What types of indexes are there in mysql?

MySQL index can quickly find data by storing column values ​​and data pointers in key-value pairs. Common index types include: B-Tree index: supports range queries and has good performance when the amount of data is large. Hash index: Exact matching query is fast, but updating data is expensive. Full-text indexing: Index text data and support full-text search. Spatial index: Index geospatial data and support spatial queries. Concurrent B-Tree index: better performance in high concurrency environment. Covering Index: Contains the required data without accessing the table. When choosing an index, consider your data type, query pattern, and performance requirements.

MySQL Index Type

An index is a structure in MySQL used to quickly find and retrieve data. They do this by creating key-value pairs in a data table, where the key is a specific column or combination of columns of data and the value is a pointer to that data.

MySQL provides several types of indexes, each with its own advantages and disadvantages:

B-Tree Index

• The most commonly used index type
• Supports range queries (for example, all records between x and y)
• Has good performance when the amount of data is large

Hash index

• Suitable for exact match queries (for example, finding records with a specific ID)
• Faster than B-Tree indexes , but the overhead is greater when updating data

Full-text index

• For indexing text data
• Supports full-text search, Includes a search word or phrase

Spatial index (R-tree index)

• Used to index geospatial data (e.g., longitude and latitude)
• Support spatial query, such as finding records in a specific area

Concurrent B-Tree index

• B-Tree index Variant
• Provides better performance in high concurrency environments

Covering index

• Contains all the information required by the query Column data
• Eliminates the need for disk access to the underlying table

Choosing the right index

Choosing the right index depends on Data types, query patterns, and performance requirements. Here are some suggestions:

• For columns that are frequently used in range queries, use B-Tree indexes.
• For exact match queries, use a hash index.
• For text searches, use full-text indexing.
• For geospatial queries, use a spatial index.
• For high-concurrency environments, please use concurrent B-Tree indexes.
• For queries that return the required data without accessing the table, use a covering index.

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