We live in an era driven by data; an infinite volume of data is outgrowing the processing and storage capabilities of today’s computers. Also the data formats are getting diversified into more complex forms.

This eventually leads up to questions like

  •   How to store these huge amounts of data in less volume of memory?
  •   How to segment the various forms of data?
  •   How these vast data points can be analyzed?

Hadoop is the key to resolve all these challenges. Hadoop gets its name from a funny story by the publisher of a related theory paper which you can Google to know more. Hadoop is a complete eco-system of open source projects (OSP) which provides the frameworks to deal with big data.

What exactly is Hadoop?

It is basically a framework composed of

  •  Distributed computation tier using programming of MapReduce
  •  HDFS which stands for Hadoop Distributed File System
  •  Master Node/NameNode which controls the processing
  •  Cluster-Low cost commodity servers connected together
  •  Data Nodes to store and process the data

How Scala goes with Hadoop?

Scala adds perspective and accessibility to Hadoop. There are myriad reasons to craft a Hadoop framework using Scala. Compared to the traditional Java, Scala is much more secure and scalable. In addition to this, it is more concise, flexible and is composed of a straightforward syntax. This enhances the performance and allows for a much quicker implementation. You get excellent XML support, seamless integration with existing Java codes and it is much easier to solve the concurrent issues that arise

How Hadoop with Scala works?

  •  Many machines are inter-connected in a cluster work simultaneously for fast crunching of data
  •  Data is bucketed into small blocks of 64MB/128MB and stored on a minimum of three machines at a time to ensure data availability and reliability
  •  If any one of the machines fail, the work would be assigned to a working machine automatically
  •  MapReduce breaks down complex tasks into smaller chunks to be processed in parallel

Big data- Where does blockchain fit in?

With all the buzz surrounding blockchain technology which in recent times have been fueled by the rise of Bitcoin. It has made data analysts reconsider the possibility of Blockchain implementation with big data. Hadoop being and important element in Big data can be integrated with the blockchain structures and functionalities to enhance the user experience.

With the blockchain one would imbibe the qualities such as decentralization, shared control, audit traits, immutability, and native exchanges or assets. In the big data environment blockchain is highly scalable by building over the best distributed databases like MongoDB. This paves to uncover the potential for high and interesting applications in big data, providing the possibility for a universal data exchange.