If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems.
Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users.
- Analyze, explore, transform, and visualize data in Apache Spark with R
- Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows
- Perform analysis and modeling across many machines using distributed computing techniques
- Use large-scale data from multiple sources and different formats with ease from within Spark
- Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale
- Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions