Big Data and Hadoop-Learn by Example

It includes research work of various topics, theoretical and practical approach, each component of the architecture is described along with current industry trends.
Big Data and Hadoop taken together are a new skill as per the industry standards. Readers will get a compact book along with the industry experience, and would be a reference to help readers.

KEY FEATURES
Overview Of Big Data | Basics of Hadoop | Hadoop Distributed File System | HBase, MapReduce | HIVE: The Data-ware House Of Hadoop | PIG: The Higher Level Programming Environment | SQOOP: Importing Data From Heterogeneous Sources | Flume, Ozzie, Zookeeper & Big Data Stream Mining.

CONTENTS
Chapter 1: Big Data- Introduction and Demand
Chapter 2: No SQL Data Management
Chapter 3: Basics of Hadoop
Chapter 4: Hadoop Installation (Step-by-Step)
Chapter 5: MapReduce Applications
Chapter 6: Hadoop Related Tools-I (Hbase & Cassandra)
Chapter 7: Hadoop Related Tools -II (PigLatin & HiveQL)
Chapter 8: Practical & Research based Topics
Appendix: Hadoop Commands
Chapter wise Questions
Previous Year Question Paper