Hi,
I haven't tried the code yet. Is there a way to parse this data
using R and create bar plots so that each program's 'RAM used'
figures are
grouped together.
So 'uuidd' bars will be together. The data will have about 50 sets. So
if
there are 100 processes each will have about 50 bars.
What is the recommended way to graph these big barplots ? I am looking for
only 'RAM used' figures.
Thanks,
Mohan
Private + Shared = RAM used Program
96.0 KiB + 11.5 KiB = 107.5 KiB uuidd
108.0 KiB + 12.5 KiB = 120.5 KiB klogd
124.0 KiB + 17.0 KiB = 141.0 KiB hidd
116.0 KiB + 30.0 KiB = 146.0 KiB acpid
124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage
144.0 KiB + 15.0 KiB = 159.0 KiB gpm
136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check
---------------------------------------------------------
453.9 MiB
================================ Private + Shared = RAM used Program
96.0 KiB + 11.5 KiB = 107.5 KiB uuidd
108.0 KiB + 12.5 KiB = 120.5 KiB klogd
124.0 KiB + 17.0 KiB = 141.0 KiB hidd
116.0 KiB + 30.0 KiB = 146.0 KiB acpid
124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage
144.0 KiB + 15.0 KiB = 159.0 KiB gpm
136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check
----------------------------------------------------------
453.9 MiB
================================
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Hi For reading data into R you shall look to read.table and similar. For plotting ggplot could handle it. However I wonder if 100 times 50 bars is the way how to present your data. You shall think over what do you want to show to yourself or your audience. Maybe boxplots or scatterplots could be better. Petr> -----Original Message----- > From: r-help-bounces at r-project.org [mailto:r-help-bounces at r- > project.org] On Behalf Of mohan.radhakrishnan at polarisft.com > Sent: Friday, August 30, 2013 1:25 PM > To: r-help at r-project.org > Subject: [R] Memory usage bar plot > > Hi, > I haven't tried the code yet. Is there a way to parse this > data using R and create bar plots so that each program's 'RAM used' > figures are grouped together. > So 'uuidd' bars will be together. The data will have about 50 sets. So > if there are 100 processes each will have about 50 bars. > > What is the recommended way to graph these big barplots ? I am looking > for only 'RAM used' figures. > > > Thanks, > Mohan > > > Private + Shared = RAM used Program > > 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd > 108.0 KiB + 12.5 KiB = 120.5 KiB klogd > 124.0 KiB + 17.0 KiB = 141.0 KiB hidd > 116.0 KiB + 30.0 KiB = 146.0 KiB acpid > 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage > 144.0 KiB + 15.0 KiB = 159.0 KiB gpm > 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check > --------------------------------------------------------- > 453.9 MiB > > ================================> Private + Shared = RAM used Program > > 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd > 108.0 KiB + 12.5 KiB = 120.5 KiB klogd > 124.0 KiB + 17.0 KiB = 141.0 KiB hidd > 116.0 KiB + 30.0 KiB = 146.0 KiB acpid > 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage > 144.0 KiB + 15.0 KiB = 159.0 KiB gpm > 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check > ---------------------------------------------------------- > 453.9 MiB > ================================> > > This e-Mail may contain proprietary and confidential information and is > sent for the intended recipient(s) only. If by an addressing or > transmission error this mail has been misdirected to you, you are > requested to delete this mail immediately. You are also hereby notified > that any use, any form of reproduction, dissemination, copying, > disclosure, modification, distribution and/or publication of this e- > mail message, contents or its attachment other than by its intended > recipient/s is strictly prohibited. > > Visit us at http://www.polarisFT.com > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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.
Hello,
This memory usage should be graphed with time. Are there
examples of scatterplots that can clearly show usage vs time ? This is
for memory leak detection.
Thanks,
Mohan
From: PIKAL Petr <petr.pikal@precheza.cz>
To: "mohan.radhakrishnan@polarisft.com"
<mohan.radhakrishnan@polarisft.com>, "r-help@r-project.org"
<r-help@r-project.org>
Date: 08/30/2013 05:33 PM
Subject: RE: [R] Memory usage bar plot
Hi
For reading data into R you shall look to read.table and similar.
For plotting ggplot could handle it. However I wonder if 100 times 50 bars
is the way how to present your data. You shall think over what do you want
to show to yourself or your audience. Maybe boxplots or scatterplots could
be better.
Petr
> -----Original Message-----
> From: r-help-bounces@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of mohan.radhakrishnan@polarisft.com
> Sent: Friday, August 30, 2013 1:25 PM
> To: r-help@r-project.org
> Subject: [R] Memory usage bar plot
>
> Hi,
> I haven't tried the code yet. Is there a way to parse this
> data using R and create bar plots so that each program's 'RAM
used'
> figures are grouped together.
> So 'uuidd' bars will be together. The data will have about 50 sets.
So
> if there are 100 processes each will have about 50 bars.
>
> What is the recommended way to graph these big barplots ? I am looking
> for only 'RAM used' figures.
>
>
> Thanks,
> Mohan
>
>
> Private + Shared = RAM used Program
>
> 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd
> 108.0 KiB + 12.5 KiB = 120.5 KiB klogd
> 124.0 KiB + 17.0 KiB = 141.0 KiB hidd
> 116.0 KiB + 30.0 KiB = 146.0 KiB acpid
> 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage
> 144.0 KiB + 15.0 KiB = 159.0 KiB gpm
> 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check
> ---------------------------------------------------------
> 453.9 MiB
>
> ================================> Private + Shared = RAM used
Program
>
> 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd
> 108.0 KiB + 12.5 KiB = 120.5 KiB klogd
> 124.0 KiB + 17.0 KiB = 141.0 KiB hidd
> 116.0 KiB + 30.0 KiB = 146.0 KiB acpid
> 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage
> 144.0 KiB + 15.0 KiB = 159.0 KiB gpm
> 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check
> ----------------------------------------------------------
> 453.9 MiB
> ================================>
>
> This e-Mail may contain proprietary and confidential information and is
> sent for the intended recipient(s) only. If by an addressing or
> transmission error this mail has been misdirected to you, you are
> requested to delete this mail immediately. You are also hereby notified
> that any use, any form of reproduction, dissemination, copying,
> disclosure, modification, distribution and/or publication of this e-
> mail message, contents or its attachment other than by its intended
> recipient/s is strictly prohibited.
>
> Visit us at http://www.polarisFT.com
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> 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.
This e-Mail may contain proprietary and confidential information and is sent for
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immediately. You are also hereby notified that any use, any form of
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and/or publication of this e-mail message, contents or its attachment other than
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Here is how to parse the data and put it into groups. Not sure what the 'timing' of each group is since not time information was given. Also not sure is there is an 'MiB' qualifier on the data, but you have the matrix of data which is easy to do with as you want.> input <- readLines(textConnection("+ Private + Shared = RAM used Program + + 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd + 108.0 KiB + 12.5 KiB = 120.5 KiB klogd + 124.0 KiB + 17.0 KiB = 141.0 KiB hidd + 116.0 KiB + 30.0 KiB = 146.0 KiB acpid + 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage + 144.0 KiB + 15.0 KiB = 159.0 KiB gpm + 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check + --------------------------------------------------------- + 453.9 MiB + + ================================+ Private + Shared = RAM used Program + + 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd + 108.0 KiB + 12.5 KiB = 120.5 KiB klogd + 124.0 KiB + 17.0 KiB = 141.0 KiB hidd + 116.0 KiB + 30.0 KiB = 146.0 KiB acpid + 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage + 144.0 KiB + 15.0 KiB = 159.0 KiB gpm + 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check + ---------------------------------------------------------- + 453.9 MiB + ================================="))> > # keep only the data > input <- input[grepl('=', input)] > > # separate into groups > grps <- split(input, cumsum(grepl("= RAM", input))) > > # parse the data (not sure if there is also 'MiB') > parsed <- lapply(grps, function(.grp){+ # parse ignoring first and last lines + .data <- sub(".*= ([^ ]+) ([^ ]+)\\s+(.*)", "\\1 \\2 \\3" + , .grp[2:(length(.grp) - 1L)] + ) + # return matrix + do.call(rbind, strsplit(.data, ' ')) + })> > > > parsed$`1` [,1] [,2] [,3] [1,] "107.5" "KiB" "uuidd" [2,] "120.5" "KiB" "klogd" [3,] "141.0" "KiB" "hidd" [4,] "146.0" "KiB" "acpid" [5,] "153.5" "KiB" "hald-addon-storage" [6,] "159.0" "KiB" "gpm" [7,] "162.5" "KiB" "pam_timestamp_check" $`2` [,1] [,2] [,3] [1,] "107.5" "KiB" "uuidd" [2,] "120.5" "KiB" "klogd" [3,] "141.0" "KiB" "hidd" [4,] "146.0" "KiB" "acpid" [5,] "153.5" "KiB" "hald-addon-storage" [6,] "159.0" "KiB" "gpm" [7,] "162.5" "KiB" "pam_timestamp_check">Jim Holtman Data Munger Guru What is the problem that you are trying to solve? Tell me what you want to do, not how you want to do it. On Fri, Aug 30, 2013 at 7:24 AM, <mohan.radhakrishnan at polarisft.com> wrote:> Hi, > I haven't tried the code yet. Is there a way to parse this data > using R and create bar plots so that each program's 'RAM used' figures are > grouped together. > So 'uuidd' bars will be together. The data will have about 50 sets. So if > there are 100 processes each will have about 50 bars. > > What is the recommended way to graph these big barplots ? I am looking for > only 'RAM used' figures. > > > Thanks, > Mohan > > > Private + Shared = RAM used Program > > 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd > 108.0 KiB + 12.5 KiB = 120.5 KiB klogd > 124.0 KiB + 17.0 KiB = 141.0 KiB hidd > 116.0 KiB + 30.0 KiB = 146.0 KiB acpid > 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage > 144.0 KiB + 15.0 KiB = 159.0 KiB gpm > 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check > --------------------------------------------------------- > 453.9 MiB > > ================================> Private + Shared = RAM used Program > > 96.0 KiB + 11.5 KiB = 107.5 KiB uuidd > 108.0 KiB + 12.5 KiB = 120.5 KiB klogd > 124.0 KiB + 17.0 KiB = 141.0 KiB hidd > 116.0 KiB + 30.0 KiB = 146.0 KiB acpid > 124.0 KiB + 29.5 KiB = 153.5 KiB hald-addon-storage > 144.0 KiB + 15.0 KiB = 159.0 KiB gpm > 136.0 KiB + 26.5 KiB = 162.5 KiB pam_timestamp_check > ---------------------------------------------------------- > 453.9 MiB > ================================> > > This e-Mail may contain proprietary and confidential information and is sent for the intended recipient(s) only. If by an addressing or transmission error this mail has been misdirected to you, you are requested to delete this mail immediately. You are also hereby notified that any use, any form of reproduction, dissemination, copying, disclosure, modification, distribution and/or publication of this e-mail message, contents or its attachment other than by its intended recipient/s is strictly prohibited. > > Visit us at http://www.polarisFT.com > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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.