XMLTable Index - An Efficient Way of Indexing and Querying XML Property Data

Liu, Zhen Hua; Krishnaprasad, Muralidhar; Chang, Hsu-Kuang; Arora, Vikas

doi:10.1109/icde.2007.368978

Cited by 13 publications

(16 citation statements)

References 9 publications

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“…Furthermore, well-structured data in the XML can be extracted into relational tables by building XML indexes on top of XML storage (Liu et al, 2007). This approach of persisting data as XML first and extracting well-structured data within XML as XMLTable based XMLIndex is the practical means to fulfill the spirit of "data first schema later".…”

Section: Etl Flexibilitymentioning

confidence: 99%

Towards Business Intelligence over Unified Structured and Unstructured Data Using XML

Liu¹,

Krishnamurthy²

2012

Business Intelligence - Solution for Business Development

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Section: Etl Flexibilitymentioning

confidence: 99%

Towards Business Intelligence over Unified Structured and Unstructured Data Using XML

Liu¹,

Krishnamurthy²

2012

Business Intelligence - Solution for Business Development

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“…The path-value-order keybased indexing is conceptually similar to path-based indexing technique described in [20] with ordered Dewey key [18]. The structured XMLTable based index is discussed in [12].…”

Section: Overview Of Xml Storage and Index In Oracle Xmldbmentioning

confidence: 99%

“…TPOX [60] models such XML use-cases. TPOX queries can be optimized fully by the Oracle XMLDB XQuery engine using a structured XMLIndex [12] (XTXI), path-valueorder based XMLIndex (PVXI) or binary XML stream evaluation (SEB). However, there are performance differences among them.…”

Section: Tpoxmentioning

confidence: 99%

Towards a physical XML independent XQuery/SQL/XML engine

et al. 2008

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There has been a lot of research and industrial effort on building XQuery engines with different kinds of XML storage and index models. However, most of these efforts focus on building either an efficient XQuery engine with one kind of XML storage, index, view model in mind or a general XQuery engine without any consideration of the underlying XML storage, index and view model. We need an underlying framework to build an XQuery engine that can work with and provide optimization for different XML storage, index and view models. Besides XQuery, RDBMSs also support SQL/XML, a standard language that integrates XML and relational processing. There are industrial efforts for building hybrid XQuery and SQL/XML engines that support both languages so that users can manage and query both relational and XML data on one platform. However, we need a theoretical framework to optimize both SQL/XML and XQuery languages in one RDBMS. In this paper, we show our industrial work of building a combined XQuery and SQL/XML engine that is able to work and provide optimization for different kinds of XML storage and index models in Oracle XMLDB. This work is based on XML extended relational algebra as the underlying tuple-based logical algebra and incorporates tree and automata based physical algebra into the logical tuple-based algebra so as to provide optimization for different physical XML formulations. This results in logical and physical rewrite techniques to optimize XQuery and SQL/XML over a variety of physical XML storage, index and view models, including schema aware object relational XML storage with relational indexes, binary XML storage with schema agnostic path-value-order key XMLIndex, SQL/XML view over relational data and relational view over XML. Furthermore, we show the approach of leveraging cost based XML physical rewrite strategy to evaluate different physical rewrite plans.

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“…The idea of table index [16] is used, to efficiently execute UNSED table queries. Table index can be presented in two physical forms in dealing with UNSED.…”

Section: Mapreduce Frameworkmentioning

confidence: 99%

Analysis and Evaluation of Techniques for Managing Unstructured and Semi-Structured Data in a MapReduce Platform

Darwish¹

2017

IJECS

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Abstract:The increasing demand for large-size data mining and data analysis applications drives both industry and academia to create new types of highly scalable data-intensive computing platforms. MapReduce is one of the most popular platforms in which the dataflow is in the form of a directed acyclic graph of operators. This paper presents a modified version of the MapReduce framework that is developed to manage unstructured and semi-structured data. Since, almost most kinds of database systems are designed to manage well-structured data requiring users to design a schema before storing and querying data. However, there are significant amount of unstructured data and semistructured data that cannot be effectively managed this way. In this paper, we develop the engineering principles and practices to manage unstructured and semi-structured data in a MapReduce platform. Having a single data platform for managing both well-structured data, unstructured and semi-structured data is beneficial to users; this approach reduces significantly integration, migration, development, maintenance, and operational issues. The Hadoop environment is used to write SQL/XML schemas first, then, all commands are translated to Hadoop as MapReduce jobs. The efficiency of using this method in MapReduce software is discussed and evaluated.

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XMLTable Index - An Efficient Way of Indexing and Querying XML Property Data

Cited by 13 publications

References 9 publications

Towards Business Intelligence over Unified Structured and Unstructured Data Using XML

Towards Business Intelligence over Unified Structured and Unstructured Data Using XML

Towards a physical XML independent XQuery/SQL/XML engine

Analysis and Evaluation of Techniques for Managing Unstructured and Semi-Structured Data in a MapReduce Platform

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