java qr code reader app Ensuring data consistency in Java

Generator QR-Code in Java Ensuring data consistency

Ensuring data consistency
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Integrity rules are an important part of your database schema. The most important responsibility of your database is to protect your information and to guarantee that it s never in an inconsistent state. This is called consistency, and it s part of the ACID criteria commonly applied to transactional database management systems. Rules are part of your business logic, so you usually have a mix of businessrelated rules implemented in your application code and in your database. Your application is written so as to avoid any violation of the database rules. However, it s the job of the database management system to never allow any false (in the business logic sense) information to be stored permanently for example, if one of the applications accessing the database has bugs. Systems that ensure integrity only in application code are prone to data corruption and often degrade the quality of the database over time. Keep in mind that the primary purpose of most business applications is to produce valuable business data in the long run. In contrast to ensuring data consistency in procedural (or object-oriented) application code, database-management systems allow you to implement integrity rules declaratively as part of your data schema. The advantages of declarative rules include fewer possible errors in code and a chance for the database-management system to optimize data access.
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Legacy databases and custom SQL
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We identify four levels of rules:
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Domain constraint A domain is (loosely speaking, and in the database world) a datatype in a database. Hence, a domain constraint defines the range of possible values a particular datatype can handle. For example, an int datatype is usable for integer values. A char datatype can hold character strings: for example, all characters defined in ASCII. Because we mostly use datatypes that are built in to the database management system, we rely on the domain constraints as defined by the vendor. If you create user-defined datatypes (UDT), you ll have to define their constraints. If they re supported by your SQL database, you can use the (limited) support for custom domains to add additional constraints for particular datatypes. Column constraint Restricting a column to hold values of a particular domain is equivalent to adding a column constraint. For example, you declare in DDL that the INITIAL_PRICE column holds values of the domain MONEY, which internally uses the datatype number(10,2). You use the datatype directly most of the time, without defining a domain first. A special column constraint in an SQL database is NOT NULL. Table constraint An integrity rule that applies to a single row or several rows is a table constraint. A typical declarative table constraints is UNIQUE (all rows are checked for duplicate values). A sample rule affecting only a single row is end date of an auction must be later than the start date. Database constraint If a rule applies to more than one table, it has database scope. You should already be familiar with the most common database constraint, the foreign key. This rule guarantees the integrity of references between rows, usually in separate tables, but not always (self-referencing foreign key constraints aren t uncommon).
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Most (if not all) SQL database-management systems support the mentioned levels of constraints and the most important options in each. In addition to simple keywords, such as NOT NULL and UNIQUE, you can usually also declare more complex rules with the CHECK constraint that applies an arbitrary SQL expression. Still, integrity constraints are one of the weak areas in the SQL standard, and solutions from vendors can differ significantly. Furthermore, nondeclarative and procedural constraints are possible with database triggers that intercept data-modification operations. A trigger can then implement the constraint procedure directly or call an existing stored procedure.
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