Submit Search
Upload
Introduction to SQL
•
Download as PPT, PDF
•
0 likes
•
69 views
D
DHAAROUN
Follow
Introduction to SQL.Here you can learn the basics of SQL.
Read less
Read more
Software
Report
Share
Report
Share
1 of 66
Download now
Recommended
Relational Database Design
Relational Database Design
Archit Saxena
Chapter 2 database environment
Chapter 2 database environment
>. <
Data Dictionary
Data Dictionary
Vishal Anand
STRUCTURE OF SQL QUERIES
STRUCTURE OF SQL QUERIES
VENNILAV6
SQL - Structured query language introduction
SQL - Structured query language introduction
Smriti Jain
Sql database object
Sql database object
Harry Potter
Relational Database Fundamentals
Relational Database Fundamentals
KHALID C
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
Raj vardhan
Recommended
Relational Database Design
Relational Database Design
Archit Saxena
Chapter 2 database environment
Chapter 2 database environment
>. <
Data Dictionary
Data Dictionary
Vishal Anand
STRUCTURE OF SQL QUERIES
STRUCTURE OF SQL QUERIES
VENNILAV6
SQL - Structured query language introduction
SQL - Structured query language introduction
Smriti Jain
Sql database object
Sql database object
Harry Potter
Relational Database Fundamentals
Relational Database Fundamentals
KHALID C
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
Raj vardhan
Dbms 3: 3 Schema Architecture
Dbms 3: 3 Schema Architecture
Amiya9439793168
Codd's rules
Codd's rules
Mohd Arif
Integrity Constraints
Integrity Constraints
Megha yadav
Chapter1
Chapter1
Jafar Nesargi
Introduction to database & sql
Introduction to database & sql
zahid6
Structure of dbms
Structure of dbms
Megha yadav
Relational database- Fundamentals
Relational database- Fundamentals
Mohammed El Hedhly
EER modeling
EER modeling
Dabbal Singh Mahara
Types Of Keys in DBMS
Types Of Keys in DBMS
PadamNepal1
Database : Relational Data Model
Database : Relational Data Model
Smriti Jain
Relational model
Relational model
Dabbal Singh Mahara
2 database system concepts and architecture
2 database system concepts and architecture
Kumar
MySql Triggers Tutorial - The Webs Academy
MySql Triggers Tutorial - The Webs Academy
thewebsacademy
Advanced sql
Advanced sql
Dhani Ahmad
Data Manipulation Language
Data Manipulation Language
Jas Singh Bhasin
Elmasri Navathe DBMS Unit-1 ppt
Elmasri Navathe DBMS Unit-1 ppt
AbhinavPandey274499
ER model to Relational model mapping
ER model to Relational model mapping
Shubham Saini
Sql Authorization
Sql Authorization
Fhuy
SQL for interview
SQL for interview
Aditya Kumar Tripathy
Dbms notes
Dbms notes
Prof. Dr. K. Adisesha
ch3.ppt
ch3.ppt
Ashwini Rao
Sql.pptx
Sql.pptx
TanishaKochak
More Related Content
What's hot
Dbms 3: 3 Schema Architecture
Dbms 3: 3 Schema Architecture
Amiya9439793168
Codd's rules
Codd's rules
Mohd Arif
Integrity Constraints
Integrity Constraints
Megha yadav
Chapter1
Chapter1
Jafar Nesargi
Introduction to database & sql
Introduction to database & sql
zahid6
Structure of dbms
Structure of dbms
Megha yadav
Relational database- Fundamentals
Relational database- Fundamentals
Mohammed El Hedhly
EER modeling
EER modeling
Dabbal Singh Mahara
Types Of Keys in DBMS
Types Of Keys in DBMS
PadamNepal1
Database : Relational Data Model
Database : Relational Data Model
Smriti Jain
Relational model
Relational model
Dabbal Singh Mahara
2 database system concepts and architecture
2 database system concepts and architecture
Kumar
MySql Triggers Tutorial - The Webs Academy
MySql Triggers Tutorial - The Webs Academy
thewebsacademy
Advanced sql
Advanced sql
Dhani Ahmad
Data Manipulation Language
Data Manipulation Language
Jas Singh Bhasin
Elmasri Navathe DBMS Unit-1 ppt
Elmasri Navathe DBMS Unit-1 ppt
AbhinavPandey274499
ER model to Relational model mapping
ER model to Relational model mapping
Shubham Saini
Sql Authorization
Sql Authorization
Fhuy
SQL for interview
SQL for interview
Aditya Kumar Tripathy
Dbms notes
Dbms notes
Prof. Dr. K. Adisesha
What's hot
(20)
Dbms 3: 3 Schema Architecture
Dbms 3: 3 Schema Architecture
Codd's rules
Codd's rules
Integrity Constraints
Integrity Constraints
Chapter1
Chapter1
Introduction to database & sql
Introduction to database & sql
Structure of dbms
Structure of dbms
Relational database- Fundamentals
Relational database- Fundamentals
EER modeling
EER modeling
Types Of Keys in DBMS
Types Of Keys in DBMS
Database : Relational Data Model
Database : Relational Data Model
Relational model
Relational model
2 database system concepts and architecture
2 database system concepts and architecture
MySql Triggers Tutorial - The Webs Academy
MySql Triggers Tutorial - The Webs Academy
Advanced sql
Advanced sql
Data Manipulation Language
Data Manipulation Language
Elmasri Navathe DBMS Unit-1 ppt
Elmasri Navathe DBMS Unit-1 ppt
ER model to Relational model mapping
ER model to Relational model mapping
Sql Authorization
Sql Authorization
SQL for interview
SQL for interview
Dbms notes
Dbms notes
Similar to Introduction to SQL
ch3.ppt
ch3.ppt
Ashwini Rao
Sql.pptx
Sql.pptx
TanishaKochak
Ch3
Ch3
Vivek Kumar
DBMS_INTRODUCTION OF SQL
DBMS_INTRODUCTION OF SQL
Azizul Mamun
ch3[1].ppt
ch3[1].ppt
IndraThanaya1
Ch3
Ch3
Deny Fauzy
Intro to Relational Model
Intro to Relational Model
HazemWaheeb1
ch3
ch3
KITE www.kitecolleges.com
DBMS _Relational model
DBMS _Relational model
Azizul Mamun
Ch4
Ch4
Welly Dian Astika
Relational Algebra and relational queries .ppt
Relational Algebra and relational queries .ppt
ShahidSultan24
Database System Concepts ch4.pdf
Database System Concepts ch4.pdf
UsamaAlZayan
Ch6 formal relational query languages
Ch6 formal relational query languages
uoitc
Unit04 dbms
Unit04 dbms
arnold 7490
Ch3
Ch3
Subhankar Chowdhury
Ch3
Ch3
balbeerrawat
Ch 2.pdf
Ch 2.pdf
MuhammadAsif1069
ch6.ppt
ch6.ppt
Shobi29
Ch3_Rel_Model-95.ppt
Ch3_Rel_Model-95.ppt
AtharvaBagul2
Ch3
Ch3
Ivan Krstic
Similar to Introduction to SQL
(20)
ch3.ppt
ch3.ppt
Sql.pptx
Sql.pptx
Ch3
Ch3
DBMS_INTRODUCTION OF SQL
DBMS_INTRODUCTION OF SQL
ch3[1].ppt
ch3[1].ppt
Ch3
Ch3
Intro to Relational Model
Intro to Relational Model
ch3
ch3
DBMS _Relational model
DBMS _Relational model
Ch4
Ch4
Relational Algebra and relational queries .ppt
Relational Algebra and relational queries .ppt
Database System Concepts ch4.pdf
Database System Concepts ch4.pdf
Ch6 formal relational query languages
Ch6 formal relational query languages
Unit04 dbms
Unit04 dbms
Ch3
Ch3
Ch3
Ch3
Ch 2.pdf
Ch 2.pdf
ch6.ppt
ch6.ppt
Ch3_Rel_Model-95.ppt
Ch3_Rel_Model-95.ppt
Ch3
Ch3
Recently uploaded
React Server Component in Next.js by Hanief Utama
React Server Component in Next.js by Hanief Utama
Hanief Utama
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
StefanoLambiase
MYjobs Presentation Django-based project
MYjobs Presentation Django-based project
AnoyGreter
Cloud Data Center Network Construction - IEEE
Cloud Data Center Network Construction - IEEE
VICTOR MAESTRE RAMIREZ
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
BradBedford3
Unveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML Diagrams
Ahmed Mohamed
software engineering Chapter 5 System modeling.pptx
software engineering Chapter 5 System modeling.pptx
nada99848
Salesforce Certified Field Service Consultant
Salesforce Certified Field Service Consultant
AxelRicardoTrocheRiq
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
stazi3110
Hot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort Service
Hot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort Service
9953056974 Low Rate Call Girls In Saket, Delhi NCR
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
Ortus Solutions, Corp
Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...
OnePlan Solutions
Implementing Zero Trust strategy with Azure
Implementing Zero Trust strategy with Azure
Dinusha Kumarasiri
chapter--4-software-project-planning.ppt
chapter--4-software-project-planning.ppt
kotipi9215
Folding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a series
Philip Schwarz
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
soniya singh
EY_Graph Database Powered Sustainability
EY_Graph Database Powered Sustainability
Neo4j
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
MyIntelliSource, Inc.
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
MyIntelliSource, Inc.
Asset Management Software - Infographic
Asset Management Software - Infographic
Hr365.us smith
Recently uploaded
(20)
React Server Component in Next.js by Hanief Utama
React Server Component in Next.js by Hanief Utama
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
Dealing with Cultural Dispersion — Stefano Lambiase — ICSE-SEIS 2024
MYjobs Presentation Django-based project
MYjobs Presentation Django-based project
Cloud Data Center Network Construction - IEEE
Cloud Data Center Network Construction - IEEE
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Adobe Marketo Engage Deep Dives: Using Webhooks to Transfer Data
Unveiling Design Patterns: A Visual Guide with UML Diagrams
Unveiling Design Patterns: A Visual Guide with UML Diagrams
software engineering Chapter 5 System modeling.pptx
software engineering Chapter 5 System modeling.pptx
Salesforce Certified Field Service Consultant
Salesforce Certified Field Service Consultant
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Building a General PDE Solving Framework with Symbolic-Numeric Scientific Mac...
Hot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort Service
Hot Sexy call girls in Patel Nagar🔝 9953056974 🔝 escort Service
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
BATTLEFIELD ORM: TIPS, TACTICS AND STRATEGIES FOR CONQUERING YOUR DATABASE
Advancing Engineering with AI through the Next Generation of Strategic Projec...
Advancing Engineering with AI through the Next Generation of Strategic Projec...
Implementing Zero Trust strategy with Azure
Implementing Zero Trust strategy with Azure
chapter--4-software-project-planning.ppt
chapter--4-software-project-planning.ppt
Folding Cheat Sheet #4 - fourth in a series
Folding Cheat Sheet #4 - fourth in a series
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
Russian Call Girls in Karol Bagh Aasnvi ➡️ 8264348440 💋📞 Independent Escort S...
EY_Graph Database Powered Sustainability
EY_Graph Database Powered Sustainability
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Try MyIntelliAccount Cloud Accounting Software As A Service Solution Risk Fre...
Asset Management Software - Infographic
Asset Management Software - Infographic
Introduction to SQL
1.
Database System Concepts,
6th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use Chapter 3: Introduction to SQL
2.
©Silberschatz, Korth and
Sudarshan 3.2 Database System Concepts - 6th Edition Outline Overview of The SQL Query Language Data Definition Basic Query Structure Additional Basic Operations Set Operations Null Values Aggregate Functions Nested Subqueries Modification of the Database
3.
©Silberschatz, Korth and
Sudarshan 3.3 Database System Concepts - 6th Edition History IBM Sequel language developed as part of System R project at the IBM San Jose Research Laboratory Renamed Structured Query Language (SQL) ANSI and ISO standard SQL: SQL-86 SQL-89 SQL-92 SQL:1999 (language name became Y2K compliant!) SQL:2003 Commercial systems offer most, if not all, SQL-92 features, plus varying feature sets from later standards and special proprietary features. Not all examples here may work on your particular system.
4.
©Silberschatz, Korth and
Sudarshan 3.4 Database System Concepts - 6th Edition Data Definition Language The schema for each relation. The domain of values associated with each attribute. Integrity constraints And as we will see later, also other information such as The set of indices to be maintained for each relations. Security and authorization information for each relation. The physical storage structure of each relation on disk. The SQL data-definition language (DDL) allows the specification of information about relations, including:
5.
©Silberschatz, Korth and
Sudarshan 3.5 Database System Concepts - 6th Edition Domain Types in SQL char(n). Fixed length character string, with user-specified length n. varchar(n). Variable length character strings, with user-specified maximum length n. int. Integer (a finite subset of the integers that is machine-dependent). smallint. Small integer (a machine-dependent subset of the integer domain type). numeric(p,d). Fixed point number, with user-specified precision of p digits, with d digits to the right of decimal point. (ex., numeric(3,1), allows 44.5 to be stores exactly, but not 444.5 or 0.32) real, double precision. Floating point and double-precision floating point numbers, with machine-dependent precision. float(n). Floating point number, with user-specified precision of at least n digits. More are covered in Chapter 4.
6.
©Silberschatz, Korth and
Sudarshan 3.6 Database System Concepts - 6th Edition Create Table Construct An SQL relation is defined using the create table command: create table r (A1 D1, A2 D2, ..., An Dn, (integrity-constraint1), ..., (integrity-constraintk)) r is the name of the relation each Ai is an attribute name in the schema of relation r Di is the data type of values in the domain of attribute Ai Example: create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8,2))
7.
©Silberschatz, Korth and
Sudarshan 3.7 Database System Concepts - 6th Edition Integrity Constraints in Create Table not null primary key (A1, ..., An ) foreign key (Am, ..., An ) references r Example: create table instructor ( ID char(5), name varchar(20) not null, dept_name varchar(20), salary numeric(8,2), primary key (ID), foreign key (dept_name) references department); primary key declaration on an attribute automatically ensures not null
8.
©Silberschatz, Korth and
Sudarshan 3.8 Database System Concepts - 6th Edition And a Few More Relation Definitions create table student ( ID varchar(5), name varchar(20) not null, dept_name varchar(20), tot_cred numeric(3,0), primary key (ID), foreign key (dept_name) references department); create table takes ( ID varchar(5), course_id varchar(8), sec_id varchar(8), semester varchar(6), year numeric(4,0), grade varchar(2), primary key (ID, course_id, sec_id, semester, year) , foreign key (ID) references student, foreign key (course_id, sec_id, semester, year) references section); Note: sec_id can be dropped from primary key above, to ensure a student cannot be registered for two sections of the same course in the same semester
9.
©Silberschatz, Korth and
Sudarshan 3.9 Database System Concepts - 6th Edition And more still create table course ( course_id varchar(8), title varchar(50), dept_name varchar(20), credits numeric(2,0), primary key (course_id), foreign key (dept_name) references department);
10.
©Silberschatz, Korth and
Sudarshan 3.10 Database System Concepts - 6th Edition Updates to tables Insert insert into instructor values (‘10211’, ’Smith’, ’Biology’, 66000); Delete Remove all tuples from the student relation delete from student Drop Table drop table r Alter 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. All exiting tuples in the relation are assigned null as the value for the new attribute. alter table r drop A where A is the name of an attribute of relation r Dropping of attributes not supported by many databases.
11.
©Silberschatz, Korth and
Sudarshan 3.11 Database System Concepts - 6th Edition Basic Query Structure A typical SQL query has the form: select A1, A2, ..., An from r1, r2, ..., rm where P Ai represents an attribute Ri represents a relation P is a predicate. The result of an SQL query is a relation.
12.
©Silberschatz, Korth and
Sudarshan 3.12 Database System Concepts - 6th Edition The select Clause The select clause lists the attributes desired in the result of a query corresponds to the projection operation of the relational algebra Example: find the names of all instructors: select name from instructor NOTE: SQL names are case insensitive (i.e., you may use upper- or lower-case letters.) E.g., Name ≡ NAME ≡ name Some people use upper case wherever we use bold font.
13.
©Silberschatz, Korth and
Sudarshan 3.13 Database System Concepts - 6th Edition The select Clause (Cont.) SQL allows duplicates in relations as well as in query results. To force the elimination of duplicates, insert the keyword distinct after select. Find the department names of all instructors, and remove duplicates select distinct dept_name from instructor The keyword all specifies that duplicates should not be removed. select all dept_name from instructor
14.
©Silberschatz, Korth and
Sudarshan 3.14 Database System Concepts - 6th Edition The select Clause (Cont.) An asterisk in the select clause denotes “all attributes” select * from instructor An attribute can be a literal with no from clause select ‘437’ Results is a table with one column and a single row with value “437” Can give the column a name using: select ‘437’ as FOO An attribute can be a literal with from clause select ‘A’ from instructor Result is a table with one column and N rows (number of tuples in the instructors table), each row with value “A”
15.
©Silberschatz, Korth and
Sudarshan 3.15 Database System Concepts - 6th Edition The select Clause (Cont.) The select clause can contain arithmetic expressions involving the operation, +, –, , and /, and operating on constants or attributes of tuples. The query: select ID, name, salary/12 from instructor would return a relation that is the same as the instructor relation, except that the value of the attribute salary is divided by 12. Can rename “salary/12” using the as clause: select ID, name, salary/12 as monthly_salary
16.
©Silberschatz, Korth and
Sudarshan 3.16 Database System Concepts - 6th Edition The where Clause The where clause specifies conditions that the result must satisfy Corresponds to the selection predicate of the relational algebra. To find all instructors in Comp. Sci. dept select name from instructor where dept_name = ‘Comp. Sci.' Comparison results can be combined using the logical connectives and, or, and not To find all instructors in Comp. Sci. dept with salary > 80000 select name from instructor where dept_name = ‘Comp. Sci.' and salary > 80000 Comparisons can be applied to results of arithmetic expressions.
17.
©Silberschatz, Korth and
Sudarshan 3.17 Database System Concepts - 6th Edition The from Clause The from clause lists the relations involved in the query Corresponds to the Cartesian product operation of the relational algebra. Find the Cartesian product instructor X teaches select from instructor, teaches generates every possible instructor – teaches pair, with all attributes from both relations. For common attributes (e.g., ID), the attributes in the resulting table are renamed using the relation name (e.g., instructor.ID) Cartesian product not very useful directly, but useful combined with where-clause condition (selection operation in relational algebra).
18.
©Silberschatz, Korth and
Sudarshan 3.18 Database System Concepts - 6th Edition Cartesian Product instructor teaches
19.
©Silberschatz, Korth and
Sudarshan 3.19 Database System Concepts - 6th Edition Examples Find the names of all instructors who have taught some course and the course_id select name, course_id from instructor , teaches where instructor.ID = teaches.ID Find the names of all instructors in the Art department who have taught some course and the course_id select name, course_id from instructor , teaches where instructor.ID = teaches.ID and instructor. dept_name = ‘Art’
20.
©Silberschatz, Korth and
Sudarshan 3.20 Database System Concepts - 6th Edition The Rename Operation The SQL allows renaming relations and attributes using the as clause: old-name as new-name Find the names of all instructors who have a higher salary than some instructor in ‘Comp. Sci’. select distinct T.name from instructor as T, instructor as S where T.salary > S.salary and S.dept_name = ‘Comp. Sci.’ Keyword as is optional and may be omitted instructor as T ≡ instructor T
21.
©Silberschatz, Korth and
Sudarshan 3.21 Database System Concepts - 6th Edition Self Join Example Relation emp-super Find the supervisor of “Bob” Find the supervisor of the supervisor of “Bob” Find ALL the supervisors (direct and indirect) of “Bob person supervisor Bob Alice Mary Susan Alice David David Mary
22.
©Silberschatz, Korth and
Sudarshan 3.22 Database System Concepts - 6th Edition String Operations SQL includes a string-matching operator for comparisons on character strings. The operator like uses patterns that are described using two special characters: percent ( % ). The % character matches any substring. underscore ( _ ). The _ character matches any character. Find the names of all instructors whose name includes the substring “dar”. select name from instructor where name like '%dar%' Match the string “100%” like ‘100 %' escape '' in that above we use backslash () as the escape character.
23.
©Silberschatz, Korth and
Sudarshan 3.23 Database System Concepts - 6th Edition String Operations (Cont.) Patterns are case sensitive. Pattern matching examples: ‘Intro%’ matches any string beginning with “Intro”. ‘%Comp%’ matches any string containing “Comp” as a substring. ‘_ _ _’ matches any string of exactly three characters. ‘_ _ _ %’ matches any string of at least three characters. SQL supports a variety of string operations such as concatenation (using “||”) converting from upper to lower case (and vice versa) finding string length, extracting substrings, etc.
24.
©Silberschatz, Korth and
Sudarshan 3.24 Database System Concepts - 6th Edition Ordering the Display of Tuples List in alphabetic order the names of all instructors select distinct name from instructor order by name We may specify desc for descending order or asc for ascending order, for each attribute; ascending order is the default. Example: order by name desc Can sort on multiple attributes Example: order by dept_name, name
25.
©Silberschatz, Korth and
Sudarshan 3.25 Database System Concepts - 6th Edition Where Clause Predicates SQL includes a between comparison operator Example: Find the names of all instructors with salary between $90,000 and $100,000 (that is, $90,000 and $100,000) select name from instructor where salary between 90000 and 100000 Tuple comparison select name, course_id from instructor, teaches where (instructor.ID, dept_name) = (teaches.ID, ’Biology’);
26.
©Silberschatz, Korth and
Sudarshan 3.26 Database System Concepts - 6th Edition Duplicates In relations with duplicates, SQL can define how many copies of tuples appear in the result. Multiset versions of some of the relational algebra operators – given multiset relations r1 and r2: 1. (r1): If there are c1 copies of tuple t1 in r1, and t1 satisfies selections ,, then there are c1 copies of t1 in (r1). 2. A (r ): For each copy of tuple t1 in r1, there is a copy of tuple A (t1) in A (r1) where A (t1) denotes the projection of the single tuple t1. 3. r1 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
27.
©Silberschatz, Korth and
Sudarshan 3.27 Database System Concepts - 6th Edition Duplicates (Cont.) Example: Suppose multiset relations r1 (A, B) and r2 (C) are as follows: r1 = {(1, a) (2,a)} r2 = {(2), (3), (3)} Then B(r1) would be {(a), (a)}, while B(r1) x r2 would be {(a,2), (a,2), (a,3), (a,3), (a,3), (a,3)} SQL duplicate semantics: select A1,, A2, ..., An from r1, r2, ..., rm where P is equivalent to the multiset version of the expression: )) ( ( 2 1 , , , 2 1 m P A A A r r r n
28.
©Silberschatz, Korth and
Sudarshan 3.28 Database System Concepts - 6th Edition Set Operations Find courses that ran in Fall 2009 or in Spring 2010 Find courses that ran in Fall 2009 but not in Spring 2010 (select course_id from section where sem = ‘Fall’ and year = 2009) union (select course_id from section where sem = ‘Spring’ and year = 2010) Find courses that ran in Fall 2009 and in Spring 2010 (select course_id from section where sem = ‘Fall’ and year = 2009) intersect (select course_id from section where sem = ‘Spring’ and year = 2010) (select course_id from section where sem = ‘Fall’ and year = 2009) except (select course_id from section where sem = ‘Spring’ and year = 2010)
29.
©Silberschatz, Korth and
Sudarshan 3.29 Database System Concepts - 6th Edition Set Operations (Cont.) Find the salaries of all instructors that are less than the largest salary. select distinct T.salary from instructor as T, instructor as S where T.salary < S.salary Find all the salaries of all instructors select distinct salary from instructor Find the largest salary of all instructors. (select “second query” ) except (select “first query”)
30.
©Silberschatz, Korth and
Sudarshan 3.30 Database System Concepts - 6th Edition Set Operations (Cont.) Set operations union, intersect, and except 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: m + n times in r union all s min(m,n) times in r intersect all s max(0, m – n) times in r except all s
31.
©Silberschatz, Korth and
Sudarshan 3.31 Database System Concepts - 6th Edition Null Values It is possible for tuples to have a null value, denoted by null, for some of their attributes null signifies an unknown value or that a value does not exist. The result of any arithmetic expression involving null is null Example: 5 + null returns null The predicate is null can be used to check for null values. Example: Find all instructors whose salary is null. select name from instructor where salary is null
32.
©Silberschatz, Korth and
Sudarshan 3.32 Database System Concepts - 6th Edition Null Values and Three Valued Logic Three values – true, false, unknown Any comparison with null returns unknown Example: 5 < null or null <> null or null = null Three-valued logic using the value unknown: OR: (unknown or true) = true, (unknown or false) = unknown (unknown or unknown) = unknown AND: (true and unknown) = unknown, (false and unknown) = false, (unknown and unknown) = unknown NOT: (not unknown) = unknown “P is unknown” evaluates to true if predicate P evaluates to unknown Result of where clause predicate is treated as false if it evaluates to unknown
33.
©Silberschatz, Korth and
Sudarshan 3.33 Database System Concepts - 6th Edition Aggregate Functions 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
34.
©Silberschatz, Korth and
Sudarshan 3.34 Database System Concepts - 6th Edition Aggregate Functions (Cont.) Find the average salary of instructors in the Computer Science department select avg (salary) from instructor where dept_name= ’Comp. Sci.’; Find the total number of instructors who teach a course in the Spring 2010 semester select count (distinct ID) from teaches where semester = ’Spring’ and year = 2010; Find the number of tuples in the course relation select count (*) from course;
35.
©Silberschatz, Korth and
Sudarshan 3.35 Database System Concepts - 6th Edition Aggregate Functions – Group By Find the average salary of instructors in each department select dept_name, avg (salary) as avg_salary from instructor group by dept_name; avg_salary
36.
©Silberschatz, Korth and
Sudarshan 3.36 Database System Concepts - 6th Edition Aggregation (Cont.) Attributes in select clause outside of aggregate functions must appear in group by list /* erroneous query */ select dept_name, ID, avg (salary) from instructor group by dept_name;
37.
©Silberschatz, Korth and
Sudarshan 3.37 Database System Concepts - 6th Edition Aggregate Functions – Having Clause Find the names and average salaries of all departments whose average salary is greater than 42000 Note: predicates in the having clause are applied after the formation of groups whereas predicates in the where clause are applied before forming groups select dept_name, avg (salary) from instructor group by dept_name having avg (salary) > 42000;
38.
©Silberschatz, Korth and
Sudarshan 3.38 Database System Concepts - 6th Edition Null Values and Aggregates Total all salaries select sum (salary ) from instructor Above statement ignores null amounts Result is null if there is no non-null amount All aggregate operations except count(*) ignore tuples with null values on the aggregated attributes What if collection has only null values? count returns 0 all other aggregates return null
39.
©Silberschatz, Korth and
Sudarshan 3.39 Database System Concepts - 6th Edition Nested Subqueries SQL provides a mechanism for the nesting of subqueries. A subquery is a select-from-where expression that is nested within another query. The nesting can be done in the following SQL query select A1, A2, ..., An from r1, r2, ..., rm where P as follows: Ai can be replaced be a subquery that generates a single value. ri can be replaced by any valid subquery P can be replaced with an expression of the form: B <operation> (subquery) Where B is an attribute and <operation> to be defined later.
40.
©Silberschatz, Korth and
Sudarshan 3.40 Database System Concepts - 6th Edition Subqueries in the Where Clause
41.
©Silberschatz, Korth and
Sudarshan 3.41 Database System Concepts - 6th Edition Subqueries in the Where Clause A common use of subqueries is to perform tests: For set membership For set comparisons For set cardinality.
42.
©Silberschatz, Korth and
Sudarshan 3.42 Database System Concepts - 6th Edition Set Membership Find courses offered in Fall 2009 and in Spring 2010 Find courses offered in Fall 2009 but not in Spring 2010 select distinct course_id from section where semester = ’Fall’ and year= 2009 and course_id in (select course_id from section where semester = ’Spring’ and year= 2010); select distinct course_id from section where semester = ’Fall’ and year= 2009 and course_id not in (select course_id from section where semester = ’Spring’ and year= 2010);
43.
©Silberschatz, Korth and
Sudarshan 3.43 Database System Concepts - 6th Edition Set Membership (Cont.) Find the total number of (distinct) students who have taken course sections taught by the instructor with ID 10101 Note: Above query can be written in a much simpler manner. The formulation above is simply to illustrate SQL features. select count (distinct ID) from takes where (course_id, sec_id, semester, year) in (select course_id, sec_id, semester, year from teaches where teaches.ID= 10101);
44.
©Silberschatz, Korth and
Sudarshan 3.44 Database System Concepts - 6th Edition Set Comparison – “some” Clause Find names of instructors with salary greater than that of some (at least one) instructor in the Biology department. Same query using > some clause select name from instructor where salary > some (select salary from instructor where dept name = ’Biology’); select distinct T.name from instructor as T, instructor as S where T.salary > S.salary and S.dept name = ’Biology’;
45.
©Silberschatz, Korth and
Sudarshan 3.45 Database System Concepts - 6th Edition Definition of “some” Clause F <comp> some r t r such that (F <comp> t ) Where <comp> can be: 0 5 6 (5 < some ) = true 0 5 0 ) = false 5 0 5 (5 some ) = true (since 0 5) (read: 5 < some tuple in the relation) (5 < some ) = true (5 = some (= some) in However, ( some) not in
46.
©Silberschatz, Korth and
Sudarshan 3.46 Database System Concepts - 6th Edition Set Comparison – “all” Clause Find the names of all instructors whose salary is greater than the salary of all instructors in the Biology department. select name from instructor where salary > all (select salary from instructor where dept name = ’Biology’);
47.
©Silberschatz, Korth and
Sudarshan 3.47 Database System Concepts - 6th Edition Definition of “all” Clause F <comp> all r t r (F <comp> t) 0 5 6 (5 < all ) = false 6 10 4 ) = true 5 4 6 (5 all ) = true (since 5 4 and 5 6) (5 < all ) = false (5 = all ( all) not in However, (= all) in
48.
©Silberschatz, Korth and
Sudarshan 3.48 Database System Concepts - 6th Edition Test for Empty Relations The exists construct returns the value true if the argument subquery is nonempty. exists r r Ø not exists r r = Ø
49.
©Silberschatz, Korth and
Sudarshan 3.49 Database System Concepts - 6th Edition Use of “exists” Clause Yet another way of specifying the query “Find all courses taught in both the Fall 2009 semester and in the Spring 2010 semester” select course_id from section as S where semester = ’Fall’ and year = 2009 and exists (select * from section as T where semester = ’Spring’ and year= 2010 and S.course_id = T.course_id); Correlation name – variable S in the outer query Correlated subquery – the inner query
50.
©Silberschatz, Korth and
Sudarshan 3.50 Database System Concepts - 6th Edition Use of “not exists” Clause Find all students who have taken all courses offered in the Biology department. select distinct S.ID, S.name from student as S where not exists ( (select course_id from course where dept_name = ’Biology’) except (select T.course_id from takes as T where S.ID = T.ID)); • First nested query lists all courses offered in Biology • Second nested query lists all courses a particular student took Note that X – Y = Ø X Y Note: Cannot write this query using = all and its variants
51.
©Silberschatz, Korth and
Sudarshan 3.51 Database System Concepts - 6th Edition Test for Absence of Duplicate Tuples The unique construct tests whether a subquery has any duplicate tuples in its result. The unique construct evaluates to “true” if a given subquery contains no duplicates . Find all courses that were offered at most once in 2009 select T.course_id from course as T where unique (select R.course_id from section as R where T.course_id= R.course_id and R.year = 2009);
52.
©Silberschatz, Korth and
Sudarshan 3.52 Database System Concepts - 6th Edition Subqueries in the Form Clause
53.
©Silberschatz, Korth and
Sudarshan 3.53 Database System Concepts - 6th Edition Subqueries in the Form Clause SQL allows a subquery expression to be used in the from clause Find the average instructors’ salaries of those departments where the average salary is greater than $42,000.” select dept_name, avg_salary from (select dept_name, avg (salary) as avg_salary from instructor group by dept_name) where avg_salary > 42000; Note that we do not need to use the having clause Another way to write above query select dept_name, avg_salary from (select dept_name, avg (salary) from instructor group by dept_name) as dept_avg (dept_name, avg_salary) where avg_salary > 42000;
54.
©Silberschatz, Korth and
Sudarshan 3.54 Database System Concepts - 6th Edition With Clause The with clause provides a way of defining a temporary relation whose definition is available only to the query in which the with clause occurs. Find all departments with the maximum budget with max_budget (value) as (select max(budget) from department) select department.name from department, max_budget where department.budget = max_budget.value;
55.
©Silberschatz, Korth and
Sudarshan 3.55 Database System Concepts - 6th Edition Complex Queries using With Clause Find all departments where the total salary is greater than the average of the total salary at all departments with dept _total (dept_name, value) as (select dept_name, sum(salary) from instructor group by dept_name), dept_total_avg(value) as (select avg(value) from dept_total) select dept_name from dept_total, dept_total_avg where dept_total.value > dept_total_avg.value;
56.
©Silberschatz, Korth and
Sudarshan 3.56 Database System Concepts - 6th Edition Subqueries in the Select Clause
57.
©Silberschatz, Korth and
Sudarshan 3.57 Database System Concepts - 6th Edition Scalar Subquery Scalar subquery is one which is used where a single value is expected List all departments along with the number of instructors in each department select dept_name, (select count(*) from instructor where department.dept_name = instructor.dept_name) as num_instructors from department; Runtime error if subquery returns more than one result tuple
58.
©Silberschatz, Korth and
Sudarshan 3.58 Database System Concepts - 6th Edition Modification of the Database Deletion of tuples from a given relation. Insertion of new tuples into a given relation Updating of values in some tuples in a given relation
59.
©Silberschatz, Korth and
Sudarshan 3.59 Database System Concepts - 6th Edition Deletion Delete all instructors delete from instructor Delete all instructors from the Finance department delete from instructor where dept_name= ’Finance’; Delete all tuples in the instructor relation for those instructors associated with a department located in the Watson building. delete from instructor where dept name in (select dept name from department where building = ’Watson’);
60.
©Silberschatz, Korth and
Sudarshan 3.60 Database System Concepts - 6th Edition Deletion (Cont.) Delete all instructors whose salary is less than the average salary of instructors delete from instructor where salary < (select avg (salary) from instructor); Problem: as we delete tuples from deposit, the average salary changes Solution used in SQL: 1. First, compute avg (salary) and find all tuples to delete 2. Next, delete all tuples found above (without recomputing avg or retesting the tuples)
61.
©Silberschatz, Korth and
Sudarshan 3.61 Database System Concepts - 6th Edition Insertion Add a new tuple to course insert into course values (’CS-437’, ’Database Systems’, ’Comp. Sci.’, 4); or equivalently insert into course (course_id, title, dept_name, credits) values (’CS-437’, ’Database Systems’, ’Comp. Sci.’, 4); Add a new tuple to student with tot_creds set to null insert into student values (’3003’, ’Green’, ’Finance’, null);
62.
©Silberschatz, Korth and
Sudarshan 3.62 Database System Concepts - 6th Edition Insertion (Cont.) Add all instructors to the student relation with tot_creds set to 0 insert into student select ID, name, dept_name, 0 from instructor 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 problem
63.
©Silberschatz, Korth and
Sudarshan 3.63 Database System Concepts - 6th Edition Updates Increase salaries of instructors whose salary is over $100,000 by 3%, and all others by a 5% Write two update statements: update instructor set salary = salary * 1.03 where salary > 100000; update instructor set salary = salary * 1.05 where salary <= 100000; The order is important Can be done better using the case statement (next slide)
64.
©Silberschatz, Korth and
Sudarshan 3.64 Database System Concepts - 6th Edition Case Statement for Conditional Updates Same query as before but with case statement update instructor set salary = case when salary <= 100000 then salary * 1.05 else salary * 1.03 end
65.
©Silberschatz, Korth and
Sudarshan 3.65 Database System Concepts - 6th Edition Updates with Scalar Subqueries Recompute and update tot_creds value for all students update student S set tot_cred = (select sum(credits) from takes, course where takes.course_id = course.course_id and S.ID= takes.ID.and takes.grade <> ’F’ and takes.grade is not null); Sets tot_creds to null for students who have not taken any course Instead of sum(credits), use: case when sum(credits) is not null then sum(credits) else 0 end
66.
Database System Concepts,
6th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use End of Chapter 3
Download now