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Managing Job Dependencies with DAGMan in Grid Workflow Systems

DAGMan (Directed Acyclic Graph Manager) is a powerful tool for managing job dependencies in grid computing, specifically within the Condor-G framework. It allows users to specify complex workflows where certain jobs depend on the completion of others, ensuring that tasks execute in a defined order. This is crucial for applications like the Sloan Digital Sky Survey and the Montage project, which require coordination among numerous jobs. DAGMan provides features such as automatic retry of failed jobs and the ability to create rescue files, making job management efficient and reliable.

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Managing Job Dependencies with DAGMan in Grid Workflow Systems

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  1. Part 8:DAGMan

  2. Part 8: DAGMan • A: Grid Workflow Management • B: DAGMan • C: Laboratory: DAGMan

  3. A: Grid Workflow Management

  4. Job Dependencies • In many applications, some jobs are dependent on other jobs • E.g. job A must finish before job B starts • Often because job B uses output from job A • We call a set of interdependent jobs a workflow • Condor-G can run jobs in any order • We need a workflow manager

  5. Two Motivating Examples The Sloan Digital Sky Survey The Montage Project

  6. Sloan Digital Sky Survey • Map one-quarter of the entire sky • Determine the positions and absolute brightness of more than 100 million celestial objects. • Measure the distance to a million of the nearest galaxies, and to 100,000 quasars. http://www.sdss.org

  7. field brg cluster field catalog tsObj core brg core brg field tsObj brg field tsObj tsObj 2 1 4 1 1 3 2 2 2 1 5 3 Workflow to Find Galaxy Clusters getCatalog bcgCoal maxBcg maxBrg fieldPrep

  8. Workflow to Find Galaxy Clusters getCatalog bcgCoal maxBcg maxBrg

  9. Montage • Create a large mosaic image from many smaller images • Used for astronomy data • Correct optical distortions and intensity differences http://montage.ipac.caltech.edu

  10. Data Stage in nodes Montage compute nodes Data stage out nodes Inter pool transfer nodes Montage Workflow

  11. Montage Workflow 1202 nodes

  12. B: DAGMan

  13. DAGMan • Directed Acyclic Graph Manager • Workflow manager for Condor-G • DAGMan allows you to specify the dependencies between your Condor jobs, so it can manage them automatically for you. • By default, Condor may run your jobs in any order, or everything simultaneously, so we need DAGMan to enforce an ordering when necessary. • (e.g., “Don’t run job “B” until job “A” has completed successfully.”)

  14. Job A Job B Job C Job D What is a DAG? • A DAG is the datastructure used by DAGMan to represent these dependencies. • Each job is a “node” in the DAG. • Each node can have any number of “parent” or “children” nodes – as long as there are no loops!

  15. Job A Job B Job C Job D Defining a DAG • A DAG is defined by a .dagfile, listing each of its nodes and their dependencies: # diamond.dag Job A a.sub Job B b.sub Job C c.sub Job D d.sub Parent A Child B C Parent B C Child D • each node will run the Condor job specified by its accompanying Condor submit file

  16. Submitting a DAG • To start your DAG, just run condor_submit_dag with your .dag file, and Condor will start a personal DAGMan daemon which to begin running your jobs: % condor_submit_dag diamond.dag • condor_submit_dag submits a job with DAGMan as the executable. • This job happens to run on the submitting machine, not any other computer. • Thus the DAGMan daemon itself runs as a Condor job, so you don’t have to baby-sit it.

  17. Running a DAG • DAGMan acts as a “meta-scheduler”, managing the submission of your jobs to Condor based on the DAG dependencies. DAGMan A Condor Job Queue .dag File A B C D

  18. Running a DAG (cont’d) • DAGMan holds & submits jobs to the Condor queue at the appropriate times. DAGMan A Condor Job Queue B B C C D

  19. Running a DAG (cont’d) • In case of a job failure, DAGMan continues until it can no longer make progress, and then creates a “rescue” file with the current state of the DAG. DAGMan A Condor Job Queue Rescue File B X D

  20. Recovering a DAG • Once the failed job is ready to be re-run, the rescue file can be used to restore the prior state of the DAG. DAGMan A Condor Job Queue Rescue File B C C D

  21. Recovering a DAG (cont’d) • Once that job completes, DAGMan will continue the DAG as if the failure never happened. DAGMan A Condor Job Queue B C D D

  22. Finishing a DAG • Once the DAG is complete, the DAGMan job itself is finished, and exits. DAGMan A Condor Job Queue B C D

  23. Additional DAGMan Features • Provides other handy features for job management… • nodes can have PRE & POST scripts • failed nodes can be automatically re-tried a configurable number of times • job submission can be “throttled”

  24. Job A Job B Job C Job D Another sample DAGMan submit file # Filename: diamond.dag Job A A.condor Job B B.condor Job C C.condor Job D D.condor Script PRE A top_pre.csh Script PRE B mid_pre.perl $JOB Script POST B mid_post.perl $JOB $RETURN Script PRE C mid_pre.perl $JOB Script POST C mid_post.perl $JOB $RETURN Script PRE D bot_pre.csh PARENT A CHILD B C PARENT B C CHILD D Retry C 3

  25. Lab 8: DAGMan

  26. Lab 8: DAGMan • In this lab, you’ll: • Run a simple DAGMan job • Run a more complex DAGMan job • Recover a failed DAGMan job

  27. Credits • NSF disclaimer • Portions of this presentation were adapted from the following sources: • Jaime Frey, UW-Madison

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