Paper Info
Title
Parallel XPath query based on cost optimization
Abstract
The performance of XPath query is the key factor to the capacity of XML processing. It is an important way to improve the performance of XPath by making full use of multi-threaded computing resources for parallel processing. However, in the process of XPath parallelization, load imbalance and thread inefficiency often lead to the decline of parallel performance. In this paper, we propose a cost optimization-based parallel XPath query method named coPXQ. This method improves the parallel processing effect of navigational XPath query through a series of optimization measures. The main measures include as follows: first, by optimizing the storage of XML node relation index, both storage and access efficiency of the index are improved. Secondly, load balancing is realized by a new cost estimation method according to the number of XML node relations to optimize parallel relation index creation and parallel primitive execution. Thirdly, the strategy of determining the number of worker threads based on parallel effectiveness estimation is utilized to ensure the effective use of threads in query. Compared with the existing typical methods, the experimental results show that our method can obtain better parallel performance.
Year
DOI
Venue
2022
10.1007/s11227-021-04074-y
The Journal of Supercomputing
Keywords
DocType
Volume
XPath query, Relation index, Cost estimation, Load balancing, Parallel effectiveness
Journal
78
Issue
ISSN
Citations 
4
0920-8542
0
PageRank 
References 
Authors
0.34
7
5
Name
Order
Citations
PageRank
Rongxin Chen100.34
Zhijin Wang200.34
Hang Su300.34
Shutong Xie400.34
Zongyue Wang521.40