Hadoop: Data Processing and Modelling

Hadoop: Data Processing and ModellingReviews
Author: Garry Turkington, Tanmay Deshpande, Sandeep Karanth
Pub Date: 2016
ISBN: 978-1787125162
Pages: 979
Language: English
Format: PDF/EPUB/AZW3
Size: 32 Mb

Download

Unlock the power of your data with Hadoop 2.X ecosystem and its data warehousing techniques across large data sets
As Marc Andreessen has said “Data is eating the world,” which can be witnessed today being the age of Big Data, businesses are producing data in huge volumes every day and this rise in tide of data need to be organized and analyzed in a more secured way. With proper and effective use of Hadoop, you can build new-improved models, and based on that you will be able to make the right decisions.
The first module, Hadoop beginners Guide will walk you through on understanding Hadoop with very detailed instructions and how to go about using it. Commands are explained using sections called “What just happened” for more clarity and understanding.
The second module, Hadoop Real World Solutions Cookbook, 2nd edition, is an essential tutorial to effectively implement a big data warehouse in your business, where you get detailed practices on the latest technologies such as YARN and Spark.
Big data has become a key basis of competition and the new waves of productivity growth. Hence, once you get familiar with the basics and implement the end-to-end big data use cases, you will start exploring the third module, Mastering Hadoop.
So, now the question is if you need to broaden your Hadoop skill set to the next level after you nail the basics and the advance concepts, then this course is indispensable.
When you finish this course, you will be able to tackle the real-world scenarios and become a big data expert using the tools and the knowledge based on the various step-by-step tutorials and recipes.
What You Will Learn

  • Best practices for setup and configuration of Hadoop clusters, tailoring the system to the problem at hand
  • Integration with relational databases, using Hive for SQL queries and Sqoop for data transfer
  • Installing and maintaining Hadoop 2.X cluster and its ecosystem
  • Advanced Data Analysis using the Hive, Pig, and Map Reduce programs
  • Machine learning principles with libraries such as Mahout and Batch and Stream data processing using Apache Spark
  • Understand the changes involved in the process in the move from Hadoop 1.0 to Hadoop 2.0
  • Dive into YARN and Storm and use YARN to integrate Storm with Hadoop
  • Deploy Hadoop on Amazon Elastic MapReduce and Discover HDFS replacements and learn about HDFS Federation