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As users come to depend on MySQL, they find that they have to deal with issues of reliability, scalability, and performance--issues that are not well documented but are critical to a smoothly functioning site. This book is an insider's guide to these little understood topics. Author Jeremy Zawodny has managed large numbers of MySQL servers for mission-critical work at Yahoo!, maintained years of contacts with the MySQL AB team, and presents regularly at conferences. Jeremy and Derek have spent months experimenting, interviewing major users of MySQL, talking to MySQL AB, benchmarking, and writing some of their own tools in order to produce the information in this book. In High Performance MySQL you will learn about MySQL indexing and optimization in depth so you can make better use of these key features. You will learn practical replication, backup, and load-balancing strategies with information that goes beyond available tools to discuss their effects in real-life environments. And you'll learn the supporting techniques you need to carry out these tasks, including advanced configuration, benchmarking, and investigating logs. Topics include: * A review of configuration and setup options * Storage engines and table types * Benchmarking * Indexes * Query Optimization * Application Design * Server Performance * Replication * Load-balancing * Backup and Recovery * Security
This paper is behind a registration-wall, you can't do anything on the MySQL site without filling out a form of some kind, but it's a short, decent introduction to using MySQL for a good sized website.
Eventually every database system hit its limits. Especially on the Internet, where you have millions of users which theoretically access your database simultaneously, eventually your IO system will be a bottleneck. [A] promising but more complex solution with nearly no scale-out limits is application partitioning. If and when you get into the top-1000 rank on alexa [1], you have to think about such solutions.
If the clustered file system, clustered storage system, storage virtualization movement is new to you then this is a good intro paper. I's a both vendor puff piece and informative, so it might be worth your time.
Follow this blog and you'll learn a lot about MySQL and how to make it sing.
Replication Under Scalable Hashing: A Family of Algorithms for Scalable Decentralized Data Distribution Typical algorithms for decentralized data distribution work best in a system that is fully built before it first used; adding or removing components results in either extensive reorganization of data or load imbalance in the system. We have developed a family of decentralized algorithms, RUSH (Replication Under Scalable Hashing), that maps replicated objects to a scalable collection of storage servers or disks. RUSH algorithms distribute objects to servers according to user-specified server weighting. While all RUSH variants support addition of servers to the system, different variants have different characteristics with respect to lookup time in petabyte-scale systems, performance with mirroring (as opposed to redundancy codes), and storage server removal. All RUSH variants redistribute as few objects as possible when new servers are added or existing servers are removed, and all variants guarantee that no two replicas of a particular object are ever placed on the same server. Because there is no central directory, clients can compute data locations in parallel, allowing thousands of clients to access objects on thousands of servers simultaneously.
Web Analytics: An Hour A Day is the first book by an in-the-trenches practitioner of web analytics. It provides a unique insider’s perspective of the challenges and opportunities that web analytics presents to each person who touches the Web in your organization. Rather than spamming you with metrics and definitions, Web Analytics: An Hour A Day will enhance your mindset and teach you how to fish for yourself. Avinash Kaushik is a expert in web analytics and author of the top-rated blog Occam’s Razor (http://www.kaushik.net/avinash). In this book, he goes beyond web analytics concepts and definitions to provide a step-by-step guide to implementing a successful web analytics strategy. His revolutionary approach to web analytics challenges prevalent thinking about the field and guides readers to a solution that will provide truly informed and actionable insights.
Building, scaling, and optimizing the next generation of web applications. Learn the tricks of the trade so you can build and architect applications that scale quickly--without all the high-priced headaches and service-level agreements associated with enterprise app servers and proprietary programming and database products. Culled from the experience of the Flickr.com lead developer, Building Scalable Web Sites offers techniques for creating fast sites that your visitors will find a pleasure to use. Creating popular sites requires much more than fast hardware with lots of memory and hard drive space. It requires thinking about how to grow over time, how to make the same resources accessible to audiences with different expectations, and how to have a team of developers work on a site without creating new problems for visitors and for each other. Presenting information to visitors from all over the world * Integrating email with your web applications * Planning hardware purchases and hosting options to have as much as you need without breaking your wallet * Partitioning and distributing databases to support large datasets and simultaneous transactions * Monitoring your applications to find and clear bottlenecks * Providing services APIs and using services from other providers to increase your site's reach and capabilities Whether you're starting a small web site with hopes of growing big or you already have a large system that needs maintenance, you'll find Building
Author of Web Analytics An Hour of Day. Has a fresh and practical take on unlocking the power of web research and web analytics to create truly data driven organizations for gaining a strategic competitive advantage.