Perfomance of XSLT processors on large data sets

Zavoral, Filip; Dvořáková, Jana

doi:10.1109/icadiwt.2009.5273945

Cited by 5 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To analyze the large amounts of XML data in science workflow, an approach for exploiting data parallelism in XML processing pipelines through novel compilation strategies within the MapReduce framework was presented in paper [11]. However, to the best of our knowledge, an efficient and scalable framework, which combines the MapReduce and XSLT technologies to implement large-scale XML data transformation, is still in blank [15].…”

Section: Introductionmentioning

confidence: 99%

A Scalable XSLT Processing Framework based on MapReduce

Li¹,

Luo²,

Yang³

et al. 2013

JCP

View full text Add to dashboard Cite

The eXtensible Stylesheet Language Transformation (XSLT) is a de-facto standard for XML data transforming and extracting. Efficient processing of large amounts of XML data brings challenges to conventional XSLT processors, which are designed to run in a single machine context. To solve these data-intensive problems, MapReduce paradigm in the cloud computing domain has received a comprehensive attention in both academia and IT industry recently. In this paper, a novel MapReduce-based XSLT distributed processing framework named CloudXSLT is proposed to implement efficient and scalable XML data transforming. First, the architecture of CloudXSLT framework is outlined. Subsequently, several XML data and XSLT rule representation models which are suitable for MapReduce paradigm are defined, and several MapReduce-based XSLT distributed processing algorithms are proposed. Finally, an experiment on a simulation environment with real XML datasets shows our framework is more efficient and scalable than conventional XSLT processors when processing large size of XML data.

show abstract

Section: Introductionmentioning

confidence: 99%

A Scalable XSLT Processing Framework based on MapReduce

Li¹,

Luo²,

Yang³

et al. 2013

JCP

View full text Add to dashboard Cite

show abstract

“…First, in this approach an XSLT transformation processing is not load-balanced. Second, an XSLT transformation becomes inefficient if the size of the target XML document is large [20]. This implies that the centralized approach is inefficient even if the size of each XML fragment is small, whenever the merged document is large.…”

Section: Introductionmentioning

confidence: 99%

An XSLT Transformation Method for Distributed XML

Hiroki

Suzuki

2015

Journal of Information Processing

View full text Add to dashboard Cite

Abstract:Recently, the sizes of XML documents have rapidly been increasing. Distributed XML is a novel form of XML document, in which an XML document is partitioned into fragments and managed separately in plural sites. Distributed XML documents can often be managed more easily than a single large document, according to geographical and/or administrative factors. In this paper, we consider performing XSLT transformation efficiently for distributed XML. To obtain an efficient method for this transformation, we devise an efficient evaluation method for XSLT pattern, which is a subset of XPath, and integrate it into top-down XSLT transformation. To evaluate an XSLT pattern for node v in a distributed environment, the site having v may need to access other sites many times. We propose two novel techniques to reduce such accesses; (1) precomputation of ancestors and (2) cache for predicate evaluation. We implemented our method in Ruby and made evaluation experiments. This result suggests that our method is more efficient than a centralized approach.

show abstract

A Simple XSLT Processor for Distributed XML

Hiroki

Suzuki

2013

Web Technologies and Applications

View full text Add to dashboard Cite

Perfomance of XSLT processors on large data sets

Cited by 5 publications

References 10 publications

A Scalable XSLT Processing Framework based on MapReduce

A Scalable XSLT Processing Framework based on MapReduce

An XSLT Transformation Method for Distributed XML

A Simple XSLT Processor for Distributed XML

Contact Info

Product

Resources

About