From josh.m.ulrich at gmail.com  Mon Jul 23 14:15:26 2012
From: josh.m.ulrich at gmail.com (Joshua Ulrich)
Date: Mon, 23 Jul 2012 07:15:26 -0500
Subject: [Rd] Reading many large files causes R to crash - Possible Bug
 in R 2.15.1 64-bit Ubuntu
In-Reply-To: <002d01cd6895$dbef6ed0$93ce4c70$@gmail.com>
References: <000001cd6843$bf5700a0$3e0501e0$@gmail.com>
	<500C66F9.5050503@gmail.com>
	<002d01cd6895$dbef6ed0$93ce4c70$@gmail.com>
Message-ID: <CAPPM_gS=a-XoYT3-zUttsQpdqg3KgJnZY172ekGvbyGUk6mGPA@mail.gmail.com>

David,

You still haven't provided a reproducible example.  As Duncan already
said, "if you don't post code that allows us to reproduce the crash,
it's really unlikely that we'll be able to fix it."

And R-devel is not the appropriate venue to discuss this if it's truly
an issue with xts/zoo.

Best,
--
Joshua Ulrich  |  about.me/joshuaulrich
FOSS Trading  |  www.fosstrading.com


On Mon, Jul 23, 2012 at 12:41 AM, David Terk <david.terk at gmail.com> wrote:
> Looks like the call to:
>
> dat.i <- to.period(dat.i, period=per, k=subper, name=NULL)
>
> If what is causing the issue.  If variable name is not set, or set to any
> value other than NULL.  Than no hang occurs.
>
> -----Original Message-----
> From: David Terk [mailto:david.terk at gmail.com]
> Sent: Monday, July 23, 2012 1:25 AM
> To: 'Duncan Murdoch'
> Cc: 'r-devel at r-project.org'
> Subject: RE: [Rd] Reading many large files causes R to crash - Possible Bug
> in R 2.15.1 64-bit Ubuntu
>
> I've isolated the bug.  When the seg fault was produced there was an error
> that memory had not been mapped.  Here is the odd part of the bug.  If you
> comment out certain code and get a full run than comment in the code which
> is causing the problem it will actually run.   So I think it is safe to
> assume something wrong is taking place with memory allocation.  Example.
> While testing, I have been able to get to a point where the code will run.
> But if I reboot the machine and try again, the code will not run.
>
> The bug itself is happening somewhere in XTS or ZOO.  I will gladly upload
> the data files.  It is happening on the 10th data file which is only 225k
> lines in size.
>
> Below is the simplified code.  The call to either
>
> dat.i <- to.period(dat.i, period=per, k=subper, name=NULL)
> index(dat.i) <- index(to.period(templateTimes, period=per, k=subper))
>
> is what is causing R to hang or crash.  I have been able to replicate this
> on Windows 7 64 bit and Ubuntu 64 bit.  Seems easiest to consistently
> replicate from R Studio.
>
> The code below will consistently replicate when the appropriate files are
> used.
>
> parseTickDataFromDir = function(tickerDir, per, subper) {
>   tickerAbsFilenames = list.files(tickerDir,full.names=T)
>   tickerNames = list.files(tickerDir,full.names=F)
>   tickerNames = gsub("_[a-zA-Z0-9].csv","",tickerNames)
>   pb <- txtProgressBar(min = 0, max = length(tickerAbsFilenames), style = 3)
>
>   for(i in 1:length(tickerAbsFilenames)) {
>     dat.i = parseTickData(tickerAbsFilenames[i])
>     dates <- unique(substr(as.character(index(dat.i)), 1,10))
>     times <- rep("09:30:00", length(dates))
>     openDateTimes <- strptime(paste(dates, times), "%F %H:%M:%S")
>     templateTimes <- NULL
>
>     for (j in 1:length(openDateTimes)) {
>       if (is.null(templateTimes)) {
>         templateTimes <- openDateTimes[j] + 0:23400
>       } else {
>         templateTimes <- c(templateTimes, openDateTimes[j] + 0:23400)
>       }
>     }
>
>     templateTimes <- as.xts(templateTimes)
>     dat.i <- merge(dat.i, templateTimes, all=T)
>     if (is.na(dat.i[1])) {
>       dat.i[1] <- -1
>     }
>     dat.i <- na.locf(dat.i)
>         dat.i <- to.period(dat.i, period=per, k=subper, name=NULL)
>         index(dat.i) <- index(to.period(templateTimes, period=per,
> k=subper))
>     setTxtProgressBar(pb, i)
>   }
>   close(pb)
> }
>
> parseTickData <- function(inputFile) {
>   DAT.list <- scan(file=inputFile,
> sep=",",skip=1,what=list(Date="",Time="",Close=0,Volume=0),quiet=T)
>   index <- as.POSIXct(paste(DAT.list$Date,DAT.list$Time),format="%m/%d/%Y
> %H:%M:%S")
>   DAT.xts <- xts(DAT.list$Close,index)
>   DAT.xts <- make.index.unique(DAT.xts)
>   return(DAT.xts)
> }
>
> DATTick <- parseTickDataFromDir(tickerDirSecond, "seconds",10)
>
> -----Original Message-----
> From: Duncan Murdoch [mailto:murdoch.duncan at gmail.com]
> Sent: Sunday, July 22, 2012 4:48 PM
> To: David Terk
> Cc: r-devel at r-project.org
> Subject: Re: [Rd] Reading many large files causes R to crash - Possible Bug
> in R 2.15.1 64-bit Ubuntu
>
> On 12-07-22 3:54 PM, David Terk wrote:
>> I am reading several hundred files.  Anywhere from 50k-400k in size.
>> It appears that when I read these files with R 2.15.1 the process will
>> hang or seg fault on the scan() call.  This does not happen on R 2.14.1.
>
> The code below doesn't do anything other than define a couple of functions.
> Please simplify it to code that creates a file (or multiple files), reads it
> or them, and shows a bug.
>
> If you can't do that, then gradually add the rest of the stuff from these
> functions into the mix until you figure out what is really causing the bug.
>
> If you don't post code that allows us to reproduce the crash, it's really
> unlikely that we'll be able to fix it.
>
> Duncan Murdoch
>
>>
>>
>>
>> This is happening on the precise build of Ubuntu.
>>
>>
>>
>> I have included everything, but the issue appears to be when
>> performing the scan in the method parseTickData.
>>
>>
>>
>> Below is the code.  Hopefully this is the right place to post.
>>
>>
>>
>> parseTickDataFromDir = function(tickerDir, per, subper, fun) {
>>
>>    tickerAbsFilenames = list.files(tickerDir,full.names=T)
>>
>>    tickerNames = list.files(tickerDir,full.names=F)
>>
>>    tickerNames = gsub("_[a-zA-Z0-9].csv","",tickerNames)
>>
>>    pb <- txtProgressBar(min = 0, max = length(tickerAbsFilenames),
>> style = 3)
>>
>>
>>
>>    for(i in 1:length(tickerAbsFilenames)) {
>>
>>
>>
>>      # Grab Raw Tick Data
>>
>>      dat.i = parseTickData(tickerAbsFilenames[i])
>>
>>      #Sys.sleep(1)
>>
>>      # Create Template
>>
>>      dates <- unique(substr(as.character(index(dat.i)), 1,10))
>>
>>      times <- rep("09:30:00", length(dates))
>>
>>      openDateTimes <- strptime(paste(dates, times), "%F %H:%M:%S")
>>
>>      templateTimes <- NULL
>>
>>
>>
>>      for (j in 1:length(openDateTimes)) {
>>
>>        if (is.null(templateTimes)) {
>>
>>          templateTimes <- openDateTimes[j] + 0:23400
>>
>>        } else {
>>
>>          templateTimes <- c(templateTimes, openDateTimes[j] + 0:23400)
>>
>>        }
>>
>>      }
>>
>>
>>
>>      # Convert templateTimes to XTS, merge with data and convert NA's
>>
>>      templateTimes <- as.xts(templateTimes)
>>
>>      dat.i <- merge(dat.i, templateTimes, all=T)
>>
>>      # If there is no data in the first print, we will have leading
>> NA's.  So set them to -1.
>>
>>      # Since we do not want these values removed by to.period
>>
>>      if (is.na(dat.i[1])) {
>>
>>        dat.i[1] <- -1
>>
>>      }
>>
>>      # Fix remaining NA's
>>
>>      dat.i <- na.locf(dat.i)
>>
>>      # Convert to desired bucket size
>>
>>      dat.i <- to.period(dat.i, period=per, k=subper, name=NULL)
>>
>>      # Always use templated index, otherwise merge fails with other
>> symbols
>>
>>      index(dat.i) <- index(to.period(templateTimes, period=per,
>> k=subper))
>>
>>      # If there was missing data at open, set close to NA
>>
>>      valsToChange <- which(dat.i[,"Open"] == -1)
>>
>>      if (length(valsToChange) != 0) {
>>
>>        dat.i[valsToChange, "Close"] <- NA
>>
>>      }
>>
>>      if(i == 1) {
>>
>>        DAT = fun(dat.i)
>>
>>      } else {
>>
>>        DAT = merge(DAT,fun(dat.i))
>>
>>      }
>>
>>      setTxtProgressBar(pb, i)
>>
>>    }
>>
>>    close(pb)
>>
>>    colnames(DAT) = tickerNames
>>
>>    return(DAT)
>>
>> }
>>
>>
>>
>> parseTickData <- function(inputFile) {
>>
>>    DAT.list <- scan(file=inputFile,
>> sep=",",skip=1,what=list(Date="",Time="",Close=0,Volume=0),quiet=T)
>>
>>    index <-
>> as.POSIXct(paste(DAT.list$Date,DAT.list$Time),format="%m/%d/%Y
>> %H:%M:%S")
>>
>>    DAT.xts <- xts(DAT.list$Close,index)
>>
>>    DAT.xts <- make.index.unique(DAT.xts)
>>
>>    return(DAT.xts)
>>
>> }
>>
>>
>>
>>
>>
>>
>>       [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-devel at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>
>
> ______________________________________________
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> https://stat.ethz.ch/mailman/listinfo/r-devel



[Rd] Reading many large files causes R to crash - Possible Bug in R 2.15.1 64-bit Ubuntu
Joshua Ulrich