mvl2R

If the object is stored in MVL file, we return its pure R representation. 
Otherwise, we return the object itself.

Mappable vector library provides convenient way to access large datasets. Use all of your data at once, with few limits. Memory mapped data can be shared between multiple R processes. Access speed depends on storage medium, so solid state drive is recommended, preferably with PCI Express (or M.2 nvme) interface or a fast network file system. The data is memory mapped into R and then accessed using usual R list and array subscription operators. Convenience functions are provided for merging, grouping and indexing large vectors and data.frames. The layout of underlying MVL files is optimized for large datasets. The vectors are stored to guarantee alignment for vector intrinsics after memory map. The package is built on top of libMVL, which can be used as a standalone C library. libMVL has simple C API making it easy to interchange datasets with outside programs. Large MVL datasets are distributed via Academic Torrents <https://academictorrents.com/collection/mvl-datasets>.

Vladimir Dergachev

RMVL

Mappable Vector Library for Handling Large Datasets

mvl2R function

<dl><dt>obj</dt>
<dd>- MVL object retrieved by subscription of MVL library or other objects</dd>
<dt>raw</dt>
<dd>- request to return data in raw format when it does not map exactly to R data types.</dd></dl>

Arguments

Make sure the object is fully converted to its R representation — mvl2R

<dl>

<dt>obj</dt>
<dd>- MVL object retrieved by subscription of MVL library or other objects</dd>


<dt>raw</dt>
<dd>- request to return data in raw format when it does not map exactly to R data types.</dd>

</dl>

mvl2R: Make sure the object is fully converted to its R representation

Description

Usage

Value

Arguments