Condor week summary
From UABgrid Documentation
Condor week 2012, UW-Madison, May 1 - May 5, 2012
Attendees: John-Paul Robinson, Poornima Pochana, Thomas Anthony
Condor Week is a four day annual event that gives collaborators and users the chance to exchange ideas and experiences, to learn about latest research, and to influence our short and long term research and development directions.
Day 1: Tutorials
Basic Introduction to using Condor: Karen Miller
Background HTC Definitions: Job, Class Ads, Match Making, Central Manager, Submit host, Execute Host
What Condor does: submit- condor bundles up the executable and input files, condor locates a machine, runs the job, and gets the output back to the submit host.
Requirements (needs), Rank( preferences)
Condor Class Ads: used to describe aspects of each item outside condor. job Class ad: machine class ad:
Match making: requirement, rank and priorities (fair share allocation)
Getting started: universe, make job batch -ready, submit file, condor_submit
Universe-environment batch ready- run w/o interaction (as if in the background), make input, output available, data files submit description file- # comments, commands on left are not case sensitive, filenames are
Good advice: always have a log file
file transfer; Transfer_Input_Files, Transfer_Output_Files
Should_transfer_Files: Yes (no shared files system), NO (use shared FS) IF_NEEDED
emails: NOTIFICATION = complete, never, error, error, always.
Job Identifier: cluster.process eg. 20.1, 20.2 etc..
Multiple jobs : to create directories (based on the process id) InitialDir=run_0,run_1 etc… Queue all 1,000,000 jobs
Queue 100000 $(Process)
use macro subs: %this gives the process id.. InitialDir=run_$(Process)
Condor and Workflows: Nathan Panike
Introduction: Workflows? sequence of connected steps..
launch and forget
DAG MAN -dependencies define possible order of job execution
Pegasus - A system to run, manage and debug complex workflows on top of Condor: Karan Vahi
Scientific workflows,larger monolithic applications broken to smaller jobs
Why workflows: portable, scalable, reuse, reproduce, WMS-recovery
Pegasus: local desktop, local condor pool. campus cluster.
Pegasus GUI Mapping- workflow monitoring: SQLite and MySQL, python api to query, transfers executable s as part of workflow
Basic Condor Administration: Alan De Semet
Starting job: condor_master= all machines.. (start other processes)
Central manager: master, negotiator, collector collector: daemon knows about other daemons
Submit: master, schedd, schedd--.>shadow
Compute machine: master, startd, startd --->starter ---> launches Job
condor compile---> calls condor Syscall Lib
***** configuration file***** /etc/condor/condor_config LOCAL_CONFIG_FILE (CSV) long entry \ splits across multiple lines
****Policy****** specified in condor_config ends up in slot ClassAD
Machine -- one computer, managed by one started
START Policy: RANK- floating point, larger number are higher ranked, Suspend and continue: Preemt (polite) Kill (sigkill)
Slot states: Custom slot attributes: dynamic attributes settings STARTD_CRON_*
***Job priorities*** condor_userprio: lower number means more machines.. real priority and priority factor:
priority factor-default is 1,assign it user by user basis
preemption_requirements=false % no preemption
condor_config_val condor_conifg_cal -v CONDOR_HOST condor_conifg_cal config condor_Status -master conder_status -long (everything) condor_status -format '%s' Arch -format '%s\n' -constraint -format condor_q -analyze Debug level: D_FULLDEBUG D_COMMAND