Optimizing SQL Queries with Common Table Expressions (CTEs): A Guide to Removing Duplicate Rows

Understanding CTEs and Row Removal in SQL

Introduction to Common Table Expressions (CTEs)

Common Table Expressions (CTEs) are a powerful feature in SQL that allows you to create temporary views of data. They provide a way to define a derived table that can be used within a single query, making it easier to perform complex operations and calculations.

In this article, we’ll explore how CTEs work and their role in removing duplicate rows from an original table.

How CTEs Work

A CTE is defined using the WITH keyword followed by the name of the CTE. The CTE is then used within a query, just like any other table.

Here’s a basic example:

WITH my_cte AS (
  SELECT * FROM my_table
)
SELECT * FROM my_cte;

In this example, my_cte is defined as a CTE that selects all columns (*) from the original table (my_table). The CTE can then be used within the main query to select data.

Using CTEs for Duplicate Removal

When using CTEs for duplicate removal, we often use the ROW_NUMBER() or RANK() function to assign a unique number to each row based on some criteria. We can then update or delete rows based on this numbering system.

In the provided Stack Overflow question, the author uses CTE with ROW_NUMBER() and updates the Row_no column within the CTE. However, when they delete rows from the CTE using WHERE Rno != 1, it also removes rows from the original table.

This behavior might seem counterintuitive at first, but let’s dive deeper into how it works.

How Deleting Rows from a CTE Affects the Original Table

When we update or delete rows within a CTE, the changes are reflected in the original table because both are connected through the same underlying data. The CTE is simply a virtual view of the original data, and when we modify its contents, those modifications are propagated to the original table.

Here’s what happens behind the scenes:

CTE creation: When we define a CTE, the database engine creates an intermediate result set that contains the selected rows.
CTE query execution: When we execute a query against the CTE, the database engine executes the CTE query and returns the results to us.
CTE modification: When we update or delete rows within the CTE using UPDATE or DELETE, the changes are applied to the intermediate result set.

Now, here’s where things get interesting:

CTE rewrite: When we execute a SELECT statement against the CTE, the database engine rewrites the query to include the modifications made in step 3.
Original table update: The rewritten query is then executed against the original table, which means any updates or deletions made within the CTE are applied to the original data.

This process ensures that when we delete rows from a CTE, those rows are also removed from the original table.

Why Updating Columns in the CTE Doesn’t Affect the Original Table

Now, let’s address why updating columns in the CTE doesn’t affect the original table. The reason lies in how the database engine handles updates versus deletions.

When we update a column within a CTE, the changes are applied to the intermediate result set, but these modifications are not reflected in the original table. This is because the UPDATE statement only modifies the local copy of the data held by the CTE, whereas deletion removes rows from the underlying data completely.

In other words, when we update columns within a CTE, we’re modifying the virtual view, whereas when we delete rows from the CTE, we’re removing actual data from the original table.

Example Walkthrough

To illustrate this concept further, let’s walk through an example query:

WITH my_cte AS (
  SELECT ID, NAME, ROW_NUMBER() OVER(PARTITION BY ID, NAME ORDER BY ID) AS rNO
  FROM my_table
)
UPDATE CTE SET Row_no = 100 WHERE Rno = 1;
SELECT * FROM TABLE_DUPLICATEREMOVALTEST;

In this example:

We first create a CTE that assigns a unique row number to each row within the my_table.
We then update the Row_no column in the CTE where Rno equals 1.
Finally, we select all columns from the original table (SELECT * FROM TABLE_DUPLICATEREMOVALTEST;).

Because we updated the Row_no column within the CTE but didn’t affect the underlying data, no changes are reflected in the original table. However, if we had deleted rows from the CTE using WHERE Rno != 1, it would have removed those actual rows from the original table.

Conclusion

In conclusion, when using CTEs for duplicate removal, deleting rows from a CTE affects the original table because both are connected through the same underlying data. The modifications made within the CTE are applied to the intermediate result set, which is then used to update or delete actual data in the original table.

Understanding this behavior is crucial when working with CTEs and duplicate removal, as it allows you to make informed decisions about how to modify your queries and ensure accurate results.

Best Practices for Using CTEs for Duplicate Removal

Here are some best practices for using CTEs for duplicate removal:

Use the ROW_NUMBER() or RANK() function to assign a unique number to each row based on some criteria.
Update columns within the CTE, rather than deleting rows, when possible.
Be aware of how changes within the CTE affect the original table.

By following these best practices and understanding how CTEs work for duplicate removal, you can write more efficient and effective queries that accurately remove duplicates from your data.

Last modified on 2024-03-20