What’s Your Second Biggest SQL Server Problem?

Checking It Twice

Make a list of the top 3-5 problems you have on your SQL Server. Go ahead, I’ll wait.

Now put them in order. Which one is the biggest problem, and who is it a problem for?

That’s a big problem, huh? It’d take a lot of time and effort to fix that problem.

But what about the rest of your problems? If you look down the list, you’ll probably find stuff that you could make some progress on in the meantime.

Don’t Get Stuck

Just as an example, let’s say you have to install SQL Server. When you go to set it up, you realize that the service accounts weren’t made for it, and the Sysadmin who takes care of that stuff is out sick (of being a Sysadmin).

You might hold off on doing everything else because of that roadblock, even though you could have the server ready to go, and just swap the service account in later.

The same thing happens to people with other problems, too. Let’s say the list looks like this:

  1. We’re importing XML and shredding it constantly while queries run
  2. There are some scalar valued functions that we use as helpers to parse the XML
  3. We’ve got tables that need indexes (including clustered indexes)
  4. tempdb only has one data file
  5. Our parallelism settings are wrong

A lot of people will get stuck on their biggest problem. It’s happened to me, too.

Heck, just setting things up here over the past week has been full of roadblocks, and sometimes I’d find myself saying “well, what’s the point of doing X if I don’t have Y yet?”.

Current Events

Right now, my biggest problem is waiting on some paperwork so I can open a business checking account, but if I sat around waiting on that before setting up a mailing list, blogging, setting up Zapier, and all that, I’d be way far behind when that stuff did come in.

And when it did, my second biggest problem would turn into my biggest problem.

If you find yourself not working on other problems because you’ve got one monolithic problem, try to remember that solving smaller problems has an upstream effect. Especially with SQL Server, where small changes can make big impacts.

I’ve seen servers go from constantly running out of worker threads to humming along happily just by having smarter parallelism settings.

Going Further

If this is the kind of SQL Server stuff you love learning about, you’ll love my training. I’m offering a 75% discount to my blog readers if you click from here. I’m also available for consulting if you just don’t have time for that and need to solve performance problems quickly.