Data compression with r

Most of the time when you use R for data mining or scientific purposes, you find at the very beginning that the data you are working with is huge in size, from a couple hundred MBs to GBs or even TBs.
Depending on your situation you may not have the physical capacity on your computer to have these files as they are.
Enter compression.

R supports two primary ways of accessing compressed data.
This allows you to keep your data files on disk compressed saving space, and often time (since the file I/O saved by compression is often more expensive than the cpu cycles it uses).
If you are storing your data in native format, simply use the compress option of save:.

Maybe it's too late to answer this question, but I thought I better share some recent work in R that allows compressing data frames.
Currently, there is a package in R called fst ( Lightning Fast Serialization of Data Frames for R) , in which you can create compressed fst objects for your data frame.

Enter compression.
Most of the time the numeric data you are working with has a pretty decent compress ratio, and by utilizing this technique you can save your ever precious computing resources by simply storing the data compressed, and let R do the magic.
You must make a clear distinction between the following two cases:.

R supports two primary ways of accessing compressed data

This allows you to keep your data files on disk compressed saving space, and often time (since the file I/O saved by compression is often more expensive than the cpu cycles it uses)

If you are storing your data in native format, simply use the compress option of save:

Maybe it's too late to answer this question, but I thought I better share some recent work in R that allows compressing data frames

Currently, there is a package in R called fst ( Lightning Fast Serialization of Data Frames for R) , in which you can create compressed fst objects for your data frame

Most of the time the numeric data you are working with has a pretty decent compress ratio, and by utilizing this technique you can save your ever precious computing resources by simply storing the data compressed, and let R do the magic

You must make a clear distinction between the following two cases: