Understanding the ANALYZE TABLE Statement in MySQL 8.4

The ANALYZE TABLE statement in MySQL is a crucial tool for database administrators and developers seeking to optimize database performance. This statement gathers and stores statistics about table data and index distributions, which the MySQL optimizer uses to make informed decisions about query execution plans. In this article, we'll delve deep into the ANALYZE TABLE statement, covering its syntax, usage, and impact on query performance in MySQL 8.4.

What Does ANALYZE TABLE Do?

The ANALYZE TABLE statement serves a vital role in maintaining an efficient MySQL database. It primarily performs two key functions:

• Key Distribution Analysis: This involves analyzing the distribution of key values within a table's indexes. The collected statistics help the optimizer choose the most efficient index for query execution.
• Histogram Statistics Analysis: This generates and manages histogram statistics for table column values, providing insights into the data distribution within specific columns.

By providing the MySQL optimizer with accurate and up-to-date information, ANALYZE TABLE helps ensure that queries are executed in the most efficient manner possible.

Syntax of the ANALYZE TABLE Statement

The ANALYZE TABLE statement offers several variations in its syntax, accommodating different analysis requirements. Here's a breakdown of the available options:

• Basic Syntax (Key Distribution Analysis):

  ANALYZE [NO_WRITE_TO_BINLOG | LOCAL] TABLE tbl_name [, tbl_name] ...
  

  This form performs a key distribution analysis on the specified table(s).

• Histogram Management Syntax:

  ANALYZE [NO_WRITE_TO_BINLOG | LOCAL] TABLE tbl_name
  UPDATE HISTOGRAM ON col_name [, col_name] ... [WITH N BUCKETS] [{MANUAL | AUTO} UPDATE]
  ANALYZE [NO_WRITE_TO_BINLOG | LOCAL] TABLE tbl_name
  UPDATE HISTOGRAM ON col_name [USING DATA 'json_data']
  ANALYZE [NO_WRITE_TO_BINLOG | LOCAL] TABLE tbl_name
  DROP HISTOGRAM ON col_name [, col_name] ...
  

  These variations allow you to create, update, or drop histogram statistics for specific columns within a table.

Required Privileges

To execute the ANALYZE TABLE statement, you must have the SELECT and INSERT privileges for the table being analyzed. These privileges are necessary because the statement reads data from the table and may update statistics tables in the data dictionary.

Supported Storage Engines

The ANALYZE TABLE statement is compatible with the following storage engines:

• InnoDB
• NDB
• MyISAM

It is important to note that ANALYZE TABLE does not work with views.

Key Distribution Analysis in Detail

When executed without the HISTOGRAM clause, ANALYZE TABLE focuses on key distribution analysis. Here's what you need to know:

• Purpose: To analyze the distribution of key values within a table's indexes.
• Impact: The optimizer uses this information to determine the optimal order for joining tables and to select the most appropriate indexes for query execution.
• Checking Cardinality: You can examine the stored key distribution cardinality using the SHOW INDEX statement or by querying the INFORMATION_SCHEMA.STATISTICS table. You can find more about the INFORMATION_SCHEMA here.
• InnoDB Considerations: For InnoDB tables, ANALYZE TABLE estimates index cardinality by performing random dives on index trees. The accuracy of these estimates can be improved by enabling innodb_stats_persistent.
• Persistent Statistics: When innodb_stats_persistent is enabled, it's crucial to run ANALYZE TABLE after significant changes to index column data.
• Join Optimization: If a join query is not optimized correctly, running ANALYZE TABLE can help the optimizer make better decisions. In cases where ANALYZE TABLE doesn't provide sufficient information, you can use FORCE INDEX or adjust the max_seeks_for_key system variable. To find out more about optimization-related problems, check this out.

Histogram Statistics Analysis in Detail

The HISTOGRAM clause provides granular control over histogram statistics. Let's explore the available operations:

• UPDATE HISTOGRAM: Generates histogram statistics for specified columns and stores them in the data dictionary.
  • You can specify the number of buckets using the WITH N BUCKETS clause (N must be between 1 and 1024). The default is 100 buckets.
  • The AUTO UPDATE clause enables automatic histogram updates when the table is analyzed or when persistent statistics are recalculated.
  • The MANUAL UPDATE clause disables automatic updates (this is the default).
• DROP HISTOGRAM: Removes histogram statistics for specified columns from the data dictionary.
• USING DATA: Allows setting the histogram of a single column to a user-defined JSON value

Additional important information

• DDL Statements: DROP TABLE, DROP DATABASE, RENAME TABLE, and ALTER TABLE statements can affect histogram statistics.
• Memory Management: The histogram_generation_max_mem_size system variable controls the maximum memory available for histogram generation.
• Sampling: If the estimated data size exceeds the histogram_generation_max_mem_size limit, MySQL samples the data. The sampling-rate value in the COLUMN_STATISTICS table indicates the fraction of data sampled.

Other Considerations

• ANALYZE TABLE clears table statistics from the INNODB_TABLESTATS table and sets the STATS_INITIALIZED column to Uninitialized. Statistics are collected again the next time the table is accessed.

By understanding and effectively utilizing the ANALYZE TABLE statement, MySQL administrators and developers can significantly improve query performance and maintain a healthy, optimized database environment.