Hi everyone,
After the new release (2.7.0), I have been playing around with the machine
learning algorithms a bit.
We have some data in a cache created with the "withKeepBinary()" option, and
I wanted
to test if the machine learning algos would work with such a cache. I tried,
but it fails with
Hello
Couple of things I would like to with my experience
1. Cache Groups : Around 100 caches, I do not think we need to go for Cache
groups, as you mentioned cache groups will have impact on you read/writes.
However, changing the partition count to 128 from default 1024 would improve
your
Question on Ignite Persistence:
On a deployed Ignite (3 node) cluster, I see one one node being taken out of
the cluster because it encounters GC Pauses. Worse, when this node leaves the
cluster, a Rebalance is initiated (and re-initiated when the node joins back).
Note: Data that Ignite Cluster
I'd have at least 80-90 caches, assuming each cache corresponds to a table.
Any feedback regarding other questions?
thanks,
Clay
On Mon, Dec 31, 2018 at 9:58 AM Mikael wrote:
> Hi!
>
> You have to try, if you just have a few caches (<10) you may not need to
> go for any cache groups at all but
