Adaptive Stream Query Processing Approach for Linked Stream Data

摘要

Over the last few years, numerous efforts [1-4, 7] have been proposed based on SPARQL-like query languages on harvesting Linked Stream Data (LSD) processing in RDF and related formats. While each existing processor has advantages, neither of them wins in diverse settings. They differ on a wide range of aspects including the execution method, operational semantics, streaming operators and more. Considering state-of-the-art solutions, recent evaluations by [5, 6, 8] show that C-SPARQL [2] suffers from duplicate results for simple queries and misses some certain output in complex queries but provides more correct results than others. On the otherhand CQELS [7] performs better than others in terms of throughput and functionalities [6]. This diversity in output result is true for other processors including EP-SPARQL [1] and StreamingSPARQL [3].