How to create high-performance MySQL index operations using Go language

In large-scale data storage and processing, MySQL is widely used as an efficient and reliable relational database management system. Indexing is one of the most important functions in MySQL, which can speed up query operations and improve system performance. In the process of using Go language to perform MySQL index operations, we need to pay attention to some key points, which will be introduced one by one below.

1. Using table engines

The table engines in MySQL are divided into many types, among which MyISAM and InnoDB are the most commonly used. MyISAM has advantages in read performance, while InnoDB performs better in transaction processing and concurrency, so we recommend using InnoDB as the default table engine. When creating a table, you can specify the ENGINE=InnoDB parameter, for example:

CREATE TABLE users (
  id INT UNSIGNED NOT NULL AUTO_INCREMENT,
  name VARCHAR(50) NOT NULL,
  age INT UNSIGNED NOT NULL,
  PRIMARY KEY (id)
) ENGINE=InnoDB;

2. Create the correct index

The correct index design can greatly improve the performance of the database, and the wrong The index design will reduce query efficiency. When using Go language for MySQL index operations, you need to pay attention to the following points:

(1) Try to avoid using the SELECT * statement, because it will read information from all columns, resulting in low query efficiency. The columns to be queried should be selected based on the actual situation.

(2) The index should be built on a column with high distinction, that is, the more unique the value of the column, the higher the index efficiency. For example, the id field in the user table is a good index column.

(3) When querying in multiple columns, you should try to use joint indexes, that is, merge the indexes of multiple columns into one. For example, a query that queries both the name and age fields in the user table can use the following statement to create a joint index:

CREATE INDEX idx_name_age ON users (name, age);

(4) Avoid using functions or expressions on index columns, because this will make the index unavailable. For example, the UPPER function is used in the following statement to convert the name field, which will invalidate the index:

SELECT * FROM users WHERE UPPER(name) = 'JACK';

(5) Avoid using too long index columns, because this will reduce the efficiency of the index. It is recommended to control the index column within 64 characters.

3. Use connection pool

The connection pool can reduce the number of times the system connects to the MySQL database, thereby improving execution efficiency. In Go language, you can use the DB structure in the golang.org/x/database/mysql package to implement connection pooling. For example:

import (
  "database/sql"
  _ "github.com/go-sql-driver/mysql"
)

func main() {
  db, err := sql.Open("mysql", "user:password@tcp(127.0.0.1:3306)/dbname")
  if err != nil {
    panic(err.Error())
  }
  defer db.Close()

  db.SetMaxIdleConns(10)
  db.SetMaxOpenConns(100)

  // ...
}

Among them, SetMaxIdleConns() specifies the maximum number of idle connections in the connection pool, and SetMaxOpenConns() specifies the maximum number of active connections in the connection pool.

In short, using Go language to create high-performance MySQL index operations requires attention to the design of the index and the use of connection pools. Correct index design can improve query efficiency, and the connection pool can reduce the number of connections to MySQL, thereby improving execution efficiency.

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