[R] Reading large files

[jim holtman]

In perl the 'unpack' command makes it very easy to parse fixed fielded data.

On Fri, Feb 5, 2010 at 9:09 PM, Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:
> Note that the filter= argument on read.csv.sql can be used to pass the
> input through a filter written in perl, [g]awk or other language.
> For example: read.csv.sql(..., filter = "gawk -f myfilter.awk")
>
> gawk has the FIELDWIDTHS variable for automatically parsing fixed
> width fields, e.g.
> http://www.delorie.com/gnu/docs/gawk/gawk_44.html
> making this very easy but perl or whatever you are most used to would
> be fine too.
>
> On Fri, Feb 5, 2010 at 8:50 PM, Vadlamani, Satish {FLNA}
> <SATISH.VADLAMANI at fritolay.com> wrote:
>> Hi Gabor:
>> Thanks. My files are all in fixed width format. They are a lot of them. It would take me some effort to convert them to CSV. I guess this cannot be avoided? I can write some Perl scripts to convert fixed width format to CSV format and then start with your suggestion. Could you let me know your thoughts on the approach?
>> Satish
>>
>>
>> -----Original Message-----
>> From: Gabor Grothendieck [mailto:ggrothendieck at gmail.com]
>> Sent: Friday, February 05, 2010 5:16 PM
>> To: Vadlamani, Satish {FLNA}
>> Cc: r-help at r-project.org
>> Subject: Re: [R] Reading large files
>>
>> If your problem is just how long it takes to load the file into R try
>> read.csv.sql in the sqldf package.  A single read.csv.sql call can
>> create an SQLite database and table layout for you, read the file into
>> the database (without going through R so R can't slow this down),
>> extract all or a portion into R based on the sql argument you give it
>> and then remove the database.  See the examples on the home page:
>> http://code.google.com/p/sqldf/#Example_13._read.csv.sql_and_read.csv2.sql
>>
>> On Fri, Feb 5, 2010 at 2:11 PM, Satish Vadlamani
>> <SATISH.VADLAMANI at fritolay.com> wrote:
>>>
>>> Matthew:
>>> If it is going to help, here is the explanation. I have an end state in
>>> mind. It is given below under "End State" header. In order to get there, I
>>> need to start somewhere right? I started with a 850 MB file and could not
>>> load in what I think is reasonable time (I waited for an hour).
>>>
>>> There are references to 64 bit. How will that help? It is a 4GB RAM machine
>>> and there is no paging activity when loading the 850 MB file.
>>>
>>> I have seen other threads on the same types of questions. I did not see any
>>> clear cut answers or errors that I could have been making in the process. If
>>> I am missing something, please let me know. Thanks.
>>> Satish
>>>
>>>
>>> End State
>>>> Satish wrote: "at one time I will need to load say 15GB into R"
>>>
>>>
>>> -----
>>> Satish Vadlamani
>>> --
>>> View this message in context: http://n4.nabble.com/Reading-large-files-tp1469691p1470667.html
>>> Sent from the R help mailing list archive at Nabble.com.
>>>
>>> ______________________________________________
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>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>
>
> ______________________________________________
> R-help at r-project.org mailing list
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> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?