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Spark is one of the most widely-used large-scale data processing engines and runs extremely fast. It is a framework that has tools which that are equally useful for application developers as well as data scientists. SparkR or “R on Spark” in the Spark framework opened the door of Spark data processing capability to the R users.
This book starts with the fundamentals of Spark 2.0 and covers the core data processing framework and API, installation, and application development setup. Then the Spark programming model is introduced through real-world examples followed by the Spark SQL programming with DataFrames. An introduction to SparkR is covered next.Later, we cover the charting and plotting features of Python in conjunction with Spark data processing. After that, we take a look at Spark’s stream processing, machine learning, and graph processing libraries. The last chapter combines all the skills you learned from the preceding chapters to develop a real-world Spark application.
What You Will Learn
Get to know the fundamentals of Spark 2.0 and the Spark programming model using Scala and Python
Know how to use Spark SQL and DataFrames using Scala and Python
Get an introduction to Spark programming using R
Perform Spark data processing, charting, and plotting using Python
Get acquainted with Spark stream processing using Scala and Python
Be introduced to machine learning with Spark using Scala and Python
Get started with with graph processing with Spark using Scala
Develop a complete Spark application