BITS Embryo conducted a talk by Hemath Yamijala on 15th Oct as part of ATMOS’16. The talk had a huge turnout. Hemanth Yamijala is a data engineer and principal consultant on BigData Projects with an extensive industry experience which includes companies like AdNear, Thought-Works and Yahoo!. He is also a contributor, committer and a project lead of Hadoop MapReduce, Hadoop on Demand and the first version of the Capacity Scheduler, which is one of the main schedulers in Hadoop. As a principle Engineer at HortonWorks, Mr.Hemanth works on the development and support of Apache Hadoop. His talk was primarily focused on BigData, large scale Distributed systems and frameworks for the same.
In the current situation where data plays a huge role in everyday life, they come to the rescue by providing solutions to the data management problems. There are basically two ways, scale up and scale out which help with this. But scale out is most often preferred as it is more cost efficient and can scale to internet volumes. Scale up is restricted to a point, it can’t expand beyond a certain point. Though the main difference is that they make bigger servers in scale up while they just add more servers in scale out. Here he quoted Grace Hopper, “If one ox could not do the job they did not try to grow a bigger ox, but used two oxen. When we need greater computer power, the answer is not to get a bigger computer, but to build systems of computers and operate them in parallel.” He then proceeded on to explain the different ways we can increase the efficiency of a system.
Mr. Hemanth gave us a valuable insight into how a company like Hortonworks, Inc. works. This company was actually founded in 2011 from the Yahoo! Hadoop team. It became the first and only publicly listed Hadoop company in India. Also it was the fastest to reach 100million revenue. The company is fast growing and now has branches in over 16 countries with 1000+ employees. All the students were enthusiastic and had a great many doubts to ask. Unfortunately, due to some time constraints the talk had to end. All in all, the talk left the students understand the importance of Hadoop and the amount of data being put to use on a daily basis.