The process of database refactoring
What have you learned in a vision of the agile data method that agile methods like Extreme Programming (XP) (Beck, 2000) and DSDM (Stapleton, 2003) adopts an iterative and incremental approach to software development. Application developers on Windows XP and DSDM projects often leave big design up front (BDUF) approaches for new approaches in designing a system evolves over the life of the project. In an agile development project, the final design is often not known until the application is ready to be released. It is a very different way of working for several experienced professionals to work. The implication is that the traditional approach of creating a (nearly) complete logical and physical data models in the front does not work. The main advantage of the traditional approach is complicating the task manager’s process database (DBA) is much easier – the pattern of data takes place early and that’s what people use. However, there are several drawbacks. First, it requires developers to do things, forcing identify most of the requirements even earlier in the project, and therefore require your project team, taking a serial approach to development. Second, do not change easily. As the project progresses the project stakeholders to understand what it takes to develop, motivate them to change their needs. The business environment also will change during the project, again to motivate his players to change their needs. In short, the traditional way of work just does not feel well in a flexible environment. If Agile DBAs will work and support of project teams following agile methodologies they need to find technical support work in an iterative and gradual. My experience is that criticism is a technique of database refactoring. Contents 1. Refactoring 2. * Why Database Refactoring Refactoring database? * Preserving the semantics * What database refactorings Do not 3. Why Database Refactoring is Hard 4. How Refactor your database * Step 1: Initiate the development of his litter box Step 2: Implement the integration of the local copy (ES) * Step 3: Install in the production of 5. Take the database refactoring in your organization 6. Refactoring database of best practices 7. Database Refactoring in the real world 8. The refactorings catalog database (shown as a separate page) 1. RefactoringMartin Fowler (1999) describes a programming technique called refactoring, a disciplined way to restructure the code. The basic idea is to make small changes to your code to improve your project, so it is easier to understand and modify. Refactoring allows you to change your code slowly over time, having an iterative and progressive programming. Martin refactoring website, www. refactoring. com is an online resource as well. A critical aspect of a refactoring is that it preserves the behavioral semantics of your code, unless a point of view of the black box. For example, there is a very simple method called rename refactoring, perhaps getPerson () to getPeople (). Although this change on the surface it seems easy to do more than simply making this change, so too must every single call of this operation through your application code to invoke the new name. Once you’ve made these changes, then we can say that really has redesigned the code as it continues to operate as before. It is important to understand that you do not add functionality when it is restructured. Refactor to improve the existing code when you add the functionality to add the new code. Yes, you may need Refactor your existing code before adding new features. Yes, you may discover later that you need to Refactor the new code you just added. The point to note is that the refactoring and adding new features two missions are different, but complementary. 2. RefactoringIn Database February 2002, the number of software development describes a technique called refactoring of data. This article describes my experience preliminary to something more appropriate would have been called database refactoring in the fall. Hence the new name. From now on I will use the term refactoring code refactoring described by Fowler traditional to distinguish it from the database refactoring. Let’s start with some definitions. One database refactoring is a simple pattern change of a database design that improves, keeping both his behavior and semantic information. For purposes of this discussion, a database model includes both structural aspects such as table and view definitions as well as functional aspects, such as stored procedures and triggers. One interesting thing to note is that a database refactoring is conceptually more difficult than a code refactoring, code refactorings enough to behave in a semantic database refactorings must also maintain the semantic information. There is a database called refactoring to split a column, one of many described in a catalog database refactorings when replacing a single-column table, with two or more columns. For example, work on the table, nobody in their database and discovered that the firstDate column is used for two different purposes – if the person is a client of this column stores the date of birth and when the person is an employee who stores the date. Your application has to support people who can be both a client and a employee if you have a problem. Before you can implement this new requirement, you must fix your database schema by replacing the column firstDate date of birth and HireDate columns. To maintain the semantics of the conduct of their database schema that you must update all the source code that accesses firstDate column now working with two new columns. To maintain the semantics of information, you should write a script that runs the migration of the table determines the type, then copies the existing date in the appropriate column. Although it seems easy and sometimes it is, my experience is that database refactoring is extremely difficult in practice when cultural issues are taken into account (see below). 2. 1 Why Database Refactoring? There are two basic reasons why they should be interested in refactoring database: 1. To establish secure bases of existing legacy data. The key is that the old database will not fix and that a technical perspective of database refactoring is a simple and safe way to improve data quality and database over time. My July 2006 study on the current management of the data shows that 33% of organizations are or are taking an approach based on data from refactoring production to meet current quality problems. 2. To support the development of evolution. Modern processes of software development such as RUP, XP and UPA, all work in a progressive if not nimble. Professional technical data should take, including one that allows them to work in such manner. 2. 2 Preserving the SemanticsInformational semantics concerns the meaning of information within the database from the perspective of users of this information. To preserve the semantics of information means that changing the data values stored in a column of customers, this information should not be affected by this improvement. Similarly, with respect to the behavior of semantics, the goal is to maintain the functionality of a black box, the same – all the source code that works with the schema changed aspects of your database must be reworked in order to perform the same functions as before. 2. 3 What database are processing a small refactorings his scheme to extend it, like adding a new column or table, not a database refactoring because change is its design. Many small changes applied simultaneously to schedule your database, such as renaming of ten columns, is not considered a database refactoring, because only a small change. Database refactorings are small changes to your database schema to improve the design while preserving the semantics of behavior and information. That’s all. I have no doubt that you can make changes to your schema, and may even follow a similar process, but they are database refactorings. 3. Why Database Refactoring is HardCoupling. As you learned in 101 relational databases coupling is a measure of the degree of dependence between two points – the two most strongly coupled, it is more likely that a change in one will require a change in the other. The coupling is the “root of all evil”, while in the field of database refactoring, more things to your database schema is complemented by the more difficult it is redrafted. Unfortunately, you have learned in the relational database 101, that model relational database are potentially close to a variety of things: * Your request for application source code * Other Sources * Data sources * loading code extract data from the persistence framework of origin * / layers * The database schema script data migration * * * test code Documentation
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