Michael J. Swart

The last ACID property is D, Durability. Again, Haerder and Reuter describe Durability:

“Once a transaction has been completed and has committed its results to the database, the system must guarantee that these results survive any subsequent malfunctions.”

What does this mean exactly? That’s a tall order for a database system! I mean any malfunction whatsoever? I’m pretty sure our database systems are designed to survive a power failure but I don’t expect that they could survive something as severe as the heat death of the universe.

Actually databases don’t have to go that far. When designing a database system, only two kinds of malfunctions are considered: media failure and system failure.

Media Failures

For media failure (e.g. a faulty hard drive) databases are recovered by using backups and transaction logs. And this leads directly to three bits of super-common DBA advice:

• Take backups regularly.
• Keep your transaction logs and your main database files on different hard drives.
• When dealing with a disk failures, step one is backing up the tail of the log

System Failures

System failures (e.g. system crashes, power outages etc…) have to be handled too.

SQL Server does it this way. When SQL Server is processing transactions, it will first write changes to a transaction log and then write the associated changes to the database file. Always always in that order (There’s a bit more too it, but that’s the main part). It’s called the Write-Ahead Transaction Log.

But when there’s a system malfunction, a few things need to be cleaned up the next time the server restarts (to maintain atomicity and consistency). There may be transactions that were interrupted and not yet committed. And some transactions may not have their changes written to disk, or sometimes not written completely to disk. How do you recover from stuff like that?

Well the database recovers from a failure like that during a startup process called (unsurprisingly) “recovery”. It can look at these half-performed transactions and it can roll them back using the info in the logs. Or alternatively it can roll-forward and replay committed transactions that haven’t made it to disk if the conditions are right and there’s enough info in the transaction log to do so. (Further Information at MCM Prep Video: Log File Internals and Maintenance)

So What Does This Mean To You?

If an ACID database system like SQL Server reports that your transaction has committed successfully then because it’s durable, your transaction is truly persisted: You don’t have to worry about buffer flushes or power failures “losing” your work.

Example

So what is interestingly durable? Durability in database systems usually means that something is redundant so that if one thing is lost, the transaction is not lost. So I give a list here of things that are too redundant:

• The Hydra‘s heads (Greek Mythology)
• Enchanted Brooms from the Sorcerer’s Apprentice.
• Autofac (An interesting short story by Philip K. Dick which I finished reading last night).

Counter-Example

I have two examples and they both come from the career of Richard Harris (best known to my family as the first Dumbledore). Did you know he was a one-hit wonder? He had a hit single in the seventies called MacArthur Park. If you’ve never heard the song, skip this article and experience the utter madness that is MacArthur Park. You won’t regret it.

Back to the example. The singer of MacArthur Park would like to have his cake. Unfortunately, it’s been left out in the rain (malfunction). But that’s okay right? He could always get out the recipe (transaction log) and make a new one right? Wrong! He’ll never have that recipe again (durability fail). Had he persisted that recipe, the poor sucker would still have his cake.

Bonus Richard Harris Counterexample

You may remember he played Emperor Marcus Aurelius in the movie Gladiator. (Spoiler alert!) In that movie, he plans to make Maximus his heir instead of his son Commodus. He first tells his plans to Maximus (who is reluctant to rule Rome) and then he tells Commodus who did not take the news well at all. In fact he murdered his father after hearing it!  The Emperor’s plans never make it to the public and so Commodus becomes Emperor.

You see, his plans to make Maximus his heir was not durable! Had the Emperor told a bunch of other people first, then his intended heir Maximus would have ruled Rome as he wanted (Not to mention it would have removed the motive for his murder).

That’s The Series

So that’s it. I had fun with it. It gave me a chance to “geek out”. And even though blog post series are a nice way of treating a topic in depth, I still found myself struggling to keep each article to blog-post length. There’s just so much to learn here. I guarantee I learned more writing this series than a reader would reading it 😉

Tell me what you think!

So the third ACID property of database transactions is I for Isolation. This is the only ACID property that deals with behaviour of a transaction with respect to other concurrent transactions (all the other properties describe the behaviour of single transactions). Haerder and Reuter describe it as:

Isolation: Events within a transaction must be hidden from other transactions running concurrently.

It’s not super-rigorous, but I think of it like this: No looking at works-in-progress

(Actually, I don’t always believe in that advice, but it helps the cartoon)

So there are different kinds of database isolation. Even with the the guideline: no looking at other transactions in progress. And now these levels of isolation are well defined. I wrote a series on those earlier, the different levels are READ UNCOMMITTED, READ COMMITTED, REPEATABLE READ and SERIALIZABLE. By the way READ UNCOMMITTED is the only isolation level here that is not really isolated, more on that later.

Isolation in SQL Server

SQL Server supports all of these isolation levels. It enforces this isolation using various locks on data (fascinating stuff actually), processes will wait to maintain isolation. In contrast, Oracle supports only SERIALIZABLE and a kind of READ COMMITTED that is closer in behaviour to SQL Server’s SNAPSHOT isolation. No matter how it’s implemented, READ COMMITTED is the default isolation level in both SQL Server and Oracle.

Unisolated Transactions:

So it is possible for other transactions to see the effects of a transaction in-flight (i.e. as it’s happening, before it’s committed). This is done with NOLOCK hints or with the READ UNCOMMITTED isolation level. In fact, I learned recently that when using NOLOCK hints, you not only can see the effects of an in-flight transaction, but you can see the effects of an in-flight statement. This is an Isolation failure and it boils down to this: SQL Server transactions are atomic, but when using NOLOCK, it might not seem that way. So take care.

Example

Today’s example and counterexample both come from the newspapers headlines of Chicago.

For the example – a fictional example – I explain a situation that’s all about not making assumptions. It’s all about being cautious and not committing to a decision while the jury’s still out. This immediately brought to mind a scene from the movie Chicago [spoiler alert!] :

The movie (and play) is about a court case. The main character Roxie is on trial for murder. It’s a sensational trial and the papers are eager to publish the results of the trial. The papers are so eager in fact that the papers have printed out two editions of their newspapers. One headline read “She’s Innocent” the other headline read “She’s Guilty”. But those two stacks of papers are just sitting there in the van. The man in the newspaper van waits for a signal from the courthouse. Once he got the proper signal, he cracked open the innocent edition and gave them to a paper boy to hand out.

It’s about not acting on information while the jury is still out. The jury is isolated from the world and no one can act on what the jury has to say until they’ve committed to a verdict.

Counter-Example

Our counter-example comes from non-fiction. In reality, the assumptions we make tend to be correct. Our assumptions are only interesting when they turn out to be incorrect. This counter-example comes from the most incorrect newspaper headline I can think of:

“Dewey Defeats Truman”

Click through for Wikipedia’s page on cool piece of newspaper history (Chicago newspaper history). It’s a great example of what can go wrong when we act on tentative (uncommitted) information. The Chicago Tribune published the wrong presidential candidate as the winner.

But the really really cautious reporters would report neither candidate as the winner. They’d be waiting at the Electoral College convention. They’d be keen on seeing how that turns out.