Highly Parallel SPARQL Engine for RDF  

作　　者：Fan Feng Weikang Zhou Ding Zhang Jinhui Pang 

机构地区：[1]Tianjin University,Tianjin,China [2]Beijing Institute of Technology,Beijing,China

出　　处：《国际计算机前沿大会会议论文集》2020年第1期61-71,共11页International Conference of Pioneering Computer Scientists, Engineers and Educators（ICPCSEE）

基　　金：by Big Data Research Foundation of PICC.

摘　　要：In this paper,a highly parallel batch processing engine is designed for SPARQL queries.Machine learning algorithms were applied to make time predictions of queries and reasonably group them,and further make reasonable estimates of the memory footprint of the queries to arrange the order of each group of queries.Finally,the query is processed in parallel by introducing pthreads.Based on the above three points,a spall time prediction algorithm was proposed,including data processing,to better deal with batch SPARQL queries,and the introduction of pthread can make our query processing faster.Since data processing was added to query time prediction,the method can be implemented in any set of data-queries.Experiments show that the engine can optimize time and maximize the use of memory when processing batch SPARQL queries.

关 键 词：SPARQL Pthread MULTITHREADING Performance prediction 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]