HBase High Performance Cookbook

Exciting projects that will teach you how complex data can be exploited to gain maximum insights

HBase High Performance Cookbook

This ebook is included in a Mapt subscription
Ruchir Choudhry

Exciting projects that will teach you how complex data can be exploited to gain maximum insights
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Book Details

ISBN 139781783983063
Paperback350 pages

Book Description

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

Chapter 1: Configuring HBase
Introduction
Configuring and deploying HBase
Using the filesystem
Administering clusters
Managing clusters
Chapter 2: Loading Data from Various DBs
Introduction
Extracting data from Oracle
Loading data using Oracle Big data connector
Bulk utilities
Using Hive with Apache HBase
Using Sqoop
Chapter 3: Working with Large Distributed Systems Part I
Introduction
Scaling elastically or Auto Scaling with built-in fault tolerance
Auto Scaling HBase using AWS
Works on different VM/physical, cloud hardware
Chapter 4: Working with Large Distributed Systems Part II
Introduction
Read path
Write Path
Snappy
LZO compression
LZ4 compressor
Replication
Chapter 5: Working with Scalable Structure of tables
Introduction
HBase data model part 1
HBase data model part 2
How HBase truly scales on key and schema design
Chapter 6: HBase Clients
Introduction
HBase REST and Java Client
Working with Apache Thrift
Working with Apache Avro
Working with Protocol buffer
Working with Pig and using Shell
Chapter 7: Large-Scale MapReduce
Introduction
Chapter 8: HBase Performance Tuning
Introduction
Working with infrastructure/operating systems
Working with Java virtual machines
Changing the configuration of components
Working with HDFS
Chapter 9: Performing Advanced Tasks on HBase
Machine learning using Hbase
Real-time data analysis using Hbase and Mahout
Full text indexing using Hbase
Chapter 10: Optimizing Hbase for Cloud
Introduction
Configuring Hbase for the Cloud
Connecting to an Hbase cluster using the command line
Backing up and restoring Hbase
Terminating an HBase cluster
Accessing HBase data with hive
Viewing the Hbase user interface
Monitoring HBase with CloudWatch
Monitoring Hbase with Ganglia
Chapter 11: Case Study
Introduction
Configuring Lily Platform
Integrating elastic search with Hbase
Configuring

What You Will Learn

  • Configure HBase from a high performance perspective
  • Grab data from various RDBMS/Flat files into the HBASE systems
  • Understand table design and perform CRUD operations
  • Find out how the communication between the client and server happens in HBase
  • Grasp when to use and avoid MapReduce and how to perform various tasks with it
  • Get to know the concepts of scaling with HBase through practical examples
  • Set up Hbase in the Cloud for a small scale environment
  • Integrate HBase with other tools including ElasticSearch

Authors

Table of Contents

Chapter 1: Configuring HBase
Introduction
Configuring and deploying HBase
Using the filesystem
Administering clusters
Managing clusters
Chapter 2: Loading Data from Various DBs
Introduction
Extracting data from Oracle
Loading data using Oracle Big data connector
Bulk utilities
Using Hive with Apache HBase
Using Sqoop
Chapter 3: Working with Large Distributed Systems Part I
Introduction
Scaling elastically or Auto Scaling with built-in fault tolerance
Auto Scaling HBase using AWS
Works on different VM/physical, cloud hardware
Chapter 4: Working with Large Distributed Systems Part II
Introduction
Read path
Write Path
Snappy
LZO compression
LZ4 compressor
Replication
Chapter 5: Working with Scalable Structure of tables
Introduction
HBase data model part 1
HBase data model part 2
How HBase truly scales on key and schema design
Chapter 6: HBase Clients
Introduction
HBase REST and Java Client
Working with Apache Thrift
Working with Apache Avro
Working with Protocol buffer
Working with Pig and using Shell
Chapter 7: Large-Scale MapReduce
Introduction
Chapter 8: HBase Performance Tuning
Introduction
Working with infrastructure/operating systems
Working with Java virtual machines
Changing the configuration of components
Working with HDFS
Chapter 9: Performing Advanced Tasks on HBase
Machine learning using Hbase
Real-time data analysis using Hbase and Mahout
Full text indexing using Hbase
Chapter 10: Optimizing Hbase for Cloud
Introduction
Configuring Hbase for the Cloud
Connecting to an Hbase cluster using the command line
Backing up and restoring Hbase
Terminating an HBase cluster
Accessing HBase data with hive
Viewing the Hbase user interface
Monitoring HBase with CloudWatch
Monitoring Hbase with Ganglia
Chapter 11: Case Study
Introduction
Configuring Lily Platform
Integrating elastic search with Hbase
Configuring

Book Details

ISBN 139781783983063
Paperback350 pages
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