Quick start for `Rcollectl`

library("Rcollectl")

Collectl will perform measurements on system resource consumption of various types. We provide a demonstration output with the package:

lk = cl_parse(system.file("demotab/demo_1123.tab.gz", package="Rcollectl"))
dim(lk)
#> [1] 478  71
attr(lk, "meta")
#>  [1] "################################################################################"
#>  [2] "# Collectl:   V4.3.1-1  HiRes: 1  Options: -scdnm -P -f./col2.txt "              
#>  [3] "# Host:       stvjc-XPS-13-9300  DaemonOpts: "                                   
#>  [4] "# Booted:     1606052236.57 [20201122-08:37:16]"                                 
#>  [5] "# Distro:     debian bullseye/sid, Ubuntu 20.04.1 LTS  Platform: "               
#>  [6] "# Date:       20201123-144054  Secs: 1606160454 TZ: -0500"                       
#>  [7] "# SubSys:     cdnm Options:  Interval: 1 NumCPUs: 8 [HYPER] NumBud: 0 Flags: i"  
#>  [8] "# Filters:    NfsFilt:  EnvFilt:  TcpFilt: ituc"                                 
#>  [9] "# HZ:         100  Arch: x86_64-linux-gnu-thread-multi PageSize: 4096"           
#> [10] "# Cpu:        GenuineIntel Speed(MHz): 1745.513 Cores: 4  Siblings: 8 Nodes: 1"  
#> [11] "# Kernel:     5.4.0-54-generic  Memory: 15969160 kB  Swap: 2097148 kB"           
#> [12] "# NumDisks:   1 DiskNames: nvme0n1"                                              
#> [13] "# NumNets:    4 NetNames: lo:?? enxc03ebaccccfd:100 docker0:?? wlp0s20f3:??"     
#> [14] "################################################################################"
lk[1:5,1:5]
#>      #Date     Time CPU_User% CPU_Nice% CPU_Sys%
#> 1 20201123 14:40:56         2         0        1
#> 2 20201123 14:40:57         1         0        0
#> 3 20201123 14:40:58         1         0        0
#> 4 20201123 14:40:59         2         0        0
#> 5 20201123 14:41:00         3         0        1

plot_usage(lk)

From this display, we can see that about a burst of network activity around 14:43 is followed by consumption of CPU, memory, and disk resources. The % CPU active never exceeds 30, memory consumption started relatively high when sampling began, growing to about 15.5 GB. and 250MB were written to disk over the entire interval.

To generate a display like this, we use commands shown below:

id = cl_start([target file prefix])
[use R until task to be measured is complete]
cl_stop(id)
usage_df = cl_parse(dir(patt=[target file prefix]))
# analyze or filter the usage_df (for example, to trim away
# time related to task delay or delay of `cl_stop`
plot_usage(usage_df)

Reproducibility

The Rcollectl package (Carey, 2020) was made possible thanks to:

R (R Core Team, 2020)
BiocStyle (Oleś, Morgan, and Huber, 2020)
knitcitations (Boettiger, 2019)
knitr (Xie, 2020)
rmarkdown (Allaire, Xie, McPherson, Luraschi, et al., 2020)
sessioninfo (Csárdi, core, Wickham, Chang, et al., 2018)
testthat (Wickham, 2011)

This package was developed using biocthis.

Code for creating the vignette

## Create the vignette
library("rmarkdown")
system.time(render("Rcollectl.Rmd", "BiocStyle::html_document"))

## Extract the R code
library("knitr")
knit("Rcollectl.Rmd", tangle = TRUE)

## Clean up
file.remove("Rcollectl.bib")
#> [1] TRUE

Date the vignette was generated.

#> [1] "2021-01-04 09:45:14 EST"

Wallclock time spent generating the vignette.

#> Time difference of 1.622 secs

R session information.

#> ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
#>  setting  value                                      
#>  version  R version 4.0.2 Patched (2020-07-19 r78892)
#>  os       Ubuntu 20.04 LTS (fossa-melisa X20)        
#>  system   x86_64, linux-gnu                          
#>  ui       X11                                        
#>  language (EN)                                       
#>  collate  en_US.UTF-8                                
#>  ctype    en_US.UTF-8                                
#>  tz       America/New_York                           
#>  date     2021-01-04                                 
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────
#>  package       * version date       lib source        
#>  assertthat      0.2.1   2019-03-21 [2] CRAN (R 4.0.2)
#>  BiocManager     1.30.10 2019-11-16 [2] CRAN (R 4.0.2)
#>  BiocStyle     * 2.18.1  2020-11-24 [2] Bioconductor  
#>  bookdown        0.21    2020-10-13 [2] CRAN (R 4.0.2)
#>  cli             2.2.0   2020-11-20 [2] CRAN (R 4.0.2)
#>  colorspace      2.0-0   2020-11-11 [2] CRAN (R 4.0.2)
#>  crayon          1.3.4   2017-09-16 [2] CRAN (R 4.0.2)
#>  desc            1.2.0   2018-05-01 [2] CRAN (R 4.0.2)
#>  digest          0.6.27  2020-10-24 [2] CRAN (R 4.0.2)
#>  dplyr           1.0.2   2020-08-18 [2] CRAN (R 4.0.2)
#>  ellipsis        0.3.1   2020-05-15 [2] CRAN (R 4.0.2)
#>  evaluate        0.14    2019-05-28 [2] CRAN (R 4.0.2)
#>  fansi           0.4.1   2020-01-08 [2] CRAN (R 4.0.2)
#>  farver          2.0.3   2020-01-16 [2] CRAN (R 4.0.2)
#>  fs              1.5.0   2020-07-31 [2] CRAN (R 4.0.2)
#>  generics        0.1.0   2020-10-31 [2] CRAN (R 4.0.2)
#>  ggplot2         3.3.2   2020-06-19 [2] CRAN (R 4.0.2)
#>  glue            1.4.2   2020-08-27 [2] CRAN (R 4.0.2)
#>  gtable          0.3.0   2019-03-25 [2] CRAN (R 4.0.2)
#>  htmltools       0.5.0   2020-06-16 [2] CRAN (R 4.0.2)
#>  httr            1.4.2   2020-07-20 [2] CRAN (R 4.0.2)
#>  jsonlite        1.7.2   2020-12-09 [2] CRAN (R 4.0.2)
#>  knitcitations * 1.0.10  2019-09-15 [2] CRAN (R 4.0.2)
#>  knitr           1.30    2020-09-22 [2] CRAN (R 4.0.2)
#>  labeling        0.4.2   2020-10-20 [2] CRAN (R 4.0.2)
#>  lifecycle       0.2.0   2020-03-06 [2] CRAN (R 4.0.2)
#>  lubridate       1.7.9.2 2020-11-13 [2] CRAN (R 4.0.2)
#>  magrittr        2.0.1   2020-11-17 [2] CRAN (R 4.0.2)
#>  memoise         1.1.0   2017-04-21 [2] CRAN (R 4.0.2)
#>  munsell         0.5.0   2018-06-12 [2] CRAN (R 4.0.2)
#>  pillar          1.4.7   2020-11-20 [2] CRAN (R 4.0.2)
#>  pkgconfig       2.0.3   2019-09-22 [2] CRAN (R 4.0.2)
#>  pkgdown         1.6.1   2020-09-12 [2] CRAN (R 4.0.2)
#>  plyr            1.8.6   2020-03-03 [2] CRAN (R 4.0.2)
#>  processx        3.4.5   2020-11-30 [2] CRAN (R 4.0.2)
#>  ps              1.5.0   2020-12-05 [2] CRAN (R 4.0.2)
#>  purrr           0.3.4   2020-04-17 [2] CRAN (R 4.0.2)
#>  R6              2.5.0   2020-10-28 [2] CRAN (R 4.0.2)
#>  ragg            0.4.0   2020-10-05 [2] CRAN (R 4.0.2)
#>  Rcollectl     * 0.0.11  2021-01-04 [1] Bioconductor  
#>  Rcpp            1.0.5   2020-07-06 [2] CRAN (R 4.0.2)
#>  RefManageR      1.3.0   2020-11-13 [2] CRAN (R 4.0.2)
#>  rlang           0.4.9   2020-11-26 [2] CRAN (R 4.0.2)
#>  rmarkdown       2.6     2020-12-14 [2] CRAN (R 4.0.2)
#>  rprojroot       2.0.2   2020-11-15 [2] CRAN (R 4.0.2)
#>  scales          1.1.1   2020-05-11 [2] CRAN (R 4.0.2)
#>  sessioninfo   * 1.1.1   2018-11-05 [2] CRAN (R 4.0.2)
#>  stringi         1.5.3   2020-09-09 [2] CRAN (R 4.0.2)
#>  stringr         1.4.0   2019-02-10 [2] CRAN (R 4.0.2)
#>  systemfonts     0.3.2   2020-09-29 [2] CRAN (R 4.0.2)
#>  textshaping     0.2.1   2020-11-13 [2] CRAN (R 4.0.2)
#>  tibble          3.0.4   2020-10-12 [2] CRAN (R 4.0.2)
#>  tidyselect      1.1.0   2020-05-11 [2] CRAN (R 4.0.2)
#>  vctrs           0.3.6   2020-12-17 [2] CRAN (R 4.0.2)
#>  withr           2.3.0   2020-09-22 [2] CRAN (R 4.0.2)
#>  xfun            0.19    2020-10-30 [2] CRAN (R 4.0.2)
#>  xml2            1.3.2   2020-04-23 [2] CRAN (R 4.0.2)
#>  yaml            2.2.1   2020-02-01 [2] CRAN (R 4.0.2)
#> 
#> [1] /tmp/RtmpFuUmIk/temp_libpath1dc9e309620e5
#> [2] /home/stvjc/R-4-0-dist/lib/R/library

Bibliography

This vignette was generated using BiocStyle (Oleś, Morgan, and Huber, 2020) with knitr (Xie, 2020) and rmarkdown (Allaire, Xie, McPherson, Luraschi, et al., 2020) running behind the scenes.

Citations made with knitcitations (Boettiger, 2019).

[1] J. Allaire, Y. Xie, J. McPherson, J. Luraschi, et al. rmarkdown: Dynamic Documents for R. R package version 2.6. 2020. <URL: https://github.com/rstudio/rmarkdown>.

[2] C. Boettiger. knitcitations: Citations for ‘Knitr’ Markdown Files. R package version 1.0.10. 2019. <URL: https://CRAN.R-project.org/package=knitcitations>.

[3] V. Carey. Rcollectl: What the Package Does (One Line, Title Case). R package version 0.0.11. 2020. <URL: https://github.com/vjcitn/Rcollectl>.

[4] G. Csárdi, R. core, H. Wickham, W. Chang, et al. sessioninfo: R Session Information. R package version 1.1.1. 2018. <URL: https://CRAN.R-project.org/package=sessioninfo>.

[5] A. Oleś, M. Morgan, and W. Huber. BiocStyle: Standard styles for vignettes and other Bioconductor documents. R package version 2.18.1. 2020. <URL: https://github.com/Bioconductor/BiocStyle>.

[6] R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria, 2020. <URL: https://www.R-project.org/>.

[7] H. Wickham. “testthat: Get Started with Testing”. In: The R Journal 3 (2011), pp. 5-10. <URL: https://journal.r-project.org/archive/2011-1/RJournal_2011-1_Wickham.pdf>.

[8] Y. Xie. knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.30. 2020. <URL: https://yihui.org/knitr/>.

Rcollectl

Vince Carey

4 January 2021

Quick start for `Rcollectl`

Reproducibility

Bibliography

Rcollectl

Vince Carey

4 January 2021

Quick start for Rcollectl

Reproducibility

Bibliography

Quick start for `Rcollectl`