Mastering MySQL Indexes: Costs, Pitfalls, and Best Practices
This article walks through practical MySQL index usage, illustrating space and time costs, back‑table overhead, covering indexes and index condition pushdown, common scenarios where indexes fail, and concrete best‑practice guidelines, all demonstrated with a 5‑million‑row InnoDB table and real SQL examples.
Introduction
The article explains how to use MySQL indexes effectively. An InnoDB table user_innodb with more than 5 million rows is created, containing columns id (primary key), name, gender, phone, and a composite index on (name, phone):
CREATE TABLE `user_innodb` (
`id` int NOT NULL AUTO_INCREMENT,
`name` varchar(255) DEFAULT NULL,
`gender` tinyint(1) DEFAULT NULL,
`phone` varchar(11) DEFAULT NULL,
PRIMARY KEY (`id`),
INDEX IDX_NAME_PHONE (name, phone)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;Signed-in readers can open the original source through BestHub's protected redirect.
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