Data

Tools

Indexes

Applications

Experiments

Open Source Science

BatchJobs

BatchJobs: Batch computing with R

https://github.com/tudo-r/batchjobs

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 12 committers (16.7%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.7%) to scientific vocabulary

Keywords from Contributors

reproducibility mlr model-based-optimization mlrmbo hyperparameter-optimization black-box-optimization bayesian-optimization survival-analysis stacking predictive-modeling
Last synced: 11 months ago · JSON representation

Repository

BatchJobs: Batch computing with R

Basic Info
  • Host: GitHub
  • Owner: tudo-r
  • License: other
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 1.96 MB
Statistics
  • Stars: 85
  • Watchers: 14
  • Forks: 20
  • Open Issues: 48
  • Releases: 0
Created over 12 years ago · Last pushed over 4 years ago
Metadata Files
Readme License

README.md

BatchJobs

CRAN_Status_Badge CRAN Downloads Build Status Build status Coverage Status

NOTE: Development continues in the new package batchtools

Provides Map, Reduce and Filter variants to generate jobs on batch computing systems like PBS/Torque, LSF and Sun Grid Engine. Multicore and SSH systems are also supported.

  • Official CRAN release site: https://cran.r-project.org/package=BatchJobs

  • R Documentation in HTML: https://www.rdocumentation.org/packages/BatchJobs

  • Run this in R to install the current GitHub version: splus devtools::install_github("tudo-r/BatchJobs")

  • Further installation instructions

If you use the package, please cite it and star it here

JSS link: https://www.jstatsoft.org/v64/i11

``` To cite BatchJobs or BatchExperiments in publications use:

Bernd Bischl, Michel Lang, Olaf Mersmann, Jörg Rahnenführer, Claus Weihs (2015). BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments. Journal of Statistical Software, 64(11), 1-25. URL https://www.jstatsoft.org/v64/i11/.

A BibTeX entry for LaTeX users is

@Article{, title = {{BatchJobs} and {BatchExperiments}: Abstraction Mechanisms for Using {R} in Batch Environments}, author = {Bernd Bischl and Michel Lang and Olaf Mersmann and J{\"o}rg Rahnenf{\"u}hrer and Claus Weihs}, journal = {Journal of Statistical Software}, year = {2015}, volume = {64}, number = {11}, pages = {1--25}, url = {https://www.jstatsoft.org/v64/i11/}, } ```

Core features

  • Create, submit and control R jobs on batch systems
  • Provides the functional programming tools Map, Reduce and Filter to operate on the cluster
  • Supported systems include Torque/PBS, SGE, SLURM, OpenLava and LSF
  • Support for makeshift SSH clusters and local (multicore) execution
  • Convenient collection and aggregation of results
  • Further Map and Reduce results from previous jobs as batch jobs
  • Optional mail sending using sendmailR after job completion
  • Query status of jobs and display log files inside R
  • Possibility to write your own simple cluster interface if your architecture is not supported
  • BatchExperiments extends this package with functionality required for comprehensive computer experiments and simulation studies.

Configuration

A fresh installation defaults to a local execution mode. Proceed to Configuration to set up cluster execution. The package also allows a few R options to be set, see here.

Documentation

Probably the best way to get started in 5 minutes is to read our paper or Henrik Bengtsson's intro slides. If you have more time, read our technical report. For more detailed information on the functions consult the R documentation We also provide a FAQ in our wiki. And here is a nice intro article for BatchJobs with Torque on R Bloggers.

We also have a mailing list.

Owner

  • Name: TU Dortmund - R
  • Login: tudo-r
  • Kind: organization
  • Location: Dortmund

R related repositories from the Statistics Department of the TU Dortmund

GitHub Events

Total
Last Year

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 1,129
  • Total Committers: 12
  • Avg Commits per committer: 94.083
  • Development Distribution Score (DDS): 0.431
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
mllg m****g@g****m 642
berndbischl b****l@g****t 431
hb hb@a****g 15
Michel Lang l****g@s****e 13
Bernd Bischl y****u@e****m 12
openlava o****a@n****) 4
Dirk Surmann s****n@s****e 3
Jakob Richter c****e@j****e 3
Martina Feilke d****p@l****e 2
gmbecker b****l@g****m 2
Gábor Csárdi c****r@g****m 1
ReadmeCritic f****t@g****m 1
Committer Domains (Top 20 + Academic)
statistik.tu-dortmund.de: 2 gene.com: 1 lxa191.cos.lrz.de: 1 jakob-r.de: 1 node3.(none): 1 aroma-project.org: 1 gmx.net: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 85
  • Total pull requests: 15
  • Average time to close issues: 4 months
  • Average time to close pull requests: about 11 hours
  • Total issue authors: 33
  • Total pull request authors: 12
  • Average comments per issue: 3.38
  • Average comments per pull request: 2.0
  • Merged pull requests: 8
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • HenrikBengtsson (18)
  • berndbischl (14)
  • renozao (4)
  • vjcitn (4)
  • surmann (3)
  • larskotthoff (3)
  • cfhammill (3)
  • jakob-r (3)
  • mllg (3)
  • krlmlr (2)
  • ringprince (2)
  • mshvartsman (2)
  • ghost (2)
  • mschubert (2)
  • jgrn307 (2)
Pull Request Authors
  • ghost (3)
  • renozao (2)
  • krlmlr (1)
  • dagola (1)
  • mshvartsman (1)
  • gaborcsardi (1)
  • gmbecker (1)
  • ja-thomas (1)
  • jakob-r (1)
  • surmann (1)
  • mllg (1)
  • ReadmeCritic (1)
Top Labels
Issue Labels
enhancement (17) bug (2) question (1) wontfix (1)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • cran 1,011 last-month
  • Total docker downloads: 74,705
  • Total dependent packages: 5
    (may contain duplicates)
  • Total dependent repositories: 29
    (may contain duplicates)
  • Total versions: 18
  • Total maintainers: 1
cran.r-project.org: BatchJobs

Batch Computing with R

  • Versions: 14
  • Dependent Packages: 5
  • Dependent Repositories: 29
  • Downloads: 1,011 Last month
  • Docker Downloads: 74,705
Rankings
Docker downloads count: 0.6%
Forks count: 3.6%
Stargazers count: 4.4%
Dependent repos count: 5.0%
Average: 5.4%
Dependent packages count: 8.2%
Downloads: 10.7%
Maintainers (1)
bernd_bischl@gmx.net
Last synced: 12 months ago
conda-forge.org: r-batchjobs
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Stargazers count: 31.9%
Forks count: 32.6%
Dependent repos count: 34.0%
Average: 37.4%
Dependent packages count: 51.2%
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • BBmisc >= 1.9 depends
  • R >= 3.0.0 depends
  • methods * depends
  • DBI * imports
  • RSQLite >= 1.0.9011 imports
  • backports >= 1.1.1 imports
  • brew * imports
  • checkmate >= 1.8.0 imports
  • data.table >= 1.9.6 imports
  • digest * imports
  • parallel * imports
  • sendmailR * imports
  • stats * imports
  • stringi >= 0.4 imports
  • utils * imports
  • MASS * suggests
  • testthat * suggests