Query optimization in MySQL is essential for improving database performance, especially when dealing with large data sets

1. Use the correct index

• Index speeds up data retrieval by reducing the amount of data scanned

 select * from employees where last_name = 'smith';

• If you look up a column in a table multiple times, create an index for that column

• Create a composite index if you or your app needs data from multiple columns based on the criteria

2. Avoid choosing*

• Select only those columns you need, if you select all the columns you don't need, this will only consume more server memory and cause the server to slow down at high load or frequency times

For example, your table contains columns like created_at and updated_at and timestamps, and then avoid selecting * because they are not required under normal circumstances

Inefficient query

 select * from orders where order_date > '2023-01-01';

Optimize query

 select order_id, customer_id from orders where order_date > '2023-01-01';

1. Optimize connections

• Make sure that the index exists on the columns used in the join condition.

If you use primary key to join the table, you don't need to create it because the primary key is already an index

 select orders.order_id, customers.name from orders
join customers on orders.customer_id = customers.id
where customers.country = 'usa';

In the above query, orders.customer_id needs to be indexed and its relationship with another table

customers.id is the primary key of the customers table, so there is no need to create an index

customers.country needs to be indexed because it is a conditional

5. Avoid subqueries; use connection instead

6. Use query cache

• If your query results do not change frequently, use mysql's query cache.

For example, user and order lists and other infrequently changed content

7. Partition the large table

 CREATE TABLE orders (
    order_id INT NOT NULL,
    order_date DATE NOT NULL,
    ...
    PRIMARY KEY (order_id, order_date)
)
PARTITION BY RANGE (YEAR(order_date)) (
    PARTITION p0 VALUES LESS THAN (2000),
    PARTITION p1 VALUES LESS THAN (2010),
    PARTITION p2 VALUES LESS THAN (2020),
    PARTITION p3 VALUES LESS THAN MAXVALUE
);

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