bdpar: Big Data Preprocessing Architecture

Provide a tool to easily build customized data flows to pre-process large volumes of information from different sources. To this end, 'bdpar' allows to (i) easily use and create new functionalities and (ii) develop new data source extractors according to the user needs. Additionally, the package provides by default a predefined data flow to extract and pre-process the most relevant information (tokens, dates, ... ) from some textual sources (SMS, Email, tweets, YouTube comments).

Version: 3.0.0
Depends: R (≥ 3.5.0)
Imports: digest, parallel, R6, rlist, tools, utils
Suggests: cld2, knitr, rex, rjson, rmarkdown, rtweet, stringi, stringr, testthat (≥ 2.3.1), tuber
Published: 2020-11-25
Author: Miguel Ferreiro-Díaz [aut, cre], David Ruano-Ordás [aut, ctr], Tomás R. Cotos-Yañez [aut, ctr], University of Vigo [cph]
Maintainer: Miguel Ferreiro-Díaz <miguel.ferreiro.diaz at>
License: GPL-3
NeedsCompilation: no
SystemRequirements: Python (>= 2.7 or >= 3.6)
Materials: NEWS
CRAN checks: bdpar results


Reference manual: bdpar.pdf
Vignettes: A Brief Introduction to bdpar
Basic example using bdpar package
Image processing example using bdpar package
Package source: bdpar_3.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: bdpar_3.0.0.tgz, r-oldrel: bdpar_3.0.0.tgz
Old sources: bdpar archive


Please use the canonical form to link to this page.