Optimize MySQL Large Table Queries

To improve query efficiency when dealing with single-table queries of tens of millions of records, the following methods can be used.

1. Using appropriate indexes: Creating indexes on primary key fields and fields frequently used for queries can speed up query performance. However, it is important to consider that indexes also take up storage space and can increase the time for updates and insert operations.
2. Avoid full table scans: Try to avoid querying fields without an index, as this can lead to a full table scan, consuming a lot of time and resources. You can prevent full table scans by using techniques such as querying in batches or using pagination.
3. Optimize queries: avoid using complex queries as much as possible, use the explain command to view the execution plan of the queries, identify the reasons for slow queries, and optimize them.
4. Partitioning a table can improve query efficiency for tables with a large amount of data by dividing it based on time or other fields.
5. Utilizing cache: For data with query results that do not change frequently, it is worth considering caching the results to reduce the number of database queries.
6. Regular maintenance of the database, such as cleaning up unnecessary data and optimizing and rebuilding indexes, helps to maintain database performance.

In conclusion, by using appropriate indexing, avoiding full table scans, optimizing query statements, partitioning tables, utilizing caching, and regularly maintaining the database, the efficiency of querying millions of data records in a single table can be greatly improved.