SparklyR
Edgar Ruiz | Databases using R The latest | RStudio (2019)
Learn about the latest packages and techniques that can help you access and analyze data found inside databases using R. Many of the techniques we will cover are based on our personal and the community’s experiences of implementing concepts introduced last year, such as offloading most of the data wrangling to the database using dplyr, and using the RStudio IDE to preview the database’s layout and data. Also, learn more about the most recent improvements to the RStudio products that are geared to aid developers in using R with databases effectively.
VIEW MATERIALS https://github.com/edgararuiz/databases-w-r
About the Author Edgar Ruiz Edgar is the author and administrator of the https://db.rstudio.com web site, and current administrator of the [sparklyr] web site: https://spark.rstudio.com . Author of the Data Science in Spark with sparklyr cheatsheet. Co-author of the dbplyr package and creator of the dbplot package
Javier Luraschi | Scaling R with Spark | RStudio (2019)
This talk introduces new features in sparklyr that enable real-time data processing, brand new modeling extensions and significant performance improvements. The sparklyr package provides an interface to Apache Spark to enable data analysis and modeling in large datsets through familiar packages like dplyr and broom.
VIEW MATERIALS https://github.com/rstudio/rstudio-conf/tree/master/2019/Scaling%20R%20with%20Spark%20-%20Javier%20Luraschi
About the Author Javier Luraschi Javier is a Software Engineer with experience in technologies ranging from desktop, web, mobile and backend; to augmented reality and deep learning applications. He previously worked for Microsoft Research and SAP and holds a double degree in Mathematics and Software Engineering
Understanding Sparklyr Deployment Modes | RStudio Webinar - 2017
This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/webinars/ . We try to host a couple each month with the goal of furthering the R community’s understanding of R and RStudio’s capabilities.
We are always interested in receiving feedback, so please don’t hesitate to comment or reach out with a personal message
Sparklyr: Using Spark with RMarkdown | RStudio Webinar - 2016
This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/web … . We try to host a couple each month with the goal of furthering the R community’s understanding of R and RStudio’s capabilities.
We are always interested in receiving feedback, so please don’t hesitate to comment or reach out with a personal message
Extending Spark Using Sparklyr | RStudio Webinar - 2017
This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/webinars/ . We try to host a couple each month with the goal of furthering the R community’s understanding of R and RStudio’s capabilities.
We are always interested in receiving feedback, so please don’t hesitate to comment or reach out with a personal message
Advanced Features of Sparkyr | RStudio Webinar - 2017
This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/webinars/ . We try to host a couple each month with the goal of furthering the R community’s understanding of R and RStudio’s capabilities.
We are always interested in receiving feedback, so please don’t hesitate to comment or reach out with a personal message
