Introduction to Apache Hadoop and Apache Spark

Apache Hadoop and Apache Spark are both open-source data processing frameworks that can process and analyze large amounts of data. They are both distributed systems that can scale to process data, and are made up of multiple software modules that work together. However, they have different strengths and weaknesses, and may need to be integrated with other software depending on the use case.

Apache Hadoop: is an open-source software utility that allows users to manage big data sets (from gigabytes to petabytes) by enabling a network of computers (or “nodes”) to solve vast and intricate data problems. It is a highly scalable, cost-effective solution that stores and processes structured, semi-structured and unstructured data (e.g., Internet clickstream records, web server logs, IoT sensor data, etc.).

Benefits of the Hadoop framework include the following:

• Data protection amid a hardware failure
• Vast scalability from a single server to thousands of machines
• Real-time analytics for historical analyses and decision-making processes

The Hadoop ecosystem

Hadoop supports advanced analytics for stored data (e.g., predictive analysis, data mining, machine learning (ML), etc.). It enables big data analytics…