Category: Wacky Ideas

Grant Fritchey argues that the DBA role is here to stay:

One of the reasons I love DevOps so much is because I’ve done it successfully. I’ve worked on teams that built fully automated deployment mechanisms to get code from Dev to Production. Further, we automated the creation of dev & test servers. We automated the creation of production servers too. We automated the heck out of everything.
And then they fired me…
Kidding.
When we started building our DevOps processes, I was supporting two development teams. As we got better at automating our work, I was supporting three teams. By the time we had fully automated all the various processes, I was supporting between five and seven teams at different levels.

To support Grant’s point, I’ve had a draft in my personal blog entitled “The Cloud is not Stealing Our Jobs” from May of 2017 that I never got around to finishing. Back in 2017, that was what was going to kill the DBA role.

The role has certainly changed over the years. I suppose if your definition of a DBA is someone who lays out indexes starting on certain drive sectors to take advantage of rotation speed on that single 5400 RPM spinning disk drive AND NOTHING ELSE, then your job might not be there. But that describes exactly zero people I have ever known in the industry.

Tomaz Kastrun has created a job title generator in T-SQL:

While writing a sample random function in using T-SQL Server, I have remembered, why not write a job title generator for T-SQL domain only. You might have seen so called bulls**t job title generator and similar, but this one is T-SQL SQL server specific.

So, why not come up with random, yet funny T-SQL job titles. And making it, I have to tell you, it was fun. And I was simply hitting that F5 button in SSMS, to get new job title generated and laugh out loud.

It took me a few clicks, but I got “Qualitative R ggplot library Stackover subscriber,” which might be hitting the mark a little close.

Alex Woodie reviews the latest Gartner Hype Cycle for Emerging Tech:

Democratized artificial intelligence is one of five trends driving Gartner’s latest Hype Cycle for Emerging Technologies, which it updates this month, as it traditionally does during the month of August.

The analyst group took a slightly different approach with this year’s Hype Cycle for Emerging Tech and grouped the 35 individual technologies into major groups, which includes digitalized ecosystems, do-it-yourself biohacking, transparently immersive experiences, and ubiquitous infrastructure, along with democratized AI.

The five trends will “blur the lines between human and machine,” Gartner says. “CIOs and technology leaders should always be scanning the market along with assessing and piloting emerging technologies to identify new business opportunities with high impact potential and strategic relevance for their business,” writes Mike J. Walker, research vice president at Gartner.

It’s an interesting exercise and parlor game.

Riley Major continues his series on tic-tac-toe:

We could give it some smarts. For example, we know that in our game, we can only choose X or O, so we could put a data constraint on the Play column. And we know that in our game, you can’t play on the same space more than once, so we could put a unique constraint on the combination of GameID and Position. You could even be really creative and enforce our game’s alternating player moves by putting a data constraint on the Player column such that it equaled 1 when (Turn Modulo 2) equaled 1 and 2 otherwise. (Really it wouldn’t need to be a data column at that point, just a calculated column.)

But imposing those restrictions robs our data structure from its raison d’être. It’s no longer a general purpose game play storage system; it only works for our game.

Instead of saddling the data storage itself with all of those rules, we could enforce all of the game mechanics through our data interpretation and manipulation logic. When we saved a game move, we could make sure that an X or O was played and it could check to see whether the specified square was already used. When we analyzed a game to determine a win, all of the criteria could be housed in that consuming query. But this flexible design isn’t done inflicting its complexity on us.

Riley covers a number of T-SQL features in the process of this post.

Lukas Eder has a fun post on Tupper’s self-referential formula:

Luckily, this syntax also happens to be SQL syntax, so we’re almost done. So, let’s try plotting this formula for the area of x BETWEEN 0 AND 105 and y BETWEEN k AND k + 16, where k is just some random large number, let’s say

96093937991895888497167296212785275471500433966012930665
15055192717028023952664246896428421743507181212671537827
70623355993237280874144307891325963941337723487857735749
82392662971551717371699516523289053822161240323885586618
40132355851360488286933379024914542292886670810961844960
91705183454067827731551705405381627380967602565625016981
48208341878316384911559022561000365235137034387446184837
87372381982248498634650331594100549747005931383392264972
49461751545728366702369745461014655997933798537483143786
841806593422227898388722980000748404719

Unfortunately, most SQL databases cannot handle such large numbers without any additional libraries, except for the awesome PostgreSQL, whose decimal / numeric types can handle up to 131072 digits before the decimal point and up to 16383 digits after the decimal point.

Yet again, unfortunately, even PostgreSQL by default can’t handle such precisions / scales, so we’re using a trick to expand the precision beyond what’s available by default.

Check it out.