Javier Luraschi

Javier is the author of “Mastering Spark with R”, pins, sparklyr, mlflow and torch. He holds a double degree in Math and Software Engineer and decades of industry experience with a focus on data analysis. Javier is currently working on a project of his own; and previously worked in RStudio, Microsoft Research and SAP.


Using pins with Python and JavaScript

rstudio::global 2021

Using pins with Python and JavaScript

January 21, 2021

Last year, pins got released as a brand new R package to pin, discover and cache remote resources for R users.

Datasets in Reproducible Research with 'pins'

rstudio::conf 2020

Datasets in Reproducible Research with 'pins'

February 4, 2020

Open source code is an essential piece in making science reproducible. Tools like 'rmarkdown' and GitHub facilitate running and sharing outcomes with colleagues and with the broad scientific community

Scaling R with Spark

rstudio::conf 2019

Scaling R with Spark

January 25, 2019

This talk introduces new features in sparklyr that enable real-time data processing, brand new modeling extensions and significant performance improvements.

Part 3 - Advanced features of sparklyr

Webinars

Part 3 - Advanced features of sparklyr

August 23, 2017

sparklyr facilitates a connection between R and Spark using a full-fledged dplyr backend with support for the entirety of Spark’s MLlib library.

Part 2 - Extending Spark using sparklyr

Webinars

Part 2 - Extending Spark using sparklyr

August 17, 2017

sparklyr facilitates a connection between R and Spark using a full-fledged dplyr backend with support for the entirety of Spark’s MLlib library.