Several weeks back, I blogged about a missed opportunity with the new parameter sensitive plan feature. At the time, I thought that there was indeed sufficient skewness available to trigger the additional plan variants, and apparently some nice folks at Microsoft agreed.
I’m not gonna go into a lot of depth here, because I’m writing this while traveling, but we get the (mostly) desired outcome of two different plans being generated. Each plan is more suitable to the amount of data that the query has to process.
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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.
There are some code comments you see that really set the stage for how tuning a query is going to go.
Usually one misgiving about how SQL Server works gives way to a whole levee-breaking bevy of other ones and three days later you can’t feel your legs but dammit it’s done.
Okay, maybe it was three hours, but it felt like three days. Something about the gravitation pull of these black hole queries.
One fix I’ve been wishing for, or wish I’ve been fixing for, is a cure for local variables. I’d even be cool if Forced Parameterization was that cure, but you know…
Time will tell.
Husk
Let’s say we’ve got this stored procedure, which does something similar to the “I’m gonna fix parameter sniffing with a local variable hey why is everything around me turning to brimstone before my very eyes?” idea, but with… less of an end-of-times vibe.
CREATE OR ALTER PROCEDURE
dbo.IndexTuningMaster
(
@OwnerUserId int,
@ParentId int,
@PostTypeId int
)
AS
BEGIN
SET NOCOUNT, XACT_ABORT ON;
/*Someone passed in bad data and we got a bad query plan,
and we have to make sure that doesn't happen again*/
DECLARE
@ParentIdFix int =
CASE
WHEN @ParentId < 0
THEN 0
ELSE @ParentId
END;
SELECT TOP (1)
p.*
FROM dbo.Posts AS p
WHERE p.ParentId = @ParentIdFix
AND p.PostTypeId = @PostTypeId
AND p.OwnerUserId = @OwnerUserId
ORDER BY
p.Score DESC,
p.Id DESC;
END;
We get a super low guess for both. obviously that guess hurts a large set of matched data far worse than a small one, but the important thing here is that both queries receive the same bad guess.
This is a direct side effect of the local variable’s poor estimate, which PSP isn’t quite yet ready to go up against.
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.
While the Parameter Sensitive Plan (PSP) optimization won’t fix every problem with this lazy coding habit, it can fix some of them in very specific circumstances, assuming:
The parameter is eligible for PSP
The parameter is present across IF branches
We’re going to use a simple one parameter example to illustrate the potential utility here.
After all, if I make these things too complicated, someone might leave a comment question.
The horror
IFTTT
Here’s the procedure we’re using. The point is to execute one branch if @Reputation parameter is equal to one, and another branch if it equals something else.
In the bad old days, both queries would get a plan optimized at compile time, and neither one would get the performance boost that you hoped for.
In the good news days that you’ll probably get to experience around 2025, things are different!
CREATE OR ALTER PROCEDURE
dbo.IFTTT
(
@Reputation int
)
AS
BEGIN
SET NOCOUNT, XACT_ABORT ON;
SET STATISTICS XML ON;
IF @Reputation = 1
BEGIN
SELECT
u.Id,
u.DisplayName,
u.Reputation,
u.CreationDate
FROM dbo.Users AS u
WHERE u.Reputation = @Reputation;
END;
IF @Reputation > 1
BEGIN
SELECT
u.Id,
u.DisplayName,
u.Reputation,
u.CreationDate
FROM dbo.Users AS u
WHERE u.Reputation = @Reputation;
END;
SET STATISTICS XML OFF;
END;
GO
Johnson & Johnson
If we execute these queries back to back, each one gets a new plan:
EXEC dbo.IFTTT
@Reputation = 1;
GO
EXEC dbo.IFTTT
@Reputation = 2;
GO
psychic driving
Optimize For You
The reason why is in the resulting queries, as usual. The Reputation column has enough skew present to trigger the PSP optimization, so executions with differently-bucketed parameter values end up with different plans.
And of course, each plan has different compile and runtime values:
care
If I were to run this demo in a compatibility level under 160, this would all look totally different.
This is one change I’m sort of interested to see the play-out on.
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.
After seeing places where the Parameter Sensitive Plan (PSP) optimization quite stubbornly refuses to kick in, it’s somewhat amusing to see it kick in where it can’t possibly have any positive impact.
Even though some parameters are responsible for filtering on columns with highly skewed data, certain other factors may be present that don’t allow for the type of plan quality issues you might run into under normal parameter sensitivity scenarios:
Adequate indexing
Row goals
Other filtering elements
This isn’t to say that they can always prevent problems, but they certainly tend to reduce risks much of the time.
If only everything were always ever perfect, you know?
Setup
Let’s start by examining some data in the Posts table.
First, PostTypeIds:
resultant
Questions and answers are the main types of Posts. The data is clearly skewed, here, and in my testing this does qualify for PSP on its own.
The thing is, there are several attributes that Questions can have that Answers can’t. One of those is a ParentId. Looking through how the top 15 or so of those counts breaks down:
hitherto
Okay, so! Wikis don’t have ParentIds, neither do Moderator Nominations. More importantly, Questions don’t.
The Question with the Most answers is Id 184618, with 518. A far cry from the next-nearest Post Types, and light years from the number of Questions with a ParentId of zero.
More important than loving your data is knowing your data.
To Query A Butterfly
Let’s say we have this query:
SELECT TOP (5000)
p.Id,
p.OwnerUserId,
p.Score
FROM dbo.Posts AS p
WHERE p.PostTypeId = @po
AND p.ParentId = @pa
ORDER BY
p.Score DESC;
The three things we care about getting done are:
Filtering to PostTypeId
Filtering to ParentId
Ordering by Score
Either of these indexes would be suitable for that:
CREATE INDEX
popa
ON dbo.Posts
(
PostTypeId,
ParentId,
Score DESC
)
WITH
(
SORT_IN_TEMPDB = ON,
DATA_COMPRESSION = PAGE
);
CREATE INDEX
papo
ON dbo.Posts
(
ParentId,
PostTypeId,
Score DESC
)
WITH
(
SORT_IN_TEMPDB = ON,
DATA_COMPRESSION = PAGE
);
With No PSP At All
Under compatibility level 150, we can run the query in a variety of ways and get nearly identical performance results:
There’s a 27 millisecond difference between the two to find the first 5000 rows that match both predicates. You would have to run these in a very long loop to accumulate a meaningful overall difference.
In this case, both queries use and reuse the same execution plan. You can see that in the estimates.
With All The PSP
Switching to compat level 160, the queries are injected with the PLAN PER VALUE hint.
SELECT TOP (5000)
p.Id,
p.OwnerUserId,
p.Score
FROM dbo.Posts AS p
WHERE p.PostTypeId = @po
AND p.ParentId = @pa
ORDER BY
p.Score DESC
OPTION
(
PLAN PER VALUE
(
QueryVariantID = 2,
predicate_range
(
[StackOverflow2013].[dbo].[Posts].[PostTypeId] = @po,
100.0,
10000000.0
)
)
)
SELECT TOP (5000)
p.Id,
p.OwnerUserId,
p.Score
FROM dbo.Posts AS p
WHERE p.PostTypeId = @po
AND p.ParentId = @pa
ORDER BY
p.Score DESC
OPTION
(
PLAN PER VALUE
(
QueryVariantID = 3,
predicate_range
(
[StackOverflow2013].[dbo].[Posts].[PostTypeId] = @po,
100.0,
10000000.0
)
)
)
The thing is, both queries end up with identical execution times to when there was no PSP involved at all.
In other words, there is no parameter sensitivity in this scenario, despite there being skew in the column data.
Even searching for the “big” result — Questions with a ParentId of zero, finishes in <30 milliseconds.
Ah well. Gotta train the models somehow.
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.
When I talk to clients about using dynamic SQL, they’re usually under the misconception that those plans can’t get reused.
That may be true under some circumstances when:
It’s not properly parameterized
You use EXEC only and not sp_executesql
Under more favorable circumstances, dynamic SQL gets run, executed, and plans cached and reused with the same frequency as stored procedures.
Now, dynamic SQL isn’t exactly the same as stored procedures. There’s a lot you can do with those that just looks a mess in dynamic SQL, especially longer bits of code.
In today’s post, we’re going to look at how the Parameter Sensitive Plan (PSP) optimization works with dynamic SQL.
Bright, Sunshiny
I just learned how to spell “sunshiny”. Don’t let anyone ever tell you there’s nothing left to learn.
To keep up the sunshiny visage of today’s post, let’s get a TL;DR here: PSP does work with parameterized dynamic SQL.
Here’s an example, using a query with a parameter eligible for the PSP optimization.
DECLARE
@sql nvarchar(MAX) =
N'',
@parameters nvarchar(MAX) =
N'@ParentId int';
SELECT
@sql += N'
SELECT
c = COUNT_BIG(*)
FROM dbo.Posts AS p
WHERE p.ParentId = @ParentId;
';
EXEC sys.sp_executesql
@sql,
@parameters,
0;
EXEC sys.sp_executesql
@sql,
@parameters,
184618;
Both executions here get the option(plan per value... text at the end that indicates PSP kicked in, along with different query plans as expected.
end of time
Being Dense
Writing the not-good kind of dynamic SQL, like so:
SELECT
@sql = N'
SELECT
c = COUNT_BIG(*)
FROM dbo.Posts AS p
WHERE p.ParentId = ' + CONVERT(nvarchar(11), 0) + ';';
You will of course get different execution plans, but you’ll get a new execution plan for every different value that gets passed in. You will not get the PSP optimization.
This is not a good example of how you should be writing dynamic SQL. Please don’t do this, unless you have a good reason for it.
Anyway, this is good news, especially for parameterized ORM queries that currently plague many systems in crisis that I get to see every week.
Fun.
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.
The index and proc creation script for this are a bit on the long side, so I’m going to stick them in a GitHub gist to keep the post concise, since we have some other ground to cover here.
I want to lead with the statistics object that gets used for the query, which has a single equality predicate on the parameter value to search the VoteTypeId column.
The relevant portion of the query is this:
FROM dbo.Votes AS v
WHERE v.VoteTypeId = @VoteTypeId
The histogram matches the row counts from the table precisely. Thanks, full scan!
So, what’s the problem?
Autoproblematic
To my eye, there’s sufficient skewness here to present parameter sensitivity issues.
skewdriver
But SQL Server disagrees!
ouch dude
733 records vs. 37 million records seems appropriately skewed to me, but we get all of the typical parameter sensitivity symptoms.
Take a moment here to admire the somewhat confusing plan timing that Batch Mode operations are presenting here: The bottom query runs for around 32 seconds.
Up to the Nested Loops join, we use ~17 seconds of wall clock time with our serial execution plan. The Hash Match operator runs for 15 seconds on its own, in Batch Mode.
Parameter sensitivity still happens in SQL Server 2022.
Reversi
If we run the procedure in reverse order, using 4 to cache the plan and then 2 to reuse, we get a similar regression:
little things
Now, okay, let’s pause for a minute here. I need to backtrack, but I don’t want to spend a ton of blogspace on it. I’m also going to put the information in a very snooty block quote.
If we re-run the procedure from the section up above to search for VoteTypeId 2 a second time, Memory Grant Feedback will fix the spill at the Hash Join, and bring the total execution time down to about 15 seconds.
That is an improvement, but… Look at the plan here. If VoteTypeId 2 uses a plan more suited to the number of rows it has to process, the overall time is around 4 seconds, with no need for a memory grant correction.
The second plan for this execution sequence, searching for VoteTypeId 4 second in order, the overall time goes from 0 seconds and 0 milliseconds to 1.4 seconds. The big plan does not make searching for infrequent values faster.
So you see, the big plan isn’t always better.
Missed Connections
Hey, look, this is the first CTP. Maybe stuff like this is still getting ironed out. Maybe this blog post will change the course of history.
I am only moderately influential in the eyes of Microsoft, though, so perhaps not.
Anyway, this seems like a situation with sufficient skew to produce the Dispatcher plan and then additional sub-plans to account for far different row counts present in the VoteTypeId column.
If this scenario (and other similar scenarios) is outside the scope of the feature, query tuning folks are still going to have a whole lot of parameter sensitivity issues to deal with.
And should that be the case, I’d like to speak to the manager.
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.
I’ve used this proc as an example in the past. It’s a great parameter sniffing demo.
Why is it great? Because there’s exactly one value in the Posts table that causes an issue. It causes that issue because someone hated the idea of normalization.
The better thing to do here would be to have separate tables for questions and answers. Because we don’t have those, we end up with a weird scnenario.
In the Posts table, because questions and answers are lumped in together, there are certain traits that different types of posts can’t share:
Answers can’t have answers
Questions can’t have parent questions
There are other examples, but those are the two most obvious ones. But anyway, because of that, every Question has a ParentId of zero, and every Answer has the ParentId of the question it was posted under.
With around 6 million questions in the Posts table, that means there are around 6 million rows with a ParentId of zero, and around 11 million rows with other values.
lopsided
Current Affairs
In compat level 150, if I run this procedure like so:
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.
parameter_sensitive_plan_optimization: This event is fired when a query uses Parameter Sensitive Plan (PSP) Optimization feature.
parameter_sensitive_plan_optimization_skipped_reason: Occurs when the parameter sensitive plan feature is skipped. Use this event to monitor the reason why parameter sensitive plan optimization is skipped
parameter_sensitive_plan_testing: Fired when parameter sensitive plan is tested.
query_with_parameter_sensitivity: This event is fired when a query is discovered to have parameter sensitivity. This telemetry will help us in identifying queries that are parameter sensitive and how skewed the columns involved in the query are.
The only one I haven’t gotten to fire yet in my testing is parameter_sensitive_plan_testing which does not break my heart.
Mythos
Most of what gets returned by those is barely useful. The one that I thought was most promising was the skipped_reasonevent. I was able to track map values down for that one:
Reading through that list, there are some interesting points where the feature won’t kick in. These points are sort of a ghosts of query anti-patterns past.
TableVariable
HasLocalVar
CursorWithPopulate
Tvf
ParamSniffDisabled
NonInlinedUDF
And, of course, this one gave me quite the chuckle: QueryTextTooLarge.
YOU HEAR THAT ENTITY FRAMEWORK?
Dulls
The results from my Extended Event session, and… I’ll talk through my disappointment in a moment, was not terribly spectacular.
ho hum
The skipped_reason doesn’t reliably collect query text the way the other events do. That makes identifying the query that got skipped pretty difficult. There may be another action (like the stack) that captures it, but I haven’t had time to fully investigate yet.
so what?
Okay. Fine.
yep.
What do you do with this? I’m not sure yet. I don’t think I see much use in these just yet.
Hey, tomorrow’s another day. We’ll look at how the feature kicks in and fixes a parameter sniffing issue with this procedure.
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.
In the bad old days, which are still your days (but at least you have better days to look forward to), SQL Server’s cost-based optimizer would take a parametrized query, come up with a query plan, and then reuse that plan until:
Plan cache clearing event
Plan evicting event
There are a bunch of reasons for those things. They’re not important here.
What is important is the future, where SQL Server will have some more options for getting out of parameter sensitive jams.
While Cardinality Estimation Feedback is a between-executions like Memory Grant Feedback, the Parameter Sensitive Plan feature is a heuristic runtime decision, sort of like Adaptive Joins and Batch Mode On Row Store.
Like most things, you’ll need to be in the latest compatibility level, 160, and… it hasn’t been announced yet, but traditionally things like this are Enterprise Only.
Time will tell.
Shellac
The way this feature works is, rather than caching a single query plan for every other execution to use, it creates what’s called a Dispatcher plan (if your query qualifies).
You’ll see something like this in the properties of the root node of your query plan, and your query will have some additional funny business at the end of it.
sticky business
And that other thing:
SELECT TOP (10)
u.DisplayName,
p.*
FROM dbo.Posts AS p
JOIN dbo.Users AS u
ON p.OwnerUserId = u.Id
WHERE p.ParentId = @ParentId
ORDER BY u.Reputation DESC
OPTION
(
PLAN PER VALUE
(
QueryVariantID = 3,
predicate_range
(
[StackOverflow2013].[dbo].[Posts].[ParentId] = @ParentId,
100.0,
1000000.0
)
)
)
Note that I formatted the option part of the query a bit to make it a bit more likable (to me).
The basic message here is that for the @ParentId parameter, there are three plan variants (the limit currently), and this is the third one.
There are also a couple numbers there that indicate the upper and lower bounds for bucketizing the three plan variants.
S/M/L
The basic idea here is to generate small, medium, and large plans for different cardinality estimation ranges.
Most of the examples I’ve been able to come up with have only generated two plans, one for the very low end, and one for the very high end.
As far as I can tell, the limitations for this feature seem to be:
In tomorrow’s post, we’ll look at some of the Extended Events attached to this feature that give you some insights into when the feature kicks in, when it doesn’t, and what SQL Server thought about how sensitive your query is.
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.
