The "HBase Administration Cookbook" is your hands-on guide to mastering HBase administration and configuration. Through practical recipes, this book covers the essential tasks like setting up clusters, optimizing performance, and integrating with the Hadoop ecosystem to manage vast amounts of data effectively. What this Book will help me do Set up and administer HBase clusters for scalability and high availability. Perform routine HBase management tasks confidently and efficiently. Optimize HBase and Hadoop ecosystem settings for maximum performance. Understand troubleshooting to address and resolve typical HBase issues. Leverage advanced configurations for specific read/write-heavy use cases. Author(s) Yifeng Jiang is a seasoned software engineer and database expert with deep experience in working with distributed databases like HBase. He is passionate about teaching and conveying complex concepts through approachable explanations and actionable steps. Yifeng's writing style reflects his hands-on expertise and focus on practical application. Who is it for? This book is designed for system administrators, database managers, and developers looking to master HBase administration and configuration. Whether you are relatively new to HBase with basic familiarity with Hadoop or are an experienced Hadoop administrator wanting to enhance your database management skills, this book provides valuable insights and thorough guidance.

The need to handle increasingly larger data volumes is one factor driving the adoption of a new class of nonrelational “NoSQL” databases. Advocates of NoSQL databases claim they can be used to build systems that are more performant, scale better, and are easier to program. NoSQL Distilled is a concise but thorough introduction to this rapidly emerging technology. Pramod J. Sadalage and Martin Fowler explain how NoSQL databases work and the ways that they may be a superior alternative to a traditional RDBMS. The authors provide a fast-paced guide to the concepts you need to know in order to evaluate whether NoSQL databases are right for your needs and, if so, which technologies you should explore further. The first part of the book concentrates on core concepts, including schemaless data models, aggregates, new distribution models, the CAP theorem, and map-reduce. In the second part, the authors explore architectural and design issues associated with implementing NoSQL. They also present realistic use cases that demonstrate NoSQL databases at work and feature representative examples using Riak, MongoDB, Cassandra, and Neo4j. In addition, by drawing on Pramod Sadalage’s pioneering work, NoSQL Distilled shows how to implement evolutionary design with schema migration: an essential technique for applying NoSQL databases. The book concludes by describing how NoSQL is ushering in a new age of Polyglot Persistence, where multiple data-storage worlds coexist, and architects can choose the technology best optimized for each type of data access.

Starting with the core architecture and structure of Couchbase Server, this title will tell you everything you need to know to install and setup your first Couchbase cluster. You'll be given guidance on sizing your cluster so that you maximise your performance. After installation, you'll be shown how to use the admin web console to administer your server, and then learn the techniques behind the specific tasks behind cluster management. This includes adding and removing nodes, rebalancing, and backing up and restoring your cluster.

Data is getting bigger and more complex by the day, and so are the choices in handling that data. As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once. Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs. What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

CouchDB is a new breed of database for the Internet, geared to meet the needs of today’s dynamic web applications. With this concise introduction, you’ll learn how CouchDB’s simple model for storing, processing, and accessing data makes it ideal for the type of data and rapid response users now demand from your applications—and how easy CouchDB is to set up, deploy, maintain, and scale. The code-packed examples in this book will help you learn how to work with documents, populate a simple database, replicate data from one database to another, and a host of other tasks. Install CouchDB on Linux, Mac OS X, Windows, or (if you must) from the source code Interact with data through CouchDB’s RESTful API, and use standard HTTP operations, such as PUT, GET, POST, and DELETE Use Futon—CouchDB’s web-based interface— to manage databases and documents, and to configure replications Learn how to create, update, and delete documents in JSON format, and how to create and delete databases Work with design documents to get the formatting and indexing your application requires

What would happen if you optimized a data store for the operations application developers actually use? You’d arrive at MongoDB, the reliable document-oriented database. With this concise guide, you’ll learn how to build elegant database applications with MongoDB and PHP. Written by the Chief Solutions Architect at 10gen—the company that develops and supports this open source database—this book takes you through MongoDB basics such as queries, read-write operations, and administration, and then dives into MapReduce, sharding, and other advanced topics. Get out of the relational database rut, and take advantage of a high-performing system optimized for operations and scale. Learn step-by-step the tools you need to build PHP applications with MongoDB Perform Create, Read, Update, and Delete (CRUD) operations, and learn how to perform queries to retrieve data Administer your database, and access and manipulate data with the MongoDB Shell Use functions to work with sets, arrays, and multiple documents to perform synchronous, asynchronous, and atomic operations Discover PHP’s community tools and libraries, and why they’re valuable Work with regular expressions, aggregation, MapReduce, replication, and sharding

NEWER EDITION AVAILABLE MongoDB in Action, Second Edition is now available. An eBook of this older edition is included at no additional cost when you buy the revised edition! A limited number of pBook copies of this edition are still available. Please contact Manning Support to inquire about purchasing previous edition copies. MongoDB in Action is a comprehensive guide to MongoDB for application developers. The book begins by explaining what makes MongoDB unique and describing its ideal use cases. A series of tutorials designed for MongoDB mastery then leads into detailed examples for leveraging MongoDB in e-commerce, social networking, analytics, and other common applications. About the Technology Big data can mean big headaches. MongoDB is a document-oriented database designed to be flexible, scalable, and very fast, even with big data loads. It's built for high availability, supports rich, dynamic schemas, and lets you easily distribute data across multiple servers. About the Book MongoDB in Action introduces you to MongoDB and the document-oriented database model. This perfectly paced book provides both the big picture you'll need as a developer and enough low-level detail to satisfy a system engineer. Numerous examples will help you develop confidence in the crucial area of data modeling. You'll also love the deep explanations of each feature, including replication, auto-sharding, and deployment. What's Inside Indexes, queries, and standard DB operations Map-reduce for custom aggregations and reporting Schema design patterns Deploying for scale and high availability About the Reader Written for developers. No MongoDB or NoSQL experience required. About the Author Kyle Banker is a software engineer at 10gen where he maintains the official MongoDB drivers for Ruby and C. Quotes Awesome! MongoDB in a nutshell. - Hardy Ferentschik, Red Hat Excellent. Many practical examples. - Curtis Miller, Flatterline Not only the how, but also the why. - Philip Hallstrom, PJKH, LLC Has a developer-centric flavor--an excellent reference. - Rick Wagner, Red Hat A must-read. - Daniel Bretoi, Advanced Energy

Learn how to leverage MongoDB with your Python applications, using the hands-on recipes in this book. You get complete code samples for tasks such as making fast geo queries for location-based apps, efficiently indexing your user documents for social-graph lookups, and many other scenarios. This guide explains the basics of the document-oriented database and shows you how to set up a Python environment with it. Learn how to read and write to MongoDB, apply idiomatic MongoDB and Python patterns, and use the database with several popular Python web frameworks. You’ll discover how to model your data, write effective queries, and avoid concurrency problems such as race conditions and deadlocks. The recipes will help you: Read, write, count, and sort documents in a MongoDB collection Learn how to use the rich MongoDB query language Maintain data integrity in replicated/distributed MongoDB environments Use embedding to efficiently model your data without joins Code defensively to avoid keyerrors and other bugs Apply atomic operations to update game scores, billing systems, and more with the fast accounting pattern Use MongoDB with the Pylons 1.x, Django, and Pyramid web frameworks

To help you navigate the large number of new data tools available, this guide describes 60 of the most recent innovations, from NoSQL databases and MapReduce approaches to machine learning and visualization tools. Descriptions are based on first-hand experience with these tools in a production environment. This handy glossary also includes a chapter of key terms that help define many of these tool categories: NoSQL Databases—Document-oriented databases using a key/value interface rather than SQL MapReduce—Tools that support distributed computing on large datasets Storage—Technologies for storing data in a distributed way Servers—Ways to rent computing power on remote machines Processing—Tools for extracting valuable information from large datasets Natural Language Processing—Methods for extracting information from human-created text Machine Learning—Tools that automatically perform data analyses, based on results of a one-off analysis Visualization—Applications that present meaningful data graphically Acquisition—Techniques for cleaning up messy public data sources Serialization—Methods to convert data structure or object state into a storable format

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

A hands-on guide to leveraging NoSQL databases NoSQL databases are an efficient and powerful tool for storing and manipulating vast quantities of data. Most NoSQL databases scale well as data grows. In addition, they are often malleable and flexible enough to accommodate semi-structured and sparse data sets. This comprehensive hands-on guide presents fundamental concepts and practical solutions for getting you ready to use NoSQL databases. Expert author Shashank Tiwari begins with a helpful introduction on the subject of NoSQL, explains its characteristics and typical uses, and looks at where it fits in the application stack. Unique insights help you choose which NoSQL solutions are best for solving your specific data storage needs. Professional NoSQL: Demystifies the concepts that relate to NoSQL databases, including column-family oriented stores, key/value databases, and document databases. Delves into installing and configuring a number of NoSQL products and the Hadoop family of products. Explains ways of storing, accessing, and querying data in NoSQL databases through examples that use MongoDB, HBase, Cassandra, Redis, CouchDB, Google App Engine Datastore and more. Looks at architecture and internals. Provides guidelines for optimal usage, performance tuning, and scalable configurations. Presents a number of tools and utilities relating to NoSQL, distributed platforms, and scalable processing, including Hive, Pig, RRDtool, Nagios, and more.

Redis is an open source, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets. This book will provide developers with problem and solutions in our useful cookbook style. This is an example-driven ebook.

Getting started with MongoDB is easy, but once you begin building applications with it, you'll face some complex issues. What are the tradeoffs between normalized and denormalized data? How do you handle replica set failure and failover? This collection of MongoDB tips, tricks, and hacks helps you resolve issues with everything from application design and implementation to data safety and monitoring. You get specific guidance in five topic areas directly from engineers at 10gen, the company that develops and supports this open source database: Application Design Tips: What to keep in mind when designing your schema Implementation Tips: Programming applications against MongoDB Optimization Tips: Speeding up your applications Data Safety Tips: Using replication and journaling to keep data safe—without sacrificing too much performance Administration Tips: How to configure MongoDB and keep it running smoothly

This practical guide offers a short course on scaling CouchDB to meet the capacity needs of your distributed application. Through a series of scenario-based examples, this book lets you explore several methods for creating a system that can accommodate growth and meet expected demand. In the process, you learn about several tools that can help you with replication, load balancing, clustering, and load testing and monitoring. Apply performance tips for tuning your database Replicate data, using Futon and CouchDB’s RESTful interface Distribute CouchDB’s workload through load balancing Learn options for creating a cluster of CouchDB nodes, including BigCouch, Lounge, and Pillow Conduct distributed load testing with Tsung

Learn how to create MapReduce views in CouchDB that let you query the document-oriented database for meaningful data. With this short and concise ebook, you'll get step-by-step instructions and lots of sample code to create and explore several MapReduce views, using an example database you construct.

Create a MongoDB cluster that will to grow to meet the needs of your application. With this short and concise book, you'll get guidelines for setting up and using clusters to store a large volume of data, and learn how to access the data efficiently. In the process, you'll understand how to make your application work with a distributed database system. Scaling MongoDB will help you: Set up a MongoDB cluster through sharding Work with a cluster to query and update data Operate, monitor, and backup your cluster Plan your application to deal with outages By following the advice in this book, you'll be well on your way to building and running an efficient, predictable distributed system using MongoDB.

What could you do with data if scalability wasn't a problem? With this hands-on guide, you'll learn how Apache Cassandra handles hundreds of terabytes of data while remaining highly available across multiple data centers -- capabilities that have attracted Facebook, Twitter, and other data-intensive companies. Cassandra: The Definitive Guide provides the technical details and practical examples you need to assess this database management system and put it to work in a production environment. Author Eben Hewitt demonstrates the advantages of Cassandra's nonrelational design, and pays special attention to data modeling. If you're a developer, DBA, application architect, or manager looking to solve a database scaling issue or future-proof your application, this guide shows you how to harness Cassandra's speed and flexibility. Understand the tenets of Cassandra's column-oriented structure Learn how to write, update, and read Cassandra data Discover how to add or remove nodes from the cluster as your application requires Examine a working application that translates from a relational model to Cassandra's data model Use examples for writing clients in Java, Python, and C# Use the JMX interface to monitor a cluster's usage, memory patterns, and more Tune memory settings, data storage, and caching for better performance

MongoDB, a cross-platform NoSQL database, is the fastest-growing new database in the world. MongoDB provides a rich document orientated structure with dynamic queries that you'll recognize from RDMBS offerings such as MySQL. In other words, this is a book about a NoSQL database that does not require the SQL crowd to re-learn how the database world works! MongoDB has reached 1.0 and already boasts 50,000+ users. The community is strong and vibrant and MongoDB is improving at a fast rate. With scalable and fast databases becoming critical for today's applications, this book shows you how to install, administer and program MongoDB without pretending SQL never existed.

How does MongoDB help you manage a huMONGOus amount of data collected through your web application? With this authoritative introduction, you'll learn the many advantages of using document-oriented databases, and discover why MongoDB is a reliable, high-performance system that allows for almost infinite horizontal scalability. Written by engineers from 10gen, the company that develops and supports this open source database, MongoDB: The Definitive Guide provides guidance for database developers, advanced configuration for system administrators, and an overview of the concepts and use cases for other people on your project. Learn how easy it is to handle data as self-contained JSON-style documents, rather than as records in a relational database. Explore ways that document-oriented storage will work for your project Learn how MongoDB’s schema-free data model handles documents, collections, and multiple databases Execute basic write operations, and create complex queries to find data with any criteria Use indexes, aggregation tools, and other advanced query techniques Learn about monitoring, security and authentication, backup and repair, and more Set up master-slave and automatic failover replication in MongoDB Use sharding to scale MongoDB horizontally, and learn how it impacts applications Get example applications written in Java, PHP, Python, and Ruby

Three of CouchDB's creators show you how to use this document-oriented database as a standalone application framework or with high-volume, distributed applications. With its simple model for storing, processing, and accessing data, CouchDB is ideal for web applications that handle huge amounts of loosely structured data. That alone would stretch the limits of a relational database, yet CouchDB offers an open source solution that's reliable, scales easily, and responds quickly. CouchDB works with self-contained data that has loose or ad-hoc connections. It's a model that fits many real-world items, such as contacts, invoices, and receipts, but you'll discover that this database can easily handle data of any kind. With this book, you'll learn how to work with CouchDB through its RESTful web interface, and become familiar with key features such as simple document CRUD (create, read, update, delete), advanced MapReduce, deployment tuning, and more. Understand the basics of document-oriented storage and manipulation Interact with CouchDB entirely though HTTP using its RESTful interface Model data as self-contained JSON documents Handle evolving data schemas naturally Query and aggregate data in CouchDB using MapReduce views Replicate data between nodes Tune CouchDB for increased performance and reliability