Efficient Value Update with Large Database I have a table as large as 8GB and with 20M records. There is an int field called mth. The mth field stores date information in form of YYYYMM, I want to transform the mth field to consecutive integers. So I use a formula to get the year and month from field mth and calculate the month order, specifically, I use the following code:

create function mth_to_num(@month int)
returns int
as 
begin
   return(round(@month/100,0)*12+@month-100*round(@month/100,0))
end


Then I use the following code to update the value in the huge table

update full_orig_month_Q1_1999 
set mth_order = dbo.mth_to_num(period)
Go 


However, the code took quite long time to execute, roughly 2-3 minutes. My system is windows 10 64 bit with SQL server 2016. Is there any way I can speed it up?

Another problem is that I found SQL server occupying as much as 8GB in the database after executing the above query. Does it need so much memory? How can I release them?

Thanks for your help in advance!

Jason
When possible don't use scalar user defined functions (UDF) in queries. They force the entire plan to be serial, they can cause a lot of additional CPU resources to be used, they are a black box to the optimizer and can lead to cardinality estimation issues in other parts of the plan, and they can result in needlessly large memory grants.

Try running your UPDATE query without the UDF. Just take the code that you have and put it into the UPDATE query directly. Something like this:

update full_orig_month_Q1_1999 
set mth_order = round(period/100,0)*12+period-100*round(period/100,0);


Does that improve the runtime and memory usage?