CSE 5330/7330CSE 5330/7330Database IntroductionDatabase Introduction

Fall 2009Fall 2009

Margaret H. DunhamMargaret H. DunhamDepartment of Computer Science and EngineeringDepartment of Computer Science and Engineering

Southern Methodist UniversitySouthern Methodist UniversityPOBox 750122POBox 750122

Dallas, Texas 75275-0122Dallas, Texas 75275-0122

CSE 5330/7330 Fall 2009 1

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Database IntroductionDatabase Introduction

NOTE: These slides provide an overview NOTE: These slides provide an overview of the basic database concepts. During of the basic database concepts. During the semester we will return to them to the semester we will return to them to provide an overview and summary of provide an overview and summary of each section covered.each section covered.

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Database OutlineDatabase Outline

IntroductionIntroduction File Organization & IndexingFile Organization & Indexing Data ModelsData Models Relational ModelRelational Model SQL/Query ProcessingSQL/Query Processing TransactionsTransactions

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Database HistoryDatabase History

A Short Database History by John VaughnA Short Database History by John Vaughn

http://math.hws.edu/vaughn/cpsc/343/2003/http://math.hws.edu/vaughn/cpsc/343/2003/history.htmhistory.htmll

A Brief History of Database SystemsA Brief History of Database Systems

http://www.comphist.org/computing_history/new_page_9.htm

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DB History SnapshotsDB History Snapshots

CFMS/DBOMP (Late 60s)CFMS/DBOMP (Late 60s) EF Codd Paper (1970)EF Codd Paper (1970) DBTG Report (1974)DBTG Report (1974) IMS/IDMS (Early 1970s)IMS/IDMS (Early 1970s) System R (1970s)System R (1970s) Transactions – Jim Gray (1970s)Transactions – Jim Gray (1970s) ER Model (1976)ER Model (1976) OODB (1985)OODB (1985) XML/Internet (1990s)XML/Internet (1990s)

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What is a Database?What is a Database?

Collection of Related DataCollection of Related Data– DataData– HardwareHardware– Software (DBMS)Software (DBMS)– Users Users

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File vs. DatabaseFile vs. Database

Single user vs. multiple usersSingle user vs. multiple users Simple relationships vs. complex Simple relationships vs. complex

relationshipsrelationships Integrity supportIntegrity support Concurrency controlConcurrency control RecoveryRecovery Query languageQuery language SecuritySecurity Different Views of dataDifferent Views of data

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Some DB TermsSome DB Terms Data/Information/KnowledgeData/Information/Knowledge DataBase Management System (DBMS)DataBase Management System (DBMS) Data Dictionary/Directory/MetadataData Dictionary/Directory/Metadata Data ModelData Model Data Definition Languare (DDL)Data Definition Languare (DDL) Data Manipulaiton Language (DML)Data Manipulaiton Language (DML) DataBase Administrator (DBA)DataBase Administrator (DBA) Data Administrator (DA)Data Administrator (DA) Database designerDatabase designer Information Resource Manager (IRM)Information Resource Manager (IRM) Chief Information Officer (CIO)Chief Information Officer (CIO) ……

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DBMS ComponentsDBMS Components DDL CompilerDDL Compiler DML CompilerDML Compiler Precompiler (embedded language support)Precompiler (embedded language support) Access methodsAccess methods Concurrency ControlConcurrency Control RecoveryRecovery SecuritySecurity Data Dictionary (Metadata)Data Dictionary (Metadata) Utility ServicesUtility Services ……

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Views of DataViews of Data

Levels of AbstractionLevels of Abstraction– External viewExternal view– Conceptual schemaConceptual schema– Physical (Internal schema)Physical (Internal schema)

Data independenceData independence

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Data ModelData Model Way to “picture” and access data independent of Way to “picture” and access data independent of

how it is actually stored.how it is actually stored.– Data DescriptionData Description– Data RelationshipsData Relationships– OperationsOperations– Integrity/Consistency constraintsIntegrity/Consistency constraints

Examples:Examples:– Entity-Relationship (ER/ERA)Entity-Relationship (ER/ERA)– RelationalRelational– Object OrientedObject Oriented– Object/RelationalObject/Relational– Older – Network/HierarchicalOlder – Network/Hierarchical

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Relational Model*Relational Model* Based on tables, as:Based on tables, as:

acct #acct # NameName BalanceBalance

1234512345 SallySally 1000.211000.21

3456734567 SueSue 285.48 285.48

…… …… … … Rows (tuples)Rows (tuples) Columns (attributes)Columns (attributes) Today used in Today used in mostmost DBMS's DBMS's..

Most of the following slides were obtained from the home page for Most of the following slides were obtained from the home page for A First Course in Database SystemsA First Course in Database Systems by Jeffrey D. by Jeffrey D. Ullman and Jennifer Widom, Prentice Hall, 2002, http://www-db.stanford.edu/~ullman/fcdb.htmlUllman and Jennifer Widom, Prentice Hall, 2002, http://www-db.stanford.edu/~ullman/fcdb.html

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Data RelationshipsData Relationships One-to-one (1:1)One-to-one (1:1)

Ex: Name to SSNEx: Name to SSN One-to-many (1:M)One-to-many (1:M)

Ex: Name to PhoneEx: Name to Phone Many-to many (M:n)Many-to many (M:n)

Ex: Part to SupplierEx: Part to Supplier What data structures can be used to What data structures can be used to

store these relationships?store these relationships?

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Database OutlineDatabase Outline IntroductionIntroduction

File Organization & IndexingFile Organization & Indexing Data ModelsData Models Relational ModelRelational Model SQL/Query ProcessingSQL/Query Processing TransactionsTransactions

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Typical Data Structures used Typical Data Structures used in DBMSsin DBMSs

Sequential FilesSequential Files Hash TableHash Table

– Extendible Hash TableExtendible Hash Table B-Tree (Multiway Search Tree)B-Tree (Multiway Search Tree)

– B+-TreeB+-Tree Combinations of theseCombinations of these IndicesIndices

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Placement of Data on DiskPlacement of Data on Disk Record/Cylinder/Block/SectorRecord/Cylinder/Block/Sector Blocking FactorBlocking Factor AllocationAllocation

– ContiguousContiguous– LinkedLinked– ExtentsExtents– IndexedIndexed

ClusteringClustering PartitioningPartitioning RAIDRAID

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Data Structure PointersData Structure Pointers

LogicalLogical– KeyKey– Relative BlockRelative Block

PhysicalPhysical– Memory - Physical Address (offset)Memory - Physical Address (offset)– Disk – Physical Address Disk – Physical Address

» Device/Cylinder/Track/Sector/Block/OffsetDevice/Cylinder/Track/Sector/Block/Offset

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Disk vs. Memory Data Disk vs. Memory Data StructuresStructures

ObjectiveObjective– Disk – minimize I/ODisk – minimize I/O– Memory – minimize memory accesses or Memory – minimize memory accesses or

CPU timeCPU time TreeTree

– Disk – large nodes, shallowDisk – large nodes, shallow– Memory – small nodes. DeepMemory – small nodes. Deep

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AccessAccess

Sequential – Retrieve records in order Sequential – Retrieve records in order (logical/physical)(logical/physical)

Random – Retrieve record based on keyRandom – Retrieve record based on key Direct – Retrieve record based on physical Direct – Retrieve record based on physical

addressaddress Relative – Retrieve record based on relative Relative – Retrieve record based on relative

position in fileposition in file Binary Search – Randomly retrieve record Binary Search – Randomly retrieve record

doing binary searchdoing binary search

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OrganizationOrganization Sequential – Records stored in logical order of Sequential – Records stored in logical order of

key.key.Access: Sequential, relative, binary searchAccess: Sequential, relative, binary search

Heap – Records added to end or where space.Heap – Records added to end or where space.Access: DirectAccess: Direct

Btree – Multiway balanced search tree.Btree – Multiway balanced search tree.Access: Sequential, randomAccess: Sequential, random

Hash – Store and access record based on Hash – Store and access record based on address determined when key is hashed.address determined when key is hashed.Access: RandomAccess: Random

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IndexingIndexing Speed up processing of data by Speed up processing of data by

providing alternative access path.providing alternative access path. Both index and primary storage of data Both index and primary storage of data

provide access method.provide access method. Ex: Ex:

Employee Data

Hash on ID

BTree index on last name

BTree index on job type

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Index TypesIndex Types

Number of entriesNumber of entries– Dense – One index entry for each record in Dense – One index entry for each record in

filefile– Sparse – One index entry for many recordsSparse – One index entry for many records

KeyKey– Primary – Same key as main filePrimary – Same key as main file– Secondary – Different key from original fileSecondary – Different key from original file

Organizations: Hash, BTree, Organizations: Hash, BTree, Sequential, BSTSequential, BST

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Index Search TimesIndex Search TimesOrganizationOrganization WorstWorst ExpectedExpected

SequentialSequential O(n)O(n) O(n/2)O(n/2)

HashHash O(n)O(n) O(1.??)O(1.??)

Tree Tree (Balanced)(Balanced)

O(n)O(n) O(lg n)O(lg n)

B+-TreeB+-Tree O(lg n)O(lg n) O(lg n)O(lg n)

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HashingHashing

Bucket in one block (or cluster thereof)Bucket in one block (or cluster thereof) Hash value may be precise address or Hash value may be precise address or

relative block (bucket) numberrelative block (bucket) number Collisions handled by linked listsCollisions handled by linked lists Dynamic Hashing – Allows hash table Dynamic Hashing – Allows hash table

size to growsize to grow

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Multiple Key IndexingMultiple Key Indexing

Key composed of many subkeysKey composed of many subkeys Access based on all or subset of theseAccess based on all or subset of these Some indexing structures specifically Some indexing structures specifically

targeted to n-dimensional accessingtargeted to n-dimensional accessing

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Database OutlineDatabase Outline IntroductionIntroduction File Organization & IndexingFile Organization & Indexing

Data ModelsData Models Relational ModelRelational Model SQL/Query ProcessingSQL/Query Processing TransactionsTransactions

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Data Model Data Model EvolutionEvolution

Hierarchical

60’s

70's

80's

90’s

now

RelationalChoice for most new

applications

Object Bases Knowledge Bases

Network

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Entity/Relationship ModelEntity/Relationship Model

Diagrams to represent designs.Diagrams to represent designs. EntityEntity like object, = “thing.” like object, = “thing.” Entity setEntity set like class = set of “similar” like class = set of “similar”

entities/objects.entities/objects. AttributeAttribute = property of entities in an entity set. = property of entities in an entity set. In diagrams:In diagrams:

– entity set entity set rectangle rectangle– attribute attribute oval. oval.

Students

ID name phone

height

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RelationshipsRelationships

Connect two or more entity sets.Connect two or more entity sets. Represented by diamonds.Represented by diamonds.

Students CoursesTaking

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Relationship SetRelationship SetThink of the “value” of a relationship set as a table.Think of the “value” of a relationship set as a table. One column for each of the connected entity sets.One column for each of the connected entity sets. One row for each list of entities, one from each set, One row for each list of entities, one from each set,

that are connected by the relationship.that are connected by the relationship.StudentsStudents CoursesCourses

SallySally CS180CS180

SallySally CS111CS111

JoeJoe CS180CS180

…… ……

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StudentsStudents CoursesCourses TAsTAsAnnAnn CS180CS180 JanJanSueSue CS180CS180 PatPatBobBob CS180CS180 JanJan…… …… ……

Students

Courses

TAs

Enrolls

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Beers-Bars-Drinkers ExampleBeers-Bars-Drinkers Examplename addr license

name manf name addr

Beers Drinkers

BarsServes Frequents

Likes

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Multiplicity of RelationshipsMultiplicity of Relationships

Representation of Many-OneRepresentation of Many-One E/R: arrow pointing to “one.”E/R: arrow pointing to “one.”

– Rounded arrow = “exactly one.”Rounded arrow = “exactly one.”

Many-many Many-one One-one

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Example:Example:Drinkers Have Favorite BeersDrinkers Have Favorite Beers

name addr license

name manf name addr

Beers Drinkers

BarsServes Frequents

Likes

Favorite

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One-One RelationshipsOne-One RelationshipsPut arrows in both directions.Put arrows in both directions.

Design Issue:Design Issue:Is the rounded arrow justified?Is the rounded arrow justified?Design Issue:Design Issue:Here, manufacturer is an E.S.Here, manufacturer is an E.S.In earlier diagrams it is an attribute.In earlier diagrams it is an attribute.Which is right?Which is right?

Manfs BeersBest-seller

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Attributes on RelationshipsAttributes on Relationships

Shorthand for 3-way relationship:Shorthand for 3-way relationship:

Bars BeersSells

price

Bars BeersSells

price

Prices

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RolesRoles

Sometimes an E.S. participates more Sometimes an E.S. participates more than once in a relationship.than once in a relationship.

Label edges with Label edges with rolesroles to distinguish. to distinguish.Husband Wifed1 d2d3 d4… …

Drinkers

Married

husband wife

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Notice Notice BuddiesBuddies is symmetric, Married not. is symmetric, Married not.– No way to say “symmetric” in E/R.No way to say “symmetric” in E/R.

Design QuestionDesign Question

Should we replace Should we replace husbandhusband and and wifewife by one by one relationship relationship spousespouse??

Buddy1 Buddy2d1 d2d1 d3d2 d1d2 d4… …

Drinkers

Buddies

1 2

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Multiple InheritanceMultiple InheritanceTheoretically, an E.S. could be a subclass Theoretically, an E.S. could be a subclass

of several other entity sets.of several other entity sets.name manf

Beers

name manf

Wines

GrapeBeers

isaisa

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KeysKeys

A A keykey is a set of attributes whose values can is a set of attributes whose values can belong to at most one entity.belong to at most one entity.

In E/R model, every E.S. must have a key.In E/R model, every E.S. must have a key.– It could have more than one key, but one set of It could have more than one key, but one set of

attributes is the “designated” key.attributes is the “designated” key.

In E/R diagrams, you should underline all In E/R diagrams, you should underline all attributes of the designated key.attributes of the designated key.

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ExampleExample Suppose Suppose namename is key for is key for BeersBeers..

Beer name is also key for ales.Beer name is also key for ales.– In general, key at root is key for all.In general, key at root is key for all.

name manfBeers

Alescolor

isa

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Example: A Multiattribute KeyExample: A Multiattribute Key

Possibly, the combination of hours + Possibly, the combination of hours + room also forms a key, but we have not room also forms a key, but we have not designated it as such.designated it as such.

dept roomCourses

number hours

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Database OutlineDatabase Outline IntroductionIntroduction File Organization & IndexingFile Organization & Indexing Data ModelsData Models

Relational ModelRelational Model SQL/Query ProcessingSQL/Query Processing TransactionsTransactions

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Relational ModelRelational Model Table = Table = relationrelation.. Column headers = Column headers = attributesattributes.. Row = Row = tupletuple

BeersBeers Relation schemaRelation schema = name(attributes) + other structure info., = name(attributes) + other structure info.,

e.g., keys, other constraints. Example: Beers(name, manf)e.g., keys, other constraints. Example: Beers(name, manf)– Order of attributes is arbitrary, but in practice we need to assume Order of attributes is arbitrary, but in practice we need to assume

the order given in the relation schema.the order given in the relation schema. Relation instanceRelation instance is current set of rows for a relation is current set of rows for a relation

schema.schema. Database schemaDatabase schema = collection of relation schemas. = collection of relation schemas.

name manfWinterBrew Pete’sBudLite A.B.… …

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Relation Relation InstanceInstance

NameName AddressAddress TelephoneTelephone

BobBob 123 Main St123 Main St 555-1234555-1234

BobBob 128 Main St128 Main St 555-1235555-1235

PatPat 123 Main St123 Main St 555-1235555-1235

HarryHarry 456 Main St456 Main St 555-2221555-2221

SallySally 456 Main St456 Main St 555-2221555-2221

SallySally 456 Main St456 Main St 555-2223555-2223

PatPat 12 State St12 State St 555-1235555-1235

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Why Relations?Why Relations?

Very simple model.Very simple model. OftenOften a good match for the way we a good match for the way we

think about our data.think about our data. Abstract model that underlies SQL, the Abstract model that underlies SQL, the

most important language in DBMS’s most important language in DBMS’s today.today.

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Relational DesignRelational DesignSimplest approach (not always best): convert each Simplest approach (not always best): convert each

E.S. to a relation and each relationship to a E.S. to a relation and each relationship to a relation.relation.

Entity Set Entity Set Relation RelationE.S. attributes become relational attributes.E.S. attributes become relational attributes.

Becomes:Becomes:Beers(Beers(namename, manf), manf)

Beers

name manf

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Keys in RelationsKeys in Relations

An attribute or set of attributes An attribute or set of attributes KK is a is a keykey for a relation for a relation RR if we expect that in no if we expect that in no instance of instance of RR will two different tuples will two different tuples agree on all the attributes of agree on all the attributes of KK..

Indicate a key by underlining the key Indicate a key by underlining the key attributes.attributes.

Example: If name is a key for Beers:Example: If name is a key for Beers:Beers(Beers(namename, manf), manf)

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E/R Relationships E/R Relationships Relations Relations

Relation has attribute for Relation has attribute for keykey attributes of attributes of each E.S. that participates in the each E.S. that participates in the relationship.relationship.

Add any attributes that belong to the Add any attributes that belong to the relationship itself.relationship itself.

Renaming attributes OK.Renaming attributes OK.– Essential if multiple roles for an E.S.Essential if multiple roles for an E.S.

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Drinkers

For one-one relation Married, we can For one-one relation Married, we can choose either husband or wife as key.choose either husband or wife as key.

Likes(drinker, beer)Favorite(drinker, beer)Married(husband, wife)Buddies(name1, name2)

BeersLikes

name manfname addr

Buddies

Married

Favorite

1 2

husband wife

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Combining RelationsCombining RelationsSometimes it makes sense to combine relations.Sometimes it makes sense to combine relations. Common case: Relation for an E.S. Common case: Relation for an E.S. EE plus the relation for plus the relation for

some many-one relationship from some many-one relationship from EE to another E.S. to another E.S.

ExampleExampleCombine Combine Drinker(Drinker(namename, addr), addr) with with Favorite(Favorite(drinkerdrinker, beer), beer) to get to get

Drinker1(Drinker1(namename, addr, favBeer), addr, favBeer).. Danger in pushing this idea too far: redundancy.Danger in pushing this idea too far: redundancy. e.ge.g., combining Drinker with Likes causes the drinker's ., combining Drinker with Likes causes the drinker's

address to be repeated, viz.:address to be repeated, viz.: namename addraddr beerbeer

SallySally 123 Maple123 Maple BudBudSallySally 123 Maple123 Maple MillerMiller

Notice the difference: Notice the difference: FavoriteFavorite is many-one; is many-one;LikesLikes is many-many. is many-many.

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Keys of RelationsKeys of Relations

KK is a is a keykey for relation for relation RR if: if:

1. 1. KK all attributes of all attributes of RR. . (Uniqueness)(Uniqueness)

2. For no proper subset of 2. For no proper subset of KK is (1) true. is (1) true. (Minimality)(Minimality)

If If KK at least satisfies (1), then at least satisfies (1), then KK is a is a superkeysuperkey..

ConventionsConventions Pick one key; underline key attributes in the Pick one key; underline key attributes in the

relation schema.relation schema.

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ExampleExampleDrinkers(Drinkers(namename, addr, , addr, beersLikedbeersLiked, manf, favoriteBeer), manf, favoriteBeer) {name, beersLiked} FD’s all attributes, as seen.{name, beersLiked} FD’s all attributes, as seen.

– Shows {Shows {name, beersLikedname, beersLiked} is a superkey.} is a superkey.

name name beersLiked is false, so name not a superkey. beersLiked is false, so name not a superkey.

beersLiked beersLiked name also false, so beersLiked not a name also false, so beersLiked not a

superkey. superkey. Thus, {name, beersLiked} is a key.Thus, {name, beersLiked} is a key. No other keys in this example.No other keys in this example.

– Neither Neither namename nor nor beersLikedbeersLiked is on the right of any observed is on the right of any observed

FD, so they must be part of FD, so they must be part of anyany superkey. superkey.

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Example 2Example 2

Keys are Keys are {Lastname, Firstname}{Lastname, Firstname} and and {StudentID}{StudentID}

Lastname Firstname Student ID Major

Key Key

(2 attributes)

Superkey

Note: There are alternate keys

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NormalizationNormalization Process of simplifying relational design:Process of simplifying relational design:

– Avoid redundancyAvoid redundancy Functional Dependencies (FD)Functional Dependencies (FD)

– Identify relationships between data valuesIdentify relationships between data values– SSN SSN Name Name

» In any tuple, the value for SSN determines a unique value In any tuple, the value for SSN determines a unique value for Name.for Name.

» If the same SSN exists in two tuples, you’ll have the same If the same SSN exists in two tuples, you’ll have the same Name duplicated.Name duplicated.

FDs are used by algorithms to determine best FDs are used by algorithms to determine best relations to be used given a set of attributes. relations to be used given a set of attributes.

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Example of ProblemsExample of ProblemsDrinkers(Drinkers(namename, addr, , addr, beersLikedbeersLiked, manf, favoriteBeer), manf, favoriteBeer)

FD’s:FD’s:1. name 1. name addr addr2. name 2. name favoriteBeer favoriteBeer3. beersLiked 3. beersLiked manf manf ???’s are redundant, since we can figure them out from the ???’s are redundant, since we can figure them out from the

FD’s.FD’s. Update anomalies: If Janeway gets transferred to the Update anomalies: If Janeway gets transferred to the

IntrepidIntrepid, will we change addr in each of her tuples?, will we change addr in each of her tuples? Deletion anomalies: If nobody likes Bud, we lose track of Deletion anomalies: If nobody likes Bud, we lose track of

Bud’s manufacturer.Bud’s manufacturer.

name addr beersLikedmanf favoriteBeer

J aneway Voyager Bud A.B. WickedAleJ aneway ??? WickedAle Pete's ???Spock Enterprise Bud ??? Bud

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Database OutlineDatabase Outline IntroductionIntroduction File Organization & IndexingFile Organization & Indexing Data ModelsData Models Relational ModelRelational Model

SQL/Query ProcessingSQL/Query Processing TransactionsTransactions

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““Core” Relational AlgebraCore” Relational AlgebraA small set of operators that allow us to manipulate A small set of operators that allow us to manipulate

relations in limited but useful ways. The operators relations in limited but useful ways. The operators are:are:

1.1. Union, intersection, and difference: the usual set Union, intersection, and difference: the usual set operators.operators.– But the relation schemas must be the same.But the relation schemas must be the same.

2.2. SelectionSelection: Picking certain rows from a relation.: Picking certain rows from a relation.

3.3. ProjectionProjection: Picking certain columns.: Picking certain columns.

4.4. Products and joinsProducts and joins: Composing relations in useful : Composing relations in useful ways.ways.

5.5. RenamingRenaming of relations and their attributes. of relations and their attributes.

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SelectionSelectionRR11 = = CC((RR22))

where where CC is a condition involving the attributes of relation is a condition involving the attributes of relation RR22..

ExampleExampleRelation Sells:Relation Sells:

JoeMenu = JoeMenu = bar=Joe'sbar=Joe's(Sells)(Sells)

bar beer priceJoe's Bud 2.50Joe's Miller 2.75Sue's Bud 2.50Sue's Coors 3.00

bar beer priceJoe's Bud 2.50Joe's Miller 2.75

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ProjectionProjectionRR11 = = LL((RR22))

where where LL is a list of attributes from the is a list of attributes from the schema of schema of RR22..

ExampleExamplebeer,pricebeer,price(Sells)(Sells)

Notice elimination of duplicate tuples.Notice elimination of duplicate tuples.

beer priceBud 2.50Miller 2.75Coors 3.00

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ProductProduct

RR = = RR11 RR22

pairs each tuple pairs each tuple tt11 of of RR11 with each tuple with each tuple tt22

of of RR22 and puts in and puts in RR a tuple a tuple tt11tt22..

A B C D D E F A B C D D' E F

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Sells Bars Sells Bars

BarInfo = Sells BarInfo = Sells Sells.Bar=Bars.NameSells.Bar=Bars.Name Bars Bars

bar beer priceJoe's Bud 2.50Joe's Miller 2.75Sue's Bud 2.50Sue's Coors 3.00

name addrJoe's Maple St.Sue's River Rd.

bar beer price name addrJoe's Bud 2.50 Joe's Maple St.Joe's Miller 2.75 Joe's Maple St.Sue's Bud 2.50 Sue's River Rd.Sue's Coors 3.00 Sue's River Rd.

JoinJoin

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SQLSQL

SEQUEL in System RSEQUEL in System R Structured English QUEry LanguageStructured English QUEry Language DDL and DMLDDL and DML Standard Relational query languageStandard Relational query language

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SQL OperationsSQL Operations

SELECT … FROM … WHERE …SELECT … FROM … WHERE … UPDATE … SET … WHERE …UPDATE … SET … WHERE … INSERT INTO … VALUES (…)INSERT INTO … VALUES (…) DELETE … WHERE …DELETE … WHERE …

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SQLSQLEmployee

Name Dept

Department

Dept Manager

SQL

SELECT ManagerSELECT ManagerFROM Employee, DepartmentFROM Employee, DepartmentWHERE Employee.name = "Clark Kent”WHERE Employee.name = "Clark Kent”

AND Employee.Dept = Department.DeptAND Employee.Dept = Department.Dept

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Host Host Languages Languages

C, C++, Fortran, Lisp, COBOL

Application prog.

Local Vars

DBMS

Calls toDB

(Memory)

(Storage) Different DBMSs support different Different DBMSs support different host language interfaces host language interfaces

PrecompilerPrecompiler ODBC/JDBCODBC/JDBC

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Embedded SQLEmbedded SQL

Add to a conventional programming Add to a conventional programming language (C in our examples) certain language (C in our examples) certain statements that represent SQL statements that represent SQL operations.operations.

Each embedded SQL statement Each embedded SQL statement introduced with EXEC SQL.introduced with EXEC SQL.

Preprocessor converts C + SQL to pure Preprocessor converts C + SQL to pure C.C.– SQL statements become procedure calls.SQL statements become procedure calls.

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ExampleExampleFind the price for a given beer at a given bar.Find the price for a given beer at a given bar.

Sells(Sells(barbar, , beerbeer, price), price)

EXEC SQL BEGIN DECLARE SECTION;EXEC SQL BEGIN DECLARE SECTION;char theBar[21], theBeer[21];char theBar[21], theBeer[21];float thePrice;float thePrice;

EXEC SQL END DECLARE SECTION;EXEC SQL END DECLARE SECTION;. . .. . .

/* assign to theBar and theBeer *//* assign to theBar and theBeer */. . .. . .

EXEC SQL SELECT priceEXEC SQL SELECT priceINTO :thePriceINTO :thePriceFROM SellsFROM SellsWHERE beer = :theBeer ANDWHERE beer = :theBeer AND

bar = :theBar;bar = :theBar;. . .. . .

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Call-Level InterfacesCall-Level InterfacesA more modern approach to the host-A more modern approach to the host-

language/SQL connection is a language/SQL connection is a call-level call-level interfaceinterface, in which the C (or other language) , in which the C (or other language) program creates SQL statements as program creates SQL statements as character strings and passes them to character strings and passes them to functions that are part of a library.functions that are part of a library.

Similar to what really happens in embedded Similar to what really happens in embedded SQL implementations.SQL implementations.

Two major approaches: SQL/CLI (standard of Two major approaches: SQL/CLI (standard of ODBC = ODBC = open database connectivityopen database connectivity) and ) and JDBC (Java database connectivity).JDBC (Java database connectivity).

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JDBCJDBC Start with a Start with a ConnectionConnection object, obtained from the DBMS (see text). object, obtained from the DBMS (see text). Method Method createStatementcreateStatement() returns an object of class () returns an object of class StatementStatement (if (if

there is no argument) or there is no argument) or PreparedStatementPreparedStatement if there is an SQL if there is an SQL statement as argument.statement as argument.

ExampleExampleStatement stat1 = myCon.createStatement();Statement stat1 = myCon.createStatement();PreparedStatement stat2 =PreparedStatement stat2 =

myCon.createStatement(myCon.createStatement("SELECT beer, price " +"SELECT beer, price " +"FROM Sells" +"FROM Sells" +"WHERE bar = 'Joe''s Bar'""WHERE bar = 'Joe''s Bar'"

);); myCon is a connection, stat1 is an “empty” statement object, and myCon is a connection, stat1 is an “empty” statement object, and

stat2 is a (prepared) statement object that has an SQL statement stat2 is a (prepared) statement object that has an SQL statement associated.associated.

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Executing StatementsExecuting Statements JDBC distinguishes queries from JDBC distinguishes queries from updatesupdates Methods Methods executeQueryexecuteQuery() and () and executeUpdateexecuteUpdate() ()

are used to execute these two kinds of SQL are used to execute these two kinds of SQL statements.statements.

When a query is executed, it returns an object When a query is executed, it returns an object of class of class ResultSetResultSet..

ExampleExamplestat1.executeUpdate(stat1.executeUpdate("INSERT INTO Sells" +"INSERT INTO Sells" +"VALUES('Brass Rail', 'Bud', 3.00)""VALUES('Brass Rail', 'Bud', 3.00)"););ResultSet Menu = stat2.executeQuery();ResultSet Menu = stat2.executeQuery();

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Getting the Tuples of a Getting the Tuples of a ResultSetResultSet Method Method NextNext() applies to a () applies to a ResultSetResultSet and moves a and moves a

“cursor” to the next tuple in that set.“cursor” to the next tuple in that set.– Apply Apply NextNext() once to get to the first tuple.() once to get to the first tuple.– NextNext() returns FALSE if there are no more tuples.() returns FALSE if there are no more tuples.

While a given tuple is the current of the cursor, you While a given tuple is the current of the cursor, you can get its can get its iith component by applying to a th component by applying to a ResultSetResultSet a method of the form get a method of the form get XX(i), where (i), where XX is the name is the name for the type of that component.for the type of that component.

ExampleExamplewhile(Menu.Next()) {while(Menu.Next()) {

theBeer = Menu.getString(1);theBeer = Menu.getString(1);thePrice = Menu.getFloat(2);thePrice = Menu.getFloat(2);

......}}

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Database OutlineDatabase Outline IntroductionIntroduction File Organization & IndexingFile Organization & Indexing Data ModelsData Models Relational ModelRelational Model SQL/Query ProcessingSQL/Query Processing

TransactionsTransactions

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TransactionsTransactions= units of work that must be:= units of work that must be:1.1. AtomicAtomic = either all work is done, or none of it. = either all work is done, or none of it.2.2. ConsistentConsistent = relationships among values = relationships among values

maintained.maintained.3.3. IsolatedIsolated = appear to have been executed = appear to have been executed

when no other DB operations were being when no other DB operations were being performed.performed.

– Often called Often called serializableserializable behavior. behavior.

4.4. DurableDurable = effects are permanent even if = effects are permanent even if system crashes.system crashes.

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Commit/Abort DecisionCommit/Abort Decision

Each transaction ends with either:Each transaction ends with either:

1.1. CommitCommit = the work of the transaction is installed = the work of the transaction is installed in the database; previously its changes may be in the database; previously its changes may be invisible to other transactions.invisible to other transactions.

2.2. AbortAbort = no changes by the transaction appear in = no changes by the transaction appear in the database; it is as if the transaction never the database; it is as if the transaction never occurred.occurred.

– ROLLBACK is the term used in SQL and the Oracle ROLLBACK is the term used in SQL and the Oracle systemsystem

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ExampleExampleSells(Sells(barbar, , beerbeer, price), price)

Joe's Bar sells Bud for $2.50 and Miller for $3.00.Joe's Bar sells Bud for $2.50 and Miller for $3.00. Sally is querying the database for the highest and lowest Sally is querying the database for the highest and lowest

price Joe charges:price Joe charges:(1)(1) SELECT MAX(price) FROM SellsSELECT MAX(price) FROM Sells

WHERE bar = 'Joe''s Bar';WHERE bar = 'Joe''s Bar';(2)(2) SELECT MIN(price) FROM SellsSELECT MIN(price) FROM Sells

WHERE bar = 'Joe''s Bar';WHERE bar = 'Joe''s Bar'; At the same time, Joe has decided to replace Miller and Bud At the same time, Joe has decided to replace Miller and Bud

by Heineken at $3.50:by Heineken at $3.50:((3)3) DELETE FROM SellsDELETE FROM Sells

WHERE bar = 'Joe''s Bar' ANDWHERE bar = 'Joe''s Bar' AND (beer = 'Miller' OR beer = 'Bud');(beer = 'Miller' OR beer = 'Bud');

(4)(4) INSERT INTO SellsINSERT INTO SellsVALUES('Joe''s bar', 'Heineken', 3.50);VALUES('Joe''s bar', 'Heineken', 3.50);

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Example: Problem With RollbackExample: Problem With Rollback

Suppose Joe executes statement 4 (insert Suppose Joe executes statement 4 (insert Heineken), but then, during the transaction thinks Heineken), but then, during the transaction thinks better of it and issues a ROLLBACK statement.better of it and issues a ROLLBACK statement.

If Sally is allowed to execute her statement 1 (find If Sally is allowed to execute her statement 1 (find max) just before the rollback, she gets the answer max) just before the rollback, she gets the answer $3.50, even though Joe doesn't sell any beer for $3.50, even though Joe doesn't sell any beer for $3.50.$3.50.

Fix by making statement 4 a transaction, or part of Fix by making statement 4 a transaction, or part of a transaction, so its effects cannot be seen by a transaction, so its effects cannot be seen by Sally unless there is a COMMIT action.Sally unless there is a COMMIT action.

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Deadlock Deadlock ANDAND

1. Wait and hold hold some locks while you wait for others1. Wait and hold hold some locks while you wait for others

2. Circular chain of waiters T42. Circular chain of waiters T4

wait-for graph T1 T3wait-for graph T1 T3

T2T2

3. No pre-emption3. No pre-emption

We can avoid deadlock by doing at least ONE of:We can avoid deadlock by doing at least ONE of:

1. Get all your locks at once1. Get all your locks at once

2. Apply an ordering to acquiring locks2. Apply an ordering to acquiring locks

3. Allow preemption (for example, use timeout on waits)3. Allow preemption (for example, use timeout on waits)

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Serializability of schedulesSerializability of schedulesT1T1

Read (A)Read (A)A:= A-50A:= A-50Write (A)Write (A)Read (B)Read (B)B:= B+50B:= B+50Write (B)Write (B)

Schedule is serializable if effect is the same as Schedule is serializable if effect is the same as a serial schedulea serial schedule

T1 –> T2 T2 –> T1T1 –> T2 T2 –> T1A= A=A= A=B= B= B= B=

T2Read (A)temp:= A * 0.1A:= A + tempWrite (A)Read (B)B:= B - tempWrite (B)

A Bdisk 100 200

T1

T2

T1 T2

A

B

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If no progress is possible, then there is a cycle

T3

T6

T4

T5

A

A B

C

T1T2T3T4T5T6T2

T1

D

C

D

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Cascading AbortCascading Abort

T1T1 T2T2LOCK ALOCK ARead ARead Achange Achange AWrite AWrite AUNLOCK AUNLOCK A

LOCK ALOCK ARead ARead Achange Achange AWrite AWrite AUNLOCK AUNLOCK A

LOCK BLOCK BRead BRead BDiscover problemDiscover problemABORTABORT

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Two-Phase Locking (2PL)Two-Phase Locking (2PL)

Phase I: All requesting of locks precedesPhase I: All requesting of locks precedes Phase II: Any releasing of locksPhase II: Any releasing of locks

Theorem: Any schedule for 2-phase locked Theorem: Any schedule for 2-phase locked transaction is serializabletransaction is serializable

Time

Locks