An Unusual R Services Problem

Published On: 2017-08-11By:

I have had the good luck of having a customer was onboard with SQL Server 2016 very early—like we started testing in March of 2015, and went live in August of 2015. In fact, their home directory refers to vNext instead of 2016. This customer also adopted what felt like most of the new features list. Temporal tables, columnstore, PolyBase, and R Services amongst other features. Anyway, we had R up and running, and it ran for a while.

Recently, and unfortunately I don’t have an exact date on when this started failing (though it was around service pack 1 install time) with the following error:

Error
Msg 39012, Level 16, State 1, Line 10
Unable to communicate with the runtime for ‘R’ script. Please check the requirements of ‘R’ runtime.
STDERR message(s) from external script:
 
DLL ‘C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER1601\MSSQL\Binn\sqlsatellite.dll’ cannot be loaded.
Error in eval(expr, envir, enclos) :
   DLL ‘C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER1601\MSSQL\Binn\sqlsatellite.dll’ cannot be loaded.
Calls: source -> withVisible -> eval -> eval -> .Call
Execution halted
STDOUT message(s) from external script:
 
Failed to load dll ‘C:\Program Files\Microsoft SQL Server\MSSQL13.MSSQLSERVER1601\MSSQL\Binn\sqlsatellite.dll’ with 182 error.

I troubleshot this with some colleagues at Microsoft and we weren’t able to resolve. We tried a couple of different approaches including reinstalling CU1, but all to no avail. Yesterday, I got on a call with a couple of folks on the product team to try an isolate the problem. We looked at binaries and timestamps and it looked like everything matched up. Then, my friend Arvind Shyamsundar (b|t) suggested we run procmon on the server.

image

There Arvind noticed these odd calls to sqlos.dll in the shared directory. We then looked at add/remove programs and found the following item installed:

Screen Shot 2017-08-11 at 8.19.38 AM

The T-SQL compiler service which was a legacy of CTP 2.3 was there, and as soon as we uninstalled our problems went away. So, if you happen to be running on a server that you’ve upgraded since very early versions of SQL Server 2016, you may see this issue.

Just to give credit to Microsoft and the current SQL Server install process, this server has had nearly every release of SQL Server 2016 on it (we’re behind a couple of CUs), and this is the only issue we’ve had. Thanks again to Arvind and UC for solving this tough issue.


Analyzing Your Dump Files

Published On: 2017-08-08By:

I’m blogging about this, because A) It’s something really awesome that the SQL Server team built and B) it seems to have terrible SEO, because it took me like three google searches to find the page. With the introduction of SQL Server Management Studio 17, the Tiger team at Microsoft built a plugin that allows you to debug and resolve memory dumps you may have encountered during otherwise normal operations. This is really awesome, as it is something that usually requires a support case with CSS.

For those of you wearing aluminum hats, this does require you do upload the dump file to Azure, where it is analyzed for free (as in beer) on Microsoft’s software. You can even choose your region if you have data provenance concerns. And according to this blog post the memory dumps are stored in accorded with Microsoft’s Privacy Policy.

You will need SSMS 17 for this, as well as to install the plug in, which you can get here.

image

After that you can quickly get feedback on your dumps. Microsoft have even built an API, so if you want to built something automated to upload your dump files using Python or PowerShell you can.


The Self-Tuning Database?

Published On: 2017-07-31By:

There was a lot of talk on Twitter over the weekend, about automation, and the future of the DBA role. I’ve spoken frequently on the topic, and even though the PASS Summit program committee has had limited interest in my automation sessions, they have been amongst my most popular talks at other large conferences. Automating mundane tasks makes you a better DBA, and escalating the level of those tasks allows you to focus on activities that really help your business like better data quality, and watching cat videos on YouTube.

But Tuning is Hard

Performance tuning has always been something of a black art. I remember that Oracle called 9i the self-tuning database, because we no longer had to manually calculate how many blocks (pages) of memory where allocated to each pool. That was a joke—and those databases still required a lot of manual effort for tuning. However, that was then, and we’re in the future now. We’ll call the future August. Stay with me here, I’m going to talk about some theories I have.

So It’s August 2017

Let’s say you were a vendor of a major RDBMS, who also happened to own a major hyperscale cloud, and you had invested heavily in collecting query metadata in the last two releases of your RDBMS. Let us also accept the theory that the best way to get an optimal execution plan, is to generate as many potential execution plans as possible. Most databases attempt a handful of plans, before picking the best available plan—this is always a compromise as generating execution plans involves a lot of math, and is very expensive from a CPU perspective. Let us also portend that as owner of the hyperscale cloud, you also have a lot of available processing power, and you’ve had your users opt-in to reviewing their metadata for performance purposes.

rube-goldberg-stamp

Still With Me?

Ok, so we have all the tools in place to build our self-tuning database, so let’s think about what we would need to do. Let’s take a somewhat standard heuristic I like to use in query tuning—if a query takes more than 30ms to execute or is executed more than 1000/times in a day, we should pay attention to it for tuning purposes. That’s a really big filter—so we’ve already narrowed down the focus of our tuning engine (and we have this information in our runtime engine, which we’ll call the Query Boutique). We have also had our users opt-in to use using their metadata to help improve performance.

So we identify our problem queries in your database. We then export the statistics from your database, into our backed tuning system. We look for (and attempt to apply) any missing indexes to the structure, to evaluate the benefit of a missing index. We then attempt to generate all of the execution plans (yes, all of them—this processing is asynchronous, and doesn’t need to be real time). We could even collect read/write statistics on given objects and apply a weighted value to a given index. We could then take all of this data and run it through our back end machine learning service, to ensure that our query self tuner algorithm was accurate, and to help improve our process.

We could then feed this data back into the production system as a pinned execution plan. Since we are tracking the runtime statistics, if the performance of the plan drops off, or we noticed that the statistics changed, we could force out our new execution plan, and start the whole process over again.

So there, I didn’t write a line of code, but I laid out the architecture for a self-tuning database. I’m sure this would talk years and many versions to come into effect. Or not at all. To be successful in this changing world of data, you need to stay ahead of the curve, learn about clouds work, how to script, how to automate, and how to add value.


Drive By #$%^ing—er, Tweeting.

Published On: 2017-07-26By:

Note: This post may contain some vulgarities, but no obscenity, at least as defined by the Supreme Court in Miller v. California (1973)

So, my morning started of early, with a lovely bike ride. It was nice in cool in Southern California, so I had a lovely 20 miles. Then, I took my phone out of my pocket and was confronted with two really shitty posts. The first was on twitter, and the second was so shallow that it may as well been a tweet.

I love Twitter, I’ve been on for almost ten years, and as a data nerd, and sports fan, it is like the end all be all of services. However, for discourse, 140 characters leaves out the ability to for any nuance or subtlety. (See the President of United States, not that he had any nuance or subtlety to begin with). However, when you legitimately want to critique something, prose works far better than a 140 characters.

The First #$%, er Tweeter

So I got back from my ride, and the first thing I saw was:

Screen Shot 2017-07-26 at 8.09.53 AM

Richie, that tweet was school on Sunday dude. Not cool—I get that you may not like the sessions picked, or general direction of the organization (I certainly disagree with a ton of what PASS does, and am moderately vocal about it). But when you write a tweet like that, you are basically inferring that a bunch of shitty speakers, submitted a a bunch of shitty sessions, and the program committee organized a total shit show. You probably didn’t mean that—I personally think the new emphasis on development isn’t the right approach for a database conference. However, that’s a) not my decision, and b) a more nuanced thought than “Summit sucks, haha.”

The old saying about “if you don’t have anything nice to say, don’t say anything”, is wrong. However, if you don’t have anything constructive to say,don’t insult 150+ speakers,volunteers, and potential sponsors who might be reading your stream.

The Second #$%e, Blogger

I’m not linking to this guy’s shit. Because it’s shit.

Screen Shot 2017-07-26 at 9.11.10 AM

Here’s the gist of this post—Azure SQL Database and Azure Blob Storage are completely $%^&ing insecure because they have public IP addresses. Never mind, that you can completely lock them down to all IP addresses, and Azure. (Granted a database or storage account that no one can access is probably of limited value). However, these services are fully accessed controlled and have built-in security. Additionally, in the case of SQL DB, you have the option of built-in threat detection that will detect anomalous behavior like SQL injection, or rogue logins.

Currently, Azure doesn’t have the ability the put your database on a VNet. I’d be shocked if the Azure team is not working on said feature. In the article, the author makes a point of Amazon having the ability to do this for RDS. That’s cool, and probably why Microsoft is working on it. But instead of focusing on how to secure your app in a hybrid platform, he just shits on the vendor with a clickbait headline.

Wheaton’s Law

Wheaton’s Law, which also happens to be the core of our HR policy at DCAC, is simply “Don’t be a dick”. Think before you write and tweet—don’t write clickbait crap, and if you want to criticize an org, do it carefully, and write a blog post. Or send someone a DM.


1 2 3 16

Video

Globally Recognized Expertise

As Microsoft MVP’s and Partners as well as VMware experts, we are summoned by companies all over the world to fine-tune and problem-solve the most difficult architecture, infrastructure and network challenges.

And sometimes we’re asked to share what we did, at events like Microsoft’s PASS Summit 2015.