MySQL uses row and column data structures to organize data, and provides storage engines (such as InnoDB, which uses B-tree indexes) to find data efficiently. Index structures such as B-tree indexes, hash indexes, bitmap indexes, and full-text indexes are optimized based on data type and query type to improve data retrieval speed.
Data structures used by MySQL
MySQL is a relational database management system that uses the following data structures To store and organize data:
Rows and columns
- Database data is stored in tables, and each table consists of rows and columns.
- Rows represent specific data records, while columns represent specific fields or attributes in the record.
- Rows in a table are unique and identified by a primary key.
Storage Engine
- MySQL provides different storage engines, each of which has its own specific way of managing data.
- The most commonly used storage engine is InnoDB, which uses B-tree indexes to quickly find data.
B Tree index
- B Tree index is a balanced search tree structure used to find data quickly.
- It organizes the data in the table into a series of ordered pages, each page has its own index key.
- Index keys are used to quickly find specific rows, while the B-tree structure allows efficient traversal of the data.
Hash index
- A hash index is an index structure that uses a hash function to map data to index keys.
- Hash functions convert data values into unique keys for fast lookups.
- Hash indexes are very efficient for finding single values based on the equals operator.
Bitmap index
- A bitmap index is an index structure that maps data values to a bitmap.
- A bitmap is a series of bits, each of which represents the presence or absence of a data value.
- Bitmap indexes are very efficient for finding set comparisons involving multiple values.
Full-text index
- Full-text index is an index structure used to search text data such as documents or emails.
- It tokenizes text data and stores it in an index for fast searching for specific words or phrases.
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