InnoDB handles SELECT COUNT(*) and SELECT COUNT(1) operations in the same way. There is no performance difference.

MySQL :: MySQL 8.0 Reference Manual :: 12.20.1 Aggregate Function Descriptions https://dev.mysql.com/doc/refman/8.0/en/aggregate-functions.html#function_count

• COUNT(expr) [over_clause]

  Returns a count of the number of non-NULL values of expr in the rows retrieved by a SELECT statement. The result is a BIGINT value.

  If there are no matching rows, COUNT() returns 0. COUNT(NULL) returns 0.

  This function executes as a window function if over_clause is present. over_clause is as described in Section 12.21.2, “Window Function Concepts and Syntax”.

  mysql> SELECT student.student_name,COUNT(*)
         FROM student,course
         WHERE student.student_id=course.student_id
         GROUP BY student_name;

  COUNT(*) is somewhat different in that it returns a count of the number of rows retrieved, whether or not they contain NULL values.

  For transactional storage engines such as InnoDB, storing an exact row count is problematic. Multiple transactions may be occurring at the same time, each of which may affect the count.

  InnoDB does not keep an internal count of rows in a table because concurrent transactions might “see” different numbers of rows at the same time. Consequently, SELECT COUNT(*) statements only count rows visible to the current transaction.

  As of MySQL 8.0.13, SELECT COUNT(*) FROM tbl_name query performance for InnoDB tables is optimized for single-threaded workloads if there are no extra clauses such as WHERE or GROUP BY.

  InnoDB processes SELECT COUNT(*) statements by traversing the smallest available secondary index unless an index or optimizer hint directs the optimizer to use a different index. If a secondary index is not present, InnoDB processes SELECT COUNT(*) statements by scanning the clustered index.

  Processing SELECT COUNT(*) statements takes some time if index records are not entirely in the buffer pool. For a faster count, create a counter table and let your application update it according to the inserts and deletes it does. However, this method may not scale well in situations where thousands of concurrent transactions are initiating updates to the same counter table. If an approximate row count is sufficient, use SHOW TABLE STATUS.

  InnoDB handles SELECT COUNT(*) and SELECT COUNT(1) operations in the same way. There is no performance difference.

  For MyISAM tables, COUNT(*) is optimized to return very quickly if the SELECT retrieves from one table, no other columns are retrieved, and there is no WHERE clause. For example:

  mysql> SELECT COUNT(*) FROM student;

  This optimization only applies to MyISAM tables, because an exact row count is stored for this storage engine and can be accessed very quickly. COUNT(1) is only subject to the same optimization if the first column is defined as NOT NULL.

• COUNT(DISTINCT expr,[expr...])

  Returns a count of the number of rows with different non-NULL expr values.

  If there are no matching rows, COUNT(DISTINCT) returns 0.

  mysql> SELECT COUNT(DISTINCT results) FROM student;

  In MySQL, you can obtain the number of distinct expression combinations that do not contain NULL by giving a list of expressions. In standard SQL, you would have to do a concatenation of all expressions inside COUNT(DISTINCT ...).

 

MySQL :: MySQL 8.0 Reference Manual :: 3.3.4.8 Counting Rows https://dev.mysql.com/doc/refman/8.0/en/counting-rows.html

MySQL :: MySQL 8.0 Reference Manual :: 13.7.7.38 SHOW TABLE STATUS Statement https://dev.mysql.com/doc/refman/8.0/en/show-table-status.html

Rows

The number of rows. Some storage engines, such as MyISAM, store the exact count. For other storage engines, such as InnoDB, this value is an approximation, and may vary from the actual value by as much as 40% to 50%. In such cases, use SELECT COUNT(*) to obtain an accurate count.

The Rows value is NULL for INFORMATION_SCHEMA tables.

For InnoDB tables, the row count is only a rough estimate used in SQL optimization. (This is also true if the InnoDB table is partitioned.)