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Curated SQL Posts

Change Data Capture and the Cosmos DB Analytical Store

Published 2023-04-04 by Kevin Feasel

Mark Kromer and Revin Chalil show off an interesting preview feature:

Making it super-easy to create efficient and fast ETL processing the cloud, Azure Data Factory has invested heavily in change data capture features. Today, we are super-excited to announce that Azure Cosmos DB analytics store now supports Change Data Capture (CDC), for Azure Cosmos DB API for NoSQL, and Azure Cosmos DB API for Mongo DB in public preview!

This capability, available in public preview, allows you to efficiently consume a continuous and (inserted, updated, and deleted) data from the analytical store. CDC is seamlessly integrated with Azure Synapse Analytics and Azure Data Factory, a scalable no-code experience for high data volume. As CDC is based on the analytical store, it does not consume provisioned RUs, does not affect the performance of your transactional workloads, provides lower latency, and has lower TCO.

Click through to see how it works.

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Fending off Sessions while in Single-User Mode

Published 2023-04-03 by Kevin Feasel

Eitan Blumin just wants to switch the database type:

Today we had an interesting use case where a customer reported that one of the databases they just restored from a backup got stuck in “Single-User” mode in one of their environments.

To resolve it, I first tried running the following command:

ALTER DATABASE MyDB SET MULTI_USER WITH ROLLBACK IMMEDIATE;

In response, I got deadlocked with the dreaded error 1205:

There were a few different attempts with no success until Eitan came up with the final script. Eitan’s analogy was to curling, though the first thing I thought of was Odysseus fighting off his wife’s suitors as he came back to claim his home.

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Power BI Dataset CI/CD with Azure DevOps

Published 2023-04-03 by Kevin Feasel

Stephanie Bruno does a bit of continuous integration:

There’s a lot of information on how to get around the lack of an out-of-the box CI/CD solution for Power BI datasets, but for me it’s often complicated and I have to read too many pages before making much progress on my own. This post is here to strip it down and provide you with the easiest way we know to enable a bonafide CI/CD process for Power BI datasets with Azure DevOps. The post is still longer than we’d like, but it includes detailed step-by-step instructions to walk you through every part of the process. To save space, we used slideshows for the screenshots, but you can pause them as you follow along.

There are a lot of steps but the goal is a worthwhile one.

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Tips for Enhancing Power BI User Experience

Published 2023-04-03 by Kevin Feasel

Mara Pereira provides some guidance:

Before we dive into the nitty-gritty, let’s address the elephant in the room – what exactly is user experience, and why is it such an indispensable factor in reporting and Power BI?

To put it simply, user experience (UX) is the overall impression and interaction your audience has with your report. It goes beyond aesthetics; UX focuses on the ease of understanding, navigation, and the ability to extract valuable insights from the data presented. In the world of reporting, having a top-notch user experience is crucial, as it can make or break the effectiveness and adoption of your reports.

The post stays mostly at a high level, providing motivational guidance rather than “here are the specific actions to take on a given report.” What it does provide is the reasoning behind why you would make those changes.

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Which Power Query Operations Are Most Resource-Intensive?

Published 2023-04-03 by Kevin Feasel

Chris Webb answers a question:

Last year I wrote a post about a change in the Power BI Service that meant the CPU Time associated with Power Query transformations was added to the total shown for a dataset refresh operation in Profiler traces and Log Analytics:

https://blog.crossjoin.co.uk/2022/07/03/measuring-power-query-cpu-usage-during-power-bi-dataset-refresh/

This was useful, but it didn’t tell you directly how much CPU Time was used by Power Query and it didn’t tell you which tables or partitions in a refresh were using the most CPU. It also didn’t tell you anything about Power Query memory usage. The good news that recently there has been another change that solves these problems.

Click through for the solution.

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ANSI SQL and Trailing Spaces

Published 2023-04-03 by Kevin Feasel

Chris Johnson finds a language quirk:

Recently I found a quirk of T-SQL, where a group by statement was treating strings as the same if the only difference was one or more trailing spaces. So, ‘aa’ would be grouped with ‘aa ‘. I did some digging, and this is what I found.

Yeah, this isn’t just Microsoft’s T-SQL variant—it’s a standard part of SQL, as Chris notes later in the post.

My “just-so” story is that this might have been implemented to deal with CHAR(x) comparisons, such as CHAR(2) to CHAR(3). There’s no way to make that comparison unless you treat trailing spaces as irrelevant. Because we almost always use VARCHAR(x) or NVARCHAR(x), it isn’t something top of mind to most database practitioners, but there is a method to the madness.

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April Tools Day

Published 2023-04-03 by Kevin Feasel

Erin Stellato dispels some myths:

Myth #1 Azure Data Studio is the only standalone solution now that SSMS is deprecated.

SQL Server Management Studio (SSMS) is not deprecated.  We thought about writing that in ALL CAPS, but figured bold is sufficient.  SSMS has not been deprecated, and we are not planning on deprecating it.  You will see new functionality being added to Azure Data Studio, but we have a fair number of things lined up for SSMS, including migration to the Visual Studio 2022 shell, which brings 64-bit support.

Bold plus all caps might have been a bit too much, yeah.

Click through to see what’s happening in the world of SQL Server tooling from Microsoft.

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Join Operations in BigQuery

Published 2023-03-31 by Kevin Feasel

Rathish Kumar joins a few tables together:

SQL joins are used to combine columns from multiple tables to get desired result set. In a typical Relational model we use normalized tables, each table represents an entity (example: employee, department, etc) and its relationships and when we need to get data from more than one tables, for example employee name and employee department, we use joins to combine employee name column from employee table, department name column from department table based on employee number key column, which is available on both the tables.

Similarly, typical data warehouse setup follows Star or Snowflake schema consisting of a primary fact table and satellite dimension tables. Fact tables represents events (example: orders table in a ecommerce business) and dimension table represents attributes and slowly changing information (example: customer, product tables).

The syntax is rather similar to most database engines, though there are a few physical join operators which differ from typical relational database management systems. Also, I’ll take this moment to say thank you to Rathish for not using Venn diagrams to show joins and instead using a proper technique.

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Tracking Change Events in Snowflake

Published 2023-03-31 by Kevin Feasel

Kevin Wilkie shows off an interesting window function:

Notice that it has the OVER operator, you can order the data, and even partition the data as needed (Not seen in this example)!

But, as usual with Snowflake, there are even more functions we can work with! Sometimes, you just need to know when items are changed. Enter the CONDITIONAL_CHANGE_EVENT windowing function!

Click through for an example of how CONDITIONAL_CHANGE_EVENT() works.

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Finding Columnstore Index Storage and Memory Allocations

Published 2023-03-31 by Kevin Feasel

Jose Manuel Jurado Diaz has a few scripts for us:

Today, we got a new question how much is the size used by a columnstore index table at storage level and memory usage.

TSQL to obtain the total number of rows, size per schema, table and index.

Using the view sys.column_store_row_groups (Transact-SQL) – SQL Server | Microsoft Learn we could see the total number of rows and space usage at storage level.

Click through for that script, as well as a few more to learn how much space and memory that columnstore index is taking.

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