Overview

This page lists metrics that we wish to derive for Pegasus workflows.

Metrics

Aggregations:

• Total number of workflows executed

  Code Block
  SELECT count(wf_id) from workflow

• Number of workflows executed per day

  Code Block
  Best aggregated with code glue/datetime libs but currently doable.

• Total runtime of each workflow

  Code Block
  select max(timestamp) - min(timestamp) from jobstate where job_id in ( select job_id from job where wf_id = ( select wf_id from workflow where wf_uuid = 'b5310bb2-2871-423d-bdee-8cd0ed1f925a' ) )

  • Sum of task durations with and without pre/post script

    Code Block
    select j.job_id, (select max(timestamp) - min(timestamp) from jobstate where job_id = j.job_id) as total, (select max(timestamp) - min(timestamp) from jobstate where job_id = j.job_id and state not like '%SCRIPT%') as noprepostscript from job as j where j.wf_id = ( select wf_id from workflow where wf_uuid = 'b5310bb2-2871-423d-bdee-8cd0ed1f925a' )

• Total walltime of each workflow
  • Sum of dagman time (difference between dagman end and start times)
• Total number of workflow jobs/tasks executed. This means total jobs and tasks (including failed, repeats, success what not). These are all the job executions for a given workflow.
  • Total number of workflow jobs and tasks that failed
  • Total number of workflow jobs and tasks that succeeded

    Code Block

    select count(*) total_jobs, sum((select count(*) from jobstate where job_id = j.job_id and state = 'JOB_SUCCESS')) as job_success, sum((select count(*) from jobstate where job_id = j.job_id and state = 'JOB_FAILURE')) as job_failure, sum((select count(*) from task where job_id = j.job_id and exitcode = 0)) as task_success, sum((select count(*) from task where job_id = j.job_id and exitcode <> 0)) as task_failure from job as j where j.wf_id = ( select wf_id from workflow where wf_uuid = 'b5310bb2-2871-423d-bdee-8cd0ed1f925a' )

• Total number of workflow jobs/tasks that were automatically retried. 

  Code Block
  select count(*) from ( select name, count(job_submit_seq) from job where wf_id = ( select wf_id from workflow where wf_uuid = 'b5310bb2-2871-423d-bdee-8cd0ed1f925a' ) group by name having count(job_submit_seq) > 1 )

• Workflow jobs/tasks that were retried (breakdown by jobmaname or transformation.

  Code Block
  select name from job where wf_id = ( select wf_id from workflow where wf_uuid = 'b5310bb2-2871-423d-bdee-8cd0ed1f925a' ) group by name having count(job_submit_seq) > 1 Etc....

• Number of jobs/tasks executed per <time-period>: day, per week , per month, per hour, per year

  Code Block
  Best aggregated with code glue/datetime libs but currently doable.

• Overheads for the jobs (cumulative and average). We should also be able to quantify the % overhead in relation to the overall job time.
  • DAGMan overhead
  • amount of time spent in the Condor Q
  • time from release to the queue to running
  • Kickstart overhead

Related to resource utilization:

• Number of jobs executed on a host/glidein for a particular provisioning request
• Average number of idle jobs in the queue over time (also maybe min/max)
• Average number of running jobs over time (also maybe min/max)
• Average number of idle glide-ins over time (and min/max)

Filters:

• Job type (data transfer in/out, registration, application, other Pegasus jobs)

Graphs:

• Workflows/jobs/tasks over time

Links to Pegasus pages

Gathering Information About a Workflow
Workflow Metrics that can be obtained