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Chapter 2: Relational Model




          Database System Concepts, 1 st Ed.
 © VNS InfoSolutions Private Limited, Varanasi(UP), India 221002
          See www.vnsispl.com for conditions on re-use
Chapter 2: Relational Model
            s Structure of Relational Databases
            s Fundamental Relational-Algebra-Operations
            s Additional Relational-Algebra-Operations
            s Extended Relational-Algebra-Operations
            s Null Values
            s Modification of the Database




Database System Concepts – 1 st Ed.           2.2   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example of a Relation




Database System Concepts – 1 st Ed.            2.3   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Basic Structure
        s Formally, given sets D1, D2, …. Dn a relation r is a subset of
                     D1 x D2 x … x Dn
             Thus, a relation is a set of n-tuples (a1, a2, …, an) where each ai ∈ Di

        s Example: If

               q   customer_name = {Jones, Smith, Curry, Lindsay, …}
                                                        /* Set of all customer names */
               q   customer_street = {Main, North, Park, …} /* set of all street names*/
               q   customer_city           = {Harrison, Rye, Pittsfield, …} /* set of all city names */
               Then r = {             (Jones, Main, Harrison),
                                      (Smith,   North, Rye),
                                      (Curry,   North, Rye),
                                      (Lindsay, Park, Pittsfield) }
                    is a relation over
                      customer_name x customer_street x customer_city
Database System Concepts – 1 st Ed.                        2.4   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Attribute Types
            s Each attribute of a relation has a name
            s The set of allowed values for each attribute is called the domain of the
                 attribute
            s Attribute values are (normally) required to be atomic; that is, indivisible
                   q   E.g. the value of an attribute can be an account number,
                       but cannot be a set of account numbers
            s Domain is said to be atomic if all its members are atomic
            s The special value null is a member of every domain
            s The null value causes complications in the definition of many operations
                   q   We shall ignore the effect of null values in our main presentation
                       and consider their effect later




Database System Concepts – 1 st Ed.                  2.5   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Relation Schema
            s A1, A2, …, An are attributes


            s R = (A1, A2, …, An ) is a relation schema

                 Example:
                 Customer_schema = (customer_name, customer_street, customer_city)


            s r(R) denotes a relation r on the relation schema R
                 Example:
                 customer (Customer_schema)




Database System Concepts – 1 st Ed.             2.6   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Relation Instance
            s The current values (relation instance) of a relation are specified by a
                 table
            s An element t of r is a tuple, represented by a row in a table




                                                                                        attributes
                                                                                      (or columns)
                          customer_name customer_street       customer_city

                           Jones         Main               Harrison
                           Smith         North              Rye                             tuples
                           Curry         North              Rye                           (or rows)
                           Lindsay       Park               Pittsfield

                                            customer




Database System Concepts – 1 st Ed.              2.7   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Relations are Unordered

            s Order of tuples is irrelevant (tuples may be stored in an arbitrary order)
            s Example: account relation with unordered tuples




Database System Concepts – 1 st Ed.               2.8   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Database
            s    A database consists of multiple relations
            s    Information about an enterprise is broken up into parts, with each relation
                 storing one part of the information

                         account : stores information about accounts
                        depositor : stores information about which customer
                                     owns which account
                        customer : stores information about customers
            s    Storing all information as a single relation such as
                   bank(account_number, balance, customer_name, ..)
                 results in
                   q   repetition of information
                            e.g.,if two customers own an account (What gets repeated?)
                   q   the need for null values
                            e.g., to represent a customer without an account
            s    Normalization theory (Chapter 7) deals with how to design relational schemas


Database System Concepts – 1 st Ed.                       2.9   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The customer Relation




Database System Concepts – 1 st Ed.        2.10   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The depositor Relation




Database System Concepts – 1 st Ed.        2.11   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Keys
       s Let K ⊆ R
       s K is a superkey of R if values for K are sufficient to identify a unique tuple of
            each possible relation r(R)
              q   by “possible r ” we mean a relation r that could exist in the enterprise we
                  are modeling.
              q   Example: {customer_name, customer_street} and
                                  {customer_name}
                  are both superkeys of Customer, if no two customers can possibly have
                  the same name
                       In real life, an attribute such as customer_id would be used instead of
                        customer_name to uniquely identify customers, but we omit it to keep
                        our examples small, and instead assume customer names are unique.




Database System Concepts – 1 st Ed.                  2.12   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Keys (Cont.)
            s K is a candidate key if K is minimal
                 Example: {customer_name} is a candidate key for Customer, since it
                 is a superkey and no subset of it is a superkey.
            s Primary key: a candidate key chosen as the principal means of
                 identifying tuples within a relation
                   q   Should choose an attribute whose value never, or very rarely,
                       changes.
                   q   E.g. email address is unique, but may change




Database System Concepts – 1 st Ed.                 2.13   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Foreign Keys
            s A relation schema may have an attribute that corresponds to the primary
                 key of another relation. The attribute is called a foreign key.
                   q   E.g. customer_name and account_number attributes of depositor are
                       foreign keys to customer and account respectively.
                   q   Only values occurring in the primary key attribute of the referenced
                       relation may occur in the foreign key attribute of the referencing
                       relation.
            s Schema diagram




Database System Concepts – 1 st Ed.                2.14   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Query Languages
             s Language in which user requests information from the database.
             s Categories of languages
                   q    Procedural
                   q    Non-procedural, or declarative
             s “Pure” languages:
                   q    Relational algebra
                   q    Tuple relational calculus
                   q    Domain relational calculus
             s Pure languages form underlying basis of query languages that people
                  use.




Database System Concepts – 1 st Ed.                  2.15   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Relational Algebra
            s Procedural language
            s Six basic operators

                   q   select: σ
                   q   project: ∏
                   q   union: ∪
                   q   set difference: –
                   q   Cartesian product: x
                   q   rename: ρ
            s The operators take one or two relations as inputs and produce a new
                 relation as a result.




Database System Concepts – 1 st Ed.           2.16   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Select Operation – Example
            s Relation r
                                      A   B   C      D

                                      α   α   1      7
                                      α   β   5      7
                                      β   β   12     3
                                      β   β   23 10



              σA=B ^ D > 5 (r)
                                      A   B    C      D

                                      α   α    1      7
                                      β   β   23 10



Database System Concepts – 1 st Ed.           2.17   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Select Operation
            s    Notation: σ p(r)
            s    p is called the selection predicate
            s    Defined as:

                                      σp(r) = {t | t ∈ r and p(t)}

                 Where p is a formula in propositional calculus consisting of terms
                 connected by : ∧ (and), ∨ (or), ¬ (not)
                 Each term is one of:
                                      <attribute>        op <attribute> or <constant>
                where op is one of: =, ≠, >, ≥. <. ≤

            s    Example of selection:

                                      σ branch_name=“ Perryridge” (account)




Database System Concepts – 1 st Ed.                                2.18   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Project Operation – Example
            s Relation r:                 A   B    C

                                          α   10   1
                                          α   20   1
                                          β   30   1
                                          β   40   2



            ∏A,C (r)                  A   C        A    C

                                      α   1        α    1
                                      α   1   =    β    1
                                      β   1        β    2
                                      β   2



Database System Concepts – 1 st Ed.                    2.19   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Project Operation
            s Notation:
                                           ∏    A1 , A2 ,, Ak   (r )
                 where A1, A2 are attribute names and r is a relation name.
            s The result is defined as the relation of k columns obtained by erasing
                 the columns that are not listed
            s Duplicate rows removed from result, since relations are sets
            s Example: To eliminate the branch_name attribute of account

                                      ∏account_number, balance (account)




Database System Concepts – 1 st Ed.                              2.20   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Union Operation – Example
            s Relations r, s:
                                      A       B                   A       B

                                      α       1                   α       2
                                      α       2                   β       3
                                      β       1                       s
                                          r


                                                  A     B

            s r ∪ s:                              α      1
                                                  α      2
                                                  β      1
                                                  β      3



Database System Concepts – 1 st Ed.                   2.21   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Union Operation
            s Notation: r ∪ s
            s Defined as:
                                      r ∪ s = {t | t ∈ r or t ∈ s}
            s For r ∪ s to be valid.
                 1. r, s must have the same arity (same number of attributes)
                 2. The attribute domains must be compatible (example: 2nd column
                    of r deals with the same type of values as does the 2nd
                    column of s)

            s Example: to find all customers with either an account or a loan

                     ∏customer_name (depositor) ∪ ∏customer_name (borrower)




Database System Concepts – 1 st Ed.                         2.22   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Set Difference Operation – Example
            s Relations r, s:
                                      A       B                    A       B

                                      α       1                    α       2
                                      α       2                    β       3
                                      β       1                        s
                                          r


            s r – s:
                                                  A      B

                                                  α      1
                                                  β      1




Database System Concepts – 1 st Ed.                   2.23   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Set Difference Operation
            s Notation r – s
            s Defined as:
                          r – s = {t | t ∈ r and t ∉ s}


            s Set differences must be taken between compatible
                 relations.
                   q   r and s must have the same arity
                   q   attribute domains of r and s must be compatible




Database System Concepts – 1 st Ed.                       2.24   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Cartesian-Product Operation –
                                  Example
            s Relations r, s:
                                      A       B               C      D      E

                                      α       1               α      10     a
                                                              β      10     a
                                      β       2               β      20     b
                                          r                   γ      10     b
                                                                       s
            s r x s:
                                      A       B   C   D       E
                                      α       1   α   10      a
                                      α       1   β   10      a
                                      α       1   β   20      b
                                      α       1   γ   10      b
                                      β       2   α   10      a
                                      β       2   β   10      a
                                      β       2   β   20      b
                                      β       2   γ   10      b


Database System Concepts – 1 st Ed.                        2.25   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Cartesian-Product Operation
            s Notation r x s
            s Defined as:
                                      r x s = {t q | t ∈ r and q ∈ s}

            s Assume that attributes of r(R) and s(S) are disjoint. (That is, R ∩ S = ∅).
            s If attributes of r(R) and s(S) are not disjoint, then renaming must be
                 used.




Database System Concepts – 1 st Ed.                        2.26   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Composition of Operations
            s Can build expressions using multiple operations
            s Example: σA=C(r x s)
            s rxs
                                      A   B   C   D    E
                                      α   1   α   10   a
                                      α   1   β   10   a
                                      α   1   β   20   b
                                      α   1   γ   10   b
                                      β   2   α   10   a
                                      β   2   β   10   a
                                      β   2   β   20   b
                                      β   2   γ   10   b

            s σA=C(r x s)

                                      A   B   C   D    E

                                      α   1   α 10     a
                                      β   2   β 10     a
                                      β   2   β 20     b

Database System Concepts – 1 st Ed.                        2.27   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Rename Operation
            s Allows us to name, and therefore to refer to, the results of relational-
                 algebra expressions.
            s Allows us to refer to a relation by more than one name.
            s Example:

                                               ρ x (E)

                 returns the expression E under the name X
            s If a relational-algebra expression E has arity n, then

                                      ρx ( A ,A
                                           1    2 ,..., An   )   (E )

                 returns the result of expression E under the name X, and with the
                 attributes renamed to A1 , A2 , … An .
                                                  .,




Database System Concepts – 1 st Ed.                               2.28   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Banking Example
            branch (branch_name, branch_city, assets)

            customer (customer_name, customer_street, customer_city)

            account (account_number, branch_name, balance)

            loan (loan_number, branch_name, amount)

            depositor (customer_name, account_number)

            borrower (customer_name, loan_number)




Database System Concepts – 1 st Ed.           2.29   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Queries
             s Find all loans of over $1200


                                 σamount > 1200 (loan)


             s Find the loan number for each loan of an amount greater than
                              $1200

                                ∏loan_number (σamount > 1200 (loan))

             s Find the names of all customers who have a loan, an account, or both,
                  from the bank

                             ∏customer_name (borrower) ∪ ∏customer_name (depositor)



Database System Concepts – 1 st Ed.                  2.30   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Queries
            s Find the names of all customers who have a loan at the Perryridge
                 branch.

                                      ∏customer_name (σbranch_name=“           Perryridge”

                            (σborrower.loan_number = loan.loan_number(borrower x loan)))

            s Find the names of all customers who have a loan at the
                Perryridge branch but do not have an account at any branch of
                the bank.

            ∏customer_name (σbranch_name = “ Perryridge”

             (σborrower.loan_number = loan.loan_number(borrower x loan))) –

                 ∏customer_name(depositor)


Database System Concepts – 1 st Ed.                   2.31   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Queries
            s Find the names of all customers who have a loan at the Perryridge branch.


                  q    Query 1

                         ∏customer_name (σbranch_name = “Perryridge” (
                         σborrower.loan_number = loan.loan_number (borrower x loan)))

                 q      Query 2

                  ∏customer_name(σloan.loan_number = borrower.loan_number (

                                      (σbranch_name = “Perryridge” (loan)) x borrower))



Database System Concepts – 1 st Ed.                    2.32   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Queries
         s    Find the largest account balance
                q   Strategy:
                         Find those balances that are not the largest
                           – Rename account relation as d so that we can compare each
                             account balance with all others
                         Use set difference to find those account balances that were not found
                          in the earlier step.
                q   The query is:


                      ∏balance(account) - ∏account.balance
                           (σaccount.balance < d.balance (account x ρd (account)))




Database System Concepts – 1 st Ed.                      2.33   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Formal Definition
            s A basic expression in the relational algebra consists of either one of the
                 following:
                  q   A relation in the database
                  q   A constant relation
            s Let E1 and E2 be relational-algebra expressions; the following are all
                 relational-algebra expressions:

                  q   E1 ∪ E2

                  q   E1 – E2

                  q   E1 x E2

                  q   σp (E1), P is a predicate on attributes in E1

                  q   ∏s(E1), S is a list consisting of some of the attributes in E1

                  q   ρ (E ), x is the new name for the result of E1 Private Limited, Varanasi(UP), India 22100
Database System Conceptsx 1 st Ed.
                         –     1                  2.34 ©VNS InfoSolutions
Additional Operations
            We define additional operations that do not add any power to the
            relational algebra, but that simplify common queries.

            s Set intersection
            s Natural join
            s Division
            s Assignment




Database System Concepts – 1 st Ed.             2.35   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Set-Intersection Operation
            s Notation: r ∩ s
            s Defined as:
            s r ∩ s = { t | t ∈ r and t ∈ s }
            s Assume:
                   q   r, s have the same arity
                   q   attributes of r and s are compatible
            s Note: r ∩ s = r – (r – s)




Database System Concepts – 1 st Ed.                 2.36   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Set-Intersection Operation –
                                    Example

            s Relation r, s:
                                          A           B          A         B
                                          α       1                α       2
                                          α       2                β       3
                                          β       1

                                              r                        s

            s r∩s

                                      A           B

                                      α           2




Database System Concepts – 1 st Ed.                       2.37   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Natural-Join Operation
            s     Notation: r         s
            s Let r and s be relations on schemas R and S respectively.
                 Then, r          s is a relation on schema R ∪ S obtained as follows:
                   q   Consider each pair of tuples tr from r and ts from s.

                   q   If tr and ts have the same value on each of the attributes in R ∩ S, add a
                       tuple t to the result, where

                              t has the same value as tr on r

                              t has the same value as ts on s
            s Example:
                   R = (A, B, C, D)
                   S = (E, B, D)
                   q   Result schema = (A, B, C, D, E)
                   q   r       s is defined as:
Database System Concepts – 1 st Ed.                      2.38   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Natural Join Operation – Example
            s Relations r, s:


                           A     B        C   D                           B     D      E

                           α     1        α   a                           1     a      α
                           β     2        γ   a                           3     a      β
                           γ     4        β   b                           1     a      γ
                           α     1        γ   a                           2     b      δ
                           δ     2        β   b                           3     b      ∈
                                      r                                         s

            s r        s
                                                  A   B   C      D      E
                                                  α   1   α      a      α
                                                  α   1   α      a      γ
                                                  α   1   γ      a      α
                                                  α   1   γ      a      γ
                                                  δ   2   β      b      δ

Database System Concepts – 1 st Ed.                           2.39   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Division Operation

                s Notation:           r÷s
                s Suited to queries that include the phrase “for all”.
                s Let r and s be relations on schemas R and S respectively
                  where
                       q   R = (A1, …, Am , B1, …, Bn )
                       q   S = (B1, …, Bn)
                       The result of r ÷ s is a relation on schema
                       R – S = (A1, …, Am)

                             r ÷ s = { t | t ∈ ∏ R-S (r) ∧ ∀ u ∈ s ( tu ∈ r ) }

                       Where tu means the concatenation of tuples t and u to
                           produce a single tuple



Database System Concepts – 1 st Ed.                      2.40   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Division Operation – Example
             s Relations r, s:
                                          A       B                B
                                          α       1
                                                                   1
                                          α       2
                                          α       3                2
                                          β       1                s
                                          γ       1
                                          δ       1
                                          δ       3
                                          δ       4
                                          ∈       6
                                          ∈       1
                                          β       2
             s r ÷ s:                 A       r

                                      α
                                      β

Database System Concepts – 1 st Ed.                   2.41   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Another Division Example
             s Relations r, s:
                                      A   B   C     D    E                        D       E

                                      α   a    α    a       1                     a       1
                                      α   a     γ   a       1                     b       1
                                      α   a     γ   b       1                         s
                                      β   a     γ   a       1
                                      β   a     γ   b       3
                                      γ   a     γ   a       1
                                      γ   a     γ   b       1
                                      γ   a    β    b       1
                                              r
             s r ÷ s:
                                              A     B   C

                                              α     a   γ
                                              γ     a   γ


Database System Concepts – 1 st Ed.                     2.42    ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Division Operation (Cont.)
            s    Property
                   q   Let q = r ÷ s
                   q   Then q is the largest relation satisfying q x s ⊆ r
            s    Definition in terms of the basic algebra operation
                 Let r(R) and s(S) be relations, and let S ⊆ R


                            r ÷ s = ∏R-S (r ) – ∏R-S ( ( ∏R-S (r ) x s ) – ∏R-S,S(r ))


                 To see why
                   q   ∏R-S,S (r) simply reorders attributes of r


                   q   ∏R-S (∏R-S (r ) x s ) – ∏R-S,S(r) ) gives those tuples t in

                        ∏R-S (r ) such that for some tuple u ∈ s, tu ∉ r.




Database System Concepts – 1 st Ed.                          2.43   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Assignment Operation
             s    The assignment operation (←) provides a convenient way to express
                  complex queries.
                  q    Write query as a sequential program consisting of
                            a series of assignments
                            followed by an expression whose value is displayed as a result of
                             the query.
                  q   Assignment must always be made to a temporary relation variable.
             s    Example: Write r ÷ s as

                                       temp1 ← ∏R-S (r )
                                       temp2 ← ∏R-S ((temp1 x s ) – ∏R-S,S (r ))
                                       result = temp1 – temp2
                  q   The result to the right of the ← is assigned to the relation variable on
                      the left of the ←.
                  q   May use variable in subsequent expressions.




Database System Concepts – 1 st Ed.                         2.44   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Bank Example Queries
            s Find the names of all customers who have a loan and an account at
                bank.

                    ∏customer_name (borrower) ∩ ∏customer_name (depositor)



            s Find the name of all customers who have a loan at the bank and the
                 loan amount

                     ∏customer_name, loan_number, amount (borrower           loan)




Database System Concepts – 1 st Ed.                2.45   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Bank Example Queries
            s Find all customers who have an account from at least the “Downtown”
                 and the Uptown” branches.
                q Query 1

                       ∏customer_name (σbranch_name = “Downtown” (depositor            account )) ∩

                              ∏customer_name (σbranch_name = “Uptown” (depositor          account))

                   q   Query 2

                        ∏customer_name, branch_name (depositor            account)

                                 ÷ ρtemp(branch_name) ({(“ Downtown” ), (“ Uptown” )})

                   Note that Query 2 uses a constant relation.




Database System Concepts – 1 st Ed.                      2.46   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Bank Example Queries
            s Find all customers who have an account at all branches located in
                 Brooklyn city.

                          ∏customer_name, branch_name (depositor            account)
                          ÷ ∏branch_name (σbranch_city = “Brooklyn” (branch))




Database System Concepts – 1 st Ed.                  2.47   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Extended Relational-Algebra-
                                   Operations
            s Generalized Projection
            s Aggregate Functions
            s Outer Join




Database System Concepts – 1 st Ed.    2.48   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Generalized Projection
            s Extends the projection operation by allowing arithmetic functions to be
                 used in the projection list.


                                            ∏ F1 ,F2 ,..., Fn (E )
            s E is any relational-algebra expression

            s Each of F1, F2, …, Fn are are arithmetic expressions involving constants
                 and attributes in the schema of E.
            s Given relation credit_info(customer_name, limit, credit_balance), find
                 how much more each person can spend:
                             ∏customer_name, limit – credit_balance (credit_info)




Database System Concepts – 1 st Ed.                            2.49   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Functions and Operations
            s Aggregation function takes a collection of values and returns a
                 single value as a result.
                                              avg: average value
                                              min: minimum value
                                              max: maximum value
                                              sum: sum of values
                                              count: number of values
            s Aggregate operation in relational algebra

                               G1 ,G2 ,,Gn
                                              ϑF ( A ),F ( A ,,F ( A ) (E )
                                                 1   1   2   2   n   n


                 E is any relational-algebra expression
                   q   G1, G2 …, Gn is a list of attributes on which to group (can be empty)
                   q   Each Fi is an aggregate function
                   q   Each Ai is an attribute name



Database System Concepts – 1 st Ed.                              2.50    ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Operation – Example
            s Relation r:

                                      A    B          C

                                      α    α          7
                                      α    β          7
                                      β    β          3
                                      β    β          10




            s g sum(c) (r)            sum(c )

                                          27




Database System Concepts – 1 st Ed.            2.51   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Operation – Example
              s Relation account grouped by branch-name:


                                  branch_name account_number                        balance
                                  Perryridge                A-102                      400
                                  Perryridge                A-201                      900
                                  Brighton                  A-217                      750
                                  Brighton                  A-215                      750
                                  Redwood                   A-222                      700


                branch_name           g   sum(balance)   (account)
                                                  branch_name sum(balance)
                                                  Perryridge                  1300
                                                  Brighton                    1500
                                                  Redwood                      700



Database System Concepts – 1 st Ed.                         2.52   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Functions (Cont.)
            s Result of aggregation does not have a name
                   q   Can use rename operation to give it a name
                   q   For convenience, we permit renaming as part of aggregate
                       operation


                       branch_name    g   sum(balance) as sum_balance (account)




Database System Concepts – 1 st Ed.                   2.53   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Outer Join
            s An extension of the join operation that avoids loss of information.
            s Computes the join and then adds tuples form one relation that does not
                 match tuples in the other relation to the result of the join.
            s Uses null values:
                   q   null signifies that the value is unknown or does not exist
                   q   All comparisons involving null are (roughly speaking) false by
                       definition.
                            We shall study precise meaning of comparisons with nulls later




Database System Concepts – 1 st Ed.                   2.54   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Outer Join – Example
            s Relation loan



                               loan_number branch_name             amount
                              L-170             Downtown             3000
                              L-230             Redwood              4000
                              L-260             Perryridge           1700


            s Relation borrower

                                      customer_name loan_number
                                      Jones         L-170
                                      Smith         L-230
                                      Hayes         L-155




Database System Concepts – 1 st Ed.                    2.55   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Outer Join – Example
            s Join

                 loan        borrower

                       loan_number        branch_name         amount customer_name
                       L-170              Downtown            3000          Jones
                       L-230              Redwood             4000          Smith

            s Left Outer Join
                loan           borrower
                         loan_number      branch_name         amount customer_name
                        L-170             Downtown             3000         Jones
                        L-230             Redwood              4000         Smith
                        L-260             Perryridge           1700         null




Database System Concepts – 1 st Ed.                    2.56   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Outer Join – Example
            s Right Outer Join
                loan          borrower

                    loan_number          branch_name    amount customer_name
                   L-170                Downtown          3000          Jones
                   L-230                Redwood           4000          Smith
                   L-155                null               null         Hayes
            s Full Outer Join
                loan          borrower
                   loan_number         branch_name     amount customer_name
                  L-170                Downtown          3000          Jones
                  L-230                Redwood           4000          Smith
                  L-260                Perryridge        1700          null
                  L-155                null               null         Hayes



Database System Concepts – 1 st Ed.                    2.57   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Null Values
             s It is possible for tuples to have a null value, denoted by null, for some
                  of their attributes
             s null signifies an unknown value or that a value does not exist.

             s The result of any arithmetic expression involving null is null.

             s Aggregate functions simply ignore null values (as in SQL)

             s For duplicate elimination and grouping, null is treated like any other
                  value, and two nulls are assumed to be the same (as in SQL)




Database System Concepts – 1 st Ed.               2.58   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Null Values
            s Comparisons with null values return the special truth value: unknown
                   q   If false was used instead of unknown, then          not (A < 5)
                                 would not be equivalent to                A >= 5
            s Three-valued logic using the truth value unknown:
                   q   OR: (unknown or true)    = true,
                           (unknown or false)   = unknown
                           (unknown or unknown) = unknown
                   q   AND: (true and unknown)     = unknown,
                            (false and unknown)   = false,
                            (unknown and unknown) = unknown
                   q   NOT: (not unknown) = unknown
                   q   In SQL “P is unknown” evaluates to true if predicate P evaluates
                       to unknown
            s Result of select predicate is treated as false if it evaluates to unknown




Database System Concepts – 1 st Ed.                2.59   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Modification of the Database
            s The content of the database may be modified using the following
                 operations:
                   q   Deletion
                   q   Insertion
                   q   Updating
            s All these operations are expressed using the assignment
                 operator.




Database System Concepts – 1 st Ed.           2.60   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Deletion
            s A delete request is expressed similarly to a query, except
                 instead of displaying tuples to the user, the selected tuples are
                 removed from the database.
            s Can delete only whole tuples; cannot delete values on only
                 particular attributes
            s A deletion is expressed in relational algebra by:
                                         r←r–E
                 where r is a relation and E is a relational algebra query.




Database System Concepts – 1 st Ed.                2.61   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Deletion Examples
            s Delete all account records in the Perryridge branch.

                   account ← account – σ branch_name = “ Perryridge” (account )

            s Delete all loan records with amount in the range of 0 to 50

                      loan ← loan – σ amount ≥ 0 and amount ≤ 50 (loan)

             s Delete all accounts at branches located in Needham.

                  r1 ← σ branch_city = “   Needham”   (account        branch )

                  r2 ← ∏ account_number, branch_name, balance (r1)

                  r3 ← ∏ customer_name, account_number (r2          depositor)
                  account ← account – r2
                  depositor ← depositor – r3


Database System Concepts – 1 st Ed.                     2.62   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Insertion
             s To insert data into a relation, we either:
                   q    specify a tuple to be inserted
                   q    write a query whose result is a set of tuples to be inserted
             s in relational algebra, an insertion is expressed by:
                                            r← r ∪ E
                  where r is a relation and E is a relational algebra expression.
             s The insertion of a single tuple is expressed by letting E be a constant
                  relation containing one tuple.




Database System Concepts – 1 st Ed.                  2.63   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Insertion Examples
            s Insert information in the database specifying that Smith has $1200 in
                 account A-973 at the Perryridge branch.

                  account ← account ∪ {(“A-973”, “Perryridge”, 1200)}
                  depositor ← depositor ∪ {(“Smith”, “A-973”)}


            s Provide as a gift for all loan customers in the Perryridge
                 branch, a $200 savings account. Let the loan number serve
                 as the account number for the new savings account.

                      r1 ← (σbranch_name = “ Perryridge” (borrower       loan))
                      account ← account ∪ ∏loan_number, branch_name, 200 (r1)
                      depositor ← depositor ∪ ∏customer_name, loan_number (r1)



Database System Concepts – 1 st Ed.                    2.64   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Updating
             s A mechanism to change a value in a tuple without charging all values in
                  the tuple
             s Use the generalized projection operator to do this task


                                      r ← ∏ F ,F ,,F , ( r )
                                                1   2    l

             s Each Fi is either

                   q    the I th attribute of r, if the I th attribute is not updated, or,
                   q    if the attribute is to be updated Fi is an expression, involving only
                        constants and the attributes of r, which gives the new value for the
                        attribute




Database System Concepts – 1 st Ed.                          2.65   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Update Examples

             s Make interest payments by increasing all balances by 5 percent.

                       account ← ∏ account_number, branch_name, balance * 1.05 (account)




             s Pay all accounts with balances over $10,000 6 percent interest
                  and pay all others 5 percent


                  account ← ∏ account_number, branch_name, balance * 1.06 (σ BAL > 10000 (account ))
                                      ∪ ∏ account_number, branch_name, balance * 1.05 (σBAL ≤ 10000 (account))




Database System Concepts – 1 st Ed.                            2.66   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
End of Chapter 2




         Database System Concepts, 1 st Ed.
© VNS InfoSolutions Private Limited, Varanasi(UP), India 221002
         See www.vnsispl.com for conditions on re-use
Figure 2.3. The branch relation




Database System Concepts – 1 st Ed.   2.68   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.6: The loan relation




Database System Concepts – 1 st Ed.   2.69   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.7: The borrower relation




Database System Concepts – 1 st Ed.   2.70   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.9
                      Result of σbranch_name = “Perryridge” (loan)




Database System Concepts – 1 st Ed.       2.71   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Loan number and the amount of the
                            loan




Database System Concepts – 1 st Ed.   2.72   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
who have either an account or an
                               loan




Database System Concepts – 1 st Ed.   2.73   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Customers with an account but no
                              loan




Database System Concepts – 1 st Ed.   2.74   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.13: Result of borrower |X|
                              loan




Database System Concepts – 1 st Ed.   2.75   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.14




Database System Concepts – 1 st Ed.       2.76   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.15




Database System Concepts – 1 st Ed.       2.77   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.16




Database System Concepts – 1 st Ed.       2.78   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.17
             Largest account balance in the bank




Database System Concepts – 1 st Ed.   2.79   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.18: Customers who live on
            the same street and in the same city
                          as Smith




Database System Concepts – 1 st Ed.   2.80   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.19: Customers with both an
                account and a loan at the bank




Database System Concepts – 1 st Ed.   2.81   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.20




Database System Concepts – 1 st Ed.       2.82   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.21




Database System Concepts – 1 st Ed.       2.83   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.22




Database System Concepts – 1 st Ed.       2.84   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.23




Database System Concepts – 1 st Ed.       2.85   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.24: The credit_info relation




Database System Concepts – 1 st Ed.   2.86   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.25




Database System Concepts – 1 st Ed.       2.87   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.26: The pt_works relation




Database System Concepts – 1 st Ed.   2.88   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The pt_works relation after
                                  regrouping




Database System Concepts – 1 st Ed.    2.89   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.28




Database System Concepts – 1 st Ed.       2.90   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.29




Database System Concepts – 1 st Ed.       2.91   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.30
            The employee and ft_works relations




Database System Concepts – 1 st Ed.   2.92   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.31




Database System Concepts – 1 st Ed.       2.93   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.32




Database System Concepts – 1 st Ed.       2.94   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.33




Database System Concepts – 1 st Ed.       2.95   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 2.34




Database System Concepts – 1 st Ed.       2.96   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100

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VNSISPL_DBMS_Concepts_ch2

  • 1. Chapter 2: Relational Model Database System Concepts, 1 st Ed. © VNS InfoSolutions Private Limited, Varanasi(UP), India 221002 See www.vnsispl.com for conditions on re-use
  • 2. Chapter 2: Relational Model s Structure of Relational Databases s Fundamental Relational-Algebra-Operations s Additional Relational-Algebra-Operations s Extended Relational-Algebra-Operations s Null Values s Modification of the Database Database System Concepts – 1 st Ed. 2.2 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 3. Example of a Relation Database System Concepts – 1 st Ed. 2.3 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 4. Basic Structure s Formally, given sets D1, D2, …. Dn a relation r is a subset of D1 x D2 x … x Dn Thus, a relation is a set of n-tuples (a1, a2, …, an) where each ai ∈ Di s Example: If q customer_name = {Jones, Smith, Curry, Lindsay, …} /* Set of all customer names */ q customer_street = {Main, North, Park, …} /* set of all street names*/ q customer_city = {Harrison, Rye, Pittsfield, …} /* set of all city names */ Then r = { (Jones, Main, Harrison), (Smith, North, Rye), (Curry, North, Rye), (Lindsay, Park, Pittsfield) } is a relation over customer_name x customer_street x customer_city Database System Concepts – 1 st Ed. 2.4 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 5. Attribute Types s Each attribute of a relation has a name s The set of allowed values for each attribute is called the domain of the attribute s Attribute values are (normally) required to be atomic; that is, indivisible q E.g. the value of an attribute can be an account number, but cannot be a set of account numbers s Domain is said to be atomic if all its members are atomic s The special value null is a member of every domain s The null value causes complications in the definition of many operations q We shall ignore the effect of null values in our main presentation and consider their effect later Database System Concepts – 1 st Ed. 2.5 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 6. Relation Schema s A1, A2, …, An are attributes s R = (A1, A2, …, An ) is a relation schema Example: Customer_schema = (customer_name, customer_street, customer_city) s r(R) denotes a relation r on the relation schema R Example: customer (Customer_schema) Database System Concepts – 1 st Ed. 2.6 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 7. Relation Instance s The current values (relation instance) of a relation are specified by a table s An element t of r is a tuple, represented by a row in a table attributes (or columns) customer_name customer_street customer_city Jones Main Harrison Smith North Rye tuples Curry North Rye (or rows) Lindsay Park Pittsfield customer Database System Concepts – 1 st Ed. 2.7 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 8. Relations are Unordered s Order of tuples is irrelevant (tuples may be stored in an arbitrary order) s Example: account relation with unordered tuples Database System Concepts – 1 st Ed. 2.8 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 9. Database s A database consists of multiple relations s Information about an enterprise is broken up into parts, with each relation storing one part of the information account : stores information about accounts depositor : stores information about which customer owns which account customer : stores information about customers s Storing all information as a single relation such as bank(account_number, balance, customer_name, ..) results in q repetition of information  e.g.,if two customers own an account (What gets repeated?) q the need for null values  e.g., to represent a customer without an account s Normalization theory (Chapter 7) deals with how to design relational schemas Database System Concepts – 1 st Ed. 2.9 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 10. The customer Relation Database System Concepts – 1 st Ed. 2.10 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 11. The depositor Relation Database System Concepts – 1 st Ed. 2.11 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 12. Keys s Let K ⊆ R s K is a superkey of R if values for K are sufficient to identify a unique tuple of each possible relation r(R) q by “possible r ” we mean a relation r that could exist in the enterprise we are modeling. q Example: {customer_name, customer_street} and {customer_name} are both superkeys of Customer, if no two customers can possibly have the same name  In real life, an attribute such as customer_id would be used instead of customer_name to uniquely identify customers, but we omit it to keep our examples small, and instead assume customer names are unique. Database System Concepts – 1 st Ed. 2.12 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 13. Keys (Cont.) s K is a candidate key if K is minimal Example: {customer_name} is a candidate key for Customer, since it is a superkey and no subset of it is a superkey. s Primary key: a candidate key chosen as the principal means of identifying tuples within a relation q Should choose an attribute whose value never, or very rarely, changes. q E.g. email address is unique, but may change Database System Concepts – 1 st Ed. 2.13 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 14. Foreign Keys s A relation schema may have an attribute that corresponds to the primary key of another relation. The attribute is called a foreign key. q E.g. customer_name and account_number attributes of depositor are foreign keys to customer and account respectively. q Only values occurring in the primary key attribute of the referenced relation may occur in the foreign key attribute of the referencing relation. s Schema diagram Database System Concepts – 1 st Ed. 2.14 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 15. Query Languages s Language in which user requests information from the database. s Categories of languages q Procedural q Non-procedural, or declarative s “Pure” languages: q Relational algebra q Tuple relational calculus q Domain relational calculus s Pure languages form underlying basis of query languages that people use. Database System Concepts – 1 st Ed. 2.15 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 16. Relational Algebra s Procedural language s Six basic operators q select: σ q project: ∏ q union: ∪ q set difference: – q Cartesian product: x q rename: ρ s The operators take one or two relations as inputs and produce a new relation as a result. Database System Concepts – 1 st Ed. 2.16 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 17. Select Operation – Example s Relation r A B C D α α 1 7 α β 5 7 β β 12 3 β β 23 10  σA=B ^ D > 5 (r) A B C D α α 1 7 β β 23 10 Database System Concepts – 1 st Ed. 2.17 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 18. Select Operation s Notation: σ p(r) s p is called the selection predicate s Defined as: σp(r) = {t | t ∈ r and p(t)} Where p is a formula in propositional calculus consisting of terms connected by : ∧ (and), ∨ (or), ¬ (not) Each term is one of: <attribute> op <attribute> or <constant> where op is one of: =, ≠, >, ≥. <. ≤ s Example of selection: σ branch_name=“ Perryridge” (account) Database System Concepts – 1 st Ed. 2.18 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 19. Project Operation – Example s Relation r: A B C α 10 1 α 20 1 β 30 1 β 40 2 ∏A,C (r) A C A C α 1 α 1 α 1 = β 1 β 1 β 2 β 2 Database System Concepts – 1 st Ed. 2.19 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 20. Project Operation s Notation: ∏ A1 , A2 ,, Ak (r ) where A1, A2 are attribute names and r is a relation name. s The result is defined as the relation of k columns obtained by erasing the columns that are not listed s Duplicate rows removed from result, since relations are sets s Example: To eliminate the branch_name attribute of account ∏account_number, balance (account) Database System Concepts – 1 st Ed. 2.20 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 21. Union Operation – Example s Relations r, s: A B A B α 1 α 2 α 2 β 3 β 1 s r A B s r ∪ s: α 1 α 2 β 1 β 3 Database System Concepts – 1 st Ed. 2.21 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 22. Union Operation s Notation: r ∪ s s Defined as: r ∪ s = {t | t ∈ r or t ∈ s} s For r ∪ s to be valid. 1. r, s must have the same arity (same number of attributes) 2. The attribute domains must be compatible (example: 2nd column of r deals with the same type of values as does the 2nd column of s) s Example: to find all customers with either an account or a loan ∏customer_name (depositor) ∪ ∏customer_name (borrower) Database System Concepts – 1 st Ed. 2.22 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 23. Set Difference Operation – Example s Relations r, s: A B A B α 1 α 2 α 2 β 3 β 1 s r s r – s: A B α 1 β 1 Database System Concepts – 1 st Ed. 2.23 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 24. Set Difference Operation s Notation r – s s Defined as: r – s = {t | t ∈ r and t ∉ s} s Set differences must be taken between compatible relations. q r and s must have the same arity q attribute domains of r and s must be compatible Database System Concepts – 1 st Ed. 2.24 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 25. Cartesian-Product Operation – Example s Relations r, s: A B C D E α 1 α 10 a β 10 a β 2 β 20 b r γ 10 b s s r x s: A B C D E α 1 α 10 a α 1 β 10 a α 1 β 20 b α 1 γ 10 b β 2 α 10 a β 2 β 10 a β 2 β 20 b β 2 γ 10 b Database System Concepts – 1 st Ed. 2.25 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 26. Cartesian-Product Operation s Notation r x s s Defined as: r x s = {t q | t ∈ r and q ∈ s} s Assume that attributes of r(R) and s(S) are disjoint. (That is, R ∩ S = ∅). s If attributes of r(R) and s(S) are not disjoint, then renaming must be used. Database System Concepts – 1 st Ed. 2.26 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 27. Composition of Operations s Can build expressions using multiple operations s Example: σA=C(r x s) s rxs A B C D E α 1 α 10 a α 1 β 10 a α 1 β 20 b α 1 γ 10 b β 2 α 10 a β 2 β 10 a β 2 β 20 b β 2 γ 10 b s σA=C(r x s) A B C D E α 1 α 10 a β 2 β 10 a β 2 β 20 b Database System Concepts – 1 st Ed. 2.27 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 28. Rename Operation s Allows us to name, and therefore to refer to, the results of relational- algebra expressions. s Allows us to refer to a relation by more than one name. s Example: ρ x (E) returns the expression E under the name X s If a relational-algebra expression E has arity n, then ρx ( A ,A 1 2 ,..., An ) (E ) returns the result of expression E under the name X, and with the attributes renamed to A1 , A2 , … An . ., Database System Concepts – 1 st Ed. 2.28 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 29. Banking Example branch (branch_name, branch_city, assets) customer (customer_name, customer_street, customer_city) account (account_number, branch_name, balance) loan (loan_number, branch_name, amount) depositor (customer_name, account_number) borrower (customer_name, loan_number) Database System Concepts – 1 st Ed. 2.29 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 30. Example Queries s Find all loans of over $1200 σamount > 1200 (loan) s Find the loan number for each loan of an amount greater than $1200 ∏loan_number (σamount > 1200 (loan)) s Find the names of all customers who have a loan, an account, or both, from the bank ∏customer_name (borrower) ∪ ∏customer_name (depositor) Database System Concepts – 1 st Ed. 2.30 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 31. Example Queries s Find the names of all customers who have a loan at the Perryridge branch. ∏customer_name (σbranch_name=“ Perryridge” (σborrower.loan_number = loan.loan_number(borrower x loan))) s Find the names of all customers who have a loan at the Perryridge branch but do not have an account at any branch of the bank. ∏customer_name (σbranch_name = “ Perryridge” (σborrower.loan_number = loan.loan_number(borrower x loan))) – ∏customer_name(depositor) Database System Concepts – 1 st Ed. 2.31 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 32. Example Queries s Find the names of all customers who have a loan at the Perryridge branch. q Query 1 ∏customer_name (σbranch_name = “Perryridge” ( σborrower.loan_number = loan.loan_number (borrower x loan))) q Query 2 ∏customer_name(σloan.loan_number = borrower.loan_number ( (σbranch_name = “Perryridge” (loan)) x borrower)) Database System Concepts – 1 st Ed. 2.32 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 33. Example Queries s Find the largest account balance q Strategy:  Find those balances that are not the largest – Rename account relation as d so that we can compare each account balance with all others  Use set difference to find those account balances that were not found in the earlier step. q The query is: ∏balance(account) - ∏account.balance (σaccount.balance < d.balance (account x ρd (account))) Database System Concepts – 1 st Ed. 2.33 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 34. Formal Definition s A basic expression in the relational algebra consists of either one of the following: q A relation in the database q A constant relation s Let E1 and E2 be relational-algebra expressions; the following are all relational-algebra expressions: q E1 ∪ E2 q E1 – E2 q E1 x E2 q σp (E1), P is a predicate on attributes in E1 q ∏s(E1), S is a list consisting of some of the attributes in E1 q ρ (E ), x is the new name for the result of E1 Private Limited, Varanasi(UP), India 22100 Database System Conceptsx 1 st Ed. – 1 2.34 ©VNS InfoSolutions
  • 35. Additional Operations We define additional operations that do not add any power to the relational algebra, but that simplify common queries. s Set intersection s Natural join s Division s Assignment Database System Concepts – 1 st Ed. 2.35 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 36. Set-Intersection Operation s Notation: r ∩ s s Defined as: s r ∩ s = { t | t ∈ r and t ∈ s } s Assume: q r, s have the same arity q attributes of r and s are compatible s Note: r ∩ s = r – (r – s) Database System Concepts – 1 st Ed. 2.36 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 37. Set-Intersection Operation – Example s Relation r, s: A B A B α 1 α 2 α 2 β 3 β 1 r s s r∩s A B α 2 Database System Concepts – 1 st Ed. 2.37 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 38. Natural-Join Operation s Notation: r s s Let r and s be relations on schemas R and S respectively. Then, r s is a relation on schema R ∪ S obtained as follows: q Consider each pair of tuples tr from r and ts from s. q If tr and ts have the same value on each of the attributes in R ∩ S, add a tuple t to the result, where  t has the same value as tr on r  t has the same value as ts on s s Example: R = (A, B, C, D) S = (E, B, D) q Result schema = (A, B, C, D, E) q r s is defined as: Database System Concepts – 1 st Ed. 2.38 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 39. Natural Join Operation – Example s Relations r, s: A B C D B D E α 1 α a 1 a α β 2 γ a 3 a β γ 4 β b 1 a γ α 1 γ a 2 b δ δ 2 β b 3 b ∈ r s s r s A B C D E α 1 α a α α 1 α a γ α 1 γ a α α 1 γ a γ δ 2 β b δ Database System Concepts – 1 st Ed. 2.39 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 40. Division Operation s Notation: r÷s s Suited to queries that include the phrase “for all”. s Let r and s be relations on schemas R and S respectively where q R = (A1, …, Am , B1, …, Bn ) q S = (B1, …, Bn) The result of r ÷ s is a relation on schema R – S = (A1, …, Am) r ÷ s = { t | t ∈ ∏ R-S (r) ∧ ∀ u ∈ s ( tu ∈ r ) } Where tu means the concatenation of tuples t and u to produce a single tuple Database System Concepts – 1 st Ed. 2.40 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 41. Division Operation – Example s Relations r, s: A B B α 1 1 α 2 α 3 2 β 1 s γ 1 δ 1 δ 3 δ 4 ∈ 6 ∈ 1 β 2 s r ÷ s: A r α β Database System Concepts – 1 st Ed. 2.41 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 42. Another Division Example s Relations r, s: A B C D E D E α a α a 1 a 1 α a γ a 1 b 1 α a γ b 1 s β a γ a 1 β a γ b 3 γ a γ a 1 γ a γ b 1 γ a β b 1 r s r ÷ s: A B C α a γ γ a γ Database System Concepts – 1 st Ed. 2.42 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 43. Division Operation (Cont.) s Property q Let q = r ÷ s q Then q is the largest relation satisfying q x s ⊆ r s Definition in terms of the basic algebra operation Let r(R) and s(S) be relations, and let S ⊆ R r ÷ s = ∏R-S (r ) – ∏R-S ( ( ∏R-S (r ) x s ) – ∏R-S,S(r )) To see why q ∏R-S,S (r) simply reorders attributes of r q ∏R-S (∏R-S (r ) x s ) – ∏R-S,S(r) ) gives those tuples t in ∏R-S (r ) such that for some tuple u ∈ s, tu ∉ r. Database System Concepts – 1 st Ed. 2.43 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 44. Assignment Operation s The assignment operation (←) provides a convenient way to express complex queries. q Write query as a sequential program consisting of  a series of assignments  followed by an expression whose value is displayed as a result of the query. q Assignment must always be made to a temporary relation variable. s Example: Write r ÷ s as temp1 ← ∏R-S (r ) temp2 ← ∏R-S ((temp1 x s ) – ∏R-S,S (r )) result = temp1 – temp2 q The result to the right of the ← is assigned to the relation variable on the left of the ←. q May use variable in subsequent expressions. Database System Concepts – 1 st Ed. 2.44 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 45. Bank Example Queries s Find the names of all customers who have a loan and an account at bank. ∏customer_name (borrower) ∩ ∏customer_name (depositor) s Find the name of all customers who have a loan at the bank and the loan amount ∏customer_name, loan_number, amount (borrower loan) Database System Concepts – 1 st Ed. 2.45 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 46. Bank Example Queries s Find all customers who have an account from at least the “Downtown” and the Uptown” branches. q Query 1 ∏customer_name (σbranch_name = “Downtown” (depositor account )) ∩ ∏customer_name (σbranch_name = “Uptown” (depositor account)) q Query 2 ∏customer_name, branch_name (depositor account) ÷ ρtemp(branch_name) ({(“ Downtown” ), (“ Uptown” )}) Note that Query 2 uses a constant relation. Database System Concepts – 1 st Ed. 2.46 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 47. Bank Example Queries s Find all customers who have an account at all branches located in Brooklyn city. ∏customer_name, branch_name (depositor account) ÷ ∏branch_name (σbranch_city = “Brooklyn” (branch)) Database System Concepts – 1 st Ed. 2.47 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 48. Extended Relational-Algebra- Operations s Generalized Projection s Aggregate Functions s Outer Join Database System Concepts – 1 st Ed. 2.48 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 49. Generalized Projection s Extends the projection operation by allowing arithmetic functions to be used in the projection list. ∏ F1 ,F2 ,..., Fn (E ) s E is any relational-algebra expression s Each of F1, F2, …, Fn are are arithmetic expressions involving constants and attributes in the schema of E. s Given relation credit_info(customer_name, limit, credit_balance), find how much more each person can spend: ∏customer_name, limit – credit_balance (credit_info) Database System Concepts – 1 st Ed. 2.49 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 50. Aggregate Functions and Operations s Aggregation function takes a collection of values and returns a single value as a result. avg: average value min: minimum value max: maximum value sum: sum of values count: number of values s Aggregate operation in relational algebra G1 ,G2 ,,Gn ϑF ( A ),F ( A ,,F ( A ) (E ) 1 1 2 2 n n E is any relational-algebra expression q G1, G2 …, Gn is a list of attributes on which to group (can be empty) q Each Fi is an aggregate function q Each Ai is an attribute name Database System Concepts – 1 st Ed. 2.50 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 51. Aggregate Operation – Example s Relation r: A B C α α 7 α β 7 β β 3 β β 10 s g sum(c) (r) sum(c ) 27 Database System Concepts – 1 st Ed. 2.51 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 52. Aggregate Operation – Example s Relation account grouped by branch-name: branch_name account_number balance Perryridge A-102 400 Perryridge A-201 900 Brighton A-217 750 Brighton A-215 750 Redwood A-222 700 branch_name g sum(balance) (account) branch_name sum(balance) Perryridge 1300 Brighton 1500 Redwood 700 Database System Concepts – 1 st Ed. 2.52 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 53. Aggregate Functions (Cont.) s Result of aggregation does not have a name q Can use rename operation to give it a name q For convenience, we permit renaming as part of aggregate operation branch_name g sum(balance) as sum_balance (account) Database System Concepts – 1 st Ed. 2.53 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 54. Outer Join s An extension of the join operation that avoids loss of information. s Computes the join and then adds tuples form one relation that does not match tuples in the other relation to the result of the join. s Uses null values: q null signifies that the value is unknown or does not exist q All comparisons involving null are (roughly speaking) false by definition.  We shall study precise meaning of comparisons with nulls later Database System Concepts – 1 st Ed. 2.54 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 55. Outer Join – Example s Relation loan loan_number branch_name amount L-170 Downtown 3000 L-230 Redwood 4000 L-260 Perryridge 1700 s Relation borrower customer_name loan_number Jones L-170 Smith L-230 Hayes L-155 Database System Concepts – 1 st Ed. 2.55 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 56. Outer Join – Example s Join loan borrower loan_number branch_name amount customer_name L-170 Downtown 3000 Jones L-230 Redwood 4000 Smith s Left Outer Join loan borrower loan_number branch_name amount customer_name L-170 Downtown 3000 Jones L-230 Redwood 4000 Smith L-260 Perryridge 1700 null Database System Concepts – 1 st Ed. 2.56 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 57. Outer Join – Example s Right Outer Join loan borrower loan_number branch_name amount customer_name L-170 Downtown 3000 Jones L-230 Redwood 4000 Smith L-155 null null Hayes s Full Outer Join loan borrower loan_number branch_name amount customer_name L-170 Downtown 3000 Jones L-230 Redwood 4000 Smith L-260 Perryridge 1700 null L-155 null null Hayes Database System Concepts – 1 st Ed. 2.57 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 58. Null Values s It is possible for tuples to have a null value, denoted by null, for some of their attributes s null signifies an unknown value or that a value does not exist. s The result of any arithmetic expression involving null is null. s Aggregate functions simply ignore null values (as in SQL) s For duplicate elimination and grouping, null is treated like any other value, and two nulls are assumed to be the same (as in SQL) Database System Concepts – 1 st Ed. 2.58 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 59. Null Values s Comparisons with null values return the special truth value: unknown q If false was used instead of unknown, then not (A < 5) would not be equivalent to A >= 5 s Three-valued logic using the truth value unknown: q OR: (unknown or true) = true, (unknown or false) = unknown (unknown or unknown) = unknown q AND: (true and unknown) = unknown, (false and unknown) = false, (unknown and unknown) = unknown q NOT: (not unknown) = unknown q In SQL “P is unknown” evaluates to true if predicate P evaluates to unknown s Result of select predicate is treated as false if it evaluates to unknown Database System Concepts – 1 st Ed. 2.59 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 60. Modification of the Database s The content of the database may be modified using the following operations: q Deletion q Insertion q Updating s All these operations are expressed using the assignment operator. Database System Concepts – 1 st Ed. 2.60 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 61. Deletion s A delete request is expressed similarly to a query, except instead of displaying tuples to the user, the selected tuples are removed from the database. s Can delete only whole tuples; cannot delete values on only particular attributes s A deletion is expressed in relational algebra by: r←r–E where r is a relation and E is a relational algebra query. Database System Concepts – 1 st Ed. 2.61 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 62. Deletion Examples s Delete all account records in the Perryridge branch. account ← account – σ branch_name = “ Perryridge” (account ) s Delete all loan records with amount in the range of 0 to 50 loan ← loan – σ amount ≥ 0 and amount ≤ 50 (loan) s Delete all accounts at branches located in Needham. r1 ← σ branch_city = “ Needham” (account branch ) r2 ← ∏ account_number, branch_name, balance (r1) r3 ← ∏ customer_name, account_number (r2 depositor) account ← account – r2 depositor ← depositor – r3 Database System Concepts – 1 st Ed. 2.62 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 63. Insertion s To insert data into a relation, we either: q specify a tuple to be inserted q write a query whose result is a set of tuples to be inserted s in relational algebra, an insertion is expressed by: r← r ∪ E where r is a relation and E is a relational algebra expression. s The insertion of a single tuple is expressed by letting E be a constant relation containing one tuple. Database System Concepts – 1 st Ed. 2.63 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 64. Insertion Examples s Insert information in the database specifying that Smith has $1200 in account A-973 at the Perryridge branch. account ← account ∪ {(“A-973”, “Perryridge”, 1200)} depositor ← depositor ∪ {(“Smith”, “A-973”)} s Provide as a gift for all loan customers in the Perryridge branch, a $200 savings account. Let the loan number serve as the account number for the new savings account. r1 ← (σbranch_name = “ Perryridge” (borrower loan)) account ← account ∪ ∏loan_number, branch_name, 200 (r1) depositor ← depositor ∪ ∏customer_name, loan_number (r1) Database System Concepts – 1 st Ed. 2.64 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 65. Updating s A mechanism to change a value in a tuple without charging all values in the tuple s Use the generalized projection operator to do this task r ← ∏ F ,F ,,F , ( r ) 1 2 l s Each Fi is either q the I th attribute of r, if the I th attribute is not updated, or, q if the attribute is to be updated Fi is an expression, involving only constants and the attributes of r, which gives the new value for the attribute Database System Concepts – 1 st Ed. 2.65 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 66. Update Examples s Make interest payments by increasing all balances by 5 percent. account ← ∏ account_number, branch_name, balance * 1.05 (account) s Pay all accounts with balances over $10,000 6 percent interest and pay all others 5 percent account ← ∏ account_number, branch_name, balance * 1.06 (σ BAL > 10000 (account )) ∪ ∏ account_number, branch_name, balance * 1.05 (σBAL ≤ 10000 (account)) Database System Concepts – 1 st Ed. 2.66 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 67. End of Chapter 2 Database System Concepts, 1 st Ed. © VNS InfoSolutions Private Limited, Varanasi(UP), India 221002 See www.vnsispl.com for conditions on re-use
  • 68. Figure 2.3. The branch relation Database System Concepts – 1 st Ed. 2.68 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 69. Figure 2.6: The loan relation Database System Concepts – 1 st Ed. 2.69 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 70. Figure 2.7: The borrower relation Database System Concepts – 1 st Ed. 2.70 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 71. Figure 2.9 Result of σbranch_name = “Perryridge” (loan) Database System Concepts – 1 st Ed. 2.71 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 72. Loan number and the amount of the loan Database System Concepts – 1 st Ed. 2.72 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 73. who have either an account or an loan Database System Concepts – 1 st Ed. 2.73 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 74. Customers with an account but no loan Database System Concepts – 1 st Ed. 2.74 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 75. Figure 2.13: Result of borrower |X| loan Database System Concepts – 1 st Ed. 2.75 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 76. Figure 2.14 Database System Concepts – 1 st Ed. 2.76 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 77. Figure 2.15 Database System Concepts – 1 st Ed. 2.77 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 78. Figure 2.16 Database System Concepts – 1 st Ed. 2.78 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 79. Figure 2.17 Largest account balance in the bank Database System Concepts – 1 st Ed. 2.79 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 80. Figure 2.18: Customers who live on the same street and in the same city as Smith Database System Concepts – 1 st Ed. 2.80 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 81. Figure 2.19: Customers with both an account and a loan at the bank Database System Concepts – 1 st Ed. 2.81 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 82. Figure 2.20 Database System Concepts – 1 st Ed. 2.82 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 83. Figure 2.21 Database System Concepts – 1 st Ed. 2.83 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 84. Figure 2.22 Database System Concepts – 1 st Ed. 2.84 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 85. Figure 2.23 Database System Concepts – 1 st Ed. 2.85 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 86. Figure 2.24: The credit_info relation Database System Concepts – 1 st Ed. 2.86 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 87. Figure 2.25 Database System Concepts – 1 st Ed. 2.87 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 88. Figure 2.26: The pt_works relation Database System Concepts – 1 st Ed. 2.88 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 89. The pt_works relation after regrouping Database System Concepts – 1 st Ed. 2.89 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 90. Figure 2.28 Database System Concepts – 1 st Ed. 2.90 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 91. Figure 2.29 Database System Concepts – 1 st Ed. 2.91 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 92. Figure 2.30 The employee and ft_works relations Database System Concepts – 1 st Ed. 2.92 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 93. Figure 2.31 Database System Concepts – 1 st Ed. 2.93 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 94. Figure 2.32 Database System Concepts – 1 st Ed. 2.94 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 95. Figure 2.33 Database System Concepts – 1 st Ed. 2.95 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 96. Figure 2.34 Database System Concepts – 1 st Ed. 2.96 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100