Function dependence and multi-valued dependence were different types of data dependence. Ordinary multi-valued dependence was not a functional dependence. The functional dependence reflected the relationship between attributes or attribute groups. When one attribute set determined another attribute set, the other attribute set was said to be dependent on the attribute set. Multi-valued dependence was within the definition of 4nf, which was much more complicated than functional dependence. In functional dependence, whether X and Y had a functional dependence only needed to examine the two sets of attributes of X and Y, and had nothing to do with other attributes. In multi-valued dependence, whether X and Y had a multi-valued dependence depended on attribute Z. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
Let the relation model R(U), U = {A, B, C}, let X = {A}, Y = {B}, Z = {C} and Z = U-X- Y. If for any relation r of R(U), given a pair of (A's value, C's value), there is a set of B's value, and this set of B's value only depends on the value of A and has nothing to do with the value of C. When Z is an empty set (that is, there are only two attribute sets of A and B in the relation pattern), it forms an ordinary multi-valued dependence X→→Y. For example, if there is a relationship that represents the student's course selection, assume that the student can only choose one course.(The situation is simplified here for example), the relationship model has an attribute set {student name, course name, teacher name}. If we only consider the two attribute sets {student name} and {course name}, for each student name, the course name is determined (there is no multi-valued situation, because the setting can only choose one course). At this time, if the other attribute sets are regarded as empty sets (here is the attribute set of teacher name), this can be regarded as an ordinary multi-valued dependence. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
In a multi-valued dependence, let R(U) be a relation pattern on the property set U, X, Y, and Z be a set of U, and Z = U-X- Y. If X→→Y and Z is an empty set, then X→→Y is called a trivial multi-valued dependence; if Z is not empty, then X→→Y is called a non-trivial multi-valued dependence. For example, in the relationship model <Warehouse Manager, Warehouse No., Warehouse Item No.>(Assuming that a product can only be placed in one warehouse, but a warehouse can have several managers), there is a warehouse number corresponding to a <Warehouse Manager, Warehouse Item No.>, but in fact, this warehouse number is only related to the inventory item number and has nothing to do with the manager. This is a manifestation of multi-value dependence. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
4.<strong></strong> Let me explain it to you in detail. ###Fourth Normal Form (4GN) and Multi-valued Dependence (MVR) In database design, 4HF was a very important model. It required that every non-main attribute in the relationship model could not depend on the non-main attributes of other non-main attributes. In other words, a relationship model should have no multi-valued dependence and no joint dependence. Multi-valued dependence refers to the fact that an attribute in a relationship model depends on multiple values of other non-main attribute sets in the relationship model. ###Ordinary and Non-Ordinary Multivalue Dependences - ** Ordinary multi-valued dependence **: When the set of values of Y is a sub-set of X, that is, Y X, the multi-valued dependence X→→Y is called ordinary. This meant that the value of Y was completely determined by the value of X, regardless of whether there were other attributes in Y. - ** Non-trivial multi-valued dependence **: If Y is not a set of X, that is, Y X, then the multi-valued dependence X→→Y is called non-trivial. In this case, the value of Y not only depended on the value of X, but it might also depend on attributes other than X. ### 4 Multivalue Dependences in HF In 4HF, only trivial multi-valued dependence is allowed. This meant that if there were any non-trivial multi-valued dependence, it would need to be eliminated through the database normalisation process. This usually involves breaking down the relationship model into smaller, more manageable parts to ensure data integrity and integrity. Through the above analysis, we can see that there is a close relationship between 4HF and multi-valued dependence, but there are also obvious differences. I hope this information will help you better understand the concepts of 4HF and multi-valued dependence and their application in database design. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
In the database relationship model, there was an unbalanced situation in the multi-valued dependence. Generally speaking, multi-valued dependence refers to a relationship where one attribute group has a dependence on another attribute group. This relationship is independent of other attributes, does not involve the uniqueness of keys, and is different from functional dependence. For example, in the relationship StudentClasses (StudentID, Course, Instructor), StudentID ->> Course means that the student can take multiple courses (there is a multi-valued dependence between the student and the course). This is an unbalanced relationship because the course cannot determine the student (the unbalanced characteristic), and this dependence is independent of the teacher (the characteristic of multi-valued dependence is independent of other attributes). This kind of non-symmetrical multi-valued dependence was of great significance in the process of database design and regularisation. For example, when detecting multi-valued dependence, it was necessary to analyze this kind of non-symmetrical attribute group relationship and verify whether it met the conditions of multi-valued dependence through a formal definition (for the relationship R and the attribute group A, B, C, if A ->> B, then for each fixed value of A, there is a set of unique B values. These B values and C values are independent) to ensure the accuracy and efficiency of the database design. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
In the relation pattern R(U)(U is the property set), let X, Y, and Z be a set of U, and Z = U-X- Y. If the multi-valued dependence in the relation pattern is true, and the set is not empty, then the multi-valued dependence is called non-trivial. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
If X->->Y, and X, Y, and Z are subsets of U, Z = U-X- Y, then X->->Y is called a non-trivial multi-valued dependence if Z is not empty. For example, in the relationship model, if there is U = warehouse + administrator + item,(warehouse, item) determines a group of administrators, but the administrator is only determined by the warehouse,(R-warehouse-administrator) is not an empty set, here warehouse->-> administrator is a non-trivial multi-valued dependence. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
Based on context alone 1. ** Ordinary Function Dependence ** - In a database, let R(U) be a relation pattern on a set of attributes U, and X and Y be a set of attributes U. If Y is a sub-set of X (that is, Y X), then X→Y is a trivial functional dependence. - For example, in the relationship mode of students (student number, name, gender),{student number, name}→{name} is a trivial functional dependence, because the name itself is a part of {student number, name}. Semantically speaking, trivial functional dependence represented an obviously established dependence relationship. This dependence relationship did not actually contain much meaningful new information, because it only indicated that the dependence of a set of attributes on its own set must exist. 2. ** Part of Function Dependence ** - Let (X,Y) be the property set of the relation pattern (R). If (X→Y) exists a proper set of (X ') such that (X'→Y), then (Y) is partially dependent on (X). - For example, in the Relational Mode course selection (student number, course number, grades, course name),{student number, course number}→{course name}, but in fact,{course number}→{course name}, which meant that the course name only depended on the student number and the course number in the course number, not the entire {student number, course number}, so the course name was partially dependent on {student number, course number}. Partial functional dependence may cause data redundancy-like problems. In the standardized design of a database, it is usually necessary to eliminate partial functional dependence to achieve a higher standard. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
Let X and Y be the attributes of a relation, and X→Y. If Y is contained in X, then X→Y is called a trivial functional dependence. If Y is not contained in X, then X→Y is called a non-trivial functional dependence. The trivial functional dependence was automatically established because it was determined by the reflexive nature of the functional dependence. The functional dependence that was generally studied was mostly non-trivial functional dependence. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
Non-trivial functional dependence: In the Relational Model, if there is an attribute set X and an attribute set Y, and X→Y, but Y is not a sub-set of X, this functional dependence is called a non-trivial functional dependence. For example, in the relationship between students (student number, name, class, course, grade), student number → grade was a non-trivial functional dependence, because grades were not a sub-set of student number, and the student number could determine the attribute of grades. Complete functional dependence: In a relationship, if a non-main attribute data item depends on all keywords, it is called complete functional dependence. For example, in the relationship course selection (student number, course number, score), the score was completely dependent on the combination of the student number and course number. This was because the student number or course number alone could not determine the score. Only the combination of the two could determine the score. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!
The following are some examples of functional dependence: 1. In student relationships, the student number determined the student's name, age, and department. It could be expressed as student number → (name, age, department). Since one student number corresponded to one student, once the student number was determined, the corresponding name, age, and faculty would also be determined. 2. In the course selection relationship, the student number and the course number could be added together to determine the results of a student's course, that is,(student number, course number)→ results. A single student number or course number could not determine the results. This was a complete functional dependence. 3. In describing the relationship between students, student number → name, student number → department. Because one student number corresponded to one and only one student, and one student studied in a certain department, when the value of the "student number" attribute was determined, the value of "name" and "department" was also uniquely determined. 4. In the relationship mode, the course number determines the course name, which can be expressed as: course number → course name. The Extraordinary Ordinary Life novel is equally exciting. Everyone is welcome to click and read it!