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In this article, the authors present an efficient SPARQL processing system that uses MapReduce and HBase. The system runs a job optimized query plan using their proposed abstract RDF data to decrease the number of jobs and also decrease the amount of input data. The authors also present an efficient algorithm of using Map-side joins while also using the abstract RDF data to filter out unneeded RDF data. Experimental results show that the proposed approach demonstrates better performance when processing queries with a large amount of input data than those found in previous works.<\/jats:p>","DOI":"10.4018\/jdm.2019010102","type":"journal-article","created":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T06:50:47Z","timestamp":1559026247000},"page":"22-40","source":"Crossref","is-referenced-by-count":6,"title":["Map-Side Join Processing of SPARQL Queries Based on Abstract RDF Data Filtering"],"prefix":"10.4018","volume":"30","author":[{"given":"Minjae","family":"Song","sequence":"first","affiliation":[{"name":"Yonsei University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyunsuk","family":"Oh","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seungmin","family":"Seo","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyong-Ho","family":"Lee","sequence":"additional","affiliation":[{"name":"Yonsei University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"JDM.2019010102-0","doi-asserted-by":"crossref","unstructured":"Abadi, D. 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