Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hadoop Blueprints

You're reading from   Hadoop Blueprints Use Hadoop to solve business problems by learning from a rich set of real-life case studies

Arrow left icon
Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781783980307
Length 316 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Sudheesh Narayan Sudheesh Narayan
Author Profile Icon Sudheesh Narayan
Sudheesh Narayan
Tanmay Deshpande Tanmay Deshpande
Author Profile Icon Tanmay Deshpande
Tanmay Deshpande
Anurag Shrivastava Anurag Shrivastava
Author Profile Icon Anurag Shrivastava
Anurag Shrivastava
Arrow right icon
View More author details
Toc

Table of Contents (9) Chapters Close

Preface 1. Hadoop and Big Data 2. A 360-Degree View of the Customer FREE CHAPTER 3. Building a Fraud Detection System 4. Marketing Campaign Planning 5. Churn Detection 6. Analyze Sensor Data Using Hadoop 7. Building a Data Lake 8. Future Directions

Building open source Hadoop

In 2006, Doug Cutting joined Yahoo in a team led by Eric Baldeschweiler (also known as eric14 or e14). This team had grid computing experts and users. Eric was in charge of figuring out how to build a next generation search grid computing framework for web searches. Here is a quote from a Yahoo employee at that time that described the situation prevailing at that time:

"Fortunately, and I remember the day well, Eric14 assembled the merry bunch of Grid (then called 'Utility Computing') engineers, and started down the path of rethinking the strategy - focussing on figuring out how to make Hadoop functional, featureful, and robust, instead." (Kumar, 2011)

The new team split out of Hadoop from Nutch with the leadership of Doug Cutting and created an open source Hadoop Framework based upon Hadoop Distributed File System as its storage system, and the MapReduce paradigm as the parallel computing model. Yahoo put more than 300 person-years of effort into Hadoop projects between 2006 - 2011. A team of nearly 100 people worked upon Apache Hadoop, and related projects such as Pig, ZooKeeper, Hive, HBase and Oozie.

In 2011, Yahoo was running Hadoop on over 40,000 machines (>300 cores). Hadoop has over a thousand regular users who use Hadoop for search-related research, advertising, detection of spam and personalization apart from many other topics. Hadoop has proven itself at Yahoo in many revenue driving improvement projects.

Building open source Hadoop
Figure 1 Timeline of Hadoop evolution

Nowadays, Hadoop is a top-level project at Apache Foundation. Hadoop is a software library that contains programs that allow processing of very large datasets, also known as big data, on a large cluster of commodity servers using a simple programming model known as MapReduce. At the time of writing this book, Hadoop 2.7.1 is the latest stable version.

It should be evident from the history of Hadoop that it was invented to solve the problem of searching and indexing massive data sets in large Internet companies. The purpose of Hadoop was to store and process the information inside Yahoo. Yahoo decided to make Hadoop open source so that the Hadoop project could benefit from the innovative ideas and involvement of the open source community.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at £16.99/month. Cancel anytime