No, that's not true.
On Sat., 22 Sep. 2018, 21:58 onmstester onmstester,
wrote:
>
> If you have problems with balance you can add new nodes using the
> algorithm and it'll balance out the cluster. You probably want to stick to
> 256 tokens though.
>
>
> I read somewhere (don't remember the ref)
If you have problems with balance you can add new nodes using the algorithm and
it'll balance out the cluster. You probably want to stick to 256 tokens though.
I read somewhere (don't remember the ref) that all nodes of the cluster should
use the same algorithm, so if my cluster suffer from imba
>
> But one more question, should i use num_tokens : 8 (i would follow
> datastax recommendation) and allocate_tokens_for_local_replication_factor=3
> (which is max RF among my keyspaces) for new clusters which i'm going to
> setup?
16 is probably where it's at. Test beforehand though.
> Is the A
Thanks, Because all my clusters are already balanced, i won't change their
config But one more question, should i use num_tokens : 8 (i would follow
datastax recommendation) and allocate_tokens_for_local_replication_factor=3
(which is max RF among my keyspaces) for new clusters which i'm going t
If you have problems with balance you can add new nodes using the algorithm
and it'll balance out the cluster. You probably want to stick to 256 tokens
though.
To reduce your # tokens you'll have to do a DC migration (best way). Spin
up a new DC using the algorithm on the nodes and set a lower numb
I noticed that currently there is a discussion in ML with subject: changing
default token behavior for 4.0. Any recommendation to guys like me who already
have multiple clusters ( > 30 nodes in each cluster) with random partitioner
and num_tokens = 256? I should also add some nodes to existing c
