Pipelines as jobs » History » Version 7

Peter Amstutz, 09/18/2014 03:54 PM

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h1. Everything is a job
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h2. Problem
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Currently we have tasks, jobs, and pipelines.  While this corresponds to a common pattern for building bioinfomatics analysis, in practice we are finding that this design is overly rigid with several unintended consequences:
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# arv-run-pipeline-instance is currently a special privileged pipeline runner.  However, there are potentially many other pipeline frameworks we would like to support, such as bcbio-nextgen, rmake, snakemake, Nextflow, etc. that should be usable by regular users and so can't be privileged processes.
# Need to work with batches and pipelines of pipelines.  If we have a pipeline that processes a single sample, and we want to run it 100 times, currently we need to create 100 pipelines by hand, by a script that runs outside of the system, or using a separate job.
# Currently, we can create jobs which either 1. submits stages as subtasks or 2. submits stages as additional jobs.
## In the first approach, job reuse features are not available with tasks, and all subtasks must be able to run out of the same docker image.  
## In the second approach, the controller job currently ties up a whole node, even though it is mostly idle, and we currently do not track the process tree (which job submissions were made by which other jobs.)
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h2. Proposed solution
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# Improve job scheduling so that we can have more than one job on a node, with jobs can be allocated to a single core (possibly even fractions of a core).
# Remove arv-run-pipeline-instance from its privileged position and run it as a job in a container just like everything else.
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# Deprecate tasks, prefer to submit jobs instead (enables work reuse)
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# Use the API token associated with the job to track which job submissions were made by the controlling job (add a spawned_by_job_uuid field to the jobs object).  Unify the display of jobs and pipelines so that a pipeline is just a job that creates other jobs.
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Another benefit: supports the proposed v2 Python SDK by enabling users to orchestrate pipelines where "python" is the same whether it runs locally, runs locally and submits jobs, or runs as a crunch job itself and submits jobs.
h2. Related ideas
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Currently, porting tools like bcbio or rmake still requires the tool be modified so that it schedules jobs on the cluster instead of running locally.  We could use LD_PRELOAD to intercept a whitelist of exec() calls and redirect them to a script that causes the tool to run on the cluster.