- The R6 classes that wrap the C++ classes are now documented and exported and have been renamed to be more R-friendly. Users of the high-level R interface in this package are not affected. Those who want to interact with the Arrow C++ API more directly should work with these objects and methods. As part of this change, many functions that instantiated these R6 objects have been removed in favor of
Class$create() methods. Notably,
arrow::table() have been removed in favor of
Table$create(), eliminating the package startup message about masking
base functions. For more information, see the new
- Due to a subtle change in the Arrow message format, data written by the 0.15 version libraries may not be readable by older versions. If you need to send data to a process that uses an older version of Arrow (for example, an Apache Spark server that hasn’t yet updated to Arrow 0.15), you can set the environment variable
as_tibble argument in the
read_*() functions has been renamed to
as_data_frame (ARROW-6337, @jameslamb)
arrow::Column class has been removed, as it was removed from the C++ library
RecordBatch objects have S3 methods that enable you to work with them more like
data.frames. Extract columns, subset, and so on. See
?RecordBatch for examples.
- Initial implementation of bindings for the C++ File System API. (ARROW-6348)
- Compressed streams are now supported on Windows (ARROW-6360), and you can also specify a compression level (ARROW-6533)
- Parquet file reading is much, much faster, thanks to improvements in the Arrow C++ library.
read_csv_arrow() supports more parsing options, including
read_feather() can ingest data from a
raw vector (ARROW-6278)
- File readers now properly handle paths that need expanding, such as
- Improved support for creating types in a schema: the types’ printed names (e.g. “double”) are guaranteed to be valid to use in instantiating a schema (e.g.
double()), and time types can be created with human-friendly resolution strings (“ms”, “s”, etc.). (ARROW-6338, ARROW-6364)
Initial CRAN release of the
arrow package. Key features include:
- Read and write support for various file formats, including Parquet, Feather/Arrow, CSV, and JSON.
- API bindings to the C++ library for Arrow data types and objects, as well as mapping between Arrow types and R data types.
- Tools for helping with C++ library configuration and installation.