Partitioning ensures that all observations in a group end up on the same worker. To try and keep the observations on each worker balanced, 'partition()' uses a greedy algorithm that iteratively assign each group to the worker that currently has the fewest rows.
Dataset to partition, typically grouped. When grouped, all observations in a group will be assigned to the same cluster.
Cluster to use.
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