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Iotools

High-performance I/O tools to run distributed R jobs seamlessly on Hadoop and handle chunk-wise data processing

Install / Use

/learn @s-u/Iotools
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

High-performance I/O tools for R

Anyone dealing with large data knows that stock tools in R are bad at loading (non-binary) data to R. This package started as an attempt to provide high-performance parsing tools that minimize copying and avoid the use of strings when possible (see mstrsplit, for example). A paper describing the some functionality of the package can be found here

To allow processing of arbitrarily large files we have added way to process chunk-wise input, making it possible to compute on streaming input as well as very large files (see chunk.reader and chunk.apply).

The next natural progress was to wrap support for Hadoop streaming. The major goal was to make it possible to compute using Hadoop Map Reduce by writing code that is very natural - very much like using lapply on data chunks without the need to know anything about Hadoop. See the WiKi page for the idea and hmr function for the documentation.

CRAN RForge check

View on GitHub
GitHub Stars48
CategoryDevelopment
Updated1mo ago
Forks11

Languages

C

Security Score

75/100

Audited on Feb 19, 2026

No findings