Why would a Clustered Index Seek return a higher “Actual Number of Rows” than there are rows in the...












6















I'm troubleshooting an issue related to SQL Server (Azure SQL Database technically) occasionally choosing a bad execution plan, presumably due to skewed stats. sp_updatestats fixes it every time, until a few hours or days later when a bad plan gets cached again.



Looking at the "bad" plan, I noticed something that strikes me as odd: there is a Clustered Index Seek on a table that currently has about 1.7 million rows. The "Estimated Number of Rows" for this operation is about 1200, which is definitely in line with the average row count I would expect from that operation in this case, but the "Actual Number of Rows" is in excess of 60 million! Following the fat line from this leaf node, various downstream operations such as joins and sorts are being performed on all 60 million, causing excessive slowness, spills to tempdb, and other badness.



I must be misunderstanding what a Clustered Index Seek actually does, because I wouldn't think it's possible for it to "output" more rows than are in the underlying table. What could cause this? And better yet, any pointers on how to fix it?



[Bonus points for including something like "sp_updatestats fixes it every time but can't figure out how to fix it permanently? Go read this article." This has been a general problem for us on a few different fronts lately.]










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  • Certainly: brentozar.com/pastetheplan/?id=BktRIhC1V

    – Todd Menier
    Dec 12 '18 at 16:27











  • 60m row index seek in question is on ProductCatalog. I do see there's an index scan in the plan as well and I may look into it, but the "good" plan contains that too and time-wise it looks to be a non-factor in both cases.

    – Todd Menier
    Dec 12 '18 at 16:30
















6















I'm troubleshooting an issue related to SQL Server (Azure SQL Database technically) occasionally choosing a bad execution plan, presumably due to skewed stats. sp_updatestats fixes it every time, until a few hours or days later when a bad plan gets cached again.



Looking at the "bad" plan, I noticed something that strikes me as odd: there is a Clustered Index Seek on a table that currently has about 1.7 million rows. The "Estimated Number of Rows" for this operation is about 1200, which is definitely in line with the average row count I would expect from that operation in this case, but the "Actual Number of Rows" is in excess of 60 million! Following the fat line from this leaf node, various downstream operations such as joins and sorts are being performed on all 60 million, causing excessive slowness, spills to tempdb, and other badness.



I must be misunderstanding what a Clustered Index Seek actually does, because I wouldn't think it's possible for it to "output" more rows than are in the underlying table. What could cause this? And better yet, any pointers on how to fix it?



[Bonus points for including something like "sp_updatestats fixes it every time but can't figure out how to fix it permanently? Go read this article." This has been a general problem for us on a few different fronts lately.]










share|improve this question

























  • Certainly: brentozar.com/pastetheplan/?id=BktRIhC1V

    – Todd Menier
    Dec 12 '18 at 16:27











  • 60m row index seek in question is on ProductCatalog. I do see there's an index scan in the plan as well and I may look into it, but the "good" plan contains that too and time-wise it looks to be a non-factor in both cases.

    – Todd Menier
    Dec 12 '18 at 16:30














6












6








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I'm troubleshooting an issue related to SQL Server (Azure SQL Database technically) occasionally choosing a bad execution plan, presumably due to skewed stats. sp_updatestats fixes it every time, until a few hours or days later when a bad plan gets cached again.



Looking at the "bad" plan, I noticed something that strikes me as odd: there is a Clustered Index Seek on a table that currently has about 1.7 million rows. The "Estimated Number of Rows" for this operation is about 1200, which is definitely in line with the average row count I would expect from that operation in this case, but the "Actual Number of Rows" is in excess of 60 million! Following the fat line from this leaf node, various downstream operations such as joins and sorts are being performed on all 60 million, causing excessive slowness, spills to tempdb, and other badness.



I must be misunderstanding what a Clustered Index Seek actually does, because I wouldn't think it's possible for it to "output" more rows than are in the underlying table. What could cause this? And better yet, any pointers on how to fix it?



[Bonus points for including something like "sp_updatestats fixes it every time but can't figure out how to fix it permanently? Go read this article." This has been a general problem for us on a few different fronts lately.]










share|improve this question
















I'm troubleshooting an issue related to SQL Server (Azure SQL Database technically) occasionally choosing a bad execution plan, presumably due to skewed stats. sp_updatestats fixes it every time, until a few hours or days later when a bad plan gets cached again.



Looking at the "bad" plan, I noticed something that strikes me as odd: there is a Clustered Index Seek on a table that currently has about 1.7 million rows. The "Estimated Number of Rows" for this operation is about 1200, which is definitely in line with the average row count I would expect from that operation in this case, but the "Actual Number of Rows" is in excess of 60 million! Following the fat line from this leaf node, various downstream operations such as joins and sorts are being performed on all 60 million, causing excessive slowness, spills to tempdb, and other badness.



I must be misunderstanding what a Clustered Index Seek actually does, because I wouldn't think it's possible for it to "output" more rows than are in the underlying table. What could cause this? And better yet, any pointers on how to fix it?



[Bonus points for including something like "sp_updatestats fixes it every time but can't figure out how to fix it permanently? Go read this article." This has been a general problem for us on a few different fronts lately.]







sql-server optimization execution-plan azure-sql-database






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edited Dec 12 '18 at 16:36







Todd Menier

















asked Dec 12 '18 at 16:23









Todd MenierTodd Menier

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  • Certainly: brentozar.com/pastetheplan/?id=BktRIhC1V

    – Todd Menier
    Dec 12 '18 at 16:27











  • 60m row index seek in question is on ProductCatalog. I do see there's an index scan in the plan as well and I may look into it, but the "good" plan contains that too and time-wise it looks to be a non-factor in both cases.

    – Todd Menier
    Dec 12 '18 at 16:30



















  • Certainly: brentozar.com/pastetheplan/?id=BktRIhC1V

    – Todd Menier
    Dec 12 '18 at 16:27











  • 60m row index seek in question is on ProductCatalog. I do see there's an index scan in the plan as well and I may look into it, but the "good" plan contains that too and time-wise it looks to be a non-factor in both cases.

    – Todd Menier
    Dec 12 '18 at 16:30

















Certainly: brentozar.com/pastetheplan/?id=BktRIhC1V

– Todd Menier
Dec 12 '18 at 16:27





Certainly: brentozar.com/pastetheplan/?id=BktRIhC1V

– Todd Menier
Dec 12 '18 at 16:27













60m row index seek in question is on ProductCatalog. I do see there's an index scan in the plan as well and I may look into it, but the "good" plan contains that too and time-wise it looks to be a non-factor in both cases.

– Todd Menier
Dec 12 '18 at 16:30





60m row index seek in question is on ProductCatalog. I do see there's an index scan in the plan as well and I may look into it, but the "good" plan contains that too and time-wise it looks to be a non-factor in both cases.

– Todd Menier
Dec 12 '18 at 16:30










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The Seek returns more rows because it is on the inner (bottom) side of a Nested Loop. Every row returned by the outer operation results in a new Seek operation. So you're not getting 60m rows from a single Seek, but from over 9000 of them (number of executions).



Also of note: when looking at estimations, the total number of rows estimated will be Estimated Number of Executions multiplied by Estimated Number of Rows






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    The Seek returns more rows because it is on the inner (bottom) side of a Nested Loop. Every row returned by the outer operation results in a new Seek operation. So you're not getting 60m rows from a single Seek, but from over 9000 of them (number of executions).



    Also of note: when looking at estimations, the total number of rows estimated will be Estimated Number of Executions multiplied by Estimated Number of Rows






    share|improve this answer






























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      The Seek returns more rows because it is on the inner (bottom) side of a Nested Loop. Every row returned by the outer operation results in a new Seek operation. So you're not getting 60m rows from a single Seek, but from over 9000 of them (number of executions).



      Also of note: when looking at estimations, the total number of rows estimated will be Estimated Number of Executions multiplied by Estimated Number of Rows






      share|improve this answer




























        6












        6








        6







        The Seek returns more rows because it is on the inner (bottom) side of a Nested Loop. Every row returned by the outer operation results in a new Seek operation. So you're not getting 60m rows from a single Seek, but from over 9000 of them (number of executions).



        Also of note: when looking at estimations, the total number of rows estimated will be Estimated Number of Executions multiplied by Estimated Number of Rows






        share|improve this answer















        The Seek returns more rows because it is on the inner (bottom) side of a Nested Loop. Every row returned by the outer operation results in a new Seek operation. So you're not getting 60m rows from a single Seek, but from over 9000 of them (number of executions).



        Also of note: when looking at estimations, the total number of rows estimated will be Estimated Number of Executions multiplied by Estimated Number of Rows







        share|improve this answer














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        edited Dec 12 '18 at 16:53

























        answered Dec 12 '18 at 16:41









        ForrestForrest

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