Clustered index determines the physical storage order of data, and each table can only have one; non-clustered indexes create independent structures, and there can be multiple ones. 1. Clustered indexes are suitable for columns with high uniqueness, frequent queries, and many range queries, such as primary keys or commonly used filtering condition fields, but will affect the insertion performance. 2. Non-clustered indexes are suitable for different query scenarios. Data rows are positioned through pointers and support multi-field composite indexes. The most frequently filtered fields should be placed in front of them, and overwrite indexes can be built to avoid back-to-table queries. 3. When creating an index, you need to weigh the read and write performance to avoid excessive indexes that increase maintenance overhead and occupy additional space. You should analyze the query mode in combination with the execution plan and design reasonably to achieve the optimal effect.

Creating indexes in SQL is an important way to improve query performance, especially when you are processing large amounts of data. Understanding and rationally using Clustered Index and Non-Clustered Index can significantly optimize database efficiency.

What is clustered index?

Clustered index determines the physical storage order of data in the table. Each table can only have one clustered index, because the data rows themselves can only be sorted in one way. Usually the primary key is established as a clustered index by default, but you can also manually specify other fields as clustered indexes according to the query requirements.

For example, if you frequently filter order information based on "order date", it may be more appropriate to set the clustered index to "order date", so that the data will be stored in chronological order on disk and scan faster.

suggestion:

• Select columns with high uniqueness, frequent queries, and many range queries as clustered indexes.
• Clustered indexes have a certain impact on insertion performance, because the data sequence needs to be maintained, which may cause page splits.
• If your primary key is an autoincrement ID, it is usually a good clustered index candidate.

How to use non-clustered indexes?

Instead of changing the storage order of the data itself, nonclustered indexes create a separate structure containing the index column and pointers to the actual data rows (a clustered key in the clustered index table). You can create multiple nonclustered indexes on a table, suitable for different query scenarios.

For example, if you frequently look up orders through "customer name", you can create a nonclustered index on this field. When the query hits the index, the database engine can quickly locate the corresponding clustered index key and then find the complete record.

A few things to note:

• Nonclustered indexes take up additional storage space and affect write performance (INSERT, UPDATE, DELETE).
• Composite indexes containing multiple fields should be properly arranged in the order of fields, and the fields that are most commonly used for filtering are placed in front.
• You can consider using "overwrite index", that is, the index contains all the fields required for the query to avoid back-to-table query.

Basic syntax for creating indexes

SQL Server and most SQL-enabled database systems provide statements for creating indexes:

 --Create clustered index CREATE CLUSTERED INDEX IX_Orders_OrderDate
ON Orders(OrderDate);

--Create nonclustered index CREATE NONCLUSTERED INDEX IX_Customers_Name
ON Customers(CustomerName);

If it is a composite index:

 CREATE NONCLUSTERED INDEX IX_Orders_CustomerID_Status
ON Orders(CustomerID, Status);

Note that different database systems may have some differences. For example, there is no CLUSTERED keyword in MySQL, but instead, clustered indexes are automatically managed through primary keys.

Summarize common misunderstandings

Many people think that the more indexes, the better, but in fact it is not. Indexing is not a free lunch, it brings overhead in the following aspects:

• Insert and update are slower because indexes also need to be updated
• Take up more disk space
• Query optimizer may ignore inefficient indexes, causing waste

Therefore, before creating an index, you should first analyze the query pattern, view the execution plan, and find out missing indexes or high-cost operations. The "Show Execution Plan" feature in tools such as SQL Server Management Studio (SSMS) can help you determine whether you need to add an index.

Basically that's it. Index design is a balanced art, which takes care of reading performance and cannot ignore write overhead.

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