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    <p>As others have mentioned, when you delete 42 million rows, the db has to log 42 million deletions against the database. Thus, the transaction log has to grow substantially. What you might try is to break up the delete into chunks. In the following query, I use the NTile ranking function to break up the rows into 100 buckets. If that is too slow, you can expand the number of buckets so that each delete is smaller. It will help tremendously if there is an index on <code>owner_cats.id_owner</code>, <code>owner_cats.id_cats</code> and <code>cats.id_cat</code> (which I assumed the primary key and numeric).</p> <pre><code>Declare @Cats Cursor Declare @CatId int --assuming an integer PK here Declare @Start int Declare @End int Declare @GroupCount int Set @GroupCount = 100 Set @Cats = Cursor Fast_Forward For With CatHerd As ( Select cats.id_cat , NTile(@GroupCount) Over ( Order By cats.id_cat ) As Grp From cats Join owner_cats On owner_cats.id_cat = cats.id_cat Where owner_cats.id_owner = 1 ) Select Grp, Min(id_cat) As MinCat, Max(id_cat) As MaxCat From CatHerd Group By Grp Open @Cats Fetch Next From @Cats Into @CatId, @Start, @End While @@Fetch_Status = 0 Begin Delete cats Where id_cat Between @Start And @End Fetch Next From @Cats Into @CatId, @Start, @End End Close @Cats Deallocate @Cats </code></pre> <p>The notable catch with the above approach is that it is not transactional. Thus, if it fails on the 40th chunk, you will have deleted 40% of the rows and the other 60% will still exist. </p>
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    1. PODELETE SQL with correlated subquery for table with 42 million rows?
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    1. COThanks, I might have to try this. But what do you think about my `TOP (25) PERCENT` idea?
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    2. CO@John B - The downside of the TOP X% solution is that you have to requery/reevaluate TOP X% on each iteration instead of just once like I've done here.
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