Note that you can shorten #1 to read.csv.sql("out.txt") since your
other arguments are the default values.For the second one, use read.csv.sql, eliminate the arguments that are defaults anyways (should not cause a problem but its error prone) and add an explicit eol= argument since SQLite can have problems with end of line in some cases. Also test out your perl script separately from R first to ensure that it works: test_df <- read.csv.sql(file="3wkoutstatfcst_small.dat", filter="perl parse_3wkout.pl", eol = "\n") SQLite has some known problems with end of line so try it with and without the eol= argument just in case. When I just made up the following gawk example I noticed that I did need to specify the eol= argument. Also I have added a complete example using gawk as Example 13c on the home page just now: http://code.google.com/p/sqldf/#Example_13._read.csv.sql_and_read.csv2.sql On Sat, Feb 6, 2010 at 3:52 PM, Vadlamani, Satish {FLNA} <satish.vadlam...@fritolay.com> wrote: > Gabor: > > I had success with the following. > 1. I created a csv file with a perl script called "out.txt". Then ran the > following successfully > library("sqldf") > test_df <- read.csv.sql(file="out.txt", sql = "select * from file", header = > TRUE, sep = ",", dbname = tempfile()) > > 2. I did not have success with the following. Could you tell me what I may be > doing wrong? I could paste the perl script if necessary. From the perl > script, I am reading the file, creating the csv record and printing each > record one by one and then exiting. > > Thanks. > > Not had success with below.. > #test_df <- read.csv2.sql(file="3wkoutstatfcst_small.dat", sql = "select * > from file", header = TRUE, sep = ",", filter="perl parse_3wkout.pl", dbname = > tempfile()) > test_df > > Error message below: > test_df <- read.csv2.sql(file="3wkoutstatfcst_small.dat", sql = "select * > from file", header = TRUE, sep = ",", filter="perl parse_3wkout.pl", dbname = > tempfile()) > Error in readRegistry(key, maxdepth = 3) : > Registry key 'SOFTWARE\R-core' not found > In addition: Warning messages: > 1: closing unused connection 14 (3wkoutstatfcst_small.dat) > 2: closing unused connection 13 (3wkoutstatfcst_small.dat) > 3: closing unused connection 11 (3wkoutstatfcst_small.dat) > 4: closing unused connection 9 (3wkoutstatfcst_small.dat) > 5: closing unused connection 3 (3wkoutstatfcst_small.dat) >> test_df <- read.csv2.sql(file="3wkoutstatfcst_small.dat", sql = "select * >> from file", header = TRUE, sep = ",", filter="perl parse_3wkout.pl", dbname >> = tempfile()) > Error in readRegistry(key, maxdepth = 3) : > Registry key 'SOFTWARE\R-core' not found > > -----Original Message----- > From: Gabor Grothendieck [mailto:ggrothendi...@gmail.com] > Sent: Saturday, February 06, 2010 12:14 PM > To: Vadlamani, Satish {FLNA} > Cc: r-help@r-project.org > Subject: Re: [R] Reading large files > > No. > > On Sat, Feb 6, 2010 at 1:01 PM, Vadlamani, Satish {FLNA} > <satish.vadlam...@fritolay.com> wrote: >> Gabor: >> Can I pass colClasses as a vector to read.csv.sql? Thanks. >> Satish >> >> >> -----Original Message----- >> From: Gabor Grothendieck [mailto:ggrothendi...@gmail.com] >> Sent: Saturday, February 06, 2010 9:41 AM >> To: Vadlamani, Satish {FLNA} >> Cc: r-help@r-project.org >> Subject: Re: [R] Reading large files >> >> Its just any Windows batch command string that filters stdin to >> stdout. What the command consists of should not be important. An >> invocation of perl that runs a perl script that filters stdin to >> stdout might look like this: >> read.csv.sql("myfile.dat", filter = "perl myprog.pl") >> >> For an actual example see the source of read.csv2.sql which defaults >> to using a Windows vbscript program as a filter. >> >> On Sat, Feb 6, 2010 at 10:16 AM, Vadlamani, Satish {FLNA} >> <satish.vadlam...@fritolay.com> wrote: >>> Jim, Gabor: >>> Thanks so much for the suggestions where I can use read.csv.sql and embed >>> Perl (or gawk). I just want to mention that I am running on Windows. I am >>> going to read the documentation the filter argument and see if it can take >>> a decent sized Perl script and then use its output as input. >>> >>> Suppose that I write a Perl script that parses this fwf file and creates a >>> CSV file. Can I embed this within the read.csv.sql call? Or, can it only be >>> a statement or something? If you know the answer, please let me know. >>> Otherwise, I will try a few things and report back the results. >>> >>> Thanks again. >>> Saitsh >>> >>> >>> -----Original Message----- >>> From: jim holtman [mailto:jholt...@gmail.com] >>> Sent: Saturday, February 06, 2010 6:16 AM >>> To: Gabor Grothendieck >>> Cc: Vadlamani, Satish {FLNA}; r-help@r-project.org >>> Subject: Re: [R] Reading large files >>> >>> 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 >>> <ggrothendi...@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.vadlam...@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:ggrothendi...@gmail.com] >>>>> Sent: Friday, February 05, 2010 5:16 PM >>>>> To: Vadlamani, Satish {FLNA} >>>>> Cc: r-help@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.vadlam...@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. >>>>>> >>>>>> ______________________________________________ >>>>>> R-help@r-project.org mailing list >>>>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>>>> PLEASE do read the posting guide >>>>>> http://www.R-project.org/posting-guide.html >>>>>> and provide commented, minimal, self-contained, reproducible code. >>>>>> >>>>> >>>> >>>> ______________________________________________ >>>> R-help@r-project.org mailing list >>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>> PLEASE do read the posting guide >>>> http://www.R-project.org/posting-guide.html >>>> 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? >>> >> > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
