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benrutter avatar benrutter commented on June 12, 2024 1

I think scaling is theoretically possible with something like this: https://docs.databricks.com/api/workspace/clusters#resize I guess the tricky bits are:

  • Additional access tokens etc required to manage cluster with the api
  • Not accidently giving people footguns to scale above previously specified max-clusters
  • Maybe most imporantly, databricks provides "autoscale" functionality, which I think is normally on (although I have no stats at all). Worst case scenario would be the dask cluster and databricks getting in an argument over who's in charge of scaling.

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jacobtomlinson avatar jacobtomlinson commented on June 12, 2024

In #9 @benrutter added an initial implementation of this, but we should explore migrating the base class over to Cluster instead of LocalCluster.

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jacobtomlinson avatar jacobtomlinson commented on June 12, 2024

I'd also be very curious to know if we can somehow scale the Databricks cluster from within our notebooks. If so we could wire up the DatabricksCluster.scale() method.

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jacobtomlinson avatar jacobtomlinson commented on June 12, 2024

Thanks @benrutter these are all good points. It might not be a sensible thing to do. Your comment does lead me to wonder how the autoscaling is triggered, is it based on node properties such as CPU/Memory or does Spark make those decisions? If it's Spark then there is no way for Dask to trigger that scale-up.

In general, I think autoscaling Dask on Databricks is an advanced topic that is best saved for later.

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