Book Image

Hadoop Essentials

By : Shiva Achari
Book Image

Hadoop Essentials

By: Shiva Achari

Overview of this book

This book jumps into the world of Hadoop and its tools, to help you learn how to use them effectively to optimize and improve the way you handle Big Data. Starting with the fundamentals Hadoop YARN, MapReduce, HDFS, and other vital elements in the Hadoop ecosystem, you will soon learn many exciting topics such as MapReduce patterns, data management, and real-time data analysis using Hadoop. You will also explore a number of the leading data processing tools including Hive and Pig, and learn how to use Sqoop and Flume, two of the most powerful technologies used for data ingestion. With further guidance on data streaming and real-time analytics with Storm and Spark, Hadoop Essentials is a reliable and relevant resource for anyone who understands the difficulties - and opportunities - presented by Big Data today. With this guide, you'll develop your confidence with Hadoop, and be able to use the knowledge and skills you learn to successfully harness its unparalleled capabilities.
Table of Contents (15 chapters)
Hadoop Essentials
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
3
Pillars of Hadoop – HDFS, MapReduce, and YARN
Index

Summary


In this chapter, you have learned that HBase is a NoSQL, Column-oriented database with flexible schema. It has the following components – MasterServer, RegionServer, and Regions and utilizes Zookeeper to monitor them with two caches – WAL in RegionServers and MemStore in Regions. We also saw how HBase manages the data by performing RegionSplitting and Compaction. HBase provides partition tolerance and much higher consistency levels as compared to availability from the CAP theorem.

The HBase Data Model is different from the traditional RDBMS as data is stored in a column oriented database and in a multidimensional map of key-value pairs. Rows are identified by rowkey and are distributed across clusters using a range of values of rowkey. Rowkey is critical in designing schema for HBase for performance and data management.

In a Hadoop project, data management is a very critical step. In the context of Big Data, Hadoop has the benefit of the data management aspect. But managing it with...