Improved Centralized XML Query Processing Using Distributed Query Workload
Autor: | Su-Cheng Haw, Lay-Ki Soon, Samini Subramaniam |
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Rok vydání: | 2021 |
Předmět: |
XML labeling
General Computer Science Computer science computer.internet_protocol Distributed computing 02 engineering and technology computer.software_genre Market fragmentation 020204 information systems Server 0202 electrical engineering electronic engineering information engineering General Materials Science centralized query processing Pruning (decision trees) XML indexing Search engine indexing General Engineering Process (computing) InformationSystems_DATABASEMANAGEMENT Workload Distributed query processing XML database 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering lcsh:TK1-9971 computer XML query processing XML |
Zdroj: | IEEE Access, Vol 9, Pp 29127-29142 (2021) |
ISSN: | 2169-3536 |
Popis: | eXtensible Markup Language (XML) is used widely to transfer data among a wide variety of systems. Due to an increase in query workloads and management of larger datasets, centralized processing is no longer feasible for XML query processing. To address this issue, we propose a technique that improves XML query processing through query workload distribution. An effective distributed XML query processing can be affected by several criteria such as indexing, fragmentation, distribution strategy, and well as the query handling in the distributed servers. However, we believe that an efficient labeling mechanism and an inexpensive centralized query processors or a pruning method at dedicated servers contribute greatly to the overall performance of a distributed query processor. In this paper, we present an effective centralized pruning technique that is adopted into our proposed distributed XML query processing technique to process XML queries robustly. Experimental evaluations showed that the proposed distributed query processor superseded the performance of centralized query processor. |
Databáze: | OpenAIRE |
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