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 nodes 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. Scaling out operations add nodes based on the node ID in ascending order, while scaling in operations remove nodes based on the node ID in descending order.

Currently, the TiDB cluster supports management by Helm or by TidbCluster Custom Resource (CR). You can choose the scaling method based on the management method of your TiDB cluster.

Horizontal scaling operations (CR)

Scale PD, TiDB, and TiKV

Modify spec.pd.replicas, spec.tidb.replicas, and spec.tikv.replicas in the TidbCluster object of the cluster to a desired value using kubectl.

Scale out TiFlash

If TiFlash is deployed in the cluster, you can scale out TiFlash by modifying spec.tiflash.replicas.

Scale TiCDC

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

Scale in TiFlash

  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 0;
      
  5. Wait for TiFlash replicas in the related tables to be deleted.

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

    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.

Horizontal scaling operations (Helm)

To perform a horizontal scaling operation, take the following steps:

  1. Modify pd.replicas, tidb.replicas, tikv.replicas in the value.yaml file of the cluster to a desired value.

  2. Run the helm upgrade command to scale out or in:

    helm upgrade ${release_name} pingcap/tidb-cluster -f values.yaml --version=${version}
    

View the 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.

Note:

  • The PD, TiKV and TiFlash components do not trigger scaling in and out operations during the rolling update.
  • When the TiKV component scales in, TiDB Operator calls the PD interface to mark the corresponding TiKV instance as offline, and then migrates the data on it to other TiKV nodes. During the data migration, the TiKV Pod is still in the Running state, and the corresponding Pod is deleted only after the data migration is completed. The time consumed by scaling in depends on the amount of data on the TiKV instance to be scaled in. You can check whether TiKV is in the Offline state by running kubectl get tidbcluster -n ${namespace} ${release_name} -o json | jq '.status.tikv.stores'.
  • The TiKV component does not support scale out while a scale-in operation is in progress. Forcing a scale-out operation might cause anomalies in the cluster. If an anomaly already happens, refer to TiKV Store is in Tombstone status abnormally to fix it.
  • The TiFlash component has the same scale-in logic as TiKV.
  • When the PD, TiKV, and TiFlash components scale in, the PVC of the deleted node is retained during the scaling in process. Because the PV's reclaim policy is changed to Retain, the data can still be retrieved even if the PVC is deleted.

Vertical scaling

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

Currently, the TiDB cluster supports management by Helm or by TidbCluster Custom Resource (CR). You can choose the scaling method based on the management method of your TiDB cluster.

Vertical scaling operations (CR)

Modify spec.pd.resources, spec.tikv.resources, and spec.tidb.resources in the TidbCluster object that corresponds to the cluster to the desired values using kubectl.

If TiFlash is deployed in the cluster, you can scale up and down TiFlash by modifying spec.tiflash.resources.

If TiCDC is deployed in the cluster, you can scale up and down TiCDC by modifying spec.ticdc.resources.

Vertical scaling operations (Helm)

To perform a vertical scaling operation:

  1. Modify tidb.resources, tikv.resources, pd.resources in the values.yaml file to a desired value.

  2. Run the helm upgrade command to upgrade:

    helm upgrade ${release_name} pingcap/tidb-cluster -f values.yaml --version=${version}
    

View the upgrade 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.

Note:

  • If the resource's requests field is modified during the vertical scaling process, and if PD, TiKV, and TiFlash use Local PV, they will be scheduled back to the original node after the upgrade. At this time, if the original node does not have enough resources, the Pod ends up staying in the Pending status and thus impacts the service.
  • TiDB is a horizontally scalable database, so it is recommended to take advantage of it simply by adding more nodes rather than upgrading hardware resources like you do with a traditional database.