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

An Overview of HBase


HBase is designed based on a Google white paper, Big Table: A Distributed Storage System for Structured Data and defined as a sparse, distributed, persistent multidimensional sorted map. HBase is a columnar and partition oriented database, but is stored in key value pair of data. I know it's confusing and tricky, so let's look at the terms again in detail.

  • Sparse: HBase is columnar and partition oriented. Usually, a record may have many columns and many of them may have null data, or the values may be repeated. HBase can efficiently and effectively save the space in sparse data.

  • Distributed: Data is stored in multiple nodes, scattered across the cluster.

  • Persistent: Data is written and saved in the cluster.

  • Multidimensional: A row can have multiple versions or timestamps of values.

  • Map: Key-Value Pair links the data structure to store the data.

  • Sorted: The Key in the structure is stored in a sorted order for faster read and write optimization.

The HBase Data Model, as...