The Web has evolved from a system of internet servers supporting formatted documents into a web of linked data. In the last years, the Web of Data is constantly growing. Consequently, it has developed a large collection of interlinked data sets from multiple domains. To exploit the diversity of all available data, federated queries are needed. However, many problems such as processing power, query response time, high workload or outdated information are hindering the query processing. In this paper, I am aiming to explain various optimization techniques which have the potential to lead a significant improvement on the final query runtime. I will start by briefly introducing recent approaches of federation and show why SPARQL federation endpoints are mostly in my focus. Specifically, I will compare state-of-the-art SPARQL query federation engines and analyze respective optimization approaches. The main federation engines I will analyze in terms of query optimization are FedX, DARQ and SPLENDID. As the result I provide concrete examples and conclude which of the engines has the best performance based on the query execution time as key criterion.
Basic Math Practice worksheet
By Matthew Ferguson
Randomly Generates a PDF with
56 addition problems for a desired
Difficulty level (currently single digits).
Useful as a worksheet for early elementary school students.
The aim of the experiment is to study elliptically polarized light using a Fresnel rhomb and to determine the ratio of semi major axis to the semi minor axis of the various elliptically polarised light forms for different angles of plane polarised incidence at the rhomb
Bioinformatics provides a forum for the exchange of information in the fields of computational molecular biology and post-genome bioinformatics, with emphasis on the documentation of new algorithms and databases that allows the progress of bioinformatics and biomedical research in a significant manner.
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