Hadoop for Beginners

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What is Hadoop?

It’s an Apache’s major software project to facilitate distributed data processing across various commodity servers. Apache has it as an open source project, given the wide potential usability. Building up on sole server to a huge set of servers is a real prospect. The optimal degree of fault tolerance is what makes Hadoop stand apart.

Why Hadoop makes it count?

Unarguably Hadoop impacts the economic climate of large scale computing. Dynamics of the clouded computing has been positively influenced by this high calibration software. Let’s look at factors which make you consider Hadoop:

  • Fault tolerance: The architecture helps making it error tolerant. When a node is lost, request is redirecting to another node available for access.
  • Compatibility: Wide variety of data types processed by Hadoop makes it compatible with any sort of storage. Structured or non-structured data from multiple sources can be merged.
  • Better Economical nature: Cost effectiveness is improved in regards to commodity servers. Cost per every gigabyte of storage comes down drastically.
  • High scalability: Given the highest flexibility offered through compatible protocols, new nodes can be added effortlessly making Hadoop system extremely scalable.

Decoding its mojo…

Calibration of this software has been the key to its effectiveness. You are equipped with the finest high level architecture when it comes to Hadoop. It’s complimented really well through other Apache’s projects such as Pig, Hive, and Zookeeper. The two major building blogs to the software architecture is YARN and HDFS. YARN or Yet another Resource Negotiator assigns applications and CPU memory correspondingly. Hadoop Distributed File System plays the role of a file system and hence spans through every node in every Hadoop cluster.

How it all started?

It all started just a decade ago, when Hadoop seemed to be the ultimate solution to yahoo search engine flaws. It has traveled levels up to unveil a new era of general purpose computing. Data based applications enjoys highest level of applicability, thanks largely to Apache’s Hadoop. Every popular website since then has been using Hadoop to work with humongous heap of data generated through user activity. It all had origin from ideas pertaining to provide solutions to creating flawless internet archive in an internet sphere of 700 million web sites.

More Insights on its functioning:

Businesses now have the license to think big when it comes to data storage. Hadoop lets you store files with size larger than your system’s capacity through usage of multiple nodes. Ability to process the data stored has been enhanced through an invented concept called “MapReduce”. MapReduce helps provides for the essential framework to process the heap of data stored.

Common Applications of Hadoop:

Hadoop is often hosted on clouds by top companies to mimic an onsite datacenter. This has been the most cost effective approach involving Hadoop. Elastic Reduce, Microsoft Azure, Amazon E3 are few examples.

Notable users:

Yahoo firstly launched the self-proclaimed largest Hadoop app by 2008. Yahoo subsequently made it an open source Hadoop system in the following year. Facebook had to get their Hadoop system to process their 21 PB data storage in 2010. Hadoop has gained massive popularity since then and studies suggest most fortune 50 companies use Hadoop


Hadoop A Solution to Big Data Analytics