What can you do when database performance doesn't meet expectations? Before you turn to expensive hardware upgrades to solve the problem, reach for this book. Refactoring SQL Applications provides a set of tested options for making code modifications to dramatically improve the way your database applications function. Backed by real-world examples, you'll find quick fixes for simple problems, in-depth answers for more complex situations, and complete solutions for applications with extensive problems. Learn to: Determine if and where you can expect performance gains Apply quick fixes, such as limiting calls to the database in stored functions and procedures Refactor tasks, such as replacing application code by a stored procedure, or replacing iterative, procedural statements with sweeping SQL statements Refactor flow by increasing parallelism and switching business-inducted processing from synchronous to asynchronous Refactor design using schema extensions, regular views, materialized views, partitioning, and more Compare before and after versions of a program to ensure you get the same results once you make modifications Refactoring SQL Applications teaches you to recognize and assess code that needs refactoring, and to understand the crucial link between refactoring and performance. If and when your application bogs down, this book will help you get it back up to speed.

Refactoring has proven its value in a wide range of development projects–helping software professionals improve system designs, maintainability, extensibility, and performance. Now, for the first time, leading agile methodologist Scott Ambler and renowned consultant Pramodkumar Sadalage introduce powerful refactoring techniques specifically designed for database systems. Ambler and Sadalage demonstrate how small changes to table structures, data, stored procedures, and triggers can significantly enhance virtually any database design–without changing semantics. You’ll learn how to evolve database schemas in step with source code–and become far more effective in projects relying on iterative, agile methodologies. This comprehensive guide and reference helps you overcome the practical obstacles to refactoring real-world databases by covering every fundamental concept underlying database refactoring. Using start-to-finish examples, the authors walk you through refactoring simple standalone database applications as well as sophisticated multi-application scenarios. You’ll master every task involved in refactoring database schemas, and discover best practices for deploying refactorings in even the most complex production environments. The second half of this book systematically covers five major categories of database refactorings. You’ll learn how to use refactoring to enhance database structure, data quality, and referential integrity; and how to refactor both architectures and methods. This book provides an extensive set of examples built with Oracle and Java and easily adaptable for other languages, such as C#, C++, or VB.NET, and other databases, such as DB2, SQL Server, MySQL, and Sybase. Using this book’s techniques and examples, you can reduce waste, rework, risk, and cost–and build database systems capable of evolving smoothly, far into the future.

Refactoring is gaining momentum amongst the object oriented programming community. It can transform the internal dynamics of applications and has the capacity to transform bad code into good code. This book offers an introduction to refactoring.

This book will show you how to modernize your page-based, include-oriented PHP application by extracting and replacing its legacy artifacts. We will use a step-by-step approach, moving slowly and methodically, to improve your application from the ground up. Each completed step in the process will keep your codebase fully operational with higher quality. Please note that this book is about modernizing in terms of practice and technique, and not in terms of tools. We are not going to discuss the latest, hottest frameworks or libraries. Most of the very limited code we do add to your application is specific to this book. When we are done, you will be able to breeze through your code like the wind. Your code will be fully modernized: autoloaded, dependency-injected, unit-tested, layer-separated, and front-controlled.

Design and write simple and efficient T-SQL code in SQL Server 2019 and beyond. Writing T-SQL that pulls back correct results can be challenging. This book provides the help you need in writing T-SQL that performs fast and is easy to maintain. You also will learn how to implement version control, testing, and deployment strategies. Hands-on examples show modern T-SQL practices and provide straightforward explanations. Attention is given to selecting the right data types and objects when designing T-SQL solutions. Author Elizabeth Noble teaches you how to improve your T-SQL performance through good design practices that benefit programmers and ultimately the users of the applications. You will know the common pitfalls of writing T-SQL and how to avoid those pitfalls going forward. What You Will LearnChoose correct data types and database objects when designing T-SQL Write T-SQL that searches data efficiently and uses hardware effectively Implement source control and testing methods to streamline the deployment process Design T-SQL that can be enhanced or modified with less effort Plan for long-term data management and storage Who This Book Is For Database developers who want to improve the efficiency of their applications, and developers who want to solve complex query and data problems more easily by writing T-SQL that performs well, brings back correct results, and is easy for other developers to understand and maintain

'NoSQL Distilled' is designed to provide you with enough background on how NoSQL databases work, so that you can choose the right data store without having to trawl the whole web to do it. It won't answer your questions definitively, but it should narrow down the range of options you have to consider.

knowledgewrappedinrules,databases,ortheWeballowsonetoexploreintere- ing hidden knowledge.Declarativetechniques for the transformation,deduction, induction, visualization, or querying of knowledge, or data mining techniques for exploring knowledge have the advantage of high transparency and better maintainability compared to procedural approaches.