distributed 2021.10.0

_rebalance_find_msgs(self, keys: 'Set[Hashable] | None', workers: 'Iterable[WorkerState]') -> 'list[tuple[WorkerState, WorkerState, TaskState]]'

This method only defines the work to be performed; it does not start any network transfers itself.

The big-O complexity is O(wt + ke*log(we)), where

There is a degenerate edge case O(wt + kt*log(we)) when kt is much greater than the number of whitelisted keys, or when most keys are replicated or cannot be moved for some other reason.

Returns list of tuples to feed into _rebalance_move_data:

Identify workers that need to lose keys and those that can receive them, together with how many bytes each needs to lose/receive. Then, pair a sender worker with a recipient worker for each key, until the cluster is rebalanced.

Examples

See :

Local connectivity graph

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


File: /distributed/scheduler.py#6157
type: <class 'function'>
Commit: