SQL Server – Monitoring a Rollback

Recently bumped into an issue where we needed to kill a large insert, obviously causing SQL Server to perform a rollback. I needed to find out what was going on, so looked to Pinal Dave’s blog post about finding out which queries are running, which you can find here. Which uses the sys.dm_exec_requests and sys.dm_exec_sql_text DMVs.

The below script adds a few little things, to tell you for a given SPID, what the SQL text is that’s being executed and most importantly the expected finish time.

--Set how long you want the script to run for in HH:MM:SS format.
--The longer you leave it running the more accurate it will be
DECLARE @Delay VARCHAR(20)	= '00:00:10';

--Add your SPID, which you can get from sp_who2
DECLARE @SPID INT			= 206;


DECLARE @StartPercent DECIMAL(18,9), @Statement VARCHAR(MAX), @EndPercent DECIMAL(18,9), @DelaySeconds INT, @PercentToGo DECIMAL(18,9), @Increase DECIMAL(18,9);

--Set the starting percentage complete
SELECT @StartPercent = req.percent_complete, @Statement = sqltext.TEXT
FROM sys.dm_exec_requests req
CROSS APPLY sys.dm_exec_sql_text(sql_handle) AS sqltext
WHERE session_id = @SPID

--Wait for the specified delay time
WAITFOR DELAY @Delay

--Get the end percentage complete
SELECT @EndPercent = req.percent_complete
FROM sys.dm_exec_requests req
WHERE session_id = 206

SET @PercentToGo = 100 - @EndPercent;
SET @Increase = @EndPercent - @StartPercent
SET @DelaySeconds = DATEDIFF(SECOND, 0, @Delay)

--Return the output including the expected finish time
SELECT @SPID [SPID], @Statement [SQLText], @DelaySeconds [DelaySeconds], @StartPercent [StartPercent], @EndPercent [EndPercent], @Increase [Increase], DATEADD(SECOND,(@PercentToGo / @Increase) * @DelaySeconds, GETDATE()) [ExpectedFinishTime]

 

You can use the same query to monitor the below events (source):

ALTER INDEX REORGANIZE
AUTO_SHRINK option with ALTER DATABASE
BACKUP DATABASE
DBCC CHECKDB
DBCC CHECKFILEGROUP
DBCC CHECKTABLE
DBCC INDEXDEFRAG
DBCC SHRINKDATABASE
DBCC SHRINKFILE
RECOVERY
RESTORE DATABASE
ROLLBACK
TDE ENCRYPTION

SQL Server – Join to list of Strings

This one can also be used when passing a multi-value parameter from SSRS to the database.

Firstly you need to use the delimited8k split function that was created and refined by many people such as Itzek Ben Gan, Lynn Pettis and Jeff Modern. If you don’t know who these people are, go and find out as there’s some excellent reading to be had. Anyway, you can download the function here: http://www.sqlservercentral.com/articles/Tally+Table/72993/

Here’s some code you can use to see it in action: 

DECLARE @IntsAsStrings VARCHAR(100) = '1,2,3,4,5,6,7,8,9';

DECLARE @TestTable TABLE 
(
	Id INTEGER IDENTITY(1,1),
	ValueString VARCHAR(50)
);

INSERT INTO @TestTable VALUES ('We'),('Are'),('Leeds'),('MOT');

SELECT *
FROM @TestTable t
RIGHT JOIN [dbo].[DelimitedSplit8K](@IntsAsStrings, ',') ss ON ss.ItemNumber = t.Id

You can then pass a string into your proc and at the top split that out into a table or join directly onto the split function table results (as it’s a Table Valued Function (TVF)).

Merge – Incremental Soft Delete

Sometimes we may have situations where we only load a day’s worth of data into our data warehouse. We may also need to keep the destination data in line with the incoming data.

For instance, imagine we had a shopping basket filled with items one day, which we load into our data warehouse, but the next day (for whatever reason) two of the products are no longer valid. How can we remove these records without deleting all of the other values in our data warehouse for our other trolleys that aren’t in the incoming data set?

The answer is with an incremental MERGE: 

--Declare temp tables to store data
DECLARE @Target TABLE
(
PackageId INTEGER,
JournalId INTEGER,
Amount MONEY,
IsDeleted BIT DEFAULT 0
)


DECLARE @Source TABLE
(
PackageId INTEGER,
JournalId INTEGER,
Amount MONEY
)

--Insert some dummy data
INSERT INTO @Source VALUES (1,1,10),(1,2,20),(1,3,30),(2,1,40),(2,2,50)

--Now merge it into the destination table.
MERGE INTO @Target AS TARGET
	USING
	@Source AS SOURCE
	ON TARGET.PackageId = SOURCE.PackageId
	AND TARGET.JournalId = SOURCE.JournalId

--When we match on the merge key, then update the destination table with the new value
WHEN MATCHED THEN
	UPDATE SET
		TARGET.Amount = Source.Amount

--Whne we don't match, then we're a new record, so insert the new record into the destination
WHEN NOT MATCHED BY TARGET THEN
	INSERT
	(
	PackageId,
	JournalId,
	Amount
	)
	VALUES
	(
	SOURCE.PackageId,
	SOURCE.JournalId,
	SOURCE.Amount
	);

--Now show our results.
SELECT * FROM @Source;
SELECT * FROM @Target;


--Now let's get rid of some data and carry out an update to show how we would handle a merge for
--an incremental load
DELETE FROM @Source WHERE PackageId = 1 OR (PackageId = 2 AND JournalId = 1);
UPDATE @Source SET Amount = Amount + 20

--Use a CTE to limit the destination rows we want to match against, becuase if we've only loaded
--1 day worth of values in from our source system, we could end up deleting lots of data by accident
;WITH tgtCTE AS
(
SELECT T.*
FROM @Source S
INNER JOIN @Target T ON T.PackageId = S.PackageId
)


MERGE INTO tgtCTE AS TARGET
	USING @Source AS SOURCE
	ON TARGET.PackageId = SOURCE.PackageId
	AND TARGET.JournalId = SOURCE.JournalId

--Again, update any existing records
WHEN MATCHED THEN
	UPDATE SET
		TARGET.Amount = Source.Amount

--Again, insert any new records
WHEN NOT MATCHED BY TARGET THEN
	INSERT
	(
	PackageId,
	JournalId,
	Amount
	)
	VALUES
	(
	SOURCE.PackageId,
	SOURCE.JournalId,
	SOURCE.Amount
	)

--Here is the intersting part; we're going to soft delete any records from the 
--destination table that do not exist in the incoming data set.
WHEN NOT MATCHED BY SOURCE THEN UPDATE SET TARGET.IsDeleted = 1;


--Show our final results. As you can see in the second merge we only had 1 record for PackageId = 2
--the other JournalId didn't exist in the source table, so it was soft deleted from the destination.
SELECT * FROM @Source;
SELECT * FROM @Target;

Go ahead and run the above code and see how it all works. Hopefully this will help you on your way.

Paul White gives a great example here at DBA.StackExchange