Skip to content

Workflows Exercise 1.3: A More Complex DAG

The objective of this exercise is to run a real set of jobs with DAGMan.

Make Your Job Submission Files

We'll run our goatbrot example. If you didn't read about it yet, please do so now. We are going to make a DAG with four simultaneous jobs (goatbrot) and one final node to stitch them together (montage). This means we have five jobs. We're going to run goatbrot with more iterations (100,000) so each job will take longer to run.

You can create your five jobs. The goatbrot jobs are very similar to each other, but they have slightly different parameters and output files.

goatbrot1.sub

executable              = /usr/local/bin/goatbrot
arguments               = -i 100000 -c -0.75,0.75 -w 1.5 -s 500,500 -o tile_0_0.ppm
log                     = goatbrot.log
output                  = goatbrot.out.0.0
error                   = goatbrot.err.0.0
request_memory          = 1GB
request_disk            = 1GB
request_cpus            = 1
queue

goatbrot2.sub

executable              = /usr/local/bin/goatbrot
arguments               = -i 100000 -c 0.75,0.75 -w 1.5 -s 500,500 -o tile_0_1.ppm
log                     = goatbrot.log
output                  = goatbrot.out.0.1
error                   = goatbrot.err.0.1
request_memory          = 1GB
request_disk            = 1GB
request_cpus            = 1
queue

goatbrot3.sub

executable              = /usr/local/bin/goatbrot
arguments               = -i 100000 -c -0.75,-0.75 -w 1.5 -s 500,500 -o tile_1_0.ppm
log                     = goatbrot.log
output                  = goatbrot.out.1.0
error                   = goatbrot.err.1.0
request_memory          = 1GB
request_disk            = 1GB
request_cpus            = 1
queue

goatbrot4.sub

executable              = /usr/local/bin/goatbrot
arguments               = -i 100000 -c 0.75,-0.75 -w 1.5 -s 500,500 -o tile_1_1.ppm
log                     = goatbrot.log
output                  = goatbrot.out.1.1
error                   = goatbrot.err.1.1
request_memory          = 1GB
request_disk            = 1GB
request_cpus            = 1
queue

montage.sub

You should notice that the transfer_input_files statement refers to the files created by the other jobs.

executable              = /usr/bin/montage
arguments               = tile_0_0.ppm tile_0_1.ppm tile_1_0.ppm tile_1_1.ppm -mode Concatenate -tile 2x2 mandel-from-dag.jpg
transfer_input_files    = tile_0_0.ppm,tile_0_1.ppm,tile_1_0.ppm,tile_1_1.ppm
output                  = montage.out
error                   = montage.err
log                     = montage.log
request_memory          = 1GB
request_disk            = 1GB
request_cpus            = 1
queue

Make your DAG

In a file called goatbrot.dag, you have your DAG specification:

JOB g1 goatbrot1.sub
JOB g2 goatbrot2.sub
JOB g3 goatbrot3.sub
JOB g4 goatbrot4.sub
JOB montage montage.sub
PARENT g1 g2 g3 g4 CHILD montage

Ask yourself: do you know how we ensure that all the goatbrot commands can run simultaneously and all of them will complete before we run the montage job?

Running the DAG

Submit your DAG:

[email protected] $ condor_submit_dag goatbrot.dag
-----------------------------------------------------------------------
File for submitting this DAG to Condor           : goatbrot.dag.condor.sub
Log of DAGMan debugging messages                 : goatbrot.dag.dagman.out
Log of Condor library output                     : goatbrot.dag.lib.out
Log of Condor library error messages             : goatbrot.dag.lib.err
Log of the life of condor_dagman itself          : goatbrot.dag.dagman.log

Submitting job(s).
1 job(s) submitted to cluster 71.

-----------------------------------------------------------------------

Watch Your DAG

Let’s follow the progress of the whole DAG:

  1. Use the condor_watch_q command to keep an eye on the running jobs. See more information about this tool here.

    [email protected] $ condor_watch_q
    

    If you're quick enough, you may have seen DAGMan running as the lone job, before it submitted additional job nodes:

    BATCH                IDLE  RUN  DONE  TOTAL  JOB_IDS
    goatbrot.dag+222059     -    1     -      1  222059.0
    
    [=============================================================================]
    
    Total: 1 jobs; 1 running
    
    Updated at 2021-07-28 13:52:57
    

    DAGMan has submitted the goatbrot jobs, but they haven't started running yet

    BATCH                IDLE  RUN  DONE  TOTAL  JOB_IDS
    goatbrot.dag+222059     4    1     -      5  222059.0 ... 222063.0
    
    [===============--------------------------------------------------------------]
    
    Total: 5 jobs; 4 idle, 1 running
    
    Updated at 2021-07-28 13:53:53
    

    They're running

    BATCH                IDLE  RUN  DONE  TOTAL  JOB_IDS
    goatbrot.dag+222059     -    5     -      5  222059.0 ... 222063.0
    [=============================================================================]
    
    Total: 5 jobs; 5 running
    
    Updated at 2021-07-28 13:54:33
    

    They finished, but DAGMan hasn't noticed yet. It only checks periodically:

    BATCH                IDLE  RUN  DONE  TOTAL  JOB_IDS
    goatbrot.dag+222059     -    1    4     -      5  222059.0 ... 222063.0
    
    [##############################################################===============]
    
    Total: 5 jobs; 4 completed, 1 running
    
    Updated at 2021-07-28 13:55:13
    

    Eventually, you'll see the montage job submitted, then running, then leave the queue, and then DAGMan will leave the queue.

  2. Examine your results. For some reason, goatbrot prints everything to stderr, not stdout.

    [email protected] $ cat goatbrot.err.0.0 
    Complex image: Center: -0.75 + 0.75i Width: 1.5 Height: 1.5 Upper Left: -1.5 + 1.5i Lower Right: 0 + 0i
    
    Output image: Filename: tile_0_0.ppm Width, Height: 500, 500 Theme: beej Antialiased: no
    
    Mandelbrot: Max Iterations: 100000 Continuous: no
    
    Goatbrot: Multithreading: not supported in this build
    
    Completed: 100.0%
    
  3. Examine your log files (goatbrot.log and montage.log) and DAGMan output file (goatbrot.dag.dagman.out). Do they look as you expect? Can you see the progress of the DAG in the DAGMan output file?

  4. As you did earlier, copy the resulting mandel-from-dag.jpg to your public_html directory, then access it from your web browser. Does the image look correct?
  5. Clean up your results by removing all of the goatbrot.dag.* files if you like. Be careful to not delete the goatbrot.dag file.

Bonus Challenge

  • Re-run your DAG. When jobs are running, try condor_q -nobatch -dag. What does it do differently?
  • Challenge, if you have time: Make a bigger DAG by making more tiles in the same area.