Native Xquery processing in oracle XMLDB

Liu, Zhen Hua; Krishnaprasad, Muralidhar; Arora, Vikas

doi:10.1145/1066157.1066259

Cited by 42 publications

(33 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We prefer to clearly separate logical and physical algebra, as it is done e.g. in (Jagadish et al, 2002;Liu et al, 2005;Boncz et al, 2006) where the logical algebra is not concerned with specific implementations of operators. These implementations are defined by the physical algebra.…”

Section: Query Representations For Xquery Optimizationmentioning

confidence: 99%

“…Commercial relational database products also support XQuery to a varying extent. Microsoft SQL Server (Pal et al, 2005) and Oracle XML DB (Liu et al, 2005) support fragments of the XQuery specification. Queries are translated into algebraic expressions and, if possible, rewriting techniques of the relational optimizer are used for optimizations.…”

Section: Query Representations For Xquery Optimizationmentioning

confidence: 99%

“…Pathfinder and MonetDB/XQuery Full Full Logical algebra and either SQL (Pathfinder) or physical algebra (MonetDB) MS SQL Server (Pal et al, 2005) Partial Partial Logical and physical algebra Oracle XML DB (Liu et al, 2005) Partial Partial Logical and physical algebra IBM DB2 (Ozcan et al, 2005;Nicola & van der Linden, 2005) Full Full Calculus and physical algebra …”

Section: Approachmentioning

confidence: 99%

“…Recently algebraic optimization techniques, as they are standard in relational databases, were used to build XQuery processors where optimizations are stated as algebraic equivalences, e.g. (Naughton et al, 2001;Jagadish et al, 2002;Fiebig et al, 2002;May et al, 2006;Ozcan et al, 2005;Nicola & van der Linden, 2005;Boncz et al, 2006;Liu et al, 2005;Pal et al, 2005). This development is motivated by the ability (1) to apply optimizations known from relational databases and adopt them for XML processing, (2) to prove the correctness of query optimizations based on a formallydefined query representation.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Normalization and Translation of XQuery

May

Moerkotte²

2010

Advanced Applications and Structures in XML Processing

View full text Add to dashboard Cite

Early approaches to XQuery processing proposed proprietary techniques to optimize and evaluate XQuery statements. In this chapter, we argue for an algebraic optimization and evaluation technique for XQuery as it allows us to benefit from experience gained with relational databases. An algebraic XQuery processing method requires a translation into an algebra representation. While many publications already exist on algebraic optimizations and evaluation techniques for XQuery, an assessment of translation techniques is required. Consequently, we give a comprehensive survey for translating XQuery into various query representations. We relate these approaches to the way normalization and translation is implemented in Natix and discuss these two steps in detail. In our experience, our translation method is a good basis for further optimizations and query evaluation.

show abstract

Section: Query Representations For Xquery Optimizationmentioning

confidence: 99%

Section: Query Representations For Xquery Optimizationmentioning

confidence: 99%

Section: Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Normalization and Translation of XQuery

May

Moerkotte²

2010

Advanced Applications and Structures in XML Processing

View full text Add to dashboard Cite

show abstract

“…Object-Relational DBMSs such as Oracle 10g provide a repository functionality called XML native type to store XML documents in the database without any conversion, and support updates, indexing, search, and multiple views on this data type (Liu, 2005). As an alternative, most commercial DBMS products (e.g.…”

Section: Related Researchmentioning

confidence: 99%

Integration of Weakly Heterogeneous Semistructured Data

Feuerlicht

Pokorný

Richta

et al. 2009

Information Systems Development

View full text Add to dashboard Cite

While most business applications typically operate on structured data that can be effectively managed using relational databases, some applications use more complex semistructured data that lacks a stable schema. XML techniques are available for the management of semistructured data, but such techniques tend to be ineffective when applied to large amounts of heterogeneous data, in particular in applications with complex query requirements. In this paper we describe an approach that relies on the mapping of multiple semistructured data sets to objectrelational structures and uses an object-relational database to support complex query requirements. We illustrate this approach using weakly heterogeneous oceanographic data.

show abstract