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Asked: 2024-09-27T05:10:37+05:30 In:

how to delete repeated rows in sql

I hope someone can help me with a challenge I’m facing in SQL. I’m working with a database where I’m noticing that some of my tables contain repeated rows, and this is becoming a major issue for my data integrity and the accuracy of my reports. For instance, I have a table that is supposed to store unique customer records, but somehow, there are multiple entries for the same customer with identical information.

I’ve tried a few approaches to remove these duplicates, like writing queries with the DISTINCT keyword, but I’m not sure if that’s effective for my situation since I might still be left with unwanted duplicates in some cases. I want to be sure that I delete only the duplicate records while keeping one instance of each unique row intact.

Should I use a temporary table, a Common Table Expression (CTE), or something else entirely to achieve this? I’m a bit concerned about accidentally losing important data, so I’d love to hear the best practices or specific SQL queries that can help me safely delete the repeated rows. Any guidance would be greatly appreciated!

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    2 Answers

    1. Deleting Duplicate Rows in SQL (Like a Rookie)

      So, you have this table, right? And it’s got like, a bunch of rows that are just the same. Super annoying! Here’s a kinda simple way to do it. Just follow along…

      Step 1: Find the Duplicates

      First, you gotta see where those duplicates are hiding. You can use this command:

      SELECT column1, column2, COUNT(*) 
FROM your_table 
GROUP BY column1, column2 
HAVING COUNT(*) > 1;

      Replace column1 and column2 with the names of the columns that you think are repeating. This will show you the rows that are duplicated.

      Step 2: Delete the Duplicates

      Okay, now to actually delete them. One way to do this is using a common table expression (CTE). It sounds fancy, but it’s not too scary!

      WITH CTE AS (
    SELECT *, ROW_NUMBER() OVER (PARTITION BY column1, column2 ORDER BY (SELECT NULL)) AS row_num
    FROM your_table
)
DELETE FROM CTE WHERE row_num > 1;

      This code keeps the first row and deletes the rest where it thinks it’s duplicate. Remember to replace your_table, column1, and column2 with your actual names!

      Step 3: Check Your Work

      Finally, run the first SELECT query again to make sure those pesky duplicates are gone! If they’re still there, uh-oh!

      And that’s it! You did it! Now your table should be nice and neat without all those repeated rows. You might wanna back up your data first because, you know, better safe than sorry!


    2. To delete repeated rows in SQL, you can utilize the Common Table Expressions (CTE) combined with the `ROW_NUMBER()` window function. This approach ranks rows within each group of duplicates and allows you to target and delete the specific repeated entries while preserving one instance. For example, if you have a table named `my_table` with a column `id` and you want to delete duplicates based on another column `name`, your query may look like this:

      “`sql
      WITH CTE AS (
      SELECT *,
      ROW_NUMBER() OVER (PARTITION BY name ORDER BY id) AS row_num
      FROM my_table
      )
      DELETE FROM CTE WHERE row_num > 1;
      “`
      This SQL statement assigns a unique row number to each instance of `name`, and the `DELETE` operation removes all rows where the `row_num` exceeds 1, effectively retaining only one record for each duplicate entry.

      Another method involves using a temporary table or creating a new table to store distinct records. You can achieve this using a `SELECT DISTINCT` statement and then inserting the results into the new table, followed by truncating or dropping the original table. This method, while effective, can be more resource-intensive, especially for large datasets. The basic syntax for this approach is as follows:

      “`sql
      CREATE TABLE temp_table AS
      SELECT DISTINCT *
      FROM my_table;

      DROP TABLE my_table;

      ALTER TABLE temp_table RENAME TO my_table;
      “`
      This creates a new table `temp_table` with distinct rows from `my_table`, deletes the original table, and renames the new one to maintain continuity in your database schema.

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