Exploiting native XML indexing techniques for XML retrieval in relational database systems

Weigel, Felix; Schulz, Klaus U.; Meuss, Holger

doi:10.1145/1097047.1097054

Cited by 12 publications

(5 citation statements)

References 26 publications

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“…The path index is a substantial summarization of the whole document. Use of a path index has been well studied, with several solutions available [8], [15], [23], and [26]; and we will reuse the concept here. The MTree path index is efficiently created during the SAX event stream, simultaneously with the creation of the MTree index.…”

Section: Path Indexmentioning

confidence: 99%

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Efficient XPath query processing

Pettovello

Fotouhi

2008

Proceedings of the 2008 Conference of the Center for Advanced Studies on Collaborative Research Meeting of Minds - CASCON '08

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We propose improved XPath query processing algorithms on XML documents by extending the MTree navigational XML database index. Our algorithms efficiently resolve element name specific XPath navigational queries, in many cases without a need for sorting or for qualified name filtering on intermediate sequences. The optimization methods are applicable for all axes but are presented for the four major XPath axes: descendant, ancestor, following and preceding. Experimental results are included that show substantial performance improvements over other well known methods.

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Section: Path Indexmentioning

confidence: 99%

“…Similarly, path indexes, also known as structure index or schema index, are discussed in [15], [23], and [26]. Closely related to our path index, linking a struc- ture index to an inverted list is discussed in [15] and called extent chaining, but in contrast we overlay several doubly linked paths through each node.…”

Section: Related Workmentioning

confidence: 99%

Efficient XPath query processing

Pettovello

Fotouhi

2008

Proceedings of the 2008 Conference of the Center for Advanced Studies on Collaborative Research Meeting of Minds - CASCON '08

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“…The main difficulty in implementing a DGAS-RUS is that the RUS interface handles XML documents while DGAS stores records in a relational database. XML documents can be stored in fundamentally different ways: in flat files (that are not considered here), native XML database systems or mapped to relational database tables (see for example [24,25,26,27]).…”

Section: Storage Models For Xml Documentsmentioning

confidence: 99%

“…The most important advantage of native XML databases is the native supporting of XML query languages such as XPath [21], XQuery [22] and XUpdate [23]. The major disadvantage is the generally lower performance compared to relational databases (see for example [26]). Research on more performant indexing techniques for XML documents in native XML databases is still going on.…”

Section: Native Xml Databasesmentioning

confidence: 99%

Tracing Resource Usage over Heterogeneous Grid Platforms: A Prototype RUS Interface for DGAS

Piro

Pace²,

Ghiselli³

et al. 2007

Third IEEE International Conference on E-Science and Grid Computing (E-Science 2007)

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Tracing resource usage by Grid users is of utmost importance especially in the context of large-scale scienti c collaborations such as within the High Energy Physics (HEP) community to guarantee fairness of resource sharing, but many dif culties can arise when tracing the resource usage of distributed applications over heterogeneous Grid platforms. These dif culties are often related to a lack of interoperability of the accounting components across middlewares. This paper brie y describes the architecture and workow of the Distributed Grid Accounting System (DGAS) [1] and evaluates the possibility to extend it with a Resource Usage Service (RUS) [2, 3] interface according to the Open Grid Forum (OGF) speci cation that allows to store and retrieve OGF Usage Records (URs) [4, 5] via Web Services. In this context the OGF RUS and UR speci cations are critically analyzed. Furthermore, a prototype of a RUS interface for DGAS (DGAS-RUS) is presented and the most recent test results towards a full interoperability between heterogeneous Grid platforms are outlined

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“…They leverage the years of data management research to advance XML technology to the same standards expected from mature relational systems. Weigel et al combine the indexing structures of a native XML database with the power of a relational database in [53].…”

Section: Xml Searchmentioning

confidence: 99%

Using a relational database for scalable XML search

2007

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XML is a flexible and powerful tool that enables information and security sharing in heterogeneous environments. Scalable technologies are needed to effectively manage the growing volumes of XML data. A wide variety of methods exist for storing and searching XML data; the two most common techniques are conventional tree-based and relational approaches. Tree-based approaches represent XML as a tree and use indexes and path join algorithms to process queries. In contrast, the relational approach utilizes the power of a mature relational database to store and search XML. This method relationally maps XML queries to SQL and reconstructs the XML from the database results. To date, the limited acceptance of the relational approach to XML processing is due to the need to redesign the relational schema each time a new XML hierarchy is defined. We, in contrast, describe a relational approach that is fixed schema eliminating the need for schema redesign at the expense of potentially longer runtimes. We show, however, that these potentially longer runtimes are still significantly shorter than those of the tree approach.Using a relational database for scalable XML search 147 We use a popular XML benchmark to compare the scalability of both approaches. We generated large collections of heterogeneous XML documents ranging in size from 500 MB to 8 GB using the XBench benchmark. The scalability of each method was measured by running XML queries that cover a wide range of XML search features on each collection. We measure the scalability of each method over different query features as the collection size increases. In addition, we examine the performance of each method as the result size and the number of predicates increase. Our results show that our relational approach provides a scalable approach to XML retrieval by leveraging existing relational database optimizations. Furthermore, we show that the relational approach typically outperforms the tree-based approach while scaling consistently over all collections studied.

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Exploiting native XML indexing techniques for XML retrieval in relational database systems

Cited by 12 publications

References 26 publications

Efficient XPath query processing

Efficient XPath query processing

Tracing Resource Usage over Heterogeneous Grid Platforms: A Prototype RUS Interface for DGAS

Using a relational database for scalable XML search

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