{"id":163,"date":"2026-07-26T00:29:43","date_gmt":"2026-07-25T16:29:43","guid":{"rendered":"http:\/\/www.avafoodie.com\/blog\/?p=163"},"modified":"2026-07-26T00:29:43","modified_gmt":"2026-07-25T16:29:43","slug":"how-to-find-duplicate-rows-in-a-table-in-sql-4648-78e7b8","status":"publish","type":"post","link":"http:\/\/www.avafoodie.com\/blog\/2026\/07\/26\/how-to-find-duplicate-rows-in-a-table-in-sql-4648-78e7b8\/","title":{"rendered":"How to find duplicate rows in a table in SQL?"},"content":{"rendered":"

Hey there! I’m a Table supplier, and in the world of data management, SQL is like a superhero tool. One common headache many database users face is finding duplicate rows in a table. It might sound like a small problem, but it can really mess up your data analysis and reporting. So, I’m gonna walk you through different ways to find those pesky duplicate rows in SQL. Table<\/a><\/p>\n

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Why Duplicates Matter<\/h3>\n

Before we dive into the how-to, let’s quickly chat about why finding duplicates is important. Duplicate rows can bloat your database, making it slower to query. They can also lead to inaccurate reports and analysis since the same data gets counted multiple times. For example, if you’re tracking sales data and have duplicate entries, your sales figures might be inflated. As a Table supplier, I know how crucial it is to have clean and accurate data, whether it’s stored in our tables or not.<\/p>\n

Using GROUP BY and HAVING<\/h3>\n

One of the most common ways to find duplicate rows in SQL is by using the GROUP BY<\/code> and HAVING<\/code> clauses. The basic idea is to group the rows by the columns you think might have duplicates and then filter out the groups that have more than one row.<\/p>\n

Let’s say you have a table called customers<\/code> with columns customer_id<\/code>, name<\/code>, email<\/code>, and phone<\/code>. You suspect there might be duplicate customers based on their email addresses. Here’s how you can find them:<\/p>\n

SELECT email, COUNT(*)\nFROM customers\nGROUP BY email\nHAVING COUNT(*) > 1;\n<\/code><\/pre>\n
In this query, we first group the rows by the email<\/code> column using GROUP BY<\/code>. Then, we use the COUNT(*)<\/code> function to count the number of rows in each group. Finally, we use the HAVING<\/code> clause to filter out the groups that have more than one row. The result will be a list of email addresses that appear more than once in the table, along with the number of times they appear.<\/p>\n
If you want to see the actual duplicate rows, you can use a subquery:<\/p>\n
SELECT *\nFROM customers\nWHERE email IN (\n    SELECT email\n    FROM customers\n    GROUP BY email\n    HAVING COUNT(*) > 1\n);\n<\/code><\/pre>\n
This query first finds the duplicate email addresses using the subquery, and then it selects all the rows from the customers<\/code> table where the email address is one of the duplicate addresses.<\/p>\n
Using Window Functions<\/h3>\n
Window functions are another powerful tool for finding duplicate rows in SQL. They allow you to perform calculations across a set of rows that are related to the current row.<\/p>\n
Let’s use the same customers<\/code> table as before. Here’s how you can use a window function to find duplicate rows based on the email<\/code> column:<\/p>\n
SELECT customer_id, name, email, phone\nFROM (\n    SELECT customer_id, name, email, phone,\n           ROW_NUMBER() OVER (PARTITION BY email ORDER BY customer_id) as rn\n    FROM customers\n) sub\nWHERE rn > 1;\n<\/code><\/pre>\n
In this query, we first use the ROW_NUMBER()<\/code> window function to assign a unique number to each row within each group of rows that have the same email address. The PARTITION BY<\/code> clause divides the rows into groups based on the email<\/code> column, and the ORDER BY<\/code> clause determines the order in which the numbers are assigned.<\/p>\n
Then, we use a subquery to select all the rows where the row number is greater than 1. These are the duplicate rows.<\/p>\n
Using SELF JOIN<\/h3>\n
Another way to find duplicate rows is by using a self join. A self join is when you join a table to itself.<\/p>\n
Let’s say you want to find duplicate rows in the customers<\/code> table based on the name<\/code> and phone<\/code> columns. Here’s how you can do it:<\/p>\n
SELECT c1.*\nFROM customers c1\nJOIN customers c2\nON c1.name = c2.name AND c1.phone = c2.phone\nAND c1.customer_id < c2.customer_id;\n<\/code><\/pre>\n
In this query, we join the customers<\/code> table to itself using the JOIN<\/code> clause. We use the ON<\/code> clause to specify the conditions for the join, which are that the name<\/code> and phone<\/code> columns must be the same in both tables.<\/p>\n
We also add the condition c1.customer_id < c2.customer_id<\/code> to avoid selecting the same row twice. This condition ensures that we only select duplicates where the customer_id<\/code> of the first row is less than the customer_id<\/code> of the second row.<\/p>\n
Which Method to Choose?<\/h3>\n
So, which method should you use to find duplicate rows? Well, it depends on your specific situation.<\/p>\n