Efficient algorithms for minimizing tree pattern queries

Ramanan, Prakash

doi:10.1145/564691.564726

Cited by 54 publications

(67 citation statements)

References 22 publications

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“…So, no matter whether we use a naive XML to relational translation, or these more sophisticated translation schemes, in the end the RDBMS will evaluate SQ 1 1 . Another valid question to ask at this point is whether the algorithms for minimizing XML queries, such as in [3,18], will help in this context. These algorithms remove parts of the XML query that are made redundant by other parts of the query.…”

Section: Translation Examplementioning

confidence: 99%

Efficient XML-to-SQL Query TranslationWhere to Add the Intelligence?

Krishnamurthy¹,

Kaushik²,

Naughton³

2004

Proceedings 2004 VLDB Conference

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We consider the efficiency of queries generated by XML to SQL translation. We first show that published XML-to-SQL query translation algorithms are suboptimal in that they often translate simple path expressions into complex SQL queries even when much simpler equivalent SQL queries exist. There are two logical ways to deal with this problem. One could generate suboptimal SQL queries using a fairly naive translation algorithm, and then attempt to optimize the resulting SQL; or one could use a more intelligent translation algorithm with the hopes of generating efficient SQL directly. We show that optimizing the SQL after it is generated is problematic, becoming intractable even in simple scenarios; by contrast, designing a translation algorithm that exploits information readily available at translation time is a promising alternative. To support this claim, we present a translation algorithm that exploits translation time information to generate efficient SQL for path expression queries over tree schemas.

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Section: Translation Examplementioning

confidence: 99%

Efficient XML-to-SQL Query TranslationWhere to Add the Intelligence?

Krishnamurthy¹,

Kaushik²,

Naughton³

2004

Proceedings 2004 VLDB Conference

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“…Since the size of an XPath query (in terms of the number of steps) is a key determinant of its evaluation complexity (e.g., [8]), an obvious optimization that has been explored is to minimize the size of a XPath query by eliminating redundant steps [17,2,13]. More recent work has shifted to understanding the properties of XPath expressions to identify useful rewriting rules [3], eliminating reverse axes in queries to facilitate their evaluation on streaming data [12], and to transforming queries to algebraic form for efficient evaluation [10].…”

Section: Permission To Copy Without Fee All or Part Of This Materials mentioning

confidence: 99%

“…In contrast to the research on minimizing redundant XPath steps [17,2,13] which relies on integrity constraints of the data schema, our rewriting techniques are designed for minimizing non-redundant wildcard steps and do not require knowledge of the data schema. Another difference from these work is that our techniques apply to a larger fragment of XPath queries beyond the child and descendant axes considered for twig queries there.…”

Section: Related Workmentioning

confidence: 99%

Taming XPath Queries by Minimizing Wildcard Steps

Chan

Fan

Zeng

2004

Proceedings 2004 VLDB Conference

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This paper presents a novel and complementary technique to optimize an XPath query by minimizing its wildcard steps. Our approach is based on using a general composite axis called the layer axis, to rewrite a sequence of XPath steps (all of which are wildcard steps except for possibly the last) into a single layer-axis step. We describe an efficient implementation of the layer axis and present a novel and efficient rewriting algorithm to minimize both non-branching as well as branching wildcard steps in XPath queries. We also demonstrate the usefulness of wildcard-step elimination by proposing an optimized evaluation strategy for wildcard-free XPath queries that enables selective loading of only the relevant input XML data for query evaluation. Our experimental results not only validate the scalability and efficiency of our optimized evaluation strategy, but also demonstrate the effectiveness of our rewriting algorithm for minimizing wildcard steps in XPath queries. To the best of our knowledge, this is the first effort that addresses this new optimization problem.

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“…The query equivalence problem is closely linked to the query minimization problem, which is essential for data base researchers. Since the time required for the evaluation of a given query Q is linear with respect to the size of Q ( [6]), the minimization -possibility of replacing Q by an equivalent query of smaller size -is of interest from the point of view of complexity ( [7,8,9,10]). …”

Section: Introductionmentioning

confidence: 99%