Coding Series - SQL : Delete Duplicate emails | SQL Interview | Data Engineer Interview Question
Video 187: This is the 46th video in our series "Crack SQL Interview in 50 Questions," and in this exercise, we continue with the topic of "Advanced String Functions"
We are given Person table which has customer id and email. Due to some process issue the table got duplicate emails inserted into the table. we are asked for a solution to delete all duplicate emails, keeping only one unique email with the smallest id.
In this video, we delve into various efficient methods for eliminating duplicate entries from a SQL database table. Each approach provides a distinct way to achieve the same objective of ensuring data integrity and cleanliness within the database.
** Approach 1: Self Join **
In this approach, we utilize a self join operation to identify and delete duplicate entries based on a specific condition, such as matching email addresses and comparing unique identifiers.
** Approach 2: Correlated Subquery **
Using a correlated subquery, we target duplicate entries by comparing each record with others sharing the same criteria, such as email addresses. This approach allows for more granular control over the deletion process.
** Approach 3: Simple Subquery **
In this straightforward approach, we employ a subquery to identify and remove duplicate entries based on a distinct identifier, ensuring that only one instance of each unique record remains in the database.
** Approach 4: Windows Function **
By leveraging window functions, we can efficiently partition and rank records based on specific criteria, such as email addresses, allowing us to selectively delete duplicate entries while retaining the desired data integrity.
Each approach offers unique advantages and considerations, depending on factors such as database size, indexing, and performance requirements. By understanding and utilizing these strategies effectively, database administrators can maintain a clean and optimized database environment.
For a comprehensive understanding of these SQL methodologies and their application, please refer to this explanatory video.
code: https://github.com/jeganpillai/crack_...
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