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Typing Massive JSON Datasets

Dario Colazzo 1, 2 Giorgio Ghelli 3 Carlo Sartiani 4
2 OAK - Database optimizations and architectures for complex large data
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : Cloud-specific languages are usually untyped, and no guarantees about the correctness of complex jobs can be statically obtained. Datasets too are usually untyped and no schema information is needed for their manipulation. In this paper we sketch a typing algorithm for JSON datasets. Our approach can be used to infer a succinct type from scratch for a collection of JSON objects, as well as to validate a dataset against a human-designed type and, if necessary, to adapt and improve this type.
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Conference papers
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https://hal.inria.fr/hal-00758716
Contributor : Dario Colazzo <>
Submitted on : Thursday, November 29, 2012 - 11:04:54 AM
Last modification on : Tuesday, April 21, 2020 - 1:05:07 AM

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  • HAL Id : hal-00758716, version 1

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Dario Colazzo, Giorgio Ghelli, Carlo Sartiani. Typing Massive JSON Datasets. International Workshop on Cross-model Language Design and Implementation (XLDI), Sep 2012, Copenhagen, Denmark. ⟨hal-00758716⟩

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