1. SQL Primer
SQL Primer
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2. SQL Overview
Text-based query language developed by IBM for an experimental RDBMS called System R
originally called SEQUEL
Most widely supported query language among commercial RDBMS products
although no one supports the standard exactly
Uses the more informal terms table, row, and column in place of relation, tuple, and attribute
Declarative, not procedural
Large, comprehensive database language
reference document is over 600 pages long
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3. ANSI/ISO Standardization
Year
Name
Comment
1986
SQL-86
Initial standard
1989
SQL-89
Minor revision
1992
SQL-92
(a.k.a. SQL2)
Major revision (ISO 9075)
1999
SQL:1999
(a.k.a. SQL3)
Added regular expressions, recursive queries, triggers, non-scalar types, some O-O features.
2003
SQL:2003
Introduced XML-related features and auto-generated column values.
2006
SQL:2006
Defined ways of importing and storing XML data.
2008
SQL:2008
Added INSTEAD OF triggers and TRUNCATE statement.
2011
SQL:2011
Added temporal data definition and manipulation.
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4. SQL Data Types Boolean and Bit String Types Character types
SQL Primer
SQL Data Types
Boolean and Bit String Types
boolean : can be true, false, or null
bit(n) : n-length bit string (exactly n binary bits)
bit varying(n), varbit(n) : variable n-length bit string (up to n binary bits)
Character types
character (n), char(n) : fixed n-length character string
character varying(n), varchar(n) : variable length character string of up to n characters
national character(n) or nchar(n) : fixed n-length string supporting an international character set
national character varying(n) or nvarchar(n) : variable length string supporting an international character set
no longer
part of SQL
standard
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5. SQL Data Types Numeric types Date and time types
SQL Primer
SQL Data Types
Numeric types
smallint : signed 2-byte integer
integer, int : signed 4-byte integer
real, float : 4-byte floating-point number
double precision : 8-byte floating-point number
numeric(p, s), decimal(p, s) : an exact numeric type with arbitrary precision p and scale s
Date and time types
date : calendar date (day, month, and year)
time : time of day
timestamp (includes time zone) : both the date and time
interval : an arbitrarily specified length of time
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6. SQL Data Types Large Objects
SQL Primer
SQL Data Types
Large Objects
BLOB (binary large object): variable sized binary object with no size constraint (maximum size is 2 billion bytes)
CLOB (character large object) : string of variable length without a size constraint (maximum size is 1 billion characters)
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7. Using SQL Data Types in the Real World
SQL Primer
Using SQL Data Types in the Real World
Warning: The actual data types and type names differ greatly among the individual RDBMS implementations.
Examples
Data Type
SQL Standard
Oracle
MS Access
DECIMAL
yes no
CURRENCY
NUMBER
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8. Writing SQL Statements
SQL Primer
Writing SQL Statements
Free format
SQL commands not case sensitive – string literals are
Commas separate items in a list
Period separates table name and column name
Comment lines begin with double dash (--)
Single quotes around string literals
Access also allows double quotes
Semicolon marks the end of a statement
String concatenation uses |
sometimes shows up as ¦
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9. SQL Primer
SQL Queries
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10. Retrieving Data from Tables: The SELECT Statement
SQL Primer
Retrieving Data from Tables: The SELECT Statement
SQL uses the SELECT statement (with many options and variations) as the primary statement for data retrieval.
Basic format:
select <columns>
from <tables>
where <conditions>
order by <sort columns>;
Example
select name, phone
from customer; select name, phone from customer where area_code = '843';
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11. SQL Primer
Duplicates
By default, SQL does not eliminate duplicate rows from the result of a SELECT statement.
The user may explicitly request that duplicate rows be eliminated by using the keyword DISTINCT as part of the request.
select distinct state
from customer;
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12. SQL Primer
Conditions
Conditions are specified within the WHERE clause of a SELECT statement.
select *
from orders
where total_invoice > 1000;
Note: “*” selects all columns.
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13. Operators Used in Conditions
SQL Primer
Operators Used in Conditions
Parentheses for grouping
Relational Operators
= <> or != < > <= >=
Logical Operators
AND OR NOT
Test Operators
IN BETWEEN IS NULL IS NOT NULL
Pattern Matching Operators
LIKE (plus a pattern)
_ matches single character (? for Access) % matches multiple characters (* for Access)
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14. Examples: Queries on a Single Table
SQL Primer
Examples: Queries on a Single Table
select order_num, sale_date, ship_date, total_invoice
from orders
where total_invoice > 1000
order by total_invoice desc;
select order_num, cust_num, total_invoice, amount_paid
where amount_paid < total_invoice
and total_invoice between 1000 and 2000;
select *
from customer
where last_name like 'M%'
order by last_name;
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15. SQL Primer
Compound Conditions
The boolean operators AND and OR can be used to create compound conditions. Parentheses can be used for grouping
Example
select order_num, cust_num, ship_date, total_invoice
from orders
where (total_invoice > 1000 and amount_paid < 100)
or amount_paid < 1;
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16. Set Operators on Tables
SQL Primer
Set Operators on Tables
Set union – UNION
Set difference – EXCEPT
Set intersection – INTERSECT
Example:
(select name from customer where state = 'FL')
union
(select name from vendor where state = 'FL');
Note: The output of an SQL query
is another table (closure property).
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17. SQL Primer
Joining Two Tables
The join operation can be specified in terms of SELECT, FROM, and WHERE clauses. Attributes from different tables can be qualified by the table name.
Example
select customer.name, customer.phone,
orders.total_invoice, orders.amount_paid
from customer, orders
where customer.cust_num = orders.cust_num
and orders.amount_paid < orders.total_invoice;
Alternate format using a table alias:
select c.name, c.phone, o.total_invoice, o.amount_paid
from customer c, orders o
where c.cust_num = o.cust_num
and o.amount_paid < o.total_invoice;
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18. Comments on the Join Example
SQL Primer
Comments on the Join Example
The first condition in the where clause specifies the “join” condition.
Table name qualification of attributes can be omitted when there is no ambiguity.
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19. Alternate Syntax for Join
SQL Primer
Alternate Syntax for Join
A join could be specified more simply using the explicit INNER JOIN (keyword INNER can be omitted) or the NATURAL JOIN operator, which was added in SQL/92.
select c.name, c.phone, o.total_invoice, o.amount_paid
from customer c join orders o
on c.cust_num = o.cust_num
where o.amount_paid < o.total_invoice;
from customer c natural join orders o
where o.total_amount_paid < o.total_invoice;
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20. More Complicated Queries
SQL Primer
More Complicated Queries
Complicated, multi-relation queries often involve combinations of tables, columns, and conditions.
select c.name, c.phone
from customer c, orders o, lineitem li
where c.cust_num = o.cust_num
and o.order_num = li.order_num
and li.quantity > 5;
Alternatively, we could express this query using the NATURAL JOIN operator.
from customer c natural join orders o
natural join lineitem li
where li.quantity > 5;
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21. Inner Joins
When querying data from two or more tables using joins, most of the time you will want to use an inner join. All examples thus far have used inner joins.
Example (inner join)
select p.name, b.title
from publisher p join book b
on p.publisher_id = b.publisher_id;
An inner join will include rows from a table only if there are matching rows in the joined table. In the above example, publishers will not be included if there are no books published by them in the book table.
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22. Outer Joins
To include all rows in a table whether or not there are matching rows in the other table, use an outer join.
Example
select p.name, b.title
from publisher p left outer join book b
on p.publisher_id = b.publisher_id;
(Note: The word “outer” can be omitted from this query.)
The above example will select all publishers, even if there are no corresponding books in the book table. Values for b.title will be null for publishers without corresponding books.
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23. Outer Joins (continued)
Outer joins can be “left”, “right”, or “full”, where “full” includes values from both tables.
Some database systems do not support full outer joins directly, but full outer joins can be simulated by using left and right outer joins and unions.
(select p.name, b.title
from publisher p left join book b
on p.publisher_id = b.publisher_id)
union
from publisher p right join book b
on p.publisher_id = b.publisher_id);
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24. Subqueries
A subquery can be used to select data involving two or more tables, but … the selected data can come only from the top-level table.
Example
select name
from customer
where cust_id in
(select cust_id
from orders
where total_invoice > 1000);
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25. Correlated Subqueries
A correlated subquery uses the same table in both levels of the query. The inner query is recomputed for each row in the outer query.
Example
select b1.title
from book b1
where b1.title in
(select b2.title
from book b2
where b1.title = b2.title
and b1.book_id <> b2.book_id);
Finds different books (different IDs) with the same title.
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26. EXISTS and NOT EXISTS
EXISTS and NOT EXISTS are boolean operators that can be used in the “where” clause of correlated subqueries.
General format:
select columns
from tables
where exists (subquery);
An EXISTS condition is true if any row in the subquery meets the specified conditions.
A NOT EXISTS condition is true only if all rows in the subquery do not meet the specified condition/
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27. Example: Using the EXISTS Operator
Find the names of all publishers that publish a book on Java (i.e., has the word “Java” in the title).
select name
from publisher
where exists
(select *
from book
where book.publisher_id = publisher.publisher_id
and book.title like '%Java%');
The above query is equivalent to the following:
where publisher_id in
(select publisher_id
where book.title like '%Java%');
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28. Derived (Computed) Attributes
SQL Primer
Derived (Computed) Attributes
Queries can be used to compute derived attributes.
select order_num, cust_num, sale_date, ship_date,
total_invoice, amount_paid,
total_invoice - amount_paid as balance_due
from orders;
Derived attributes are often computed as part of a view.
create view extended_orders as
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29. SQL Primer
SQL Updates
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30. Update Statements INSERT INTO – inserts rows
SQL Primer
Update Statements
INSERT INTO – inserts rows
DELETE FROM – deletes rows
UPDATE – modifies attribute values
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31. Adding Rows to a Table -- insert a single row, all columns
SQL Primer
Adding Rows to a Table
-- insert a single row, all columns
insert into customer
values (6159, 'George W. Bush',
'1600 Pennsylvania Avenue',
'Washington', 'DC', '20000', ' ')
-- insert a single row, selected columns
-- (uses defaults/nulls)
insert into customer (cust_num, name, phone)
values (8152, 'John Smith', ' ')
-- insert multiple rows with a query
select cust_num, name, phone
from customer_temp;
where state = 'SC';
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32. Deleting Rows from a Table
SQL Primer
Deleting Rows from a Table
General form
delete from table
where condition;
Example
delete from vendor
where vendor_num in (2190, 5001, 5002);
Note: If you omit the “where” clause,
you will delete all rows in the table!
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33. Modifying Data in a Table
SQL Primer
Modifying Data in a Table
General form
update table
set name1 = value1,
name2 = value2,
...
where condition;
Example
-- give everyone in IT a 6% raise
update employee
set salary = salary*1.06
where dept = 'IT';
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34. Modifying Data Using Views
SQL Primer
Modifying Data Using Views
Update statements can also be used to modify data through updateable views.
Conditions for an updateable view
one table
subset of columns and rows
no summarizing or condensing
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35. SQL Primer
SQL Data Definition
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36. Data Definition in SQL CREATE DROP ALTER (restructure) schema – domain
SQL Primer
Data Definition in SQL
CREATE
schema – domain
table – view
index
DROP
ALTER (restructure)
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37. Creating a Table: Example 1
SQL Primer
Creating a Table: Example 1
create table customer (
cust_num integer not null,
last_name varchar(25) not null,
first_name varchar(20),
company_name varchar(40),
_addr varchar(40) not null,
constraint customer_pk primary key (cust_num),
constraint customer_ak unique( _addr) );
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38. Creating a Table: Example 2
SQL Primer
Creating a Table: Example 2
create table orders (
order_num integer not null,
cust_num integer,
sale_date date not null,
ship_date date,
total_invoice decimal(10,2),
amount_paid decimal(10,2),
constraint orders_pk primary key (order_num),
constraint customer_fk foreign key (cust_num)
references customer(cust_num)
on delete cascade );
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39. Creating a Table from a Query
SQL Primer
Creating a Table from a Query
create table sales_personel as
select employee_num, name, phone_num
from employee
where dept = 'SALES';
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40. Creating a View Views are created using queries
SQL Primer
Creating a View
Views are created using queries
create view sales_personel as
select employee_num, name, phone_num
from employee
where dept = 'SALES';
Access does not support views directly, but it allows stored queries which accomplish similar goals.
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41. Creating Indexes and Domains
SQL Primer
Creating Indexes and Domains
Creating an index
create index cust_name_index on customer.last_name;
Note: Database systems usually generate “backing indexes” automatically for primary key, foreign key, and unique constraints.
Creating a domain
create domain ssn_type as char(9);
Note: The ability to create user-defined types (domains) is not available in some database systems.
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42. Dropping Database Objects
SQL Primer
Dropping Database Objects
drop table employee;
drop view sales_personel;
drop index cust_name_index;
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43. Adding Constraints to a Table
SQL Primer
Adding Constraints to a Table
-- adding a primary key
alter table departments
add constraint pk_departments primary key(dept_num);
-- adding a foreign key
alter table employee
add constraint fk_emp_dept foreign key (dept_num)
references departments(dept_num)
on delete set null
on update cascade;
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44. Adding and Dropping Columns
SQL Primer
Adding and Dropping Columns
Adding a column to a table
alter table orders
add payment_method char(10);
Note: Access requires “ADD COLUMN”, but the keyword “COLUMN” can usually be omitted for other database systems.
Dropping a column from a table (not available in all database systems)
drop column payment_method;
To drop a foreign key column, the foreign key constraint must be dropped first.
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45. SQL Primer
The Data Dictionary
Oracle has a Data Dictionary that maintains all information about the structure of the database (metadata)
The Data Dictionary is itself a set of tables.
USER_TABLES – ALL_TABLES
USER_VIEWS – ALL_VIEWS
USER_TAB_COLUMNS – ALL_TAB_COLUMNS
Access does not provide a way to query the data dictionary but provides similar information through a GUI.
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46. Obtaining Metadata (Oracle Only)
SQL Primer
Obtaining Metadata (Oracle Only)
-- find the names of all of your tables
select table_name
from user_tables;
-- find information about columns
select column_name, data_type, data_length
from user_tab_columns
where table_name = 'CUSTOMER';
-- find all constraints (e.g., keys) on the ORDERS table
select *
from user_cons_columns
where table_name = 'ORDERS';
Note: Similar capabilities exist in other database systems.
Example (Derby): select tablename from sys.systables;
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47. Additional SQL Statements and Operators
SQL Primer
Additional SQL Statements and Operators
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48. Row Functions and Operators
SQL Primer
Row Functions and Operators
Row functions and operators can be used to calculate new values as part of a query
select cust_num, name, phone
from customer
where credit_limit > 20000;
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49. Sample Row Functions and Operators
SQL Primer
Sample Row Functions and Operators
Numeric
* / SQRT (SQR) ABS FLOOR (INT)
Text
|| (&) SUBSTR (MID) UPPER (UCASE)
LENGTH (LEN) INITCAP (STRCONV(x, 3))
Date
+ number - (DATEDIFF) MONTHS_BETWEEN (DATEDIFF)
Note: Values in parentheses are those for Access.
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50. Example Using Row Functions
SQL Primer
Example Using Row Functions
-- find all employees who have been with the
-- company at least one year
select name, hire_date
from employee
where trunc(months_between(hire_date, sysdate), 0) > 12;
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51. Column Functions Column functions can be used to summarize data
SQL Primer
Column Functions
Column functions can be used to summarize data
Sample column functions
MIN MAX COUNT SUM AVG
Examples
select count(*)
from orders;
select name
from customer c, orders o
where c.cust_num = o.cust_num
and o.total_invoice in
(select max(o.total_invoice)
from orders);
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52. Counting Distinct Values
By default, the count function does not eliminate duplicate values. In order to count the number of distinct values, combine the distinct keyword with the count function.
Example
select count(distinct state) as num_states
from customer;
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53. SQL Primer
The GROUP BY Clause
A GROUP BY clause can be used to group query results
select state, count(state)
from customer
group by state
order by state;
A GROUP BY clause can use more than one column.
When using the GROUP BY clause, only the column or columns in the GROUP BY expression and the built-in functions can be used in the expressions in the SELECT clause.
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54. Using Summary Operators with a GROUP BY Clause
SQL Primer
Using Summary Operators with a GROUP BY Clause
Summary operators (AVG, MAX, SUM, etc.) can be applied to queries about groups of rows. The GROUP BY clause specifies the grouping attributes.
select c.cust_num, c.name, avg(o.amount_paid)
from customer c, orders o
where c.cust_num = o.cust_num
group by c.cust_num, c.name;
As before we could simplify this query using the NATURAL JOIN operator.
from customer c natural join orders o
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55. SQL Primer
The HAVING Clause
When a query result contains data that is grouped and summarized, a HAVING clause can eliminate some of the groups.
Example query without a HAVING clause (shows order count for all customers)
select name, phone_num, count(order_num)
from customer, orders
where customer.cust_num=orders.cust_num
group by name, phone_num
order by name;
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56. The HAVING Clause (continued)
SQL Primer
The HAVING Clause (continued)
Example query with a HAVING clause (shows order count for all customers with at least 3 orders)
select name, phone_num, count(order_num)
from customer, orders
where customer.cust_num=orders.cust_num
group by name, phone_num
having count(order_num) >= 3
order by customer.name;
Note: A “where” clause can’t be used with aggregate functions.
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