Algebraic query optimisation for database programming languages

Poulovassilis, Alexandra; Small, Carol

doi:10.1007/s007780050019

Cited by 9 publications

(6 citation statements)

References 25 publications

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“…In this subsection, we present transformation rules which eliminate the above expressions, including "parenthesized", FLWOR, and "if" expressions, and variable references from in-binding expressions. Some of these are already known [12] [13] [16]. By transforming expressions through these rules, function cp f can eliminate all redundant element construction operators and all redundant expressions in child-path expressions.…”

Section: Auxiliary Transformations To Support Child-pathmentioning

confidence: 99%

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Rewriting XQuery by child-path folding

Kato¹,

Hidaka²,

Yoshikawa³

2007

Prog. Inform.

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An XQuery optimization by rewriting based on a partial evaluation using folding expressions is proposed. It consists of two parts: one is the main algorithm, which is a recursive algorithm based on an inductive definition of XQuery expressions. The other is invoked by the main algorithm with an expression whose subexpressions are already folded as its input, and it applies the expression-specific folding function. The main contributions of this paper is to propose an algorithm of an expression-specific folding called "child-path folding". For a given query to the child axis over an element constructed by another XQuery, that is, a composite XQuery, this folding eliminates redundant element construction operators and expressions. These kinds of queries are typical in Global-As-View approach to data integration systems. We also show that all redundant element construction operators and expressions in child-path expressions are eliminated by applying auxiliary transformations. In addition to child-path folding, we discuss folding of major XQuery constructors including FLWOR and quantified expressions. Moreover, we improve the rewriting algorithm based on pruning by adding two annotations to the parsed trees of XQuery expressions.

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Section: Auxiliary Transformations To Support Child-pathmentioning

confidence: 99%

“…Some of these transformations are from [13] [16], or [12]. For example, function ffl stems from the "associative law" of for-expressions in XQuery Core [13], and is almost the same as (R2) of the "Standard XQuery Rewriting Rules" in [12].…”

Section: Auxiliary Transformations To Support Child-pathmentioning

confidence: 99%

Rewriting XQuery by child-path folding

Kato¹,

Hidaka²,

Yoshikawa³

2007

Prog. Inform.

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“…We investigated many useful equivalences for optimising functional DBPLs in (Poulovassilis, et al 1994). A representative sample of the equivalences over comprehensions which we require here govern splitting and merging compound filters, commuting two filters, commuting a filter and a generator, commuting two generators, and moving a filter into a In (Poulovassilis, et al 1996) we also discuss a class of functions called selectors that optimise retrieval from relations by taking advantage of any physical-level indexes available.…”

Section: Optimisation Of Functional Dbplsmentioning

confidence: 99%

“…A representative sample of the equivalences over comprehensions which we require here govern splitting and merging compound filters, commuting two filters, commuting a filter and a generator, commuting two generators, and moving a filter into a In (Poulovassilis, et al 1996) we also discuss a class of functions called selectors that optimise retrieval from relations by taking advantage of any physical-level indexes available. In particular, associated with each relation r is a set of system-defined selectors rp where p is a variable-free pattern all of whose constants are either f or b (denoting "free" and "bound" respectively).…”

Section: Optimisation Of Functional Dbplsmentioning

confidence: 99%

“…These features allow properties of expressions, such as termination and equivalence with other expressions, to be formally proven. Thus whereas imperative DBPLs apply different optimisations to 'program' and 'DML' statements, and support only fine-grained optimisations for program statements, functional DBPLs support powerful, coarse-grained optimisations (such as those discussed in (Poulovassilis, et al 1994)) for all sub-expressions of a query since they do not distinguish between 'program' and 'DML' statements.…”

Section: Introductionmentioning

confidence: 99%

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A formal semantics for an active functional DBPL

1996

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We describe how the functional database programming language PFL is extended with an active component without compromising either its declarative semantics or its syntax. We give a formal specification of the active component using PFL itself, including event specification and detection, parameter-binding, reaction scheduling and abort handling. We describe how a user-specified function can be cast as a primitive event, and discuss the expressiveness of events and the optimisation of event detection.

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A Framework for the Investigation of Aggregate Functions in Database Queries

Cabibbo

Torlone

1999

Lecture Notes in Computer Science

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Algebraic query optimisation for database programming languages

Cited by 9 publications

References 25 publications

Rewriting XQuery by child-path folding

Rewriting XQuery by child-path folding

A formal semantics for an active functional DBPL

A Framework for the Investigation of Aggregate Functions in Database Queries

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