Common Mistakes in SQL Queries and How to Avoid Them

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SQL (Structured Query Language) is a powerful tool for managing and manipulating data in relational databases.       However, even experienced developers can make mistakes when writing SQL queries, leading to performance issues, incorrect results, or security vulnerabilities. We all make mistakes and learn from them. It is a good practice to make mistakes but not repeat them in the future.  In this article, we will discuss some common SQL mistakes and provide tips on how to avoid them.

  1. Order of Execution of the Query

One of the crucial points that should not be ignored at any cost is the order of execution of a particular query. The order needs to be in the below format, or the output won’t be the desired one, and sometimes it even creates an error in the query.

Getting the Data (From, Join)

Filtering the Row (Where)

Grouping (Group by)

Group Filter (Having)

Return Expressions (Select)

Order & Paging (Order by & Limit / Offset)

  1. Know the best plan for your query

Save yourself the trouble by planning and executing the command for the big queries. The last thing you want to do is execute a big query with too many nested loops.Always make a habit of planning and structuring the query format and even testing out the query with the sample data.

  1. Not Using Indexes:

Failing to use indexes can severely impact query performance, especially on large tables. It's essential to identify columns that are frequently used in WHERE, JOIN, or ORDER BY clauses and create indexes on those columns.

Incorrect Query:

SELECT * FROM payments WHERE payment_date = '2024-05-01';

Corrected Query (with Index):

SELECT * FROM payments WHERE payment_date = '2024-05-01'

AND customer_id = 123;

  1. Never use Select *

Using SELECT * to retrieve all columns from a table is not only inefficient but can also lead to unexpected results, especially when the table structure changes. Not to use select * is mainly for performance and security reasons. For the following example.

Incorrect Query

SELECT * FROM payments

Corrected Query

SELECT payment_id, payment_amount, payment_date FROM payment

  1. Not Handling NULL Values Properly:

NULL is a special marker in SQL that represents the absence of a value. Many developers make the mistake of using the equality operator (=) to compare NULL values, which doesn't work as expected. To handle NULL values correctly, you should use the IS NULL or IS NOT NULL operators instead of equality operators.

  1. Using DISTINCT unnecessarily

The DISTINCT keyword is a powerful tool in SQL that allows you to remove duplicate rows from the results of a query. However, using DISTINCT can also have a negative impact on PostgreSQL performance, especially when it is used unnecessarily.

To avoid using DISTINCT unnecessarily, it’s important to carefully consider whether it is needed for your queries. In some cases, you may be able to rewrite your queries to avoid the need for DISTINCT. For example, you may be able to use a GROUP BY clause to group the results and eliminate duplicates.

  1. Use EXISTS() Instead of COUNT()

Though you can use both EXIST() and COUNT() to discover whether the table has a specific record, using EXIST() is more effective. While COUNT() will search the entire table to provide the total number of matching records, EXIST() will only run until it locates the record’s first entry in the table, saving you time and computing power and enabling you to optimize SQL queries.



In conclusion, when it comes to writing efficient SQL queries, it is important to avoid some common mistakes. To avoid these mistakes, it is important to carefully analyse the data and the requirements of the query and choose the most appropriate approach. This may involve using indexing, optimizing queries for performance, and minimizing data transfers. Always double-check your queries before executing them and test them thoroughly to ensure they return the expected results.


- Bhagyashree Patil

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