What Is Hadoop?

Apache Hadoop is an open-source software framework created in 2005, specifically engineered for creating and supporting big data and large scale processing applications – something that a traditional software isn’t able to do.

The whole Hadoop framework relies on 4 main modules that work together:

  1. Hadoop Common is like the SDK for the whole Hadoop framework, providing the necessary libraries and utilities needed by the other 3 modules.
  2. Hadoop Distributed Files System (HDFS) is the file system that stores all of the data at high bandwidth, in clusters (think RAID).
  3. Hadoop Yarn is the module that manages the computational resources, again in clusters, for application scheduling.
  4. Finally, Hadoop Mapreduce is the programming model for creating the large scale and big data applications.


  • With the onset of huge mobile subscriptions and the prolific usage of the social media globally, there is a deluge of data in all forms, meaning structured, semi-structured and unstructured.
  • Traditional storage that houses the relational data has given way to concurrent distributed data processing.
  • Hadoop framework comes with a columnar structure and stores the data and metadata across nodes.
  • The data is replicated across so that any failed node instance is taken care automatically.
  • Hadoop platform is ideal for building statistical and forecasting models using machine learning and AI.

What Shasta has Done

  • We are using Hadoop framework that allows for distributed processing for large datasets across clusters of computers.
  • We are handling 10 cluster computing for Hadoop file system.
  • Primary name node can store only the meta data of HDFS - the directory trees of all files and track the files across the cluster.
  • Secondary NameNode in Hadoop is a specially dedicated node in HDFS cluster whose main function is to take checkpoints of the file system metadata present on Name Node. we are storing the data in the remaining 8 clusters.
  • Map Reduce will do the parallel processing of large data sets and YARN will do cluster resource Management and job scheduling. We are storing a large volume of structured, semi-structured and unstructured data in the Hadoop file system. HDFS replicates the data across multiple nodes to increase the throughput.

We’re Professionals To Grow Your Business!

Data are becoming the new raw material of business. Shasta is ready to answer your questions and get a complete understanding of your needs – to receive a customized demo, Fill out the form.

Follow us on