Re: [R] big data?

Thu, 07 Aug 2014 10:51:12 -0700

correcting a typo (400 MB, not GB. Thanks to David Winsemius for reporting it). Spencer 

###############



      Thanks to all who replied.  For the record, I will summarize here 
what I tried and what I learned:




      Mike Harwood suggested the ff package.  David Winsemius suggested 
data.table and colbycol.  Peter Langfelder suggested sqldf.




      sqldf::read.csv.sql allowed me to create an SQL command to read a 
column or a subset of the rows of a 400 MB tab-delimited file in roughly 
a minute on a 2.3 GHz dual core machine running Windows 7 with 8 GB RAM. 
 It also read a column of a 1.3 GB file in 4 minutes.  The 
documentation was sufficient to allow me to easily get what I wanted 
with a minimum of effort.




      If I needed to work with these data regularly, I might experiment 
with colbycol and ff:  The documentation suggested to me that these 
packages might allow me to get quicker answers from routine tasks after 
some preprocessing.  Of course, I could also do the preprocessing 
manually with sqldf.



      Thanks, again.
      Spencer


On 8/6/2014 9:39 AM, Mike Harwood wrote:

The read.table.ffdf function in the ff package can read in delimited files
and store them to disk as individual columns.  The ffbase package provides
additional data management and analytic functionality.  I have used these
packages on 15 Gb files of 18 million rows and 250 columns.


On Tuesday, August 5, 2014 1:39:03 PM UTC-5, David Winsemius wrote:


On Aug 5, 2014, at 10:20 AM, Spencer Graves wrote:


      What tools do you like for working with tab delimited text files up

to 1.5 GB (under Windows 7 with 8 GB RAM)?

?data.table::fread


      Standard tools for smaller data sometimes grab all the available

RAM, after which CPU usage drops to 3% ;-)


      The "bigmemory" project won the 2010 John Chambers Award but "is

not available (for R version 3.1.0)".


      findFn("big data", 999) downloaded 961 links in 437 packages. That

contains tools for data PostgreSQL and other formats, but I couldn't find
anything for large tab delimited text files.


      Absent a better idea, I plan to write a function getField to

extract a specific field from the data, then use that to split the data
into 4 smaller files, which I think should be small enough that I can do
what I want.

There is the colbycol package with which I have no experience, but I
understand it is designed to partition data into column sized objects.
#--- from its help file-----
cbc.get.col {colbycol}        R Documentation
Reads a single column from the original file into memory

Description

Function cbc.read.table reads a file, stores it column by column in disk
file and creates a colbycol object. Functioncbc.get.col queries this object
and returns a single column.


      Thanks,
      Spencer

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David Winsemius
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