Download Relational Languages SQL, QBE, Calculus

Κεφάλαιο 5
SQL Data Definition Language
και άλλες γλώσσες Σχεσιακών Βάσεων Δεδομένων
(QBE)
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SQL Data Definition

The Data Definition Language (DDL) of SQL is used to
CREATE, DROP and ALTER the descriptions of the relations
in the database
CREATE TABLE DEPARTMENT
( DNumber
integer
keymember 0
not null,
DName
varchar(12) keymember 1
not null,
MgrSSN
char(9)
references EMPLOYEE.SSN,
MgrSD
char(9)
);

In several (older) SQL systems, there is no support for
REFERENCES (foreign key) and KEYMEMBER (key)
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SQL DDL - continued

The command:
DROP TABLE DEPENDENT
deletes the full table DEPENDENT and its definition
longer be used in queries, updates, etc.)

(can no
The command:
ALTER TABLE EMPLOYEE ADD JOB VARCHAR(15)
adds a new attribute, named JOB, in relation EMPLOYEE
– All values for this new attribute will initially be NULL
– Ôhey can be changed in each tuple with the UPDATE command.
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Creating Indexes in SQL


In most cases, a base relation corresponds to a stored file
The CREATE INDEX command is used to specify an index
which always has a name (index name)
CREATE INDEX LN_INDEX on EMPLOYEE (Name);

To specify a key constraint on the indexing attribute (or
combination of attributes) the keyword UNIQUE is used
CREATE UNIQUE INDEX S_IND on EMPLOYEE (SSN);

To specify that an index is a clustering index, the keyword
CLUSTER is used
CREATE INDEX D_IN on EMPLOYEE(DNumber) CLUSTER;

In most DBMSs, a variation of the B+-tree is used as the
implementation data structure for indexes
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Relational Views and SQL

The three-level database architecture implies that different users
see different external schemas - this is accomplished with the
concept of VIEW in the relational model.
External
Schema 1
External
Schema 2
Conceptual
Schema
.....
External
Schema N
RELATIONAL
VIEWS
RELATIONAL
DATABASE
SCHEMA (RELATIONS)
Internal
Schema
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Relational Views - Definition

A VIEW is a relation which is not part of the conceptual
schema (the base relations) but is made visible to the user as a
virtual relation
– A user is not aware if a relation is a view or a base relation
– A view is not stored (materialized) in the database
– The contents of the view are determined by its stored definition as
a function of the contents of the stored database
– A view is defined on base tables or other views via a query
– Queries and updates on views are translated into queries and
updates on their defining base relations
– There are no limitations on querying a view
– Only few updates on views are allowed
– A view changes dynamically with the database
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Relational Views - Format
CREATE VIEW table_name
[ ( view_column_list ) ]
AS query_expression
[ WITH CHECK OPTION ]

V1: Project workers
CREATE VIEW PROJWORKER(EName, Address, Project)
AS select Name, Address, PName
from EMPLOYEE, PROJECT, WORKS_ON
where PROJECT.PNumber = WORKS_ON.PNumber
and WORKS_ON.SSN=EMPLOYEE.SSN ;
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Relational Views - Examples

When the view_column_list is missing, the view attributes are
inherited from the attribute names in the defining query

V2: Employees that are well-paid
CREATE VIEW BIGSHARKS
AS
select *
from EMPLOYEE
where Salary > 50000 and BirthDate > 31.12.65;
– The user may ask questions directly on this new table called
BIGSHARKS, which has exactly the same attribute names as the
base relation EMPLOYEE
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View Examples (2)

A view can have different units (attributes) than the
conceptual schema

V3: Information data on departments (average salary,
etc.)
CREATE VIEW DEPTINFO (Name, NoOfEmpl, AvgSalary)
AS
select DName, COUNT(*), AVG(Salary)
from DEPARTMENT d, EMPLOYEE e
where d.DNumber = e.DNumber
group by DName ;
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View Examples (3)

V4: Find the number of employees and average salary in
the research department (also print the department name)
select
from
where

*
DEPTINFO
Name = “research”
V5: Increase by 1 the number of employees in the research
department
– Such an update is NOT allowed (why?)
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View Execution

As said before, the system translates retrievals (updates) on
views into retrievals (updates) on the base relation(s).
HOW is this done?
– NAIVE Effort 1: Materialize the view (temporary table) and
then run the query on it.
– NAIVE Effort 2: Maintain the view at all times -- that is,
keep it materialized (called, a snapshot) and whenever
relevant updates on base relations are made then propagate
them on the view. Run the query on the snapshot.
– CORRECT Effort: Modify the query by replacing the view
with its defining query on base relations, and run the query
on these base relations.
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View Execution Example

For instance, given the query:
select
from
where
Name, Address
BIGSHARKS
DNumber = 5
we modify it accordingly and we execute the query:
select
from
where
Name, Address
EMPLOYEE
Salary > 50000 and BirthDate > 31.12.65
and DNumber = 5
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Updating on Views



In general, a view has restrictions on updates
A view update is unambiguous if one update on the base
relations can accomplish the desired update effect on the
view
OBSERVATIONS:
– A view with a single defining table is updatable if the view
attributes contain the primary key
– Views defined on multiple tables are generally not updatable
– Views defined with aggregate functions are not updatable

View updating is still an open research area
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VIEWS - Comments

The “WITH CHECK OPTION” is used with updatable views to
deal with the vanishing rows problem
For instance consider the view:
CREATE VIEW V AS select * from R where A = “X”
Now, assume the update:
UPDATE V set A = “Y”
The update will go on without a problem, but the rows (tuples) that
were previously seen in V will disappear! (they no longer meet the
WHERE-clause condition)


Views should be used whenever certain subqueries or
expressions are used very frequently
Views are also used as a security and authorization mechanism
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Integrity Constraints

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The relational model allows for the specification of 6 types of
integrity constraints: (a) entity integrity, (b) referential
integrity, (c) primary key integrity, (d) column integrity, (e)
domain integrity, and (f) user-defined.
Most commercial relational database systems do not enforce all
integrity constraints (enforcing means that if an update violates
a constraint, it is not allowed to execute)
We have seen how entity, referential and key integrity are
specified - they are the inherent to the model constraints ---The
other three constraints are explicitly specified. Modern
DBMSs enforce many of these constraints, with notable example
the system: Access 2.0 of Microsoft.
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Relational Model Constraints

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When enforcing (supporting) referential integrity, several
actions must be taken by the DBMS. These are usually the
cascade delete and the cascade update.
Some DBMSs support directly the cascade options (Access)
Other DBMSs require from the user to write triggers
(procedures) in order to support the options (SQL Server)
Column and Domain constraints are partially supported (not
always by strong-typing or other powerful mechanisms)
User-defined constraints were introduced in the newest SQL
standard (SQL-92) with ASSERTIONS (stand-alone rules)
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Assertions -- Examples

Every employee is either male or female
ASSERT gender ON EMPLOYEE: Sex=“m” OR Sex=“f”

Salaries have to be above 10000
ASSERT salary_bound ON EMPLOYEE: Salary > 10000
If someone attempts to insert a tuple in EMPLOYEE such as:
insert into EMPLOYEE (select Name=“tom”,.., Salary=12000..)
the update is modified from the assert rule to:
insert into EMPLOYEE (select Name=“tom”,.., Salary=12000..
where 12000 > 10000 )
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Embedding SQL in a Programming Language
DML commands are often embedded into host language
programs (these commands amount to calls to the DBMS)
 The embedded SQL statement is distinguished from the
programming language statements with a special “prefix”
 There are two ways to “embed” a DML:
1.- Extend the Programming Language (Compiler)
For example, RIGEL, MODULA-R, Gemstone, Orion, etc.)
These are called database programming languages
2.- Use a pre-processor for the DML statements
The pre-processor replaces all DML commands with calls to the
host language, which are then executed (the usual case)

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Example with C as Host

When SQL is embedded in C, all DML statements and all
declarations of variables are preceded by a “##”.
## char ename[30]
## int salary;
...
prog () {
## sql companydb
## select ename=Name, salary=Salary from EMPLOYEE
## where DNumber=5
## {
/* process returns values */
## }
}
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Embedded SQL

SQL commands can be called from within a host language
(e.g., C or COBOL) program.
– SQL statements can refer to host variables (including special
variables used to return status).
– Must include a statement to connect to the right database.
– Requires compiler preprocessing
– SQL relations are (multi-) sets of records, with no a priori
bound on the number of records. No such data structure in
C.
– SQL supports a mechanism called a cursor to handle this.
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Cursors



Can declare a cursor on a relation or query statement
(which generates a relation).
Can open a cursor, and repeatedly fetch a tuple then move
the cursor, until all tuples have been retrieved.
– Can use ORDER BY to control the order in which
tuples are returned.
» Fields in ORDER BY clause must also appear
in SELECT clause.
Can also modify/delete tuple pointed to by a cursor.
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Cursor that gets names of sailors who’ve reserved
a red boat, in alphabetical order

DECLARE sinfo CURSOR FOR
SELECT S.sname
FROM Sailors S, Boats B, Reserves R
WHERE S.sid=R.sid AND R.bid=B.bid AND B.color=‘red’
ORDER BY S.sname;
FETCH 5 IN sinfo;

Note that it is illegal to replace S.sname by, say, S.sid in the
ORDER BY clause! (Why?)
Can we add S.sid to the SELECT clause and replace S.sname by
S.sid in the ORDER BY clause???

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Embedding SQL in C -- An Example
char SQLSTATE[6];
EXEC SQL BEGIN DECLARE SECTION
char c_sname[20]; short c_minrating; float c_age;
EXEC SQL END DECLARE SECTION
c_minrating = random();
EXEC SQL DECLARE sinfo CURSOR FOR
SELECT S.sname, S.age FROM Sailors S
WHERE S.rating > :c_minrating
ORDER BY S.sname;
do {
EXEC SQL FETCH sinfo INTO :c_sname, :c_age;
printf(“%s is %d years old\n”, c_sname, c_age);
} while (SQLSTATE != ‘02000’);
EXEC SQL CLOSE sinfo;
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Database APIs: alternative to embedding

Rather than modify compiler, add library with database
calls (API)
– special procedures/objects
– passes SQL strings from language, presents result sets in a
language-friendly way
– Microsoft’s ODBC becoming C/C++ standard on Windows
– Sun’s JDBC a Java equivalent
– Supposedly DBMS-neutral
» a “driver” traps the calls and translates them into DBMSspecific code
» database can be across a network
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SQL API in Java (JDBC)
Connection con = // connect
DriverManager.getConnection(url, ”login", ”pass");
Statement stmt = con.createStatement(); // set up stmt
String query = "SELECT COF_NAME, PRICE FROM COFFEES";
ResultSet rs = stmt.executeQuery(query);
try { // handle exceptions
// loop through result tuples
while (rs.next()) {
String s = rs.getString("COF_NAME");
Float n = rs.getFloat("PRICE");
System.out.println(s + "
" + n);
}
} catch(SQLException ex) {
System.out.println(ex.getMessage ()
+ ex.getSQLState () + ex.getErrorCode ());
}
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Disadvantages of having Host Programming
Languages

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
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Mixing Procedural and Declarative languages (the famous
language mismatch problem)
Different pre-processors are required for different languages
Relations are not treated as 1st class objects in the language
(e.g., cannot pass a relation as a parameter to a procedure)
The host language may not support required constructs (e.g.,
FORTRAN does not support records)
The alternative, that is database programming languages are
gaining ground, especially in object-oriented DBMSs
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Shortcomings of SQL
SQL does not support strong typing, inheritance, etc.
 SQL tables are NOT relations (they allow duplicate rows)
 SQL tables can not be nested (be values of another table)
 SQL does not support several relational operators, like:
generalized restriction, division, forall
 SQL does not support 3-V logic (at least, not correctly)
 SQL does not support transition constraints
 SQL does not provide support for declaring (and using)
functional dependencies
 SQL does not support integrity constraints on views
DESPITE ALL THAT, SQL is the STANDARD LANGUAGE

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Query-by-Example (QBE)

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A Query Language developed at IBM (by Moshe Zloof) found
in a product called QMF (interface option to DB2)
Easier to use than SQL for the average end-user
(VISUAL and TWO-DIMENSIONAL)
IDEA: The system provides the user with a skeleton of the
relations in the database and the user fills-in the tables with
examples of what the answer should look like
QBE1: Find the names of employees in department 4
EMPLOYEE
SSN
Name
BDate
P.__x
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Address
Sex
Salary
SupSSN
DNumber
4
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QBE Summary

PRINCIPLES
–
–
–
–

user does not have to remember names of columns/relations
in query specification, no rigid rules apply
based on domain relational calculus (columns are variables)
relationally complete specification of queries, but also support of
transitive closure
HOW IT WORKS
– Tokens with an underscore preceding “_”, are VARIABLES
– Tokens with no underscore are CONSTANT VALUES (they
signify an equality selection-condition)
– The prefix “P.” is used to indicate which attributes will be printed
(it signifies a projection)
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QBE Summary - The Process

QUERY PROCESS
–
–
–
–
–
the user first chooses the tables needed to specify the query
templates of the chosen tables are displayed
user moves to the appropriate columns using special keys
example values (variables), constants, etc. are typed-in
other comparison operators than equality (automatic with a
constant value) must be typed-in (like, >, <, etc.)
– more complex conditions are entered in a condition box
– conditions in the same row, specify the Boolean AND
– conditions in distinct rows, specify the Boolean OR
– negation (Boolean NOT) is specified by the symbol “  “
– JOINS are expressed by using common example values in
multiple tables
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QBE -- Examples

QBE2:
Find the names of employees who work in a
department with a manager different than 3334
EMPLOYEE
SSN
Name
BDate
Address
Sex
P.__x
Salary
SupSSN
DNumber
no
DEPARTMENT
DNumber
DName
no
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MgrSSN
MgrSD

227
QBE -- Examples (2)

QBE3: Find names of employees who earn more than
30000 AND work in department 5
SSN
Name
BDate
Address
Sex
P.__x

Salary
SupSSN
>30000
DNumber
5
QBE4: Find names of employees who earn more than
30000 OR work in department 5
SSN
Name
BDate
Address
Sex
Salary
P. x
P. y
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SupSSN
DNumber
5
>30000
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QBE -- Examples (3)

QBE5: Find names and addresses of employees in
department 4 who earn more than someone who works in
department 5
EMPLOYEE
SSN
Name
BDate
P. tom
Address
Sex
Salary
P. kifis
CONDITION BOX
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SupSSN
DNumber
10
4
20
5
__10 > __20
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QBE -- Examples (4)

QBE6: Find names of employees who earn more than
their department manager
EMPLOYEE
SSN
Name
BDate
Address
P. tom
Sex
Salary
10
SupSSN
DNumber
6
__
4444
15
DEPARTMENT
DNumber
DName
6
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MgrSSN

MgrSD
CONDITION BOX
__10>__15
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QBE -- Examples (5)

QBE7: Find all DEPENDENT tuples for employees who
have a dependent born in 1972 while no other dependents
were born before 1975
DEPENDENT
ESSN
P.

Name Sex
BDate Relation
44
44
1972
44
<1975
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QBE -- Examples (6)

QBE8: Find the total salary of all the employees
EMPLOYEE
SSN
Name
BDate
Address
Sex
Salary
SupSSN
DNumber
P.SUM.ALL. x

QBE9: Insert a new employee
EMPLOYEE
SSN
I.
Name
6669 thomas
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BDate
Address
8.2.65
ekali
Sex
Salary
m
60000
SupSSN
9876
DNumber
4
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QBE -- Examples (7)

QBE10: Give a 15% salary increase to all employees in
department 5
EMPLOYEE
SSN
Name
44
BDate
Address
Sex
Salary
s
SupSSN
DNumber
5
__
U.
44
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s* 1.15
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A Peek at MS Access
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Summary




QBE is an elegant, user-friendly query language based on
DRC.
It is quite expressive (relationally complete, if the update
features are taken into account).
Simple queries are especially easy to write in QBE, and
there is a minimum of syntax to learn.
Has influenced the graphical query facilities offered in
many products, including Borland’s Paradox and
Microsoft’s Access.
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