Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICITCS.2016.7740360 | 2016 6th International Conference on IT Convergence and Security (ICITCS) |
Keywords | Field | DocType |
parallel prime number labeling,massive XML data,extensible markup language,MapReduce,XML data labeling scheme,structural query processing,interval-based labeling scheme,prefix-based labeling scheme,prime number-based labeling scheme,arithmetic operations,parallel algorithm,cluster-based technique,XML datasets | XML framework,XML Encryption,Efficient XML Interchange,Streaming XML,XML,Computer science,XML database,Theoretical computer science,Simple API for XML,XML Signature | Conference |
ISSN | ISBN | Citations |
2473-0122 | 978-1-5090-3766-7 | 0 |
PageRank | References | Authors |
0.34 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinhyun Ahn | 1 | 0 | 0.34 |
| Dong-Hyuk Im | 2 | 35 | 6.06 |
| Taewhi Lee | 3 | 17 | 3.08 |
| Hong-Gee Kim | 4 | 225 | 22.83 |