Technical Overview

Disco is based on the master-slave architecture.

• Disco master receives jobs from clients, adds them to the job queue, and runs them in the cluster when CPUs become available.

• Client processes are Python programs that submit jobs to the master using the :func:`disco.job` function.

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• A worker supervisor is started automatically by the master on each node in the cluster. Its responsibility is to spawn and monitor all Python worker processes that run on that particular node.

• Python workers take the user-specified :term:`job functions`, run them with the specified input, and write output to result files. As the result, they send addresses of the result files to the master through their supervisor.

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• Input files are accessed via HTTP, unless Python worker runs on the same node where an input file is located, in which case it will be read directly from the disk. To be able to access input files on remote nodes, a httpd daemon (web server), runs on each node. Disco master tries to maintain data locality by scheduling tasks on the same nodes where their inputs can be found.

Each map or reduce instance is given exclusive access to a CPU while it executes. This means that in a cluster with N CPUs, at most N Disco tasks can run in parallel.

If high availability of the system is a concern, CPUs in the cluster can be partitioned amongst arbitrary many Disco masters. This way several Disco masters can co-exist, which eliminates the only single point of failure in the system.