adapt(self, *args, minimum=0, maximum=inf, minimum_cores: 'int' = None, maximum_cores: 'int' = None, minimum_memory: 'str' = None, maximum_memory: 'str' = None, **kwargs) -> 'Adaptive'
This scales Dask clusters automatically based on scheduler activity.
Minimum number of workers
Maximum number of workers
Minimum number of cores/threads to keep around in the cluster
Maximum number of cores/threads to keep around in the cluster
Minimum amount of memory to keep around in the cluster Expressed as a string like "100 GiB"
Maximum amount of memory to keep around in the cluster Expressed as a string like "100 GiB"
Turn on adaptivity
dask.distributed.Adaptive
for more keyword arguments
>>> cluster.adapt(minimum=0, maximum_memory="100 GiB", interval='500ms')See :
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them