On Fri, Oct 15, 2010 at 6:14 AM, Chris Howden
ch...@trickysolutions.com.au wrote:
Thanks for the advice Gabor,
I was indeed not starting and finishing with sqldf(). Which was why it was
not working for me. Please forgive a blatantly obvious mistake.
I have tried what U suggested and
7878
ch...@trickysolutions.com.au
-Original Message-
From: Gabor Grothendieck [mailto:ggrothendi...@gmail.com]
Sent: Friday, 15 October 2010 1:03 PM
To: Chris Howden
Cc: r-help@r-project.org
Subject: Re: [R] merging and working with BIG data sets. Is sqldf the best
way??
On Thu, Oct 14
...@gmail.com]
Sent: Thursday, 14 October 2010 9:02 AM
To: Chris Howden
Cc: r-help@r-project.org
Subject: Re: [R] merging and working with BIG data sets. Is sqldf the best
way??
On Tue, Oct 12, 2010 at 2:39 AM, Chris Howden
ch...@trickysolutions.com.au wrote:
I’m working with some very big datasets
On Thu, Oct 14, 2010 at 10:56 PM, Chris Howden
ch...@trickysolutions.com.au wrote:
Thanks for the suggestion and code Gabor,
I've tried creating 2 indices:
1) just for the variable I intend to merge on
2) on the entire data set I am merging (which I think is the one I should
be using??)
On Tue, Oct 12, 2010 at 2:39 AM, Chris Howden
ch...@trickysolutions.com.au wrote:
I’m working with some very big datasets (each dataset has 11 million rows
and 2 columns). My first step is to merge all my individual data sets
together (I have about 20)
I’m using the following command from
Hi everyone,
Im working with some very big datasets (each dataset has 11 million rows
and 2 columns). My first step is to merge all my individual data sets
together (I have about 20)
Im using the following command from sqldf
data1 - sqldf(select A.*, B.* from A inner join B
Chris Howden wrote:
Hi everyone,
I’m working with some very big datasets (each dataset has 11 million rows
and 2 columns). My first step is to merge all my individual data sets
together (I have about 20)
I’m using the following command from sqldf
data1 - sqldf(select A.*, B.*
I can't speak for ff and filehash, but bigmemory's data structure
doesn't allow clever merges (for actually good reasons). However,
it is still probably less painful (and faster) than other options,
though we don't implement it: we leave it to the user because details
may vary depending on the
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