MySQL: Handling 10M Records

There are several methods that can be used to handle a MySQL database with ten million records:

1. Creating appropriate indexes: establishing indexes for frequently used fields can speed up query processing and reduce data retrieval time.
2. Data sharding: Data is dispersed into multiple tables according to certain rules, reducing the data volume in each table and enhancing query efficiency.
3. Data partitioning: splitting data into different disk partitions according to specific rules can improve query efficiency.
4. Regularly clean and optimize data: Regularly cleaning out unnecessary data and optimizing database table structures can reduce data volume and improve query speed.
5. Utilizing caching: Employing caching technology can reduce the number of times the database is accessed, thereby improving query speed.
6. Utilizing a database cluster: distributing data across multiple database nodes can increase query efficiency and load balancing.
7. Choose the appropriate hardware: selecting high-performance hardware devices and configuring the database parameters properly can enhance the processing capacity of the database.

Using the above methods can efficiently handle ten million records in a MySQL database, improving the performance and query efficiency of the database.