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Author: Kevin Feasel

Team Data Science Process Updates

Published 2017-11-02 by Kevin Feasel

David Smith announces updates to the Team Data Science Process:

It’s been over a year since we first introduced introduced the Team Data Science Process (TDSP). The data, technology and practices behind Data Science continue to evolve, and the TDSP has evolved in parallel. Over the past year, several new facets have been added, including:

  • The IDEAR (Interactive Data Exploration, Analysis and Reporting) framework, an open source extension to R and Python designed to standardize the process of data exploration and reporting;

  • Guidance for use of Spark 2.0, including an end-to-end Spark v2.0 walkthrough;

  • Guidance for use of in-database Python with SQL Server, including an end-to-end in-database Python tutorial;

Click through for more changes, as well as links to further resources.

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Python For The DBA: Copying SQL Logins

Published 2017-11-02 by Kevin Feasel

David Fowler has an example of how DBAs can use Python to do something interesting:

There are plenty of times when you might want to copy your SQL logins (including the SID) from one server to another.  Perhaps you’re running an AG and need to make sure that all users exist on all your secondaries with the correct SID, perhaps you’re migrating servers and need all the logins on your new server.  Whatever the reason, there are a number of different ways in which you can do this but they usually require scripting out on one server and then running the script into another server, or of course there’s Powershell.

The below script will use Python to copy all or specified logins from one server to another, including the password and SID.

Click through for the script.  The main use case for a SQL Server DBA to learn Python as a DBA scripting language would be if you run SQL on Linux—I don’t think Powershell on Linux is far enough developed to handle the full range of DBA tasks.  Otherwise, I’d use Powershell and dbatools.

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Stack Shuffle Custom Visual

Published 2017-11-02 by Kevin Feasel

Devin Knight continues his Power BI custom visuals series:

In this module you will learn how to use the Enlighten Stack Shuffle Custom Visual.  The Enlighten Stack Shuffle is helpful when you want to display a Top N set of values.  For example if you want to display your top 5 selling employees this visual can make that very easy.

This looks pretty good on a dashboard, especially if you have a top-heavy data set, where the top few items are by far the most important.

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Sentiment Analysis With Python In SQL Server

Published 2017-11-02 by Kevin Feasel

Nellie Gustafsson has a quick example of sentiment analysis using SQL Server Machine Learning Services:

You don’t have to be a data scientist to use machine learning in SQL Server. You can use pre-trained models available for usage out of the box to do your analysis. The following example shows you how you quickly get started and do text sentiment analysis.

Before starting to use this model, you need to install it. The installation is quick and instructions for installing the model can be found here: How to install the models on SQL Server

Once you have SQL Server installed with Machine Learning Services, enabled external script execution, and installed the pre-trained model, you can execute the following  script to create a stored procedure that uses Python and the microsoftml function get_sentiment with the pre-trained model to determine the probability of positive sentiment of a text:

Click through to read the whole thing.

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SQL Server Operations Studio

Published 2017-11-02 by Kevin Feasel

Rohan Kumar announces a new management interface for SQL Server (among other things):

These new cross-platform capabilities have made SQL Server accessible to users of Windows, Linux and Mac. At PASS Summit, we are excited to provide a sneak peek at Microsoft SQL Operations Studio. In a few weeks, users will be able to download and evaluate this free, light-weight tool for modern database development and operations on Windows, Mac or Linux machines for SQL Server, Azure SQL Database, and Azure SQL Data Warehouse. Increase your productivity with smart T-SQL code snippets and customizable dashboards to monitor and quickly detect performance bottlenecks in your SQL databases on-premises or in Azure. You’ll be able to leverage your favorite command line tools like Bash, PowerShell, sqlcmd, bcp and ssh in the Integrated Terminal window. Users can contribute directly to SQL Operations Studio via pull requests from the GitHub repository.

Steve Stedman comments on it:

This appears to be a new cross platform (Mac, Linux, and Windows) for running queries against SQL Server.

Perhaps this is a replacement for SQL Server Management Studio, or may just a subset of what SSMS does today, however it works cross platform, unlike SSMS.

You won’t be giving up Management Studio anytime soon, but there are some really cool parts of SQL Operations Studio forthcoming.

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Vectorized UDFs For PySpark

Published 2017-11-01 by Kevin Feasel

Li Jin talks about a performance optimization coming in Apache Spark 2.3:

To enable data scientists to leverage the value of big data, Spark added a Python API in version 0.7, with support for user-defined functions. These user-defined functions operate one-row-at-a-time, and thus suffer from high serialization and invocation overhead. As a result, many data pipelines define UDFs in Java and Scala, and then invoke them from Python.

Vectorized UDFs built on top of Apache Arrow bring you the best of both worlds—the ability to define low-overhead, high performance UDFs entirely in Python.

This looks like a good performance improvement coming to PySpark, bringing it closer to Scala/Java performance with respect to UDFs.

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Hive Without Hadoop

Published 2017-11-01 by Kevin Feasel

Anubhav Tarar notes that you can run Hive queries against data even without a Hadoop installation:

Starting with release 0.7, Hive also supports a mode to run map-reduce jobs in local-mode automatically

you just have to do two things first create your warehouse in local system and give the default fs name to local put these properties inside your hive-site.xml

This is a fairly short post; click through to see the changes you’d make to hive-site.xml.

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Text Preprocessing With R

Published 2017-11-01 by Kevin Feasel

Sibanjan Das has started a new series on text mining in R:

Next, we need to preprocess the text to convert it into a format that can be processed for extracting information. It is essential to reduce the size of the feature space before analyzing the text. There are various preprocessing methods that we can use here, such as stop word removal, case folding, stemming, lemmatization, and contraction simplification. However, it is not necessary to apply all of the normalization methods to the text. It depends on the data we retrieve and the kind of analysis to be performed.

The series starts off with a quick description of some preprocessing steps and then building an LDA model to extract key terms from articles.

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Could Not Find Function rxSqlUpdateLibPaths

Published 2017-11-01 by Kevin Feasel

I ran into an error after installing SQL Server 2017:

After installation completed, the DBA enabled SQL Server 2017 Machine Learning Services, but as soon as I tried to run a simple R script, it stalled for about 30 seconds and then I got an error:

Msg 39012, Level 16, State 1, Line 0
Unable to communicate with the runtime for ‘R’ script. Please check the requirements of ‘R’ runtime.
STDERR message(s) from external script:
Error: could not find function “rxSqlUpdateLibPaths”
Execution halted

Click through for the solution.

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String Splitting With Multi-Character Delimiters

Published 2017-11-01 by Kevin Feasel

Derek Colley shows a way of using the STRING_SPLIT function when your delimiter is more than one character:

But what happens if we try to use STRING_SPLIT with a multi-character separator, like this?

SELECT * FROM STRING_SPLIT(@GodawfulString, ‘,,’)

Msg 214, Level 16, State 11, Line 67
Procedure expects parameter ‘separator’ of type ‘nchar(1)/nvarchar(1)’.

Ah.  That’s a no, then.

Click through for the solution.

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