What's in a name might be true for a rose, but perhaps not for Resilient Distributed Datasets (RDD) which, in essence, describes what an RDD is.
They are basically datasets, which are distributed across a cluster (remember the Spark framework is inherently based on an MPP architecture), and provide resilience (automatic failover) by nature.
Before we go into any further detail, let's try to understand this a little bit, and again we are trying to be as abstract as possible. Let us assume that you have a sensor data from aircraft sensors and you want to analyze the data irrespective of its size and locality. For example, an Airbus A350 has roughly 6000 sensors across the entire plane and generates 2.5 TB data per day, while the newer model expected to launch in 2020 will generate roughly 7.5 TB per day. From a data engineering point of view, it might be important to understand the data pipeline, but from an analyst and a data scientist point of view, the major concern is to...
