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SQL: Queries, Constraints, Triggers

Structured Query Language

CS430/630
Lecture 4

Slides based on Database Management Systems 3rd ed, Ramakrishnan and Gehrke

Relational Query Language: SQL

Supports simple, yet powerful querying of data.

Precise semantics for relational queries.

DML (Data Manipulation Language)

DDL (Data Definition Language)

SQL developed by IBM (system R) in the 1970s

Standards:

SQL-86

SQL-89 (minor revision)

SQL-92 (major revision)

SQL-99 (major extensions, triggers, recursive queries)

SQL 2003 (XML), 2006, 2008, 2011

2

SQL Data Types

Character strings

CHAR(n), VARCHAR(n): fixed and variable-length strings

Bits

BOOLEAN values TRUE, FALSE, UNKNOWN

BIT(n)

Numerical:

INTEGER (INT)

Floating point: FLOAT (or REAL), DOUBLE PRECISION

Fixed precision: DECIMAL(n,d)

1234.56 is of type DECIMAL(6,2), precision 6, scale 2

DATE and TIME

3

Creating Relations in SQL

CREATE TABLE Students

(sid CHAR(20),
name CHAR(20),
login CHAR(10),
age INTEGER,
gpa REAL);

CREATE TABLE Enrolled

(sid CHAR(20),
cid CHAR(20),
grade CHAR(2));

DDL

4

DDL

Destroying and Altering Relations

Deletes relation Students, including schema information and

all the tuples

DROP TABLEStudents;

ALTER TABLEStudents
ADD firstYear INTEGER;

Add new column to schema

Every tuple is extended with NULL value in added field

Default value may be specified instead of NULL

DDL

DDL

5

Structure of SQL SELECT Query

relation-list= list of relation names

possibly with a range-variable after each name

target-list= list of attributes of relations in relation-list

qualification= conditions Attr op const or Attr1 op Attr2

op is one of , or string operators

Expressions connected using AND, OR and NOT

DISTINCT = optional, eliminates duplicates

By default duplicates are NOT eliminated!

SELECT[DISTINCT]target-list
FROM relation-list
WHEREqualification

,,,,,

Conceptual Evaluation Strategy

Semantics of SQL query

1. Compute the cross-product of relation-list

2. Discard resulting tuples if they fail qualifications

3. Delete attributes that are not in target-list

4. If DISTINCT is specified, eliminate duplicate rows

This strategy is least efficient way to compute a query!

Optimizer finds efficient strategies to compute the same result

Example Schema

sid sname rating age

22 dustin 7 45.0

31 lubber 8 55.5

58 rusty 10 35.0

sid bid day

22 101 10/10/96

58 103 11/12/96

Reserves

Sailors

bid name color

101 interlake red

103 clipper green

Boats

Conceptual Evaluation Example

SELECTS.sname
FROM Sailors S, Reserves R
WHERES.sid=R.sid AND R.bid=103

(sid) sname rating age (sid) bid day

22 dustin 7 45.0 22 101 10/10/96

22 dustin 7 45.0 58 103 11/12/96

31 lubber 8 55.5 22 101 10/10/96

31 lubber 8 55.5 58 103 11/12/96

58 rusty 10 35.0 22 101 10/10/96

58 rusty 10 35.0 58 103 11/12/96

A Note on Range Variables

Really needed only if the same relation appears twice in

the FROM clause (SELECT FROM Sailors S1, Sailors S2)

SELECTS.sname
FROM Sailors S, Reserves R
WHERES.sid=R.sid AND R.bid=103

SELECTsname
FROM Sailors, Reserves
WHERESailors.sid=Reserves.sid AND bid=103

It is good style,
however, to use
range variables
always!

Instead of

Duplicate Tuples and DISTINCT

Would adding DISTINCT to this query make a difference?

What is the effect of replacing S.sname by S.sid in the

SELECT clause?

Would adding DISTINCT to this variant of the query

make a difference?

SELECTS.sname
FROMSailors S, Reserves R
WHERES.sid=R.sid

Expressions and Strings

Find rating and number of years to retirement for sailors whose

names begin with d, end with n and contain at least three

characters

AS allows to (re)name fields in result.

LIKE is used for string matching

_ stands for any one character

% stands for 0 or more arbitrary characters

SELECTS.rating, 60 S.age AS Yr_to_retire
FROMSailors S
WHERES.sname LIKEd_%n

Expressions and Strings Example

Sailors

sid sname rating age

22 dustin 7 45.0

31 lubber 8 55.5

58 rusty 10 35.0

SELECTS.rating, 60 S.age AS Yr_to_retire
FROMSailors S
WHERES.sname LIKE d_%n

rating Yr_to_retire

7 15

Set Operations

UNION

compute the union of any two union-compatible sets of tuples

INTERSECT

compute the intersection of any two union-compatible sets of

tuples

EXCEPT or MINUS

Set difference of any two union-compatible sets of tuples

Duplicates eliminated by default!

UNION ALL, INTERSECT ALL, EXCEPT ALL retain duplicates

Contrast with non-set SQL operations

Adding and Deleting Tuples

Insert single tuple

INSERT INTOStudents (sid, name, login, age, gpa)
VALUES(53688, Smith, smith@ee, 18, 3.2);

DELETE
FROM Students S
WHERE S.name = Smith;

Delete all tuples satisfying condition

15

Data Modifications: Inserts

Values and attribute domains must match

Attributes not specified will be assigned value NULL

Variation: insert tuples returned by SELECT

INSERT INTOTable (attr1, attr2, )
VALUES(val1, val2, );

INSERT INTOTable (attr1, attr2, )
SELECT col1, col2,
FROM
[WHERE
GROUP BY
HAVING ];

Data Modifications: Updates

No new tuples created

Attribute values of existing tuples modified

Values and attribute domains must match

It is possible to use subqueries:

UPDATE Table
SETattr1=expression1, attr2=expression2 [,]
WHERE condition;

UPDATE Table
SETattr1= (SELECT value1
FROM
WHERE )
WHERE condition;

Integrity Constraints (ICs)

IC: condition that must hold for any instance of the

database; e.g., domain constraints

Specified when schema is defined.

Checked when relations are modified.

A legal instance satisfies all specified ICs

It is the DBMSs role to enforce IC

ICs we study

Primary key constraints

Foreign key constraints

Referential integrity

18

Primary and Candidate Keys in SQL

Primary keys specified by keyword PRIMARY KEY

Candidate keysspecified by keyword UNIQUE

Distinctions between the two:

Any attribute in the primary key is NOT allowed to have NULL

values

Primary key attributes may have special roles in the DBMS internals

(although from the logical point of view is same as unique)

Declaration

In-line with the respective attribute

Only if one-attribute key!

Or as separate constraint line

19

Keys in SQL Examples

Schema and Instance

Enrolled

sid cid grade

53666 114 A

53650 115 B

53666 115 B

Students Courses

sid sname age

53666 Smith 20

53650 Jones 25

53681 Adams 22

cid cname room

114 Calculus M123

115 Databases M234

Keys in SQL Examples

CREATE TABLE Enrolled
(sid CHAR(20),
cidCHAR(20),
grade CHAR(2),
PRIMARY KEY(sid,cid))

For a given student and course,
there is a single grade.

Students can take only one course,
and receive a single grade for that
course; further, no two students in
a course receive the same grade.

CREATE TABLE Enrolled
(sid CHAR(20) PRIMARY KEY,
cidCHAR(20),
grade CHAR(2),
UNIQUE (cid, grade) )

Foreign Keys, Referential Integrity

Foreign key

Set of fields in relation A that refer to a tuple in relation B

Must correspond to primary key of relation B (or UNIQUE)

Not necessary for field names in A and B to be the same!!!

FOREIGN KEY (attr1) REFERENCES B (attr2)

E.g. sid in Enrolled is a foreign key referring to Students:

Enrolled(sid: string, cid: string, grade: string)

Referential integrity is achieved by enforcing all foreign keys

no dangling references

22

Foreign Keys in SQL

Only students listed in the Students relation should be

allowed to enroll for courses

CREATE TABLE Enrolled
(sid CHAR(20),cid CHAR(20),grade CHAR(2),
PRIMARY KEY(sid,cid),
FOREIGN KEY (sid) REFERENCES Students )

Enrolled Students

23

sid cid grade

53666 114 A

53650 115 B

53666 115 B

sid sname age

53666 Smith 20

53650 Jones 25

53681 Adams 22

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