MEASURING THE ENERGY EFFICIENCY OF RDF QUERY PROCESSING
Keywords:
database, energy, RDF, RDF4JAbstract
The cost of electric power consumed by a server computer is a significant component of its total cost of ownership. Since database servers are essential in the era of Big Data, we studied the performance and energy consumption of a small server. To achieve this, we stored a large set of RDF (Resource Description Framework) data in a database (RDF4J) running on consumer-grade hardware. Using realistic SPARQL language queries from Wiki data and a low-cost power/energy meter, we measured the energy consumption of RDF query processing. Our database management system responded to queries over a network connection, demonstrating that the network processing overhead in query processing was quite low (about 2 to 4%). We found that the most energy-efficient processing (queries per Watt) could be achieved with a slightly larger degree of parallelism than the best throughput (queries per hour). Moreover, we discovered that using a stripped-down version of the operating system on which the database ran did not affect the energy consumption of the query processing.
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