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Implementation Technology Based on Client/Server Data Integrity Constraints

Abstract: This paper mainly discusses the client/Server data integrity constraint and how to implement enterprise business rules. Taking SQLServer and PowerBuilder as examples, the paper introduces the implementation technology of data integrity constraints. Keywords: Client/Server, Data Integrity Constraints, Enterprise Business Rules DBMS has evolved from an early decentralized computing model, network/archive service computing model to the current Client/Server computing model. The Client/Server model is non-equivalent, the client makes a service request, the server responds, and provides the service, the so-called "request-driven". DB's Client/Server system consists of a DBServer, a client application, and a network. DBServer is responsible for effectively managing system resources, mainly responsible for data processing, concurrency control, data security, data integrity, and data backup and recovery. The client application is the part of the system that allows the user to interact with the data. The main task is to provide an interactive interface to complete the data entry, analysis, inspection and display, to send requests to the DBServer and receive results and error messages. Network and communication software are tools for data transfer between clients and servers in the system. Since the current database is open and multi-user shared, it is important to maintain the correctness of the database. The integrity of the database is described as a set of integrity constraints for the contents of the repository, where integrity constraints refer to whether a state of the repository is reasonable, which is a set of predicates. The DBS checks the status and state transitions of the data to determine if they are reasonable and should be accepted. For a database operation, to determine whether it meets the integrity constraint, all assertions can be executed without contradiction. The formal definition of integrity constraints is I=, where O is the set of data objects involved in the integrity constraint, P is the predicate that the object satisfies, A is the condition that triggers the check, and R is the reaction action when the constraint is not satisfied [2] I. Common Data Integrity Constraints According to different classification angles, integrity constraints can be divided into the following categories: • Domain, tuple, set integrity, immediate constraint and deferred constraint • state constraint and state evolution constraint. Standard and Customized Data Integrity Constraints In practical systems, data integrity constraints are generally divided into standard data integrity constraints and custom data integrity constraints. Standard data integrity constraints are internal rules that DBS has implemented, including domain integrity, entity integrity, and referential integrity. Domain integrity guarantees that a database does not contain meaningless or unreasonable values, that is, any value of a column of a guaranteed table is a member of that column domain. The method is to limit the data type, precision, range, format, and length of the column. Entity integrity guarantees that each row in a table must be unique. To ensure entity integrity, you need to specify a table

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