DISTINCT deduplication by sorting or hashing, but affects performance. 1. Working principle: The database forces a unique combination value to return, and often recognizes duplicate rows through sorting or hashing operations, consuming memory, CPU and even I/O resources. 2. Source of performance problems: large data set scanning, sorting/hashing overhead, unused indexing and misuse. 3. Optimization method: confirm whether you need to deduplicate, replace it with GROUP BY, create a suitable index, and combine it with LIMIT pagination. 4. Be cautious when using it with JOIN: it takes time to connect and expand the result set before deduplication, and can be replaced by EXISTS or subqueries.

Using the DISTINCT keyword is common in SQL queries, but many people just know that it can "deduplicate", but they don't know what's going on behind it. In fact, DISTINCT not only affects the structure of the result set, but may also have a significant impact on query performance, especially when the data volume is large.

1. How does DISTINCT work?

When you use DISTINCT on one or more fields, the database forces a unique combination value that is not duplicated. For example:

 SELECT DISTINCT department FROM employees;

This statement returns all different department names. To do this, the database usually performs sort or hash operations to identify and remove duplicate rows.

This process can consume a lot of memory and CPU resources, especially when the amount of data being processed is large. Some databases are sorted in temporary disk space, which also brings I/O overhead.

2. Where do DISTINCT performance problems come from?

The most common performance bottlenecks DISTINCT appear in the following aspects:

• Large dataset scan : If the original table is very large, even if the final result set is small, you need to scan the entire table first.
• Sorting/hashing operations are expensive : deduplication requires additional calculation steps, which are usually resource-intensive.
• Indexes are not utilized : If there is no suitable index to support deduplication fields, the database may only be able to do full table scans.
• Misuse leads to unnecessary overhead : Sometimes the data itself is not duplicated, but DISTINCT is still added, which is a redundant operation.

For example, if you wrote:

 SELECT DISTINCT name FROM users WHERE status = 'active';

In fact, name field itself is unique (for example, the user name does not allow duplication), so adding DISTINCT here is a waste of time.

3. How to optimize or replace DISTINCT?

In actual development, the following ways can be considered to reduce the performance burden caused by DISTINCT :

• ?Confirm whether it really needs to be deduplicated
  First check whether there are duplications in the data, and then decide whether to use DISTINCT . In many cases, data is naturally unique.

• ?Use GROUP BY instead
  In some database systems, GROUP BY and DISTINCT are actually executed the same plan, but are more semantically clearer, especially when you still need aggregate functions.

   SELECT department FROM employees GROUP BY department;

• ?Create a suitable index
  If you often need to deduplicate a field, you can index it on the field so that the database can quickly locate different values.

• ?Pagination or limit return quantity
  If you only need the first few different records, you can use it in conjunction with LIMIT to avoid scanning all data.

4. Be careful when combining DISTINCT and JOIN

Using DISTINCT in queries involving multiple table joins can easily cause performance problems. Because the connection itself will expand the result set, it will be even more difficult to remove the heavy load.

For example, the following writing method:

 SELECT DISTINCT u.name
FROM users u
JOIN orders o ON u.id = o.user_id
WHERE o.amount > 100;

If a user has multiple orders that meet the criteria, then u.name will appear multiple times, so DISTINCT is needed. But a better approach might be to use EXISTS or subquery instead:

 SELECT u.name
FROM users u
WHERE EXISTS (
    SELECT 1
    FROM orders o
    WHERE o.user_id = u.id AND o.amount > 100
);

This not only makes the logic clearer, but also avoids unnecessary duplication and sorting.

Overall, DISTINCT is a practical but easily abused keyword. It is best to understand the data structure and distribution before use, and view its real overhead through execution plans if necessary. Basically, if you master these points, you can write more efficient SQL queries in most scenarios.

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