Book Image

HBase High Performance Cookbook

By : Ruchir Choudhry
Book Image

HBase High Performance Cookbook

By: Ruchir Choudhry

Overview of this book

Apache HBase is a non-relational NoSQL database management system that runs on top of HDFS. It is an open source, disturbed, versioned, column-oriented store and is written in Java to provide random real-time access to big Data. We’ll start off by ensuring you have a solid understanding the basics of HBase, followed by giving you a thorough explanation of architecting a HBase cluster as per our project specifications. Next, we will explore the scalable structure of tables and we will be able to communicate with the HBase client. After this, we’ll show you the intricacies of MapReduce and the art of performance tuning with HBase. Following this, we’ll explain the concepts pertaining to scaling with HBase. Finally, you will get an understanding of how to integrate HBase with other tools such as ElasticSearch. By the end of this book, you will have learned enough to exploit HBase for boost system performance.
Table of Contents (19 chapters)
HBase High Performance Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
7
Large-Scale MapReduce
Index

Machine learning using Hbase


Before we dive deep into the details of Hbase/Hadoop, Mahout, and machine learning, it's vital to discuss and highlight some important concepts, which will be used in this chapter.

Data science—in software engineering terms—is an operation of a set of programs that churns a large quantity of data to evaluate supervised or unsupervised learning models and provides a valuable tool to data scientists or systems through which decisions can be made.

The most important aspect is applying programming/algorithms that provide a cleaner dataset on which the next program can be synthesized. This also allows us to look at different patterns that can change as the size of data grows. Thus, it's important to use some form of machine learning that can adapt as the size of data grows exponentially.

There are various use cases that can be solved with different types of machine learning techniques:

  • Supervised learning

  • Unsupervised learning

  • Recommender system

  • Model efficacy

The use of...