Eliminating Duplicate Rows Made Easy with CTE and ROW_NUMBER() Function

Deleting Duplicate Rows from SQL Table Using CTE and ROW_NUMBER() Function

When it comes to managing large datasets, it is quite common to encounter duplicate rows in a SQL table. Duplicate rows not only make it difficult to analyze and interpret data but they can also slow down your query performance.

Fortunately, there is an effective way to remove duplicate rows from a SQL table using Common Table Expression (CTE) and ROW_NUMBER() function.

CTE is a powerful feature in SQL Server that allows you to define a temporary result set that can be referred to within a SELECT, INSERT, UPDATE, or DELETE statement.

ROW_NUMBER() function assigns a unique incremental number to each row within a result set according to the specified ORDER BY clause. By combining CTE with ROW_NUMBER(), we can easily identify and remove duplicate rows from a SQL table.

Let’s take a closer look at how to delete duplicate rows from a SQL table using CTE and ROW_NUMBER() function:

Step 1: Create a CTE with ROW_NUMBER()

To start off, we need to define a CTE that contains the ROW_NUMBER() function. The CTE should return all columns in the SQL table along with the unique incremental numbers assigned to each row based on a specified ORDER BY clause.

For example, if we have a table called “Customers” with columns “Name”, “Address”, “Phone”, and “Email”, the CTE would look like this:


WITH CTE AS (
SELECT Name, Address, Phone, Email,
ROW_NUMBER() OVER (
PARTITION BY Name, Address, Phone, Email
ORDER BY Name
) AS RowNum
FROM Customers
)


In this CTE, we are partitioning the results by “Name”, “Address”, “Phone”, and “Email” columns and ordering them by “Name”.

Step 2: Delete duplicate rows

Now that we have a CTE that assigns a unique number to each row in the SQL table, we can use this CTE to delete duplicate rows.

We can simply use a DELETE statement to remove all rows where the RowNum is greater than 1.


DELETE FROM CTE
WHERE RowNum > 1


This will delete all duplicate rows from the SQL table and keep only one row with unique values in the “Name”, “Address”, “Phone”, and “Email” columns.

Example: Duplicate Employee Records

Let’s say you have a large employee data table with thousands of records, and you discover that there are many duplicates.

This can occur when data gets duplicated or there are issues with data quality. Here is an example SQL table with duplicate employee records:

As you can see in this example, there are duplicates with the same FirstName, LastName, and Email.

Let’s use CTE and ROW_NUMBER() function to remove these duplicates.

Step 1: Create CTE with ROW_NUMBER()

We write a CTE that has a ROW_NUMBER function to partition the data by “FirstName”, “LastName”, and “Email”.

This allows us to assign unique IDs to each distinct Employee record and filter out those with duplicates.


WITH EmployeeCTE AS (
SELECT EmployeeID, FirstName, LastName, Email, Phone,
ROW_NUMBER() OVER (
PARTITION BY FirstName, LastName, Email ORDER BY EmployeeID
) AS RowNum
FROM EmployeeData
)


Step 2: Delete duplicate rows

After creating a CTE, we now use the DELETE statement to remove all rows where the RowNum is greater than 1.


DELETE FROM EmployeeCTE
WHERE RowNum > 1


This will delete all duplicate rows from the EmployeeData table and keep only one row with unique values.

In conclusion, removing duplicate rows from a SQL table is essential for keeping data clean and improving query performance.

Using CTE and ROW_NUMBER() function is an effective and easy way to achieve this task and can save you a lot of time searching through duplicates manually.

Deleting Duplicate Rows using CTE and ROW_NUMBER() Function

Duplicate rows in SQL tables can often cause complications when dealing with large datasets.

They not only make it difficult to obtain accurate results, but they can also affect query performance. Luckily, we can use Common Table Expressions (CTE) and ROW_NUMBER() function to identify and delete duplicates.

In this article, we will look at an alternative solution using CTE and a Duplicate Count Column to delete duplicate rows in SQL.

Creating CTE with Duplicate Count Column

In this solution, we will use a CTE to create a new column for the duplicate count. The duplicate count column will count the number of times a value occurs in a table and then assign each row a value.

Afterward, we can use this column to delete duplicate rows from the table. Heres an example of the CTE that creates a duplicate count column:


WITH CTE AS (
SELECT [Column1], [Column2], [Column3], [Column4], [Column5],
ROW_NUMBER() OVER(PARTITION BY [Column1], [Column2], [Column3], [Column4], [Column5] ORDER BY [Column1]) AS [DuplicateCounter]
FROM [TableName]
)


Note that the CTE uses the PARTITION BY clause to group the columns according to a specific set of conditions. Here, we are using five columns named Column1, Column2, Column3, Column4, and Column5.

Deleting Duplicate Rows

After creating the CTE, we can use the DELETE statement to delete all rows with a higher value than 1 in the DuplicateCounter column. This statement will remove duplicates from the table.


DELETE
FROM CTE
WHERE [DuplicateCounter] > 1


Once the duplicates have been deleted from the table, you can use the table for your analysis purposes without worrying about inaccurate results and performance.

Discussion on the Solution

Lets dive deeper into this solution and explore the CTE with duplicate count column and how we can use it to delete duplicates from the table.

Explanation of CTE and Duplicate Count Column

Common Table Expressions (CTE) are temporary result sets that are defined within an SQL statement and are not stored in a database by themselves. They allow us to create named temporary results that can be referenced within the scope of a SELECT, INSERT, UPDATE, or DELETE statement.

In our case, we used a CTE to create a new column for duplicate count. This column assigns a unique number to each row in the table based on the criteria we specified in the PARTITION BY clause.

The PARTITION BY clause divides the input into separate partitions according to the specified partition expression. Here, we have partitioned the input by Column1, Column2, Column3, Column4, and Column5.

The ORDER BY clause sorts rows within each partition. The ROW_NUMBER() function is used to assign the row numbers to each row.

Example of Duplicates in CTE

Let us suppose that we have a table named Product that has five columns named ProductCode, Name, Description, Category, and Price. If we group the table by ProductCode and Category and then select only the rows having two or more occurrences, the response would be duplicates.

Heres an example of the CTE that locates duplicates in the above-mentioned table:


WITH Duplicates AS (
SELECT [ProductCode], [Category], COUNT(1) AS [DuplicateCounter]
FROM [Product]
GROUP BY [ProductCode], [Category]
HAVING COUNT(1) > 1
)
SELECT [ProductCode], [Name], [Description], [Category], [Price]
FROM [Product]
WHERE EXISTS(
SELECT 1
FROM [Duplicates]
WHERE [Product].[ProductCode] = [Duplicates].[ProductCode] AND [Product].[Category] = [Duplicates].[Category]
)


In this CTE, we partitioned the input by the ProductCode and Category columns and counted the duplicates. We then used a SELECT statement to show a list of duplicates in the table.

Deleting Duplicates with Duplicate Count Column

After creating a CTE with duplicate count column, we can use it to delete duplicates by selecting rows with higher duplicate counter values than 1. Heres an example delete statement that effectively targets duplicates in a table with the CTE structure:


DELETE
FROM CTE
WHERE [DuplicateCounter] > 1


This statement deletes duplicate rows from a table since all rows with DuplicateCounter values greater than 1 are excluded from the table. In conclusion, removing duplicate rows from a SQL table can be made easier by utilizing both CTE and a Duplicate Count Column.

By identifying duplicates in the table and then selecting and deleting them, you can maintain a clean and efficient database. The use of CTE is essential for defining a result set that can be used to filter out duplicates.

In conclusion, duplicate rows in SQL tables can cause complications when dealing with large datasets, making it difficult to obtain accurate results and affect query performance. Utilizing Common Table Expressions (CTE) and Duplicate Count Columns can easily identify and remove duplicate rows, fostering an efficient and accurate database.

By partitioning and grouping the data according to specific conditions, you can assign each row a unique value, allowing you to select and delete duplicates. Clean data leads to streamlined analysis, so it is imperative to maintain a clean and efficient database.

The use of CTE is essential to define a result set that can filter out duplicates and ensure a successful SQL analysis.