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Garage v0.9 #473

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doc/book/operations/layout.md
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@ -94,12 +94,13 @@ follow the following recommendations:
## Understanding unexpected layout calculations ## Understanding unexpected layout calculations
When adding, removing or modifying nodes in a cluster layout, sometimes When adding, removing or modifying nodes in a cluster layout, sometimes
unexpected assigntations of partitions to node can occure. These assignations unexpected assigntations of partitions to node can occur. These assignations
are in fact normal and logical, given the objectives of the algorihtm. Indeed, are in fact normal and logical, given the objectives of the algorihtm. Indeed,
**the layout algorithm prioritizes moving less data between nodes over the fact **the layout algorithm prioritizes moving less data between nodes over the fact
of achieving equal distribution of load**. This section presents two examples of achieving equal distribution of load. It also tries to use all links between
and illustrates how one can control Garage's behavior to obtain the desired pairs of nodes in equal proportions when moving data.** This section presents
results. two examples and illustrates how one can control Garage's behavior to obtain
the desired results.
### Example 1 ### Example 1
@ -266,8 +267,8 @@ This explains why node3 ends with 75% utilization (100% from before minus 25%
that is moved to node1), and node4 ends with 25% (50% from before minus 25% that is moved to node1), and node4 ends with 25% (50% from before minus 25%
that is moved to node1). that is moved to node1).
This illustrates another principle of the layout computation: **if there is a This illustrates the second principle of the layout computation: **if there is
choice in moving data out of some nodes, then all links between pairs of nodes a choice in moving data out of some nodes, then all links between pairs of
are used in equal proportions** (this is approximately true, there is nodes are used in equal proportions** (this is approximately true, there is
randomness in the algorihtm to achieve this so there might be some small randomness in the algorihtm to achieve this so there might be some small
fluctuations, as we see above). fluctuations, as we see above).