Fundamentals of Hadoop

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Hadoop has revolutionized the management of large data sets also known as Big Data. As datasets grow in size, complexities escalate. Hadoop is designed to solve big data problems that relational databases such as SQL Server, My SQL and Oracle can’t. It is being used by several big tech giants such as Yahoo, Facebook, Microsoft, and IBM to name just a few. In this article, we outline the fundamentals of Hadoop and how you can benefit from it.

What is Hadoop?

Fundamentals of Hadoop have to start with what Hadoop really is. But before we jump into it, it is important to note here that Hadoop is not a database in itself, but an alternative file system called Hadoop File System (HDFS) that has a processing library. So, when you bring Hadoop onboard, keep in mind that it will be an addition to your existing RDBMS and not a replacement for it.

Moving on to what Hadoop is. Apache Hadoop is an ecosystem of open source software framework that is used for running applications and storing data. Its biggest advantage is that it allows for the distributed processing of large datasets across clusters of computers. It can be scaled up from single servers to several thousand machines, each with its own computation and storage capabilities. Failures are detected and handled at the application layer of the library eliminating the need to rely on hardware.

Despite the magnitude of its scale, Hadoop makes use of simple programming models. Virtually any software can be plugged into it to use for data visualization. Hadoop has also gained popularity for its power for processing large amounts of semi-structured and unstructured data. However, it’s important to keep in mind that its strength lies in handling big data sets that are in petabytes or terabytes and is not recommended for smaller data sets that are in MBs or GBs.

What does Hadoop do?

Apache Hadoop is a versatile software and can be used for several use cases. It makes use of behavioral data to enable better decision making. Some examples of how Hadoop can be used are; for product recommendations, fraud detection, risk analysis, infrastructure management, identifying diseases, online travel management, energy savings, sentiment analysis, etc.

Hadoop can be applied to diverse markets from retail, to service, manufacturing to financial, insurance, social media, healthcare and any industry that deals with massive amounts of data for decision making.

Benefits of Hadoop

So, it all comes down to the benefits that Hadoop offers to your business and some are listed below.

  1. Cost effective: Being an open source program and procedure, it is free for anyone to use or modify for the most part.
  2. Easy to use: With Hadoop you can just feed the data and it works. No preliminary preparation or data manipulation is required to leverage your data.
  3. Flexible: Data comes from a variety of different sources and can be unstructured and in any format. Luckily, Hadoop is capable of seamlessly processing all formats of data.
  4. Scalable: Hadoop scales data organically, using low-cost hardware so you can keep on adding more and more data clusters.
  5. Speed: Hadoop is designed to process data at high speed, actually very high speed.
  6. Reliable: When/if failure happens, Hadoop automatically replicates data for you by re-directing it to other nodes making it extremely reliable.


As is evident through these fundamentals of Hadoop, this Java-based programming framework’s flexible nature allows organizations to expand and adjust their data analysis operations as their business grows. Hadoop makes big data analysis possible. Effective Hadoop implementation requires a good understanding of the unique business environment it is being installed in.

It’s important to get the right start especially when dealing with large data sets in order to avoid pitfalls of poor implementation. Make sure to partner with a consultant that has expertise in Hadoop and can make your transition seamless. Cyber Chasse professionals are Hadoop trained with a wealth of experience in successful implementation and can be contacted here.