상세정보
학술대회
Parallel Prime Number Labeling of Large XML Data Using MapReduce
- 저자
- 안진현, 임동혁, 이태휘, 김홍기
- 발행일
- 201609
- 출처
- International Conference on IT Convergence and Security (ICITCS) 2016, pp.1-2
- 협약과제
- 16ZS1400, 듀얼모드 배치.쿼리 분석을 제공하는 빅데이터 플랫폼 핵심기술 개발, 원종호
- 초록
- Massive XML (Extensible Markup Language) data are available on the web. XML data labeling schemes have been suggested for structural query processing of massive XML data. Notable schemes include interval- based, prefix-based, and prime number-based labeling schemes. Of these, the prime number labeling scheme has the advantage of query processing by simple arithmetic operations. However, a parallel algorithm for this scheme does not exist. The requirement that all parents' labels have to be multiplied to obtain the label of a node makes it difficult to label XML data in a parallel fashion. To address the issue, in this paper, we propose a cluster-based technique wherein all parent nodes for a node are aggregated to compute its label by two-step MapReduce jobs. Our experiments on real-world XML datasets showed the advantages over a single machine-based system.
- KSP 제안 키워드
- Arithmetic operations, Data Labeling, Extensible markup language(XML), Labeling scheme, Parallel Algorithm, Prime number labeling, Query Processing, Real-world, Two-Step, XML Data, based system