Hi,
I've 8 data nodes right now in production. I want to test ML in production, how many dedicated nodes would ML require? Also, I won't be adding any new nodes, so, how can I make the existing data nodes, machine learning nodes?
How do I reroute shards allocated to that data node, because wouldn't ES allocate those shards back to balance the shards throughout the cluster?
My question is, how do I convert a data node into dedicated ML node after assigning the shards allocated to it to the rest of the cluster?
Thanks for the reply.
To safely distribute the shard data and decommission the node i'll have to use allocation filter instead of repurpose, right?
I understand if I have to make the existing node into a dedicated ML node then I'll have to use node.roles: ml option. And inorder to do that I'll have make changes in elasticsearch.yml, but since we have a common elasticsearch.yml file for all the nodes in the cluster how do I use that config option in command line?
Mark, Any way to change the role while restarting the node in the command line?
Something like: bin/elasticsearch -Dnode.roles=ml
And for data nodes: bin/elasticsearch -Dnode.roles=data
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