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
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