9 Ways to Optimize SQL Queries

SQL query optimization is important, just like any other component of your database management system. If you don’t optimize the queries that access your data, the database’s performance will suffer. In many cases, this slowdown can prevent users from accessing the necessary information quickly. This article will talk about various SQL query optimization techniques that can be used to improve query performance and reduce the cost of the solution.

Tip 1. Instead of * use column names in a select statement

If you want to choose only a certain number of columns then column names should be used instead of * in the select statement. Although this is simpler to write, the database will need more time to process the query. By limiting the number of columns you choose, you can decrease the size of the result table, lower network traffic, and improve query performance as a whole.

Example :

Original Query 
Select * from sales;
Improved Query :
Select product_id from sales;        

Tip 2. Instead of HAVING use WHERE to define the filters

A SQL-optimized query will only retrieve the necessary records from the database. HAVING statements are computed after WHERE statements in accordance with the SQL Order of Operations. A WHERE statement is more effective if the goal is to filter a query based on conditions.

Example :

Original query
SELECT customer_id,count(customer_id)
FROM sales
GROUP BY customer_id
HAVING customer_id != '16' AND customer_id != '2';
Improved query:
SELECT customer_id,count(customer_id)
FROM sales
WHERE customer_id != '16'
AND customer_id !='2'
GROUP BY customer_id;        

Tip 3. Avoid Unnecessary distinct conditions

Using a Distinct statement is a handy way to remove duplicates. It works by creating groups in a query. However, a lot of computing power is needed to achieve this goal. Furthermore, data may be inaccurately classified to a certain extent. The solution is to choose more fields to produce distinct results instead of using SELECT DISTINCT.

Example :

Original Query
SELECT DISTINCT FirstName, LastName, State
FROM Teachers;
Improved Query
SELECT FirstName, LastName, Address, State,CourseName,Timings
FROM Teachers;        

Tip 4. Use JOIN instead of a SUBQUERY

The advantage of using join is that it executes faster as compared to subquery. Unlike sub-queries, which will execute all the queries and load all the data to perform the processing, JOINs allow RDBMS to construct an execution plan that is better for your query and can forecast what data should be loaded to be processed and save time.

Example :

Original query
SELECT *
FROM products p
WHERE p.product_id =
(SELECT s.product_id
FROM sales s
WHERE s.customer_id = 2468
AND s.quantity_sold = 12 );
Improved query:
SELECT p.*
FROM products p, sales s
WHERE p.product_id = s.product_id
AND s.customer_id = 2468
AND s.quantity_sold = 12;        

Tip 5. Use In predicate when querying an index column

For indexed retrieval, the IN-list predicate can be used, and the optimizer can sort the IN-list to match the index’s sort order for more effective retrieval. Keep in mind that the IN-list can only contain constants — that is, things that remain the same during a single execution of the query block — like outer references.

Example :

Original query
SELECT *
FROM sales
WHERE product_id = 4
OR product_id = 7;
Improved query:
SELECT *
FROM sales
WHERE product_id IN (4, 7);        

Tip 6. When using table joins that involve tables with one-to-many relationships, use EXISTS rather than DISTINCT.

DISTINCT works by creating groups in a query which takes a lot of computation power. You can use subquery with EXISTS keyword so that you can avoid returning an entire table.

Example :

Original query
SELECT DISTINCT c.country_id, c.country_name
FROM countries c, customers e
WHERE e.country_id = c.country_id;
Improved query:
SELECT c.country_id, c.country_name
FROM countries c
WHERE EXISTS (SELECT * FROM customers e
WHERE e.country_id = c.country_id);        

Tip 7. Use Union ALL instead of Union wherever possible

Union ALL executes faster than Union because, in UNION, duplicates are removed whether they exist or not. Union ALL displays the data with duplicates.

Example :

Original query
SELECT customer_id
FROM sales
UNION
SELECT customer_id
FROM customers;
Improved query:
SELECT customer_id
FROM sales
UNION ALL
SELECT customer_id
FROM customers;        

Tip 8. Avoid using OR in join queries

The query slows down by a factor of 2 if OR is used while joining queries.

Example :

Original query
SELECT *
FROM costs c
INNER JOIN products p ON c.unit_price =
p.product_min_price OR c.unit_price = p.product_list_price;
Improved query:
SELECT *
FROM costs c
INNER JOIN products p ON c.unit_price =
p.product_min_price
UNION ALL
SELECT *
FROM costs c
INNER JOIN products p ON c.unit_price =
p.product_list_price;        

Tip 9. Avoid using aggregate functions on the right side of the operator

Avoiding using aggregate functions on the right side of the operator will optimize SQL queries drastically.

Example :

Original query
SELECT *
FROM sales
WHERE EXTRACT (YEAR FROM TO_DATE (time_id, ‘DD-
MON-YYYY’)) = 2021 AND EXTRACT (MONTH FROM
TO_DATE (time_id, ‘DD-MON-YYYY’)) = 2002;
Improved query:
SELECT * FROM sales
WHERE TRUNC (time_id) BETWEEN
TRUNC(TO_DATE(‘12/01/2001’, ’mm/dd/yyyy’)) AND
TRUNC (TO_DATE (‘12/30/2001’,’mm/dd/yyyy’));        

Conclusion

Query optimization is a regular operation carried out by database administrators, data analysts, and application designers to fine-tune the overall performance of the database system. So following these simple tips will help to optimize the SQL query.