What is the best way to remove duplicate rows from a fairly large SQL Server
table (i.e. 300,000+ rows)?
The rows, of course, will not be perfect duplicates because of the existence of the RowID
identity field.
MyTable
RowID int not null identity(1,1) primary key,
Col1 varchar(20) not null,
Col2 varchar(2048) not null,
Col3 tinyint not null
I prefer the subquery\having count(*) > 1 solution to the inner join because I found it easier to read and it was very easy to turn into a SELECT statement to verify what would be deleted before you run it.
Using CTE. The idea is to join on one or more columns that form a duplicate record and then remove whichever you like:
There's a good article on removing duplicates on the Microsoft Support site. It's pretty conservative - they have you do everything in separate steps - but it should work well against large tables.
I've used self-joins to do this in the past, although it could probably be prettied up with a HAVING clause:
The other way is Create a new table with same fields and with Unique Index. Then move all data from old table to new table. Automatically SQL SERVER ignore (there is also an option about what to do if there will be a duplicate value: ignore, interrupt or sth) duplicate values. So we have the same table without duplicate rows. If you don't want Unique Index, after the transfer data you can drop it.
Especially for larger tables you may use DTS (SSIS package to import/export data) in order to transfer all data rapidly to your new uniquely indexed table. For 7 million row it takes just a few minute.
I had a table where I needed to preserve non-duplicate rows. I'm not sure on the speed or efficiency.
Yet another easy solution can be found at the link pasted here. This one easy to grasp and seems to be effective for most of the similar problems. It is for SQL Server though but the concept used is more than acceptable.
Here are the relevant portions from the linked page:
Consider this data:
So how can we delete those duplicate data?
First, insert an identity column in that table by using the following code:
Use the following code to resolve it: