That’s right; SQL Server will just pick any child. It will not update the parent row for each child. When the MERGE statement runs into this problem, it raises an error and rolls back the UPDATE but our query will silently pick any value and move on. We don’t want to update data like this, we want our query to dictate the logic explicitly. This will require some changes to our query.
I prefer to write these types of updates with the use of a CTE. This allows us to easily highlight the SELECT in the CTE and execute it to see which rows will be updated (@variables can cause problems here though). Adding a COUNT can help to identify the problem in the previous query.
Highlight and execute the code inside the CTE below to check for duplicates. If this returns 0 rows then you are good to remove the COUNT, GROUP BY and HAVING then add the name columns before executing the whole statement.
When writing T-SQL updates with joins, it’s important to consider whether the grain changes, and if that change can make a difference in your update set.
So here, the JSON and
STRING_SPLITmethods took about 10 seconds each, while the Numbers table, CLR, and XML approaches took less than a second. Perplexed, I investigated the waits, and sure enough, the four methods on the left incurred significant
LATCH_EXwaits (about 25 seconds) not seen in the other three, and there were no other significant waits to speak of.
And since the latch waits were greater than total duration, it gave me a clue that this had to do with parallelism (this particular machine has 4 cores). So I generated test code again, changing just one line to see what would happen without parallelism:
There’s a lot going on in that post, so I recommend checking it out.
Someone posted to #sqlhelp on Twitter, asking the following: “Wondered if anyone could enlighten me as to why ISNUMERIC(‘7d8’) returns 1?”
SELECT ISNUMERIC('7d8')returns a 1.
Great answer and explanation, and his advice to use TRY_CONVERT() for 2012 and up is spot-on.
Let it be known that the word “backup” is a noun (it refers to a thing), and “back up” is a verb (it refers to an action.
I’m going to back up the database.
It will produce a backup.
I’ll save that backup until we back up the database three more times.
Now back up a moment here; I need to come up with a backup plan…
Simple sorts are pretty easy. In the ORDER BY clause you can list out the columns by name or by position in the field list and determine if you want them sorted ascending or descending. But how about going beyond that?
Every now and again you need a fairly complex sort order. Say for example you want to order your data differently depending on the Status (say DueDate if theStatus is 1, 2 or 3 and ShipDate otherwise). But you also want anyone with aTotalDue greater than $5000 sorted separately from those with a TotalDue less than $5000.
Conditional sorting isn’t something you should be doing in every query, but it’s important enough to know about.
I got asked a question about the OUTPUT clause recently and realized I didn’t remember the syntax. I’ve rarely used this, so I had to look it up and thought this would be a good basic post.
The idea with OUTPUT is that the data from the inserted and deleted tables can be output from the INSERT statement, outside of your triggers. This is the same data, but you can access it in the insert.
The format is
INSERT xxx OUTPUT yyyy INTO @zzz VALUES (or SELECT) mmmm
If I had one thing I could change about OUTPUT, I’d like to be able to output directly into variables for those cases in which I know I’m only going to get one result (or maybe I only care about one arbitrary result in a set).
What makes this interesting is when I am using UNION to join the results. How do you place a final resultset from a UNION, EXCEPT, or INTERSECT into a temporary table using SELECT INTO? Where does the INTO portion of the query go?
This is actually a pretty simple thing to do. The INTO for the SELECT INTO goes into the first query of the set. An example of UNIONing the results from sys.dm_exec_query_stats and sys.dm_exec_query_stats into a temporary table is provided in listing 1.
No subqueries are necessary here.
The new String_Split function is a table function which has two inputs:
String_Split(<main string as input>,<delimiter>)
Usage of it should be within From clause of your query because this is a table function.
I’m curious to see how this compares performance-wise to CLR and tally table split methods.
Let’s say you have a table called
dbo.BugReports, and you need to change it to
dbo.SupportIncidents. This can be quite disruptive if you have references to the original name scattered throughout stored procedures, views, functions, and application code. Modern tools like SSDT can make a refactor relatively straightforward within the database (as long as queries aren’t constructed from user input and/or dynamic SQL), but for distributed applications, it can be a lot more complex.
A synonym can allow you to change the database now, and worry about the application later – even in phases. You just rename the table from the old name to the new name (or use
ALTER TABLE ... SWITCHand then drop the original), and then create a synonym named with the old name that “points to” the new name
I’ve used synonyms once or twice, but they’re pretty low on my list, in part because of network effects: if I create this great set of synonyms but the next guy doesn’t know about them, it makes maintenance that much harder.
So here is the thing. When you change one you change them all. That means if you don’t specify a precision when you can then you get the default. That’s not exactly a common problem though. Usually what you are changing is the precision (or possibly the datatype). What is a common mistake is not specifying the nullability.
When modifying DDL, make sure that you keep it consistent and complete.