Why use a READ UNCOMMITTED isolation level?

Question

This isolation level allows dirty reads. One transaction may see uncommitted changes made by some other transaction.

To maintain the highest level of isolation, a DBMS usually acquires locks on data, which may result in a loss of concurrency and a high locking overhead. This isolation level relaxes this property.

You may want to check out the Wikipedia article on READ UNCOMMITTED for a few examples and further reading.

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You may also be interested in checking out Jeff Atwood's blog article on how he and his team tackled a deadlock issue in the early days of Stack Overflow. According to Jeff:

But is nolock dangerous? Could you end up reading invalid data with read uncommitted on? Yes, in theory. You'll find no shortage of database architecture astronauts who start dropping ACID science on you and all but pull the building fire alarm when you tell them you want to try nolock. It's true: the theory is scary. But here's what I think: "In theory there is no difference between theory and practice. In practice there is."

I would never recommend using nolock as a general "good for what ails you" snake oil fix for any database deadlocking problems you may have. You should try to diagnose the source of the problem first.

But in practice adding nolock to queries that you absolutely know are simple, straightforward read-only affairs never seems to lead to problems... As long as you know what you're doing.

One alternative to the READ UNCOMMITTED level that you may want to consider is the READ COMMITTED SNAPSHOT. Quoting Jeff again:

Snapshots rely on an entirely new data change tracking method ... more than just a slight logical change, it requires the server to handle the data physically differently. Once this new data change tracking method is enabled, it creates a copy, or snapshot of every data change. By reading these snapshots rather than live data at times of contention, Shared Locks are no longer needed on reads, and overall database performance may increase.

My favorite use case for read uncommited is to debug something that is happening inside a transaction.

Start your software under a debugger, while you are stepping through the lines of code, it opens a transaction and modifies your database. While the code is stopped, you can open a query analyzer, set on the read uncommited isolation level and make queries to see what is going on.

You also can use it to see if long running procedures are stuck or correctly updating your database.

It is great if your company loves to make overly complex stored procedures.

This can be useful to see the progress of long insert queries, make any rough estimates (like COUNT(*) or rough SUM(*)) etc.

In other words, the results the dirty read queries return are fine as long as you treat them as estimates and don't make any critical decisions based upon them.

The advantage is that it can be faster in some situations. The disadvantage is the result can be wrong (data which hasn't been committed yet could be returned) and there is no guarantee that the result is repeatable.

If you care about accuracy, don't use this.

More information is on MSDN:

Implements dirty read, or isolation level 0 locking, which means that no shared locks are issued and no exclusive locks are honored. When this option is set, it is possible to read uncommitted or dirty data; values in the data can be changed and rows can appear or disappear in the data set before the end of the transaction. This option has the same effect as setting NOLOCK on all tables in all SELECT statements in a transaction. This is the least restrictive of the four isolation levels.

When is it ok to use READ UNCOMMITTED?

Rule of thumb

Good: Big aggregate reports showing constantly changing totals.

Risky: Nearly everything else.

The good news is that the majority of read-only reports fall in that Good category.

More detail...

Ok to use it:

• Nearly all user-facing aggregate reports for current, non-static data e.g. Year to date sales. It risks a margin of error (maybe < 0.1%) which is much lower than other uncertainty factors such as inputting error or just the randomness of when exactly data gets recorded minute to minute.

That covers probably the majority of what an Business Intelligence department would do in, say, SSRS. The exception of course, is anything with $ signs in front of it. Many people account for money with much more zeal than applied to the related core metrics required to service the customer and generate that money. (I blame accountants).

When risky

• Any report that goes down to the detail level. If that detail is required it usually implies that every row will be relevant to a decision. In fact, if you can't pull a small subset without blocking it might be for the good reason that it's being currently edited.

• Historical data. It rarely makes a practical difference but whereas users understand constantly changing data can't be perfect, they don't feel the same about static data. Dirty reads won't hurt here but double reads can occasionally be. Seeing as you shouldn't have blocks on static data anyway, why risk it?

• Nearly anything that feeds an application which also has write capabilities.

When even the OK scenario is not OK.

• Are any applications or update processes making use of big single transactions? Ones which remove then re-insert a lot of records you're reporting on? In that case you really can't use NOLOCK on those tables for anything.

Regarding reporting, we use it on all of our reporting queries to prevent a query from bogging down databases. We can do that because we're pulling historical data, not up-to-the-microsecond data.

Use READ_UNCOMMITTED in situation where source is highly unlikely to change.

• When reading historical data. e.g some deployment logs that happened two days ago.
• When reading metadata again. e.g. metadata based application.

Don't use READ_UNCOMMITTED when you know souce may change during fetch operation.