How to remove duplicate rows in SQL Server, MySql and Oracle?

In this article we will see how to eliminate duplicate rows in SQL Server, in MySQL and Oracle.


How to delete duplicate rows in SQL Server

Suponiendo que no tienes valores nulos, agrupa las columnas exclusivas (por ejemplo, col_1, col_2, col_3) y seleccionas la columna identificadora (el ID) el MIN o MAX (por ejemplo, row_id) como la fila que se debe conservar. Luego, elimine todo lo que no tenía un ID:

DELETE my_table
FROM my_table
                LEFT OUTER JOIN (
                SELECT MIN(row_id) as row_id, col_1, col_2, col_3
                FROM my_table
                GROUP BY col_1, col_2, col_3
) as keep_rows ON
                my_table.row_id = keep_rows.row_id
WHERE
                keep_rows.row_id IS NULL

If you have a GUID instead of an integer as an ID, use the following.

CONVERT(uniqueidentifier, MIN(CONVERT(char(36), my_guid_column)))

How to delete duplicate rows in MySQL?

Continuing with the previous example, the primary key: id, the unique columns:  col_1, col_2, col_3. You can use a temporary table, like:

create temporary table temp_table (id int);
insert  temp_table
        (id)
select  id
from    your_table t1
where   exists
        (
        select  *
        from    your_table t2
        where   t2.col_1 = t1.col_1
                and t2.col_2 = t1.col_2
                and t2.col_3 = t1.col_3
                and t2.id > t1.id
        );
delete
from    your_table
where   id in (select id from temp_table);

Or you can add a UNIQUE index to the table. When you execute this, all duplicate rows will be deleted. As an additional benefit, INSERT futures that are duplicates will fail. And you'd better make a backup before executing this statement.

ALTER IGNORE TABLE your_table ADD UNIQUE INDEX idx_name (col_1, col_2, col_3);

How to delete duplicate rows in Oracle?

The following example deletes all duplicate rows and leaves only one of them in Oracle

DELETE FROM my_table
WHERE rowid not in
(SELECT MIN(rowid)
FROM my_table
GROUP BY column1, column2, column3...) ;
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