Improving list comprehension database queries

Trinder, Phil; Wadler, Philip

doi:10.1109/tencon.1989.176921

Cited by 34 publications

(26 citation statements)

References 11 publications

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“…Many programming languages provide a comprehension notation offering operations over lists analogous to those provided by SQL over tables (Trinder and Wadler 1989;Buneman et al 1994). F# also supports a form of comprehension notation called computation expressions (Petricek and Syme 2012).…”

Section: Comprehensions and Queriesmentioning

confidence: 99%

A practical theory of language-integrated query

Cheney

Lindley

Wadler

2013

Proceedings of the 18th ACM SIGPLAN International Conference on Functional Programming

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Language-integrated query is receiving renewed attention, in part because of its support through Microsoft's LINQ framework. We present a practical theory of language-integrated query based on quotation and normalisation of quoted terms. Our technique supports join queries, abstraction over values and predicates, composition of queries, dynamic generation of queries, and queries with nested intermediate data. Higher-order features prove useful even for constructing first-order queries. We prove a theorem characterising when a host query is guaranteed to generate a single SQL query. We present experimental results confirming our technique works, even in situations where Microsoft's LINQ framework either fails to produce an SQL query or, in one case, produces an avalanche of SQL queries.

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Section: Comprehensions and Queriesmentioning

confidence: 99%

A practical theory of language-integrated query

Cheney

Lindley

Wadler

2013

Proceedings of the 18th ACM SIGPLAN International Conference on Functional Programming

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“…Trinder and Wadler (Trinder and Wadler 1989) demonstrate how query optimization based on relational algebra identities can be performed by corresponding transformations on queries in list comprehension form. Consider the query…”

Section: Algebraic Optimizationsmentioning

confidence: 99%

Optimizing relational algebra operations using generic equivalence discriminators and lazy products

Henglein

2010

Proceedings of the 2010 ACM SIGPLAN Workshop on Partial Evaluation and Program Manipulation

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We show how to efficiently evaluate generic map-filter-product queries, generalizations of select-project-join (SPJ) queries in relational algebra, based on a combination of two novel techniques: generic discrimination-based joins and lazy (formal) products.Discrimination-based joins are based on the notion of (equivalence) discriminator. A discriminator partitions a list of values according to a user-specified equivalence relation on keys the values are associated with. Equivalence relations can be specified in an expressive embedded language for denoting equivalence relations. We show that discriminators can be constructed generically (by structural recursion on equivalence expressions), purely functionally, and efficiently (worst-case linear time). The array-based basic multiset discrimination algorithm of Cai and Paige (1995) provides a base discriminator that is both asymptotically and practically efficient. In contrast to hashing, discrimination is fully abstract (only depends on which equivalences hold on its inputs), and in contrast to comparison-based sorting, it does not require an ordering relation on its inputs. In particular, it is applicable to references (pointers). Furthermore, it has better asymptotic computational complexity than both sorting and hashing.We represent cross-products and unions lazily (symbolically) as formal products of the argument sets (relations). This allows the selection operation to recognize on the fly whenever it is applied to a cross-product and invoke an efficient equijoin implementation. In particular, queries can still be formulated naively, using filter, map and product without an explicit join operation, yet garner the advantages of efficient join-algorithms during evaluation.The techniques subsume many of the optimization techniques based on relational algebra equalities, without need for a query preprocessing phase. They require no indexes and behave purely functionally. They can be considered a form of symbolic execution of set expressions that automate and encapsulate dynamic program transformation of such expressions and lead to asymptotic performance improvements over naive execution in many cases.

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“…This mixing is not possible for monad comprehensions, since they restrict the inputs and the output of a comprehension to be of the same type. Monad comprehensions were first proposed as a convenient database language by Trinder and Wadler [1989]; Trinder [1991];and Chan and Trinder [1994], who also presented many algebraic transformations over these forms, as well as methods for converting comprehensions into joins. The monad comprehension syntax was also adopted by Buneman et al [1994] as an alternative syntax to monoid homomorphisms.…”

Section: Related Workmentioning

confidence: 99%

Optimizing object queries using an effective calculus

Fegaras

Maier

2000

ACM Trans. Database Syst.

110

104

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Object-oriented databases (OODBs) provide powerful data abstractions and modeling facilities, but they generally lack a suitable framework for query processing and optimization. The development of an effective query optimizer is one of the key factors for OODB systems to successfully compete with relational systems, as well as to meet the performance requirements of many nontraditional applications. We propose an effective framework with a solid theoretical basis for optimizing OODB query languages. Our calculus, called the monoid comprehension calculus, captures most features of ODMG OQL, and is a good basis for expressing various optimization algorithms concisely. This article concentrates on query unnesting (also known as query decorrelation), an optimization that, even though it improves performance considerably, is not treated properly (if at all) by most OODB systems. Our framework generalizes many unnesting techniques proposed recently in the literature, and is capable of removing any form of query nesting using a very simple and efficient algorithm. The simplicity of our method is due to the use of the monoid comprehension calculus as an intermediate form for OODB queries. The monoid comprehension calculus treats operations over multiple collection types, aggregates, and quantifiers in a similar way, resulting in a uniform method of unnesting queries, regardless of their type of nesting.

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Improving list comprehension database queries

Cited by 34 publications

References 11 publications

A practical theory of language-integrated query

A practical theory of language-integrated query

Optimizing relational algebra operations using generic equivalence discriminators and lazy products

Optimizing object queries using an effective calculus

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