Redis Essentials is your go-to guide for understanding and mastering Redis, the leading in-memory data structure store. In this book, you will explore the powerful features offered by Redis, such as real-time data processing, highly scalable architectures, and practical implementations for web applications. You'll complete the journey equipped to handle and optimize Redis for your development projects. What this Book will help me do Design analytics applications with advanced data structures like Bitmaps and HyperLogLogs. Scale your application infrastructure using Redis Sentinel, Twemproxy, and Redis Cluster. Develop custom Redis commands and extend its functionality with the Lua scripting language. Implement robust security measures for Redis, including SSL encryption and firewall rules. Master the usage of Redis client libraries in PHP, Python, Node.js, and Ruby for seamless development. Author(s) Maxwell Dayvson da Silva is an experienced software engineer and author with expertise in designing high-performance systems. With a strong focus on practical knowledge and hands-on solutions, Maxwell brings over a decade of experience using Redis to this book. His approachable teaching style ensures learners grasp complex topics easily while emphasizing their practical application to real-world challenges. Who is it for? Redis Essentials is aimed at developers looking to enhance their system's performance and scalability using Redis. Whether you're moderately familiar with key-value stores or new to Redis, this book will provide the explanations and hands-on examples you need. Recommended for developers with experience in data architectures, the book bridges the gap between understanding Redis features and their real-world application. Start here to bring high-performance in-memory data solutions to your projects.

Dive into Redis, and discover how this powerful key-value database can enhance your web and business applications. "Learning Redis" explains the fundamentals of Redis and walks you through the processes of installation, configuration, and hands-on application development. By the end, you will have gained the knowledge to apply Redis in innovative ways to improve scalability and performance. What this Book will help me do Understand and install Redis to start using this NoSQL database efficiently. Master Redis commands and data structures for scalable application designs. Configure and optimize a Redis server setup to enhance performance and manage persistence. Implement solutions using Redis for real-world web application development. Learn best practices for Redis backups, recovery, and fault management to ensure reliability. Author(s) Vinoo Das, a seasoned software engineer with extensive experience in database solutions, wrote this book with a practical approach to learning Redis. Known for his clear explanations, Vinoo deeply understands how to make technical concepts accessible. His professional career spans significant contributions to SQL and NoSQL database development, making him an ideal guide for learning Redis. Who is it for? This book is perfect for SQL developers ready to deepen their expertise by exploring NoSQL databases like Redis. With only basic programming experience required, readers will appreciate the practical approach and the focus on actionable insights. Whether you're looking to build high-performance apps or understand key-value storage systems, this book will meet your needs.

NoSQL was developed to overcome the limitations of relational databases in the largest Web applications at companies such as Google, Yahoo and Facebook. As it is applied more widely, developers are finding that it can simplify scalability while requiring far less coding and management overhead. However, NoSQL requires fundamentally different approaches to database design and modeling, and many conventional relational techniques lead to suboptimal results. NoSQL for Mere Mortals is an easy, practical guide to succeeding with NoSQL in your environment. Following the classic, best-selling format pioneered in SQL Queries for Mere Mortals, enterprise database expert Dan Sullivan guides you step-by-step through choosing technologies, designing high-performance databases, and planning for long-term maintenance. Sullivan introduces each type of NoSQL database, shows how to install and manage them, and demonstrates how to leverage their features while avoiding common mistakes that lead to poor performance and unmet requirements. He uses four popular NoSQL databases as reference models: MongoDB, a document database; Cassandra, a column family data store; Redis, a key-value database; and Neo4j, a graph database. You'll find explanations of each database's structure and capabilities, practical guidelines for choosing amongst them, and expert guidance on designing databases with them. Packed with examples, NoSQL for Mere Mortals is today's best way to master NoSQL—whether you're a DBA, developer, user, or student.

Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets; distributed cloud computing offers the resources to store and analyze them; and professionals have radically new technologies at their command, including NoSQL databases. Until now, however, most books on “Big Data” have been little more than business polemics or product catalogs. is different: It’s a completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist. Data Just Right Michael Manoochehri, a former Google engineer and data hacker, writes for professionals who need practical solutions that can be implemented with limited resources and time. Drawing on his extensive experience, he helps you focus on building applications, rather than infrastructure, because that’s where you can derive the most value. Manoochehri shows how to address each of today’s key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You’ll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. Throughout, the author demonstrates techniques using many of today’s leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery. Coverage includes Mastering the four guiding principles of Big Data success—and avoiding common pitfalls Emphasizing collaboration and avoiding problems with siloed data Hosting and sharing multi-terabyte datasets efficiently and economically “Building for infinity” to support rapid growth Developing a NoSQL Web app with Redis to collect crowd-sourced data Running distributed queries over massive datasets with Hadoop, Hive, and Shark Building a data dashboard with Google BigQuery Exploring large datasets with advanced visualization Implementing efficient pipelines for transforming immense amounts of data Automating complex processing with Apache Pig and the Cascading Java library Applying machine learning to classify, recommend, and predict incoming information Using R to perform statistical analysis on massive datasets Building highly efficient analytics workflows with Python and Pandas Establishing sensible purchasing strategies: when to build, buy, or outsource Previewing emerging trends and convergences in scalable data technologies and the evolving role of the Data Scientist

Redis in Action introduces Redis and walks you through examples that demonstrate how to use it effectively. You'll begin by getting Redis set up properly and then exploring the key-value model. Then, you'll dive into real use cases including simple caching, distributed ad targeting, and more. You'll learn how to scale Redis from small jobs to massive datasets. Experienced developers will appreciate chapters on clustering and internal scripting to make Redis easier to use. About the Technology When you need near-real-time access to a fast-moving data stream, key-value stores like Redis are the way to go. Redis expands on the key-value pattern by accepting a wide variety of data types, including hashes, strings, lists, and other structures. It provides lightning-fast operations on in-memory datasets, and also makes it easy to persist to disk on the fly. Plus, it's free and open source. About the Book What's Inside Redis from the ground up Preprocessing real-time data Managing in-memory datasets Pub/sub and configuration Persisting to disk About the Reader Written for developers familiar with database concepts. No prior exposure to Redis or other NoSQL databases required. Appropriate for systems administrators comfortable with programming. About the Author Dr. Josiah L. Carlson is a seasoned database professional and an active contributor to the Redis community. Quotes A great addition to the Redis ecosystem. - From the Foreword by Salvatore Sanfilippo, Creator of Redis The examples, taken from real-world use cases, are one of the major strengths of the book. - Filippo Pacini, SG Consulting From beginner to expert with real and comprehensive examples. - Felipe Gutierrez, VMware/Spring Source Excellent in-depth analysis ... insightful real-world examples. - Bobby Abraham, Integri LLC Pure gold! - Leo Cassarani, Unboxed Consulting

Cloud services are just as susceptible to network outages as any other platform. This concise book shows you how to prepare for potentially devastating interruptions by building your own resilient and reliable applications in the public cloud. Guided by engineers from 9apps—an independent provider of Amazon Web Services and Eucalyptus cloud solutions—you’ll learn how to combine AWS with open source tools such as PostgreSQL, MongoDB, and Redis. This isn’t a book on theory. With detailed examples, sample scripts, and solid advice, software engineers with operations experience will learn specific techniques that 9apps routinely uses in its cloud infrastructures. Build cloud applications with the "rip, mix, and burn" approach Get a crash course on Amazon Web Services Learn the top ten tips for surviving outages in the cloud Use elasticsearch to build a dependable NoSQL data store Combine AWS and PostgreSQL to build an RDBMS that scales well Create a highly available document database with MongoDB Replica Set and SimpleDB Augment Redis with AWS to provide backup/restore, failover, and monitoring capabilities Work with CloudFront and Route 53 to safeguard global content delivery

Even as big data is turning the world upside down, the next phase of the revolution is already taking shape: real-time data analysis. This hands-on guide introduces you to Storm, a distributed, JVM-based system for processing streaming data. Through simple tutorials, sample Java code, and a complete real-world scenario, you’ll learn how to build fast, fault-tolerant solutions that process results as soon as the data arrives. Discover how easy it is to set up Storm clusters for solving various problems, including continuous data computation, distributed remote procedure calls, and data stream processing. Learn how to program Storm components: spouts for data input and bolts for data transformation Discover how data is exchanged between spouts and bolts in a Storm topology Make spouts fault-tolerant with several commonly used design strategies Explore bolts—their life cycle, strategies for design, and ways to implement them Scale your solution by defining each component’s level of parallelism Study a real-time web analytics system built with Node.js, a Redis server, and a Storm topology Write spouts and bolts with non-JVM languages such as Python, Ruby, and Javascript

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.

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.

Popular social networks such as Facebook and Twitter generate a tremendous amount of valuable data on topics and use patterns. Who's talking to whom? What are they talking about? How often are they talking? This concise and practical book shows you how to answer these questions and more by harvesting and analyzing data using social web APIs, Python, and pragmatic storage technologies such as Redis, CouchDB, and NetworkX. With Mining the Social Web, intermediate to advanced programmers will learn how to harvest and analyze social data in way that lends itself to hacking as well as more industrial-strength analysis. Algorithms are designed with robustness and efficiency in mind so that the approaches scale well on an ordinary piece of commodity hardware. The book is highly readable from cover to cover as content progressively grows in complexity, but also lends itself to being read in an ad-hoc fashion. Use easily adaptable scripts to access popular social network APIs including Twitter, OpenSocial, and Facebook Learn approaches for slicing and dicing social data that's been harvested from social web APIs as well as other common formats such as email and markup formats Harvest data from other sources such as Freebase and other sites to enrich your analytic capabilities with additional context Visualize and analyze data in interactive ways with tools built upon rich UI JavaScript toolkits Get a concise and straightforward synopsis of some practical technologies from the semantic web landscape that you can incorporate into your analysis This book is still in progress, but you can get going on this technology through our Rough Cuts edition, which lets you read the manuscript as it's being written, either online or via PDF.

This IBM Redbooks publication is a practical cookbook that provides up-to-date information about Cluster Systems Management (CSM) for AIX 5L for a pSeries environment. The book provides information about the latest CSM for AIX 5L enhancements, including implementation techniques, installation changes, installation tools, system management tools, monitoring tools, hardware control, file distribution, problem determination, and management server high availability. This book summarizes the latest news in CSM 1.4.0. It contains a Q&A chapter, a CSM installation scenario, a CSM advanced chapter, CSM migration scenarios, and a CSM cluster administration chapter. We include information about how to manage Linux nodes on pSeries hardware including operating system installation and node management in a mixed cluster environment. This book is targeted to technical professionals (consultants, IT architects, and IT specialists) who are responsible for providing pSeries clustering solutions.