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Section 4

Section 4. 4. Relational Databases. Many views ,. View 1. View 2. View 3. Conceptual (logical) schema. Conceptual Schema. Physical schema. Physical Schema. Section 4 # 1. Levels of Abstraction in data defined by various “schema” levels.

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Section 4

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  1. Section 4 4. Relational Databases

  2. Many views, View 1 View 2 View 3 • Conceptual (logical) schema Conceptual Schema • Physical schema. Physical Schema Section 4 # 1 Levels of Abstraction in data defined by various “schema” levels • Views describe how users see data (possibly different data models for different views) • Conceptual schema defines logical structure of entire data enterprise • Schemas are defined using Data Definition Languages or DDLs; • data are modified/queried using Data Manipulation Languages or DMLs. • Physical schema describes underlying files and indexes used. ANSI schema model

  3. These layers must consider concurrency control and recovery Query Optimization and Execution Relational Operators Files and Access Methods Buffer Management Disk Space Management DB Section 4 # 2 Structure of a DBMS • A typical DBMS has a layered architecture. • This is one of several possible architectures. • Another with a little more detail on next slide.

  4. Section 4 # 3 Structure of a DBMS QUERIES from users (or Transactions or user-workload requests) SQL (or some other User Interface Language) QUERY OPTIMIZATION LAYER Relational Operators (Select, Project, Join) DATABASE OPERATOR LAYER  File processing operators (open,close file,read/write record FILE MANAGER LAYER (provide the file concept)  Buffer managment operators (read/flush page) BUFFER MANAGER LAYER Disk transfer operators (malloc, read/write block DISK SPACE MANAGER LAYER  DB on DISK

  5. Section 4 # 4 DISK SPACE MANAGER deals with space on disk offers an interface to higher layers (mainly the BUFFER MGR) consisting of: allocate/deallocate space; read/write block can be implement on a raw disk system directly, then it would likely access data as follows: read block b of track t of cylinder c on disk d or can use OS file system (OS file = sequence of bytes) then it would likely access data as follows: read bytes b of file f and then the Operating System file manager would translate that into read block b of track t of cylinder c on disk d most systems do not use the OS files system - for portability reasons, - to avoid OS file size peculiarities (limitations)

  6. Section 4 # 5 BUFFER MANAGER partitions the main memory allocated to the DBMS into buffer page frames, brings pages to and from disk as requested by higher layers (mainly the FILE Mgr). FILE MANAGER supports the file concept to higher layers (DBMS file = collection of records and pages of records) supports access paths to the data in those files (e.g., Indexes). Not all Higher level DBMS code recognizes/ uses page concept. Almost all DBMS use the record concept, though.

  7. Section 4 # 6 DATABASE OPERATOR LAYER implements physical data model operators (e.g., relational operators; select, project, join...) QUERY OPTIMIZER produces efficient execution plans for answering user queries (e.g., execution plans as trees of relational operators: select, project, join, union, intersect translated from, e.g., SQL queries). SQL is not adequate to answer all user-database questions, e.g., Knowledge workers working on Data Warehouses ask "what if" questions (On-Line Analytic Processing or OLAP) not retrieval questions (SQL)

  8. name ssn lot Employee Section 4 # 7 Overview of Database Design • Conceptual design: • What are the entities and relationships in the enterprise? • What information about these entities and relationships should be stored in the database? • What integrity constraints or business rules should be enforced? A database `schema’ Model diagram answers these question pictorially (Entity-Relationship or ER diagrams). • Then one maps the ER diagrams into a relational schema (using the Data Definition Language provided) Entity:Real-world object type distinguishable from other object types. An entity is described using a set of Attributes. Each entity set has a key. (which is the chosen identifier attribute(s) and is underlined in these notes) Each attribute has a domain.(allowable value universe)

  9. name since name dname ssn lot ssn budget lot did Employee Works_In Employee Department super-visor subor-dinate Reports_To Degree=2 relationship between entities, Employees and Departments. Must specify the “role” of each entity to distinguish them. Section 3 # 1 ER Model (Cont.) Relationships can have attributes too! • Relationship: Association among two or more entities. E.g., Employee Jonesworks inPharmacy department. Degree=2 relationship between an entity and Itself? E.g., Employee Reports_To Employee.

  10. since since name name dname dname ssn ssn lot lot did did budget budget m n since name dname Employee Employee Manages Manages Department Department ssn budget lot did Works_In Employee Department 1 1 m 1 1-to-1 1-to Many Many-to-1 Many-to-Many Section 3 # 1 Relationship Cardinality Constraints • (many-to-many) Works_In: An employee can work in many departments. A dept can have many employees working in it. • (1-many) e.g., Manages: • It may be required that each dept has at most 1 manager. • (1-1) Manages: In addition it may be required that each manager manages at most 1 department.

  11. Section 3 # 1 Participation Constraints • Every department may have to have a manager? • This is an example of total participation constraint: • the participation of Department in Manages is said to be total (vs. partial). since since name name dname dname ssn did did budget budget lot total Departments Employees Manages Works_In since

  12. name ssn lot Employee Covering yes hours_worked hourly_wages ISA contractid Overlap allowed Contract_Emp Hourly_Emp Section 3 # 1 ISA (`is a’) Hierarchies We can use attribute inheritance to save repeating shared attributes. If we declare an ISA relationship among entity types, e.g., A ISA B (every instance of A entity is also an instance entity of entity B), then B entities “inherit” A entity attributes • Overlap constraints: Can Joe be an Hourly_Emp and a Contract_Emp? (Allowed/disallowed) • Covering constraints: Does every Employee entity also have to be an Hourly_Emp or a Contract_Emp entity? (Yes/no) e.g., every Hourly_Emp ISA Employee every Contract_Emp ISA Employee Hourly_Emps and Contract_Emps can have their own separate attributes also.

  13. Relational Database: Working Definitions Section 3 # 1 • Relational database: a set of relations • Relation: made up of 2 parts: • Instance or occurrence : a table, with rows and columns. #Rows = cardinality, #fields = degree • Schema or type:specifiesname of relation & name, type of each attribute • Students(sid: string, name: string, login: string, age: integer, gpa: real). • Strictly, a relation is a setof tuples but it is common to think of it as a table (sequence of rows made up of a sequence of attribute values)

  14. Section 3 # 1 Relational Query Languages • A major strength of the relational model: supports simple, powerful querying of data. • Queries can be written intuitively (specifying what, not how), DBMS is responsible for evaluation • The DBMS does your programming! • Allows a module called the optimizer to extensively re-order operations (even combine similar operations from different concurrent requests), and still ensure that the answer does not change.

  15. Section 3 # 1 The SQL Query Language • Developed by IBM (system R) in the 1970s • Need standards since it is used by many vendors • Standards: • SQL-86 • SQL-89 (minor revision) • SQL-92 (major revision) • SQL-99 (major extensions) • Procedural constructs (if-then-else, loops, procs) • OO constructs (inheritance, polymorphism,…)

  16. SQL Query Language What columns you want What rows you want. • Find all 18 year old students (a selection) SELECT * FROM Students S WHERE S.gpa=3.4 sid name login age gpa 53666 Jones jones@cs 18 3.4 • To find just names and logins (a projection), replace 1st line: name login SELECT S.name, S.login FROM Students S WHERE S.age=18 Jones jones@cs Section 3 # 1 • One of the simplest languages on earth very English-like! Specify what, not how. • E.g., SELECT attributes FROM relations WHERE condition

  17. What does the following query produce? SELECT S.name, E.cid FROM Students S, Enrolled E WHERE S.sid=E.sid AND E.grade=“A” suceeds Joined But Select fails sid name login age gpa 53666 Jones jones@cs 18 3.4 53650 Smith smith@ee 18 3.2 we get: S.name E.cid Smith Topology112 Section 3 # 1 Querying Multiple Relations (Join, implemented using nested loop – alternative 1) Where also used to combine (join) S & E

  18. DROP TABLE Students • Destroys the relation Students. The schema information and the tuples are deleted. ALTER TABLE Students ADD COLUMN Year: integer • The schema of Students is altered by adding a new field; every tuple in the current instance is extended, e.g., with a null value in the new field. Section 3 # 1 Destroying and Altering Relations (also DDL)

  19. Can insert a single tuple using: INSERT INTO Students (sid, name, login, age, gpa) VALUES (53688, ‘Smith’, ‘smith@ee’, 18, 3.2) Can delete all tuples satisfying some condition (e.g., name = Smith): DELETE FROM Students S WHERE S.name = ‘Smith’ Section 3 # 1 Adding and Deleting Tuples • many powerful variants of these commands are available!

  20. Views Section 3 # 1 • A viewis a relation constructable from stored or base relations. Store a definition of it, rather than the instance (actual tuples). CREATE VIEW YoungActiveStudents (name, grade) AS SELECT S.name, E.grade FROM Students S, Enrolled E WHERES.sid = E.sid and S.age<21 Views can be dropped using the DROP VIEW command. How to handle DROP TABLE if there’s a view on the table? • DROP TABLE command has options to let user specify this. • Views can be used to present necessary information (or a summary), while hiding details in underlying relation(s).

  21. Integrity Constraints (ICs) Section 3 # 1 • IC: condition that must be true for any instance in the database; e.g., domain constraints. • ICs are specified when (or after) relations are created. • ICs are checked when relations are modified. • A legalinstance of a relation is one that satisfies all its ICs. • DBMS should not allow illegal instances. • Avoids data entry errors, too!

  22. Primary Key Constraints Section 3 # 1 • A set of fields is a key (strictly speaking, a candidate key) for a relation if it satisfies: • 1. (Uniqueness condition) No two distinct tuples can have same values in the key (which may be a composite) • 2. (Minimality condition) The Uniqueness condition is not true for any subset of a composite key. • If Part 2 is false, it’s called a superkey (for superset of a key) • There’s always at least one key for a relation, one of the keys is chosen (by DBA) to be the primary key, the primary record identification or lookup column(s) • E.g., sid is a key for Students. The set {sid, gpa} is a superkey. Entity Integrity • No column of the primary key can contain a null value.

  23. Foreign Keys and Referential Integrity Section 3 # 1 • Foreign key : A field (or set of fields) in one relation used to `refer’ to a tuple in another relation. (by listing the the primary key value in the second relation.) Like a `logical pointer’. • E.g. sid in ENROLL is a foreign key referring to sid in Students (sid is the primary key of S) • If all foreign key constraints are enforced, a special integrity constraint, referential integrity , is achieved, i.e., no dangling references • E.g., if Referential Integrity is enforced (and it almost always is) an Enrolled record cannot have a sid that is not present in Students (students cannot enroll in courses until they register in the school)

  24. Enrolled Students Section 3 # 1 Foreign Keys • Only students listed in the Students relation should be allowed to enroll for courses.

  25. Enforcing Referential Integrity Section 3 # 1 • Consider Students and Enrolled; sid in Enrolled is a foreign key that references Students. • What should be done if an Enrolled tuple with a non-existent student id is inserted? (Reject it!) • What should be done if a Students tuple is deleted? • Also delete all Enrolled tuples that refer to it? • Disallow that deletion if an Enrolled tuple refers to it? • Set sid in Enrolled tuples that refer to it to a default sid? • (sometimes there is a “default default, e.g., set sid in Enrolled tuples to a special value null, denoting `not applicable’ if no other default is specified.)

  26. Referential Integrity in SQL Section 3 # 1 • SQL supports all 4 options on deletes and updates. • Default action = NO ACTION(the violating delete/update request is rejected) • CASCADE (also delete all tuples that refer to deleted tuple) • SET NULL / SET DEFAULT (sets foreign key value of referencing tuple) CREATE TABLE Enrolled (sid CHAR(20), cid CHAR(20), grade CHAR(2), PRIMARY KEY (sid,cid), FOREIGN KEY (sid) REFERENCES Students ON DELETE CASCADE ON UPDATE SET NULL)

  27. Where do ICs Come From? Section 3 # 1 • ICs are based on the semantics of the real-world enterprise that is being described in the database. I.e., the users decide semantics, not the DB experts! • Why? • We can check a database instance to see if an IC is violated, but we can NEVER infer an IC by only looking at the data instances. • An IC is a statement about all possibleinstances!

  28. If ICs were inferred from current instances, then when a relation is newly created and has, say, just 2 tuple, many, many ICs would be inferred (e.g., in sid name login age gpa 53666 Jones jones@cs 18 3.4 53688 Smith smith@ee 18 3.5 Section 3 # 1 • An IC is a statement about all possibleinstances! • It is not a statement that can be inferred from the set of currently existing instances. • the system might infer that students MUST be 18 or that • names have to be 5 characters or worse yet, that • gpa ranking must be the same as alphabetical name ordering! • Key and foreign key ICs are the most common. • The next slides deals with the IC of choosing keys.

  29. Section 3 # 1 Who decides primary key? (and other design choices?) • The Database design expert? • NO! Not in isolation, anyway. • Someone from the enterprise who understands the data and the procedures should be consulted. • The following story illustrates this point. CAST: • Mr. Goodwrench = MG (parts manager); • Ph D I've looked at your data, and decided Part Number (P#) will be designated the primary key for the relation, PARTS(P#, COLOR, WT, TIME-OF-ARRIVAL). • MG You're the expert. • Ph D Well, according to what I’ve learned in school, P# should be the primary key, because IT IS the lookup attribute! • . . . later • Pointy-headed Dbexpert = Ph D

  30. Section 3 # 1 • MG No. We store by weight! When a shipment comes in, I take each part into the back room and throw it as far as I can. The lighter ones go further than the heavy ones so they get ordered by weight! • MG Why is lookup so slow? • Ph D You do store parts in the stock room ordered by P#, right? • Ph D But, but… weight doesn't have Uniqueness property! Parts with the same weight end up together in a pile! • MG No they don't. I tire quickly, so the first one I throw goes furthest. • Ph D Then we’ll use a composite primary key, (weight, time-of-arrival). • MG We get our keys primarily from Curt’s Lock and Key. • The point is: This conversation should have taken place during the 1st meeting.

  31. Section 3 # 1 An ER Example: COMPANY is described to us as follows: 1. The company is organized into depts - each with a name, number, manager. - Each manager has a startdate. - Each department can have several locations. 2. Departments control projects - each with a name, number, location. 3. Each employee has a name, SSN, sex, address, salary, birthdate, dept, supervisor. - An employee may work on several projects (not necessarily all controlled by his dept) for which we keep hoursworked by project. 4. Each employee dependent has a name, sex, birthdate and relationship. In ER diagrams, entities are represented in boxes: |EMPLOYEE| |DEPENDENT| |DEPT| |PROJECT| An attribute (or property) of an entity describes that entity. An ENTITY has a TYPE, including name and list of its attributes. ENTITY TYPE SCHEMA describes the common structure shared by all entities of that type. Project (Name, Num,Location, Dept) ENTITY INSTANCE = individual occurrence of an entity of a particular type at a particular time (Dome, 46, 19 Ave N & Univ, Athletics) (IACC, 52, Bolley & Centennial, C.S.) (Bean Res, 31, 12 Ave N & Federal, P.S.) . . . Entity Type does not change often - very static. Entity instances get added, changed often - very dynamic

  32. Section 3 # 1 An ER Example continueed: ATTRIBUTES are written next to Entity they describe, usually something like the following: Name-------------. Name-------------. Number-----------| Number-----------| Locations--------|--|DEPARTMENT| Location---------|-|_PROJECT| Manager----------| ControlDepartment' ManagerStartDate-' .--Name |--SSN .-Employee |__EMPLOYEE__|----|--Sex |-DependentName |--Address |_DEPENDENT|--|-Sex |--Salary |-BirthDate |--BirthDate `-Relationship |--Department |--Supervisor `--WorksOn

  33. Section 3 # 1 An ER Example: CATEGORIES OF ATTRIBUTES: = COMPOSITE ATTRIBUTE = attributes that are subdivided into smaller parts with independent meaning. e.g., Name attribute of Employee may be subdivided into FName, Minit, LName. Indicated: Name (FName, Minit, LName) Also, WorksOn may be a composite attr of Employee of Project and Hours: WorksOn (Project, Hours) SINGLE-VALUED ATTRIBUTE: one value per entry. MULTIVALUED ATTRIBUTE (repeating group) have multiple values per entry: eg, Locations (as an attribute of Department since a Department can have multiple locations) - Multivalued Attribute, use {Locations} - WorksOn may be a mutlivalued attr of Employee as well composite: {WorksOn (Project,Hours)} DERIVED ATTRIBUTE is an attribute whose value can be calculated from other attribute values. eg, Age calculated from BirthDate and CurrentDate. KEY ATTRIBUTE: Each value can occur at most once. (has the uniqueness property) Used to identify entity instances. We will * key attribute(s). ATTRIBUTE DOMAIN: Set of values that may be assigned (also called Value Set). Thus the Preliminary Design of Entity Types for COMPANY db is. *Name-------------. *Name-------------. *Number-----------| *Number-----------| Locations--------|--|DEPARTMENT| Location---------|-|_PROJECT| Manager----------| ControlDepartment' ManagerStartDate-' .---Name |--*SSN .--Employee |__EMPLOYEE__|----|---Sex |-*DependentName |---Address |_DEPENDENT|--|--Sex |---Salary |--BirthDate |---BirthDate `--Relationship |---Department |---Supervisor `---WorksOn

  34. Section 3 # 1 An ER Example continued: RELATIONSHIPS among entities express relationships among them: Relationships have RELATIONSHIP TYPEs (consisting of the names of the entities and the name of the relationship). A Relationship type diagram for a relationship between EMPLOYEE and DEPARTMENT called "WorksFor" is diagrammed: (in a roundish box) |EMPLOYEE|-( WorksFor )-|DEPARTMENT| RELATIONSHIP INSTANCEs for the above relationship might be, eg: ( John Q. Smith, Athletics ) ( Fred T. Brown, Comp. Sci.) ( Betty R. Hahn, Business ) . . . RELATIONSHIP DEGREE: Number of participating entities (usually 2) If an entity participates more than once in the same relationship, then ROLE NAMES are needed to distinguish multiple participations. eg, Supervisor, Supervisee in Supervision relationship - Called Reflexive Relationships. - Unnecessary if entity types are distinct. One decision that has to be made is to decide whether attribute or relationship is the appropriate way to model, e.g., "WorksOn". Above we modeled it as an attribute of EMPLOYEE {WorksOn(Project,Hours)} The fact that it is multivalued and composite (involving another entity, project) ssuggest that it would be better to model it as a relationship (i.e., it makes a very complex attribute!) WORKS_FOR(EMPLOYEE, DEPARTMENT)

  35. Section 3 # 1 An ER Example continued: CONSTRAINTS ON A RELATIONSHIP CARDINALITY CONSTRAINT can be 1-to-1 many-to-1 1-to-many or many-to-many 1 to 1: MANAGES(EMPLOYEE, DEPARTMENT) Each manager MANAGES 1 dept Each dept is MANAGED-BY 1 manager Many to 1: WORKS_FOR(EMPLOYEE, DEPARTMENT) Each employee WORKS_FOR 1 dept Each dept is WORKED_FOR by many emps Many to Many: WORKS_ON(EMPLOYEE, PROJECT) Each employee WORKS_ON many projects Each project is WORKED_ON by many employees PARTICIPATION CONSTRAINT (for an entity in a relationship) can be Total, Partial or Min-Max Total: Every EMPLOYEE WORKS_FOR some DEPARTMENT Partial: Not every EMPLOYEE MANAGES some DEPT RELATIONSHIP can have ATTRIBUTES (properties) as well: eg, Hours for WORKS_ON Relationship, Manager_Start_Date in MANAGES relationship.

  36. Section 3 # 1 An ER Example continued: 6 RELATIONSHIPS; (role names, if any, above) CARDINALITY RELATIONSHIP ATTRIBUTES ----------- ------------ ------ (participation below) 1:1 MANAGES (EMPLOYEE, DEPARTMENT) partial total 1:many WORKS_FOR (DEPARTMENT, EMPLOYEE) total total many:many WORKS_ON (EMPLOYEE, PROJECT) total total 1:many CONTROLS (DEPARTMENT, PROJECT) partial total Reflexive relationship with role names --------------.---------. supervisor supervisee 1:many SUPERVISION (EMPLOYEE, EMPLOYEE) partial partial 1:many DEPENDENTS_OF ( EMPLOYEE, DEPENDENT) partial total

  37. Section 3 # 1 An ER Example continued: COMPANY Entity-Relationship Diagram (showing the Schema) (double connecting lines means "total" while single line means partial participation.) ( MANAGES ) 1|| |1 || (WORKS_FOR) | *Name-----------. || 1|| many|| | *Number---------| || || || / {Locations}-----|- DEPARTMENT // / number_employees' /1 // / .----' // / ( CONTROLS ) // / many // / || // / || (SUPERVISE) // / || | | // / || 1| |many // / || 'er| |'ee // / || |____|_______//_____/ .Name(FN,Mi,LN) || |_EMPLOYEE__________|---|-*SSN || // | |-Sex || // | |-Address || Hours-. // | |-Salary || | /many | `-BirthDate \\ (WORKS_ON) | \\ 1| \\ many| | \\ || ( Dependent_0f ) \\ || |many *Nane-. \\_______||___ || *Numb-|--| PROJECT | || Locatn' || || *DependentName---. . Sex--------------|--|| DEPENDENT || BirthDate--------| Relationship-----'

  38. Section 3 # 1 Thank you.

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