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Scaling ClickHouse Vertically

Last updated: Aug 09, 2022

On this page

  • How to scale ClickHouse vertically

How to scale ClickHouse vertically

Currently the easiest way to scale up a ClickHouse environment hosted by our helm chart config is to set the affinity for which node ClickHouse is deployed to and scale that node up in terms fo the resources it has available to it. This is very easy to do in practice. Let's get down to the nuts and bolts of how to get this done!

  • Create a node instance or group with more CPU and memory in your K8s cluster with a label of clickhouse:true set on it (this will be used to target that node for ClickHouse deployment). There are a few ways to create a node group and most are implementation specific to your kubernetes platform. A few references for how to create an manage node groups can be found for GKE, EKS, and DigitalOcean.
    • Essentially if you know the node that you want ClickHouse to be installed on you can run kubectl label nodes <desired-clickhouse-node-name> clickhouse=true
    • To restrict other pods from not using that node we can add a taint via kubectl taint nodes <desired-clickhouse-node-name> dedicated=clickhouse:NoSchedule
  • Update your values.yaml:
clickhouse:
nodeSelector:
clickhouse: "true"
tolerations:
- key: "dedicated"
value: "clickhouse"
operator: "Equal"
effect: "NoSchedule"
  • You might need to trigger the reallocation for the clickhouse pod, e.g. run kubectl delete pod chi-posthog-posthog-0-0-0

You can find more information about optional settings like that here and also more about nodeSelectors and taints and tolerations.

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Next article

Horizontal scaling (sharding & replication)

Sharding is a horizontal cluster scaling strategy that puts parts of one ClickHouse database on different shards. This can help you to: Improve fault tolerance. Sharding lets you isolate individual host or replica set malfunctions. If you don't use sharding, then when one host or a set of replicas fails, the entire data they contain may become inaccessible. But if 1 shard out of 5 fails, for example, then 80% of the table data is still available. Improve the query performance. Requests…

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