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Category: Query Tuning

Trying Out Interleaved Execution

Published 2017-04-20 by Kevin Feasel

Dmitry Pilugin has a test of interleaved execution of a multi-statement table-valued function:

First of all, note that Estimated Number of Rows is 10 000 now, which is correct and equals Actual Number of Rows. Due to the correct estimate the optimizer decided that there are enough rows to benefit from a partial (local/global) aggregation and introduced a partial Hash aggregate before the join.

If you take a Profiler, enable events SP:StmtStarting, SP:StmtCompleted, SQL:StmtStarting, SQL:StmtCompleted and run the query without and with a TF, you’ll see what does it actually mean “interleaved” in terms of the execution sequence.

During the regular execution the query starts executing, then the function is executed, the query continues execution and finishes the execution. We see the following event sequence:

This is a very thorough post, but if you have multi-statement TVFs, you absolutely want to read it.

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Understanding Probe Residuals

Published 2017-04-18 by Kevin Feasel

Daniel Janik explains what a probe residual is in an execution plan:

A probe residual is important because they can indicate key performance problems that might not otherwise be brought to your attention.

What is a probe residual?

Simply put, a probe residual is an extra operation that must be performed to compete the matching process. Extra being left over things to do.

Click through for an example brought about by implicit conversion.

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Benchmarking

Published 2017-03-31 by Kevin Feasel

Lukas Eder notes that the best way to compare performance is to…compare performance:

To bust a myth, if you have good reasons to think that a differently written, but semantically equivalent query might be faster (on your database), you should measure. Don’t even trust any execution plan, because ultimately, what really counts is the wall clock time in your production system.

If you can measure your queries in production, that’s perfect. But often, you cannot – but you don’t always have to. One way to compare two queries with each other is to benchmark them by executing each query hundreds or even thousands of times in a row.

Lukas goes on to compare a left join to a correlated subquery in three separate database products and the results are very interesting although absolutely not comparable across products because the DeWitt Clause is still a thing.  Great read.

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Collapsable Subqueries

Published 2017-03-08 by Kevin Feasel

Dmitry Pilugin notes a new query simplification rule in SQL Server vNext:

You may see that in the first plan, there are two clustered index scans of the table SalesOrderDetail, however the subquery is exactly the same “exists (select * from Sales.SalesOrderDetail f where f.SalesOrderID = d.SalesOrderID)” but referenced twice.

In the second case, compiled under next compatibility level, the double reference of the subquery is collapsed and we see only one reference to the SalesOrderDetails table and more efficient plan, despite the query still has two subqueries with SalesOrderDetails.

In the third case, also compiled under vNext level, we see the second branch with the SalesOrderDetail again, but that is because we turned off the rule CollapseIdenticalScalarSubquery with an undocumented hint queryruleoff (which I originally described in my blog post).

I think Dmitry has the expected use case nailed:  ORMs.  But I can see people writing (well, copy-pasting) similar queries, so maybe it’ll be useful in more contexts as well.

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Plan Comparison

Published 2017-02-16 by Kevin Feasel

Max Vernon looks at plan comparison in SQL Server Management Studio:

The table has 10,000,000 rows. I’ve create a non-clustered columnstore index on the table, which I’ll talk about in a future post. I’ve included it here because it provides a succinct difference in the two plans.

To compare the plans visually, side-by-side, you need to save the first plan by right-clicking on the plan window, clicking “Save Execution Plan As…”, and specifying a filename. Next, right-click on the plan window, and choose “Compare Showplan”:

I’ve only used this once or twice, but it is an interesting feature.

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HTDELETE Wait Type

Published 2017-02-14 by Kevin Feasel

Joey D’Antoni troubleshoots a query with excessive HTDELETE waits:

Ultimately I think any thought of the readable secondary having a vastly different plan was a red herrings. Statistics are going to be the same on both instances, and if there were a missing statistic on the secondary, SQL Server would create it in TempDB. Anyway, columnstore indexes don’t use statistics in the traditional sense.

Fortunately I was able to catch a query in the process of waiting on HTDELETE, so I no longer had to look for the needle in the haystack, and I could get to tuning the plans. I was able to grab the SELECT part of the query and generate an estimated plan on both the primary and secondary nodes. The plans were virtually the same on both nodes, with just a minor difference in memory grant between them.

Click through for the solution.

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Understanding Memory Grants

Published 2017-02-07 by Kevin Feasel

Erik Darling explains memory grants in SQL Server:

Our query memory grants range from around 8 MB to around 560 MB. This isn’t even ordering BY the larger columns, this is just doing the work to sort results by them. Even if you’re a smarty pants, and you don’t use unnecessary ORDER BY clauses in your queries, SQL may inject them into your query plans to support operations that require sorted data. Things like stream aggregates, merge joins, and occasionally key lookups may still be considered a ‘cheaper’ option by the optimizer, even with a sort in the plan.

Of course, in our query plans, we have warnings on the last two queries, which had to order the VARCHAR(8000) column.

This shows just how much difference a simple column size can make.

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Using Powershell To Shred Query Plan XML

Published 2017-02-02 by Kevin Feasel

Mike Fal shows how to use Powershell (or any .NET language) to read parts of a query plan:

Once the pattern is down, the use is pretty straightforward. There’s also more options accessible to you. If we just look at the RunTimeCountersPerThread node, we can compare other values such as Rows, Scans, and CPU time. We could really get crazy and extract all the different statements within the batch. There are numerous possibilities for analysis and review.

I’m not here to tell you that you should start using PowerShell to automate query tuning. Query performance is an art form and requires a lot of case-by-case analysis. However, like any great carpenter, it’s good to know the capabilities of your tool set. Understanding the options available to you not only helps you be more effective, but can also provide answers you may not have had access to.

It’s another tool for the belt.

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UDFs And Recompilations

Published 2017-01-27 by Kevin Feasel

Erik Darling shows how to diagnose a high recompilation problem:

So yeah, that function seems to get up to something once for every ID you pass in. Remember that in our STUFF… query, we grabbed the TOP 10 each time. In the XE session, each time we call the proc, the string splitting function compiles and executes code 10 times. Bummerino. That’s the life of a loop.

On SQL Server 2016 (and really, with any non-looping code), we can get around the constant compilations with a simple rewrite. In this case, I’m calling 2016’s STRING_SPLIT function instead of the MSTVF function.

Read on for more.

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