Efficient XML query using Relational Data Model

Sun, Fenggang; Xiong, Ping; Sun, Tao

doi:10.1109/snpd.2007.540

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…However, we explain in detail how to implement our approach using real data sets from mobile networks for Apache Hive and Apache Spark. Hong & Song (2007) propose a method for permanently storing XML files into a relational database MS SQL Server. For tests, they employ a web-based virtual collaboration tool called VCEI.…”

Section: Related Workmentioning

confidence: 99%

“… Hong & Song (2007) propose a method for permanently storing XML files into a relational database MS SQL Server. For tests, they employ a web-based virtual collaboration tool called VCEI.…”

Section: Related Workmentioning

confidence: 99%

“…The eXtensible Markup Language (XML) is now widely used on the Internet for different purposes. There are numerous XML-based applications that utilize tag-based and nested data structures ( Chituc, 2017 ; Debreceny & Gray, 2001 ; Hong & Song, 2007 ) due to greater flexibility in the representation of different types of data: these can be customized by the user. However, the main constraint is that XML representation is inefficient in terms of processing and with respect to query times; for this reason, agile and intelligent search and query proposals are required ( Hsu, Liao & Shih, 2012 ).…”

Section: Introductionmentioning

confidence: 99%

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Efficient processing of complex XSD using Hive and Spark

Martinez-Mosquera

Navarrete

Luján‐Mora

2021

PeerJ Computer Science

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The eXtensible Markup Language (XML) files are widely used by the industry due to their flexibility in representing numerous kinds of data. Multiple applications such as financial records, social networks, and mobile networks use complex XML schemas with nested types, contents, and/or extension bases on existing complex elements or large real-world files. A great number of these files are generated each day and this has influenced the development of Big Data tools for their parsing and reporting, such as Apache Hive and Apache Spark. For these reasons, multiple studies have proposed new techniques and evaluated the processing of XML files with Big Data systems. However, a more usual approach in such works involves the simplest XML schemas, even though, real data sets are composed of complex schemas. Therefore, to shed light on complex XML schema processing for real-life applications with Big Data tools, we present an approach that combines three techniques. This comprises three main methods for parsing XML files: cataloging, deserialization, and positional explode. For cataloging, the elements of the XML schema are mapped into root, arrays, structures, values, and attributes. Based on these elements, the deserialization and positional explode are straightforwardly implemented. To demonstrate the validity of our proposal, we develop a case study by implementing a test environment to illustrate the methods using real data sets provided from performance management of two mobile network vendors. Our main results state the validity of the proposed method for different versions of Apache Hive and Apache Spark, obtain the query execution times for Apache Hive internal and external tables and Apache Spark data frames, and compare the query performance in Apache Hive with that of Apache Spark. Another contribution made is a case study in which a novel solution is proposed for data analysis in the performance management systems of mobile networks.

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Section: Related Workmentioning

confidence: 99%

“… Hong & Song (2007) propose a method for permanently storing XML files into a relational database MS SQL Server. For tests, they employ a web-based virtual collaboration tool called VCEI.…”

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Efficient processing of complex XSD using Hive and Spark

Martinez-Mosquera

Navarrete

Luján‐Mora

2021

PeerJ Computer Science

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“…In addition, Hong et al [20] used a virtual collaboration system for converting the data between XML and relational databases. Some other researchers such as Zhou [21] parsed XML file into XML DOM tree by extracting DTD of the XML file and mapped XML document tree into a relational database.…”

Section: Related Workmentioning

confidence: 99%

RXML : Path-Based and XML DOM Approaches for Integrating Between Relational and XML Databases

Hamad¹

2017

IJDMS

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“…Surajit Chaudhuri [5] proposed a method to store XML document in relational database by use of logical and physical design and it can provide a fast query. Sungchul Hong [6] realized bidirectional transmission between XML document and relational database. Yoshikawa [7] proposed a structure named XRel to store XML document in relational database and used SQL language to realize XML query.…”

Section: Related Workmentioning

confidence: 99%

A Storage Method for XML Document Based on Relational Database

Liu

Guan

2008

2008 International Symposium on Computer Science and Computational Technology

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At present, storing XML document in a relational database is a hot topic because relational databases are mature and scale well. In this paper, a novel relational database storage structure that can store XML document is proposed. An algorithm that translates XML document to relational database is given according to the proposed storing structure and algorithms that translate XPath Query to SQL Query which runs on SQL Server 2000 is also given. The steps and algorithms are given in detail to describe how to use the storing structure to storage and query XML document in relational database. Then, an example is presented to show how to use this method and approve the correct of the proposed storing structure and given algorithms. Compared with other methods, the method in this paper has advantage in compact translated SQL, lesser relational database space and quicker query speed.

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Efficient XML query using Relational Data Model

Cited by 5 publications

References 11 publications

Efficient processing of complex XSD using Hive and Spark

Efficient processing of complex XSD using Hive and Spark

RXML : Path-Based and XML DOM Approaches for Integrating Between Relational and XML Databases

A Storage Method for XML Document Based on Relational Database

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