How to speed up queries

1. upgrade hardware 2. Create indexes based on query conditions, optimize indexes, optimize access methods, and limit the data volume of result sets. 3. Expand Server Memory 4. Increase server CPU count 5. Do not set Automatic database growth for large databases, it will reduce the server performance. 6. Use the WHERE clause in the query SELECT statement to limit the number of returned rows to avoid table scanning. If unnecessary data is returned, the server's I/O resources are wasted, this increases the burden on the network and reduces performance. If the table is large, the table is locked during the table scan and other connections are prohibited from accessing the table. The consequence is serious. 7. Do not return unwanted rows or columns during query. Use select Top 100/10 percent to limit the number of rows returned by the user or set rowcount to limit the number of rows to be operated. medium, place the most frequently occurring values at the beginning and the least frequently occurring values at the end, reducing the number of judgments by 10. Generally, redundant rows can be removed before the Group by having clause, so try not to use them to remove rows. Their execution sequence should be optimal as follows: Select WHERE clause Selects all appropriate rows, group by is used to group statistical rows, and having clause is used to remove redundant groups. In this way, the consumption of group by having is small, and queries are fast. Grouping and having large data rows consumes a lot of resources. If the purpose of group by is not to include computation, but to group, use distinct for faster 11. Update multiple records at a time. The score is updated multiple times. Each time, the record is updated fast, that is, the batch processing is good.