Scaling Data Science with Spark and R

Dive into the seamless integration of Apache Spark with R using Qubole’s infrastructure in our webinar hosted by Javier Luraschi from RStudio. Learn how Sparklyr brings the power of Apache Spark to the R community, enabling sophisticated data analysis and machine learning at scale without the need to master Spark’s complexity.

What You’ll Learn:

RStudio and Sparklyr Introduction:
- Discover the origins of RStudio and its mission to support the R community.
- Introduction to Sparklyr, a package that enables R users to leverage Apache Spark efficiently.
Data Science Fundamentals:
- Explore the definition and importance of data science, highlighting R’s role as a programming language designed specifically for statistical computing and graphics.
The Power of Sparklyr:
- Learn how Sparklyr simplifies the process of using Apache Spark from R, allowing you to run your R code at scale on Spark without significant changes.
Integration with Qubole:
- See how Qubole’s infrastructure supports Sparklyr and RStudio for easy, scalable data analysis in the cloud.
Sparklyr in Action:
- Watch a live demonstration of using Sparklyr in RStudio, including connecting to a Spark cluster, analyzing data, and performing machine learning.
Advancements in Sparklyr:
- Stay updated on the latest Sparklyr updates and features, including support for Spark 3.0, Apache Arrow, and new machine learning capabilities.
Rich Ecosystem and Community:
- Discover the vibrant ecosystem around Sparklyr, with extensions for graph processing, time series analysis, and more.
Resources for Learning and Growth:
- Gain access to valuable resources for mastering Sparklyr, including the O’Reilly book “Mastering Spark with R” and the Sparklyr AI website.

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