#SECTION VIEW IN MASTERCAM 2019 SERIES#
He is the creator of one of the biggest free online collections of articles on a single topic, with his 50-part series on SQL Server Always On Availability Groups. He is the author of hundreds of authoritative articles on SQL Server, Azure, MySQL, Linux, Power BI, Performance tuning, AWS/Amazon RDS, Git, and related technologies that have been viewed by over 10m readers to date. In the below query, our UDF shows value 1 that means SQL Server 2019 can incline this function.Īs an MCSA certified and Microsoft Certified Trainer in Gurgaon, India, with 13 years of experience, Rajendra works for a variety of large companies focusing on performance optimization, monitoring, high availability, and disaster recovery strategies and implementation. Run the below query and pass the scalar function name in it.
![section view in mastercam 2019 section view in mastercam 2019](http://5b0988e595225.cdn.sohucs.com/images/20190320/f0069aaae0eb4acf8e4ba399424719db.jpeg)
SQL Server 2019 introduced new column is_inlineable in sys.sql_modules. We can check whether the SQL Server is able to inline a particular scalar UDF or not. Therefore, we get the performance benefits in terms of CPU, memory, execution time etc. It does not consider this UDF as a separate identify however runs it similar to a normal select statement. SQL Server 2019 inlines the scalar UDF to optimize the execution of the query. You can see multiple operators to execute the query. In this execution plan, it shows the UDF in the lower area. In SQL Server 2019, it is able to combine the UDF operations into a single query plan due to inline functionality. Now, if we look at the actual estimated plan in SQL Server 2019, we get a complex plan compare with the earlier execution plan, as shown in below image. SQL Server needs to do an extra work each time this UDF function is called. Therefore, SQL Server treats Scalar UDF function as a separate identity until SQL Server 2017. In below plan, it shows the separate execution plan for both the query and the UDF function. We will get a more clear idea about this in the estimated execution plan. In this section, we will compare the execution plan on running the scalar UDF with SQL Server 2019 and before.īelow is the actual execution plan when we run the scalar UDF with compatibility level 140( SQL Server 2017 or before) In below table, you can see the Scalar user-defined functions performance optimization comparison with SQL Server 2019 If we compare both the execution with compatibility level 140 (SQL Server 2017) and 150 (SQL Server 2019), we can see a significant improvement over the CPU time and the elapsed time. Scan count 1, logical reads 3504, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.ĬPU time = 1071719 ms, elapsed time = 1109655 ms. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Scan count 0, logical reads 0, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0.ĬPU time = 15287 ms, elapsed time = 18782 ms. Scan count 227, logical reads 730037, physical reads 0, read-ahead reads 0, lob logical reads 0, lob physical reads 0, lob read-ahead reads 0. Scan count 5, logical reads 857, physical reads 0, read-ahead reads 0, lob logical reads 180, lob physical reads 0, lob read-ahead reads 0.
![section view in mastercam 2019 section view in mastercam 2019](https://help.autodesk.com/cloudhelp/2019/ENU/Civil3D-Tutorials/images/GUID-19B8C7B0-1878-4356-A0A7-8BDFE601CB72.png)
Now let us run the queries again in both SQL Server 2016 and SQL Server 2019 database compatibility level and capture the statistics IO and statistics time along with the actual execution plan to compare with.
![section view in mastercam 2019 section view in mastercam 2019](https://www.sme.org/globalassets/sme.org/technologies/articles/2018/06---june/0618_cnc-software-mastercam-2019-768x432.jpg)
Relatively, it is very fast to process these results. In SQL Server 2019, you can notice the query completed in just 19 seconds to process 228,176 rows compared to 12 minutes in SQL Server 2016. Run the query again with this modified compatibility level. The query batch inside this function is a single statement, therefore, it does not provide any performance issues when we use it batches or in loops.īelow is an example of inline table valued function. Inline table-valued functions: Inline table values functions are performance optimized functions.
![section view in mastercam 2019 section view in mastercam 2019](https://wiki.harvard.edu/confluence/download/attachments/236866986/roughparallel.gif)