My BARUG rquery talk went very well, thank you very much to the attendees for being an attentive and generous audience.
(John teaching rquery at BARUG, photo credit: Timothy Liu)
I am now looking for invitations to give a streamlined version of this talk privately to groups using R who want to work with SQL (with databases such as PostgreSQL or big data systems such as Apache Spark). rquery has a number of features that greatly improve team productivity in this environment (strong separation of concerns, strong error checking, high usability, specific debugging features, and high performance queries).
If your group is in the San Francisco Bay Area and using R to work with a SQL accessible data source, please reach out to me at jmount@win-vector.com, I would be honored to show your team how to speed up their project and lower development costs with rquery. If you are a big data vendor and some of your clients use R, I am especially interested in getting in touch: our system can help R users start working with your installation.
Categories: Administrativia Opinion
jmount
Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.
How does the speed compare to RMySQL + dbConnect?
I haven’t tried it on MySQL yet (not a database a current client is using, though some in the past have used it). But this is a system that sits on top of
DBI::dbConnect()and specific databases, so its speed is the speed of those systems.