Recently, an e-commerce user experienced a sharp increase in access volume due to rapid business development, resulting in bottlenecks in database capacity and performance. To reduce the database size and improve performance, the user decided to implement vertical sharding on the architecture. Sharding is performed by table, which results in less of an impact on applications and supports clear and simple sharding rules.
The user vertically divided data into three databases according to members, commodities, and orders. After the vertical sharding was performed, the data was distributed to different database instances, reducing the data volume in each database and increasing the number of instances. This process seems simple but is difficult to implement. This is because once sharding is introduced, a query originally implemented in one database instance will now be implemented across two database instances.