Publications by tomaztsql

Eight R Tidyverse tips for everyday data engineering

14.07.2022

Tidyverse is a collection of R packages, primarily for data engineering and analytics. These packages are ggplot2, purrr, tibble, dplyr, tidyr, stringr, readr, and forcats. And all combine the same language, design and “grammar” structures. Collection of Tidyverse resources. Source: Tidyverse 1. Use pipe “%>%” for nesting functions with...

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A prerelease version of Jupyter Notebooks and unleashing features in JupyterLab

11.03.2022

Jupyter notebook offers also the use of developers or prerelease versions of Jupyter notebooks. Improved Jupyter Notebook outlook What you need to do is simply run: python -m pip install notebook --pre --upgrade And with this prerelease version of the Jupyter notebook, you have in addition several options to enhance your workspace. Besides the ...

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Effect of normalization of data

26.04.2016

Clustering (distributed in particular) can  be dependent on normalization of data. With usage of distance models, data – when clustered – can produce different results or even different clustering models. A simple every day example can produce two different results. For example, measuring units.  For this purpose we will create two R data-f...

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Working folders, logs and sessions for sp_execute_external_script

20.07.2016

When running with R code and sp_execute_external_script it is very handy to know where all the output log files are being generated and what additional information about the session is available and which folders are useful when working with external stored procedure sp_execute_external_script. Session information is stored on your local disk und...

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Data science show at SQL Server Radio

22.07.2016

SQL Server Radio with Matan Yungman (info | twitter| company ) and Guy Glantser (info | twitter | company ) was hosting me for SQL Server radio 52th series. Main topic was discussion on  data science, statistics, who data scientist is and what SQL Server offers with R integration, SSRS, PowerBI, Excel and other tools. 45 minutes of talk and lau...

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Enabling sp_execute_external_script to run R scripts in SQL Server 2016

26.07.2016

SP_EXECUTE_EXTERNAL_SCRIPT is a stored procedure that execute provided script as argument on external script to a provided language (in this case R language). To enable normal function of this external stored procedure, you must have administrator access to your SQL Server instance in order to run sp_configure command (and set following configura...

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Using parameter and multiparameters with sp_execute_external_script

01.08.2016

With RTM version of SQL Server 2016, sp_execute_external_script stored procedure has undergone couple of changes prior to it’s final outlook. The parametrization of this external procedure somehow resembles a typical extended stored procedure. Indeed, sp_execute_external_script is an extended stored procedure written using CLR (whereas stored p...

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Installing R packages in SQL Server using only T-SQL

02.08.2016

Installing R packages in SSMS using T-SQL can take some time, especially when you need to switch between R Tools for Visual Studio or R Studio or your favorite R GUI tool (or R CMD). But so far, installing any additional library using sp_execute_external_script is just not working. --InstallPackage using sp_execute_external_script EXECUTE sp_exec...

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Handling required and missing R packages in Microsoft R Services

11.08.2016

I have seen several time, that execute R code using procedure sp_execute_external_script was not valid due to missing library or library dependencies. Problem is – in general – not solved out of the box. But can be solved using and maintaining a list of installed libraries used by Microsoft R services or by simply create a “pre-code” R co...

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Resource governor and external resource pool for Microsoft R Services

18.08.2016

Setting external resource pool for execution of R commands using sp_execute_external_script has proven extremely useful, especially in cases where you have other workers present, when you don’t want to overdo on data analysis and get to much resources from others (especially when running data analysis in production environment) or when you know...

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