MungingData

Mill is a SBT alternative that can be used to build Spark projects. This post explains how to create a Spark project with Mill and why you might want to […]

Spark DataFrame columns support arrays, which are great for data sets that have an arbitrary length. This blog post will demonstrate Spark methods that return ArrayType columns, describe how to […]

SBT is an interactive build tool that is used to run tests and package your projects as JAR files. SBT lets you create a project in a text editor and […]

Spark DataFrames schemas are defined as a collection of typed columns. The entire schema is stored as a StructType and individual columns are stored as StructFields. This blog post explains […]

Spark has a variety of aggregate functions to group, cube, and rollup DataFrames. This post will explain how to use aggregate functions with Spark. groupBy() Let’s create a DataFrame with […]

The Spark Column class defines a variety of column methods that are vital for manipulating DataFrames. This blog post demonstrates how to instantiate Column objects and covers the commonly used […]

This book will teach you how to be a proficient Apache Spark programmer with minimal effort. Other books focus on the theoretical underpinnings of Spark. This book skips the theory […]

Spark Datasets / DataFrames are filled with null values and you should write code that gracefully handles these null values. You don’t want to write code that thows NullPointerExceptions – […]

Spark supports DateType and TimestampType columns and defines a rich API of functions to make working with dates and times easy. This blog post will demonstrates how to make DataFrames […]