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At my company we use conda-pack to make certain packages available on the spark executors. Is there a better a better alternative to get away from creating a new environment and pack it every time I need a new python lib to be available for the executors?
databricks provides library installation in the form of PyPi packages, or wheel/egg.
If you install the packages like that on the cluster, they are automatically sent to all executors.
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