A whirlwind tour of the R language was covered in this chapter, followed by a special mention about the need to have a distinction of understanding the difference between an R DataFrame and a Spark DataFrame. Then, basic Spark programming with R was covered using the same use cases of the previous chapters. R API for Spark was covered, and the use cases have been implemented using the SQL query way and DataFrame API way. This chapter helps data scientists understand the power of Spark and use it in their R applications, using the SparkR package that comes with Spark. This opens up the door of big data processing, using Spark with R to process structured data.
The subject of Spark-based data processing in various languages has been discussed, and it is time to focus on some data analysis with charting and plotting. Python comes with a lot of charting and plotting libraries that produce publication quality pictures. The next chapter will discuss charting and plotting with the data processed...