The abstract of definitions and concepts of Database Systems      Farshad Badie   Computer Science M.Sc. farshadbadie(at)g...
Data Model: Collection of concepts that describe the structure of a database.Basic Operations: (1)Retrievals (2)Updates on...
VDL: View Definition Language, Speciefies users view/mapping to conceptualschema.Data Domain: All the unique values which ...
functional dependency on a set of attributes X (X gives Y) if and only if Each Xvalue is associated by Y value.Trivial Fun...
Database Normalization: In the design of DBMS, the process of organizing datato minimize redundancy. Goal: decompose relat...
Cartesian Product:Produces a relation that has the attributes of R1 and R2 andincludes as tuples all possible combinations...
Relationship: When an attribute of one entity type refers to another entity type.Relationship type R: Among n entity types...
Essential Definitions and Concepts in Database systems
Essential Definitions and Concepts in Database systems
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Essential Definitions and Concepts in Database systems

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Essential Definitions and Concepts in Database systems

  1. 1. The abstract of definitions and concepts of Database Systems Farshad Badie Computer Science M.Sc. farshadbadie(at)google(dot)comData: The term data refers to qualitative or quantitative attributes of set ofvariables.Database: A database is an organized collection of related data for one or morepurposesDBMS: A collection of programs that enables users to create , maintain , use adb.Database System: Is a term that constructs of a data model, databaseManagement system and database.DBA: Database administrators are responsible for (1) Authorizing access to thedb (2) monitoring it’s use (3)Acquiring software and hardware resources.End User: People whose jobs require access to the database.Meta-Data: Stored database definition / or descriptive informationCanned Transaction: May cause some data to be read or be written into the db.Deductive Database System: Provide capabilities for defining deduction rules.Transaction Processing Application: Allow multiple users to access the databaseat the same time.
  2. 2. Data Model: Collection of concepts that describe the structure of a database.Basic Operations: (1)Retrievals (2)Updates on the database.Dynamic aspect: Or behaviour of a database application; Allows the designer tospecify a set of valid operations allowed on database objects.Categories of data models: (1) “high level” or “Conceptual” data models (Closeto the way many users view data) / (2) “low level” or “Physical” data models(Describes the details of how data is stored on computer storage media) / (3)Representational data models (similar to how data organized in computerstorage)Relational data models: Entity (Real world object or concept) / Attribute(Describe entity) / Relationship (Among two or more entities)Object data model: New family of higher-level / closer to conceptual datamodels.Database schema: Description of a databaseDatabase state or snapshot: Data in database at a particular moment in time.Types of state: (1) Initial state: loaded with initial data , (2)Valid state: satisfiesthe structure and constraints specified in the schema.Three Schema architecture: (1)Internal level (describes physical storagestructure of database) , (2)Conceptual level (describes structure of the wholedatabase for a community of users , (3) External or view level (describes part ofthe database that a particular user group is interested in)Data Independence: Capacity to change the schema at one level of a dbs.DDL: Data Definition Language; Define both shemas (Logical and Physical)DML: Data Manipulation Language; Allows retrieval, insertion, deletion,modificationSDL: Storage Definition Language; Specifies the interval schema
  3. 3. VDL: View Definition Language, Speciefies users view/mapping to conceptualschema.Data Domain: All the unique values which a data element may contain / Set ofatomic values (atomic values are indivisible).Attribute: The name of a role played by some Domain D in the relation R .n-tuple: Ordered list of values 1 to n, each value is an element of dom or nullvalue: Each cell of the relation.Relation: Is a data structure which consists of “heading” and “set” and “tuple”;Which share the same time.Degree of a relation: The number of attributes.Cardinality of a relation: The number of tuples.Super Key: Is a combination of attributes that can be used to uniquely identify adatabase record. (A table might have many superkeys)Candidate key: Special subset of superkeys that do not have any extraneousinformation in them; It’s a minimal superkey. (Relation schema may have morethan one key) / Certain minimal set of one or more attributes that can uniquelyidentify individual tuples in a relation.Minimal Superkey: Cannot remove any attributes and still have uniquenessconstraint.Primary Key: Most DBMS, require a table to be defined as having a singleunique key; Rather than a number of possible unique keys ( If we have morethan one key in our relation schema, one is primary key – Others are secondarykey)ACID: Atomicity – Consistency – Isolation – DurabilityFunctional Dependency: Functional relationship among 2 sets of attributes(Xand Y). Value of X determines a unique value of Y / In a table, attribute Y has a
  4. 4. functional dependency on a set of attributes X (X gives Y) if and only if Each Xvalue is associated by Y value.Trivial Functional Dependency: Is a functional dependency of an attribute on asuperset of itself.Transitive Dependency: Is an indirect functional dependency. In which , Xgives Z , only as the result of , X gives Y , and , Y gives Z .Multi Valued Dependency: Is a constraint according to which the presence ofcertain rows in a table implies the presence of certain other rows. T3[x] = 4 = 1 =2 ... 3 = 1 ^ 4 = 2 , 3=2 ^ 4=1Relational Databases Schema (S): Set of relation schemas S={R1 , ... , Rn} / Setof Integrity constraints (IC)Relational Database State: Set of relation states: DB={r1 , ... , rm} ; Each ri isthe state of RiInvalid State: Does not obey (follow) all the IC.Valid State: Satisfies all the constraints in the defined set of IC.Entity Integrity Constraint: No primary key value can be null.Referential Integrity Constraint: Specified between two relations – Maintainsconsistency among tuples in two relations.Operations of the relational model can be categorized into “retrievals” and“updates” (Basic Operations).Basic Operations that change the states of relations in database: Insert , Delete ,Update (or Modify)Transaction Concept: Executing program, includes some database operationsmust leave the database in a valid or consistent state.Online Transaction Processing (OLTP): Execute transactions at rates that reachseveral hundred per second.
  5. 5. Database Normalization: In the design of DBMS, the process of organizing datato minimize redundancy. Goal: decompose relations with anomalies in order toproduce smaller, well-structured relations.1st Normal form: (1) no duplicate rows (2)cells are single-valued (3)entries of acolumn are same kind .2nd Normal form: (1) It is 1st, (2) all non-key attributes are dependent on all ofthe key.3rd Normal Form: (1) It is 2nd, (2) no transitive dependenciesBoyce Code Normal Form: (1) It is 3rd, (2) every determinant is a candidate key.4th Normal Form: Has no multi-valued dependencies.5th Normal Form: (1) It is 4th,(2) every join dependency in the table is aconsequence of the candidate keys of the tableList the operations of relational algebra and the purpose of each.Select: Select all tuples that satisfy the selection condition from a relation R .Project: Produces a new relation with only some of the attributes of R, andremoves duplicate tuples.Theta Join: Produces all combinations of tuples from R1 and R2 that satisfy thejoin condition .EquiJoin: Like the previous one, but with only equality comparisons.Natural Join:They have a same attribute to have the join over this attribute.Union: Produces a relation that includes all the tuples in R1 or R2 or both.Intersection:Produces a relation that includes all the tuples in both.
  6. 6. Cartesian Product:Produces a relation that has the attributes of R1 and R2 andincludes as tuples all possible combinations of tuples from R1 and R2DifferenceDivision:Using high-level conceptual data models: Conceptual Schema / Logical designor Data model mapping / Physical design phaseEntity relational model: describes data as: Entity , Relationships , AttributesType of attributes: Atomic , Single-valued versus Multi-valued , Null , ComplexEntity type, collection (or set) of entities that have the same attributes. Forexample entity type name is employee and it contains entity sets of differentemployees with their name, age, ... / or an entity type with name of company.Key or uniqueness constraint: Attributes whose values are distinct for eachindividual entity in entity setKey attribute: Uniqueness property must hold for every entity set of the entitytype.Value sets(or domain of values): set of values that assigned to that attribute foreach ind entity.*Company database , employee – department – dependent and project are entitytypes and they have attributes
  7. 7. Relationship: When an attribute of one entity type refers to another entity type.Relationship type R: Among n entity types E ... EDegree of a relationship type: Number of participating entity types, Binary-ternaryRole name: Role that a participating entity plays in each relationship instance(case)Recursive relationship: Same entity type participates more than once in arelationship type in different roles.Cardinality ratio: Maximum number of relationship instances that entity canparticipate inParticipation constraint: Whether existence of entity depends on its beingrelated to another entity , Types: total and partial

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