laf-class

A Large File object. This is a reference to a dataset on disk. The data
itself is not read into memory (yet). This can be done by the methods for
blockwise processing or by indexing the object as a data.frame. The code has
been optimised for fast access.

Methods for fast access to large ASCII files.  Currently the
following file formats are supported: comma separated format (CSV) and fixed
width format. It is assumed that the files are too large to fit into memory,
although the package can also be used to efficiently access files that do
fit into memory. Methods are provided to access and process files blockwise.
Furthermore, an opened file can be accessed as one would an ordinary
data.frame. The LaF vignette gives an overview of the functionality
provided.

Jan der Laan

Fast Access to Large ASCII Files

Jan van der Laan

laf-class function

Objects can be created by opening a file using one of the methods 
<code>laf_open_csv</code> or <code>laf_open_fwf</code>. These create a 
reference to either a CSV file or a fixed width file. The data in these
files can either be accessed using blockwise operations using the methods
<code>begin</code>, <code>next_block</code> and <code>goto</code>. Or by indexing the laf 
object as you would a data.frame. In the following example a CSV file
is opened and its first column (of type integer) is read into memory:<pre><code>
 laf &lt;- laf_open_csv("file.csv", column_types=c("integer", "double"))
 data &lt;- laf[ , 1]
 </code></pre>

Objects from the Class

Large File object — laf-class

Objects can be created by opening a file using one of the methods 
<code>laf_open_csv</code> or <code>laf_open_fwf</code>. These create a 
reference to either a CSV file or a fixed width file. The data in these
files can either be accessed using blockwise operations using the methods
<code>begin</code>, <code>next_block</code> and <code>goto</code>. Or by indexing the laf 
object as you would a data.frame. In the following example a CSV file
is opened and its first column (of type integer) is read into memory:<pre><code>
 laf &lt;- laf_open_csv("file.csv", column_types=c("integer", "double"))
 data &lt;- laf[ , 1]
 </code></pre>

laf-class: Large File object

Description

Arguments

Objects from the Class