How Can I Speed Up Row Counting Queries in Large MySQL Tables?

Speeding Up Row Counting in MySQL

Problem:

MySQL queries to count the number of rows in a large table or group them by a particular column can become slow as the table grows. Even indexing the column used for grouping doesn't consistently improve performance.

Exploration:

To optimize these queries, alternative approaches without using caching include:

• Using a Column-Based Storage Engine: This approach may improve count(*) queries, but could compromise performance for other operations.
• Maintaining a Summary Table: Triggers can update a separate summary table each time a row is inserted, deleted, or updated. This approach provides instant row counts during SELECT operations.

Implementation:

For maintaining a summary table, the following boilerplate triggers can be used:

DELIMITER //

CREATE TRIGGER ai_books AFTER INSERT ON books
FOR EACH ROW UPDATE books_cnt SET total = total + 1 WHERE status = NEW.status
//
CREATE TRIGGER ad_books AFTER DELETE ON books
FOR EACH ROW UPDATE books_cnt SET total = total - 1 WHERE status = OLD.status;
//
CREATE TRIGGER au_books AFTER UPDATE ON books
FOR EACH ROW
BEGIN
    IF (OLD.status <> NEW.status)
    THEN
        UPDATE books_cnt SET total = total + IF(status = NEW.status, 1, -1) WHERE status IN (OLD.status, NEW.status);
    END IF;
END
//

By maintaining a summary table, row counting queries can be executed much faster, regardless of the table size.

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