HBase High Performance Cookbook


Book Description

Exciting projects that will teach you how complex data can be exploited to gain maximum insights About This Book Architect a good HBase cluster for a very large distributed system Get to grips with the concepts of performance tuning with HBase A practical guide full of engaging recipes and attractive screenshots to enhance your system's performance Who This Book Is For This book is intended for developers and architects who want to know all about HBase at a hands-on level. This book is also for big data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic scalable database solution in the big data space. 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 In Detail 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. Style and approach This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications. This books also provides examples for C#, Python, and Ruby users.




Hbase Administration Cookbook


Book Description

As part of Packt's cookbook series, each recipe offers a practical, step-by-step solution to common problems found in HBase administration. This book is for HBase administrators, developers, and will even help Hadoop administrators. You are not required to have HBase experience, but are expected to have a basic understanding of Hadoop and MapReduce.




Mastering Apache Hbase


Book Description

Unlock the Power of Scalable and Distributed Data Storage with "Mastering Apache HBase" In the rapidly evolving landscape of data management, the ability to efficiently handle massive amounts of data has become an indispensable skill. "Mastering Apache HBase" serves as your definitive guide to mastering one of the most powerful and flexible distributed NoSQL databases – Apache HBase. Whether you're a seasoned data professional or a newcomer to the world of big data, this book equips you with the knowledge and skills needed to harness the full potential of Apache HBase. About the Book: "Mastering Apache HBase" takes you on a comprehensive journey through the intricacies of this robust and versatile NoSQL database. From the fundamentals of installation and configuration to advanced topics such as performance tuning and integration with other Big Data tools, this book covers it all. Each chapter is meticulously crafted to provide a deep understanding of the concepts along with practical, real-world applications. Key Features: · Solid Foundation: Build a strong understanding by exploring the core concepts of Apache HBase, including its architecture, data model, and storage components. · Efficient Data Management: Learn how to create tables, insert and retrieve data, and implement effective data modeling strategies that maximize performance and flexibility. · Scalability and Distribution: Dive into the distributed nature of Apache HBase and discover techniques to scale your cluster horizontally, ensuring seamless growth as your data needs expand. · Advanced Techniques: Master advanced topics such as data versioning, coprocessors, security, and backup and recovery, enabling you to tackle complex scenarios with confidence. · Performance Optimization: Uncover strategies and best practices for optimizing the performance of your Apache HBase cluster, ensuring your applications run smoothly even at scale. · Integration with Ecosystem: Explore how Apache HBase seamlessly integrates with other Big Data tools like Apache Hadoop, Apache Spark, and Apache Hive, opening up possibilities for data analysis and processing. · Real-World Use Cases: Learn through practical examples and use cases from various industries, including social media, e-commerce, finance, and more, to understand how Apache HBase can solve real-world data challenges. · Expert Insights: Benefit from the experience of seasoned professionals who provide insights, tips, and recommendations garnered from their years of working with Apache HBase. Who This Book Is For: "Mastering Apache HBase" is designed for data engineers, database administrators, and anyone involved in managing and analyzing large volumes of data. Whether you're a developer looking to expand your skillset or an experienced professional aiming to deepen your understanding of distributed data storage, this book is your ultimate resource. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com




Cassandra High Performance Cookbook


Book Description

This is a cookbook and all tasks are approached as recipes. A recipe describes a task and outlines the steps necessary to complete this task. Some recipes in the book are examples of writing code. An example of this is a recipe that stores and accesses the entries of a phone book in Cassandra. The recipe consists of a description of the program, a full code example is given, the example is run, the output is displayed, and finally the how it works section describes the process or code in greater detail. Other recipes in the book describe a task. An example of this is a recipe that takes a snapshot back up of data in Cassandra. This recipe contains a description of the process, it then shows how to run the snapshot command and confirm that it worked, it then explains what the snapshot command does behind the scenes, finally the see also' section references other related recipes such as the recipe to restore a snapshot. This book is designed for administrators, developers, and data architects who are interested in Apache Cassandra for redundant, highly performing, and scalable data storage. Typically these users should have experience working with a database technology, multiple node computer clusters, and high availability solutions.




Learning HBase


Book Description

If you are an administrator or developer who wants to enter the world of Big Data and BigTables and would like to learn about HBase, this is the book for you.




Hadoop MapReduce v2 Cookbook - Second Edition


Book Description

If you are a Big Data enthusiast and wish to use Hadoop v2 to solve your problems, then this book is for you. This book is for Java programmers with little to moderate knowledge of Hadoop MapReduce. This is also a one-stop reference for developers and system admins who want to quickly get up to speed with using Hadoop v2. It would be helpful to have a basic knowledge of software development using Java and a basic working knowledge of Linux.




Seven NoSQL Databases in a Week


Book Description

A beginner's guide to get you up and running with Cassandra, DynamoDB, HBase, InfluxDB, MongoDB, Neo4j, and Redis Key Features Covers the basics of 7 NoSQL databases and how they are used in the enterprises Quick introduction to MongoDB, DynamoDB, Redis, Cassandra, Neo4j, InfluxDB, and HBase Includes effective techniques for database querying and management Book Description This is the golden age of open source NoSQL databases. With enterprises having to work with large amounts of unstructured data and moving away from expensive monolithic architecture, the adoption of NoSQL databases is rapidly increasing. Being familiar with the popular NoSQL databases and knowing how to use them is a must for budding DBAs and developers. This book introduces you to the different types of NoSQL databases and gets you started with seven of the most popular NoSQL databases used by enterprises today. We start off with a brief overview of what NoSQL databases are, followed by an explanation of why and when to use them. The book then covers the seven most popular databases in each of these categories: MongoDB, Amazon DynamoDB, Redis, HBase, Cassandra, InfluxDB, and Neo4j. The book doesn't go into too much detail about each database but teaches you enough to get started with them. By the end of this book, you will have a thorough understanding of the different NoSQL databases and their functionalities, empowering you to select and use the right database according to your needs. What you will learn Understand how MongoDB provides high-performance, high-availability, and automatic scaling Interact with your Neo4j instances via database queries, Python scripts, and Java application code Get familiar with common querying and programming methods to interact with Redis Study the different types of problems Cassandra can solve Work with HBase components to support common operations such as creating tables and reading/writing data Discover data models and work with CRUD operations using DynamoDB Discover what makes InfluxDB a great choice for working with time-series data Who this book is for If you are a budding DBA or a developer who wants to get started with the fundamentals of NoSQL databases, this book is for you. Relational DBAs who want to get insights into the various offerings of popular NoSQL databases will also find this book to be very useful.




Hadoop Essentials


Book Description

If you are a system or application developer interested in learning how to solve practical problems using the Hadoop framework, then this book is ideal for you. This book is also meant for Hadoop professionals who want to find solutions to the different challenges they come across in their Hadoop projects.




HBase Essentials


Book Description

This book is intended for developers and Big Data engineers who want to know all about HBase at a hands-on level. For in-depth understanding, it would be helpful to have a bit of familiarity with HDFS and MapReduce programming concepts with no prior experience with HBase or similar technologies. This book is also for Big Data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic, scalable database solution in the Big Data space.




HBase: The Definitive Guide


Book Description

If you're looking for a scalable storage solution to accommodate a virtually endless amount of data, this book shows you how Apache HBase can fulfill your needs. As the open source implementation of Google's BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Many IT executives are asking pointed questions about HBase. This book provides meaningful answers, whether you’re evaluating this non-relational database or planning to put it into practice right away. Discover how tight integration with Hadoop makes scalability with HBase easier Distribute large datasets across an inexpensive cluster of commodity servers Access HBase with native Java clients, or with gateway servers providing REST, Avro, or Thrift APIs Get details on HBase’s architecture, including the storage format, write-ahead log, background processes, and more Integrate HBase with Hadoop's MapReduce framework for massively parallelized data processing jobs Learn how to tune clusters, design schemas, copy tables, import bulk data, decommission nodes, and many other tasks