Category: SQL Server

Drop The Verse

Why is IS NULL (not to be confused with ISNULL, the function) considered an equality predicate, and IS NOT NULL considered an inequality (or range) predicate?

It seems like they should be fairly equivalent, though opposite. One tests for a lack of values, and one tests for the presence of values, with no further examination of what those values are.

The trickier thing is that we can seek to either condition, but what happens next WILL SHOCK YOU.

Ze Index

The leading column in this index is NULLable, and has a bunch of NULLs in it.

CREATE INDEX nully_baby 
    ON dbo.Posts(LastEditDate, Score DESC);

Knowing what we know about what indexes do to data, and since the LastEditDate column is sorted ascending, all of the NULL values will be first, and then within the population of NULLs values for Score will be sorted in descending order.

But once we get to non-NULL values, Score is sorted in descending order only within any duplicate date values. For example, there are 4000 some odd posts with a LastEditDate of “2018-07-09 19:34:03.733”.

Why? I don’t know.

But within that and any other duplicate values in LastEditDate, Score will be in descending order.

Proving It

Let’s take two queries!

SELECT TOP (5000) 
    p.LastEditDate,
    p.Score
FROM dbo.Posts AS p
WHERE p.LastEditDate IS NULL
ORDER BY p.Score DESC;

SELECT TOP (5000) 
    p.LastEditDate,
    p.Score
FROM dbo.Posts AS p
WHERE p.LastEditDate IS NOT NULL
ORDER BY p.Score DESC;

Which get very different execution plans.

But Why?

I know, I know. The sort is technically non-deterministic, because Score has duplicates in it. Forget about that for a second.

For the NULL values though, Score is at least persisted in the correct order.

For the NOT NULL values, Score is not guaranteed to be in a consistent order across different date values. The ordering will reset within each group.

We’ll talk about how that works tomorrow.

Thanks for reading!

Going Further

If this is the kind of SQL Server stuff you love learning about, you’ll love my training. I’m offering a 75% discount to my blog readers if you click from here. I’m also available for consulting if you just don’t have time for that and need to solve performance problems quickly.

Frangible Tuning

Right now, the optimizer’s costing algorithm’s cost lookups as being pretty expensive.

Why? Because it’s stuck in the 90s, and it thinks that random I/O means mechanical doo-dads hopping about on a spinning platter to fetch data.

And look, I get why changes like this would be really hard. Not only would it represent a change to how costs are estimated, which could throw off a whole lot of things, but you also open potentially more queries up to parameter sniffing issues.

Neither of those prospects are great, but I hear from reliable sources that Microsoft “hope[s] to make parameter sniffing less of a problem for customers” in the future.

In the meantime, what do I mean?

Kiss of Death

Scanning clustered indexes can be painful. Not always, of course, but often enough that it’s certainly something to ask questions about in OLTP-ish queries.

Let’s use the example query from yesterday’s blog post again, with a couple minor changes, and an index.

CREATE INDEX unusable 
    ON dbo.Posts(OwnerUserId, Score DESC, CreationDate, LastActivityDate)
    INCLUDE(PostTypeId);

Let’s run this hyper-realistic query, with slightly different dates in the where clause.

SELECT TOP (5000) 
    p.OwnerUserId,
    p.Score,
    ISNULL(p.Tags, N'N/A: Question') AS Tags,
    ISNULL(p.Title, N'N/A: Question') AS Title, 
    p.CreationDate, 
    p.LastActivityDate, 
    p.Body
FROM dbo.Posts AS p
WHERE p.OwnerUserId IS NOT NULL
AND   p.CreationDate >= '20130927'
AND   p.LastActivityDate < '20140101'
ORDER BY p.Score DESC;


SELECT TOP (5000) 
    p.OwnerUserId,
    p.Score,
    ISNULL(p.Tags, N'N/A: Question') AS Tags,
    ISNULL(p.Title, N'N/A: Question') AS Title, 
    p.CreationDate, 
    p.LastActivityDate, 
    p.Body
FROM dbo.Posts AS p
WHERE p.OwnerUserId IS NOT NULL
AND p.CreationDate >= '20130928'
AND p.LastActivityDate < '20140101'
ORDER BY p.Score DESC;

The query plan for the first query looks like this:

We scan the clustered index, and the query as a whole takes around 9 seconds.

Well, okay.

What about the other query plan?

That runs about 7 seconds faster. But why?

Come Clean

There’s one of those ✌tipping points✌ you may have heard about. One day. What a difference, huh?

Let’s back up to the first query.

SELECT TOP (5000) 
    p.OwnerUserId,
    p.Score,
    ISNULL(p.Tags, N'N/A: Question') AS Tags,
    ISNULL(p.Title, N'N/A: Question') AS Title, 
    p.CreationDate, 
    p.LastActivityDate, 
    p.Body
FROM dbo.Posts AS p
WHERE p.OwnerUserId IS NOT NULL
AND   p.CreationDate >= '20130927'
AND   p.LastActivityDate < '20140101'
ORDER BY p.Score DESC;

SELECT TOP (5000) 
    p.OwnerUserId,
    p.Score,
    ISNULL(p.Tags, N'N/A: Question') AS Tags,
    ISNULL(p.Title, N'N/A: Question') AS Title, 
    p.CreationDate, 
    p.LastActivityDate, 
    p.Body
FROM dbo.Posts AS p WITH(INDEX = unusable)
WHERE p.OwnerUserId IS NOT NULL
AND   p.CreationDate >= '20130927'
AND   p.LastActivityDate < '20140101'
ORDER BY p.Score DESC;

There’s no way one day should make this thing 7 seconds slower, so we’re going to hint one copy of it to the use nonclustered index.

How do we do there?

The much slower plan has a lower cost. The optimizer gave the seek + lookup a higher cost than the scan.

If we look at the subtree cost of the first operator, you’ll see what I mean.

Zone Out

You may hear people talk about costs, either of query plans, or of operators, that indicate what took the most time. This is unfortunately not quite the case.

Note that there are no “actual cost” metrics that get calculated and added to the plan later. The estimates remain with no counterparts.

You can answer some common questions this way:

• Why didn’t my index get chosen? The optimizer thought it’d be more work
• How did it make that choice? Estimated costs of different potential plans
• Why was the optimizer wrong? Because it’s biased against random I/O.

Thanks for reading!

Going Further

If this is the kind of SQL Server stuff you love learning about, you’ll love my training. I’m offering a 75% discount to my blog readers if you click from here. I’m also available for consulting if you just don’t have time for that and need to solve performance problems quickly.