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Month: July 2017

Integrating dbatools Into VSCode

Published 2017-07-10 by Kevin Feasel

Andrew Pruski shows how to integrate dbatools Powershell commands into Visual Studio Code:

The first dbatools commands that I looked at are: –

These commands do exactly what they say on the tin. Pretty standard stuff for DBAs but what’s cool is how we can use Visual Studio Code to quickly and easily check that all our databases are being backed up and have a recent (good) CHECK DB.

I’m going to setup two scripts to run the dbatools commands against my SQL instances via Visual Studio Code Tasks.

Read on to see how Andrew did it.

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Plotly And Power BI

Published 2017-07-10 by Kevin Feasel

Leila Etaati shows how to use Plotly to generate interactive R charts in Power BI:

In the last two posts (Part 1 and 2), I have explained the main process of creating the R custom Visual Packages in Power BI. there are some parts that still need improvement which I will do in next posts. In this post, I am going to show different R charts that can be used in power BI and when we should used them for what type of data, these are Facet jitter chart, Pie chart, Polar Scatter Chart, Multiple Box Plot, and Column Width Chart. I follow the same process I did in Post 1 and Post 2. I just change the R scripts  and will explain how to use these graphs

Leila includes several examples of chart types and shows that it’s pretty easy to get this working.

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Naming Graph Edges

Published 2017-07-10 by Kevin Feasel

Greg Low is trying to find a common nomenclature for edges in graphs:

Positive (Forward) Direction

I’d also like to see the tables use a forward direction naming rather than reverse (like “Written By”). So perhaps:

($from_id) the member Wrote the post ($to_id)

($from_id) who Likes who/what ($to_id)

($from_id) the reply to the main post RepliesTo the main post ($to_id)

Avoid passive voice.  That’s good advice in general.

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Maintenance Plans In SQL Server 2016

Published 2017-07-10 by Kevin Feasel

Kendra Little describes some changes to maintenance plans in SQL Server 2016:

Working with maintenance plans is supposed to be easy, but I find it to be quite difficult.

In part, this is because they can often be buggy. To write this post today, I had to go back and install SSMS 16.5, because I wasn’t able to configure logging or change some aspects about my test maintenance plan in SSMS 17. (I use case sensitive instances, and this bug also impacts things like the maintenance plan log dialog box.)

And in part this is because the documentation for maintenance plans doesn’t tend to be as clear as the documentation for TSQL commands. So in the interest of saving other folks time, I wanted to share what I learned about the Rebuild Index Task, Reorganize Index Task, and Update Statistics Task in SQL Server 2016.

Though if you’re reading this, you probably already have a better solution than maintenance plans…

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Database Connection Leaks

Published 2017-07-10 by Kevin Feasel

Michael J. Swart explains how to find database connection leaks:

So, if your application experiences connection timeouts because of a database connection leak, the stack traces may not help you. Just like an out-of-memory exception due to a memory leak the stack trace has information about the victim, but not the root cause. So where can you go to find the leak?

Even though database connection leaks are a client problem, you can find help from the database server. On the database server, look at connections per process per database to get a rough estimate of the size of each pool:

This is a good thing to remember, particularly if you have a busy system.

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Interactive CallBimlScript

Published 2017-07-10 by Kevin Feasel

Ben Weissman introduces a feature coming to BimlExpress:

So far, there wasn’t much you could do but either replicate a lot of logic, parse the XML returned, use countless annotations or have many many different versions of your callee.

All of these options aren’t too appealing, right?

But: help is here! In addition to the known CallBimlScript, you can now use: CallBimlScriptWithOutput! It allows you to make use of a dynamic object to be returned by the CallBimlScript (in addition to the Biml code) which effectively means: you can return any kind of information back to the caller.

I can see this being useful for debugging and for centralizing flow logic a little bit better.  Click through for a sample script.

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Regularization Prevents Overfitting

Published 2017-07-07 by Kevin Feasel

Hui Li has an explanation of what regularization is and how it works to reduce the likelihood of overfitting training data:

Assume that the red line is the regression model we learn from the training data set. It can be seen that the learned model fits the training data set perfectly, while it cannot generalize well to the data not included in the training set. There are several ways to avoid the problem of overfitting.

To remedy this problem, we could:

  • Get more training examples.
  • Use a simple predictor.
  • Select a subsample of features.

In this blog post, we focus on the second and third ways to avoid overfitting by introducing regularization on the parameters βi of the model.

Read the whole thing.

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Tidygraph

Published 2017-07-07 by Kevin Feasel

Thomas Lin Pedersen announces tidygraph, a tidyverse library for dealing with graphs and trees in R:

One of the simplest concepts when computing graph based values is that of
centrality, i.e. how central is a node or edge in the graph. As this
definition is inherently vague, a lot of different centrality scores exists that
all treat the concept of central a bit different. One of the famous ones is
the pagerank algorithm that was powering Google Search in the beginning.
tidygraph currently has 11 different centrality measures and all of these are
prefixed with centrality_* for easy discoverability. All of them returns a
numeric vector matching the nodes (or edges in the case of
centrality_edge_betweenness()).

This is a big project and is definitely interesting if you’re looking at analyzing graph data.

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R’s iGraph + SQL Server Graphs

Published 2017-07-07 by Kevin Feasel

Dennes Torres has a post which shows how to use R’s iGraph library to visualize graphs created in SQL Server 2017:

The possibility to use both technologies together is very interesting. Using graph objects we can store relationships between elements, for example, relationships between forum members. Using R scripts we can build a cluster graph from the stored graph information, illustrating the relationships in the graph.

The script below creates a database for our example with a subset of the objects used in my article and a few more relationship records between the forum members.

Click through for the script.

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