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An Overview Of Hadoop And Its Applications

Defining Hadoop –

Hadoop or Apache Hadoop is a free Java based programming that helps in processing large amounts of data sets in a distributed computing environment. Hadoop as a software program renders the distributed processing of large, semi-structured and unstructured data sets across a cluster of servers. It is programmed to enhance up one server to cut across a number of machines with higher fault tolerance levels.

Origins or history of Hadoop 

The history of Hadoop dates to the time when Google File System Paper was published in 2003 that further led to another research paper from Google–Map Reduce Simplified Data Processing on large clusters. However, serious development on Hadoop started with Apache Nutch Project in 2006 when Doug Cutting – the creator of Lucene and Nutch both open source search technology projects extended Lucene into the realm of extremely large search problems by creating open source Hadoop framework. The logo of Hadoop is named after his son’s toy elephant.

Hadoop is now part of Apache project that is sponsored and managed by the Apache Software Foundation. Hadoop 0.1.0 was first released in April – 2006 and still continues to evolve with the help of many contributors under the Apache Hadoop Project. The latest version of Hadoop is 2.6.4 was released in February 2016. Hadoop is a part of big data technology having vast potential in helping businesses and governments in running businesses and bureaucracy. The present Apache Hadoop ecosystem consists of Hadoop kernel, Map Reduce, the Hadoop distributed file system (HDFS) and other related projects such as Apache Hive, HBase, and Zookeeper.

Users of Hadoop –

Google, IBM, Yahoo with the latter (Yahoo) having launched the largest Hadoop production application in 2008 run on Linux servers and claimed to be the biggest one on this planet. Facebook in 2010, claimed to have the largest Hadoop cluster in the world with 21 PB storage that increased to 100 PB in 2012 and the data is growing by half a PB per day. As of now, more than half of the 50 Fortune companies are using Hadoop that can be deployed in a traditional onsite data center and even in the cloud. 

 Advantages of Hadoop –

Hadoop’s advantage is in its power to process large amounts of unstructured, semi-structured data where time is not a constraint for businesses that includes running end of the day reports to review daily transactions or in scanning historical data that dates back to several years.

The other advantage of Hadoop is that it is designed to be robust so that Big Data applications continue to run even when individual servers or clusters fail and it does not require the applications to shuttle huge volumes of data across the network. Hadoop is modular that means that the programmers/developers can swap out almost any of its components for a different software tool. Finally, it can be said that it is a powerful tool supporting useful analytical functions with the number of companies offering commercial implementation or support for Hadoop.

As more and more organizations are starting to adopt Hadoop, there is a huge demand for professionals with knowledge of Hadoop. Tek Classes provides Big Data Hadoop training through CloudEra Certified trainer having more 10+ years of industry experience. The training is comprised of Business Use Cases and lot of hands on sessions.

Tek Classes provides Big Data Hadoop Training for beginners & experienced for more information & free demo contact us.

 

June 14, 2017

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