Skip to content

Latest commit

 

History

History
103 lines (63 loc) · 3.65 KB

README.md

File metadata and controls

103 lines (63 loc) · 3.65 KB
Raw

condor-comforter

Helper routines for using condor at Bristol, particularly aimed at CMS users. Most things require the htcondenser Python package.

Please report any issues, and add any helpful scripts for other users!

Robin Aggleton

Installation

Easiest way is via pip. If you don't have pip, you can use the one in /software/miniconda/bin/pip.

pip install -U --process-dependency-links --user git+https://github.com/BristolComputing/condor-comforter.git

The same command can also be used to update the package.

Note that if you see:

  DEPRECATION: Dependency Links processing has been deprecated and will be removed in a future release.

it can be safely ignored.

After this, cmsRunCondor.py and haddaway.py should be available like any other command. One can also import them as python modules for further extension.

For possible arguments, do cmsRunCondor.py -h or haddaway.py -h

##cmsRunCondor

This runs cmsRun jobs on HTCondor (like CRAB3), outputting to /hdfs.

Brief example (requires CMSSW 80X release):

cmsRunCondor.py pset_tutorial_analysis.py \
--dataset /QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring16MiniAODv2-PUSpring16_80X_mcRun2_asymptotic_2016_miniAODv2_v0-v1/MINIAODSIM \
--totalUnits 10 --unitsPerJob 5 --splitByFiles \
--outputDir /hdfs/user/$LOGNAME/cmsRunCondor \
--dag

You can then monitor job progress with DAGstatus (part of htcondenser package)

Features currently supported:

  • Run using a LumiMask, and/or specified run numbers

  • Run over all or part of a dataset

  • Split into jobs by # files or # lumisections

  • Run with a secondary dataset to do "2-file solution" (e.g. mixing RECO with RAW)

  • Run with a specified list of files instead of a dataset

  • Specify additional input files needed for running (e.g. calibration files)

  • Easy monitoring of jobs using DAGstatus

  • Profile cmsRun jobs with valgrind or callgrind

  • Just run with whatever is in your config (--asIs) e.g. to stop hogging resources on soolin

  • hadd the output from jobs (need to specify which module's output you want to hadd)

##haddaway

Simple script to perform hadd jobs on HTCondor, splitting them up into smaller parallel groups to speed things up (possibly, YMMV). It creates a series of intermediate hadd jobs, then does a final hadd over all of the intermediate files. You can specify the intermediate group size, and also specify the standard hadd options (e.g. for compression).

Example usage:

# passing the input filenames
haddaway.py --output final.root --size 3 --input file1.root file2.root file3.root --haddArgs="-f7"

# passing a text file (filelist.txt) with locations of files
haddaway.py --output final.root --size 3 --inputList filelist.txt --haddArgs="-f7"

##examples

There are 2 simple condor job examples included, one for a single job, another for a DAG. Note that these are only for reference/a basic understanding of how htcondor operates. For your own work, I would recommended using the htcondenser package to avoid ever having to write these, and solving other hassles.

###simpleJob

A very simple condor job file to run a script on the worker node.

Start from: script.job

###exampleDAG

This holds a simple example of a DAG (directed acyclic graph), i.e. a nice way to schedule various jobs, each of which can depend on other jobs. It shows how to setup and 'connect' jobs with parent-child relationships, and how to pass variables to the condor job file.

Start from: diamond.dag