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Month: April 2016

Joining Ubuntu To AD

Published 2016-04-13 by Kevin Feasel

Chrissy LeMaire shows us how to connect to AD from Ubuntu:

Since 2009, it seems that a couple things have changed in the client realm. In particular, winbindfell out of favor to Likewise Open (which I used to <3) which was bought by BeyondTrust and turned into PowerBroker Open. But that’s since fallen out of favor to the SSSD or “System Security Services Daemon“. SSSD seems pretty cool but everyone hates its name and assume that its name is keeping it from greater adoption.

Sometimes when researching SSSD, you’ll come across a few mentions of FreeIPA which is similar to Active Directory, OpenLDAP, and ApacheDS. Oh, and I recently found out thatSamba4 allows Linux servers to join Active Directory as Domain Controllers (!!) but I can’t tell if it can be a forest of its own (reddit review here).

There are other players I’m leaving out but after a bit of casual research, no others seem to stand out. Ultimately, while there are a number of ways to setup AD/Linux authentication with Ubuntu, it appears that SSSD is the current way to go. Let’s go ahead and set that up.

Cf Ryan Adams and LeMaire’s separate posts back in March on the topic.  As Microsoft gets serious about Linux integration, I would love to see them simplify this process significantly, either by updating an existing open-source project (my preference) or creating their own open-source project.

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Data Lakes

Published 2016-04-13 by Kevin Feasel

Jen Stirrup has a great primer on data lakes and factors to consider before you jump into the idea:

The organization will need to take a step back to understand better their existing status. Are they just starting out? Are other departments which are doing the same thing, perhaps in the local organization or somewhere else in the world? Once the organization understands their state better, they can start to broadly work out the strategy that the Data Lake is intended to provide.

As part of this understanding, the objective of the Data Lake will need to be identified. Is it for data science? Or, for example, is the Data Lake simply to store data in a holding pattern for data discovery? Identifying the objective will help align the vision and the goals, and set the scene for communication to move forward.

I would like to popularize the term Data Swamp for “that place you store a whole bunch of data of dubious origin and value.”  It’s the place that you promise management of course you can get the data back…as long as they never actually ask for it or are okay with reading terabytes of flat files from backup tapes.  The Data Swamp is the Aristotelian counterpart to the Data Lake, Goofus to its Gallant.  It will also, to my estimate, be the more common version.

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Single-Socket OLTP Systems?

Published 2016-04-13 by Kevin Feasel

Joe Chang tosses a hardware-related bomb:

Today, it is time to consider the astonishing next step, that a single socket system is the best choice for a transaction processing systems. First, with proper database architecture and tuning, 12 or so physical cores should be more than sufficient for a very large majority of requirements.

We should also factor in that the second generation hyper-threading (two logical processors per physical core) from Nehalem on has almost linear scaling in transactional workloads (heavy on index seeks involving few rows). This is very different from the first generation HT in Willamette and Northwood which was problematic, and the improved first generation in Prescott which was somewhat better in the positive aspects, and had fewer negatives.

Joe knows a lot more about this than I do, but I’m very hesitant about this for two reasons.  First, scale.  When we start looking at hundreds of concurrent requests, would a single-socket machine really work?  I don’t know to answer to that, but in my simplistic “more is better than fewer” rule of thumb, I’d err on the side of caution, especially if it isn’t my money paying for this.

Second, there are batch processes and large background activities which occur even on extremely transactional OLTP systems.  Think about running CHECKDB or ETL processing or troubleshooting/monitoring processes.  These are going to be processes which benefit from parallelism, and if you’re seriously limiting core counts (which a single socket would necessarily do), you might end up in a bad way when they run even if your “normal” workload performs a little better.

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SSIS RC2 Issues

Published 2016-04-13 by Kevin Feasel

Andy Leonard walks through his experience trying SSIS 2016 RC2:

The SSMS 2016 RC2 link works just fine. The SSDT 2016 RC2 link does not work.

Fear not! The SSIS team has provided a set of updated links for SSIS 2016 SSDT for RC2. There’s other good information in that post. If you want to tinker with SSIS 2016 RC2, I encourage you to read it.

But Wait, There’s More

Once I’d done all this, I could create an SSIS project and add a Script Task to a package. But I could not open the Visual Studio Tools for Applications (VSTA) code editor. When I clicked the “Edit Script…” button in the Script Task Editor, nothing happened.

I contacted the SSIS Development Team (we hang out), and let them know what I was seeing. They are aware of the issue and sent the following screenshot

Sounds like there are still some kinks to work out before release.

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Is Power BI SSAS In The Cloud?

Published 2016-04-13 by Kevin Feasel

Koos van Strien hits us with an interesting thought about SSAS versus Power BI:

As I’m currently planning to migrate the entire BI architecture of one of my customers to the cloud, this made me think: can we ditch SSAS as we know it already in favor of Power BI? What are the alternatives?

To study that, I’ve put some diagrams together to show the possibilities of moving BI to the cloud. First, I’ll discuss the possible architectures, then the impossible architecture (but maybe the situation I was looking for).

One man’s opinion:  there will be SSAS for Azure.  I have no proof of this, and the nice part about having no proof is that I can throw out wild speculation without fear of violating NDA….  But to me, Power BI solves a different problem and acts in conjunction with SSAS rather than as its replacement.  I also don’t see any technical reasons why SSAS couldn’t live in the cloud, and so that leads me to believe that it will be there eventually.  But hey, it turns out wild speculation is occasionally wrong…

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DATEADD With SYSUTCDATETIME

Published 2016-04-12 by Kevin Feasel

Aaron Bertrand blogs on an estimation failure with DATEADD and SYSDATETIME/SYSUTCDATETIME:

Essentially, the problem is that a poor estimate can be made not simply when SYSDATETIME() (or SYSUTCDATETIME()) appears, as Erland originally reported, but when any datetime2expression is involved in the predicate (and perhaps only when DATEADD() is also used). And it can go both ways – if we swap >= for <=, the estimate becomes the whole table, so it seems that the optimizer is looking at the SYSDATETIME() value as a constant, and completely ignoring any operations like DATEADD() that are performed against it.

Paul shared that the workaround is simply to use a datetime equivalent when calculating the date, before converting it to the proper data type. In this case, we can swap outSYSUTCDATETIME() and change it to GETUTCDATE()

I suppose switching to GETUTCDATE isn’t too much of a loss, but it looks like (according to Paul White in the second linked Connect item) this appears to have been fixed in SQL Server 2014.

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Getting The Last Row Per Group

Published 2016-04-12 by Kevin Feasel

Daniel Hutmacher wants to get the last element in each group (for example, the current records in a type-two dimension):

The CROSS APPLY and the old-school solutions are by far the best choice for dense indexes, i.e. when the first column has a low degree of uniqueness. The old-school solution is only that fast because the optimizer short-circuits the query plan.

LEAD() and the old school strategy are best for selective indexes, i.e. when the first column is highly unique.

There’s a nice set of options available so if one doesn’t work well with your particular data set, try out some of the others and see if they work for you.

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Transaction Log Analysis

Published 2016-04-12 by Kevin Feasel

Michael Swart shows how to dig into the transaction log to trace down those WRITELOG waits:

WRITELOG waits are a scalability challenge for OLTP workloads under load. Chris Adkin has a lot of experience tuning SQL Server for high-volume OLTP workloads. So I’m going to follow his advice when he writes we should minimize the amount logging generated. And because I can’t improve something if I can’t measure it, I wonder what’s generating the most logging? OLTP workloads are characterized by frequent tiny transactions so I want to measure that activity without filters, but I want to have as little impact to the system as I can. That’s my challenge.

Check out the entire post, as this is a good exercise in investigating busy transactional systems.

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Extended Events In Azure SQL Database

Published 2016-04-12 by Kevin Feasel

Julie Koesmarno walks through Extended Events in Azure SQL Database (currently in preview):

Extended Event (XEvent) feature is available as public preview in Azure SQL Database as announcedhere. XEvent supports 3 types of targets – File Target (writes to Azure Blob Storage), Ring Buffer and Event Counter. Once we’ve created an event session, how do we inspect the event session target properties? This blog post describes how to do this in 2 ways: using the User Interface in SSMS and using T-SQL.

It’s nice to see Extended Events making their way into Azure SQL Database.

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SQL Server JDBC Driver Update

Published 2016-04-11 by Kevin Feasel

Microsoft is releasing a preview of their JDBC driver:

We are committed to continuously updating the JDBC driver to bring more feature support for connecting to SQL Server, Azure SQL Database, and Azure SQL DW. Please stay tuned for upcoming releases that will have additional feature support. This applies to our wide range of client drivers including PHP 7.0, Node.js, ODBC, and ADO.NET which are already available.

Don’t forget Hadoop integration (e.g., via Sqoop) while you’re at it…

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