rquery: Relational Query Generator for Data Manipulation at Scale

A 'SQL' query generator based on Edgar F. Codd's relational algebra and experience using 'SQL' and 'dplyr' at big data scale. The design represents an attempt to make 'SQL' more teachable by denoting composition by a sequential pipeline notation instead of nested queries or functions. The implementation delivers reliable high performance data processing on large data systems such as ‘Spark' and databases. Package features include: data processing trees or pipelines as observable objects (able to report both columns produced and columns used), optimized ’SQL' generation as an explicit user visible modeling step, and convenience methods for applying query trees to in-memory 'data.frame's.

Version: 0.4.3
Depends: R (≥ 3.4.0), wrapr (≥ 1.3.0)
Imports: DBI, utils
Suggests: RSQLite, igraph, DiagrammeR, knitr, rmarkdown, testthat
Published: 2018-05-08
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount at win-vector.com>
License: GPL-3
URL: https://github.com/WinVector/rquery/, https://winvector.github.io/rquery/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: rquery results

Downloads:

Reference manual: rquery.pdf
Vignettes: Assignment Partitioner
Query Generation
rquery Introduction
Package source: rquery_0.4.3.tar.gz
Windows binaries: r-devel: rquery_0.4.3.zip, r-release: rquery_0.4.3.zip, r-oldrel: rquery_0.4.3.zip
OS X binaries: r-release: rquery_0.4.3.tgz, r-oldrel: rquery_0.4.2.tgz
Old sources: rquery archive

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