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Curated SQL Posts

Optimizing Index Spools

Published 2022-04-22 by Kevin Feasel

Francisco looks at index spools:

When we are analyzing execution plans, we may come across different types of Spool operators – Table Spools, Row Count Spools, Window Spools or Index Spools – that the Query Optimizer chooses for specific purposes. In this post we are going to briefly look into the Index Spool, how it can sometimes lead to suboptimal query performance, and what can be done to easily fix it.

My favorite description of this is Erik Darling’s: spools are SQL Server’s passive-aggressive way of telling you “I’m not saying you need an index but you need an index.”

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Logic Apps: Source Control and Deployment

Published 2022-04-22 by Kevin Feasel

Koen Verbeeck has a two-parter. First up is storing Logic App code in source control:

At a data warehouse project I’m using a couple of Logic Apps to do some lightweight data movements. For example: reading a SharePoint list and dumping the contents into a SQL Server table. Or reading CSV files from a OneDrive directory and putting them in Blob storage. Some of those things can be done in Azure Data Factory as well, but it’s easier and cheaper to do them with Logic apps.

Logic Apps are essentially JSON code behind the scenes, so they should be included into the source control system of your choice (for the remainder of the blog post we’re going to assume this is git).

The second post covers deployment:

It’s easy to duplicate an Azure Logic App in a resource group, but unfortunately you cannot duplicate a Logic App between environments (you might try to copy paste the JSON though). So unless you want to hand craft every Logic App yourself on each of your environments, you need a way to automatically deploy your Logic Apps. It’s easier, faster and less error-prone than any manual method.

Check out both posts.

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Calculating Running Totals with Window Functions

Published 2022-04-22 by Kevin Feasel

Steve Jones shows off a good use case for window functions:

Recently I was looking at some data and wanted to analyze it by month. I have a goal that is set for each day and then an actual value. I wanted to know how I was tracking against the goal, as a running total. If my goal is 10 a day, then I ought to actually get to 10 the first day, 20 for the second day (10 + 10), etc.

Read on to see how Steve solved the problem.

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Search in KQL

Published 2022-04-21 by Kevin Feasel

Robert Cain looks at the search operator in KQL:

In this post we will examine the KQL (Kusto Query Language) search operator. Search allows us to look across all columns in one or more tables for a specific text string.

The samples in this post will be run inside the LogAnalytics demo site found at https://aka.ms/LADemo. This demo site has been provided by Microsoft and can be used to learn the Kusto Query Language at no cost to you.

Click through to learn more about this very useful operator.

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Entity Framework and Include Operations

Published 2022-04-21 by Kevin Feasel

Josh Darnell has a warning:

I can imagine someone reading that and not seeing the gravity of the situation. “Hey, 500 rows isn’t that many – we have modern hardware!”

I thought it was worth writing about a real world situation where this can get seriously out of hand.

Read on for a scenario in which 64 rows turns into 100,000 rows pretty quickly.

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Quotation Marks in Azure SQL DB vs Managed Instance

Published 2022-04-21 by Kevin Feasel

Michael Bourgon notices a difference between Azure SQL DB and Managed Instance/box product:

I was trying to get some Xquery parsing working, and ran into a weird error:

"CONDITIONAL failed because the following SET options have incorrect settings: 'QUOTED_IDENTIFIER'"

Weird.  Doubly so because this code has worked on-prem for a decade, and the Managed Instance is running it now.  

Read on for the solution.

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Using Buffer Pool Extension in SQL Server

Published 2022-04-21 by Kevin Feasel

Chad Callihan looks at buffer pool extension:

Perhaps you started out with X amount of memory when your SQL server was brought online and over time, with additional load and activity on that SQL server, users are not quite getting the type of performance they’re used to getting. Sure, you can buy more memory. What if that’s not an option?

If you’re running low on memory and need a little boost, enabling buffer pool extension can take advantage of an SSD as an “extension” for the buffer pool.

This is one of those interesting features that probably help a small number of customers but shouldn’t be generally useful. That’s because even with SSD performance improvements, memory is still a couple orders of magnitude faster, so as long as you have the ability to increase RAM, that brings much better performance.

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The User Transaction Scope for Temporary Objects

Published 2022-04-21 by Kevin Feasel

Bob Dorr troubleshoots a performance problem:

When the temporary table is bound to the user transaction it is both created and destroyed as part of the transaction.  The same logic in a procedure attempts to avoid the creation and destruction, for each execution, by using temporary table caching.

From the issue I was debugging, the user transaction scope mattered because creation and destruction of metadata may be an expensive operation.  

This post ties into two separate things: first, how temp objects tie to specific sessions; and second, the cost of creating and destroying temporary objects. For the latter, a couple quick pieces of advice:

  • Reduce the number of temporary objects you create. If you can solve a problem with fewer temp tables or table variables while maintaining acceptable performance, that can help on busy systems.
  • Never explicitly drop temp tables. There’s no benefit to explicitly dropping temp tables, as they’ll go away as soon as the session ends. Also, not dropping temp tables is the first step to:
  • Embrace temp table reuse. There are specific rules around when you can re-use a temp table. Each re-use of a temp table means two fewer metadata operations (one delete and one create).
  • Use memory-optimized table variables instead of temp tables or table variables.
  • Turn on memory-optimized tempdb metadata. The biggest issue here is that you lose cross-database queries into tempdb views. That can end up being painful and is why I can’t recommend it as a general solution.

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Simplifying a Complex Multi-Visual Chart

Published 2022-04-20 by Kevin Feasel

Amy Esselman re-designs a mess of a chart:

When faced with any unfamiliar but complicated graph, it can be helpful to think about it piece by piece to gain a better understanding of what’s being communicated. That way, we’ll have a better handle on how we can improve the overall visual. 

The goal of this chart is to allow managers to compare their store’s performance against its forecasted range and the actual performance of other stores in the region. 

Click through for the full process.

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