Identifying Duplicate Entries and Updating Values in a Table

Problem Overview

When working with large datasets, it’s not uncommon to encounter duplicate entries. In this article, we’ll explore how to identify these duplicates and update values in a specific column while excluding the most recent entry.

Step 1: Finding Duplicate Entries

To begin, let’s first find all duplicate entries in our table. We can use a self-join to compare each row with every other row that has the same item_id. Here’s an example query:

SELECT `item_id`, `lookup_id`, `date`, `archive`
FROM `items`
WHERE `item_id` IN (
    SELECT `item_id` 
    FROM `items`
    GROUP BY `item_id` 
    HAVING COUNT(`item_id`) > 1
)
ORDER BY `item_id`;

This query works by first grouping all rows with the same item_id and counting the number of occurrences for each group. If a group has more than one row, it’s considered a duplicate entry.

Step 2: Updating Archive Values

Now that we have identified our duplicate entries, let’s update their archive values to 1. We’ll use an update statement with a subquery to find the most recent item for each lookup_id. Here’s the updated query:

UPDATE items i
INNER JOIN (
    SELECT max(`item_id`) as `item_id`
    FROM items
    GROUP BY `lookup_id`
) x using (`item_id`)
SET i.`archive` = 0;

This query works by first finding the most recent item for each lookup_id. It does this by grouping all rows with the same lookup_id and finding the maximum item_id for each group. Then, it uses an inner join to match these groups with the original table, updating their archive values to 0.

Step 3: Final Update

We now have our duplicate entries marked as having an archive value of 1, but we still need to update the archive value of the most recent entry for each lookup_id back to 0. We can do this by using a single UPDATE statement with an INNER JOIN:

UPDATE items i
INNER JOIN (
    SELECT max(`item_id`) as `item_id`
    FROM items
    GROUP BY `lookup_id`
) x using (`item_id`)
SET i.`archive` = 1;

This query works by finding the most recent item for each lookup_id, just like before. However, this time it updates their archive values back to 0.

Example Use Case

Let’s take a look at an example dataset:

item_id     Lookup_id   date    archive
------------------------------------------------
1234             4   1-1-19        0
1235             4   1-1-19        0
1236             4   1-1-19        0
1237             2   1-1-19        0
1238             1   1-1-19        0
1239             1   1-1-19        0

After running our query, the output would be:

item_id     Lookup_id   date    archive
------------------------------------------------
1234             4   1-1-19        1
1235             4   1-1-19        1
1236             4   1-1-19        0
1237             2   1-1-19        0
1238             1   1-1-19        1
1239             1   1-1-19        0

As we can see, the archive values have been updated correctly, with all duplicates marked as having an archive value of 1 and the most recent entry for each lookup_id updated back to 0.

Conclusion

In this article, we’ve explored how to identify duplicate entries in a table and update their archive values while excluding the most recent entry. We’ve used a combination of self-joins, groupings, and subqueries to achieve this goal. By following these steps, you can efficiently update your database with accurate and up-to-date information.

Last modified on 2023-10-14