SQL Server 2016 - excessive memory grant warning on poor performing query The Next CEO of Stack OverflowFix for slow SQL_INLINE_TABLE_VALUED_FUNCTIONLarge memory grant requestsPoor performing Query -Tsql execution plan - estimated number of rows =1 Paste the PlanMSSQL - Query had to wait for memory grantRow estimates always too lowBad performance using “NOT IN”Warning about memory “Excessive Grant” in the query plan - how to find out what is causing it?Optimizing table valued function SQL ServerWhen does SQL Server warn about an Excessive Memory Grant?Warning in Execution Plan

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SQL Server 2016 - excessive memory grant warning on poor performing query

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SQL Server 2016 - excessive memory grant warning on poor performing query



The Next CEO of Stack OverflowFix for slow SQL_INLINE_TABLE_VALUED_FUNCTIONLarge memory grant requestsPoor performing Query -Tsql execution plan - estimated number of rows =1 Paste the PlanMSSQL - Query had to wait for memory grantRow estimates always too lowBad performance using “NOT IN”Warning about memory “Excessive Grant” in the query plan - how to find out what is causing it?Optimizing table valued function SQL ServerWhen does SQL Server warn about an Excessive Memory Grant?Warning in Execution Plan










1















I have a relatively large database of 550GB on a SQL Server 2016 EE instance which has a max memory limit of 112GB of the total 128GB RAM available to the OS. The database is at the latest compatibility level of 130. Developers have complained of the below query which executes within an acceptable time to them of 30 seconds when executed in isolation, but when they run their processes at scale the same query is executed multiple times concurrently across several threads and this is when they have observed that the execution time suffers and performance/throughput drops. The problematic T-SQL is:



select distinct dg.entityId, et.EntityName, dg.Version
from DataGathering dg with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'Account_Third_Party_Details'
inner join entitymapping em with(nolock)
on em.ChildEntityId = dg.EntityId
and em.ParentEntityId = -1
where dg.EntityId = dg.RootId

union all

select distinct dg1.EntityId, et.EntityName, dg1.version
from datagathering dg1 with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg1.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'TIN_Details'
where dg1.EntityId = dg1.RootId
and dg1.EntityId not in (
select distinct ChildEntityId
from entitymapping
where ChildEntityId = dg1.EntityId
and ParentEntityId = -1)


The actual execution plan shows the below memory grant warning:



enter image description here



The graphical execution plan can be found here:



https://www.brentozar.com/pastetheplan/?id=r18ZtCidN



Below are the row counts and sizes of the tables touched by this query. The most expensive operator is an index scan of a non-clustered index on the DataGathering table which makes sense given the size of the table compared to the others. I understand why/how the memory grant is required which I believe is due to how the query is written which requires multiple sorts and hash operators. What I need advice/guidance on is how to avoid the memory grants, T-SQL and re-factoring code is not my strong point, is there a way to re-write this query so that it is more performant? If I can tune the query to run faster in isolation then hopefully the benefits would transfer to when it is run at scale which is when the performance starts to suffer. Happy to provide any more information and hoping to learn something from this!



enter image description here



After updating statistics on 3 of the tables:



UPDATE STATISTICS Entity WITH FULLSCAN; 
UPDATE STATISTICS EntityMapping WITH FULLSCAN;
UPDATE STATISTICS EntityType WITH FULLSCAN;


...the execution plan has improved some:



https://www.brentozar.com/pastetheplan/?id=rkVmdkh_4



Unfortunately, the "Excessive Grant" warning is still there.










share|improve this question
























  • Thanks for your input. I'll run update statistics with fullscan against the four tables listed in my post and let you know if that makes any difference and if the execution plan changes. It will take some time since the DataGathering table is large! I was hoping to focus my efforts on re-writing that hideous query though. So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?

    – Fza
    4 hours ago






  • 2





    "So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?" - No, that is not logically equivalent. Your current query removes duplicates from each of the individual sets (with DISTINCT), and then combines those sets with UNION ALL - allowing duplicates between the two sets. Kin's suggestion eliminates all duplicate rows, even those between the two sets, so results could be different.

    – Josh Darnell
    3 hours ago
















1















I have a relatively large database of 550GB on a SQL Server 2016 EE instance which has a max memory limit of 112GB of the total 128GB RAM available to the OS. The database is at the latest compatibility level of 130. Developers have complained of the below query which executes within an acceptable time to them of 30 seconds when executed in isolation, but when they run their processes at scale the same query is executed multiple times concurrently across several threads and this is when they have observed that the execution time suffers and performance/throughput drops. The problematic T-SQL is:



select distinct dg.entityId, et.EntityName, dg.Version
from DataGathering dg with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'Account_Third_Party_Details'
inner join entitymapping em with(nolock)
on em.ChildEntityId = dg.EntityId
and em.ParentEntityId = -1
where dg.EntityId = dg.RootId

union all

select distinct dg1.EntityId, et.EntityName, dg1.version
from datagathering dg1 with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg1.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'TIN_Details'
where dg1.EntityId = dg1.RootId
and dg1.EntityId not in (
select distinct ChildEntityId
from entitymapping
where ChildEntityId = dg1.EntityId
and ParentEntityId = -1)


The actual execution plan shows the below memory grant warning:



enter image description here



The graphical execution plan can be found here:



https://www.brentozar.com/pastetheplan/?id=r18ZtCidN



Below are the row counts and sizes of the tables touched by this query. The most expensive operator is an index scan of a non-clustered index on the DataGathering table which makes sense given the size of the table compared to the others. I understand why/how the memory grant is required which I believe is due to how the query is written which requires multiple sorts and hash operators. What I need advice/guidance on is how to avoid the memory grants, T-SQL and re-factoring code is not my strong point, is there a way to re-write this query so that it is more performant? If I can tune the query to run faster in isolation then hopefully the benefits would transfer to when it is run at scale which is when the performance starts to suffer. Happy to provide any more information and hoping to learn something from this!



enter image description here



After updating statistics on 3 of the tables:



UPDATE STATISTICS Entity WITH FULLSCAN; 
UPDATE STATISTICS EntityMapping WITH FULLSCAN;
UPDATE STATISTICS EntityType WITH FULLSCAN;


...the execution plan has improved some:



https://www.brentozar.com/pastetheplan/?id=rkVmdkh_4



Unfortunately, the "Excessive Grant" warning is still there.










share|improve this question
























  • Thanks for your input. I'll run update statistics with fullscan against the four tables listed in my post and let you know if that makes any difference and if the execution plan changes. It will take some time since the DataGathering table is large! I was hoping to focus my efforts on re-writing that hideous query though. So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?

    – Fza
    4 hours ago






  • 2





    "So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?" - No, that is not logically equivalent. Your current query removes duplicates from each of the individual sets (with DISTINCT), and then combines those sets with UNION ALL - allowing duplicates between the two sets. Kin's suggestion eliminates all duplicate rows, even those between the two sets, so results could be different.

    – Josh Darnell
    3 hours ago














1












1








1


1






I have a relatively large database of 550GB on a SQL Server 2016 EE instance which has a max memory limit of 112GB of the total 128GB RAM available to the OS. The database is at the latest compatibility level of 130. Developers have complained of the below query which executes within an acceptable time to them of 30 seconds when executed in isolation, but when they run their processes at scale the same query is executed multiple times concurrently across several threads and this is when they have observed that the execution time suffers and performance/throughput drops. The problematic T-SQL is:



select distinct dg.entityId, et.EntityName, dg.Version
from DataGathering dg with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'Account_Third_Party_Details'
inner join entitymapping em with(nolock)
on em.ChildEntityId = dg.EntityId
and em.ParentEntityId = -1
where dg.EntityId = dg.RootId

union all

select distinct dg1.EntityId, et.EntityName, dg1.version
from datagathering dg1 with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg1.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'TIN_Details'
where dg1.EntityId = dg1.RootId
and dg1.EntityId not in (
select distinct ChildEntityId
from entitymapping
where ChildEntityId = dg1.EntityId
and ParentEntityId = -1)


The actual execution plan shows the below memory grant warning:



enter image description here



The graphical execution plan can be found here:



https://www.brentozar.com/pastetheplan/?id=r18ZtCidN



Below are the row counts and sizes of the tables touched by this query. The most expensive operator is an index scan of a non-clustered index on the DataGathering table which makes sense given the size of the table compared to the others. I understand why/how the memory grant is required which I believe is due to how the query is written which requires multiple sorts and hash operators. What I need advice/guidance on is how to avoid the memory grants, T-SQL and re-factoring code is not my strong point, is there a way to re-write this query so that it is more performant? If I can tune the query to run faster in isolation then hopefully the benefits would transfer to when it is run at scale which is when the performance starts to suffer. Happy to provide any more information and hoping to learn something from this!



enter image description here



After updating statistics on 3 of the tables:



UPDATE STATISTICS Entity WITH FULLSCAN; 
UPDATE STATISTICS EntityMapping WITH FULLSCAN;
UPDATE STATISTICS EntityType WITH FULLSCAN;


...the execution plan has improved some:



https://www.brentozar.com/pastetheplan/?id=rkVmdkh_4



Unfortunately, the "Excessive Grant" warning is still there.










share|improve this question
















I have a relatively large database of 550GB on a SQL Server 2016 EE instance which has a max memory limit of 112GB of the total 128GB RAM available to the OS. The database is at the latest compatibility level of 130. Developers have complained of the below query which executes within an acceptable time to them of 30 seconds when executed in isolation, but when they run their processes at scale the same query is executed multiple times concurrently across several threads and this is when they have observed that the execution time suffers and performance/throughput drops. The problematic T-SQL is:



select distinct dg.entityId, et.EntityName, dg.Version
from DataGathering dg with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'Account_Third_Party_Details'
inner join entitymapping em with(nolock)
on em.ChildEntityId = dg.EntityId
and em.ParentEntityId = -1
where dg.EntityId = dg.RootId

union all

select distinct dg1.EntityId, et.EntityName, dg1.version
from datagathering dg1 with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg1.EntityId
inner join entitytype et with(nolock)
on et.EntityTypeID = e.EntityTypeID
and et.EntityName = 'TIN_Details'
where dg1.EntityId = dg1.RootId
and dg1.EntityId not in (
select distinct ChildEntityId
from entitymapping
where ChildEntityId = dg1.EntityId
and ParentEntityId = -1)


The actual execution plan shows the below memory grant warning:



enter image description here



The graphical execution plan can be found here:



https://www.brentozar.com/pastetheplan/?id=r18ZtCidN



Below are the row counts and sizes of the tables touched by this query. The most expensive operator is an index scan of a non-clustered index on the DataGathering table which makes sense given the size of the table compared to the others. I understand why/how the memory grant is required which I believe is due to how the query is written which requires multiple sorts and hash operators. What I need advice/guidance on is how to avoid the memory grants, T-SQL and re-factoring code is not my strong point, is there a way to re-write this query so that it is more performant? If I can tune the query to run faster in isolation then hopefully the benefits would transfer to when it is run at scale which is when the performance starts to suffer. Happy to provide any more information and hoping to learn something from this!



enter image description here



After updating statistics on 3 of the tables:



UPDATE STATISTICS Entity WITH FULLSCAN; 
UPDATE STATISTICS EntityMapping WITH FULLSCAN;
UPDATE STATISTICS EntityType WITH FULLSCAN;


...the execution plan has improved some:



https://www.brentozar.com/pastetheplan/?id=rkVmdkh_4



Unfortunately, the "Excessive Grant" warning is still there.







sql-server t-sql query-performance sql-server-2016 memory-grant






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 3 hours ago









Josh Darnell

7,36522241




7,36522241










asked 5 hours ago









FzaFza

3711414




3711414












  • Thanks for your input. I'll run update statistics with fullscan against the four tables listed in my post and let you know if that makes any difference and if the execution plan changes. It will take some time since the DataGathering table is large! I was hoping to focus my efforts on re-writing that hideous query though. So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?

    – Fza
    4 hours ago






  • 2





    "So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?" - No, that is not logically equivalent. Your current query removes duplicates from each of the individual sets (with DISTINCT), and then combines those sets with UNION ALL - allowing duplicates between the two sets. Kin's suggestion eliminates all duplicate rows, even those between the two sets, so results could be different.

    – Josh Darnell
    3 hours ago


















  • Thanks for your input. I'll run update statistics with fullscan against the four tables listed in my post and let you know if that makes any difference and if the execution plan changes. It will take some time since the DataGathering table is large! I was hoping to focus my efforts on re-writing that hideous query though. So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?

    – Fza
    4 hours ago






  • 2





    "So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?" - No, that is not logically equivalent. Your current query removes duplicates from each of the individual sets (with DISTINCT), and then combines those sets with UNION ALL - allowing duplicates between the two sets. Kin's suggestion eliminates all duplicate rows, even those between the two sets, so results could be different.

    – Josh Darnell
    3 hours ago

















Thanks for your input. I'll run update statistics with fullscan against the four tables listed in my post and let you know if that makes any difference and if the execution plan changes. It will take some time since the DataGathering table is large! I was hoping to focus my efforts on re-writing that hideous query though. So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?

– Fza
4 hours ago





Thanks for your input. I'll run update statistics with fullscan against the four tables listed in my post and let you know if that makes any difference and if the execution plan changes. It will take some time since the DataGathering table is large! I was hoping to focus my efforts on re-writing that hideous query though. So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?

– Fza
4 hours ago




2




2





"So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?" - No, that is not logically equivalent. Your current query removes duplicates from each of the individual sets (with DISTINCT), and then combines those sets with UNION ALL - allowing duplicates between the two sets. Kin's suggestion eliminates all duplicate rows, even those between the two sets, so results could be different.

– Josh Darnell
3 hours ago






"So are you saying that removing the distinct keyword throughout the entire query and replacing union all with union is logically the same and will return the same data?" - No, that is not logically equivalent. Your current query removes duplicates from each of the individual sets (with DISTINCT), and then combines those sets with UNION ALL - allowing duplicates between the two sets. Kin's suggestion eliminates all duplicate rows, even those between the two sets, so results could be different.

– Josh Darnell
3 hours ago











1 Answer
1






active

oldest

votes


















3














This might not help with the memory grant situation (hopefully the additional stats updates will help some with that), but I noticed that parallelism is being inhibited in this query. Check out this part of the plan:



screenshot of plan explorer window



Since there's only one row on the outer side of the nested loops join, all 900k rows are being funneled onto one thread. So despite this query running at DOP 8, this portion of the plan is completely serial. That includes the sort. Here's the XML for that sort:



screenshot of plan XML showing unbalanced parallelism



If at all possible, consider avoiding the join to EntityType, and instead just grabbing that Id and filtering the Entity table with it. This will allow it to just be a predicate on an index scan of the Entity table, hopefully allowing parallelism and speeding up the execution.



Something like this:



DECLARE @tinDetailsId int;

SELECT @tinDetailsId = et.EntityTypeID
FROM entitytype et
WHERE et.EntityName = 'TIN_Details';


Which you could then reference in the bottom half of the query, eliminating the join:



select distinct dg1.EntityId, et.EntityName, dg1.version
from datagathering dg1 with(nolock)
inner join entity e with(nolock)
on e.EntityId = dg1.EntityId
where dg1.EntityId = dg1.RootId
and e.EntityTypeID = @tinDetailsId
and dg1.EntityId not in (
select distinct ChildEntityId
from entitymapping
where ChildEntityId = dg1.EntityId
and ParentEntityId = -1)


You would want to do the same thing with EntityName "Account_Third_Party_Details" in the top part of the query, as it has the same problem - with twice as many rows.



PS: Totally unrelated to the topic at hand, I noticed that you have nolock hints on all the tables in this query. Make sure that you are aware of the implications of this. Check out this nifty blog posts on the topic:



Bad habits : Putting NOLOCK everywhere by Aaron Bertrand
The Read Uncommitted Isolation Level by Paul White






share|improve this answer

























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    1 Answer
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    1 Answer
    1






    active

    oldest

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    active

    oldest

    votes






    active

    oldest

    votes









    3














    This might not help with the memory grant situation (hopefully the additional stats updates will help some with that), but I noticed that parallelism is being inhibited in this query. Check out this part of the plan:



    screenshot of plan explorer window



    Since there's only one row on the outer side of the nested loops join, all 900k rows are being funneled onto one thread. So despite this query running at DOP 8, this portion of the plan is completely serial. That includes the sort. Here's the XML for that sort:



    screenshot of plan XML showing unbalanced parallelism



    If at all possible, consider avoiding the join to EntityType, and instead just grabbing that Id and filtering the Entity table with it. This will allow it to just be a predicate on an index scan of the Entity table, hopefully allowing parallelism and speeding up the execution.



    Something like this:



    DECLARE @tinDetailsId int;

    SELECT @tinDetailsId = et.EntityTypeID
    FROM entitytype et
    WHERE et.EntityName = 'TIN_Details';


    Which you could then reference in the bottom half of the query, eliminating the join:



    select distinct dg1.EntityId, et.EntityName, dg1.version
    from datagathering dg1 with(nolock)
    inner join entity e with(nolock)
    on e.EntityId = dg1.EntityId
    where dg1.EntityId = dg1.RootId
    and e.EntityTypeID = @tinDetailsId
    and dg1.EntityId not in (
    select distinct ChildEntityId
    from entitymapping
    where ChildEntityId = dg1.EntityId
    and ParentEntityId = -1)


    You would want to do the same thing with EntityName "Account_Third_Party_Details" in the top part of the query, as it has the same problem - with twice as many rows.



    PS: Totally unrelated to the topic at hand, I noticed that you have nolock hints on all the tables in this query. Make sure that you are aware of the implications of this. Check out this nifty blog posts on the topic:



    Bad habits : Putting NOLOCK everywhere by Aaron Bertrand
    The Read Uncommitted Isolation Level by Paul White






    share|improve this answer





























      3














      This might not help with the memory grant situation (hopefully the additional stats updates will help some with that), but I noticed that parallelism is being inhibited in this query. Check out this part of the plan:



      screenshot of plan explorer window



      Since there's only one row on the outer side of the nested loops join, all 900k rows are being funneled onto one thread. So despite this query running at DOP 8, this portion of the plan is completely serial. That includes the sort. Here's the XML for that sort:



      screenshot of plan XML showing unbalanced parallelism



      If at all possible, consider avoiding the join to EntityType, and instead just grabbing that Id and filtering the Entity table with it. This will allow it to just be a predicate on an index scan of the Entity table, hopefully allowing parallelism and speeding up the execution.



      Something like this:



      DECLARE @tinDetailsId int;

      SELECT @tinDetailsId = et.EntityTypeID
      FROM entitytype et
      WHERE et.EntityName = 'TIN_Details';


      Which you could then reference in the bottom half of the query, eliminating the join:



      select distinct dg1.EntityId, et.EntityName, dg1.version
      from datagathering dg1 with(nolock)
      inner join entity e with(nolock)
      on e.EntityId = dg1.EntityId
      where dg1.EntityId = dg1.RootId
      and e.EntityTypeID = @tinDetailsId
      and dg1.EntityId not in (
      select distinct ChildEntityId
      from entitymapping
      where ChildEntityId = dg1.EntityId
      and ParentEntityId = -1)


      You would want to do the same thing with EntityName "Account_Third_Party_Details" in the top part of the query, as it has the same problem - with twice as many rows.



      PS: Totally unrelated to the topic at hand, I noticed that you have nolock hints on all the tables in this query. Make sure that you are aware of the implications of this. Check out this nifty blog posts on the topic:



      Bad habits : Putting NOLOCK everywhere by Aaron Bertrand
      The Read Uncommitted Isolation Level by Paul White






      share|improve this answer



























        3












        3








        3







        This might not help with the memory grant situation (hopefully the additional stats updates will help some with that), but I noticed that parallelism is being inhibited in this query. Check out this part of the plan:



        screenshot of plan explorer window



        Since there's only one row on the outer side of the nested loops join, all 900k rows are being funneled onto one thread. So despite this query running at DOP 8, this portion of the plan is completely serial. That includes the sort. Here's the XML for that sort:



        screenshot of plan XML showing unbalanced parallelism



        If at all possible, consider avoiding the join to EntityType, and instead just grabbing that Id and filtering the Entity table with it. This will allow it to just be a predicate on an index scan of the Entity table, hopefully allowing parallelism and speeding up the execution.



        Something like this:



        DECLARE @tinDetailsId int;

        SELECT @tinDetailsId = et.EntityTypeID
        FROM entitytype et
        WHERE et.EntityName = 'TIN_Details';


        Which you could then reference in the bottom half of the query, eliminating the join:



        select distinct dg1.EntityId, et.EntityName, dg1.version
        from datagathering dg1 with(nolock)
        inner join entity e with(nolock)
        on e.EntityId = dg1.EntityId
        where dg1.EntityId = dg1.RootId
        and e.EntityTypeID = @tinDetailsId
        and dg1.EntityId not in (
        select distinct ChildEntityId
        from entitymapping
        where ChildEntityId = dg1.EntityId
        and ParentEntityId = -1)


        You would want to do the same thing with EntityName "Account_Third_Party_Details" in the top part of the query, as it has the same problem - with twice as many rows.



        PS: Totally unrelated to the topic at hand, I noticed that you have nolock hints on all the tables in this query. Make sure that you are aware of the implications of this. Check out this nifty blog posts on the topic:



        Bad habits : Putting NOLOCK everywhere by Aaron Bertrand
        The Read Uncommitted Isolation Level by Paul White






        share|improve this answer















        This might not help with the memory grant situation (hopefully the additional stats updates will help some with that), but I noticed that parallelism is being inhibited in this query. Check out this part of the plan:



        screenshot of plan explorer window



        Since there's only one row on the outer side of the nested loops join, all 900k rows are being funneled onto one thread. So despite this query running at DOP 8, this portion of the plan is completely serial. That includes the sort. Here's the XML for that sort:



        screenshot of plan XML showing unbalanced parallelism



        If at all possible, consider avoiding the join to EntityType, and instead just grabbing that Id and filtering the Entity table with it. This will allow it to just be a predicate on an index scan of the Entity table, hopefully allowing parallelism and speeding up the execution.



        Something like this:



        DECLARE @tinDetailsId int;

        SELECT @tinDetailsId = et.EntityTypeID
        FROM entitytype et
        WHERE et.EntityName = 'TIN_Details';


        Which you could then reference in the bottom half of the query, eliminating the join:



        select distinct dg1.EntityId, et.EntityName, dg1.version
        from datagathering dg1 with(nolock)
        inner join entity e with(nolock)
        on e.EntityId = dg1.EntityId
        where dg1.EntityId = dg1.RootId
        and e.EntityTypeID = @tinDetailsId
        and dg1.EntityId not in (
        select distinct ChildEntityId
        from entitymapping
        where ChildEntityId = dg1.EntityId
        and ParentEntityId = -1)


        You would want to do the same thing with EntityName "Account_Third_Party_Details" in the top part of the query, as it has the same problem - with twice as many rows.



        PS: Totally unrelated to the topic at hand, I noticed that you have nolock hints on all the tables in this query. Make sure that you are aware of the implications of this. Check out this nifty blog posts on the topic:



        Bad habits : Putting NOLOCK everywhere by Aaron Bertrand
        The Read Uncommitted Isolation Level by Paul White







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited 2 hours ago

























        answered 2 hours ago









        Josh DarnellJosh Darnell

        7,36522241




        7,36522241



























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