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Manually Scale TiDB in Kubernetes

This document introduces how to horizontally and vertically scale a TiDB cluster in Kubernetes.

Horizontal scaling

Horizontally scaling TiDB means that you scale TiDB out or in by adding or remove Pods in your pool of resources. When you scale a TiDB cluster, PD, TiKV, and TiDB are scaled out or in sequentially according to the values of their replicas.

  • To scale out a TiDB cluster, increase the value of replicas of a certain component. The scaling out operations add Pods based on the Pod ID in ascending order, until the number of Pods equals the value of replicas.

  • To scale in a TiDB cluster, decrease the value of replicas of a certain component. The scaling in operations remove Pods based on the Pod ID in descending order, until the number of Pods equals the value of replicas.

Horizontally scale PD, TiKV, and TiDB

To scale PD, TiKV, or TiDB horizontally, use kubectl to modify spec.pd.replicas, spec.tikv.replicas, and spec.tidb.replicas in the TidbCluster object of the cluster to a desired value.

  1. Modify the replicas value of a component as needed. For example, configure the replicas value of PD to 3:

    kubectl patch -n ${namespace} tc ${cluster_name} --type merge --patch '{"spec":{"pd":{"replicas":3}}}'
    
  2. Check whether your configuration has been updated in the corresponding TiDB cluster in Kubernetes.

    kubectl get tidbcluster ${cluster_name} -n ${namespace} -oyaml
    

    If your configuration is successfully updated, in the TidbCluster CR output by the command above, the values of spec.pd.replicas, spec.tidb.replicas, and spec.tikv.replicas are consistent with the values you have configured.

  3. Check whether the number of TidbCluster Pods has increased or decreased.

    watch kubectl -n ${namespace} get pod -o wide
    

    For the PD and TiDB components, it might take 10-30 seconds to scale in or out.

    For the TiKV component, it might take 3-5 minutes to scale in or out because the process involves data migration.

Horizontally scale TiFlash

This section describes how to horizontally scale out or scale in TiFlash if you have deployed TiFlash in the cluster.

Horizontally scale out TiFlash

To scale out TiFlash horizontally, you can modify spec.tiflash.replicas.

For example, configure the replicas value of TiFlash to 3:

kubectl patch -n ${namespace} tc ${cluster_name} --type merge --patch '{"spec":{"tiflash":{"replicas":3}}}'

Horizontally scale in TiFlash

To scale in TiFlash horizontally, perform the following steps:

  1. Expose the PD service by using port-forward:

    kubectl port-forward -n ${namespace} svc/${cluster_name}-pd 2379:2379
    
  2. Open a new terminal tab or window. Check the maximum number (N) of replicas of all data tables with which TiFlash is enabled by running the following command:

    curl 127.0.0.1:2379/pd/api/v1/config/rules/group/tiflash | grep count
    

    In the printed result, the largest value of count is the maximum number (N) of replicas of all data tables.

  3. Go back to the terminal window in Step 1, where port-forward is running. Press Ctrl+C to stop port-forward.

  4. After the scale-in operation, if the number of remaining Pods in TiFlash >= N, skip to Step 6. Otherwise, take the following steps:

    1. Refer to Access TiDB and connect to the TiDB service.

    2. For all the tables that have more replicas than the remaining Pods in TiFlash, run the following command:

      alter table <db_name>.<table_name> set tiflash replica ${pod_number};
      

      ${pod_number} indicates the number of remaining Pods in the TiFlash cluster after scaling in.

  5. Wait for the number of TiFlash replicas in the related tables to be updated.

    Connect to the TiDB service, and run the following command to check the number:

    SELECT * FROM information_schema.tiflash_replica WHERE TABLE_SCHEMA = '<db_name>' and TABLE_NAME = '<table_name>';
    

    If you cannot view the replication information of related tables, the TiFlash replicas are successfully deleted.

  6. Modify spec.tiflash.replicas to scale in TiFlash.

    Check whether TiFlash in the TiDB cluster in Kubernetes has updated to your desired definition. Run the following command and see whether the value of spec.tiflash.replicas returned is expected:

    kubectl get tidbcluster ${cluster-name} -n ${namespace} -oyaml
    

Horizontally scale TiCDC

If TiCDC is deployed in the cluster, you can horizontally scale out or scale in TiCDC by modifying the value of spec.ticdc.replicas.

For example, configure the replicas value of TiCDC to 3:

kubectl patch -n ${namespace} tc ${cluster_name} --type merge --patch '{"spec":{"ticdc":{"replicas":3}}}'

View the horizontal scaling status

To view the scaling status of the cluster, run the following command:

watch kubectl -n ${namespace} get pod -o wide

When the number of Pods for all components reaches the preset value and all components go to the Running state, the horizontal scaling is completed.

Vertical scaling

Vertically scaling TiDB means that you scale TiDB up or down by increasing or decreasing the limit of resources on the Pod. Vertically scaling is essentially the rolling update of the Pods.

Vertically scale components

This section describes how to vertically scale up or scale down components including PD, TiKV, TiDB, TiFlash, and TiCDC.

  • To scale up or scale down PD, TiKV, TiDB, use kubectl to modify spec.pd.resources, spec.tikv.resources, and spec.tidb.resources in the TidbCluster object that corresponds to the cluster to a desired value.

  • To scale up or scale down TiFlash, modify the value of spec.tiflash.resources.

  • To scale up or scale down TiCDC, modify the value of spec.ticdc.resources.

View the vertical scaling progress

To view the upgrade progress of the cluster, run the following command:

watch kubectl -n ${namespace} get pod -o wide

When all Pods are rebuilt and in the Running state, the vertical scaling is completed.

Scaling troubleshooting

During the horizontal or vertical scaling operation, Pods might go to the Pending state because of insufficient resources. See Troubleshoot the Pod in Pending state to resolve it.

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