Check Your Transactions

John Morehouse talks about a mistake he made:

The other day I had to update some records, in Production.  I’m a firm believer of using explicit transactions and double checking things before committing a transaction.  This helps ensure things go as expected.  This also allows me a way to rollback the changes if they don’t.  It happens.

However, this means that I have to COMMIT said explicit transaction.  And not go to lunch without doing so.

Can you see my mistake?  I bet you can.

Fortunately, it sounds like it wasn’t a critical problem.  If you want to check for open transactions, Jack Vamvas has a couple methods.

Backups Causing Transaction Log Growth In Simple Mode

Andy Mallon explains why the transaction log will grow during a backup even if you’re in simple recovery mode:

When SQL Server begins backing up data pages, it also starts keeping track of transactions, via the transaction log. After it has backed up the last data page, it then also backs up all of the transactions that occurred during the data backup. Upon restore, it will then roll those transactions forward or backward, as necessary, to ensure a consistent image is restored.

In our librarian metaphor, she would keep an activity log, which would include the changes to books A and D from the first update, then also the changes to D, X, Y, and Z from the second update. She would not “fix” the data within the backup, but simply store those update details along with her mashed-up copy. In the unlikely event she had to recreate the books (ie, a restore), then she would go back and spend the effort to piece it back together. During that restore process, she would look at the first transaction and see that her copy of Book A in her backup was too old, but Book D already had the update, and she would roll forward the update to Book A. Next, she would process the second update and see that Books X, Y, and Z had the updates, but D still needed this second update, and she would roll forward that second update to Book D. At this point, she would have successfully reconstructed an image that is consistent to the time the backup completed.

Great metaphor to describe consistency during backups.

Finding Transactions After A Crash

Paul Randal has a procedure which will find rolled-back transactions after a crash:

Then we can search in the transaction log, using the fn_dblog function, for LOP_BEGIN_XACT log records from before the crash point that have a matching LOP_ABORT_XACT log record after the crash point, and with the same transaction ID. This is easy because for LOP_BEGIN_XACT log records, there’s a Begin Time column, and for LOP_ABORT_XACT log records (and, incidentally, for LOP_COMMIT_XACT log records), there’s an End Time column in the TVF output.

And there’s a trick you need to use: to get the fn_dblog function to read log records from before the log clears (by the checkpoints that crash recovery does, in the simple recovery model, or by log backups, in other recovery models), you need to enable trace flag 2537. Now, if do all this too long after crash recovery runs, the log may have overwritten itself and so you won’t be able to get the info you need, but if you’re taking log backups, you could restore a copy of the database to the point just after crash recovery has finished, and then do the investigation.

Read on for the code, as well as a test.

Doomed Transactions

Michael Swart talks about doomed transactions:

So the procedure was complicated and it used explicit transactions, but I couldn’t find any TRY/CATCH blocks anywhere! What I needed was a stack trace, but for T-SQL. People don’t talk about T-SQL stack traces very often. Probably because they don’t program like this in T-SQL. We can’t get a T-SQL stack trace from the SQLException (the error given to the client), so we have to get it from the server.

Michael shows how to get stack trace information and provides some advice on the process (mostly, “don’t do what we did”).

Identity Column Rollback

David Alcock figures out how identity columns behave when transactions get rolled back:

Identity columns are a very commonly used feature within tables in SQL Server. Basically when specified as an identity a column will automatically increment by the specified value; so if we have an identity increment of 1 and insert 5 rows they will automatically be numbered 1 to 5.
One cautionary measure with identities is that they don’t reset themselves when rows are deleted. If we delete rows 4 and 5 the next row will still be populated as identity 6. That’s fine, but what happens if we rollback an insert.

Read on for the answer.

Log Buffers

Mark Broadbent has started a series on transaction durability.  His first topic is the log buffer:

SQL Server is a highly efficient transaction processing platform and nearly every single operation performed by it, is usually first performed within memory. When operations are performed within memory, the need to touch physical resources (such as physical disk IOPS) are also reduced, and reducing the need to touch physical resources means those physical boundaries (and their limitations) have less impact to the overall system performance. Cool right?!

Click through to read more about how log buffers work and why they help improve SQL Server’s performance.

Transaction Names Are Case Sensitive

Clive Strong notes that transaction names in SQL Server are case sensitive:

I had an issue today running a colleague’s code (the rollback and commit were commented out, but that is another story). The code failed and I tried to rollback the transaction but received this error message;

Msg 6401, Level 16, State 1, Line 5
Cannot roll back t1. No transaction or savepoint of that name was found.

I can’t remember the last time I named a transaction, but if you are in that habit, it’s important to remember.

Log Chains

Dave Mason discusses broken log chains:

There are a handful of activities that have broken my SQL Server backup routines. Sometimes a DIFFERENTIAL (or LOG) backup would fail because there was no FULL backup. Other times, a LOG backup would fail because the log chain was broken. Some of those activities include:

  1. Creating a new database.

  2. Changing the recovery model to SIMPLE.

  3. Restoring/reverting a database from a snapshot.

  4. Any other activity that breaks the transaction log chain.

Dave discusses an easy way of figuring out if you’ve just performed an activity which breaks the log chain.

Identifying Object Names Using fn_dblog()

Frank Gill digs into the transaction log to find object names used in CREATE and ALTER statements:

This is the object id of the view that was created.  So, Jes’s question was answered.  But this led me to one of my other favorite SQL Server topics: string manipulation.  The following script will identify all transactions for a particular Transaction Name and return the object name affected.  The comments provide additional information about the functionality.

Click through to check out Frank’s script.

Analyze Transaction Log Hierarchy

Paul Randal has written code to determine how much log an operation has generated:

Over the weekend there was a discussion on the MVP distribution list about the sys.dm_tran_database_transactions DMV and how one cannot use it to accurately determine how much log an operation has generated because it doesn’t provide a roll-up of the sub-transaction metrics to the outer transaction. This makes the output somewhat non-intuitive.

The discussion prompted me to write some code I’ve been meaning to do since 2012, when SQL Server 2012 introduced a field in LOP_BEGIN_XACT log records that tracks the transaction ID of the parent transaction, allowing the hierarchy of transactions to be investigated.

The actual code is at the bottom of the article, and is available in a zip file here.

It provides two stored procs, sp_SQLskillsAnalyzeLog and sp_SQLskillsAnalyzeLogInner, with the former making use of the latter, and the latter calling itself recursively.

I’d consider this squarely in the advanced troubleshooting realm.  Definitely read the whole thing and Paul’s code.

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May 2017
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