2.5 quintillion bytes of data are produced every day. With that kind of data, new technologies are needed to analyze and perform analytics and machine learning. Big datacan’t ideally fit into the disk storage or even the memory of one computer, so, in such scenarios, you’d have to look at distributed computing. This involves spreading the processing of such data to multiple computers. The biggest challenge of dealing with that kind of data is the lack of big data analysis expertise (because of the newness), storing the data, as well as analyzing and querying the data. In this article, we will look at a technology that solves these problems.
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In this tutorial, we'll learn Big Data Analytics in Spark. Exploring Dataframes, Datasets, RDDs, and Google Colab.