What is the difference between SparkSession, SparkContext HiveContext and SQLContext? In this article, I am going to cover the various entry points for Spark Applications and how these have evolved over the releases made.
In the big data era, Apache Spark is probably one of the most popular technologies as it offers a unified engine for processing enormous amount of data in a reasonable amount of time.
In this article, I am going to cover the various entry points for Spark Applications and how these have evolved over the releases made. Before doing so, it might be useful to go through some basic concepts and terms so that we can then jump more easily to the entry points namely SparkSession, SparkContext or SQLContext.
A Spark Application consists of a Driver Program and a group of Executors on the cluster. The Driver is a process that executes the main program of your Spark application and creates the SparkContext that coordinates the execution of jobs (more on this later). *The executors are processes running on the worker nodes of the cluster which are responsible for executing the *tasks the driver process has assigned to them.
The cluster manager (such as Mesos or YARN) is responsible for the allocation of physical resources to Spark Applications.
To make the most out of the benefits of offshore software development, you should understand the crucial factors that affect offshore development.
In this article, see the role of big data in healthcare and look at the new healthcare dynamics. Big Data is creating a revolution in healthcare, providing better outcomes while eliminating fraud and abuse, which contributes to a large percentage of healthcare costs.
‘Data is the new science. Big Data holds the key answers’ - Pat Gelsinger The biggest advantage that the enhancement of modern technology has brought
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