As computation continues to move into the cloud, the computing platform of interest no longer resembles a pizza box or a refrigerator, but a warehouse full of computers. These new large datacenters are quite different from traditional hosting facilities of earlier times and cannot be viewed simply as a collection of co-located servers. Large portions of the hardware and software resources in these facilities must work in concert to efficiently deliver good levels of Internet service performance, something that can only be achieved by a holistic approach to their design and deployment. In other words, we must treat the datacenter itself as one massive warehouse-scale computer (WSe. We describe the architecture of WSCs, the main factors influencing their design, operation, and cost structure, and the characteristics of their software base. We hope it will be useful to architects and programmers of today's WSCs, as well as those of future many-core platforms which may one day implement the equivalent of today's WSCs on a single board. Table of Contents: Introduction / Workloads and Software Infrastructure / Hardware Building Blocks / Datacenter Basics / Energy and Power Efficiency / Modeling Costs / Dealing with Failures and Repairs / Closing Remarks

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment.
Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility.
Understand Cassandra’s distributed and decentralized structure
Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell
Create a working data model and compare it with an equivalent relational model
Develop sample applications using client drivers for languages including Java, Python, and Node.js
Explore cluster topology and learn how nodes exchange data

PostGIS in Action, Third Edition teaches you to solve real-world geodata problems. It first gives you a background in vector-, raster-, and topology-based GIS and then quickly moves into analyzing, viewing, and mapping data. You'll learn how to optimize queries for maximum speed, simplify geometries for greater efficiency, and create custom functions for your own applications. You'll also learn how to apply your existing GIS knowledge to PostGIS and integrate with other GIS tools. Fully updated to the latest versions of PostGIS and PostgreSQL, this Third Edition covers new PostGIS features including Foreign Data Wrappers, Database as a Service, parallelization of queries, and new JSON and Vector Tiles functions that help in creating web mapping applications.
what's inside
An introduction to spatial databases
Geometry, geography, raster, and topology spatial types, functions, and queries
Applying PostGIS to real-world problems
Extending PostGIS to web and desktop applications
Updated for PostGIS 3 and PostgreSQL 12

Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. The book focuses on using SQL to find the story your data tells, with the popular open-source database PostgreSQL and the pgAdmin interface as its primary tools.
You’ll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from the U.S. Census and other federal and state government agencies. With exercises and real-world examples in each chapter, this book will teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently.
You’ll learn how to:
Create databases and related tables using your own data
Define the right data types for your information
Aggregate, sort, and filter data to find patterns
Use basic math and advanced statistical functions
Identify errors in data and clean them up
Import and export data using delimited text files
Write queries for geographic information systems (GIS)
Create advanced queries and automate tasks
Learning SQL doesn’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases.
This book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.

Learn dbatools in a Month of Lunches is a practical hands-on guide to automating SQL Server with PowerShell and the awesome dbatools module. You’ll master techniques you can immediately put into practice, from daily duties like backups and restores right through to performing security audits. Stabilize and standardize your SQL server environment, and simplify your tasks by building automation, alerting, and reporting with this powerful tool. Each lesson delivers another skill that you can use to speed through your core tasks as a SQL Server DBA!
what's inside
Installing dbatools in secure environments
Bulk-import any type of data into SQL Server
Instance-to-instance and customized migrations
Schedule and monitor PowerShell tasks in SQL Server Agent

Create database designs that scale, meet business requirements, and inherently work toward keeping your data structured and usable in the face of changing business models and software systems.
This book is about database design theory. Design theory is the scientific foundation for database design, just as the relational model is the scientific foundation for database technology in general. Databases lie at the heart of so much of what we do in the computing world that negative impacts of poor design can be extraordinarily widespread.
This second edition includes greatly expanded coverage of exotic and little understood normal forms such as: essential tuple normal form (ETNF), redundancy free normal form (RFNF), superkey normal form (SKNF), sixth normal form (6NF), and domain key normal form (DKNF). Also included are new appendixes, including one that provides an in-depth look into the crucial notion of data consistency. Sequencing of topics has been improved, and many explanations and examples have been rewritten and clarified based upon the author’s teaching of the content in instructor-led courses.
This book aims to be different from other books on design by bridging the gap between the theory of design and the practice of design. The book explains theory in a way that practitioners should be able to understand, and it explains why that theory is of considerable practical importance. Reading this book provides you with an important theoretical grounding on which to do the practical work of database design. Reading the book also helps you in going to and understanding the more academic texts as you build your base of knowledge and expertise. Anyone with a professional interest in database design can benefit from using this book as a stepping-stone toward a more rigorous design approach and more lasting database models.
What You Will Learn
Understand what design theory is and is not
Be aware of the two different goals of normalization
Know which normal forms are truly significant
Apply design theory in practice
Be familiar with techniques for dealing with redundancy
Understand what consistency is and why it is crucially important

This textbook examines database systems from the viewpoint of a software developer. This perspective makes it possible to investigate why database systems are the way they are. It is of course important to be able to write queries, but it is equally important to know how they are processed. We e.g. don’t want to just use JDBC; we also want to know why the API contains the classes and methods that it does. We need a sense of how hard is it to write a disk cache or logging facility. And what exactly is a database driver, anyway?
The first two chapters provide a brief overview of database systems and their use. Chapter 1 discusses the purpose and features of a database system and introduces the Derby and SimpleDB systems. Chapter 2 explains how to write a database application using Java. It presents the basics of JDBC, which is the fundamental API for Java programs that interact with a database. In turn, Chapters 3-11 examine the internals of a typical database engine. Each chapter covers a different database component, starting with the lowest level of abstraction (the disk and file manager) and ending with the highest (the JDBC client interface); further, the respective chapter explains the main issues concerning the component, and considers possible design decisions. As a result, the reader can see exactly what services each component provides and how it interacts with the other components in the system. By the end of this part, s/he will have witnessed the gradual development of a simple but completely functional system. The remaining four chapters then focus on efficient query processing, and focus on the sophisticated techniques and algorithms that can replace the simple design choices described earlier. Topics include indexing, sorting, intelligent buffer usage, and query optimization.
This text is intended for upper-level undergraduate or beginning graduate courses in Computer Science. It assumes that the reader is comfortable with basic Java programming; advanced Java concepts (such as RMI and JDBC) are fully explained in the text. The respective chapters are complemented by “end-of-chapter readings” that discuss interesting ideas and research directions that went unmentioned in the text, and provide references to relevant web pages, research articles, reference manuals, and books. Conceptual and programming exercises are also included at the end of each chapter. Students can apply their conceptual knowledge by examining the SimpleDB (a simple but fully functional database system created by the author and provided online) code and modifying it.

Data sets in large applications are often too massive to fit completely inside the computer's internal memory. The resulting input/output communication (or I/O) between fast internal memory and slower external memory (such as disks) can be a major performance bottleneck. Algorithms and Data Structures for External Memory surveys the state of the art in the design and analysis of external memory (or EM) algorithms and data structures, where the goal is to exploit locality and parallelism in order to reduce the I/O costs. A variety of EM paradigms are considered for solving batched and online problems efficiently in external memory. Algorithms and Data Structures for External Memory describes several useful paradigms for the design and implementation of efficient EM algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing. Algorithms and Data Structures for External Memory is an invaluable reference for anybody interested in, or conducting research in the design, analysis, and implementation of algorithms and data structures.

本书是《SQL基础教程》作者MICK为志在向中级进阶的数据库工程师编写的一本SQL技能提升指南。全书可分为两部分，第一部分介绍了SQL语言不同寻常的使用技巧，带领读者从SQL常见技术，比如CASE表达式、自连接、HAVING子句、外连接、关联子查询、EXISTS……去探索新发现。这部分不仅穿插讲解了这些技巧背后的逻辑和相关知识，而且辅以丰富的示例程序，旨在帮助读者提升编程水平；第二部分着重介绍关系数据库的发展史，把实践与理论结合起来，旨在帮助读者加深对关系数据库和SQL语言的理解。此外，每节末尾均设置有练习题，并在书末提供了解答，方便读者检验自己对书中知识点的掌握程度。

本书是畅销书《SQL基础教程》第2版，介绍了关系数据库以及用来操作关系数据库的SQL语言的使用方法。书中通过丰富的图示、大量示例程序和详实的操作步骤说明，让读者循序渐进地掌握SQL的基础知识和使用技巧，切实提高编程能力。每章结尾设置有练习题，帮助读者检验对各章内容的理解程度。另外，本书还将重要知识点总结为“法则”，方便读者随时查阅。第2版除了将示例程序更新为对应新版本的DB的SQL之外，还新增了一章，介绍如何从应用程序执行SQL。

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment.
Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility.
Understand Cassandra’s distributed and decentralized structure
Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell
Create a working data model and compare it with an equivalent relational model
Develop sample applications using client drivers for languages including Java, Python, and Node.js
Explore cluster topology and learn how nodes exchange data

Each chapter in this book helps you identify, explain, and correct a unique and dangerous antipattern. The four parts of the book group the antipatterns in terms of logical database design, physical database design, queries, and application development.
The chances are good that your application's database layer already contains problems such as Index Shotgun , Keyless Entry , Fear of the Unknown , and Spaghetti Query . This book will help you and your team find them. Even better, it will also show you how to fix them, and how to avoid these and other problems in the future.
SQL Antipatterns gives you a rare glimpse into an SQL expert's playbook. Now you can stamp out these common database errors once and for all.
Whatever platform or programming language you use, whether you're a junior programmer or a Ph.D., SQL Antipatterns will show you how to design and build databases, how to write better database queries, and how to integrate SQL programming with your application like an expert. You'll also learn the best and most current technology for full-text search, how to design code that is resistant to SQL injection attacks, and other techniques for success.

试读本书、获取示例源码请访问本书读者服务网站： RedisGuide.com
本书系统化介绍Redis命令及其应用场景，内容深入，图文并茂，巨细靡遗，是掌握Redis的案头必备参考书。
本书主要分为三大部分，共20章。
第一部分“数据结构与应用”介绍Redis最核心的九种数据结构，列举了操作这些数据结构的众多命令及其详细信息，并在其中穿插介绍了多 个使用 Redis 命令构建应用序的示例。通过这些程序示例，读者可以进一步加深对命令的认识，并学会如何在实际中应用这些命令，从而达到学而致用的目的。
第二部分“附加功能”介绍Redis在数据结构的基础上为用户提供的额外功能。其中包括数据库管理、自动过期功能、流水线与事务、Lua 脚本、持久化、发布与订阅、模块管理等。读者可以通过阅读这一部分来学会如何将 Redis 应用在更多场景中。
第三部分“多机功能”介绍 Redis 的三项多机功能：复制、Sentinel 和集群。读者可以通过阅读这一部分来获得扩展 Redis 读写性能的相关知识，并根据自己的情况为 Redis 系统选择合适的扩展方式。

There are many benefits to becoming a data-driven organization, including the ability to accelerate and improve business decision accuracy through the real-time processing of transactions, social media streams, and IoT data. But those benefits require significant changes to your infrastructure. You need flexible architectures that can copy data to analytics platforms at near-zero latency while maintaining 100% production uptime. Fortunately, a solution already exists.
This ebook demonstrates how change data capture (CDC) can meet the scalability, efficiency, real-time, and zero-impact requirements of modern data architectures. Kevin Petrie, Itamar Ankorion, and Dan Potter—technology marketing leaders at Attunity—explain how CDC enables faster and more accurate decisions based on current data and reduces or eliminates full reloads that disrupt production and efficiency.
The book examines:
How CDC evolved from a niche feature of database replication software to a critical data architecture building block
Architectures where data workflow and analysis take place, and their integration points with CDC
How CDC identifies and captures source data updates to assist high-speed replication to one or more targets
Case studies on cloud-based streaming and streaming to a data lake and related architectures
Guiding principles for effectively implementing CDC in cloud, data lake, and streaming environments
The Attunity Replicate platform for efficiently loading data across all major database, data warehouse, cloud, streaming, and Hadoop platforms

Redis 是互联网技术架构在存储系统中使用得最为广泛的中间件，也是中高级后端工程师技术面试中面试官最喜欢问的工程技能之一，特别是那些优秀的互联网公司，通常要求面试者不仅仅掌握 Redis 基础用法，还要理解 Redis 内部实现的细节原理。《Redis 深度历险：核心原理与应用实践》作者老钱在使用 Redis 上积累了丰富的实战经验，希望帮助更多后端开发者更快、更深入地掌握 Redis 技能。
《Redis 深度历险：核心原理与应用实践》分为基础和应用篇、原理篇、集群篇、拓展篇、源码篇共 5 大块内容。基础和应用篇讲解对读者来说最有价值的内容，可以直接应用到实际工作中；原理篇、集群篇让开发者透过简单的技术表面看到精致的底层世界；拓展篇帮助读者拓展技术视野和夯实基础，便于进阶学习；源码篇让高阶的读者能够读懂源码，掌握核心技术实力。
《Redis 深度历险：核心原理与应用实践》适合以下人群阅读：有 Redis 基础，渴望深度掌握 Redis 技术原理的中高级后端开发者；渴望成功进入大型互联网企业研发部的中高级后端开发者；需要支撑公司 Redis 中间件运维工作的初中级运维工程师；对 Redis 中间件技术好奇的中高级前端技术研究者。

The latest edition of a popular text and reference on database research, with substantial new material and revision; covers classical literature and recent hot topics.
Lessons from database research have been applied in academic fields ranging from bioinformatics to next-generation Internet architecture and in industrial uses including Web-based e-commerce and search engines. The core ideas in the field have become increasingly influential. This text provides both students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area―the basic material for any DBMS professional. This fourth edition has been substantially updated and revised, with 21 of the 48 papers new to the edition, four of them published for the first time. Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system. The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems.

Database System Concepts by Silberschatz, Korth and Sudarshan is now in its 7th edition and is one of the cornerstone texts of database education. It presents the fundamental concepts of database management in an intuitive manner geared toward allowing students to begin working with databases as quickly as possible.
The text is designed for a first course in databases at the junior/senior undergraduate level or the first year graduate level. It also contains additional material that can be used as supplements or as introductory material for an advanced course. Because the authors present concepts as intuitive descriptions, a familiarity with basic data structures, computer organization, and a high-level programming language are the only prerequisites. Important theoretical results are covered, but formal proofs are omitted. In place of proofs, figures and examples are used to suggest why a result is true.

Perform fast interactive SQL analytics against different data sources using the Presto distributed SQL query engine. With this practical book, you’ll learn how to conduct analytics on data where it lives, including Hive, Cassandra, relational databases, and proprietary data stores. Matt Fuller from Starburst Data and Presto cocreator Martin Traverso show analysts how to manage, use, and even develop with Presto.
Initially developed by Facebook, open source Presto is now used by Netflix, Airbnb, LinkedIn, Twitter, Uber, and many other companies. You’ll learn how a single Presto query can combine data from multiple sources to allow for analytics across your entire organization.
This book will help you:
Get started using Presto
Explore Presto architectural concepts
Learn best practices and tuning
Use Presto with various business intelligence and SQL analytical tools
Query data from different data sources, including query federation
Learn how to use Presto on Amazon Web Services, Microsoft Azure, and Google Cloud Platform

A high-performance data access layer must resonate with the underlying database system. Knowing the inner workings of a relational database and the data access frameworks in use can make the difference between a high-performance enterprise application and one that barely crawls.
This book is a journey into Java data access performance tuning. From connection management, to batch updates, fetch sizes and concurrency control mechanisms, it unravels the inner workings of the most common Java data access frameworks.
The first part aims to reduce the gap between application developers and database administrators. For this reason, it covers both JDBC and the database fundamentals that are of paramount importance when reducing transaction response times. In this first part, you'll learn about connection management, batch updates, statement caching, result set fetching and database transactions.
The second part demonstrates how you can take advantage of JPA and Hibernate without compromising application performance. In this second part, you'll learn about the most efficient Hibernate mappings (basic types, associations, inheritance), fetching best practices, caching and concurrency control mechanisms.
The third part is dedicated to jOOQ and its powerful type-safe querying capabilities, like window functions, common table expressions, upsert, stored procedures and database functions.

Graph Databases in Action teaches you everything you need to know to begin building and running applications powered by graph databases. Right off the bat, seasoned graph database experts and authors Dave Bechberger and Josh Perryman introduce you to just enough graph theory, the graph database ecosystem, and a variety of datastores. You’ll also explore modelling basics in action with real-world examples, then go hands-on with querying, coding traversals, parsing results, and other essential tasks as you build your own graph-backed social network app complete with a recommendation engine!
With valuable firsthand experience under your belt, you’re ready for advanced concepts including query tuning, data model tuning, evolving your graphs, and pitfalls and anti-patterns like supernodes, hidden entities, and anemic edges. All examples are presented in the open source Apache TinkerPop framework and the Gremlin language, and almost all concepts and constructs are compatible with Cypher/openCypher databases such as Neo4j. With this comprehensive guide, you’ll be building graph-powered applications that dramatically increase the value of data—as well as your professional value to the companies savvy enough to use them!
what's inside
Graph database fundamentals
An overview of the graph database ecosystem
Relational vs. graph database modelling
Querying graphs using Gremlin
Real-world common graph use cases
Basic graph algorithms
A hands-on graph-backed application project
Performance tuning
Pitfalls and anti-patterns
Graph analytics