Press "Enter" to skip to content

Category: Naming

What’s in a Name?

Benjamin Smith analyzes a name change:

Recently, RStudio announced its name change to Posit. For many this name change was accepted with open arms, but for some-not so. Being the statistician that I am I decided to post a poll on LinkedIn to see the sentiment of my network. After running the poll for a week the results were in:

Read on for the responses as well as an analysis using RSTAN.

Comments closed

“Expensive” Queries

Erik Darling asks, what’s in a name?

When we talk about finding queries to tune, there’s an unfortunate term that gets thrown around: Expensive Queries.

Why is it unfortunate? Well, it reinforces the wrong mindset when it comes to query tuning, and leads people down the wrong path, looking at the wrong metrics.

I disagree on the “bad name” bit but agree on the substance. The term “expensive query” has a very useful connotation: this is a query which requires a significant amount of resources. Where I fully agree with Erik is that “query cost” from the optimizer does not do a great job of describing “significant amount of resources.” There is also a relevant point that expensive queries may not be the most important ones to look at. Reasons why can include:

  • The query runs at a time when there’s little load on the system, so it does not impact anybody else.
  • The query runs within acceptable performance boundaries for customers: it may take 10 minutes to run but it’s a batch process and the relevant business unit might only need it within an hour.
  • The amount of work that the query is doing is such that further optimizations are either not possible at all or they are only possible with a significant restructure that the business is unwilling to accept.

Even so, the term “expensive query” is still very useful. So is “expensive query relative to what it could be,” although we do tend to conflate the latter with the former. But now we’re getting deep into semantics and I forgot my waders.

Comments closed

Application Names and Database Queries

Tom Zika does not like those missing application names:

Whenever I’m trying to debug a problem using sp_whoisactive or Extended Events (XE) and I see either Core Microsoft SqlClient Data Provider or .Net SqlClient Data Provider, my blood begins to boil.

It means I’ll probably spend hours asking around to try and find the owner. Sometimes knowing the host_name helps, but there can be a multi-purpose host that runs many applications – which one is having the problem?

How do you set the name? Read the post to find out.

Comments closed

Against Tibbling

Hugo Kornelis hates tibbling:

Probably the one I hate most. And one that is stubbornly persistent. Object name prefixing.

Or, to be more precise, the standard that enforces that all table names need to start with a prefix that designates them as a table, and all view names with a different prefix to clearly mark them as a view. Typically tbl_ and vw_ are used, though I have also seen just the letters t and v, and I have seen them with or without underscores.

I hate this coding standard (or rather, naming standard) with a vengeance. For a few reasons. The perceived benefit is in fact not a benefit at all. It is detrimental to a quick understanding of what I see on the screen. But my biggest objection is that it negates one of the greatest benefits of views.

Read on to understand why this is a bad idea. I completely agree with Hugo on this.

Comments closed

Reconciling Tag Names across Azure

Anthony Watherston has an interesting script:

During a recent cost optimization workshop with a customer, they mentioned that although they had some tagging policies in place there was no consistency of tag names across the Azure environment. This post introduces a script to remediate this and remove some confusion from your tagging strategy.

The customer was trying to ensure that all resources were being tagged with a cost centre tag. Some of this was automatic and some was done manually by people. While there was a policy in place to control this in the future, they needed a way to remediate the existing resources.

This is really useful if you have enough information to create a to-and-from mapping. It won’t automatically understand anything, so you’ll need to do the digging but it will do the renaming.

Comments closed

A Data Governance by any other Name

Matthew Roche wants a re-naming:

To successfully implement managed self-service business intelligence at any non-trivial scale, you need data governance. To build and nurture a successful data culture, data governance is an essential part of the success.

Despite this fact, and despite the obvious value that data governance can provide, data governance has a bad reputation. Many people – likely including the leaders you need to be your ally if you’re working to build a data culture in your organization – have had negative experiences with data governance in the past, and now react negatively when the topic of data governance is raised.

They now treat data governance as a four-letter word.

Read the whole thing, though I do disagree with Matthew. Changing the name does not change the underlying problems; all it does is make the new name just as hated as the old one because the problems are still there. Call it Data Enablement if you’d like, but if the process is the same and the tools are the same, the outcome is the same, regardless of the name.

Comments closed

Updates in Azure Synapse Analytics

Saveen Reddy shows how the Synapse product team has been busy this year:

Previously, Synapse workspaces had a kind of database called a Spark Database. Spark databases had two key characteristics:

– Tables in Spark databases kept their underlying data in Azure Storage accounts (i.e. data lakes)

– Tables in Spark databases could be queried by both Spark pools and by serverless SQL pools.

To help make it clear that these databases are supported by both Spark and SQL and to clarify their relationship to data lakes, we have renamed Spark databases to Lake databases. Lake databases work just like Spark databases did before. They just have a new name.

Okay, this is the kind of change I can do without. That’s a really dumb name. Spark databases tell you what a thing is. It’s a database which lives in Apache Spark. Lake databases run what? Apache Spark. But if anything really should be called a Lake database, it’d be a serverless SQL pool’s database because everything in there is built on top of the data lake—it’s all external tables pointing to a lake. So calling a Spark database a Lake database brings more confusion than elucidation.

Most of the other changes on that list? Really cool. This one? Not at all.

Comments closed

Dynamic Column Rename in Power BI with XMLA and TOM

Kristyna Hughes solves a problem:

For the TOM and XMLA experts, imagine this. Your customer wants to dynamically rename columns without using the Power BI Desktop and would prefer all existing report visuals not get broken by the new name. Impossible? Not with TOM, XMLA, and translations within Power BI.

If you’ve ever tried to change a column name in a Power BI source, you’ve likely run into this error on any visuals that contained the renamed column. And when you hit that “See Details”, it will tell you the column that you simply renamed is no longer available for your visual.

So how do we get around that?

Read on to see how.

Comments closed

Renaming Multiple Columns at Once in Power BI

Matt Allington wants to change a bunch of column names at once with Power BI:

This is not the first time I have shared this concept.  In my previous article I showed how it is possible to add a prefix to every column in a table. This article today is slightly different. Today I am removing text from multiple columns all at once using some M code. The trick you need to learn to solve this problem is “how to create a list of lists”.

Click through for a video to see it in action.

Comments closed