Hadoop and Big data the popular story

Big data basically is a unstructured data. We can not process it traditional methods. The volume, velocity, and variety of big data will bring most technologies to their knees.

Hadoop was developed because it represented the most pragmatic way to allow companies to manage huge volumes of data easily.

Hadoop was originally built by a Yahoo! engineer named Doug Cutting and is now an open source project managedby the Apache Software Foundation.

Hadoop and Big data

Hadoop is the framework developed by Apache to solve big data problems:

  • Hadoop Distributed File System: A reliable, high-bandwidth, low-cost, data storage cluster that facilitates the management of related files across machines.
  • MapReduce engine: A high-performance parallel/distributed data-processing implementation of the MapReduce algorithm

Hadoop is designed to process huge amounts of structured and unstructured data (terabytes to petabytes) and is implemented on racks of commodity servers as a Hadoop cluster.

Read my post on eco system.

Related articles

Author: Srini

Experienced Data Engineer, having skills in PySpark, Databricks, Python SQL, AWS, Linux, and Mainframe