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The bdpar Package: Big Data Pipelining Architecture for R

In the last years, big data has become a useful paradigm for taking advantage of multiple sources to find relevant knowledge in real domains (such as the design of personalized marketing campaigns or helping to palliate the effects of several fatal diseases). Big data programming tools and methods have evolved over time from a MapReduce to a pipeline-based archetype. Concretely the use of pipelining schemes has become the most reliable way of processing and analyzing large amounts of data. To this end, this work introduces bdpar, a new highly customizable pipeline-based framework (using the OOP paradigm provided by R6 package) able to execute multiple preprocessing tasks over heterogeneous data sources. Moreover, to increase the flexibility and performance, bdpar provides helpful features such as (i) the definition of a novel object-based pipe operator (+ACUAPgB8ACU), (ii) the ability toeasily design and deploy new (and customized) input data parsers, tasks, and pipelines, (iii) only-once execution which avoids the execution of previously processed information (instances), guaranteeing that only new both input data and pipelines are executed, (iv) the capability to perform serial or parallel operations according to the user needs, (v) the inclusion of a debugging mechanism whichallows users to check the status of each instance (and find possible errors) throughout the process.

Autores: Miguel Ferreiro-Díaz / Tomás R Cotos-Yáñez / José R. Méndez / David Ruano Ordas / 
Palabras Clave: Heterogeneous data sources - package R - pipeline

Early Integration Testing for Entity Reconciliation in the Context of Heterogeneous Data Sources

– Revista en la que fue publicado el trabajo: IEEE TRANSACTIONS ON RELIABILITY, VOL. 67, NO. 2
– Fecha de publicación: Junio 2018
– Páginas: 538-556
– DOI: 10.1109/TR.2018.2809866
– Índice JCR: 2,729
– Cuartil: Q1

Autores: Raquel Blanco / José González Enríquez / Francisco J. Domínguez-Mayo / María José Escalona / Javier Tuya / 
Palabras Clave: Early testing - Entity reconciliation - Heterogeneous data sources - Model-Driven Engineering - Software Testing - Specification-based testing

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