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Abstract:
There has been a growing practical need for querying XML streaming data efficiently. Stream requires to be read sequentially and only once into memory, the query must be processed on the fly. QXSList technique is proposed for massive data processing, which takes the SAX events sequence as input, buffer the incoming elements for further processing, remove unnecessary elements from the buffer in time, and give the results on the fly. Data model and algorithm integrated framework are defined, the integrate methods of how to process predicate and wildcard are discussed respectively. Level value is used for determining the relationship of two elements and relational pointers are constructed for linking multi lists in this method. The experimental results show that our approach is effective and efficient on this problem, and outperforms the state-of-the-art algorithms and query engines especially for data size is very large. At the same time, memory usage is nearly constant. © 2016 SERSC.
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Source :
International Journal of Database Theory and Application
ISSN: 2005-4270
Year: 2016
Issue: 10
Volume: 9
Page: 99-110
Cited Count:
WoS CC Cited Count: 0
SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
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Chinese Cited Count:
30 Days PV: 11
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