Earticle

초록

영어

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.

목차

Abstract
 1. Introduction
 2. Preliminaries and Problem Analysis
  2.1. Data Model
  2.2. XPath Query
  2.3. Problem Analysis
 3. Qxslist Algorithm Design and Implementation
  3.1. Framework of Algorithm
  3.2. Xpath Fragment XP{/, //, []} Query Processing
  3.3. XPath Fragment XP{/, //, *} Query Processing
  3.4. Optimal Method
 4. Experimental Results and Analysis
  4.1. Experimental Setup
  4.2. Running Time Performance
  4.2. Memory Space Performance
 5. Conclusion
 References

키워드

저자

• He Zhixue [ Department of Computer Science, Beijing University of Technology, Beijing, China / Computer and Remote Sensing Information Technology Institute, North China Institute of Aerospace Engineering, Langfang, China ]
• Liao Husheng [ Department of Computer Science, Beijing University of Technology, Beijing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605