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TiDB 4.0 Experimental Features

This document introduces the experimental features of TiDB v4.0. It is NOT recommended to use these features in the production environment.

Scheduling

  • Cascading Placement Rules is an experimental feature of the Placement Driver (PD) introduced in v4.0. It is a replica rule system that guides PD to generate corresponding schedules for different types of data. By combining different scheduling rules, you can finely control the attributes of any continuous data range, such as the number of replicas, the storage location, the host type, whether to participate in Raft election, and whether to act as the Raft leader. See Cascading Placement Rules for details.
  • Elastic scheduling is an experimental feature based on Kubernetes, which enables TiDB to dynamically scale out and scale in clusters. This feature can effectively mitigate the high workload during peak hours of an application and saves unnecessary overhead. See Enable TidbCluster Auto-scaling for details.

SQL feature

Service-level features

  • TiDB instances support caching the calculation results that the operator has pushed down to TiKV in the unit of Region, which improves the efficiency of SQL executions in the following scenarios. See Coprocessor Cache for details.
    • The SQL statements are the same.
    • The SQL statements contain a changing condition (limited to the primary key of tables or partitions), and the other parts are consistent.
    • The SQL statements contain multiple changing conditions and the other parts are consistent. The changing conditions exactly match a compound index column.
  • Support persisting configuration parameters in PD and dynamically modifying configuration items to improve product usability.

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