Versioning R Code In SQL Server

Steph Locke shows how to combine R models and SQL Server temporal tables for versioning:

If we’re storing our R model objects in SQL Server then we can utilise another SQL Server capability, temporal tables, to take the pain out of versioning and make it super simple.

Temporal tables will track changes automatically so you would overwrite the previous model with the new one and it would keep a copy of the old one automagically in a history table. You get to always use the latest version via the main table but you can then write temporal queries to extract any version of the model that’s ever been implemented. Super neat!

I do exactly this.  In my case, it’s to give me the ability to review those models after the fact once I know whether they generated good outcomes or not.

Related Posts

Using wrapr For A Consistent Pipe With ggplot2

John Mount shows how you can use the wrapr pipe to perform data processing and building a ggplot2 visual: Now we can run a single pipeline that combines data processing steps and ggplot plot construction. data.frame(x = 1:20) %.>% mutate(., y = cos(3*x)) %.>% ggplot(., aes(x = x, y = y)) %.>% geom_point() %.>% geom_line() %.>% ggtitle("piped ggplot2") Check […]

Read More

Using R To Hit Azure ML From Power BI

Leila Etaati shows how you can use R to hit an Azure ML endpoint to populate a data set in Power BI: You need to create a model in Azure ML Studio and create a web service for it. The traditional example in Predict a passenger on Titanic ship is going to survived or not? […]

Read More

Categories