Hadoop

A four part Big Data Series: Part 1: Big Data, GFS and MapReduce – Google’s Historic Contributions Part 2:Hadoop - The Open Source Approach To Big Data Processing You Ought To Know Part 3: MapReduce - The Big Data Crunching Framework Part 4: MapReduce Framework - How Does It Work? We understand that MapReduce eats up the Big Data behemoth one bite at a time- but how does it really take those bites?

A four part Big Data Series: Part 1: Big Data, GFS and MapReduce – Google’s Historic Contributions Part 2:Hadoop - The Open Source Approach To Big Data Processing You Ought To Know Part 3: MapReduce - The Big Data Crunching Framework Part 4:MapReduce Framework - How Does It Work? So how do you eat an elephant? Of course one bite at a time and that is exactly what MapReduce Framework does to the behemoth of Big Data.

A four part Big Data Series: Part 1: Big Data, GFS and MapReduce – Google’s Historic Contributions Part 2: Hadoop - The Open Source Approach To Big Data Processing You Ought To Know Part 3: MapReduce - The Big Data Crunching Framework Part 4: MapReduce Framework - How Does It Work? Imagine yourself around the turn of the century- sometime around 1999-2002. Internet is evolving, Java is hot, XML is roaring and more and more people are joining the formative Internet Atlantic.

A four part Big Data Series: Part 1: Big Data, GFS and MapReduce – Google’s Historic Contributions Part 2:Hadoop - The Open Source Approach To Big Data Processing You Ought To Know Part 3: MapReduce - The Big Data Crunching Framework Part 4: MapReduce Framework - How Does It Work? Big Data is the new buzzword; a name given to the enormous amount of data that is piling up over time at an unprecedented rate- and that rate is increasing explosively.

As a CS freshman I was required to present on an emerging technology of my choice. I chose Big Data Processing Using Hadoop, with the focus being on general understanding of the core rather than technical depth. So here is a four part general write up: Part 1 covers the very fundamentals of Big Data and Google’s milestone contribution towards its processing. Part 2 discusses the development of Hadoop- an open source approach for the processing of Big Data.

Big Data holds the key to wisdom and prudence. With good enough data, one can slice through and glean useful bits of information. With intelligent extrapolation of available data, future can be as clear as the night sky under brightly lit stars. Trends, shape of things to come, tomorrow, a week from now; all can be modeled, predicted and visualized. Many useful and highly prudent insights buried under mountains of data and, therefore, unavailable, can be made to surface through smart queries, resulting in co-relations hitherto un-imagined.