让往事随风而去-------------------让一切都随风

To optimize the performance of ORDER BY in SQL, you must first understand its execution mechanism and make rational use of index and query structure. When the sorting field has no index, the database will trigger "filesort", consuming a lot of resources; therefore, direct sorting of large tables should be avoided and the amount of sorted data should be reduced through the WHERE condition. Secondly, establishing a matching index for sorting fields can greatly speed up queries, such as creating reverse order indexes in MySQL 8.0 to improve efficiency. Additionally, deep paging (such as LIMIT 1000, 10) should be used instead with index-based cursor paging (such as WHERE id > 12345) to skip invalid scans. Finally, combining caching, asynchronous aggregation and other means can also further optimize the sorting performance in large data set scenarios.

SQL's ORDER BY is a common way to sort query results, but it can easily become a performance bottleneck when there is a large amount of data or inappropriate use. To make ORDER BY execute faster and more efficiently, the key is to understand its operating mechanism and make rational use of index and query structure.

Understand the execution cost of ORDER BY

ORDER BY essentially rearranges the data in a specified column, which usually requires a complete scan and sort of the database. If the sorting field does not have index support, the database must do "filesort", that is, perform actual sorting operations on memory or disk, which is very resource-consuming.

A common phenomenon is that when you see "Using filesort" appearing in a slow query log, you can basically conclude that the problem lies in ORDER BY . Although databases such as MySQL will try to optimize with memory sorting, once the amount of data exceeds the configuration threshold (such as sort_buffer_size ), it will be degraded to disk sorting, and the speed will be significantly reduced.

suggestion:

• Avoid direct sorting of large tables
• Minimize the amount of sorted data (with WHERE filtering)
• Focus on "Using filesort" in the execution plan

Use indexes to speed up sorting

One of the most effective optimization methods is to establish an appropriate index for sorting fields. When ORDER BY field of the query is consistent with the index order and the query can hit the index, the database can directly obtain ordered data from the index to avoid additional sorting operations.

For example, you often sort by created_at DESC :

 SELECT id, name FROM users ORDER BY created_at DESC LIMIT 10;

Then you can create a reverse order index (supported by MySQL 8.0):

 CREATE INDEX idx_users_created_at_desc ON users(created_at DESC);

If it is an old version, positive order index can also work, but the different directions may affect efficiency.

A few notes:

• Composite indexes should consider whether the field order matches the order of ORDER BY
• If there is still a WHERE condition, the index needs to override the query and sort fields at the same time
• Don't blindly index each sorted field, evaluate based on the actual query frequency.

Optimization techniques for paging and large data sets

When you are facing paging queries with thousands of records, such as:

 SELECT * FROM orders ORDER BY id DESC LIMIT 1000, 10;

This kind of "deep pagination" will cause the database to first fetch the first 1010 and then throw away the first 1000, which is very inefficient.

A common practice is to combine the index to locate the position of the last data and then take it back:

 SELECT * FROM orders WHERE id > 12345 ORDER BY id LIMIT 10;

This skips the previous lot of useless scanning and sorting. The premise is that your sorting field has a unique guarantee (such as auto-increment of the primary key).

Other ideas include:

• Use cache to store results of popular pages
• Use asynchronous aggregation to non-real-time requirements
• Replace traditional OFFSET paging with cursor paging

In general, optimizing ORDER BY is not a profound skill. The key is to understand the data access path and sorting mechanism behind it. Reasonable use of indexes, control data scope, and avoid deep paging can solve most performance problems.

Basically that's it.

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