Cost based plan selection for xpath

Georgiadis, Haris; Charalambides, Minas; Vassalos, Vasilis

doi:10.1145/1559845.1559909

Cited by 11 publications

(13 citation statements)

References 18 publications

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“…Independence from the XML Storage System implementation is achieved via the XPA API. An input XPath expression is parsed by the query parser, which generates a logical plan as its algebraic representation in XPAlgebra [8], our navigation-based XPath algebra.…”

Section: Architecturementioning

confidence: 99%

“…Using this initial logical plan, the Physical Plan Selector generates the best physical plan using an efficient plan selection algorithm called PSA [8], or the Physical Plan Generator generates all possible physical plans (based on a naïve algorithm called GAPH). Both PSA and GAPH make use of the available Rewriting Rules for logical transformations, access all needed statistics from the Database Statistics interface of the XPA and retrieve the costs of physical operators from their Descriptors.…”

Section: Architecturementioning

confidence: 99%

“…There is a straightforward algorithm for translating an XPath expression to its algebraic correspondence in XPalgebra which can be considered as a logical query plan. More information about XPalgebra can be found in [8]. The filter operator f corresponds to the predicate of the XPath query.…”

Section: Figure 1 System Architecturementioning

confidence: 99%

“…Experimental evaluation of the effectiveness of the overall GeCOEX system has shown that the execution time of the chosen plan is within 12% of the optimal execution time in all but one of the queries in the tested workloads [8].…”

Section: Introductionmentioning

confidence: 96%

“…The GeCOEX system is based on the framework presented in [8] and [9]. GeCOEX uses a logical XPath algebra and a set of rewriting rules that together can algebraically capture many XPath processing strategies.…”

Section: Introductionmentioning

confidence: 99%

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A query optimization assistant for XPath

Georgiadis¹,

Charalambidis²,

Vassalos³

2011

Proceedings of the 14th International Conference on Extending Database Technology

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We demonstrate a generic and extensible cost-based optimization and execution system for XPath queries, named GeCOEX, using a comprehensive suite of query analyzing and administrative tools, named QuOAX. GeCOEX supports many different physical operator implementations and XML storage engines and is agnostic to the underlying physical data model. Its optimizer is the first generic cost-based optimizer for XPath queries that always picks the cheapest estimated plan, among a very large number of possible plans, for a wide range of XPath queries and different datasets in a very small fraction of the time required for efficient execution. The QuOAX suite provides administration tools that allow the user to add new -or deactivate already deployed -physical operator implementations, physical operator cost models and rewriting rules and also to make use of different XML storage and XML statistics estimators. QuOAX also provides query plan analysis and visualization tools that allow users to visualize the physical plan chosen by the optimizer or all possible generated physical plans for a given query and to execute any of those plans. QuOAX helps users to i) easily test new XPath processing techniques, comparing them directly with existing ones and identifying the situations to which they show promise, ii) improve the effectiveness of the optimizer and iii) find out the appropriate access methods or indices that are beneficial for a specific workload.

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Section: Architecturementioning

confidence: 99%

Section: Architecturementioning

confidence: 99%

Section: Figure 1 System Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A query optimization assistant for XPath

Georgiadis¹,

Charalambidis²,

Vassalos³

2011

Proceedings of the 14th International Conference on Extending Database Technology

Self Cite

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A heuristic approach to selecting views for materialization

Roantree

2013

Softw. Pract. Exper.

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SUMMARYXML data warehouses are becoming more popular as data is harvested from the web or as output from web services. As these warehouses tend to grow significantly over time, various techniques for expediting queries have been developed. One such technique is to materialize some or all of the queries in advance of query processing. These views are then subject to change either when underlying data changes or view definitions themselves are modified by users. The work in this paper focuses on changes to view definitions or view adaptation as it is known. Our approach is to segment the materialized view into fragments to minimize the effect of view changes. One crucial aspect to this approach is how to select the best fragments for materialization. In this paper, we introduce a new approach to selecting fragments based on heuristics derived from costs associated with the view graph. Copyright © 2013 John Wiley & Sons, Ltd.

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Efficient Evaluation of NOT-Twig Queries in Tree-Unaware Relational Databases

Soh

Bhowmick

2011

Database Systems for Advanced Applications

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Cost based plan selection for xpath

Cited by 11 publications

References 18 publications

A query optimization assistant for XPath

A query optimization assistant for XPath

A heuristic approach to selecting views for materialization

Efficient Evaluation of NOT-Twig Queries in Tree-Unaware Relational Databases

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