mvl_object_stats

Provide detailed information on stored MVL object without retrieving it

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

mvl_object_stats function

<dl><dt>MVLHANDLE</dt>
<dd>either a handle provided by mvl_open() or an MVL object such as produced by indexing operators</dd>
<dt>offset</dt>
<dd>offset to the object which properties are to be retrieved</dd>
<dt>scan</dt>
<dd>scan vector element to obtain additional statistics</dd></dl>

Arguments

Return MVL object properties — mvl_object_stats

<dl>

<dt>MVLHANDLE</dt>
<dd>either a handle provided by mvl_open() or an MVL object such as produced by indexing operators</dd>


<dt>offset</dt>
<dd>offset to the object which properties are to be retrieved</dd>


<dt>scan</dt>
<dd>scan vector element to obtain additional statistics</dd>

</dl>

mvl_object_stats: Return MVL object properties

Description

Usage

Value

Arguments

Details