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Curated SQL Posts

DATEDIFF

Published 2018-11-23 by Kevin Feasel

Randolph West continues a series on covering dates and times, looking at DATEDIFF and DATEDIFF_BIG:

The only functional difference between them is that the DATEDIFF_BIG() returns values as a BIGINT, for results that exceed the boundary of an INT. Keep this in mind when deciding which one to use. For example, the maximum number of seconds an INT can hold is 68 years, while a BIGINT can comfortably store the number of seconds in 10,000 years. This becomes especially important when dealing with microseconds and nanoseconds.

The rest of the post will use DATEDIFF() to refer to both functions.

I think this might be the first time I’d read about DATEDIFF_BIG()and I’m not aware of ever having used it.  But hey, it could make sense if you need to track more than 2 billion microseconds.

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Optimizing SQL Server Workloads On VMware

Published 2018-11-23 by Kevin Feasel

Jeff Mlakar shares a few tips on hosting SQL Server via VMware virtual machine:

Why is Over-Allocating a VM Bad?

Why is is so important to allocate just the right amount of resources for your guest VM running SQL Server? We all know the problem with an undersized system; however, what about an oversized system? What problem could that be? Here are a few common issues to consider:

  • Over-allocating CPU causes poor resource utilization across all the guest VMs

  • Over-allocating memory unnecessarily increases memory contention and overhead on other guest VMs

  • Having more vCPUs assigned to the VM can have an impact on licensing.

There are some good points in the post, so check it out.

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The Risk Of Shadow IT In The Cloud

Published 2018-11-23 by Kevin Feasel

Kenneth Fisher walks us through the risk of increased Shadow IT with migration to the cloud:

Shadow IT has been, well, maybe not the bane of the IT department, but certainly a pain in the neck. On the off chance you’ve never heard of shadow IT do any of these sound familiar?

  • A user asks you to restore a corrupt database on a SQL Server you’ve never heard of and isn’t in your inventory. (And 50/50 odds there’s never been a backup taken.)

  • You do a licensing true-up and dozens of new SQL Servers suddenly show up.

  • You hear from a user: “We have this mission critical Access database that suddenly isn’t working. I know you don’t support access but you’re the database person so we need you to fix it.”

It’s an interesting short essay and worth thinking about if you’re in the cloud or moving that way.

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Casting Constants And POWER()

Published 2018-11-23 by Kevin Feasel

Steve Jones walks us through a case of an unexpected error:

I ran into an interesting problem while working with the POWER() function. I was trying to do some binary conversions and had a statement like this to process powers of 2.

SELECT POWER(2, n)

This was designed to take a value and return a power of 2. I then used a different value to determine if this was added to my conversion factor or not. In trying to work with some larger numbers, I ran into this error:

Msg 232, Level 16, State 3, Line 3
Arithmetic overflow error for type int, value = 2147483648.000000.

Click through for a description of the problem as well as Steve’s solution.

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Extended Events In Azure Data Studio

Published 2018-11-23 by Kevin Feasel

Jason Brimhall walks us through installation of the SQL Server Profiler on Azure Data Studio:

Azure Data Studio (ADS) is getting all sorts of love and attention these days. So much so that they have finally gotten around to adding Extended Events (XE) to the tool – sort of. Now we have the power to run traces on SQL Server via ADS.

The presence of XE in ADS comes via an extension and comes with a few other caveats. I will explore the extension for XE available in ADS in this article and discuss some of the caveats. As you read the article, it might be helpful to go ahead and download ADS if you do not already have it.

Jason points out the name of SQL Server Profiler and I’d like to add my own bit of irritation here.  “Don’t use Profiler, except the one good Profiler but not the Profiler you think you’re using unless you know not to use Profiler and use Profiler instead.”  Yeah, that’s pretty clear.

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dbatools: On The Way To 1.0

Published 2018-11-23 by Kevin Feasel

Chrissy LeMaire points out a bunch of changes to dbatools:

Aliases have been added for the changes, so these are not breaking changes:

  • Mismatched Copy commands have been renamed to match their corresponding Get command names (ie. Copy-DbaCentralManagementServer is now Copy-DbaCmsRegServer).

  • Most parameters named Password have been changed to SecurePassword. They’ve always been a SecureStringdata type but this makes that clear.

  • The parameters ExcludeAllSystemDb and ExcludeAllUserDb have been changed to ExcludeSystem and ExcludeUser, respectively.

These are some of the non-breaking changes, but this latest release has several breaking changes too.  Chrissy is promising no more breaking changes for a little while, so it’s probably a good time to upgrade and check those scripts to see what you need to change.

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Query Store & Spinlocks

Published 2018-11-21 by Kevin Feasel

David Fowler ran into an issue with the Query Store process experiencing waits due to spinlocks:

We were enjoying a nice peaceful afternoon when we hear panicked shouting that a SQL Server had become unresponsive and the customers were unable to do anything.

We moseyed on down to the server in question to take a look at it.  One thing stood out immediately, CPU was pegged out at 100% but SQL itself didn’t actually seem to be doing anything, transactions\second was on the floor. Unfortunately this happened a while back and I didn’t think to capture any graphs or metrics at the time so you’re just going to have to take my word for this.

The issue David ran into was subsequently fixed, making this a cautionary tale to keep those SQL Server instances patched.

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Dealing With Zero-Value Rows In dplyr

Published 2018-11-21 by Kevin Feasel

Kieran Healy shows an oddity in dplyr when dealing with zero-value records:

That looks fine. You can see in each panel the 2015 column is 100% Men. If we were working on this a bit longer we’d polish up the x-axis so that the dates were centered under the columns. But as an exploratory plot it’s fine.

But let’s say that, instead of a column plot, you looked at a line plot instead. This would be a natural thing to do given that time is on the x-axis and so you’re looking at a trend, albeit one over a small number of years.

This is behavior I hadn’t run into, and it does seem a bit odd.  On a totally unrelated note, Healy’s Data Visualization: A Practical Introduction is one of the best books on the topic.

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The Good And Bad Of Dataflows

Published 2018-11-21 by Kevin Feasel

Teo Lachev gives us the lowdown on Dataflows in Power BI:

There is a lot to like about dataflows. I can think of two primary self-service scenarios that can benefit from dataflows:

  • Data staging – Many organizations implement operational data stores (ODS) and staging databases before the data is processed and loaded in a data warehouse. As a business user, you can use data-flows for a similar purpose. For example, one of our clients is a large insurance company that uses Microsoft Dynamics 365 for customer relationship management. Various data analysts create data models from the same CRM data, but they find that refreshing the CRM data is time consuming. Instead, they can create a dataflow to stage some CRM entities before importing them in Power BI Desktop. Even better, you could import the staged CRM data into a single dataset or in an organizational semantic model to multiple data copies and duplicating business logic.

  • Certified datasets – One way to improve data quality and promote better self-service BI is to prepare a set of certified common entities, such as Organization, Product, and Vendor. A data steward can be responsible for designing and managing these entities. Once in place, data analysts can import the certified entities in their data models.

Read on for some more positives and negatives.

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