Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess communication.
The arrow package exposes an interface to the Arrow C++ library to
access many of its features in R. This includes support for working with
Parquet (read_parquet(), write_parquet()) and Feather
(read_feather(), write_feather()) files, as well as lower-level
access to Arrow memory and messages.
Install the latest release of arrow from CRAN with
install.packages("arrow")On macOS and Windows, installing a binary package from CRAN will handle Arrow’s C++ dependencies for you. On Linux, you’ll need to first install the C++ library. See the Arrow project installation page for a list of PPAs from which you can obtain it.
If you install the arrow package from source and the C++ library is
not found, the R package functions will notify you that Arrow is not
available. Call
arrow::install_arrow()for version- and platform-specific guidance on installing the Arrow C++ library.
library(arrow)
#>
#> Attaching package: 'arrow'
#> The following object is masked from 'package:utils':
#>
#> timestamp
#> The following objects are masked from 'package:base':
#>
#> array, table
set.seed(24)
tab <- arrow::table(x = 1:10, y = rnorm(10))
tab$schema
#> arrow::Schema
#> x: int32
#> y: double
tab
#> arrow::Table
as.data.frame(tab)
#> x y
#> 1 1 -0.545880758
#> 2 2 0.536585304
#> 3 3 0.419623149
#> 4 4 -0.583627199
#> 5 5 0.847460017
#> 6 6 0.266021979
#> 7 7 0.444585270
#> 8 8 -0.466495124
#> 9 9 -0.848370044
#> 10 10 0.002311942To use the development version of the R package, you’ll need to install it from source, which requires the additional C++ library setup. On macOS, you may install the C++ library using Homebrew:
# For the released version:
brew install apache-arrow
# Or for a development version, you can try:
brew install apache-arrow --HEADOn Windows, you can download a .zip file with the arrow dependencies
from the rwinlib project,
and then set the RWINLIB_LOCAL environment variable to point to that
zip file before installing the arrow R package. That project contains
released versions of the C++ library; for a development version, Windows
users may be able to find a binary by going to the Apache Arrow
project’s
Appveyor,
selecting an R job from a recent build, and downloading the
build\arrow-*.zip file from the “Artifacts” tab.
Linux users can get a released version of the library from our PPAs, as described above. If you need a development version of the C++ library, you will likely need to build it from source. See “Development” below.
Once you have the C++ library, you can install the R package from GitHub
using the remotes package. From within
an R session,
# install.packages("remotes") # Or install "devtools", which includes remotes
remotes::install_github("apache/arrow/r")or if you prefer to stay at the command line,
R -e 'remotes::install_github("apache/arrow/r")'You can specify a particular commit, branch, or
release to install by
including a ref argument to install_github().
If you need to alter both the Arrow C++ library and the R package code, or if you can’t get a binary version of the latest C++ library elsewhere, you’ll need to build it from source too.
First, install the C++ library. See the C++ developer guide for details.
Note that after any change to the C++ library, you must reinstall it and
run make clean or git clean -fdx . to remove any cached object code
in the r/ directory.
Once you’ve built the C++ library, you can install the R package and its dependencies, along with additional dev dependencies, from the git checkout:
cd ../../r
R -e 'install.packages("devtools"); devtools::install_dev_deps()'
R CMD INSTALL .If the package fails to install/load with an error like this:
** testing if installed package can be loaded from temporary location
Error: package or namespace load failed for 'arrow' in dyn.load(file, DLLpath = DLLpath, ...):
unable to load shared object '/Users/you/R/00LOCK-r/00new/arrow/libs/arrow.so':
dlopen(/Users/you/R/00LOCK-r/00new/arrow/libs/arrow.so, 6): Library not loaded: @rpath/libarrow.14.dylib
try setting the environment variable LD_LIBRARY_PATH (or
DYLD_LIBRARY_PATH on macOS) to wherever Arrow C++ was put in make install, e.g. export LD_LIBRARY_PATH=/usr/local/lib, and retry
installing the R package.
For any other build/configuration challenges, see the C++ developer guide.
The arrow package uses some customized tools on top of Rcpp to
prepare its C++ code in src/. If you change C++ code in the R package,
you will need to set the ARROW_R_DEV environment variable to TRUE
(optionally, add it to your~/.Renviron file to persist across
sessions) so that the data-raw/codegen.R file is used for code
generation.
The codegen.R script has these dependencies:
remotes::install_github("romainfrancois/decor")
install.packages(c("dplyr", "purrr", "glue"))
Within an R session, these can help with package development:
devtools::load_all() # Load the dev package
devtools::test(filter="^regexp$") # Run the test suite, optionally filtering file names
devtools::document() # Update roxygen documentation
rmarkdown::render("README.Rmd") # To rebuild README.md
pkgdown::build_site(run_dont_run=TRUE) # To preview the documentation website
devtools::check() # All package checks; see also belowAny of those can be run from the command line by wrapping them in R -e '$COMMAND'. There’s also a Makefile to help with some common tasks
from the command line (make test, make doc, make clean, etc.)
R CMD build --keep-empty-dirs .
R CMD check arrow_*.tar.gz --as-cran --no-manual