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Day: March 10, 2017

Analyzing The Ramones

Published 2017-03-10 by Kevin Feasel

Salvino Salvaggio uses R to analyze The Ramones:

Musical purists always reproached the Ramones for knowing a couple of chords only and making an excessive use of them. Data show that the band knew at least… 11 different chords (out of too-many-to-bother-counting possibilities) although 80% of their songs were built on no more than 6. And there is no evidence of a sophistication of the Ramones’ compositions over time.

It’s a fun analysis with all the R code attached.  This fun analysis, however, includes n-gram analysis, sentiment analysis, and token distribution analysis.

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Handling Overly Large Log Files

Published 2017-03-10 by Kevin Feasel

Kevin Hill shows how to recover from a scenario with an unexpectedly large SQL Server transaction log file:

Step 2: Verify if the log is full or “empty”

Verify if the log file is actually full or not.  If you are backing up and the file still grew to ridiculous size…it may have just been a one time thing and you can deal with that easily.  Right-click the database, go to reports, standard reports, disk usage.  This will give you 2 pie charts.  Left is the data file, right is the log.  If the log shows almost or completely full AND the huge size, you need to backup.  If the log file is huge and mostly empty, you simply need to shrink to an acceptable size.

Great read for a junior-level DBA.

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Getting Familiar With Shape Maps

Published 2017-03-10 by Kevin Feasel

Reza Rad shows how to generate a shape map in Power BI:

I have previously written some blog posts about Map visuals in Power BI. One of them was specifically about Filled Map, titled as Filled Map; the Good, the Bad, the Ugly! Why? you need to read that post to find the reason. In this post I want to explain the power of Shape Map which is one of the visuals Power BI team published recently. This visual is still at preview mode at the time of writing this post. This visual is much more powerful than what it looks. The actual power behind it is that you can have your own map added to it. Let’s take a closer look at this visual with an example. If you want to learn more about Power BI; read Power BI from Rookie to Rock Star.

It’s an interesting look at a new visual.

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Automating SpeedPASS Generation

Published 2017-03-10 by Kevin Feasel

Wayne Sheffield has a Powershell script to generate SQL Saturday SpeedPASSes:

My good friend, Mr. Google, found this post by Kendal Van Dyke. This post has a PowerShell script that will download and merge all of the PDFs for selected attendees into one big PDF. This enables printing out all of the SpeedPASSes at once, instead of one-by-one. However, I have a couple of problems with this script in it’s current form. First, the instructions for how to get the information from the SQLSaturday admin site have changed (they did do a major web site change last year). Secondly, it downloads all of the PDFs one-by-one, and puts them into a temporary directory, where they are all merged together. In file-name order. Not alphabetically. This means that the manual sorting is still necessary. But hey – it’s PowerShell. Surely we can come up with a way to do this sorting for us!

So I decided to re-write this script to suit my needs. Kendal’s script downloads the SpeedPASS PDF files one-by one. However, the admin site allows us to download all of them in one zip file. I like this approach better. I ended up making two major changes to the script. The first change requires pre-downloading and extracting all of the SpeedPASSes files. The second change is to get them to merge alphabetically. Like Kendal’s script, this uses the PDFSharp assemblies. This requires using PowerShell 3.0 or higher.

Click through for the script, which is probably very helpful if you ever run a SQL Saturday event.

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HDInsight Basics: Nodes

Published 2017-03-10 by Kevin Feasel

Abdullah Al Mahmood explains some of the basics of Azure HDInsight, including what Hadoop means by nodes:

HDInsight clusters consist of several virtual machines (nodes) serving different purposes. The most common architecture of an HDInsight cluster is – two head nodes, one or more worker nodes, and three zookeeper nodes.

Head nodes: Hadoop services are installed and run on head nodes. There are two head nodes to ensure high availability by allowing master services and components to continue to run on the secondary node in the event of a failure on the primary. Both head nodes are active and running within the cluster simultaneously. Some services, such as HDFS or YARN, are only ‘active’ on one head node at any given time (and ‘standby’ on the other head node). Other services such as HiveServer2 or Hive Metastore are active on both head nodes at the same time. There are services like Application Timeline Server (ATS) and Job History Server (JHS) which are installed on both head nodes but should run only on the head node where Ambari server is running. If these components sound unfamiliar, please revisit the article on Hadoop ecosystem in HDInsight.

Read on to see the other classes of nodes HDInsight uses.

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Interrogating A Stack Dump

Published 2017-03-10 by Kevin Feasel

Kendra Little looks at a SQL Server stack dump:

In the video, I show an example of a stack dump caused by running DBCC PAGE with format style 3 against a table with a filtered index in SQL Server 2014.

It looks like this bug is fixed in SQL Server 2016, at least by SP1.

Sample code to reproduce this against the AdventureWorks2012 database (which I had restored to SQL Server 2014) is in my gist here.

Click through to watch the video.

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SSMS Templates

Published 2017-03-10 by Kevin Feasel

Jana Sattainathan shows some of the value of SQL Server Management Studio templates, along with an important warning:

If you do start creating your own templates, you are responsible for backing them up. To locate the folder where they are stored

  1. Open DOS command prompt
  2. Run “echo %APPDATA%”
  3. Note the base path
  4. Navigate to %AppData%\Microsoft\Microsoft SQL Server\{SQL Server Version}\Tools\Shell\Templates\Sql\

(where %AppData% is the base path from

and {SQL Server Version} = 90 for SQL 2005, 100 for SQL 2008, 110 for SQL 2012, 120 for SQL 2014 and 130 for SQL 2016)

Templates are extremely useful for day-to-day development as well as giving a handy way of generating snippets of code, like estimating row count without having to remember to join to sys.indexes, sys.objects, and sys.dm_db_partition_stats.

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Google Compute Engine Whitepapers

Published 2017-03-10 by Kevin Feasel

Brent Ozar Unlimited has a couple whitepapers out about working with SQL Server in Google Compute Engine.  First, Brent and Tara Kizer create an Availability Group:

In this white paper we built with Google, we’ll show you:

  • How to build your first Availability Group in Google Compute Engine

  • How to test your work with four failure simulations

  • How to tell whether your databases will work well in GCE

Erik Darling also has a whitepaper on performance tuning:

Relax. Have a drink. In this white paper we built with Google, we’ll show you:

  • How to measure your current SQL Server using data you’ve already got

  • How to size a SQL Server in Google Compute Engine to perform similarly

  • After migration to GCE, how to measure your server’s bottleneck

  • How to tweak your SQL Server based on the performance metrics you’re seeing

If you’re looking at GCE as a potential migratory spot, you’ve got some extra reading material.

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