SlideShare a Scribd company logo
Chapter 3: SQL




        Database System Concepts, 1 st Ed.
©VNS InfoSolutions Private Limited, Varanasi(UP), India 221002
        See www.vnsispl.com for conditions on re-use
Chapter 3: SQL
              s Data Definition
              s Basic Query Structure
              s Set Operations
              s Aggregate Functions
              s Null Values
              s Nested Subqueries
              s Complex Queries
              s Views
              s Modification of the Database
              s Joined Relations**




Database System Concepts, 5 th Edition, Oct 5, 2006   3.2   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
History
             s IBM Sequel language developed as part of System R project at the
                  IBM San Jose Research Laboratory
             s Renamed Structured Query Language (SQL)
             s ANSI and ISO standard SQL:
                    q   SQL-86
                    q   SQL-89
                    q   SQL-92
                    q   SQL:1999 (language name became Y2K compliant!)
                    q   SQL:2003
             s Commercial systems offer most, if not all, SQL-92 features, plus
                  varying feature sets from later standards and special proprietary
                  features.
                    q   Not all examples here may work on your particular system.




Database System Concepts, 5 th Edition, Oct 5, 2006     3.3   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Data Definition Language
             Allows the specification of not only a set of relations but also
             information about each relation, including:
                    s The schema for each relation.
                    s The domain of values associated with each attribute.
                    s Integrity constraints
                    s The set of indices to be maintained for each relations.
                    s Security and authorization information for each relation.
                    s The physical storage structure of each relation on disk.




Database System Concepts, 5 th Edition, Oct 5, 2006   3.4   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Domain Types in SQL
             s char(n). Fixed length character string, with user-specified length n.
             s varchar(n). Variable length character strings, with user-specified
                  maximum length n.
             s int. Integer (a finite subset of the integers that is machine-dependent).
             s smallint. Small integer (a machine-dependent subset of the integer
                  domain type).
             s numeric(p,d). Fixed point number, with user-specified precision of p
                  digits, with n digits to the right of decimal point.
             s real, double precision. Floating point and double-precision floating
                  point numbers, with machine-dependent precision.
             s float(n). Floating point number, with user-specified precision of at least n
                  digits.
             s More are covered in Chapter 4.




Database System Concepts, 5 th Edition, Oct 5, 2006    3.5   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Create Table Construct
              s An SQL relation is defined using the create table command:
                                    create table r (A1 D1, A2 D2, ..., An Dn,
                                                 (integrity-constraint1),
                                                 ...,
                                                 (integrity-constraintk))
                     q r is the name of the relation
                     q each Ai is an attribute name in the schema of relation r

                     q   Di is the data type of values in the domain of attribute Ai


              s Example:
                                    create table branch
                                        (branch_name char(15) not null,
                                        branch_city    char(30),
                                        assets         integer)




Database System Concepts, 5 th Edition, Oct 5, 2006       3.6   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Integrity Constraints in Create Table

              s not null
              s primary key (A1, ..., An )



              Example: Declare branch_name as the primary key for branch
              .
                          create table branch
                                 (branch_name char(15),
                                   branch_city char(30),
                                  assets       integer,
                                  primary key (branch_name))




              primary key declaration on an attribute automatically ensures
                 not null in SQL-92 onwards, needs to be explicitly stated in
                 SQL-89


Database System Concepts, 5 th Edition, Oct 5, 2006   3.7   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Drop and Alter Table Constructs
             s The drop table command deletes all information about the
                  dropped relation from the database.
             s The alter table command is used to add attributes to an existing
                  relation:
                                              alter table r add A D
                  where A is the name of the attribute to be added to relation r and D
                  is the domain of A.
                    q   All tuples in the relation are assigned null as the value for the
                        new attribute.
             s The alter table command can also be used to drop attributes of a
                  relation:
                                              alter table r drop A
                  where A is the name of an attribute of relation r
                    q   Dropping of attributes not supported by many databases


Database System Concepts, 5 th Edition, Oct 5, 2006        3.8   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Basic Query Structure
             s SQL is based on set and relational operations with certain
                  modifications and enhancements
             s A typical SQL query has the form:

                                            select A1, A2, ..., An
                                            from r1, r2, ..., rm
                                            where P

                    q Ai represents an attribute
                    q Ri represents a relation
                    q P is a predicate.
             s This query is equivalent to the relational algebra expression.
                                      ∏ A1,A2 ,,An (σ P (r1 × r2 ×  × rm ))
             s The result of an SQL query is a relation.




Database System Concepts, 5 th Edition, Oct 5, 2006           3.9    ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The select Clause
             s The select clause list the attributes desired in the result of a query
                    q   corresponds to the projection operation of the relational algebra
             s Example: find the names of all branches in the loan relation:
                                                      select branch_name
                                                      from loan
             s In the relational algebra, the query would be:

                                                      ∏branch_name (loan)
             s NOTE: SQL names are case insensitive (i.e., you may use upper- or
                  lower-case letters.)
                    q   E.g. Branch_Name ≡ BRANCH_NAME ≡ branch_name
                    q   Some people use upper case wherever we use bold font.




Database System Concepts, 5 th Edition, Oct 5, 2006             3.10   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The select Clause (Cont.)
             s SQL allows duplicates in relations as well as in query results.
             s To force the elimination of duplicates, insert the keyword distinct after
                  select.
             s Find the names of all branches in the loan relations, and remove
                  duplicates
                                            select distinct branch_name
                                            from loan

             s The keyword all specifies that duplicates not be removed.


                                            select all branch_name
                                            from loan




Database System Concepts, 5 th Edition, Oct 5, 2006       3.11   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The select Clause (Cont.)
             s An asterisk in the select clause denotes “all attributes”
                                                      select *
                                                      from loan
             s The select clause can contain arithmetic expressions involving the
                  operation, +, –, ∗, and /, and operating on constants or attributes of
                  tuples.
             s The query:
                                      select loan_number, branch_name, amount ∗ 100
                                   from loan
                  would return a relation that is the same as the loan relation, except that
                  the value of the attribute amount is multiplied by 100.




Database System Concepts, 5 th Edition, Oct 5, 2006           3.12   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The where Clause
             s The where clause specifies conditions that the result must satisfy
                    q   Corresponds to the selection predicate of the relational algebra.
             s To find all loan number for loans made at the Perryridge branch with
                  loan amounts greater than $1200.
                                 select loan_number
                                 from loan
                                 where branch_name = 'Perryridge' and amount > 1200
             s Comparison results can be combined using the logical connectives and,
                  or, and not.
             s Comparisons can be applied to results of arithmetic expressions.




Database System Concepts, 5 th Edition, Oct 5, 2006   3.13   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The where Clause (Cont.)
             s SQL includes a between comparison operator
             s Example: Find the loan number of those loans with loan amounts between
                  $90,000 and $100,000 (that is, ≥ $90,000 and ≤ $100,000)
                      select loan_number
                             from loan
                             where amount between 90000 and 100000




Database System Concepts, 5 th Edition, Oct 5, 2006   3.14   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The from Clause
             s The from clause lists the relations involved in the query
                    q   Corresponds to the Cartesian product operation of the relational algebra.
             s Find the Cartesian product borrower X loan
                                     select ∗
                                     from borrower, loan
              s Find the name, loan number and loan amount of all customers
                having a loan at the Perryridge branch.

                 select customer_name, borrower.loan_number, amount
                       from borrower, loan
                       where borrower.loan_number = loan.loan_number and
                                   branch_name = 'Perryridge'




Database System Concepts, 5 th Edition, Oct 5, 2006   3.15   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
The Rename Operation
             s The SQL allows renaming relations and attributes using the as clause:
                                            old-name as new-name
             s Find the name, loan number and loan amount of all customers; rename the
                  column name loan_number as loan_id.


                select customer_name, borrower.loan_number as loan_id, amount
                from borrower, loan
                where borrower.loan_number = loan.loan_number




Database System Concepts, 5 th Edition, Oct 5, 2006      3.16   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Tuple Variables
              s Tuple variables are defined in the from clause via the use of the as
                   clause.
              s Find the customer names and their loan numbers for all customers
                   having a loan at some branch.

                          select customer_name, T.loan_number, S.amount
                                from borrower as T, loan as S
                                where T.loan_number = S.loan_number

             s     Find the names of all branches that have greater assets than
                   some branch located in Brooklyn.
                          select distinct T.branch_name
                        from branch as T, branch as S
                        where T.assets > S.assets and S.branch_city = 'Brooklyn'
             sKeyword as is optional and may be omitted
                    borrower as T ≡ borrower T




Database System Concepts, 5 th Edition, Oct 5, 2006    3.17   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
String Operations
             s SQL includes a string-matching operator for comparisons on character
                  strings. The operator “like” uses patterns that are described using two
                  special characters:
                    q   percent (%). The % character matches any substring.
                    q   underscore (_). The _ character matches any character.
             s Find the names of all customers whose street includes the substring
                  “Main”.
                                         select customer_name
                                         from customer
                                         where customer_street like '% Main%'
             s Match the name “Main%”
                                                 like 'Main%' escape ''
             s SQL supports a variety of string operations such as
                    q   concatenation (using “||”)
                    q    converting from upper to lower case (and vice versa)
                    q    finding string length, extracting substrings, etc.


Database System Concepts, 5 th Edition, Oct 5, 2006           3.18   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Ordering the Display of Tuples
              s List in alphabetic order the names of all customers having a loan in
                   Perryridge branch
                            select distinct customer_name
                            from borrower, loan
                            where borrower loan_number = loan.loan_number and
                                   branch_name = 'Perryridge'
                            order by customer_name
              s We may specify desc for descending order or asc for ascending
                   order, for each attribute; ascending order is the default.
                     q   Example: order by customer_name desc




Database System Concepts, 5 th Edition, Oct 5, 2006   3.19   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Duplicates
              s In relations with duplicates, SQL can define how many copies of tuples
                   appear in the result.
              s Multiset versions of some of the relational algebra operators – given
                   multiset relations r1 and r2:

                     1.    σ θ (r1 ): If there are c1 copies of tuple t1 in r1, and t1 satisfies
                          selections σθ,, then there are c1 copies of t1 in σθ (r1).

                     2. Π A (r ): For each copy of tuple t1 in r1, there is a copy of tuple
                          ΠA (t1) in ΠA (r1) where ΠA (t1) denotes the projection of the single
                          tuple t1.
                     3. r 1 x r2 : If there are c1 copies of tuple t1 in r1 and c2 copies of
                        tuple t2 in r2, there are c1 x c2 copies of the tuple t1. t2 in r1 x r2




Database System Concepts, 5 th Edition, Oct 5, 2006        3.20   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Duplicates (Cont.)
              s Example: Suppose multiset relations r1 (A, B) and r2 (C) are as
                   follows:
                                    r1 = {(1, a) (2,a)}    r2 = {(2), (3), (3)}
              s Then ΠB(r1) would be {(a), (a)}, while ΠB(r1) x r2 would be

                                    {(a,2), (a,2), (a,3), (a,3), (a,3), (a,3)}
              s SQL duplicate semantics:

                                    select A1,, A2, ..., An
                                    from r1, r2, ..., rm
                                    where P
                   is equivalent to the multiset version of the expression:

                                         ∏ A1,A2 ,,An (σ P (r1 × r2 ×  × rm ))



Database System Concepts, 5 th Edition, Oct 5, 2006           3.21   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Set Operations
              s The set operations union, intersect, and except operate on
                   relations and correspond to the relational algebra operations ∪, ∩, −.
              s Each of the above operations automatically eliminates duplicates; to
                   retain all duplicates use the corresponding multiset versions union
                   all, intersect all and except all.

                   Suppose a tuple occurs m times in r and n times in s, then, it occurs:
                     q   m + n times in r union all s
                     q   min(m,n) times in r intersect all s
                     q   max(0, m – n) times in r except all s




Database System Concepts, 5 th Edition, Oct 5, 2006     3.22   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Set Operations

              s Find all customers who have a loan, an account, or both:

                         (select customer_name from depositor)
                         union
                         (select customer_name from borrower)

             s Find all customers who have both a loan and an account.

                         (select customer_name from depositor)
                         intersect
                         (select customer_name from borrower)

             s Find all customers who have an account but no loan.

                         (select customer_name from depositor)
                         except
                         (select customer_name from borrower)




Database System Concepts, 5 th Edition, Oct 5, 2006   3.23   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Functions
              s These functions operate on the multiset of values of a column of
                   a relation, and return a value
                                               avg: average value
                                               min: minimum value
                                               max: maximum value
                                               sum: sum of values
                                               count: number of values




Database System Concepts, 5 th Edition, Oct 5, 2006        3.24   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Functions (Cont.)
              s Find the average account balance at the Perryridge branch.

                               select avg (balance)
                                       from account
                                       where branch_name = 'Perryridge'

             s Find the number of tuples in the customer relation.

                                select count (*)
                                        from customer

             s Find the number of depositors in the bank.

                               select count (distinct customer_name)
                                       from depositor




Database System Concepts, 5 th Edition, Oct 5, 2006   3.25   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Functions – Group By

             s Find the number of depositors for each branch.


                 select branch_name, count (distinct customer_name)
                       from depositor, account
                       where depositor.account_number = account.account_number
                       group by branch_name



                Note: Attributes in select clause outside of aggregate functions must
                      appear in group by list




Database System Concepts, 5 th Edition, Oct 5, 2006   3.26   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Aggregate Functions – Having
                                      Clause

              s Find the names of all branches where the average account balance is
                   more than $1,200.

                           select branch_name, avg (balance)
                                 from account
                                 group by branch_name
                                 having avg (balance) > 1200


                   Note: predicates in the having clause are applied after the
                         formation of groups whereas predicates in the where
                         clause are applied before forming groups




Database System Concepts, 5 th Edition, Oct 5, 2006   3.27   ©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 predicate is null can be used to check for null values.
                    q   Example: Find all loan number which appear in the loan relation
                        with null values for amount.
                           select loan_number
                           from loan
                           where amount is null
             s The result of any arithmetic expression involving null is null
                    q   Example: 5 + null returns null
             s However, aggregate functions simply ignore nulls
                    q   More on next slide




Database System Concepts, 5 th Edition, Oct 5, 2006       3.28   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Null Values and Three Valued Logic

             s Any comparison with null returns unknown
                    q   Example: 5 < null or null <> null        or    null = null
             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   “P is unknown” evaluates to true if predicate P evaluates to
                        unknown
             s Result of where clause predicate is treated as false if it evaluates to
                  unknown



Database System Concepts, 5 th Edition, Oct 5, 2006   3.29   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Null Values and Aggregates
             s Total all loan amounts
                                        select sum (amount )
                                        from loan
                    q   Above statement ignores null amounts
                    q   Result is null if there is no non-null amount
             s All aggregate operations except count(*) ignore tuples with null
                  values on the aggregated attributes.




Database System Concepts, 5 th Edition, Oct 5, 2006     3.30   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Nested Subqueries
             s SQL provides a mechanism for the nesting of subqueries.
             s A subquery is a select-from-where expression that is nested within
                  another query.
             s A common use of subqueries is to perform tests for set membership, set
                  comparisons, and set cardinality.




Database System Concepts, 5 th Edition, Oct 5, 2006   3.31   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Query
              s Find all customers who have both an account and a loan at the bank.



                            select distinct customer_name
                                    from borrower
                                    where customer_name in (select customer_name
                                                          from depositor )


             s Find all customers who have a loan at the bank but do not have
                  an account at the bank

                      select distinct customer_name
                              from borrower
                              where customer_name not in (select customer_name
                                                         from depositor )




Database System Concepts, 5 th Edition, Oct 5, 2006   3.32   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Query
             s Find all customers who have both an account and a loan at the
                  Perryridge branch


                       select distinct customer_name
                               from borrower, loan
                               where borrower.loan_number = loan.loan_number and
                                 branch_name = 'Perryridge' and
                                   (branch_name, customer_name ) in
                                        (select branch_name, customer_name
                                         from depositor, account
                                         where depositor.account_number =
                                             account.account_number )


             s Note: Above query can be written in a much simpler manner. The
                           formulation above is simply to illustrate SQL features.




Database System Concepts, 5 th Edition, Oct 5, 2006    3.33   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Set Comparison

             s Find all branches that have greater assets than some branch located
                  in Brooklyn.

                               select distinct T.branch_name
                                       from branch as T, branch as S
                                       where T.assets > S.assets and
                                                 S.branch_city = 'Brooklyn'

             s Same query using > some clause

                             select branch_name
                                     from branch
                                     where assets > some
                                             (select assets
                                              from branch
                                              where branch_city = 'Brooklyn')




Database System Concepts, 5 th Edition, Oct 5, 2006   3.34   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Definition of Some Clause

             s F <comp> some r ⇔ ∃ t ∈ r such that (F <comp> t )
                  Where <comp> can be: <, ≤, >, =, ≠

                                  0
              (5 < some           5      ) = true
                                                      (read: 5 < some tuple in the relation)
                                  6
                                  0
               (5 < some          5      ) = false

                                  0
               (5 = some          5      ) = true

                                  0
              (5 ≠ some           5      ) = true (since 0 ≠ 5)
             (= some) ≡ in
             However, (≠ some) ≡ not in


Database System Concepts, 5 th Edition, Oct 5, 2006          3.35   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Query
              s Find the names of all branches that have greater assets than all
                   branches located in Brooklyn.

                             select branch_name
                                     from branch
                                     where assets > all
                                             (select assets
                                             from branch
                                             where branch_city = 'Brooklyn')




Database System Concepts, 5 th Edition, Oct 5, 2006   3.36   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Definition of all Clause
              s F <comp> all r ⇔ ∀ t ∈ r (F <comp> t)


                                          0
                          (5 < all        5      ) = false
                                          6
                                         6
                           (5 < all      10      ) = true

                                          4
                           (5 = all       5      ) = false

                                          4
                           (5 ≠ all       6      ) = true (since 5 ≠ 4 and 5 ≠ 6)
                    (≠ all) ≡ not in
                    However, (= all) ≡ in



Database System Concepts, 5 th Edition, Oct 5, 2006           3.37   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Test for Empty Relations
             s The exists construct returns the value true if the argument subquery is
                  nonempty.
             s exists r ⇔ r ≠ Ø
             s not exists r ⇔ r = Ø




Database System Concepts, 5 th Edition, Oct 5, 2006   3.38   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Query
             s Find all customers who have an account at all branches located in
                  Brooklyn.

                 select distinct S.customer_name
                         from depositor as S
                         where not exists (
                                  (select branch_name
                                  from branch
                                  where branch_city = 'Brooklyn')
                                  except
                                  (select R.branch_name
                                  from depositor as T, account as R
                                  where T.account_number = R.account_number and
                                          S.customer_name = T.customer_name ))

             s Note that X – Y = Ø ⇔ X ⊆ Y
             s Note: Cannot write this query using = all and its variants



Database System Concepts, 5 th Edition, Oct 5, 2006   3.39   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Test for Absence of Duplicate Tuples

              s The unique construct tests whether a subquery has any duplicate
                   tuples in its result.
              s Find all customers who have at most one account at the Perryridge
                   branch.
                       select T.customer_name
                        from depositor as T
                        where unique (
                              select R.customer_name
                             from account, depositor as R
                             where T.customer_name = R.customer_name and
                                    R.account_number = account.account_number and
                                    account.branch_name = 'Perryridge')




Database System Concepts, 5 th Edition, Oct 5, 2006   3.40   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Query
              s Find all customers who have at least two accounts at the Perryridge
                   branch.

                        select distinct T.customer_name
                        from depositor as T
                        where not unique (
                           select R.customer_name
                           from account, depositor as R
                           where T.customer_name = R.customer_name and
                                  R.account_number = account.account_number and
                                   account.branch_name = 'Perryridge')

              s Variable from outer level is known as a correlation variable




Database System Concepts, 5 th Edition, Oct 5, 2006   3.41   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Derived Relations
             s SQL allows a subquery expression to be used in the from clause
             s Find the average account balance of those branches where the average
                  account balance is greater than $1200.
                              select branch_name, avg_balance
                              from (select branch_name, avg (balance)
                                    from account
                                    group by branch_name )
                                   as branch_avg ( branch_name, avg_balance )
                              where avg_balance > 1200
                  Note that we do not need to use the having clause, since we compute
                  the temporary (view) relation branch_avg in the from clause, and the
                  attributes of branch_avg can be used directly in the where clause.




Database System Concepts, 5 th Edition, Oct 5, 2006   3.42   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
With Clause
             s The with clause provides a way of defining a temporary view whose
                  definition is available only to the query in which the with clause
                  occurs.
             s Find all accounts with the maximum balance

                        with max_balance (value) as
                          select max (balance)
                          from account
                       select account_number
                       from account, max_balance
                       where account.balance = max_balance.value




Database System Concepts, 5 th Edition, Oct 5, 2006       3.43   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Complex Queries using With Clause
              s Find all branches where the total account deposit is greater than the
                   average of the total account deposits at all branches.

                      with branch_total (branch_name, value) as
                           select branch_name, sum (balance)
                           from account
                           group by branch_name
                     with branch_total_avg (value) as
                           select avg (value)
                           from branch_total
                     select branch_name
                     from branch_total, branch_total_avg
                     where branch_total.value >= branch_total_avg.value




Database System Concepts, 5 th Edition, Oct 5, 2006   3.44   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Views
             s In some cases, it is not desirable for all users to see the entire logical
                  model (that is, all the actual relations stored in the database.)
             s Consider a person who needs to know a customer’s name, loan number
                  and branch name, but has no need to see the loan amount. This person
                  should see a relation described, in SQL, by

                      (select customer_name, borrower.loan_number, branch_name
                              from borrower, loan
                              where borrower.loan_number = loan.loan_number )


             s A view provides a mechanism to hide certain data from the view of
                  certain users.
             s Any relation that is not of the conceptual model but is made visible to a
                  user as a “virtual relation” is called a view.




Database System Concepts, 5 th Edition, Oct 5, 2006    3.45   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
View Definition
              s A view is defined using the create view statement which has the
                   form
                                  create view v as < query expression >

                   where <query expression> is any legal SQL expression. The view
                   name is represented by v.
              s Once a view is defined, the view name can be used to refer to the
                   virtual relation that the view generates.
              s When a view is created, the query expression is stored in the
                   database; the expression is substituted into queries using the view.




Database System Concepts, 5 th Edition, Oct 5, 2006   3.46   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Queries
             s A view consisting of branches and their customers

                   create view all_customer as
                           (select branch_name, customer_name
                            from depositor, account
                           where depositor.account_number =
                                   account.account_number )
                           union
                           (select branch_name, customer_name
                           from borrower, loan
                           where borrower.loan_number = loan.loan_number )

             s Find all customers of the Perryridge branch

                           select customer_name
                                   from all_customer
                                   where branch_name = 'Perryridge'




Database System Concepts, 5 th Edition, Oct 5, 2006   3.47   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Views Defined Using Other Views
             s One view may be used in the expression defining another view
             s A view relation v1 is said to depend directly on a view relation v2 if v2 is
                  used in the expression defining v1
             s A view relation v1 is said to depend on view relation v2 if either v1
                  depends directly to v2 or there is a path of dependencies from v1 to
                  v2
             s A view relation v is said to be recursive if it depends on itself.




Database System Concepts, 5 th Edition, Oct 5, 2006   3.48   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
View Expansion
             s A way to define the meaning of views defined in terms of other views.
             s Let view v1 be defined by an expression e1 that may itself contain uses
                  of view relations.
             s View expansion of an expression repeats the following replacement
                  step:
                       repeat
                         Find any view relation vi in e1
                         Replace the view relation vi by the expression defining vi
                       until no more view relations are present in e1
             s As long as the view definitions are not recursive, this loop will
                  terminate




Database System Concepts, 5 th Edition, Oct 5, 2006   3.49   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Modification of the Database –
                                     Deletion

             s Delete all account tuples at the Perryridge branch
                                      delete from account
                                      where branch_name = 'Perryridge'


             s Delete all accounts at every branch located in the city ‘Needham’.
                  delete from account
                  where branch_name in (select branch_name
                                         from branch
                                         where branch_city = 'Needham')




Database System Concepts, 5 th Edition, Oct 5, 2006     3.50   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Example Query
              s Delete the record of all accounts with balances below the average at
                   the bank.


                       delete from account
                            where balance < (select avg (balance )
                                             from account )


                   q    Problem: as we delete tuples from deposit, the average balance
                        changes
                   q    Solution used in SQL:
                          1. First, compute avg balance and find all tuples to delete
                          2. Next, delete all tuples found above (without recomputing avg or
                             retesting the tuples)




Database System Concepts, 5 th Edition, Oct 5, 2006   3.51   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Modification of the Database –
                                      Insertion

             s Add a new tuple to account
                               insert into account
                                     values ('A-9732', 'Perryridge', 1200)

                 or equivalently

                     insert into account (branch_name, balance, account_number)
                             values ('Perryridge', 1200, 'A-9732')


             s Add a new tuple to account with balance set to null
                               insert into account
                                     values ('A-777','Perryridge', null )




Database System Concepts, 5 th Edition, Oct 5, 2006     3.52   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Modification of the Database –
                                    Insertion

             s Provide as a gift for all loan customers of the Perryridge branch, a $200
                  savings account. Let the loan number serve as the account number for the
                  new savings account
                      insert into account
                         select loan_number, branch_name, 200
                         from loan
                         where branch_name = 'Perryridge'
                      insert into depositor
                         select customer_name, loan_number
                         from loan, borrower
                         where branch_name = 'Perryridge'
                                 and loan.account_number = borrower.account_number
             s The select from where statement is evaluated fully before any of its
                  results are inserted into the relation (otherwise queries like
                        insert into table1 select * from table1
                  would cause problems)



Database System Concepts, 5 th Edition, Oct 5, 2006   3.53   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Modification of the Database –
                                    Updates

             s Increase all accounts with balances over $10,000 by 6%, all other
                  accounts receive 5%.
                    q   Write two update statements:
                                                update account
                                                set balance = balance ∗ 1.06
                                                where balance > 10000


                                                update account
                                                set balance = balance ∗ 1.05
                                                where balance ≤ 10000
                    q   The order is important
                    q   Can be done better using the case statement (next slide)




Database System Concepts, 5 th Edition, Oct 5, 2006          3.54   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Case Statement for Conditional
                                     Updates

             s Same query as before: Increase all accounts with balances over
                  $10,000 by 6%, all other accounts receive 5%.

                       update account
                       set balance = case
                                       when balance <= 10000 then balance *1.05
                                       else balance * 1.06
                                     end




Database System Concepts, 5 th Edition, Oct 5, 2006   3.55   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Update of a View
             s Create a view of all loan data in the loan relation, hiding the amount
                  attribute
                             create view loan_branch as
                                   select loan_number, branch_name
                                   from loan
             s Add a new tuple to branch_loan
                             insert into branch_loan
                                    values ('L-37‘, 'Perryridge‘)
                  This insertion must be represented by the insertion of the tuple
                                        ('L-37', 'Perryridge', null )
                  into the loan relation




Database System Concepts, 5 th Edition, Oct 5, 2006          3.56   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Updates Through Views (Cont.)
              s Some updates through views are impossible to translate into
                   updates on the database relations
                     q   create view v as
                                  select loan_number, branch_name, amount
                                  from loan
                                  where branch_name = ‘Perryridge’
                            insert into v values ( 'L-99','Downtown', '23')


              s Others cannot be translated uniquely
                     q   insert into all_customer values ('Perryridge', 'John')
                              Have to choose loan or account, and
                               create a new loan/account number!
              s Most SQL implementations allow updates only on simple views
                   (without aggregates) defined on a single relation



Database System Concepts, 5 th Edition, Oct 5, 2006     3.57   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Joined Relations**
             s Join operations take two relations and return as a result another
                  relation.
             s These additional operations are typically used as subquery
                  expressions in the from clause
             s Join condition – defines which tuples in the two relations match,
                  and what attributes are present in the result of the join.
             s Join type – defines how tuples in each relation that do not match any
                  tuple in the other relation (based on the join condition) are treated.




Database System Concepts, 5 th Edition, Oct 5, 2006   3.58   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Joined Relations – Datasets for
                                    Examples

              s Relation loan

              s Relation borrower




             s Note: borrower information missing for L-260 and loan
               information missing for L-155




Database System Concepts, 5 th Edition, Oct 5, 2006   3.59   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Joined Relations – Examples
              s loan inner join borrower on
                    loan.loan_number = borrower.loan_number




             s loan left outer join borrower on
               loan.loan_number = borrower.loan_number




Database System Concepts, 5 th Edition, Oct 5, 2006   3.60   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Joined Relations – Examples
              s loan natural inner join borrower




             s loan natural right outer join borrower




Database System Concepts, 5 th Edition, Oct 5, 2006   3.61   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Joined Relations – Examples
              s loan full outer join borrower using (loan_number)




             s Find all customers who have either an account or a loan (but not both)
               at the bank.

                     select customer_name
                             from (depositor natural full outer join borrower )
                             where account_number is null or loan_number is null




Database System Concepts, 5 th Edition, Oct 5, 2006   3.62   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
End of Chapter 3




        Database System Concepts, 1 st Ed.
©VNS InfoSolutions Private Limited, Varanasi(UP), India 221002
        See www.vnsispl.com for conditions on re-use
Figure 3.1: Database Schema

             branch (branch_name, branch_city, assets)
             customer (customer_name, customer_street, customer_city)
             loan (loan_number, branch_name, amount)
             borrower (customer_name, loan_number)
             account (account_number, branch_name, balance)
             depositor (customer_name, account_number)




Database System Concepts, 5 th Edition, Oct 5, 2006   3.64   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 3.3: Tuples inserted into loan
                          and borrower




Database System Concepts, 5 th Edition, Oct 5, 2006   3.65   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
Figure 3.4:
                     The loan and borrower relations




Database System Concepts, 5 th Edition, Oct 5, 2006   3.66   ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100

More Related Content

What's hot

MS SQL - Database Programming Concepts by RSolutions
MS SQL - Database Programming Concepts by RSolutionsMS SQL - Database Programming Concepts by RSolutions
MS SQL - Database Programming Concepts by RSolutions
RSolutions
 
SQL Differences SQL Interview Questions
SQL Differences  SQL Interview QuestionsSQL Differences  SQL Interview Questions
SQL Differences SQL Interview Questions
MLR Institute of Technology
 
321 Rac
321 Rac321 Rac
Database Systems - SQL - DCL Statements (Chapter 3/4)
Database Systems - SQL - DCL Statements (Chapter 3/4)Database Systems - SQL - DCL Statements (Chapter 3/4)
Database Systems - SQL - DCL Statements (Chapter 3/4)
Vidyasagar Mundroy
 
Arrays and lists in sql server 2008
Arrays and lists in sql server 2008Arrays and lists in sql server 2008
Arrays and lists in sql server 2008
nxthuong
 
Intro to T-SQL - 1st session
Intro to T-SQL - 1st sessionIntro to T-SQL - 1st session
Intro to T-SQL - 1st session
Medhat Dawoud
 
Mssm及assm下索引叶块分裂的测试
Mssm及assm下索引叶块分裂的测试Mssm及assm下索引叶块分裂的测试
Mssm及assm下索引叶块分裂的测试maclean liu
 

What's hot (12)

Er model
Er modelEr model
Er model
 
MS SQL - Database Programming Concepts by RSolutions
MS SQL - Database Programming Concepts by RSolutionsMS SQL - Database Programming Concepts by RSolutions
MS SQL - Database Programming Concepts by RSolutions
 
SQL Differences SQL Interview Questions
SQL Differences  SQL Interview QuestionsSQL Differences  SQL Interview Questions
SQL Differences SQL Interview Questions
 
321 Rac
321 Rac321 Rac
321 Rac
 
Using T-SQL
Using T-SQL Using T-SQL
Using T-SQL
 
Sql 2009
Sql 2009Sql 2009
Sql 2009
 
Database Systems - SQL - DCL Statements (Chapter 3/4)
Database Systems - SQL - DCL Statements (Chapter 3/4)Database Systems - SQL - DCL Statements (Chapter 3/4)
Database Systems - SQL - DCL Statements (Chapter 3/4)
 
Arrays and lists in sql server 2008
Arrays and lists in sql server 2008Arrays and lists in sql server 2008
Arrays and lists in sql server 2008
 
Module02
Module02Module02
Module02
 
Intro to T-SQL - 1st session
Intro to T-SQL - 1st sessionIntro to T-SQL - 1st session
Intro to T-SQL - 1st session
 
Mssm及assm下索引叶块分裂的测试
Mssm及assm下索引叶块分裂的测试Mssm及assm下索引叶块分裂的测试
Mssm及assm下索引叶块分裂的测试
 
Sql server
Sql serverSql server
Sql server
 

Viewers also liked

Er model
Er modelEr model
Er model
paddu123
 
Entity relationship(er) model
Entity relationship(er) modelEntity relationship(er) model
Entity relationship(er) modelRahul Khanwani
 
Learn Database Design with MySQL - Chapter 5 - Design principles & normalization
Learn Database Design with MySQL - Chapter 5 - Design principles & normalizationLearn Database Design with MySQL - Chapter 5 - Design principles & normalization
Learn Database Design with MySQL - Chapter 5 - Design principles & normalization
Eduonix Learning Solutions
 
Normalization of database_tables_chapter_4
Normalization of database_tables_chapter_4Normalization of database_tables_chapter_4
Normalization of database_tables_chapter_4Farhan Chishti
 
Normalization case
Normalization caseNormalization case
Normalization case
Prosanta Ghosh
 
Chapter 2 Relational Data Model-part1
Chapter 2 Relational Data Model-part1Chapter 2 Relational Data Model-part1
Chapter 2 Relational Data Model-part1
Eddyzulham Mahluzydde
 

Viewers also liked (6)

Er model
Er modelEr model
Er model
 
Entity relationship(er) model
Entity relationship(er) modelEntity relationship(er) model
Entity relationship(er) model
 
Learn Database Design with MySQL - Chapter 5 - Design principles & normalization
Learn Database Design with MySQL - Chapter 5 - Design principles & normalizationLearn Database Design with MySQL - Chapter 5 - Design principles & normalization
Learn Database Design with MySQL - Chapter 5 - Design principles & normalization
 
Normalization of database_tables_chapter_4
Normalization of database_tables_chapter_4Normalization of database_tables_chapter_4
Normalization of database_tables_chapter_4
 
Normalization case
Normalization caseNormalization case
Normalization case
 
Chapter 2 Relational Data Model-part1
Chapter 2 Relational Data Model-part1Chapter 2 Relational Data Model-part1
Chapter 2 Relational Data Model-part1
 

Similar to Vnsispl dbms concepts_ch3

VNSISPL_DBMS_Concepts_ch4
VNSISPL_DBMS_Concepts_ch4VNSISPL_DBMS_Concepts_ch4
VNSISPL_DBMS_Concepts_ch4
sriprasoon
 
VNSISPL_DBMS_Concepts_appA
VNSISPL_DBMS_Concepts_appAVNSISPL_DBMS_Concepts_appA
VNSISPL_DBMS_Concepts_appA
sriprasoon
 
Vnsispl dbms concepts_ch1
Vnsispl dbms concepts_ch1Vnsispl dbms concepts_ch1
Vnsispl dbms concepts_ch1
sriprasoon
 
VNSISPL_DBMS_Concepts_ch6
VNSISPL_DBMS_Concepts_ch6VNSISPL_DBMS_Concepts_ch6
VNSISPL_DBMS_Concepts_ch6
sriprasoon
 
VNSISPL_DBMS_Concepts_AppB
VNSISPL_DBMS_Concepts_AppBVNSISPL_DBMS_Concepts_AppB
VNSISPL_DBMS_Concepts_AppB
sriprasoon
 
VNSISPL_DBMS_Concepts_ch10
VNSISPL_DBMS_Concepts_ch10VNSISPL_DBMS_Concepts_ch10
VNSISPL_DBMS_Concepts_ch10
sriprasoon
 
VNSISPL_DBMS_Concepts_ch18
VNSISPL_DBMS_Concepts_ch18VNSISPL_DBMS_Concepts_ch18
VNSISPL_DBMS_Concepts_ch18
sriprasoon
 
VNSISPL_DBMS_Concepts_ch13
VNSISPL_DBMS_Concepts_ch13VNSISPL_DBMS_Concepts_ch13
VNSISPL_DBMS_Concepts_ch13
sriprasoon
 
DBMS_INTRODUCTION OF SQL
DBMS_INTRODUCTION OF SQLDBMS_INTRODUCTION OF SQL
DBMS_INTRODUCTION OF SQL
Azizul Mamun
 
Dbms ii mca-ch7-sql-2013
Dbms ii mca-ch7-sql-2013Dbms ii mca-ch7-sql-2013
Dbms ii mca-ch7-sql-2013
Prosanta Ghosh
 
Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013
Prosanta Ghosh
 
dbms first unit
dbms first unitdbms first unit
dbms first unit
Raghu Bright
 
VNSISPL_DBMS_Concepts_ch21
VNSISPL_DBMS_Concepts_ch21VNSISPL_DBMS_Concepts_ch21
VNSISPL_DBMS_Concepts_ch21
sriprasoon
 

Similar to Vnsispl dbms concepts_ch3 (20)

VNSISPL_DBMS_Concepts_ch4
VNSISPL_DBMS_Concepts_ch4VNSISPL_DBMS_Concepts_ch4
VNSISPL_DBMS_Concepts_ch4
 
Ch3
Ch3Ch3
Ch3
 
VNSISPL_DBMS_Concepts_appA
VNSISPL_DBMS_Concepts_appAVNSISPL_DBMS_Concepts_appA
VNSISPL_DBMS_Concepts_appA
 
Vnsispl dbms concepts_ch1
Vnsispl dbms concepts_ch1Vnsispl dbms concepts_ch1
Vnsispl dbms concepts_ch1
 
VNSISPL_DBMS_Concepts_ch6
VNSISPL_DBMS_Concepts_ch6VNSISPL_DBMS_Concepts_ch6
VNSISPL_DBMS_Concepts_ch6
 
VNSISPL_DBMS_Concepts_AppB
VNSISPL_DBMS_Concepts_AppBVNSISPL_DBMS_Concepts_AppB
VNSISPL_DBMS_Concepts_AppB
 
VNSISPL_DBMS_Concepts_ch10
VNSISPL_DBMS_Concepts_ch10VNSISPL_DBMS_Concepts_ch10
VNSISPL_DBMS_Concepts_ch10
 
VNSISPL_DBMS_Concepts_ch18
VNSISPL_DBMS_Concepts_ch18VNSISPL_DBMS_Concepts_ch18
VNSISPL_DBMS_Concepts_ch18
 
ch3
ch3ch3
ch3
 
Sql.pptx
Sql.pptxSql.pptx
Sql.pptx
 
Glossary
GlossaryGlossary
Glossary
 
VNSISPL_DBMS_Concepts_ch13
VNSISPL_DBMS_Concepts_ch13VNSISPL_DBMS_Concepts_ch13
VNSISPL_DBMS_Concepts_ch13
 
DBMS_INTRODUCTION OF SQL
DBMS_INTRODUCTION OF SQLDBMS_INTRODUCTION OF SQL
DBMS_INTRODUCTION OF SQL
 
Ch3
Ch3Ch3
Ch3
 
Dbms ii mca-ch7-sql-2013
Dbms ii mca-ch7-sql-2013Dbms ii mca-ch7-sql-2013
Dbms ii mca-ch7-sql-2013
 
Ch3
Ch3Ch3
Ch3
 
Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013
 
dbms first unit
dbms first unitdbms first unit
dbms first unit
 
VNSISPL_DBMS_Concepts_ch21
VNSISPL_DBMS_Concepts_ch21VNSISPL_DBMS_Concepts_ch21
VNSISPL_DBMS_Concepts_ch21
 
Ch9
Ch9Ch9
Ch9
 

More from sriprasoon

VNSISPL_DBMS_Concepts_AppC
VNSISPL_DBMS_Concepts_AppCVNSISPL_DBMS_Concepts_AppC
VNSISPL_DBMS_Concepts_AppC
sriprasoon
 
VNSISPL_DBMS_Concepts_ch25
VNSISPL_DBMS_Concepts_ch25VNSISPL_DBMS_Concepts_ch25
VNSISPL_DBMS_Concepts_ch25
sriprasoon
 
VNSISPL_DBMS_Concepts_ch24
VNSISPL_DBMS_Concepts_ch24VNSISPL_DBMS_Concepts_ch24
VNSISPL_DBMS_Concepts_ch24
sriprasoon
 
VNSISPL_DBMS_Concepts_ch23
VNSISPL_DBMS_Concepts_ch23VNSISPL_DBMS_Concepts_ch23
VNSISPL_DBMS_Concepts_ch23
sriprasoon
 
VNSISPL_DBMS_Concepts_ch22
VNSISPL_DBMS_Concepts_ch22VNSISPL_DBMS_Concepts_ch22
VNSISPL_DBMS_Concepts_ch22
sriprasoon
 
VNSISPL_DBMS_Concepts_ch20
VNSISPL_DBMS_Concepts_ch20VNSISPL_DBMS_Concepts_ch20
VNSISPL_DBMS_Concepts_ch20
sriprasoon
 
VNSISPL_DBMS_Concepts_ch19
VNSISPL_DBMS_Concepts_ch19VNSISPL_DBMS_Concepts_ch19
VNSISPL_DBMS_Concepts_ch19
sriprasoon
 
VNSISPL_DBMS_Concepts_ch17
VNSISPL_DBMS_Concepts_ch17VNSISPL_DBMS_Concepts_ch17
VNSISPL_DBMS_Concepts_ch17
sriprasoon
 
VNSISPL_DBMS_Concepts_ch16
VNSISPL_DBMS_Concepts_ch16VNSISPL_DBMS_Concepts_ch16
VNSISPL_DBMS_Concepts_ch16
sriprasoon
 
VNSISPL_DBMS_Concepts_ch15
VNSISPL_DBMS_Concepts_ch15VNSISPL_DBMS_Concepts_ch15
VNSISPL_DBMS_Concepts_ch15
sriprasoon
 
VNSISPL_DBMS_Concepts_ch14
VNSISPL_DBMS_Concepts_ch14VNSISPL_DBMS_Concepts_ch14
VNSISPL_DBMS_Concepts_ch14
sriprasoon
 
VNSISPL_DBMS_Concepts_ch12
VNSISPL_DBMS_Concepts_ch12VNSISPL_DBMS_Concepts_ch12
VNSISPL_DBMS_Concepts_ch12
sriprasoon
 
VNSISPL_DBMS_Concepts_ch11
VNSISPL_DBMS_Concepts_ch11VNSISPL_DBMS_Concepts_ch11
VNSISPL_DBMS_Concepts_ch11
sriprasoon
 
VNSISPL_DBMS_Concepts_ch8
VNSISPL_DBMS_Concepts_ch8VNSISPL_DBMS_Concepts_ch8
VNSISPL_DBMS_Concepts_ch8
sriprasoon
 
VNSISPL_DBMS_Concepts_ch5
VNSISPL_DBMS_Concepts_ch5VNSISPL_DBMS_Concepts_ch5
VNSISPL_DBMS_Concepts_ch5
sriprasoon
 
Inventory Management
Inventory ManagementInventory Management
Inventory Managementsriprasoon
 

More from sriprasoon (16)

VNSISPL_DBMS_Concepts_AppC
VNSISPL_DBMS_Concepts_AppCVNSISPL_DBMS_Concepts_AppC
VNSISPL_DBMS_Concepts_AppC
 
VNSISPL_DBMS_Concepts_ch25
VNSISPL_DBMS_Concepts_ch25VNSISPL_DBMS_Concepts_ch25
VNSISPL_DBMS_Concepts_ch25
 
VNSISPL_DBMS_Concepts_ch24
VNSISPL_DBMS_Concepts_ch24VNSISPL_DBMS_Concepts_ch24
VNSISPL_DBMS_Concepts_ch24
 
VNSISPL_DBMS_Concepts_ch23
VNSISPL_DBMS_Concepts_ch23VNSISPL_DBMS_Concepts_ch23
VNSISPL_DBMS_Concepts_ch23
 
VNSISPL_DBMS_Concepts_ch22
VNSISPL_DBMS_Concepts_ch22VNSISPL_DBMS_Concepts_ch22
VNSISPL_DBMS_Concepts_ch22
 
VNSISPL_DBMS_Concepts_ch20
VNSISPL_DBMS_Concepts_ch20VNSISPL_DBMS_Concepts_ch20
VNSISPL_DBMS_Concepts_ch20
 
VNSISPL_DBMS_Concepts_ch19
VNSISPL_DBMS_Concepts_ch19VNSISPL_DBMS_Concepts_ch19
VNSISPL_DBMS_Concepts_ch19
 
VNSISPL_DBMS_Concepts_ch17
VNSISPL_DBMS_Concepts_ch17VNSISPL_DBMS_Concepts_ch17
VNSISPL_DBMS_Concepts_ch17
 
VNSISPL_DBMS_Concepts_ch16
VNSISPL_DBMS_Concepts_ch16VNSISPL_DBMS_Concepts_ch16
VNSISPL_DBMS_Concepts_ch16
 
VNSISPL_DBMS_Concepts_ch15
VNSISPL_DBMS_Concepts_ch15VNSISPL_DBMS_Concepts_ch15
VNSISPL_DBMS_Concepts_ch15
 
VNSISPL_DBMS_Concepts_ch14
VNSISPL_DBMS_Concepts_ch14VNSISPL_DBMS_Concepts_ch14
VNSISPL_DBMS_Concepts_ch14
 
VNSISPL_DBMS_Concepts_ch12
VNSISPL_DBMS_Concepts_ch12VNSISPL_DBMS_Concepts_ch12
VNSISPL_DBMS_Concepts_ch12
 
VNSISPL_DBMS_Concepts_ch11
VNSISPL_DBMS_Concepts_ch11VNSISPL_DBMS_Concepts_ch11
VNSISPL_DBMS_Concepts_ch11
 
VNSISPL_DBMS_Concepts_ch8
VNSISPL_DBMS_Concepts_ch8VNSISPL_DBMS_Concepts_ch8
VNSISPL_DBMS_Concepts_ch8
 
VNSISPL_DBMS_Concepts_ch5
VNSISPL_DBMS_Concepts_ch5VNSISPL_DBMS_Concepts_ch5
VNSISPL_DBMS_Concepts_ch5
 
Inventory Management
Inventory ManagementInventory Management
Inventory Management
 

Recently uploaded

Chapter 4 - Islamic Financial Institutions in Malaysia.pptx
Chapter 4 - Islamic Financial Institutions in Malaysia.pptxChapter 4 - Islamic Financial Institutions in Malaysia.pptx
Chapter 4 - Islamic Financial Institutions in Malaysia.pptx
Mohd Adib Abd Muin, Senior Lecturer at Universiti Utara Malaysia
 
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
IreneSebastianRueco1
 
2024.06.01 Introducing a competency framework for languag learning materials ...
2024.06.01 Introducing a competency framework for languag learning materials ...2024.06.01 Introducing a competency framework for languag learning materials ...
2024.06.01 Introducing a competency framework for languag learning materials ...
Sandy Millin
 
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
The simplified electron and muon model, Oscillating Spacetime: The Foundation...The simplified electron and muon model, Oscillating Spacetime: The Foundation...
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
RitikBhardwaj56
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
Ashokrao Mane college of Pharmacy Peth-Vadgaon
 
Top five deadliest dog breeds in America
Top five deadliest dog breeds in AmericaTop five deadliest dog breeds in America
Top five deadliest dog breeds in America
Bisnar Chase Personal Injury Attorneys
 
Delivering Micro-Credentials in Technical and Vocational Education and Training
Delivering Micro-Credentials in Technical and Vocational Education and TrainingDelivering Micro-Credentials in Technical and Vocational Education and Training
Delivering Micro-Credentials in Technical and Vocational Education and Training
AG2 Design
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
MysoreMuleSoftMeetup
 
Azure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHatAzure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHat
Scholarhat
 
Best Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDABest Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDA
deeptiverma2406
 
Assignment_4_ArianaBusciglio Marvel(1).docx
Assignment_4_ArianaBusciglio Marvel(1).docxAssignment_4_ArianaBusciglio Marvel(1).docx
Assignment_4_ArianaBusciglio Marvel(1).docx
ArianaBusciglio
 
Landownership in the Philippines under the Americans-2-pptx.pptx
Landownership in the Philippines under the Americans-2-pptx.pptxLandownership in the Philippines under the Americans-2-pptx.pptx
Landownership in the Philippines under the Americans-2-pptx.pptx
JezreelCabil2
 
Digital Artifact 1 - 10VCD Environments Unit
Digital Artifact 1 - 10VCD Environments UnitDigital Artifact 1 - 10VCD Environments Unit
Digital Artifact 1 - 10VCD Environments Unit
chanes7
 
DRUGS AND ITS classification slide share
DRUGS AND ITS classification slide shareDRUGS AND ITS classification slide share
DRUGS AND ITS classification slide share
taiba qazi
 
"Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe..."Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe...
SACHIN R KONDAGURI
 
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Executive Directors Chat  Leveraging AI for Diversity, Equity, and InclusionExecutive Directors Chat  Leveraging AI for Diversity, Equity, and Inclusion
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
TechSoup
 
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Ashish Kohli
 
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdfANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
Priyankaranawat4
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
heathfieldcps1
 
PIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf IslamabadPIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf Islamabad
AyyanKhan40
 

Recently uploaded (20)

Chapter 4 - Islamic Financial Institutions in Malaysia.pptx
Chapter 4 - Islamic Financial Institutions in Malaysia.pptxChapter 4 - Islamic Financial Institutions in Malaysia.pptx
Chapter 4 - Islamic Financial Institutions in Malaysia.pptx
 
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
 
2024.06.01 Introducing a competency framework for languag learning materials ...
2024.06.01 Introducing a competency framework for languag learning materials ...2024.06.01 Introducing a competency framework for languag learning materials ...
2024.06.01 Introducing a competency framework for languag learning materials ...
 
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
The simplified electron and muon model, Oscillating Spacetime: The Foundation...The simplified electron and muon model, Oscillating Spacetime: The Foundation...
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
 
Top five deadliest dog breeds in America
Top five deadliest dog breeds in AmericaTop five deadliest dog breeds in America
Top five deadliest dog breeds in America
 
Delivering Micro-Credentials in Technical and Vocational Education and Training
Delivering Micro-Credentials in Technical and Vocational Education and TrainingDelivering Micro-Credentials in Technical and Vocational Education and Training
Delivering Micro-Credentials in Technical and Vocational Education and Training
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
 
Azure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHatAzure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHat
 
Best Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDABest Digital Marketing Institute In NOIDA
Best Digital Marketing Institute In NOIDA
 
Assignment_4_ArianaBusciglio Marvel(1).docx
Assignment_4_ArianaBusciglio Marvel(1).docxAssignment_4_ArianaBusciglio Marvel(1).docx
Assignment_4_ArianaBusciglio Marvel(1).docx
 
Landownership in the Philippines under the Americans-2-pptx.pptx
Landownership in the Philippines under the Americans-2-pptx.pptxLandownership in the Philippines under the Americans-2-pptx.pptx
Landownership in the Philippines under the Americans-2-pptx.pptx
 
Digital Artifact 1 - 10VCD Environments Unit
Digital Artifact 1 - 10VCD Environments UnitDigital Artifact 1 - 10VCD Environments Unit
Digital Artifact 1 - 10VCD Environments Unit
 
DRUGS AND ITS classification slide share
DRUGS AND ITS classification slide shareDRUGS AND ITS classification slide share
DRUGS AND ITS classification slide share
 
"Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe..."Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe...
 
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Executive Directors Chat  Leveraging AI for Diversity, Equity, and InclusionExecutive Directors Chat  Leveraging AI for Diversity, Equity, and Inclusion
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
 
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
Aficamten in HCM (SEQUOIA HCM TRIAL 2024)
 
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdfANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
 
The basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptxThe basics of sentences session 5pptx.pptx
The basics of sentences session 5pptx.pptx
 
PIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf IslamabadPIMS Job Advertisement 2024.pdf Islamabad
PIMS Job Advertisement 2024.pdf Islamabad
 

Vnsispl dbms concepts_ch3

  • 1. Chapter 3: SQL 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 3: SQL s Data Definition s Basic Query Structure s Set Operations s Aggregate Functions s Null Values s Nested Subqueries s Complex Queries s Views s Modification of the Database s Joined Relations** Database System Concepts, 5 th Edition, Oct 5, 2006 3.2 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 3. History s IBM Sequel language developed as part of System R project at the IBM San Jose Research Laboratory s Renamed Structured Query Language (SQL) s ANSI and ISO standard SQL: q SQL-86 q SQL-89 q SQL-92 q SQL:1999 (language name became Y2K compliant!) q SQL:2003 s Commercial systems offer most, if not all, SQL-92 features, plus varying feature sets from later standards and special proprietary features. q Not all examples here may work on your particular system. Database System Concepts, 5 th Edition, Oct 5, 2006 3.3 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 4. Data Definition Language Allows the specification of not only a set of relations but also information about each relation, including: s The schema for each relation. s The domain of values associated with each attribute. s Integrity constraints s The set of indices to be maintained for each relations. s Security and authorization information for each relation. s The physical storage structure of each relation on disk. Database System Concepts, 5 th Edition, Oct 5, 2006 3.4 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 5. Domain Types in SQL s char(n). Fixed length character string, with user-specified length n. s varchar(n). Variable length character strings, with user-specified maximum length n. s int. Integer (a finite subset of the integers that is machine-dependent). s smallint. Small integer (a machine-dependent subset of the integer domain type). s numeric(p,d). Fixed point number, with user-specified precision of p digits, with n digits to the right of decimal point. s real, double precision. Floating point and double-precision floating point numbers, with machine-dependent precision. s float(n). Floating point number, with user-specified precision of at least n digits. s More are covered in Chapter 4. Database System Concepts, 5 th Edition, Oct 5, 2006 3.5 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 6. Create Table Construct s An SQL relation is defined using the create table command: create table r (A1 D1, A2 D2, ..., An Dn, (integrity-constraint1), ..., (integrity-constraintk)) q r is the name of the relation q each Ai is an attribute name in the schema of relation r q Di is the data type of values in the domain of attribute Ai s Example: create table branch (branch_name char(15) not null, branch_city char(30), assets integer) Database System Concepts, 5 th Edition, Oct 5, 2006 3.6 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 7. Integrity Constraints in Create Table s not null s primary key (A1, ..., An ) Example: Declare branch_name as the primary key for branch . create table branch (branch_name char(15), branch_city char(30), assets integer, primary key (branch_name)) primary key declaration on an attribute automatically ensures not null in SQL-92 onwards, needs to be explicitly stated in SQL-89 Database System Concepts, 5 th Edition, Oct 5, 2006 3.7 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 8. Drop and Alter Table Constructs s The drop table command deletes all information about the dropped relation from the database. s The alter table command is used to add attributes to an existing relation: alter table r add A D where A is the name of the attribute to be added to relation r and D is the domain of A. q All tuples in the relation are assigned null as the value for the new attribute. s The alter table command can also be used to drop attributes of a relation: alter table r drop A where A is the name of an attribute of relation r q Dropping of attributes not supported by many databases Database System Concepts, 5 th Edition, Oct 5, 2006 3.8 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 9. Basic Query Structure s SQL is based on set and relational operations with certain modifications and enhancements s A typical SQL query has the form: select A1, A2, ..., An from r1, r2, ..., rm where P q Ai represents an attribute q Ri represents a relation q P is a predicate. s This query is equivalent to the relational algebra expression. ∏ A1,A2 ,,An (σ P (r1 × r2 ×  × rm )) s The result of an SQL query is a relation. Database System Concepts, 5 th Edition, Oct 5, 2006 3.9 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 10. The select Clause s The select clause list the attributes desired in the result of a query q corresponds to the projection operation of the relational algebra s Example: find the names of all branches in the loan relation: select branch_name from loan s In the relational algebra, the query would be: ∏branch_name (loan) s NOTE: SQL names are case insensitive (i.e., you may use upper- or lower-case letters.) q E.g. Branch_Name ≡ BRANCH_NAME ≡ branch_name q Some people use upper case wherever we use bold font. Database System Concepts, 5 th Edition, Oct 5, 2006 3.10 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 11. The select Clause (Cont.) s SQL allows duplicates in relations as well as in query results. s To force the elimination of duplicates, insert the keyword distinct after select. s Find the names of all branches in the loan relations, and remove duplicates select distinct branch_name from loan s The keyword all specifies that duplicates not be removed. select all branch_name from loan Database System Concepts, 5 th Edition, Oct 5, 2006 3.11 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 12. The select Clause (Cont.) s An asterisk in the select clause denotes “all attributes” select * from loan s The select clause can contain arithmetic expressions involving the operation, +, –, ∗, and /, and operating on constants or attributes of tuples. s The query: select loan_number, branch_name, amount ∗ 100 from loan would return a relation that is the same as the loan relation, except that the value of the attribute amount is multiplied by 100. Database System Concepts, 5 th Edition, Oct 5, 2006 3.12 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 13. The where Clause s The where clause specifies conditions that the result must satisfy q Corresponds to the selection predicate of the relational algebra. s To find all loan number for loans made at the Perryridge branch with loan amounts greater than $1200. select loan_number from loan where branch_name = 'Perryridge' and amount > 1200 s Comparison results can be combined using the logical connectives and, or, and not. s Comparisons can be applied to results of arithmetic expressions. Database System Concepts, 5 th Edition, Oct 5, 2006 3.13 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 14. The where Clause (Cont.) s SQL includes a between comparison operator s Example: Find the loan number of those loans with loan amounts between $90,000 and $100,000 (that is, ≥ $90,000 and ≤ $100,000) select loan_number from loan where amount between 90000 and 100000 Database System Concepts, 5 th Edition, Oct 5, 2006 3.14 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 15. The from Clause s The from clause lists the relations involved in the query q Corresponds to the Cartesian product operation of the relational algebra. s Find the Cartesian product borrower X loan select ∗ from borrower, loan s Find the name, loan number and loan amount of all customers having a loan at the Perryridge branch. select customer_name, borrower.loan_number, amount from borrower, loan where borrower.loan_number = loan.loan_number and branch_name = 'Perryridge' Database System Concepts, 5 th Edition, Oct 5, 2006 3.15 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 16. The Rename Operation s The SQL allows renaming relations and attributes using the as clause: old-name as new-name s Find the name, loan number and loan amount of all customers; rename the column name loan_number as loan_id. select customer_name, borrower.loan_number as loan_id, amount from borrower, loan where borrower.loan_number = loan.loan_number Database System Concepts, 5 th Edition, Oct 5, 2006 3.16 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 17. Tuple Variables s Tuple variables are defined in the from clause via the use of the as clause. s Find the customer names and their loan numbers for all customers having a loan at some branch. select customer_name, T.loan_number, S.amount from borrower as T, loan as S where T.loan_number = S.loan_number s Find the names of all branches that have greater assets than some branch located in Brooklyn. select distinct T.branch_name from branch as T, branch as S where T.assets > S.assets and S.branch_city = 'Brooklyn' sKeyword as is optional and may be omitted borrower as T ≡ borrower T Database System Concepts, 5 th Edition, Oct 5, 2006 3.17 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 18. String Operations s SQL includes a string-matching operator for comparisons on character strings. The operator “like” uses patterns that are described using two special characters: q percent (%). The % character matches any substring. q underscore (_). The _ character matches any character. s Find the names of all customers whose street includes the substring “Main”. select customer_name from customer where customer_street like '% Main%' s Match the name “Main%” like 'Main%' escape '' s SQL supports a variety of string operations such as q concatenation (using “||”) q converting from upper to lower case (and vice versa) q finding string length, extracting substrings, etc. Database System Concepts, 5 th Edition, Oct 5, 2006 3.18 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 19. Ordering the Display of Tuples s List in alphabetic order the names of all customers having a loan in Perryridge branch select distinct customer_name from borrower, loan where borrower loan_number = loan.loan_number and branch_name = 'Perryridge' order by customer_name s We may specify desc for descending order or asc for ascending order, for each attribute; ascending order is the default. q Example: order by customer_name desc Database System Concepts, 5 th Edition, Oct 5, 2006 3.19 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 20. Duplicates s In relations with duplicates, SQL can define how many copies of tuples appear in the result. s Multiset versions of some of the relational algebra operators – given multiset relations r1 and r2: 1. σ θ (r1 ): If there are c1 copies of tuple t1 in r1, and t1 satisfies selections σθ,, then there are c1 copies of t1 in σθ (r1). 2. Π A (r ): For each copy of tuple t1 in r1, there is a copy of tuple ΠA (t1) in ΠA (r1) where ΠA (t1) denotes the projection of the single tuple t1. 3. r 1 x r2 : If there are c1 copies of tuple t1 in r1 and c2 copies of tuple t2 in r2, there are c1 x c2 copies of the tuple t1. t2 in r1 x r2 Database System Concepts, 5 th Edition, Oct 5, 2006 3.20 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 21. Duplicates (Cont.) s Example: Suppose multiset relations r1 (A, B) and r2 (C) are as follows: r1 = {(1, a) (2,a)} r2 = {(2), (3), (3)} s Then ΠB(r1) would be {(a), (a)}, while ΠB(r1) x r2 would be {(a,2), (a,2), (a,3), (a,3), (a,3), (a,3)} s SQL duplicate semantics: select A1,, A2, ..., An from r1, r2, ..., rm where P is equivalent to the multiset version of the expression: ∏ A1,A2 ,,An (σ P (r1 × r2 ×  × rm )) Database System Concepts, 5 th Edition, Oct 5, 2006 3.21 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 22. Set Operations s The set operations union, intersect, and except operate on relations and correspond to the relational algebra operations ∪, ∩, −. s Each of the above operations automatically eliminates duplicates; to retain all duplicates use the corresponding multiset versions union all, intersect all and except all. Suppose a tuple occurs m times in r and n times in s, then, it occurs: q m + n times in r union all s q min(m,n) times in r intersect all s q max(0, m – n) times in r except all s Database System Concepts, 5 th Edition, Oct 5, 2006 3.22 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 23. Set Operations s Find all customers who have a loan, an account, or both: (select customer_name from depositor) union (select customer_name from borrower) s Find all customers who have both a loan and an account. (select customer_name from depositor) intersect (select customer_name from borrower) s Find all customers who have an account but no loan. (select customer_name from depositor) except (select customer_name from borrower) Database System Concepts, 5 th Edition, Oct 5, 2006 3.23 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 24. Aggregate Functions s These functions operate on the multiset of values of a column of a relation, and return a value avg: average value min: minimum value max: maximum value sum: sum of values count: number of values Database System Concepts, 5 th Edition, Oct 5, 2006 3.24 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 25. Aggregate Functions (Cont.) s Find the average account balance at the Perryridge branch. select avg (balance) from account where branch_name = 'Perryridge' s Find the number of tuples in the customer relation. select count (*) from customer s Find the number of depositors in the bank. select count (distinct customer_name) from depositor Database System Concepts, 5 th Edition, Oct 5, 2006 3.25 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 26. Aggregate Functions – Group By s Find the number of depositors for each branch. select branch_name, count (distinct customer_name) from depositor, account where depositor.account_number = account.account_number group by branch_name Note: Attributes in select clause outside of aggregate functions must appear in group by list Database System Concepts, 5 th Edition, Oct 5, 2006 3.26 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 27. Aggregate Functions – Having Clause s Find the names of all branches where the average account balance is more than $1,200. select branch_name, avg (balance) from account group by branch_name having avg (balance) > 1200 Note: predicates in the having clause are applied after the formation of groups whereas predicates in the where clause are applied before forming groups Database System Concepts, 5 th Edition, Oct 5, 2006 3.27 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 28. 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 predicate is null can be used to check for null values. q Example: Find all loan number which appear in the loan relation with null values for amount. select loan_number from loan where amount is null s The result of any arithmetic expression involving null is null q Example: 5 + null returns null s However, aggregate functions simply ignore nulls q More on next slide Database System Concepts, 5 th Edition, Oct 5, 2006 3.28 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 29. Null Values and Three Valued Logic s Any comparison with null returns unknown q Example: 5 < null or null <> null or null = null 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 “P is unknown” evaluates to true if predicate P evaluates to unknown s Result of where clause predicate is treated as false if it evaluates to unknown Database System Concepts, 5 th Edition, Oct 5, 2006 3.29 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 30. Null Values and Aggregates s Total all loan amounts select sum (amount ) from loan q Above statement ignores null amounts q Result is null if there is no non-null amount s All aggregate operations except count(*) ignore tuples with null values on the aggregated attributes. Database System Concepts, 5 th Edition, Oct 5, 2006 3.30 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 31. Nested Subqueries s SQL provides a mechanism for the nesting of subqueries. s A subquery is a select-from-where expression that is nested within another query. s A common use of subqueries is to perform tests for set membership, set comparisons, and set cardinality. Database System Concepts, 5 th Edition, Oct 5, 2006 3.31 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 32. Example Query s Find all customers who have both an account and a loan at the bank. select distinct customer_name from borrower where customer_name in (select customer_name from depositor ) s Find all customers who have a loan at the bank but do not have an account at the bank select distinct customer_name from borrower where customer_name not in (select customer_name from depositor ) Database System Concepts, 5 th Edition, Oct 5, 2006 3.32 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 33. Example Query s Find all customers who have both an account and a loan at the Perryridge branch select distinct customer_name from borrower, loan where borrower.loan_number = loan.loan_number and branch_name = 'Perryridge' and (branch_name, customer_name ) in (select branch_name, customer_name from depositor, account where depositor.account_number = account.account_number ) s Note: Above query can be written in a much simpler manner. The formulation above is simply to illustrate SQL features. Database System Concepts, 5 th Edition, Oct 5, 2006 3.33 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 34. Set Comparison s Find all branches that have greater assets than some branch located in Brooklyn. select distinct T.branch_name from branch as T, branch as S where T.assets > S.assets and S.branch_city = 'Brooklyn' s Same query using > some clause select branch_name from branch where assets > some (select assets from branch where branch_city = 'Brooklyn') Database System Concepts, 5 th Edition, Oct 5, 2006 3.34 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 35. Definition of Some Clause s F <comp> some r ⇔ ∃ t ∈ r such that (F <comp> t ) Where <comp> can be: <, ≤, >, =, ≠ 0 (5 < some 5 ) = true (read: 5 < some tuple in the relation) 6 0 (5 < some 5 ) = false 0 (5 = some 5 ) = true 0 (5 ≠ some 5 ) = true (since 0 ≠ 5) (= some) ≡ in However, (≠ some) ≡ not in Database System Concepts, 5 th Edition, Oct 5, 2006 3.35 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 36. Example Query s Find the names of all branches that have greater assets than all branches located in Brooklyn. select branch_name from branch where assets > all (select assets from branch where branch_city = 'Brooklyn') Database System Concepts, 5 th Edition, Oct 5, 2006 3.36 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 37. Definition of all Clause s F <comp> all r ⇔ ∀ t ∈ r (F <comp> t) 0 (5 < all 5 ) = false 6 6 (5 < all 10 ) = true 4 (5 = all 5 ) = false 4 (5 ≠ all 6 ) = true (since 5 ≠ 4 and 5 ≠ 6) (≠ all) ≡ not in However, (= all) ≡ in Database System Concepts, 5 th Edition, Oct 5, 2006 3.37 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 38. Test for Empty Relations s The exists construct returns the value true if the argument subquery is nonempty. s exists r ⇔ r ≠ Ø s not exists r ⇔ r = Ø Database System Concepts, 5 th Edition, Oct 5, 2006 3.38 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 39. Example Query s Find all customers who have an account at all branches located in Brooklyn. select distinct S.customer_name from depositor as S where not exists ( (select branch_name from branch where branch_city = 'Brooklyn') except (select R.branch_name from depositor as T, account as R where T.account_number = R.account_number and S.customer_name = T.customer_name )) s Note that X – Y = Ø ⇔ X ⊆ Y s Note: Cannot write this query using = all and its variants Database System Concepts, 5 th Edition, Oct 5, 2006 3.39 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 40. Test for Absence of Duplicate Tuples s The unique construct tests whether a subquery has any duplicate tuples in its result. s Find all customers who have at most one account at the Perryridge branch. select T.customer_name from depositor as T where unique ( select R.customer_name from account, depositor as R where T.customer_name = R.customer_name and R.account_number = account.account_number and account.branch_name = 'Perryridge') Database System Concepts, 5 th Edition, Oct 5, 2006 3.40 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 41. Example Query s Find all customers who have at least two accounts at the Perryridge branch. select distinct T.customer_name from depositor as T where not unique ( select R.customer_name from account, depositor as R where T.customer_name = R.customer_name and R.account_number = account.account_number and account.branch_name = 'Perryridge') s Variable from outer level is known as a correlation variable Database System Concepts, 5 th Edition, Oct 5, 2006 3.41 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 42. Derived Relations s SQL allows a subquery expression to be used in the from clause s Find the average account balance of those branches where the average account balance is greater than $1200. select branch_name, avg_balance from (select branch_name, avg (balance) from account group by branch_name ) as branch_avg ( branch_name, avg_balance ) where avg_balance > 1200 Note that we do not need to use the having clause, since we compute the temporary (view) relation branch_avg in the from clause, and the attributes of branch_avg can be used directly in the where clause. Database System Concepts, 5 th Edition, Oct 5, 2006 3.42 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 43. With Clause s The with clause provides a way of defining a temporary view whose definition is available only to the query in which the with clause occurs. s Find all accounts with the maximum balance with max_balance (value) as select max (balance) from account select account_number from account, max_balance where account.balance = max_balance.value Database System Concepts, 5 th Edition, Oct 5, 2006 3.43 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 44. Complex Queries using With Clause s Find all branches where the total account deposit is greater than the average of the total account deposits at all branches. with branch_total (branch_name, value) as select branch_name, sum (balance) from account group by branch_name with branch_total_avg (value) as select avg (value) from branch_total select branch_name from branch_total, branch_total_avg where branch_total.value >= branch_total_avg.value Database System Concepts, 5 th Edition, Oct 5, 2006 3.44 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 45. Views s In some cases, it is not desirable for all users to see the entire logical model (that is, all the actual relations stored in the database.) s Consider a person who needs to know a customer’s name, loan number and branch name, but has no need to see the loan amount. This person should see a relation described, in SQL, by (select customer_name, borrower.loan_number, branch_name from borrower, loan where borrower.loan_number = loan.loan_number ) s A view provides a mechanism to hide certain data from the view of certain users. s Any relation that is not of the conceptual model but is made visible to a user as a “virtual relation” is called a view. Database System Concepts, 5 th Edition, Oct 5, 2006 3.45 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 46. View Definition s A view is defined using the create view statement which has the form create view v as < query expression > where <query expression> is any legal SQL expression. The view name is represented by v. s Once a view is defined, the view name can be used to refer to the virtual relation that the view generates. s When a view is created, the query expression is stored in the database; the expression is substituted into queries using the view. Database System Concepts, 5 th Edition, Oct 5, 2006 3.46 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 47. Example Queries s A view consisting of branches and their customers create view all_customer as (select branch_name, customer_name from depositor, account where depositor.account_number = account.account_number ) union (select branch_name, customer_name from borrower, loan where borrower.loan_number = loan.loan_number ) s Find all customers of the Perryridge branch select customer_name from all_customer where branch_name = 'Perryridge' Database System Concepts, 5 th Edition, Oct 5, 2006 3.47 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 48. Views Defined Using Other Views s One view may be used in the expression defining another view s A view relation v1 is said to depend directly on a view relation v2 if v2 is used in the expression defining v1 s A view relation v1 is said to depend on view relation v2 if either v1 depends directly to v2 or there is a path of dependencies from v1 to v2 s A view relation v is said to be recursive if it depends on itself. Database System Concepts, 5 th Edition, Oct 5, 2006 3.48 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 49. View Expansion s A way to define the meaning of views defined in terms of other views. s Let view v1 be defined by an expression e1 that may itself contain uses of view relations. s View expansion of an expression repeats the following replacement step: repeat Find any view relation vi in e1 Replace the view relation vi by the expression defining vi until no more view relations are present in e1 s As long as the view definitions are not recursive, this loop will terminate Database System Concepts, 5 th Edition, Oct 5, 2006 3.49 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 50. Modification of the Database – Deletion s Delete all account tuples at the Perryridge branch delete from account where branch_name = 'Perryridge' s Delete all accounts at every branch located in the city ‘Needham’. delete from account where branch_name in (select branch_name from branch where branch_city = 'Needham') Database System Concepts, 5 th Edition, Oct 5, 2006 3.50 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 51. Example Query s Delete the record of all accounts with balances below the average at the bank. delete from account where balance < (select avg (balance ) from account ) q Problem: as we delete tuples from deposit, the average balance changes q Solution used in SQL: 1. First, compute avg balance and find all tuples to delete 2. Next, delete all tuples found above (without recomputing avg or retesting the tuples) Database System Concepts, 5 th Edition, Oct 5, 2006 3.51 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 52. Modification of the Database – Insertion s Add a new tuple to account insert into account values ('A-9732', 'Perryridge', 1200) or equivalently insert into account (branch_name, balance, account_number) values ('Perryridge', 1200, 'A-9732') s Add a new tuple to account with balance set to null insert into account values ('A-777','Perryridge', null ) Database System Concepts, 5 th Edition, Oct 5, 2006 3.52 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 53. Modification of the Database – Insertion s Provide as a gift for all loan customers of the Perryridge branch, a $200 savings account. Let the loan number serve as the account number for the new savings account insert into account select loan_number, branch_name, 200 from loan where branch_name = 'Perryridge' insert into depositor select customer_name, loan_number from loan, borrower where branch_name = 'Perryridge' and loan.account_number = borrower.account_number s The select from where statement is evaluated fully before any of its results are inserted into the relation (otherwise queries like insert into table1 select * from table1 would cause problems) Database System Concepts, 5 th Edition, Oct 5, 2006 3.53 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 54. Modification of the Database – Updates s Increase all accounts with balances over $10,000 by 6%, all other accounts receive 5%. q Write two update statements: update account set balance = balance ∗ 1.06 where balance > 10000 update account set balance = balance ∗ 1.05 where balance ≤ 10000 q The order is important q Can be done better using the case statement (next slide) Database System Concepts, 5 th Edition, Oct 5, 2006 3.54 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 55. Case Statement for Conditional Updates s Same query as before: Increase all accounts with balances over $10,000 by 6%, all other accounts receive 5%. update account set balance = case when balance <= 10000 then balance *1.05 else balance * 1.06 end Database System Concepts, 5 th Edition, Oct 5, 2006 3.55 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 56. Update of a View s Create a view of all loan data in the loan relation, hiding the amount attribute create view loan_branch as select loan_number, branch_name from loan s Add a new tuple to branch_loan insert into branch_loan values ('L-37‘, 'Perryridge‘) This insertion must be represented by the insertion of the tuple ('L-37', 'Perryridge', null ) into the loan relation Database System Concepts, 5 th Edition, Oct 5, 2006 3.56 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 57. Updates Through Views (Cont.) s Some updates through views are impossible to translate into updates on the database relations q create view v as select loan_number, branch_name, amount from loan where branch_name = ‘Perryridge’ insert into v values ( 'L-99','Downtown', '23') s Others cannot be translated uniquely q insert into all_customer values ('Perryridge', 'John')  Have to choose loan or account, and create a new loan/account number! s Most SQL implementations allow updates only on simple views (without aggregates) defined on a single relation Database System Concepts, 5 th Edition, Oct 5, 2006 3.57 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 58. Joined Relations** s Join operations take two relations and return as a result another relation. s These additional operations are typically used as subquery expressions in the from clause s Join condition – defines which tuples in the two relations match, and what attributes are present in the result of the join. s Join type – defines how tuples in each relation that do not match any tuple in the other relation (based on the join condition) are treated. Database System Concepts, 5 th Edition, Oct 5, 2006 3.58 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 59. Joined Relations – Datasets for Examples s Relation loan s Relation borrower s Note: borrower information missing for L-260 and loan information missing for L-155 Database System Concepts, 5 th Edition, Oct 5, 2006 3.59 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 60. Joined Relations – Examples s loan inner join borrower on loan.loan_number = borrower.loan_number s loan left outer join borrower on loan.loan_number = borrower.loan_number Database System Concepts, 5 th Edition, Oct 5, 2006 3.60 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 61. Joined Relations – Examples s loan natural inner join borrower s loan natural right outer join borrower Database System Concepts, 5 th Edition, Oct 5, 2006 3.61 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 62. Joined Relations – Examples s loan full outer join borrower using (loan_number) s Find all customers who have either an account or a loan (but not both) at the bank. select customer_name from (depositor natural full outer join borrower ) where account_number is null or loan_number is null Database System Concepts, 5 th Edition, Oct 5, 2006 3.62 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 63. End of Chapter 3 Database System Concepts, 1 st Ed. ©VNS InfoSolutions Private Limited, Varanasi(UP), India 221002 See www.vnsispl.com for conditions on re-use
  • 64. Figure 3.1: Database Schema branch (branch_name, branch_city, assets) customer (customer_name, customer_street, customer_city) loan (loan_number, branch_name, amount) borrower (customer_name, loan_number) account (account_number, branch_name, balance) depositor (customer_name, account_number) Database System Concepts, 5 th Edition, Oct 5, 2006 3.64 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 65. Figure 3.3: Tuples inserted into loan and borrower Database System Concepts, 5 th Edition, Oct 5, 2006 3.65 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100
  • 66. Figure 3.4: The loan and borrower relations Database System Concepts, 5 th Edition, Oct 5, 2006 3.66 ©VNS InfoSolutions Private Limited, Varanasi(UP), India 22100

Editor's Notes

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10