Understand Hadoop and Apache Spark

Imagine a company that runs a very popular online platform. Every day, millions of users visit the website, make purchases, click on products, and generate application logs. All these activities produce a very large amount of data . After some time, the company collects terabytes of data . This data includes customer transactions, website clicks, machine logs, and system events. Now the company wants to analyze this data to answer questions like: Which products are selling the most? What time do customers visit the website? Are there any system errors? How can the company improve its services? At first, the company tries to process the data using one computer , but the data is too large. The computer becomes slow and cannot process the data efficiently. To solve this problem, the company decides to use a distributed system , where many machines work together to store and process the data. This is where Hadoop and Apache Spark come into the picture. Hadoop: Storing and Processing Large