Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. This brief tutorial provides a quick introduction to Big Data, MapReduce algorithm, and Hadoop Distributed File System.
Following is an extensive series of tutorials on developing Big-Data Applications with Hadoop. Since each section includes exercises and exercise solutions, this can also be viewed as a self-paced Hadoop training course. All the slides, source code, exercises, and exercise solutions are free for unrestricted use. Click on a section below to expand its content. The relatively few parts on IDE development and deployment use Eclipse, but of course none of the actual code is Eclipse-specific.
This series of tutorial documents will walk you through many aspects of the Apache Hadoop system. You will be shown how to set up simple and advanced cluster configurations, use the distributed file system, and develop complex Hadoop MapReduce applications. Other related systems are also reviewed.
In this tutorial we will be analyzing geolocation and truck data. We will import this data into HDFS and build derived tables in Hive. Then we will process the data using Pig and Hive. The processed data is then imported into Microsoft Excel where it can be visualized.
HadoopTutorials is a online video tutorial. This blog covers HDFS, Map Reduce, Data Fundamentals and etc.., in detail.
BigData is the latest buzzword in the IT Industry. Apache’s Hadoop is a leading Big Data platform used by IT giants Yahoo, Facebook & Google. 'Big Data' is also a data but with a huge size. 'Big Data' is a term used to describe collection of data that is huge in size and yet growing exponentially with time.In short, such a data is so large and complex that none of the traditional data management tools are able to store it or process it efficiently.
Organizations use Hadoop as a scalable framework for storing and processing massive volumes of data using a distributed computing model. From its roots as an open source Apache project, Hadoop has been tweaked and modified over the years by various users such as Yahoo!, EMC2, Apple, and Facebook4 to manage incredibly huge amounts of digital data that are being created every second. If used correctly, these data can lead to game-changing decisions in business, technology, politics, and everyday life. That’s the reason why data — like gold or diamond — is now being mined, stored, and processed nonstop by well-paid data scientists and other big data professionals.
Essential Knowledge for everyone associated with Big Data & Hadoop for Non-Geeks. This course builds an essential fundamental understanding of Big Data problems and Hadoop as a solution. This course takes you through: Understanding of Big Data problems with easy to understand examples. History and advent of Hadoop right from when Hadoop wasn’t even named Hadoop. What is Hadoop Magic which makes it so unique and powerful.
This is an introductory level course about big data, Hadoop and the Hadoop ecosystem of products. Covered are a big data definition, details about the Hadoop core components, and examples of several common Hadoop use cases: enterprise data hub, large scale log analysis, and building recommendation engines.
This course is intended for people who wants to know what is big data. The course covers what is big data, How hadoop supports concepts of Big Data and how different components like Pig, Hive,MapReduce of hadoop support large sets of data Analytics.
Originally posted on Data Science Central