Detailed Explanation of MySQL Index: Key Technologies for Optimizing Query Performance

1. The concept of an index
An index is a data structure in a database that is used to quickly locate and access data in a table. Similar to the catalog of books, indexes can help the database engine quickly find specific data rows without scanning the entire table. MySQL supports multiple index types, including B-tree indexes, hash indexes, and full-text indexes.

Two, B-tree index
B-tree index is the most commonly used index type in MySQL. It is a balanced tree structure, suitable for range lookup and exact lookup. The B-tree index stores data in the order of the keys, and quickly locates the target data by splitting the tree nodes layer by layer.

3. Hash index
Hash index is suitable for equivalent query, but does not support range query. It associates the hash value of the index key with the storage location of the data row, which can quickly locate a specific value. However, hash indexes are not sensitive to the order of index keys, and may cause hash collisions in some cases, affecting query performance.

4. Full-text index
Full-text index is used for keyword search in text data. It can provide more advanced search functions, such as full-text search, fuzzy matching and semantic search. MySQL's full-text index function is based on the inverted index, which can greatly improve the query efficiency of columns containing text content.

5. Optimize index design

1. Select the appropriate index type: Select the appropriate index type according to the query mode and data characteristics to avoid unnecessary index operations.

2. Determine the index column: Select the column that is often used in query conditions, join conditions, or sorting operations as the index column to improve query efficiency.

3. Consider composite indexes: For queries involving multiple columns, using composite indexes can better meet query requirements and avoid creating too many single-column indexes.

4. Avoid redundant indexes: Delete unnecessary redundant indexes to reduce the cost of index maintenance.

5. Pay attention to the index length: control the length of the index column to avoid performance degradation caused by too long indexes.

6. Regular index maintenance: Regularly check the usage of the index, optimize and rebuild the index to maintain the high efficiency of the index.