Two RDD transformation is to create a new dataset by using two datasets. There are only a few functions to support this transformation. So let’s take a look. Read more

The purpose of map function is to build a new collection by applying a function to all elements of this concurrent map. Let’s explore with more examples. Read more

flatMap is a frequently used combinator that combines mapping and flattening. flatMap takes a function that works on the nested lists and then concatenates the results back together. It can be very confusing at first. Let’s break it down with more examples. Read more

RDD transformation is to create a new dataset from an existing one. For example, map is a transformation that passes each dataset element through a function and returns a new RDD representing the results. Let’s look at more examples. Read more

Official Definition: Folds the elements of this mutable indexed sequence using the specified associative binary operator. Let’s dive deep into this using examples. Read more