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Replace long GROUP BY list with a subquery


Should I use left join to do my job in this scenario?How to use and optimize subquery on 100 million rowsDoes Detach/Attach or Offline/Online Clear the Buffer Cache for a Particular Database?SHOWPLAN does not display a warning but “Include Execution Plan” does for the same queryMysql join not workingWhy SELECT COUNT() query execution plan includes left joined table?Query plan missing ParameterCompiledValueDynamic SQL Server cross tabSelect value based on a test






.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty
margin-bottom:0;









6

















This is a repost of my question on Stack Overflow. They suggested to ask it here:



I found an online article from 2005, where the author claims, that many devs use GROUP BY wrong, and that you should better replace it with a subquery.



I've tested it on one of my queries, where I need to sort the result of a search by the number of joined entries from another table (more common ones should appear first). My original, classic approach was to join both tables on a common ID, group by each field in the select list and order the result by the count of the sub table.



Now, Jeff Smith from the linked blog claims, that you should better use a subselect, which does all the grouping, and than join to that subselect. Checking the execution plans of both approaches, SSMS states, that the large group by requires 52% of the time and the subselect one 48%, so from a technical standpoint, it seems, that the subselect approach is actually marginally faster. However, the "improved" SQL command seems to generate a more complicated execution plan (in terms of nodes)



What do you think? Can you give me some detail about how to interpret the execution plans in this specific case and which one is generally the preferable option?



SELECT
a.ID,
a.ID_AddressType,
a.Name1,
a.Name2,
a.Street,
a.Number,
a.ZipCode,
a.City,
a.Country
FROM dbo.[Address] a
INNER JOIN CONTAINSTABLE(
dbo.[Address],
FullAddress,
'"ZIE*"',
5
) s ON a.ID = s.[KEY]
LEFT JOIN dbo.Haul h ON h.ID_DestinationAddress = a.ID
GROUP BY
a.ID,
a.ID_AddressType,
a.Name1,
a.Name2,
a.Street,
a.Number,
a.ZipCode,
a.City,
a.Country,
s.RANK
ORDER BY s.RANK DESC, COUNT(*) DESC;

SELECT
a.ID,
a.ID_AddressType,
a.Name1,
a.Name2,
a.Street,
a.Number,
a.ZipCode,
a.City,
a.Country
FROM dbo.[Address] a
INNER JOIN CONTAINSTABLE(
dbo.[Address],
FullAddress,
'"ZIE*"',
5
) s ON a.ID = s.[KEY]
LEFT JOIN (
SELECT ID_DestinationAddress, COUNT(*) Cnt
FROM dbo.Haul
GROUP BY ID_DestinationAddress
) h ON h.ID_DestinationAddress = a.ID
ORDER BY s.RANK DESC, h.Cnt DESC;


enter image description here










share|improve this question







New contributor



André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





























    6

















    This is a repost of my question on Stack Overflow. They suggested to ask it here:



    I found an online article from 2005, where the author claims, that many devs use GROUP BY wrong, and that you should better replace it with a subquery.



    I've tested it on one of my queries, where I need to sort the result of a search by the number of joined entries from another table (more common ones should appear first). My original, classic approach was to join both tables on a common ID, group by each field in the select list and order the result by the count of the sub table.



    Now, Jeff Smith from the linked blog claims, that you should better use a subselect, which does all the grouping, and than join to that subselect. Checking the execution plans of both approaches, SSMS states, that the large group by requires 52% of the time and the subselect one 48%, so from a technical standpoint, it seems, that the subselect approach is actually marginally faster. However, the "improved" SQL command seems to generate a more complicated execution plan (in terms of nodes)



    What do you think? Can you give me some detail about how to interpret the execution plans in this specific case and which one is generally the preferable option?



    SELECT
    a.ID,
    a.ID_AddressType,
    a.Name1,
    a.Name2,
    a.Street,
    a.Number,
    a.ZipCode,
    a.City,
    a.Country
    FROM dbo.[Address] a
    INNER JOIN CONTAINSTABLE(
    dbo.[Address],
    FullAddress,
    '"ZIE*"',
    5
    ) s ON a.ID = s.[KEY]
    LEFT JOIN dbo.Haul h ON h.ID_DestinationAddress = a.ID
    GROUP BY
    a.ID,
    a.ID_AddressType,
    a.Name1,
    a.Name2,
    a.Street,
    a.Number,
    a.ZipCode,
    a.City,
    a.Country,
    s.RANK
    ORDER BY s.RANK DESC, COUNT(*) DESC;

    SELECT
    a.ID,
    a.ID_AddressType,
    a.Name1,
    a.Name2,
    a.Street,
    a.Number,
    a.ZipCode,
    a.City,
    a.Country
    FROM dbo.[Address] a
    INNER JOIN CONTAINSTABLE(
    dbo.[Address],
    FullAddress,
    '"ZIE*"',
    5
    ) s ON a.ID = s.[KEY]
    LEFT JOIN (
    SELECT ID_DestinationAddress, COUNT(*) Cnt
    FROM dbo.Haul
    GROUP BY ID_DestinationAddress
    ) h ON h.ID_DestinationAddress = a.ID
    ORDER BY s.RANK DESC, h.Cnt DESC;


    enter image description here










    share|improve this question







    New contributor



    André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.

























      6












      6








      6


      2






      This is a repost of my question on Stack Overflow. They suggested to ask it here:



      I found an online article from 2005, where the author claims, that many devs use GROUP BY wrong, and that you should better replace it with a subquery.



      I've tested it on one of my queries, where I need to sort the result of a search by the number of joined entries from another table (more common ones should appear first). My original, classic approach was to join both tables on a common ID, group by each field in the select list and order the result by the count of the sub table.



      Now, Jeff Smith from the linked blog claims, that you should better use a subselect, which does all the grouping, and than join to that subselect. Checking the execution plans of both approaches, SSMS states, that the large group by requires 52% of the time and the subselect one 48%, so from a technical standpoint, it seems, that the subselect approach is actually marginally faster. However, the "improved" SQL command seems to generate a more complicated execution plan (in terms of nodes)



      What do you think? Can you give me some detail about how to interpret the execution plans in this specific case and which one is generally the preferable option?



      SELECT
      a.ID,
      a.ID_AddressType,
      a.Name1,
      a.Name2,
      a.Street,
      a.Number,
      a.ZipCode,
      a.City,
      a.Country
      FROM dbo.[Address] a
      INNER JOIN CONTAINSTABLE(
      dbo.[Address],
      FullAddress,
      '"ZIE*"',
      5
      ) s ON a.ID = s.[KEY]
      LEFT JOIN dbo.Haul h ON h.ID_DestinationAddress = a.ID
      GROUP BY
      a.ID,
      a.ID_AddressType,
      a.Name1,
      a.Name2,
      a.Street,
      a.Number,
      a.ZipCode,
      a.City,
      a.Country,
      s.RANK
      ORDER BY s.RANK DESC, COUNT(*) DESC;

      SELECT
      a.ID,
      a.ID_AddressType,
      a.Name1,
      a.Name2,
      a.Street,
      a.Number,
      a.ZipCode,
      a.City,
      a.Country
      FROM dbo.[Address] a
      INNER JOIN CONTAINSTABLE(
      dbo.[Address],
      FullAddress,
      '"ZIE*"',
      5
      ) s ON a.ID = s.[KEY]
      LEFT JOIN (
      SELECT ID_DestinationAddress, COUNT(*) Cnt
      FROM dbo.Haul
      GROUP BY ID_DestinationAddress
      ) h ON h.ID_DestinationAddress = a.ID
      ORDER BY s.RANK DESC, h.Cnt DESC;


      enter image description here










      share|improve this question







      New contributor



      André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.












      This is a repost of my question on Stack Overflow. They suggested to ask it here:



      I found an online article from 2005, where the author claims, that many devs use GROUP BY wrong, and that you should better replace it with a subquery.



      I've tested it on one of my queries, where I need to sort the result of a search by the number of joined entries from another table (more common ones should appear first). My original, classic approach was to join both tables on a common ID, group by each field in the select list and order the result by the count of the sub table.



      Now, Jeff Smith from the linked blog claims, that you should better use a subselect, which does all the grouping, and than join to that subselect. Checking the execution plans of both approaches, SSMS states, that the large group by requires 52% of the time and the subselect one 48%, so from a technical standpoint, it seems, that the subselect approach is actually marginally faster. However, the "improved" SQL command seems to generate a more complicated execution plan (in terms of nodes)



      What do you think? Can you give me some detail about how to interpret the execution plans in this specific case and which one is generally the preferable option?



      SELECT
      a.ID,
      a.ID_AddressType,
      a.Name1,
      a.Name2,
      a.Street,
      a.Number,
      a.ZipCode,
      a.City,
      a.Country
      FROM dbo.[Address] a
      INNER JOIN CONTAINSTABLE(
      dbo.[Address],
      FullAddress,
      '"ZIE*"',
      5
      ) s ON a.ID = s.[KEY]
      LEFT JOIN dbo.Haul h ON h.ID_DestinationAddress = a.ID
      GROUP BY
      a.ID,
      a.ID_AddressType,
      a.Name1,
      a.Name2,
      a.Street,
      a.Number,
      a.ZipCode,
      a.City,
      a.Country,
      s.RANK
      ORDER BY s.RANK DESC, COUNT(*) DESC;

      SELECT
      a.ID,
      a.ID_AddressType,
      a.Name1,
      a.Name2,
      a.Street,
      a.Number,
      a.ZipCode,
      a.City,
      a.Country
      FROM dbo.[Address] a
      INNER JOIN CONTAINSTABLE(
      dbo.[Address],
      FullAddress,
      '"ZIE*"',
      5
      ) s ON a.ID = s.[KEY]
      LEFT JOIN (
      SELECT ID_DestinationAddress, COUNT(*) Cnt
      FROM dbo.Haul
      GROUP BY ID_DestinationAddress
      ) h ON h.ID_DestinationAddress = a.ID
      ORDER BY s.RANK DESC, h.Cnt DESC;


      enter image description here







      sql-server join subquery






      share|improve this question







      New contributor



      André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question







      New contributor



      André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.








      share|improve this question




      share|improve this question






      New contributor



      André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.








      asked Oct 14 at 6:43









      André ReicheltAndré Reichelt

      1333 bronze badges




      1333 bronze badges




      New contributor



      André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.




      New contributor




      André Reichelt is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.

























          1 Answer
          1






          active

          oldest

          votes


















          7


















          If you change the left join with dbo.Haul to a subquery, it will calculate these distinct values of ID_DestinationAddress (Stream Aggregate) and Count them (Compute scalar) directly after getting the data from the scan.



          This is what you are seeing in the execution plan:



          enter image description here



          While, when using the GROUP BY method it is only doing the grouping after data passed through the left join between dbo.Haul and dbo.[Address].



          enter image description here



          How much better it is will depend on the unique value ratio of dbo.Haul. Less unique values means a better outcome for the second execution plan, since the left join has to process less values.



          The other positive result of the second query is that only the uniqueness of ID_DestinationAddress is calculated, not the uniqueness of all the columns as a whole in the group by.



          Again, you should test & validate the results for your query, dataset & indexes. One of the ways to test if you are not familiar with execution plans is setting SET STATISTICS IO, TIME ON; before executing the queries and making these runtime stats more readable by pasting them in a tool such as statisticsparser.




          Testing



          A small test to show what differences in data can do for these queries.



          If the dbo.Haul table does not have many matches with the 5 records returned by the FULLTEXT index filtering, the difference is not so big:



          Group by query plan



          Subquery Query plan



          1000 rows could get filtered earlier, but the execution time is around 15ms for both queries anyway on my machine.



          Now, if I change my data so these 5 records have many more matches with dbo.Haul on the left join:



          The difference between the group by query
          enter image description here



           <QueryTimeStats CpuTime="1564" ElapsedTime="1566" />


          And the Subquery becomes more clear



          enter image description here



          and the stats:



          <QueryTimeStats CpuTime="680" ElapsedTime="690"/>





          share|improve this answer




























          • Thank you very much for all your valuable ideas and tips. The tool and the set statistics command is very helpful. I guess, that I have to wait a while, until there is a significant amount of data in my database. At the moment, there are so few data entries, that the execution time is below 1 ms.

            – André Reichelt
            Oct 14 at 9:41











          • @AndréReichelt No problem glad it helped :). I'll try to replicate your query plan when I have the time

            – Randi Vertongen
            Oct 14 at 9:46












          • @AndréReichelt added a small extra example

            – Randi Vertongen
            Oct 14 at 10:05






          • 1





            @AndréReichelt Nicely spotted, it got cut out for some reason, I re added it, thanks!

            – Randi Vertongen
            Oct 14 at 14:18






          • 1





            @AndréReichelt That is one of the factors to take in account, also how much aggreggation you have on these ID's will matter. It might be that it does not matter in the end for your dataset, but I would prefer the second one nonetheless, just to get that stream aggregate earlier in the execution plan. Happy to help!

            – Randi Vertongen
            Oct 14 at 16:02












          Your Answer








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          1 Answer
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          active

          oldest

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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          7


















          If you change the left join with dbo.Haul to a subquery, it will calculate these distinct values of ID_DestinationAddress (Stream Aggregate) and Count them (Compute scalar) directly after getting the data from the scan.



          This is what you are seeing in the execution plan:



          enter image description here



          While, when using the GROUP BY method it is only doing the grouping after data passed through the left join between dbo.Haul and dbo.[Address].



          enter image description here



          How much better it is will depend on the unique value ratio of dbo.Haul. Less unique values means a better outcome for the second execution plan, since the left join has to process less values.



          The other positive result of the second query is that only the uniqueness of ID_DestinationAddress is calculated, not the uniqueness of all the columns as a whole in the group by.



          Again, you should test & validate the results for your query, dataset & indexes. One of the ways to test if you are not familiar with execution plans is setting SET STATISTICS IO, TIME ON; before executing the queries and making these runtime stats more readable by pasting them in a tool such as statisticsparser.




          Testing



          A small test to show what differences in data can do for these queries.



          If the dbo.Haul table does not have many matches with the 5 records returned by the FULLTEXT index filtering, the difference is not so big:



          Group by query plan



          Subquery Query plan



          1000 rows could get filtered earlier, but the execution time is around 15ms for both queries anyway on my machine.



          Now, if I change my data so these 5 records have many more matches with dbo.Haul on the left join:



          The difference between the group by query
          enter image description here



           <QueryTimeStats CpuTime="1564" ElapsedTime="1566" />


          And the Subquery becomes more clear



          enter image description here



          and the stats:



          <QueryTimeStats CpuTime="680" ElapsedTime="690"/>





          share|improve this answer




























          • Thank you very much for all your valuable ideas and tips. The tool and the set statistics command is very helpful. I guess, that I have to wait a while, until there is a significant amount of data in my database. At the moment, there are so few data entries, that the execution time is below 1 ms.

            – André Reichelt
            Oct 14 at 9:41











          • @AndréReichelt No problem glad it helped :). I'll try to replicate your query plan when I have the time

            – Randi Vertongen
            Oct 14 at 9:46












          • @AndréReichelt added a small extra example

            – Randi Vertongen
            Oct 14 at 10:05






          • 1





            @AndréReichelt Nicely spotted, it got cut out for some reason, I re added it, thanks!

            – Randi Vertongen
            Oct 14 at 14:18






          • 1





            @AndréReichelt That is one of the factors to take in account, also how much aggreggation you have on these ID's will matter. It might be that it does not matter in the end for your dataset, but I would prefer the second one nonetheless, just to get that stream aggregate earlier in the execution plan. Happy to help!

            – Randi Vertongen
            Oct 14 at 16:02















          7


















          If you change the left join with dbo.Haul to a subquery, it will calculate these distinct values of ID_DestinationAddress (Stream Aggregate) and Count them (Compute scalar) directly after getting the data from the scan.



          This is what you are seeing in the execution plan:



          enter image description here



          While, when using the GROUP BY method it is only doing the grouping after data passed through the left join between dbo.Haul and dbo.[Address].



          enter image description here



          How much better it is will depend on the unique value ratio of dbo.Haul. Less unique values means a better outcome for the second execution plan, since the left join has to process less values.



          The other positive result of the second query is that only the uniqueness of ID_DestinationAddress is calculated, not the uniqueness of all the columns as a whole in the group by.



          Again, you should test & validate the results for your query, dataset & indexes. One of the ways to test if you are not familiar with execution plans is setting SET STATISTICS IO, TIME ON; before executing the queries and making these runtime stats more readable by pasting them in a tool such as statisticsparser.




          Testing



          A small test to show what differences in data can do for these queries.



          If the dbo.Haul table does not have many matches with the 5 records returned by the FULLTEXT index filtering, the difference is not so big:



          Group by query plan



          Subquery Query plan



          1000 rows could get filtered earlier, but the execution time is around 15ms for both queries anyway on my machine.



          Now, if I change my data so these 5 records have many more matches with dbo.Haul on the left join:



          The difference between the group by query
          enter image description here



           <QueryTimeStats CpuTime="1564" ElapsedTime="1566" />


          And the Subquery becomes more clear



          enter image description here



          and the stats:



          <QueryTimeStats CpuTime="680" ElapsedTime="690"/>





          share|improve this answer




























          • Thank you very much for all your valuable ideas and tips. The tool and the set statistics command is very helpful. I guess, that I have to wait a while, until there is a significant amount of data in my database. At the moment, there are so few data entries, that the execution time is below 1 ms.

            – André Reichelt
            Oct 14 at 9:41











          • @AndréReichelt No problem glad it helped :). I'll try to replicate your query plan when I have the time

            – Randi Vertongen
            Oct 14 at 9:46












          • @AndréReichelt added a small extra example

            – Randi Vertongen
            Oct 14 at 10:05






          • 1





            @AndréReichelt Nicely spotted, it got cut out for some reason, I re added it, thanks!

            – Randi Vertongen
            Oct 14 at 14:18






          • 1





            @AndréReichelt That is one of the factors to take in account, also how much aggreggation you have on these ID's will matter. It might be that it does not matter in the end for your dataset, but I would prefer the second one nonetheless, just to get that stream aggregate earlier in the execution plan. Happy to help!

            – Randi Vertongen
            Oct 14 at 16:02













          7














          7










          7









          If you change the left join with dbo.Haul to a subquery, it will calculate these distinct values of ID_DestinationAddress (Stream Aggregate) and Count them (Compute scalar) directly after getting the data from the scan.



          This is what you are seeing in the execution plan:



          enter image description here



          While, when using the GROUP BY method it is only doing the grouping after data passed through the left join between dbo.Haul and dbo.[Address].



          enter image description here



          How much better it is will depend on the unique value ratio of dbo.Haul. Less unique values means a better outcome for the second execution plan, since the left join has to process less values.



          The other positive result of the second query is that only the uniqueness of ID_DestinationAddress is calculated, not the uniqueness of all the columns as a whole in the group by.



          Again, you should test & validate the results for your query, dataset & indexes. One of the ways to test if you are not familiar with execution plans is setting SET STATISTICS IO, TIME ON; before executing the queries and making these runtime stats more readable by pasting them in a tool such as statisticsparser.




          Testing



          A small test to show what differences in data can do for these queries.



          If the dbo.Haul table does not have many matches with the 5 records returned by the FULLTEXT index filtering, the difference is not so big:



          Group by query plan



          Subquery Query plan



          1000 rows could get filtered earlier, but the execution time is around 15ms for both queries anyway on my machine.



          Now, if I change my data so these 5 records have many more matches with dbo.Haul on the left join:



          The difference between the group by query
          enter image description here



           <QueryTimeStats CpuTime="1564" ElapsedTime="1566" />


          And the Subquery becomes more clear



          enter image description here



          and the stats:



          <QueryTimeStats CpuTime="680" ElapsedTime="690"/>





          share|improve this answer
















          If you change the left join with dbo.Haul to a subquery, it will calculate these distinct values of ID_DestinationAddress (Stream Aggregate) and Count them (Compute scalar) directly after getting the data from the scan.



          This is what you are seeing in the execution plan:



          enter image description here



          While, when using the GROUP BY method it is only doing the grouping after data passed through the left join between dbo.Haul and dbo.[Address].



          enter image description here



          How much better it is will depend on the unique value ratio of dbo.Haul. Less unique values means a better outcome for the second execution plan, since the left join has to process less values.



          The other positive result of the second query is that only the uniqueness of ID_DestinationAddress is calculated, not the uniqueness of all the columns as a whole in the group by.



          Again, you should test & validate the results for your query, dataset & indexes. One of the ways to test if you are not familiar with execution plans is setting SET STATISTICS IO, TIME ON; before executing the queries and making these runtime stats more readable by pasting them in a tool such as statisticsparser.




          Testing



          A small test to show what differences in data can do for these queries.



          If the dbo.Haul table does not have many matches with the 5 records returned by the FULLTEXT index filtering, the difference is not so big:



          Group by query plan



          Subquery Query plan



          1000 rows could get filtered earlier, but the execution time is around 15ms for both queries anyway on my machine.



          Now, if I change my data so these 5 records have many more matches with dbo.Haul on the left join:



          The difference between the group by query
          enter image description here



           <QueryTimeStats CpuTime="1564" ElapsedTime="1566" />


          And the Subquery becomes more clear



          enter image description here



          and the stats:



          <QueryTimeStats CpuTime="680" ElapsedTime="690"/>






          share|improve this answer















          share|improve this answer




          share|improve this answer








          edited Oct 14 at 14:17

























          answered Oct 14 at 7:28









          Randi VertongenRandi Vertongen

          10.5k3 gold badges13 silver badges35 bronze badges




          10.5k3 gold badges13 silver badges35 bronze badges















          • Thank you very much for all your valuable ideas and tips. The tool and the set statistics command is very helpful. I guess, that I have to wait a while, until there is a significant amount of data in my database. At the moment, there are so few data entries, that the execution time is below 1 ms.

            – André Reichelt
            Oct 14 at 9:41











          • @AndréReichelt No problem glad it helped :). I'll try to replicate your query plan when I have the time

            – Randi Vertongen
            Oct 14 at 9:46












          • @AndréReichelt added a small extra example

            – Randi Vertongen
            Oct 14 at 10:05






          • 1





            @AndréReichelt Nicely spotted, it got cut out for some reason, I re added it, thanks!

            – Randi Vertongen
            Oct 14 at 14:18






          • 1





            @AndréReichelt That is one of the factors to take in account, also how much aggreggation you have on these ID's will matter. It might be that it does not matter in the end for your dataset, but I would prefer the second one nonetheless, just to get that stream aggregate earlier in the execution plan. Happy to help!

            – Randi Vertongen
            Oct 14 at 16:02

















          • Thank you very much for all your valuable ideas and tips. The tool and the set statistics command is very helpful. I guess, that I have to wait a while, until there is a significant amount of data in my database. At the moment, there are so few data entries, that the execution time is below 1 ms.

            – André Reichelt
            Oct 14 at 9:41











          • @AndréReichelt No problem glad it helped :). I'll try to replicate your query plan when I have the time

            – Randi Vertongen
            Oct 14 at 9:46












          • @AndréReichelt added a small extra example

            – Randi Vertongen
            Oct 14 at 10:05






          • 1





            @AndréReichelt Nicely spotted, it got cut out for some reason, I re added it, thanks!

            – Randi Vertongen
            Oct 14 at 14:18






          • 1





            @AndréReichelt That is one of the factors to take in account, also how much aggreggation you have on these ID's will matter. It might be that it does not matter in the end for your dataset, but I would prefer the second one nonetheless, just to get that stream aggregate earlier in the execution plan. Happy to help!

            – Randi Vertongen
            Oct 14 at 16:02
















          Thank you very much for all your valuable ideas and tips. The tool and the set statistics command is very helpful. I guess, that I have to wait a while, until there is a significant amount of data in my database. At the moment, there are so few data entries, that the execution time is below 1 ms.

          – André Reichelt
          Oct 14 at 9:41





          Thank you very much for all your valuable ideas and tips. The tool and the set statistics command is very helpful. I guess, that I have to wait a while, until there is a significant amount of data in my database. At the moment, there are so few data entries, that the execution time is below 1 ms.

          – André Reichelt
          Oct 14 at 9:41













          @AndréReichelt No problem glad it helped :). I'll try to replicate your query plan when I have the time

          – Randi Vertongen
          Oct 14 at 9:46






          @AndréReichelt No problem glad it helped :). I'll try to replicate your query plan when I have the time

          – Randi Vertongen
          Oct 14 at 9:46














          @AndréReichelt added a small extra example

          – Randi Vertongen
          Oct 14 at 10:05





          @AndréReichelt added a small extra example

          – Randi Vertongen
          Oct 14 at 10:05




          1




          1





          @AndréReichelt Nicely spotted, it got cut out for some reason, I re added it, thanks!

          – Randi Vertongen
          Oct 14 at 14:18





          @AndréReichelt Nicely spotted, it got cut out for some reason, I re added it, thanks!

          – Randi Vertongen
          Oct 14 at 14:18




          1




          1





          @AndréReichelt That is one of the factors to take in account, also how much aggreggation you have on these ID's will matter. It might be that it does not matter in the end for your dataset, but I would prefer the second one nonetheless, just to get that stream aggregate earlier in the execution plan. Happy to help!

          – Randi Vertongen
          Oct 14 at 16:02





          @AndréReichelt That is one of the factors to take in account, also how much aggreggation you have on these ID's will matter. It might be that it does not matter in the end for your dataset, but I would prefer the second one nonetheless, just to get that stream aggregate earlier in the execution plan. Happy to help!

          – Randi Vertongen
          Oct 14 at 16:02











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