The Flatter, the Better

Ulrich, Alexander; Grust, Torsten

doi:10.1145/2723372.2735359

“…Language-integrated query and web programming. Our approach is implemented in Links [Cooper et al 2006], but should also be applicable to other functional languages with support for languageintegrated query, such as Ur/Web [Chlipala 2015] and F# [Syme 2006], or the Database-Supported Haskell library [Ulrich and Grust 2015]. Our incremental relational lens definitions could also be implemented inside a database system.…”

Section: Related Workmentioning

confidence: 99%

Incremental relational lenses

Horn

¹

,

Perera

²

,

Cheney

³

2018

Proc. ACM Program. Lang.

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Lenses are a popular approach to bidirectional transformations, a generalisation of the view update problem in databases, in which we wish to make changes to source tables to effect a desired change on a view. However, perhaps surprisingly, lenses have seldom actually been used to implement updatable views in databases. Bohannon, Pierce and Vaughan proposed an approach to updatable views called relational lenses, but to the best of our knowledge this proposal has not been implemented or evaluated to date. We propose incremental relational lenses, that equip relational lenses with change-propagating semantics that map small changes to the view to (potentially) small changes to the source tables. We also present a language-integrated implementation of relational lenses and a detailed experimental evaluation, showing orders of magnitude improvement over the non-incremental approach. Our work shows that relational lenses can be used to support expressive and efficient view updates at the language level, without relying on updatable view support from the underlying database.A typical web application is based on a three-tier architecture with user interaction on the client (web browser), application logic on the server, and data stored in a (typically relational) database. Relational databases employ SQL query and update expressions, including projections, selections and joins, which correspond closely to familiar list comprehension operations in functional languages. Relational databases offer data persistence and high performance and are flexible enough for a range of applications. However, the impedance mismatch between database queries and conventional programming makes even simple programming tasks challenging [Copeland and Maier 1984]. Languages such as C# [Meijer et al. 2006], F# [Syme 2006; Cheney et al. 2013], Links [Cooper et al. 2006], and Ur/Web [Chlipala 2015], and libraries such as Database-Supported Haskell [Ulrich andGrust 2015], have partly overcome this challenge using language-integrated query, in which query expressions are integrated into the host language and type system. However, language support for database programming is still incomplete. For example, views are a fundamental concept in databases [Ramakrishnan and Gehrke 2003] that are typically not supported in language-integrated query. A view is a relation defined over the database tables using a relational query. Views have many applications: 1 Information such as the hostname, port, username and password needed to access the database also needs to be provided; this can be included in the database expression or, as here, in a separate configuration file. 2 Such constraints are not currently checked in our implementation, but this is straightforward and an orthogonal concern. Incremental Relational Lenses :5 var albumsLens = lens albumsTable with album -> quantity; var tracksLens = lens tracksTable with track -> date rating;A common workflow within a web application is to extract some view of the data from the database, associate it with a f...

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“…Furthermore, generated queries including nested collections are transparent to L 's query normalization algorithm and we can generate efficient queries even when filtering based on provenance information. This applies to other languages with similarly powerful language-integrated query facilities, notably H with the D library [Ulrich and Grust, 2015].…”

Section: "Support For Large Databases"mentioning

confidence: 99%

“…The second approach, which we call comprehension, uses monadic comprehensions or related constructs of the host language, and generates queries from such expressions. The comprehension approach builds on foundations for querying databases using comprehensions developed by Buneman et al [1995], and has been adopted in languages such as F# [Syme, 2006] and L [Cooper et al, 2007] as well as libraries such as Database-Supported H (D ) [Giorgidze et al, 2011;Ulrich and Grust, 2015] and Q Λ [Suzuki et al, 2016].…”

Section: Language-integrated Querymentioning

confidence: 99%

Language-integrated provenance

Fehrenbach

¹

,

Cheney

²

2018

Science of Computer Programming

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When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given.My thanks, first and foremost, to my advisor James Cheney for his generous guidance, encouragement, and unyielding support. I have left every single one of our meetings happier and more confident than I entered it, even and especially when things had gone poorly. I would also like to thank Peter Buneman, Ian Stark, James McKinna, and Jan Stolarek for their interest and feedback. I would like to thank Torsten Grust and Sam Lindley for agreeing to be my examiners and their feedback, and Stephen Gilmore for chairing my viva.Thanks to my awesome office mates Karoliina, Fabian, Ricardo, and Rudi; to the Friday lunch crowd Brian,

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“…Language-integrated query and web programming. Our approach is implemented in Links [Cooper et al 2006], but should also be applicable to other functional languages with support for languageintegrated query, such as Ur/Web [Chlipala 2015] andF# [Syme 2006], or the Database-Supported Haskell library [Ulrich and Grust 2015]. Our incremental relational lens definitions could also be implemented inside a database system.…”

Section: Related Workmentioning

confidence: 99%

“…However, the impedance mismatch between database queries and conventional programming makes even simple programming tasks challenging [Copeland and Maier 1984]. Languages such as C# [Meijer et al 2006], F# [Syme 2006;Cheney et al 2013], Links [Cooper et al 2006], and Ur/Web [Chlipala 2015], and libraries such as Database-Supported Haskell [Ulrich and Grust 2015], have partly overcome this challenge using language-integrated query, in which query expressions are integrated into the host language and type system. However, language support for database programming is still incomplete.…”

Section: Introductionmentioning

confidence: 99%

Replication Package for Article

Horn¹,

Perera²,

Cheney³

2018

Artifact Digital Object Group

0

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Lenses are a popular approach to bidirectional transformations, a generalisation of the view update problem in databases, in which we wish to make changes to source tables to effect a desired change on a view. However, perhaps surprisingly, lenses have seldom actually been used to implement updatable views in databases. Bohannon, Pierce and Vaughan proposed an approach to updatable views called relational lenses, but to the best of our knowledge this proposal has not been implemented or evaluated to date. We propose incremental relational lenses, that equip relational lenses with change-propagating semantics that map small changes to the view to (potentially) small changes to the source tables. We also present a language-integrated implementation of relational lenses and a detailed experimental evaluation, showing orders of magnitude improvement over the non-incremental approach. Our work shows that relational lenses can be used to support expressive and efficient view updates at the language level, without relying on updatable view support from the underlying database. INTRODUCTIONA typical web application is based on a three-tier architecture with user interaction on the client (web browser), application logic on the server, and data stored in a (typically relational) database. Relational databases employ SQL query and update expressions, including projections, selections and joins, which correspond closely to familiar list comprehension operations in functional languages. Relational databases offer data persistence and high performance and are flexible enough for a range of applications. However, the impedance mismatch between database queries and conventional programming makes even simple programming tasks challenging [Copeland and Maier 1984]. Languages such as C# [Meijer et al. 2006 2015], have partly overcome this challenge using language-integrated query, in which query expressions are integrated into the host language and type system.

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The Flatter, the Better

Cited by 12 publications

References 17 publications

Incremental relational lenses

Incremental relational lenses

Language-integrated provenance

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