Oracle SQL Tutorial User Manual

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Oracle/SQL Tutorial

Michael Gertz

Database and Information Systems Group

Department of Computer Science

University of California, Davis [email protected]

http://www.db.cs.ucdavis.edu

This Oracle/SQL tutorial provides a detailed introduction to the SQL query language and the

Oracle Relational Database Management System. Further information about Oracle and SQL can be found on the web site www.db.cs.ucdavis.edu/dbs.

Comments, corrections, or additions to these notes are welcome. Many thanks to Christina

Chung for comments on the previous version.

Recommended Literature

The complete Oracle Documentation is available online at technet.oracle.com. Free subscription!

Oracle Press has several good books on various Oracle topics. See www.osborne.com/oracle/

O’Reilly has about 30 excellent Oracle books, including Steven Feuerstein’s Oracle PL/SQL

Programming (3rd edition). See oracle.oreilly.com.

Jim Melton and Alan R. Simon: SQL: 1999 - Understanding Relational Language Components

(1st Edition, May 2001), Morgan Kaufmann.

Jim Celko has a couple of very good books that cover advanced SQL queries and programming.

Check any of your favorite (online)bookstore.

If you want to know more about constraints and triggers, you might want to check the fol-

Commercial (Object-)Relational Database Management Systems. The VLDB Journal, Volume

10, Number 4, 241-269.

1. SQL – Structured Query Language

1.1. Tables

1.2. Queries (Part I)

1.3. Data Definition in SQL

1.4. Data Modifications in SQL

1.5. Queries (Part II)

1.6. Views

2. SQL*Plus (Minimal User Guide, Editor Commands, Help System)

3. Oracle Data Dictionary

4. Application Programming

4.1. PL/SQL

4.1.1 Introduction

4.1.2 Structure of PL/SQL Blocks

4.1.3 Declarations

4.1.4 Language Elements

4.1.5 Exception Handling

4.1.6 Procedures and Functions

4.1.7 Packages

4.1.8 Programming in PL/SQL

4.2. Embedded SQL and Pro*C

5. Integrity Constraints and Triggers

5.1. Integrity Constraints

5.1.1 Check Constraints

5.1.2 Foreign Key Constraints

5.1.3 More About Column- and Table Constraints

5.2. Triggers

5.2.1 Overview

5.2.2 Structure of Triggers

5.2.3 Example Triggers

5.2.4 Programming Triggers

6. System Architecture

6.1. Storage Management and Processes

6.2. Logical Database Structures

6.3. Physical Database Structures

6.4. Steps in Processing an SQL Statement

6.5. Creating Database Objects

1 SQL – Structured Query Language

1.1 Tables

In relational database systems (DBS) data are represented using tables (relations). A query issued against the DBS also results in a table. A table has the following structure:

Column 1 Column 2 . . .

Column n

←− Tuple (or Record)

. . .

A table is uniquely identified by its name and consists of rows that contain the stored information, each row containing exactly one tuple (or record ). A table can have one or more columns.

A column is made up of a column name and a data type, and it describes an attribute of the tuples. The structure of a table, also called relation schema, thus is defined by its attributes.

The type of information to be stored in a table is defined by the data types of the attributes at table creation time.

SQL uses the terms table, row, and column for relation, tuple, and attribute, respectively. In this tutorial we will use the terms interchangeably.

A table can have up to 254 columns which may have different or same data types and sets of values (domains), respectively. Possible domains are alphanumeric data (strings), numbers and date formats. Oracle offers the following basic data types:

• char(n): Fixed-length character data (string), n characters long. The maximum size for n is 255 bytes (2000 in Oracle8). Note that a string of type char is always padded on right with blanks to full length of n. (☞ can be memory consuming).

Example: char(40)

• varchar2(n): Variable-length character string. The maximum size for n is 2000 (4000 in

Oracle8). Only the bytes used for a string require storage. Example: varchar2(80)

• number(o, d): Numeric data type for integers and reals. o = overall number of digits, d

= number of digits to the right of the decimal point.

Maximum values: o =38, d= −84 to +127. Examples: number(8), number(5,2)

Note that, e.g., number(5,2) cannot contain anything larger than 999.99 without resulting in an error. Data types derived from number are int[eger], dec[imal], smallint and real.

• date: Date data type for storing date and time.

The default format for a date is: DD-MMM-YY. Examples: ’13-OCT-94’, ’07-JAN-98’

• long: Character data up to a length of 2GB. Only one long column is allowed per table.

Note: In Oracle-SQL there is no data type boolean. It can, however, be simulated by using either char(1) or number(1).

As long as no constraint restricts the possible values of an attribute, it may have the special value null (for unknown). This value is different from the number 0, and it is also different from the empty string ’’.

Further properties of tables are:

• the order in which tuples appear in a table is not relevant (unless a query requires an explicit sorting).

• a table has no duplicate tuples (depending on the query, however, duplicate tuples can appear in the query result).

A database schema is a set of relation schemas. The extension of a database schema at database run-time is called a database instance or database, for short.

1.1.1

Example Database

In the following discussions and examples we use an example database to manage information about employees, departments and salary scales. The corresponding tables can be created under the UNIX shell using the command demobld. The tables can be dropped by issuing the command demodrop under the UNIX shell.

The table EMP is used to store information about employees:

EMPNO ENAME JOB

7369 SMITH CLERK

MGR HIREDATE SAL DEPTNO

7902 17-DEC-80 800 20

7499 ALLEN SALESMAN 7698 20-FEB-81 1600 30

7521 WARD SALESMAN 7698 22-FEB-81 1250 30

...........................................................

7698 BLAKE MANAGER 01-MAY-81 3850 30

7902 FORD ANALYST 7566 03-DEC-81 3000 10

For the attributes, the following data types are defined:

EMPNO:number(4), ENAME:varchar2(30), JOB:char(10), MGR:number(4),

HIREDATE:date, SAL:number(7,2), DEPTNO:number(2)

Each row (tuple) from the table is interpreted as follows: an employee has a number, a name, a job title and a salary. Furthermore, for each employee the number of his/her manager, the date he/she was hired, and the number of the department where he/she is working are stored.

The table DEPT stores information about departments (number, name, and location):

DEPTNO DNAME

STORE

LOC

CHICAGO

RESEARCH DALLAS

SALES NEW YORK

MARKETING BOSTON

Finally, the table SALGRADE contains all information about the salary scales, more precisely, the maximum and minimum salary of each scale.

GRADE LOSAL HISAL

700

1201

1200

1400

1401

2001

3001

2000

3000

9999

1.2 Queries (Part I)

In order to retrieve the information stored in the database, the SQL query language is used. In the following we restrict our attention to simple SQL queries and defer the discussion of more complex queries to Section 1.5

In SQL a query has the following (simplified) form (components in brackets [ ] are optional): select [distinct] <column(s)> from <table>

[ where <condition> ]

[ order by <column(s) [asc|desc]> ]

1.2.1

Selecting Columns

The columns to be selected from a table are specified after the keyword select. This operation is also called projection. For example, the query select LOC, DEPTNO from DEPT; lists only the number and the location for each tuple from the relation DEPT. If all columns should be selected, the asterisk symbol “∗” can be used to denote all attributes. The query select ∗ from EMP; retrieves all tuples with all columns from the table EMP. Instead of an attribute name, the select clause may also contain arithmetic expressions involving arithmetic operators etc.

select ENAME, DEPTNO, SAL ∗ 1.55 from EMP;

For the different data types supported in Oracle, several operators and functions are provided:

• for numbers: abs, cos, sin, exp, log, power, mod, sqrt, +, −, ∗, /, . . .

• for strings: chr, concat(string1, string2), lower, upper, replace(string, search string, replacement string), translate, substr(string, m, n), length, to date, . . .

• for the date data type: add month, month between, next day, to char, . . .

The usage of these operations is described in detail in the SQL*Plus help system (see also

Section 2).

Consider the query select DEPTNO from EMP; which retrieves the department number for each tuple. Typically, some numbers will appear more than only once in the query result, that is, duplicate result tuples are not automatically eliminated.

Inserting the keyword distinct after the keyword select, however, forces the elimination of duplicates from the query result.

It is also possible to specify a sorting order in which the result tuples of a query are displayed.

For this the order by clause is used and which has one or more attributes listed in the select clause as parameter. desc specifies a descending order and asc specifies an ascending order

(this is also the default order). For example, the query select ENAME, DEPTNO, HIREDATE from EMP; from EMP order by DEPTNO [asc], HIREDATE desc; displays the result in an ascending order by the attribute DEPTNO. If two tuples have the same attribute value for DEPTNO, the sorting criteria is a descending order by the attribute values of

HIREDATE. For the above query, we would get the following output:

ENAME DEPTNO HIREDATE

FORD 10 03-DEC-81

SMITH 20

BLAKE 30

WARD 30

17-DEC-80

01-MAY-81

22-FEB-81

ALLEN 30 20-FEB-81

...........................

1.2.2

Selection of Tuples

Up to now we have only focused on selecting (some) attributes of all tuples from a table. If one is interested in tuples that satisfy certain conditions, the where clause is used. In a where clause simple conditions based on comparison operators can be combined using the logical connectives and, or, and not to form complex conditions. Conditions may also include pattern matching operations and even subqueries (Section 1.5).

Example: List the job title and the salary of those employees whose manager has the number 7698 or 7566 and who earn more than 1500: select JOB, SAL from EMP where (MGR = 7698 or MGR = 7566) and SAL > 1500;

For all data types, the comparison operators =, != or <>, <, >, <=, => are allowed in the conditions of a where clause.

Further comparison operators are:

• Set Conditions: <column> [not] in (<list of values>)

Example: select ∗ from DEPT where DEPTNO in (20,30);

• Null value: <column> is [not] null, i.e., for a tuple to be selected there must (not) exist a defined value for this column.

Example: select ∗ from EMP where MGR is not null;

Note: the operations = null and ! = null are not defined!

• Domain conditions: <column> [not] between <lower bound> and <upper bound>

Example: • select EMPNO, ENAME, SAL from EMP where SAL between 1500 and 2500;

• select ENAME from EMP where HIREDATE between ’02-APR-81’ and ’08-SEP-81’;

1.2.3

String Operations

In order to compare an attribute with a string, it is required to surround the string by apostrophes, e.g., where LOCATION = ’DALLAS’. A powerful operator for pattern matching is the like operator. Together with this operator, two special characters are used: the percent sign

% (also called wild card), and the underline , also called position marker. For example, if one is interested in all tuples of the table DEPT that contain two C in the name of the department, the condition would be where DNAME like ’%C%C%’. The percent sign means that any

(sub)string is allowed there, even the empty string. In contrast, the underline stands for exactly one character. Thus the condition where DNAME like ’%C C%’ would require that exactly one character appears between the two Cs. To test for inequality, the not clause is used.

Further string operations are:

• upper(<string>) takes a string and converts any letters in it to uppercase, e.g., DNAME

= upper(DNAME) (The name of a department must consist only of upper case letters.)

• lower(<string>) converts any letter to lowercase,

• initcap(<string>) converts the initial letter of every word in <string> to uppercase.

• length(<string>) returns the length of the string.

• substr(<string>, n [, m]) clips out a m character piece of <string>, starting at position n. If m is not specified, the end of the string is assumed.

substr(’DATABASE SYSTEMS’, 10, 7) returns the string ’SYSTEMS’.

1.2.4

Aggregate Functions

Aggregate functions are statistical functions such as count, min, max etc. They are used to compute a single value from a set of attribute values of a column: count Counting Rows

Example: How many tuples are stored in the relation EMP?

select count(∗) from EMP;

Example: How many different job titles are stored in the relation EMP?

select count(distinct JOB) from EMP; max Maximum value for a column min Minimum value for a column

Example: List the minimum and maximum salary.

select min(SAL), max(SAL) from EMP;

Example: Compute the difference between the minimum and maximum salary.

select max(SAL) - min(SAL) from EMP; sum Computes the sum of values (only applicable to the data type number)

Example: Sum of all salaries of employees working in the department 30.

select sum(SAL) from EMP where DEPTNO = 30; avg Computes average value for a column (only applicable to the data type number)

Note: avg, min and max ignore tuples that have a null value for the specified attribute, but count considers null values.

1.3 Data Definition in SQL

1.3.1

Creating Tables

The SQL command for creating an empty table has the following form: create table <table> (

<column 1> <data type> [not null] [unique] [<column constraint>],

. . . . . . . . .

<column n> <data type> [not null] [unique] [<column constraint>],

[<table constraint(s)>]

);

For each column, a name and a data type must be specified and the column name must be unique within the table definition. Column definitions are separated by comma. There is no difference between names in lower case letters and names in upper case letters. In fact, the only place where upper and lower case letters matter are strings comparisons. A not null

constraint is directly specified after the data type of the column and the constraint requires defined attribute values for that column, different from null.

The keyword unique specifies that no two tuples can have the same attribute value for this column. Unless the condition not null is also specified for this column, the attribute value null is allowed and two tuples having the attribute value null for this column do not violate the constraint.

Example: The create table statement for our EMP table has the form create table EMP (

EMPNO

ENAME

DEPTNO

); number(4) not null, varchar2(30) not null,

JOB

SAL varchar2(10),

MGR number(4),

HIREDATE date, number(7,2), number(2)

Remark: Except for the columns EMPNO and ENAME null values are allowed.

1.3.2

Constraints

The definition of a table may include the specification of integrity constraints. Basically two types of constraints are provided: column constraints are associated with a single column whereas table constraints are typically associated with more than one column. However, any column constraint can also be formulated as a table constraint. In this section we consider only very simple constraints. More complex constraints will be discussed in Section 5.1.

The specification of a (simple) constraint has the following form:

[constraint <name>] primary key | unique | not null

A constraint can be named. It is advisable to name a constraint in order to get more meaningful information when this constraint is violated due to, e.g., an insertion of a tuple that violates the constraint. If no name is specified for the constraint, Oracle automatically generates a name of the pattern SYS C<number>.

The two most simple types of constraints have already been discussed: not null and unique.

Probably the most important type of integrity constraints in a database are primary key constraints. A primary key constraint enables a unique identification of each tuple in a table.

Based on a primary key, the database system ensures that no duplicates appear in a table. For example, for our EMP table, the specification create table EMP (

EMPNO number(4) constraint pk emp primary key,

. . . );

defines the attribute EMPNO as the primary key for the table. Each value for the attribute EMPNO thus must appear only once in the table EMP. A table, of course, may only have one primary key. Note that in contrast to a unique constraint, null values are not allowed.

Example:

We want to create a table called PROJECT to store information about projects. For each project, we want to store the number and the name of the project, the employee number of the project’s manager, the budget and the number of persons working on the project, and the start date and end date of the project. Furthermore, we have the following conditions:

- a project is identified by its project number,

- the name of a project must be unique,

- the manager and the budget must be defined.

Table definition: create table PROJECT (

PNO number(3) constraint prj pk primary key,

PNAME varchar2(60) unique,

PMGR number(4) not null,

PERSONS number(5),

BUDGET number(8,2) not null,

PSTART date,

PEND date);

A unique constraint can include more than one attribute. In this case the pattern unique(<column i>, . . . , <column j>) is used. If it is required, for example, that no two projects have the same start and end date, we have to add the table constraint constraint no same dates unique(PEND, PSTART)

This constraint has to be defined in the create table command after both columns PEND and

PSTART have been defined. A primary key constraint that includes more than only one column can be specified in an analogous way.

Instead of a not null constraint it is sometimes useful to specify a default value for an attribute if no value is given, e.g., when a tuple is inserted. For this, we use the default clause.

Example:

If no start date is given when inserting a tuple into the table PROJECT, the project start date should be set to January 1st, 1995:

PSTART date default(’01-JAN-95’)

Note: Unlike integrity constraints, it is not possible to specify a name for a default.

1.3.3

Checklist for Creating Tables

The following provides a small checklist for the issues that need to be considered before creating a table.

• What are the attributes of the tuples to be stored? What are the data types of the attributes? Should varchar2 be used instead of char ?

• Which columns build the primary key?

• Which columns do (not) allow null values? Which columns do (not) allow duplicates ?

• Are there default values for certain columns that allow null values ?

1.4 Data Modifications in SQL

After a table has been created using the create table command, tuples can be inserted into the table, or tuples can be deleted or modified.

1.4.1

Insertions

The most simple way to insert a tuple into a table is to use the insert statement insert into <table> [(<column i, . . . , column j>)] values (<value i, . . . , value j>);

For each of the listed columns, a corresponding (matching) value must be specified. Thus an insertion does not necessarily have to follow the order of the attributes as specified in the create table statement. If a column is omitted, the value null is inserted instead. If no column list is given, however, for each column as defined in the create table statement a value must be given.

Examples: insert into PROJECT(PNO, PNAME, PERSONS, BUDGET, PSTART) values(313, ’DBS’, 4, 150000.42, ’10-OCT-94’); or insert into PROJECT values(313, ’DBS’, 7411, null, 150000.42, ’10-OCT-94’, null);

If there are already some data in other tables, these data can be used for insertions into a new table. For this, we write a query whose result is a set of tuples to be inserted. Such an insert statement has the form insert into <table> [(<column i, . . . , column j>)] <query>

Example: Suppose we have defined the following table:

create table OLDEMP (

ENO number(4) not null,

HDATE date);

We now can use the table EMP to insert tuples into this new relation: insert into OLDEMP (ENO, HDATE) select EMPNO, HIREDATE from EMP where HIREDATE < ’31-DEC-60’;

1.4.2

Updates

For modifying attribute values of (some) tuples in a table, we use the update statement: update <table> set

[where <condition>];

An expression consists of either a constant (new value), an arithmetic or string operation, or an SQL query. Note that the new value to assign to <column i> must a the matching data type.

An update statement without a where clause results in changing respective attributes of all tuples in the specified table. Typically, however, only a (small) portion of the table requires an update.

Examples:

• The employee JONES is transfered to the department 20 as a manager and his salary is increased by 1000: update EMP set

JOB = ’MANAGER’, DEPTNO = 20, SAL = SAL +1000 where ENAME = ’JONES’;

• All employees working in the departments 10 and 30 get a 15% salary increase.

update EMP set

SAL = SAL ∗ 1.15 where DEPTNO in (10,30);

Analogous to the insert statement, other tables can be used to retrieve data that are used as new values. In such a case we have a <query> instead of an <expression>.

Example: All salesmen working in the department 20 get the same salary as the manager who has the lowest salary among all managers.

update EMP set

SAL = (select min(SAL) from EMP where JOB = ’MANAGER’) where JOB = ’SALESMAN’ and DEPTNO = 20;

Explanation: The query retrieves the minimum salary of all managers. This value then is assigned to all salesmen working in department 20.

It is also possible to specify a query that retrieves more than only one value (but still only one tuple!). In this case the set clause has the form set(<column i, . . . , column j>) = <query>.

It is important that the order of data types and values of the selected row exactly correspond to the list of columns in the set clause.

1.4.3

Deletions

All or selected tuples can be deleted from a table using the delete command: delete from <table> [where <condition>];

If the where clause is omitted, all tuples are deleted from the table. An alternative command for deleting all tuples from a table is the truncate table <table> command. However, in this case, the deletions cannot be undone (see subsequent Section 1.4.4).

Example:

Delete all projects (tuples) that have been finished before the actual date (system date): delete from PROJECT where PEND < sysdate; sysdate is a function in SQL that returns the system date. Another important SQL function is user, which returns the name of the user logged into the current Oracle session.

1.4.4

Commit and Rollback

A sequence of database modifications, i.e., a sequence of insert, update, and delete statements, is called a transaction. Modifications of tuples are temporarily stored in the database system. They become permanent only after the statement commit; has been issued.

As long as the user has not issued the commit statement, it is possible to undo all modifications since the last commit. To undo modifications, one has to issue the statement rollback;.

It is advisable to complete each modification of the database with a commit (as long as the modification has the expected effect). Note that any data definition command such as create table results in an internal commit. A commit is also implicitly executed when the user terminates an Oracle session.

1.5 Queries (Part II)

In Section 1.2 we have only focused on queries that refer to exactly one table. Furthermore, conditions in a where were restricted to simple comparisons. A major feature of relational databases, however, is to combine (join) tuples stored in different tables in order to display more meaningful and complete information. In SQL the select statement is used for this kind of queries joining relations:

select [distinct] [<alias a k

>.]<column i>, . . . , [<alias a l

>.]<column j> from <table 1> [<alias a

>], . . . , <table n> [<alias a n

[where <condition>]

The specification of table aliases in the from clause is necessary to refer to columns that have the same name in different tables. For example, the column DEPTNO occurs in both EMP and

DEPT. If we want to refer to either of these columns in the where or select clause, a table alias has to be specified and put in the front of the column name. Instead of a table alias also the complete relation name can be put in front of the column such as DEPT.DEPTNO, but this sometimes can lead to rather lengthy query formulations.

1.5.1

Joining Relations

Comparisons in the where clause are used to combine rows from the tables listed in the from clause.

Example: In the table EMP only the numbers of the departments are stored, not their name. For each salesman, we now want to retrieve the name as well as the number and the name of the department where he is working: select ENAME, E.DEPTNO, DNAME from EMP E, DEPT D where E.DEPTNO = D.DEPTNO

and JOB = ’SALESMAN’;

Explanation: E and D are table aliases for EMP and DEPT, respectively. The computation of the query result occurs in the following manner (without optimization):

1. Each row from the table EMP is combined with each row from the table DEPT (this operation is called Cartesian product ). If EMP contains m rows and DEPT contains n rows, we thus get n ∗ m rows.

2. From these rows those that have the same department number are selected (where

E.DEPTNO = D.DEPTNO).

3. From this result finally all rows are selected for which the condition JOB = ’SALESMAN’ holds.

In this example the joining condition for the two tables is based on the equality operator “=”.

The columns compared by this operator are called join columns and the join operation is called an equijoin.

Any number of tables can be combined in a select statement.

Example: For each project, retrieve its name, the name of its manager, and the name of the department where the manager is working: select ENAME, DNAME, PNAME from EMP E, DEPT D, PROJECT P where E.EMPNO = P.MGR

and D.DEPTNO = E.DEPTNO;

It is even possible to join a table with itself:

Example: List the names of all employees together with the name of their manager: select E1.ENAME, E2.ENAME

from EMP E1, EMP E2 where E1.MGR = E2.EMPNO;

Explanation: The join columns are MGR for the table E1 and EMPNO for the table E2.

The equijoin comparison is E1.MGR = E2.EMPNO.

1.5.2

Subqueries

Up to now we have only concentrated on simple comparison conditions in a where clause, i.e., we have compared a column with a constant or we have compared two columns. As we have already seen for the insert statement, queries can be used for assignments to columns. A query result can also be used in a condition of a where clause. In such a case the query is called a subquery and the complete select statement is called a nested query.

A respective condition in the where clause then can have one of the following forms:

1. Set-valued subqueries

<expression> [not] in (<subquery>)

<expression> <comparison operator> [any|all] (<subquery>)

An <expression> can either be a column or a computed value.

2. Test for (non)existence

[not] exists (<subquery>)

In a where clause conditions using subqueries can be combined arbitrarily by using the logical connectives and and or.

Example: List the name and salary of employees of the department 20 who are leading a project that started before December 31, 1990: select ENAME, SAL from EMP where EMPNO in

(select PMGR from PROJECT where PSTART < ’31-DEC-90’) and DEPTNO =20;

Explanation: The subquery retrieves the set of those employees who manage a project that started before December 31, 1990. If the employee working in department 20 is contained in this set (in operator), this tuple belongs to the query result set.

Example: List all employees who are working in a department located in BOSTON:

select ∗ from EMP where DEPTNO in

(select DEPTNO from DEPT where LOC = ’BOSTON’);

The subquery retrieves only one value (the number of the department located in Boston). Thus it is possible to use “=” instead of in. As long as the result of a subquery is not known in advance, i.e., whether it is a single value or a set, it is advisable to use the in operator.

A subquery may use again a subquery in its where clause. Thus conditions can be nested arbitrarily. An important class of subqueries are those that refer to its surrounding (sub)query and the tables listed in the from clause, respectively. Such type of queries is called correlated subqueries.

Example: List all those employees who are working in the same department as their manager

(note that components in [ ] are optional: select ∗ from EMP E1 where DEPTNO in

(select DEPTNO from EMP [E] where [E.]EMPNO = E1.MGR);

Explanation: The subquery in this example is related to its surrounding query since it refers to the column E1.MGR. A tuple is selected from the table EMP (E1) for the query result if the value for the column DEPTNO occurs in the set of values select in the subquery. One can think of the evaluation of this query as follows: For each tuple in the table E1, the subquery is evaluated individually. If the condition where DEPTNO in . . . evaluates to true, this tuple is selected.

Note that an alias for the table EMP in the subquery is not necessary since columns without a preceding alias listed there always refer to the innermost query and tables.

Conditions of the form <expression> <comparison operator> [any|all] <subquery> are used to compare a given <expression> with each value selected by <subquery>.

• For the clause any, the condition evaluates to true if there exists at least on row selected by the subquery for which the comparison holds. If the subquery yields an empty result set, the condition is not satisfied.

• For the clause all, in contrast, the condition evaluates to true if for all rows selected by the subquery the comparison holds. In this case the condition evaluates to true if the subquery does not yield any row or value.

Example: Retrieve all employees who are working in department 10 and who earn at least as much as any (i.e., at least one) employee working in department 30: select ∗ from EMP where SAL >= any

(select SAL from EMP where DEPTNO = 30) and DEPTNO = 10;

Note: Also in this subquery no aliases are necessary since the columns refer to the innermost from clause.

Example: List all employees who are not working in department 30 and who earn more than all employees working in department 30: select ∗ from EMP where SAL > all

(select SAL from EMP where DEPTNO = 30) and DEPTNO <> 30;

For all and any, the following equivalences hold: in

⇔

= any not in

⇔

<> all or != all

Often a query result depends on whether certain rows do (not) exist in (other) tables. Such type of queries is formulated using the exists operator.

Example: List all departments that have no employees: select ∗ from DEPT where not exists

(select ∗ from EMP where DEPTNO = DEPT.DEPTNO);

Explanation: For each tuple from the table DEPT, the condition is checked whether there exists a tuple in the table EMP that has the same department number (DEPT.DEPTNO). In case no such tuple exists, the condition is satisfied for the tuple under consideration and it is selected. If there exists a corresponding tuple in the table EMP, the tuple is not selected.

1.5.3

Operations on Result Sets

Sometimes it is useful to combine query results from two or more queries into a single result.

SQL supports three set operators which have the pattern:

The set operators are:

• union [all] returns a table consisting of all rows either appearing in the result of <query

1> or in the result of <query 2>. Duplicates are automatically eliminated unless the clause all is used.

• intersect returns all rows that appear in both results <query 1> and <query 2>.

• minus returns those rows that appear in the result of <query 1> but not in the result of

<query 2>.

Example: Assume that we have a table EMP2 that has the same structure and columns as the table EMP:

• All employee numbers and names from both tables: select EMPNO, ENAME from EMP union select EMPNO, ENAME from EMP2;

• Employees who are listed in both EMP and EMP2: select ∗ from EMP intersect select ∗ from EMP2;

• Employees who are only listed in EMP: select ∗ from EMP minus select ∗ from EMP2;

Each operator requires that both tables have the same data types for the columns to which the operator is applied.

1.5.4

Grouping

In Section 1.2.4 we have seen how aggregate functions can be used to compute a single value for a column. Often applications require grouping rows that have certain properties and then applying an aggregate function on one column for each group separately. For this, SQL provides the clause group by <group column(s)>. This clause appears after the where clause and must refer to columns of tables listed in the from clause.

select <column(s)> from <table(s)> where <condition> group by <group column(s)>

[having <group condition(s)>];

Those rows retrieved by the selected clause that have the same value(s) for <group column(s)> are grouped. Aggregations specified in the select clause are then applied to each group separately. It is important that only those columns that appear in the <group column(s)> clause can be listed without an aggregate function in the select clause !

Example: For each department, we want to retrieve the minimum and maximum salary.

select DEPTNO, min(SAL), max(SAL) from EMP group by DEPTNO;

Rows from the table EMP are grouped such that all rows in a group have the same department number. The aggregate functions are then applied to each such group. We thus get the following query result:

DEPTNO MIN(SAL) MAX(SAL)

10 1300 5000

800

950

3000

2850

Rows to form a group can be restricted in the where clause. For example, if we add the condition where JOB = ’CLERK’, only respective rows build a group. The query then would retrieve the minimum and maximum salary of all clerks for each department. Note that is not allowed to specify any other column than DEPTNO without an aggregate function in the select clause since this is the only column listed in the group by clause (is it also easy to see that other columns would not make any sense).

Once groups have been formed, certain groups can be eliminated based on their properties, e.g., if a group contains less than three rows. This type of condition is specified using the having clause. As for the select clause also in a having clause only <group column(s)> and aggregations can be used.

Example: Retrieve the minimum and maximum salary of clerks for each department having more than three clerks.

select DEPTNO, min(SAL), max(SAL) from EMP where JOB = ’CLERK’ group by DEPTNO having count(∗) > 3;

Note that it is even possible to specify a subquery in a having clause. In the above query, for example, instead of the constant 3, a subquery can be specified.

A query containing a group by clause is processed in the following way:

1. Select all rows that satisfy the condition specified in the where clause.

2. From these rows form groups according to the group by clause.

3. Discard all groups that do not satisfy the condition in the having clause.

4. Apply aggregate functions to each group.

5. Retrieve values for the columns and aggregations listed in the select clause.

1.5.5

Some Comments on Tables

Accessing tables of other users

Provided that a user has the privilege to access tables of other users (see also Section 3), she/he can refer to these tables in her/his queries. Let <user> be a user in the Oracle system and

<table> a table of this user. This table can be accessed by other (privileged) users using the command select ∗ from <user>.<table>;

In case that one often refers to tables of other users, it is useful to use a synonym instead of

<user>.<table>. In Oracle-SQL a synonym can be created using the command create synonym <name> for <user>.<table> ;

It is then possible to use simply <name> in a from clause. Synonyms can also be created for one’s own tables.

Adding Comments to Definitions

For applications that include numerous tables, it is useful to add comments on table definitions or to add comments on columns. A comment on a table can be created using the command comment on table <table> is ’<text>’;

A comment on a column can be created using the command comment on column <table>.<column> is ’<text>’;

Comments on tables and columns are stored in the data dictionary. They can be accessed using the data dictionary views USER TAB COMMENTS and USER COL COMMENTS (see also Section 3).

Modifying Table- and Column Definitions

It is possible to modify the structure of a table (the relation schema) even if rows have already been inserted into this table. A column can be added using the alter table command alter table <table> add(<column> <data type> [default <value>] [<column constraint>]);

If more than only one column should be added at one time, respective add clauses need to be separated by colons. A table constraint can be added to a table using alter table <table> add (<table constraint>);

Note that a column constraint is a table constraint, too. not null and primary key constraints can only be added to a table if none of the specified columns contains a null value. Table definitions can be modified in an analogous way. This is useful, e.g., when the size of strings that can be stored needs to be increased. The syntax of the command for modifying a column is alter table <table> modify(<column> [<data type>] [default <value>] [<column constraint>]);

Note: In earlier versions of Oracle it is not possible to delete single columns from a table definition. A workaround is to create a temporary table and to copy respective columns and rows into this new table. Furthermore, it is not possible to rename tables or columns. In the most recent version (9i), using the alter table command, it is possible to rename a table, columns, and constraints. In this version, there also exists a drop column clause as part of the alter table statement.

Deleting a Table

A table and its rows can be deleted by issuing the command drop table <table> [cascade constraints];.

1.6 Views

In Oracle the SQL command to create a view (virtual table) has the form create [or replace] view <view-name> [(<column(s)>)] as

<select-statement> [with check option [constraint <name>]];

The optional clause or replace re-creates the view if it already exists. <column(s)> names the columns of the view. If <column(s)> is not specified in the view definition, the columns of the view get the same names as the attributes listed in the select statement (if possible).

Example: The following view contains the name, job title and the annual salary of employees working in the department 20: create view DEPT20 as select ENAME, JOB, SAL∗12 ANNUAL SALARY from EMP where DEPTNO = 20;

In the select statement the column alias ANNUAL SALARY is specified for the expression SAL∗12 and this alias is taken by the view. An alternative formulation of the above view definition is create view DEPT20 (ENAME, JOB, ANNUAL SALARY) as select ENAME, JOB, SAL ∗ 12 from EMP where DEPTNO = 20;

A view can be used in the same way as a table, that is, rows can be retrieved from a view

(also respective rows are not physically stored, but derived on basis of the select statement in the view definition), or rows can even be modified. A view is evaluated again each time it is accessed. In Oracle SQL no insert, update, or delete modifications on views are allowed that use one of the following constructs in the view definition:

• Joins

• Aggregate function such as sum, min, max etc.

• set-valued subqueries (in, any, all) or test for existence (exists)

• group by clause or distinct clause

In combination with the clause with check option any update or insertion of a row into the view is rejected if the new/modified row does not meet the view definition, i.e., these rows would not be selected based on the select statement. A with check option can be named using the constraint clause.

A view can be deleted using the command delete <view-name>.

2 SQL*Plus

Introduction

SQL*Plus is the interactive (low-level) user interface to the Oracle database management system. Typically, SQL*Plus is used to issue ad-hoc queries and to view the query result on the screen. Some of the features of SQL*Plus are:

• A built-in command line editor can be used to edit (incorrect) SQL queries. Instead of this line editor any editor installed on the computer can be invoked.

• There are numerous commands to format the output of a query.

• SQL*Plus provides an online-help.

• Query results can be stored in files which then can be printed.

Queries that are frequently issued can be saved to a file and invoked later. Queries can be parameterized such that it is possible to invoke a saved query with a parameter.

A Minimal User Guide

Before you start SQL*Plus make sure that the following UNIX shell variables are properly set

(shell variables can be checked using the env command, e.g., env | grep ORACLE):

• ORACLE HOME, e.g., ORACLE HOME=/usr/pkg/oracle/734

• ORACLE SID, e.g, ORACLE SID=prod

In order to invoke SQL*Plus from a UNIX shell, the command sqlplus has to be issued.

SQL*Plus then displays some information about the product, and prompts you for your user name and password for the Oracle system.

gertz(catbert)54: sqlplus

SQL*Plus: Release 3.3.4.0.1 - Production on Sun Dec 20 19:16:52 1998

Enter user-name: scott

Enter password:

Connected to:

Oracle7 Server Release 7.3.4.0.1 - Production Release

With the distributed option

PL/SQL Release 2.3.4.0.0 - Production

SQL>

SQL> is the prompt you get when you are connected to the Oracle database system. In

SQL*Plus you can divide a statement into separate lines, each continuing line is indicated by a prompt such 2>, 3> etc. An SQL statement must always be terminated by a semicolon (;).

In addition to the SQL statements discussed in the previous section, SQL*Plus provides some special SQL*Plus commands. These commands need not be terminated by a semicolon. Upper and lower case letters are only important for string comparisons. An SQL query can always be interrupted by using <Control>C. To exit SQL*Plus you can either type exit or quit.

Editor Commands

The most recently issued SQL statement is stored in the SQL buffer, independent of whether the statement has a correct syntax or not. You can edit the buffer using the following commands:

• l[ist] lists all lines in the SQL buffer and sets the current line (marked with an ”∗”) to the last line in the buffer.

• l<number> sets the actual line to <number>

• c[hange]/<old string>/<new string> replaces the first occurrence of <old string> by

<new string> (for the actual line)

• a[ppend]<string> appends <string> to the current line

• del deletes the current line

• r[un] executes the current buffer contents

• get<file> reads the data from the file <file> into the buffer

• save<file> writes the current buffer into the file <file>

• edit invokes an editor and loads the current buffer into the editor. After exiting the editor the modified SQL statement is stored in the buffer and can be executed (command r).

The editor can be defined in the SQL*Plus shell by typing the command define editor =

<name>, where <name> can be any editor such as emacs, vi, joe, or jove.

SQL*Plus Help System and Other Useful Commands

• To get the online help in SQL*Plus just type help <command>, or just help to get information about how to use the help command. In Oracle Version 7 one can get the complete list of possible commands by typing help command.

• To change the password, in Oracle Version 7 the command alter user <user> identified by <new password>; is used. In Oracle Version 8 the command passw <user> prompts the user for the old/new password.

• The command desc[ribe] <table> lists all columns of the given table together with their data types and information about whether null values are allowed or not.

• You can invoke a UNIX command from the SQL*Plus shell by using host <UNIX command>.

For example, host ls -la *.sql lists all SQL files in the current directory.

• You can log your SQL*Plus session and thus queries and query results by using the command spool <file>. All information displayed on screen is then stored in <file> which automatically gets the extension .lst. The command spool off turns spooling off.

• The command copy can be used to copy a complete table. For example, the command copy from scott/tiger create EMPL using select ∗ from EMP; copies the table EMP of the user scott with password tiger into the relation EMPL. The relation EMP is automatically created and its structure is derived based on the attributes listed in the select clause.

• SQL commands saved in a file <name>.sql can be loaded into SQL*Plus and executed using the command @<name>.

• Comments are introduced by the clause rem[ark] (only allowed between SQL statements), or - - (allowed within SQL statements).

Formatting the Output

SQL*Plus provides numerous commands to format query results and to build simple reports.

For this, format variables are set and these settings are only valid during the SQL*Plus session.

They get lost after terminating SQL*Plus. It is, however, possible to save settings in a file named login.sql in your home directory. Each time you invoke SQL*Plus this file is automatically loaded.

The command column <column name> <option 1> <option 2> . . . is used to format columns of your query result. The most frequently used options are:

• format A<n> For alphanumeric data, this option sets the length of <column name> to

<n>. For columns having the data type number, the format command can be used to specify the format before and after the decimal point. For example, format 99,999.99

specifies that if a value has more than three digits in front of the decimal point, digits are separated by a colon, and only two digits are displayed after the decimal point.

• The option heading <text> relabels <column name> and gives it a new heading.

• null <text> is used to specify the output of null values (typically, null values are not displayed).

• column <column name> clear deletes the format definitions for <column name>.

The command set linesize <number> can be used to set the maximum length of a single line that can be displayed on screen. set pagesize <number> sets the total number of lines

SQL*Plus displays before printing the column names and headings, respectively, of the selected rows.

Several other formatting features can be enabled by setting SQL*Plus variables. The command show all displays all variables and their current values. To set a variable, type set <variable>

<value>. For example, set timing on causes SQL*Plus to display timing statistics for each

SQL command that is executed. set pause on [<text>] makes SQL*Plus wait for you to press

Return after the number of lines defined by set pagesize has been displayed. <text> is the message SQL*Plus will display at the bottom of the screen as it waits for you to hit Return.

3 Oracle Data Dictionary

The Oracle data dictionary is one of the most important components of the Oracle DBMS.

It contains all information about the structures and objects of the database such as tables, columns, users, data files etc. The data stored in the data dictionary are also often called metadata. Although it is usually the domain of database administrators (DBAs), the data dictionary is a valuable source of information for end users and developers. The data dictionary consists of two levels: the internal level contains all base tables that are used by the various

DBMS software components and they are normally not accessible by end users. The external level provides numerous views on these base tables to access information about objects and structures at different levels of detail.

3.1 Data Dictionary Tables

An installation of an Oracle database always includes the creation of three standard Oracle users:

• SYS: This is the owner of all data dictionary tables and views. This user has the highest privileges to manage objects and structures of an Oracle database such as creating new users.

• SYSTEM: is the owner of tables used by different tools such SQL*Forms, SQL*Reports etc.

This user has less privileges than SYS.

• PUBLIC: This is a “dummy” user in an Oracle database. All privileges assigned to this user are automatically assigned to all users known in the database.

The tables and views provided by the data dictionary contain information about

• users and their privileges,

• tables, table columns and their data types, integrity constraints, indexes,

• statistics about tables and indexes used by the optimizer,

• privileges granted on database objects,

• storage structures of the database.

The SQL command select ∗ from DICT[IONARY]; lists all tables and views of the data dictionary that are accessible to the user. The selected information includes the name and a short description of each table and view. Before issuing this query, check the column definitions of DICT[IONARY] using desc DICT[IONARY] and set the appropriate values for column using the format command.

The query select ∗ from TAB; retrieves the names of all tables owned by the user who issues this command. The query select ∗ from COL;

returns all information about the columns of one’s own tables.

Each SQL query requires various internal accesses to the tables and views of the data dictionary.

Since the data dictionary itself consists of tables, Oracle has to generate numerous SQL statements to check whether the SQL command issued by a user is correct and can be executed.

Example: The SQL query select ∗ from EMP where SAL > 2000; requires a verification whether (1) the table EMP exists, (2) the user has the privilege to access this table, (3) the column SAL is defined for this table etc.

3.2 Data Dictionary Views

The external level of the data dictionary provides users a front end to access information relevant to the users. This level provides numerous views (in Oracle7 approximately 540) that represent (a portion of the) data from the base tables in a readable and understandable manner. These views can be used in SQL queries just like normal tables.

The views provided by the data dictionary are divided into three groups: USER, ALL, and DBA.

The group name builds the prefix for each view name. For some views, there are associated synonyms as given in brackets below.

• USER : Tuples in the USER views contain information about objects owned by the account performing the SQL query (current user)

USER TABLES all tables with their name, number of columns, storage information, statistical information etc. (TABS)

USER CATALOG tables, views, and synonyms (CAT)

USER COL COMMENTS comments on columns

USER CONSTRAINTS constraint definitions for tables

USER INDEXES

USER OBJECTS

USER TAB COLUMNS all information about indexes created for tables (IND) all database objects owned by the user (OBJ) columns of the tables and views owned by the user

(COLS)

USER TAB COMMENTS comments on tables and views

USER TRIGGERS triggers defined by the user

USER USERS

USER VIEWS information about the current user views defined by the user

• ALL : Rows in the ALL views include rows of the USER views and all information about objects that are accessible to the current user. The structure of these views is analogous to the structure of the USER views.

ALL CATALOG owner, name and type of all accessible tables, views, and synonyms

ALL TABLES owner and name of all accessible tables

ALL OBJECTS owner, type, and name of accessible database objects

ALL TRIGGERS . . .

ALL USERS

ALL VIEWS

. . .

• DBA : The DBA views encompass information about all database objects, regardless of the owner. Only users with DBA privileges can access these views.

DBA TABLES

DBA CATALOG

DBA OBJECTS tables of all users in the database tables, views, and synonyms defined in the database object of all users

DBA DATA FILES information about data files

DBA USERS information about all users known in the database

4 Application Programming

4.1 PL/SQL

4.1.1

Introduction

The development of database applications typically requires language constructs similar to those that can be found in programming languages such as C, C++, or Pascal. These constructs are necessary in order to implement complex data structures and algorithms. A major restriction of the database language SQL, however, is that many tasks cannot be accomplished by using only the provided language elements.

PL/SQL (Procedural Language/SQL) is a procedural extension of Oracle-SQL that offers language constructs similar to those in imperative programming languages. PL/SQL allows users and designers to develop complex database applications that require the usage of control structures and procedural elements such as procedures, functions, and modules.

The basic construct in PL/SQL is a block. Blocks allow designers to combine logically related

(SQL-) statements into units. In a block, constants and variables can be declared, and variables can be used to store query results. Statements in a PL/SQL block include SQL statements, control structures (loops), condition statements (if-then-else), exception handling, and calls of other PL/SQL blocks.

PL/SQL blocks that specify procedures and functions can be grouped into packages. A package is similar to a module and has an interface and an implementation part. Oracle offers several predefined packages, for example, input/output routines, file handling, job scheduling etc. (see directory $ORACLE HOME/rdbms/admin).

Another important feature of PL/SQL is that it offers a mechanism to process query results in a tuple-oriented way, that is, one tuple at a time. For this, cursors are used. A cursor basically is a pointer to a query result and is used to read attribute values of selected tuples into variables. A cursor typically is used in combination with a loop construct such that each tuple read by the cursor can be processed individually.

In summary, the major goals of PL/SQL are to

• increase the expressiveness of SQL,

• process query results in a tuple-oriented way,

• optimize combined SQL statements,

• develop modular database application programs,

• reuse program code, and

• reduce the cost for maintaining and changing applications.

4.1.2

Structure of PL/SQL-Blocks

PL/SQL is a block-structured language.

Each block builds a (named) program unit, and blocks can be nested. Blocks that build a procedure, a function, or a package must be named.

A PL/SQL block has an optional declare section, a part containing PL/SQL statements, and an optional exception-handling part. Thus the structure of a PL/SQL looks as follows (brackets

[ ] enclose optional parts):

[<Block header>]

[declare

<User defined exceptions>] begin

[exception

<Exception handling>] end;

The block header specifies whether the PL/SQL block is a procedure, a function, or a package.

If no header is specified, the block is said to be an anonymous PL/SQL block. Each PL/SQL block again builds a PL/SQL statement. Thus blocks can be nested like blocks in conventional programming languages. The scope of declared variables (i.e., the part of the program in which one can refer to the variable) is analogous to the scope of variables in programming languages such as C or Pascal.

4.1.3

Declarations

Constants, variables, cursors, and exceptions used in a PL/SQL block must be declared in the declare section of that block. Variables and constants can be declared as follows:

<variable name> [constant] <data type> [not null] [:= <expression>];

Valid data types are SQL data types (see Section 1.1) and the data type boolean. Boolean data may only be true, false, or null. The not null clause requires that the declared variable must always have a value different from null. <expression> is used to initialize a variable.

If no expression is specified, the value null is assigned to the variable. The clause constant states that once a value has been assigned to the variable, the value cannot be changed (thus the variable becomes a constant). Example: declare hire date job title emp found salary incr

. . .

begin . . . end; date; /* implicit initialization with null */ varchar2(80) := ’Salesman’; boolean; /* implicit initialization with null */ constant number(3,2) := 1.5; /* constant */

Instead of specifying a data type, one can also refer to the data type of a table column (so-called anchored declaration). For example, EMP.Empno%TYPE refers to the data type of the column

Empno in the relation EMP. Instead of a single variable, a record can be declared that can store a complete tuple from a given table (or query result). For example, the data type DEPT%ROWTYPE specifies a record suitable to store all attribute values of a complete row from the table DEPT.

Such records are typically used in combination with a cursor. A field in a record can be accessed using <record name>.<column name>, for example, DEPT.Deptno.

A cursor declaration specifies a set of tuples (as a query result) such that the tuples can be processed in a tuple-oriented way (i.e., one tuple at a time) using the fetch statement. A cursor declaration has the form cursor <cursor name> [(<list of parameters>)] is <select statement>;

The cursor name is an undeclared identifier, not the name of any PL/SQL variable. A parameter has the form <parameter name> <parameter type>. Possible parameter types are char, varchar2, number, date and boolean as well as corresponding subtypes such as integer.

Parameters are used to assign values to the variables that are given in the select statement.

Example: We want to retrieve the following attribute values from the table EMP in a tupleoriented way: the job title and name of those employees who have been hired after a given date, and who have a manager working in a given department.

cursor employee cur (start date date, dno number) is select JOB, ENAME from EMP E where HIREDATE > start date and exists (select ∗ from EMP where E.MGR = EMPNO and DEPTNO = dno);

If (some) tuples selected by the cursor will be modified in the PL/SQL block, the clause for update[(<column(s)>)] has to be added at the end of the cursor declaration. In this case selected tuples are locked and cannot be accessed by other users until a commit has been issued.

Before a declared cursor can be used in PL/SQL statements, the cursor must be opened, and after processing the selected tuples the cursor must be closed. We discuss the usage of cursors in more detail below.

Exceptions are used to process errors and warnings that occur during the execution of PL/SQL statements in a controlled manner. Some exceptions are internally defined, such as ZERO DIVIDE.

Other exceptions can be specified by the user at the end of a PL/SQL block. User defined exceptions need to be declared using <name of exception> exception. We will discuss exception handling in more detail in Section 4.1.5

4.1.4

Language Elements

In addition to the declaration of variables, constants, and cursors, PL/SQL offers various language constructs such as variable assignments, control structures (loops, if-then-else), procedure and function calls, etc. However, PL/SQL does not allow commands of the SQL data definition language such as the create table statement. For this, PL/SQL provides special packages.

Furthermore, PL/SQL uses a modified select statement that requires each selected tuple to be assigned to a record (or a list of variables).

There are several alternatives in PL/SQL to a assign a value to a variable. The most simple way to assign a value to a variable is declare counter integer := 0;

. . .

begin counter := counter + 1;

Values to assign to a variable can also be retrieved from the database using a select statement select <column(s)> into <matching list of variables> from <table(s)> where <condition>;

It is important to ensure that the select statement retrieves at most one tuple ! Otherwise it is not possible to assign the attribute values to the specified list of variables and a runtime error occurs. If the select statement retrieves more than one tuple, a cursor must be used instead. Furthermore, the data types of the specified variables must match those of the retrieved attribute values. For most data types, PL/SQL performs an automatic type conversion (e.g., from integer to real).

Instead of a list of single variables, a record can be given after the keyword into. Also in this case, the select statement must retrieve at most one tuple !

declare employee rec EMP%ROWTYPE; max sal EMP.SAL%TYPE; begin select EMPNO, ENAME, JOB, MGR, SAL, COMM, HIREDATE, DEPTNO into employee rec from EMP where EMPNO = 5698; end; select max(SAL) into max sal from EMP;

. . .

PL/SQL provides while-loops, two types of for-loops, and continuous loops. Latter ones are used in combination with cursors. All types of loops are used to execute a sequence of statements multiple times. The specification of loops occurs in the same way as known from imperative programming languages such as C or Pascal.

A while-loop has the pattern

[<< <label name> >>] while <condition> loop

<sequence of statements>; end loop [<label name>] ;

A loop can be named. Naming a loop is useful whenever loops are nested and inner loops are completed unconditionally using the exit <label name>; statement.

Whereas the number of iterations through a while loop is unknown until the loop completes, the number of iterations through the for loop can be specified using two integers.

[<< <label name> >>] for <index> in [reverse] <lower bound>..<upper bound> loop

<sequence of statements> end loop [<label name>] ;

The loop counter <index> is declared implicitly. The scope of the loop counter is only the for loop. It overrides the scope of any variable having the same name outside the loop. Inside the for loop, <index> can be referenced like a constant. <index> may appear in expressions, but one cannot assign a value to <index>. Using the keyword reverse causes the iteration to proceed downwards from the higher bound to the lower bound.

Processing Cursors: Before a cursor can be used, it must be opened using the open statement open <cursor name> [(<list of parameters>)] ;

The associated select statement then is processed and the cursor references the first selected tuple. Selected tuples then can be processed one tuple at a time using the fetch command fetch <cursor name> into <list of variables>;

The fetch command assigns the selected attribute values of the current tuple to the list of variables. After the fetch command, the cursor advances to the next tuple in the result set.

Note that the variables in the list must have the same data types as the selected values. After all tuples have been processed, the close command is used to disable the cursor.

close <cursor name>;

The example below illustrates how a cursor is used together with a continuous loop: declare cursor emp cur is select ∗ from EMP; emp rec EMP%ROWTYPE; emp sal EMP.SAL%TYPE; begin open emp cur; loop fetch emp cur into emp rec; exit when emp cur%NOTFOUND; emp sal := emp rec.sal;

<sequence of statements> end loop; close emp cur;

. . .

end;

Each loop can be completed unconditionally using the exit clause: exit [<block label>] [when <condition>]

Using exit without a block label causes the completion of the loop that contains the exit statement. A condition can be a simple comparison of values. In most cases, however, the condition refers to a cursor. In the example above, %NOTFOUND is a predicate that evaluates to false if the most recent fetch command has read a tuple. The value of <cursor name>%NOTFOUND is null before the first tuple is fetched. The predicate evaluates to true if the most recent fetch failed to return a tuple, and false otherwise. %FOUND is the logical opposite of %NOTFOUND.

Cursor for loops can be used to simplify the usage of a cursor:

[<< <label name> >>] for <record name> in <cursor name>[(<list of parameters>)] loop

<sequence of statements> end loop [<label name>];

A record suitable to store a tuple fetched by the cursor is implicitly declared. Furthermore, this loop implicitly performs a fetch at each iteration as well as an open before the loop is entered and a close after the loop is left. If at an iteration no tuple has been fetched, the loop is automatically terminated without an exit.

It is even possible to specify a query instead of <cursor name> in a for loop: for <record name> in (<select statement>) loop

<sequence of statements> end loop;

That is, a cursor needs not be specified before the loop is entered, but is defined in the select statement.

Example: for sal rec in (select SAL + COMM total from EMP) loop

. . . ; end loop; total is an alias for the expression computed in the select statement. Thus, at each iteration only one tuple is fetched. The record sal rec, which is implicitly defined, then contains only one entry which can be accessed using sal rec.total. Aliases, of course, are not necessary if only attributes are selected, that is, if the select statement contains no arithmetic operators or aggregate functions.

For conditional control, PL/SQL offers if-then-else constructs of the pattern if <condition> then <sequence of statements>

[elsif ] <condition> then <sequence of statements>

. . .

[else] <sequence of statements> end if ;

Starting with the first condition, if a condition yields true, its corresponding sequence of statements is executed, otherwise control is passed to the next condition. Thus the behavior of this type of PL/SQL statement is analogous to if-then-else statements in imperative programming languages.

Except data definition language commands such as create table, all types of SQL statements can be used in PL/SQL blocks, in particular delete, insert, update, and commit. Note that in PL/SQL only select statements of the type select <column(s)> into are allowed, i.e., selected attribute values can only be assigned to variables (unless the select statement is used in a subquery). The usage of select statements as in SQL leads to a syntax error. If update or delete statements are used in combination with a cursor, these commands can be restricted to currently fetched tuple. In these cases the clause where current of <cursor name> is added as shown in the following example.

Example: The following PL/SQL block performs the following modifications: All employees having ’KING’ as their manager get a 5% salary increase.

declare manager EMP.MGR%TYPE; cursor emp cur (mgr no number) is select SAL from EMP where MGR = mgr no for update of SAL; begin select EMPNO into manager from EMP where ENAME = ’KING’; for emp rec in emp cur(manager) loop update EMP set SAL = emp rec.sal ∗ 1.05

where current of emp cur; end loop; commit; end;

Remark: Note that the record emp rec is implicitly defined. We will discuss another version of this block using parameters in Section 4.1.6.

4.1.5

Exception Handling

A PL/SQL block may contain statements that specify exception handling routines. Each error or warning during the execution of a PL/SQL block raises an exception. One can distinguish between two types of exceptions:

• system defined exceptions

• user defined exceptions (which must be declared by the user in the declaration part of a block where the exception is used/implemented)

System defined exceptions are always automatically raised whenever corresponding errors or warnings occur. User defined exceptions, in contrast, must be raised explicitly in a sequence of statements using raise <exception name>. After the keyword exception at the end of a block, user defined exception handling routines are implemented. An implementation has the pattern when <exception name> then <sequence of statements>;

The most common errors that can occur during the execution of PL/SQL programs are handled by system defined exceptions. The table below lists some of these exceptions with their names and a short description.

Exception name Number Remark

CURSOR ALREADY OPEN ORA-06511 You have tried to open a cursor which is

INVALID CURSOR already open

ORA-01001 Invalid cursor operation such as fetching from a closed cursor

NO DATA FOUND

TOO MANY ROWS

ZERO DIVIDE

ORA-01403 A select . . . into or fetch statement returned no tuple

ORA-01422 A select . . . into statement returned more than one tuple

ORA-01476 You have tried to divide a number by 0

Example: declare emp sal EMP.SAL%TYPE; emp no EMP.EMPNO%TYPE; too high sal exception; begin select EMPNO, SAL into emp no, emp sal from EMP where ENAME = ’KING’; if emp sal ∗ 1.05 > 4000 then raise too high sal else update EMP set SQL . . .

end if ; exception when NO DATA FOUND – – no tuple selected then rollback; when too high sal then insert into high sal emps values(emp no); commit; end;

After the keyword when a list of exception names connected with or can be specified. The last when clause in the exception part may contain the exception name others. This introduces the default exception handling routine, for example, a rollback.

If a PL/SQL program is executed from the SQL*Plus shell, exception handling routines may contain statements that display error or warning messages on the screen. For this, the procedure raise application error can be used. This procedure has two parameters <error number> and <message text>. <error number> is a negative integer defined by the user and must range between -20000 and -20999. <error message> is a string with a length up to 2048 characters.

The concatenation operator “||” can be used to concatenate single strings to one string. In order to display numeric variables, these variables must be converted to strings using the function to char. If the procedure raise application error is called from a PL/SQL block, processing the PL/SQL block terminates and all database modifications are undone, that is, an implicit rollback is performed in addition to displaying the error message.

Example: if emp sal ∗ 1.05 > 4000 then raise application error(-20010, ’Salary increase for employee with Id ’

|| to char(Emp no) || ’ is too high’);

4.1.6

Procedures and Functions

PL/SQL provides sophisticated language constructs to program procedures and functions as stand-alone PL/SQL blocks. They can be called from other PL/SQL blocks, other procedures and functions. The syntax for a procedure definition is create [or replace] procedure <procedure name> [(<list of parameters>)] is

<declarations> begin

[exception

<exception handling routines>] end [<procedure name>];

A function can be specified in an analogous way create [or replace] function <function name> [(<list of parameters>)] return <data type> is

. . .

The optional clause or replace re-creates the procedure/function. A procedure can be deleted using the command drop procedure <procedure name> (drop function <function name>).

In contrast to anonymous PL/SQL blocks, the clause declare may not be used in procedure/function definitions.

Valid parameters include all data types. However, for char, varchar2, and number no length and scale, respectively, can be specified. For example, the parameter number(6) results in a compile error and must be replaced by number. Instead of explicit data types, implicit types of the form %TYPE and %ROWTYPE can be used even if constrained declarations are referenced.

A parameter is specified as follows:

<parameter name> [IN | OUT | IN OUT] <data type> [{ := | DEFAULT} <expression>]

The optional clauses IN, OUT, and IN OUT specify the way in which the parameter is used.

The default mode for a parameter is IN. IN means that the parameter can be referenced inside the procedure body, but it cannot be changed. OUT means that a value can be assigned to the parameter in the body, but the parameter’s value cannot be referenced. IN OUT allows both assigning values to the parameter and referencing the parameter. Typically, it is sufficient to use the default mode for parameters.

Example: The subsequent procedure is used to increase the salary of all employees who work in the department given by the procedure’s parameter. The percentage of the salary increase is given by a parameter, too.

create procedure raise salary(dno number, percentage number DEFAULT 0.5) is cursor emp cur (dept no number) is select SAL from EMP where DEPTNO = dept no for update of SAL; empsal number(8); begin open emp cur(dno); - - Here dno is assigned to dept no loop fetch emp cur into empsal; exit when emp cur%NOTFOUND; update EMP set SAL = empsal ∗ ((100 + percentage)/100) where current of emp cur; end loop; close emp cur; commit; end raise salary;

This procedure can be called from the SQL*Plus shell using the command execute raise salary(10, 3);

If the procedure is called only with the parameter 10, the default value 0.5 is assumed as specified in the list of parameters in the procedure definition. If a procedure is called from a

PL/SQL block, the keyword execute is omitted.

Functions have the same structure as procedures. The only difference is that a function returns a value whose data type (unconstrained) must be specified.

Example: create function get dept salary(dno number) return number is all sal number; begin all sal := 0; for emp sal in (select SAL from EMP where DEPTNO = dno and SAL is not null) loop

all sal := all sal + emp sal.sal; end loop; return all sal; end get dept salary;

In order to call a function from the SQL*Plus shell, it is necessary to first define a variable to which the return value can be assigned. In SQL*Plus a variable can be defined using the command variable <variable name> <data type>;, for example, variable salary number. The above function then can be called using the command execute :salary := get dept salary(20); Note that the colon “:” must be put in front of the variable.

Further information about procedures and functions can be obtained using the help command in the SQL*Plus shell, for example, help [create] function, help subprograms, help stored subprograms.

4.1.7

Packages

It is essential for a good programming style that logically related blocks, procedures, and functions are combined into modules, and each module provides an interface which allows users and designers to utilize the implemented functionality. PL/SQL supports the concept of modularization by which modules and other constructs can be organized into packages. A package consists of a package specification and a package body. The package specification defines the interface that is visible for application programmers, and the package body implements the package specification (similar to header- and source files in the programming language C).

Below a package is given that is used to combine all functions and procedures to manage information about employees.

create package manage_employee as -- package specification function hire_emp (name varchar2, job varchar2, mgr number, hiredate date, sal number, comm number default 0, deptno number) return number; procedure fire_emp (emp_id number); procedure raise_sal (emp_id number, sal_incr number); end manage_employee; create package body manage_employee as function hire_emp (name varchar2, job varchar2, mgr number, hiredate date, sal number, comm number default 0, deptno number) return number is

-- Insert a new employee with a new employee Id new_empno number(10); begin select emp_sequence.nextval into new_empno from dual;

insert into emp values(new_empno, name, job, mgr, hiredate, sal, comm, deptno); return new_empno; end hire_emp; procedure fire_emp(emp_id number) is

-- deletes an employee from the table EMP begin delete from emp where empno = emp_id; if SQL%NOTFOUND then -- delete statement referred to invalid emp_id raise_application_error(-20011, ’Employee with Id ’ || to_char(emp_id) || ’ does not exist.’); end if; end fire_emp; procedure raise_sal(emp_id number, sal_incr number) is

-- modify the salary of a given employee begin update emp set sal = sal + sal_incr where empno = emp_id; if SQL%NOTFOUND then raise_application_error(-20012, ’Employee with Id ’ || to_char(emp_id) || ’ does not exist’); end if; end raise_sal; end manage_employee;

Remark: In order to compile and execute the above package, it is necessary to create first the required sequence (help sequence): create sequence emp sequence start with 8000 increment by 10;

A procedure or function implemented in a package can be called from other procedures and functions using the statement <package name>.<procedure name>[(<list of parameters>)].

Calling such a procedure from the SQL*Plus shell requires a leading execute.

Oracle offers several predefined packages and procedures that can be used by database users and application developers. A set of very useful procedures is implemented in the package

DBMS OUTPUT. This package allows users to display information to their SQL*Plus session’s screen as a PL/SQL program is executed. It is also a very useful means to debug PL/SQL programs that have been successfully compiled, but do not behave as expected. Below some of the most important procedures of this package are listed:

Procedure name

DBMS OUTPUT.ENABLE

DBMS OUTPUT.DISABLE

DBMS OUTPUT.PUT(<string>)

Remark enables output disables output appends (displays) <string> to output buffer

DBMS OUTPUT.PUT LINE(<string>) appends <string> to output buffer and appends a new-line marker

DBMS OUTPUT.NEW LINE displays a new-line marker

Before strings can be displayed on the screen, the output has to be enabled either using the procedure DBMS OUTPUT.ENABLE or using the SQL*Plus command set serveroutput on (before the procedure that produces the output is called).

Further packages provided by Oracle are UTL FILE for reading and writing files from PL/SQL programs, DBMS JOB for job scheduling, and DBMS SQL to generate SQL statements dynamically, that is, during program execution.

The package DBMS SQL is typically used to create and delete tables from within PL/SQL programs. More packages can be found in the directory

$ORACLE HOME/rdbms/admin.

4.1.8

Programming in PL/SQL

Typically one uses an editor such as emacs or vi to write a PL/SQL program. Once a program has been stored in a file <name> with the extension .sql, it can be loaded into SQL*Plus using the command @<name>. It is important that the last line of the file contains a slash

“/”.

If the procedure, function, or package has been successfully compiled, SQL*Plus displays the message PL/SQL procedure successfully completed. If the program contains errors, these are displayed in the format ORA-n <message text>, where n is a number and <message text> is a short description of the error, for example, ORA-1001 INVALID CURSOR. The SQL*Plus command show errors [<function|procedure|package|package body|trigger> <name>] displays all compilation errors of the most recently created or altered function (or procedure, or package etc.) in more detail. If this command does not show any errors, try select ∗ from USER ERRORS.

Under the UNIX shell one can also use the command oerr ORA n to get information of the following form: error description

Cause: Reason for the error

Action: Suggested action

4.2 Embedded SQL and Pro*C

The query language constructs of SQL described in the previous sections are suited for formulating ad-hoc queries, data manipulation statements and simple PL/SQL blocks in simple, interactive tools such as SQL*Plus. Many data management tasks, however, occur in sophisticated engineering applications and these tasks are too complex to be handled by such an interactive tool. Typically, data are generated and manipulated in computationally complex application programs that are written in a Third-Generation-Language (3GL), and which, therefore, need an interface to the database system. Furthermore, a majority of existing data-intensive engineering applications are written previously using an imperative programming language and now want to make use of the functionality of a database system, thus requiring an easy to use programming interface to the database system. Such an interface is provided in the form of

Embedded SQL, an embedding of SQL into various programming languages, such as C, C++,

Cobol, Fortran etc. Embedded SQL provides application programmers a suitable means to combine the computing power of a programming language with the database manipulation and management capabilities of the declarative query language SQL.

Since all these interfaces exhibit comparable functionalities, in the following we describe the embedding of SQL in the programming language C. For this, we base our discussion on the

Oracle interface to C, called Pro*C. The emphasis in this section is placed on the description of the interface, not on introducing the programming language C.

4.2.1

General Concepts

Programs written in Pro*C and which include SQL and/or PL/SQL statements are precompiled into regular C programs using a precompiler that typically comes with the database management software (precompiler package). In order to make SQL and PL/SQL statements in a Proc*C program (having the suffix .pc) recognizable by the precompiler, they are always preceded by the keywords EXEC SQL and end with a semicolon “;”. The Pro*C precompiler replaces such statements with appropriate calls to functions implemented in the SQL runtime library. The resulting C program then can be compiled and linked using a normal C compiler like any other C program. The linker includes the appropriate Oracle specific libraries. Figure 1 summarizes the steps from the source code containing SQL statements to an executable program.

4.2.2

Host and Communication Variables

As it is the case for PL/SQL blocks, also the first part of a Pro*C program has a declare section.

In a Pro*C program, in a declare section so-called host variables are specified. Host variables are the key to the communication between the host program and the database. Declarations of host variables can be placed wherever normal C variable declarations can be placed. Host variables are declared according to the C syntax. Host variables can be of the following data types:

Editor

Host

Program

Program Development

Program including SQL and PL/SQL commands

(<program>.pc)

Precompiler Translates SQL and PL/SQL commands into function calls

Source

Program

‘pure’ C−Program including libraries (.h)

(<program>.c)

C−Compiler cc, gcc or g++

Object−

Program

Linker executable

Program

Oracle Run−Time Library C Standard−Libraries

Figure 1: Translation of a Pro*C Program char <Name> char <Name>[n] int single character array of n characters integer float floating point

VARCHAR<Name>[n] variable length strings

VARCHAR

2 is converted by the Pro*C precompiler into a structure with an n-byte character array and a 2-bytes length field. The declaration of host variables occurs in a declare section having the following pattern:

EXEC SQL BEGIN DECLARE SECTION

/* e.g., VARCHAR userid[20]; */

/* e.g., char test ok; */

EXEC SQL END DECLARE SECTION

In a Pro*C program at most one such a declare section is allowed. The declaration of cursors and exceptions occurs outside of such a declare section for host variables. In a Pro*C program host variables referenced in SQL and PL/SQL statements must be prefixed with a colon “:”.

Note that it is not possible to use C function calls and most of the pointer expressions as host variable references.

Note: all uppercase letters; varchar2 is not allowed!

4.2.3

The Communication Area

In addition to host language variables that are needed to pass data between the database and

C program (and vice versa), one needs to provide some status variables containing program runtime information. The variables are used to pass status information concerning the database access to the application program so that certain events can be handled in the program properly.

The structure containing the status variables is called SQL Communication Area or SQLCA, for short, and has to be included after the declare section using the statement

EXEC SQL INCLUDE SQLCA.H

In the variables defined in this structure, information about error messages as well as program status information is maintained: struct sqlca

{

/* ub1 */ char

/* b4

/* ub1 */ char

/* b4 */ long

/* ub1 */ char

};

*/ long

*/ long sqlcaid[8]; sqlabc; sqlcode; struct

{

/* ub2 */ unsigned short sqlerrml;

/* ub1 */ char

} sqlerrm; sqlerrmc[70]; sqlerrp[8]; sqlerrd[6]; sqlwarn[8]; sqlext[8];

The fields in this structure have the following meaning: sqlcaid

Used to identify the SQLCA, set to “SQLCA” sqlabc

Holds the length of the SQLCA structure sqlcode

Holds the status code of the most recently executed SQL (PL/SQL) statement fetch or select into returns no rows.

be rolled back explicitly.

sqlerrm

Structure with two components sqlerrml: length of the message text in sqlerrmc, and sqlerrmc: error message text (up to 70 characters) corresponding to the error code recorded in sqlcode sqlerrp

Not used

sqlerrd

Array of binary integers, has 6 elements: sqlerrd[0],sqlerrd[1],sqlerrd[3],sqlerrd[6] not used; sqlerrd[2] = number of rows processed by the most recent SQL statement; sqlerrd[4] = offset specifying position of most recent parse error of SQL statement.

sqlwarn

Array with eight elements used as warning (not error!) flags. Flag is set by assigning it the character ‘W’.

sqlwarn[0]: only set if other flag is set sqlwarn[1]: if truncated column value was assigned to a host variable sqlwarn[2]: null column is not used in computing an aggregate function sqlwarn[3]: number of columns in select is not equal to number of host variables specified in into sqlwarn[4]: if every tuple was processed by an update or delete statement without a where clause sqlwarn[5]: procedure/function body compilation failed because of a PL/SQL error sqlwarn[6] and sqlwarn[7]: not used sqlext not used

Components of this structure can be accessed and verified during runtime, and appropriate handling routines (e.g., exception handling) can be executed to ensure a correct behavior of the application program. If at the end of the program the variable sqlcode contains a 0, then the execution of the program has been successful, otherwise an error occurred.

4.2.4

Exception Handling

There are two ways to check the status of your program after executable SQL statements which may result in an error or warning: (1) either by explicitly checking respective components of the SQLCA structure, or (2) by doing automatic error checking and handling using the

WHENEVER statement. The complete syntax of this statement is

EXEC SQL WHENEVER <condition> <action>;

By using this command, the program then automatically checks the SQLCA for <condition> and executes the given <action>. <condition> can be one of the following:

• SQLERROR: sqlcode has a negative value, that is, an error occurred

• SQLWARNING: In this case sqlwarn[0] is set due to a warning

• NOT FOUND: sqlcode has a positive value, meaning that no row was found that satisfies the where condition, or a select into or fetch statement returned no rows

<action> can be

• STOP: the program exits with an exit() call, and all SQL statements that have not been committed so far are rolled back

• CONTINUE: if possible, the program tries to continue with the statement following the error resulting statement

• DO <function>: the program transfers processing to an error handling function named

• GOTO <label>: program execution branches to a labeled statement (see example)

4.2.5

Connecting to the Database

At the beginning of Pro*C program, more precisely, the execution of embedded SQL or PL/SQL statements, one has to connect to the database using a valid Oracle account and password.

Connecting to the database occurs trough the embedded SQL statement

EXEC SQL CONNECT :<Account> IDENTIFIED BY :<Password>.

Both <Account> and <Password> are host variables of the type VARCHAR and must be specified and handled respectively (see also the sample Pro*C program in Section 4.2.7).

<Account> and <Password> can be specified in the Pro*C program, but can also be entered at program runtime using, e.g., the C function scanf.

4.2.6

Commit and Rollback

Before a program is terminated by the c exit function and if no error occurred, database modifications through embedded insert, update, and delete statements must be committed.

This is done by using the embedded SQL statement

EXEC SQL COMMIT WORK RELEASE;

If a program error occurred and previous non-committed database modifications need to be undone, the embedded SQL statement

EXEC SQL ROLLBACK WORK RELEASE; has to be specified in the respective error handling routine of the Pro*C program.

4.2.7

Sample Pro*C Program

The following Pro*C program connects to the database using the database account scott/tiger.

The database contains information about employees and departments (see the previous examples used in this tutorial). The user has to enter a salary which then is used to retrieve all employees (from the relation EMP) who earn more than the given minimum salary. Retrieving and processing individual result tuples occurs through using a PL/SQL cursor in a C while-loop.

/* Declarations */

#include <stdio.h>

#include <string.h>

#include <stdlib.h>

/* Declare section for host variables */

EXEC SQL BEGIN DECLARE SECTION;

VARCHAR userid[20];

VARCHAR passwd[20]; int empno;

VARCHAR ename[15]; float sal; float min_sal;

EXEC SQL END DECLARE SECTION;

/* Load SQL Communication Area */

EXEC SQL INCLUDE SQLCA.H; main() /* Main program */

{ int retval;

/* Catch errors automatically and go to error handling rountine */

EXEC SQL WHENEVER SQLERROR GOTO error;

/* Connect to Oracle as SCOTT/TIGER; both are host variables */

/* of type VARCHAR; Account and Password are specified explicitly */ strcpy(userid.arr,"SCOTT"); /* userid.arr := "SCOTT" */ userid.len=strlen(userid.arr); /* uid.len := 5 */ strcpy(passwd.arr,"SCOTT"); /* passwd.arr := "TIGER" */ passwd.len=strlen(passwd.arr); /* passwd.len := 5 */

EXEC SQL CONNECT :userid IDENTIFIED BY :passwd; printf("Connected to ORACLE as: %s\n\n", userid.arr);

/* Enter minimum salary by user */ printf("Please enter minimum salary > "); retval = scanf("%f", &min_sal); if(retval != 1) { printf("Input error!!\n");

EXEC SQL ROLLBACK WORK RELEASE;

/* Disconnect from ORACLE */ exit(2); /* Exit program */

}

/* Declare cursor; cannot occur in declare section! */

EXEC SQL DECLARE EMP_CUR CURSOR FOR

SELECT EMPNO,ENAME,SAL FROM EMP

WHERE SAL>=:min_sal;

/* Print Table header, run cursor through result set */ printf("Empployee-ID Employee-Name Salary \n"); printf("-------------------------------------\n");

EXEC SQL OPEN EMP_CUR;

EXEC SQL FETCH EMP_CUR INTO :empno, :ename, :sal; /* Fetch 1.tuple */ while(sqlca.sqlcode==0) { /* are there more tuples ? */ ename.arr[ename.len] = ’\0’; /* "End of String" */ printf("%15d %-17s %7.2f\n",empno,ename.arr,sal);

EXEC SQL FETCH EMP_CUR INTO :empno, :ename, :sal; /* get next tuple */

}

EXEC SQL CLOSE EMP_CUR;

/* Disconnect from database and terminate program */

EXEC SQL COMMIT WORK RELEASE; printf("\nDisconnected from ORACLE\n"); exit(0);

/* Error Handling: Print error message */ error: printf("\nError: %.70s \n",sqlca.sqlerrm.sqlerrmc);

EXEC SQL ROLLBACK WORK RELEASE; exit(1);

}

5 Integrity Constraints and Triggers

5.1 Integrity Constraints

In Section 1 we have discussed three types of integrity constraints: not null constraints, primary keys, and unique constraints. In this section we introduce two more types of constraints that can be specified within the create table statement: check constraints (to restrict possible attribute values), and foreign key constraints (to specify interdependencies between relations).

5.1.1

Check Constraints

Often columns in a table must have values that are within a certain range or that satisfy certain conditions. Check constraints allow users to restrict possible attribute values for a column to admissible ones. They can be specified as column constraints or table constraints. The syntax for a check constraint is

[constraint <name>] check(<condition>)

If a check constraint is specified as a column constraint, the condition can only refer that column.

Example: The name of an employee must consist of upper case letters only; the minimum salary of an employee is 500; department numbers must range between 10 and

100: create table EMP

( . . . ,

ENAME

SAL

DEPTNO varchar2(30) constraint check name check(ENAME = upper(ENAME) ), number(5,2) constraint check sal check(SAL >= 500), number(3) constraint check deptno check(DEPTNO between 10 and 100) );

If a check constraint is specified as a table constraint, <condition> can refer to all columns of the table. Note that only simple conditions are allowed. For example, it is not allowed to refer to columns of other tables or to formulate queries as check conditions. Furthermore, the functions sysdate and user cannot be used in a condition. In principle, thus only simple attribute comparisons and logical connectives such as and, or, and not are allowed. A check condition, however, can include a not null constraint:

SAL number(5,2) constraint check sal check(SAL is not null and SAL >= 500),

Without the not null condition, the value null for the attribute SAL would not cause a violation of the constraint.

Example: At least two persons must participate in a project, and the project’s start date must be before the project’s end date:

create table PROJECT

( . . . ,

PERSONS

. . . , number(5) constraint check pers check (PERSONS > 2), constraint dates ok check(PEND > PSTART) );

In this table definition, check pers is a column constraint and dates ok is a table constraint.

The database system automatically checks the specified conditions each time a database modification is performed on this relation. For example, the insertion insert into EMP values(7999,’SCOTT’,’CLERK’,7698,’31-OCT-94’,450,10); causes a constraint violation

ORA-02290: check constraint (CHECK SAL) violated and the insertion is rejected.

5.1.2

Foreign Key Constraints

A foreign key constraint (or referential integrity constraint) can be specified as a column constraint or as a table constraint:

[constraint <name>] [foreign key (<column(s)>)] references <table>[(<column(s)>)]

[on delete cascade]

This constraint specifies a column or a list of columns as a foreign key of the referencing table.

The referencing table is called the child-table, and the referenced table is called the parent-table.

In other words, one cannot define a referential integrity constraint that refers to a table R before that table R has been created.

The clause foreign key has to be used in addition to the clause references if the foreign key includes more than one column. In this case, the constraint has to be specified as a table constraint. The clause references defines which columns of the parent-table are referenced. If only the name of the parent-table is given, the list of attributes that build the primary key of that table is assumed.

Example: Each employee in the table EMP must work in a department that is contained in the table DEPT: create table EMP

( EMPNO number(4) constraint pk emp primary key,

. . . ,

DEPTNO number(3) constraint fk deptno references DEPT(DEPTNO) );

The column DEPTNO of the table EMP (child-table) builds the foreign key and references the primary key of the table DEPT (parent-table). The relationship between these two tables is illustrated in Figure 2. Since in this table definition the referential integrity constraint includes

only one column, the clause foreign key is not used. It is very important that a foreign key must refer to the complete primary key of a parent-table, not only a subset of the attributes that build the primary key !

EMP (Child−Table)

. . .

foreign key

DEPTNO

30 references

DEPT (Parent−Table)

DEPTNO

. . .

primary key

Figure 2: Foreign Key Constraint between the Tables EMP and DEPT

In order to satisfy a foreign key constraint, each row in the child-table has to satisfy one of the following two conditions:

• the attribute value (list of attribute values) of the foreign key must appear as a primary key value in the parent-table, or

• the attribute value of the foreign key is null (in case of a composite foreign key, at least one attribute value of the foreign key is null )

According to the above definition for the table EMP, an employee must not necessarily work in a department, i.e., for the attribute DEPTNO the value null is admissible.

Example: Each project manager must be an employee: create table PROJECT

( PNO number(3) constraint prj pk primary key,

PMGR number(4) not null constraint fk pmgr references EMP,

. . . );

Because only the name of the parent-table is given (DEPT), the primary key of this relation is assumed. A foreign key constraint may also refer to the same table, i.e., parent-table and child-table are identical.

Example: Each manager must be an employee: create table EMP

( EMPNO number(4) constraint emp pk primary key,

. . .

MGR number(4) not null constraint fk mgr references EMP,

. . .

);

5.1.3

More about Column- and Table Constraints

If a constraint is defined within the create table command or added using the alter table command (compare Section 1.5.5), the constraint is automatically enabled. A constraint can be disabled using the command alter table <table> disable constraint <name> | primary key | unique[<column(s)>]

[cascade];

To disable a primary key, one must disable all foreign key constraints that depend on this primary key. The clause cascade automatically disables foreign key constraints that depend on the (disabled) primary key.

Example: Disable the primary key of the table DEPT and disable the foreign key constraint in the table EMP: alter table DEPT disable primary key cascade;

In order to enable an integrity constraint, the clause enable is used instead of disable. A constraint can only be enabled successfully if no tuple in the table violates the constraint. Otherwise an error message is displayed. Note that for enabling/disabling an integrity constraint it is important that you have named the constraints.

In order to identify those tuples that violate an integrity constraint whose activation failed, one can use the clause exceptions into EXCEPTIONS with the alter table statement. EXCEPTIONS is a table that stores information about violating tuples.

Each tuple in this table is identified by the attribute ROWID. Every tuple in a database has a pseudo-column ROWID that is used to identify tuples. Besides the rowid, the name of the table, the table owner as well as the name of the violated constraint are stored.

Example: Assume we want to add an integrity constraint to our table EMP which requires that each manager must earn more than 4000: alter table EMP add constraint manager sal check(JOB != ’MANAGER’ or SAL >= 4000) exceptions into EXCEPTIONS;

If the table EMP already contains tuples that violate the constraint, the constraint cannot be activated and information about violating tuples is automatically inserted into the table

EXCEPTIONS.

Detailed information about the violating tuples can be obtained by joining the tables EMP and

EXCEPTIONS, based on the join attribute ROWID: select EMP.∗, CONSTRAINT from EMP, EXCEPTIONS where EMP.ROWID = EXCEPTIONS.ROW ID;

Before this table can be used, it must be created using the SQL script utlexcept.sql which can be found in the directory $ORACLE HOME/rdbms/admin.

Tuples contained in the query result now can be modified (e.g., by increasing the salary of managers) such that adding the constraint can be performed successfully.

Note that it is important to delete “old” violations from the relation EXCEPTIONS before it is used again.

If a table is used as a reference of a foreign key, this table can only be dropped using the command drop table <table> cascade constraints;. All other database objects that refer to this table (e.g., triggers, see Section 5.2) remain in the database system, but they are not valid.

Information about integrity constraints, their status (enabled, disabled) etc. is stored in the data dictionary, more precisely, in the tables USER CONSTRAINTS and USER CONS CONSTRAINTS.

5.2 Triggers

5.2.1

Overview

The different types of integrity constraints discussed so far provide a declarative mechanism to associate “simple” conditions with a table such as a primary key, foreign keys or domain constraints. Complex integrity constraints that refer to several tables and attributes (as they are known as assertions in the SQL standard) cannot be specified within table definitions. Triggers, in contrast, provide a procedural technique to specify and maintain integrity constraints.

Triggers even allow users to specify more complex integrity constraints since a trigger essentially is a PL/SQL procedure. Such a procedure is associated with a table and is automatically called by the database system whenever a certain modification (event ) occurs on that table.

Modifications on a table may include insert, update, and delete operations (Oracle 7).

5.2.2

Structure of Triggers

A trigger definition consists of the following (optional) components:

• trigger name create [or replace] trigger <trigger name>

• trigger time point before | after

• triggering event(s) insert or update [of <column(s)>] or delete on <table>

• trigger type (optional) for each row

• trigger restriction (only for for each row triggers !) when (<condition>)

• trigger body

The clause replace re-creates a previous trigger definition having the same <trigger name>.

The name of a trigger can be chosen arbitrarily, but it is a good programming style to use

a trigger name that reflects the table and the event(s), e.g., upd ins EMP. A trigger can be invoked before or after the triggering event. The triggering event specifies before (after) which operations on the table <table> the trigger is executed. A single event is an insert, an update, or a delete; events can be combined using the logical connective or. If for an update trigger no columns are specified, the trigger is executed after (before) <table> is updated. If the trigger should only be executed when certain columns are updated, these columns must be specified after the event update. If a trigger is used to maintain an integrity constraint, the triggering events typically correspond to the operations that can violate the integrity constraint.

In order to program triggers efficiently (and correctly) it is essential to understand the difference between a row level trigger and a statement level trigger. A row level trigger is defined using the clause for each row. If this clause is not given, the trigger is assumed to be a statement trigger. A row trigger executes once for each row after (before) the event. In contrast, a statement trigger is executed once after (before) the event, independent of how many rows are affected by the event. For example, a row trigger with the event specification after update is executed once for each row affected by the update. Thus, if the update affects 20 tuples, the trigger is executed 20 times, for each row at a time. In contrast, a statement trigger is only executed once.

When combining the different types of triggers, there are twelve possible trigger configurations that can be defined for a table: event insert update delete trigger time point trigger type before after statement row

Figure 3: Trigger Types

Row triggers have some special features that are not provided by statement triggers:

Only with a row trigger it is possible to access the attribute values of a tuple before and after the modification (because the trigger is executed once for each tuple). For an update trigger, the old attribute value can be accessed using :old.<column> and the new attribute value can be accessed using :new.<column>. For an insert trigger, only :new.<column> can be used, and for a delete trigger only :old.<column> can be used (because there exists no old, respectively, new value of the tuple). In these cases, :new.<column> refers to the attribute value of <column> of the inserted tuple, and :old.<column> refers to the attribute value of

<column> of the deleted tuple. In a row trigger thus it is possible to specify comparisons between old and new attribute values in the PL/SQL block, e.g., “if :old.SAL < :new.SAL

then . . . ”. If for a row trigger the trigger time point before is specified, it is even possible to modify the new values of the row, e.g., :new.SAL := :new.SAL ∗ 1.05 or :new.SAL := :old.SAL.

Such modifications are not possible with after row triggers. In general, it is advisable to use a after row trigger if the new row is not modified in the PL/SQL block. Oracle then can process

these triggers more efficiently. Statement level triggers are in general only used in combination with the trigger time point after.

In a trigger definition the when clause can only be used in combination with a for each row trigger. The clause is used to further restrict when the trigger is executed. For the specification of the condition in the when clause, the same restrictions as for the check clause hold. The only exceptions are that the functions sysdate and user can be used, and that it is possible to refer to the old/new attribute values of the actual row. In the latter case, the colon “:” must not be used, i.e., only old.<attribute> and new.<attribute>.

The trigger body consists of a PL/SQL block. All SQL and PL/SQL commands except the two statements commit and rollback can be used in a trigger’s PL/SQL block. Furthermore, additional if constructs allow to execute certain parts of the PL/SQL block depending on the triggering event. For this, the three constructs if inserting, if updating[(’<column>’)], and if deleting exist. They can be used as shown in the following example: create or replace trigger emp check after insert or delete or update on EMP for each row begin if inserting then

<PL/SQL block> end if ; if updating then

<PL/SQL block> end if ; if deleting then

<PL/SQL block> end if ; end;

It is important to understand that the execution of a trigger’s PL/SQL block builds a part of the transaction that contains the triggering event. Thus, for example, an insert statement in a PL/SQL block can cause another trigger to be executed. Multiple triggers and modifications thus can lead to a cascading execution of triggers. Such a sequence of triggers terminates successfully if (1) no exception is raised within a PL/SQL block, and (2) no declaratively specified integrity constraint is violated. If a trigger raises an exception in a PL/SQL block, all modifications up to the beginning of the transaction are rolled back. In the PL/SQL block of a trigger, an exception can be raised using the statement raise application error (see

Section 4.1.5). This statement causes an implicit rollback. In combination with a row trigger, raise application error can refer to old/new values of modified rows: raise application error(−20020, ’Salary increase from ’ || to char(:old.SAL) || ’ to ’ to char(:new.SAL) || ’ is too high’); or raise application error(−20030, ’Employee Id ’ || to char(:new .EMPNO) || ’ does not exist.’);

5.2.3

Example Triggers

Suppose we have to maintain the following integrity constraint: “The salary of an employee different from the president cannot be decreased and must also not be increased more than

10%. Furthermore, depending on the job title, each salary must lie within a certain salary range.

We assume a table SALGRADE that stores the minimum (MINSAL) and maximum (MAXSAL) salary for each job title (JOB). Since the above condition can be checked for each employee individually, we define the following row trigger: trig1.sql

create or replace trigger check salary EMP after insert or update of SAL, JOB on EMP for each row when (new.JOB != ’PRESIDENT’) – – trigger restriction declare minsal, maxsal SALGRADE.MAXSAL%TYPE; begin

– – retrieve minimum and maximum salary for JOB select MINSAL, MAXSAL into minsal, maxsal from SALGRADE where JOB = :new.JOB;

– – If the new salary has been decreased or does not lie within the salary range,

– – raise an exception if (:new.SAL < minsal or :new.SAL > maxsal) then raise application error(-20225, ’Salary range exceeded’); elsif (:new.SAL < :old.SAL) then raise application error(-20230, ’Salary has been decreased’); elsif (:new.SAL > 1.1 ∗ :old.SAL) then raise application error(-20235, ’More than 10% salary increase’); end if ; end;

We use an after trigger because the inserted or updated row is not changed within the PL/SQL block (e.g., in case of a constraint violation, it would be possible to restore the old attribute values).

Note that also modifications on the table SALGRADE can cause a constraint violation. In order to maintain the complete condition we define the following trigger on the table SALGRADE. In case of a violation by an update modification, however, we do not raise an exception, but restore the old attribute values.

trig2.sql

create or replace trigger check salary SALGRADE before update or delete on SALGRADE for each row when (new.MINSAL > old.MINSAL

declare or new.MAXSAL < old.MAXSAL)

– – only restricting a salary range can cause a constraint violation job emps number(3) := 0; begin if deleting then – – Does there still exist an employee having the deleted job ?

select count(∗) into job emps from EMP where JOB = :old.JOB; if job emps != 0 then raise application error(-20240, ’ There still exist employees with the job ’ ||

:old.JOB); end if ; end if ; if updating then

– – Are there employees whose salary does not lie within the modified salary range ?

select count(∗) into job emps from EMP where JOB = :new.JOB

and SAL not between :new.MINSAL and :new.MAXSAL; if job emps != 0 then – – restore old salary ranges

:new.MINSAL := :old.MINSAL;

:new.MAXSAL := :old.MAXSAL; end if ; end if ; end;

In this case a before trigger must be used to restore the old attribute values of an updated row.

Suppose we furthermore have a column BUDGET in our table DEPT that is used to store the budget available for each department. Assume the integrity constraint requires that the total of all salaries in a department must not exceed the department’s budget. Critical operations on the relation EMP are insertions into EMP and updates on the attributes SAL or DEPTNO.

trig3.sql

create or replace trigger check budget EMP after insert or update of SAL, DEPTNO on EMP declare cursor DEPT CUR is select DEPTNO, BUDGET from DEPT;

DNO DEPT.DEPTNO%TYPE;

ALLSAL DEPT.BUDGET%TYPE;

DEPT SAL number; begin open DEPT CUR; loop fetch DEPT CUR into DNO, ALLSAL; exit when DEPT CUR%NOTFOUND; select sum(SAL) into DEPT SAL from EMP where DEPTNO = DNO; if DEPT SAL > ALLSAL then raise application error(-20325, ’Total of salaries in the department ’ || to char(DNO) || ’ exceeds budget’); end if ; end loop; close DEPT CUR; end;

In this case we use a statement trigger on the relation EMP because we have to apply an aggregate function on the salary of all employees that work in a particular department. For the relation

DEPT, we also have to define a trigger which, however, can be formulated as a row trigger.

5.2.4

Programming Triggers

For programmers, row triggers are the most critical type of triggers because they include several restrictions. In order to ensure read consistency, Oracle performs an exclusive lock on the table at the beginning of an insert, update, or delete statement. That is, other users cannot access this table until modifications have been successfully completed. In this case, the table currently modified is said to be a mutating table. The only way to access a mutating table in a trigger is to use :old.<column> and :new.<column> in connection with a row trigger.

Example of an erroneous row trigger: create trigger check sal EMP after update of SAL on EMP for each row

declare sal sum number; begin select sum(SAL) into sal sum from EMP;

. . . ; end;

For example, if an update statement of the form update EMP set SAL = SAL ∗ 1.1 is executed on the table EMP, the above trigger is executed once for each modified row. While the table is being modified by the update command, it is not possible to access all tuples of the table using the select command, because it is locked. In this case we get the error message

ORA-04091: table EMP is mutating, trigger may not read or modify it

ORA-06512: at line 4

ORA-04088: error during execution of trigger ’CHECK_SAL_EMP’

The only way to access the table, or more precisely, to access the modified tuple, is to use

:old.<column> and :new.<column>.

It is recommended to follow the rules below for the definition of integrity maintaining triggers: identify operations and tables that are critical for the integrity constraint for each such table check if constraint can be checked at row level then if checked rows are modified in trigger then use before row trigger else use after row trigger else use after statement trigger

Triggers are not exclusively used for integrity maintenance. They can also be used for

• Monitoring purposes, such as the monitoring of user accesses and modifications on certain sensitive tables.

• Logging actions, e.g., on tables: create trigger LOG EMP after insert or update or delete on EMP begin if inserting then insert into EMP LOG values(user, ’INSERT’, sysdate);

end if ; if updating then insert into EMP LOG values(user, ’UPDATE’, sysdate); end if ; if deleting then insert into EMP LOG values(user, ’DELETE’, sysdate); end if ; end;

By using a row trigger, even the attribute values of the modified tuples can be stored in the table EMP LOG.

• automatic propagation of modifications. For example, if a manager is transfered to another department, a trigger can be defined that automatically transfers the manager’s employees to the new department.

5.2.5

More about Triggers

If a trigger is specified within the SQL*Plus shell, the definition must end with a point “.” in the last line. Issuing the command run causes SQL*Plus to compile this trigger definition. A trigger definition can be loaded from a file using the command @. Note that the last line in the file must consist of a slash “/”.

A trigger definition cannot be changed, it can only be re-created using the or replace clause.

The command drop <trigger name> deletes a trigger.

After a trigger definition has been successfully compiled, the trigger automatically is enabled.

The command alter trigger <trigger name> disable is used to deactivate a trigger. All triggers defined on a table can be (de)activated using the command alter table <Tabelle> enable | disable all trigger;

The data dictionary stores information about triggers in the table USER TRIGGERS. The information includes the trigger name, type, table, and the code for the PL/SQL block.

6 System Architecture

In the following sections we discuss the main components of the Oracle DBMS (Version 7.X) architecture (Section 6.1) and the logical and physical database structures (Sections 6.2 and

6.3). We furthermore sketch how SQL statements are processed (Section 6.4) and how database objects are created (Section 6.5).

6.1 Storage Management and Processes

The Oracle DBMS server is based on a so-called Multi-Server Architecture. The server is responsible for processing all database activities such as the execution of SQL statements, user and resource management, and storage management. Although there is only one copy of the program code for the DBMS server, to each user connected to the server logically a separate server is assigned. The following figure illustrates the architecture of the Oracle DBMS consisting of storage structures, processes, and files.

User 1 User 2 User 3 User n

Server−

Process

PGA

Database

Buffer

Server−

Process

PGA

Server−

Process

PGA

System Global Area (SGA)

Shared Pool

Redo−Log−

Buffer

Dictionary Cache

Server−

Process

PGA

Library Cache

Log

6.2 Logical Database Structures

For the architecture of an Oracle database we distinguish between logical and physical database structures that make up a database. Logical structures describe logical areas of storage (name spaces) where objects such as tables can be stored. Physical structures, in contrast, are determined by the operating system files that constitute the database.

The logical database structures include:

Database A database consists of one or more storage divisions, so-called tablespaces.

Tablespaces A tablespace is a logical division of a database. All database objects are logically stored in tablespaces. Each database has at least one tablespace, the SYSTEM tablespace, that contains the data dictionary. Other tablespaces can be created and used for different applications or tasks.

Segments If a database object (e.g., a table or a cluster) is created, automatically a portion of the tablespace is allocated. This portion is called a segment. For each table there is a table segment. For indexes so-called index segments are allocated. The segment associated with a database object belongs to exactly one tablespace.

Extent An extent is the smallest logical storage unit that can be allocated for a database object, and it consists a contiguous sequence of data blocks! If the size of a database object increases (e.g., due to insertions of tuples into a table), an additional extent is allocated for the object. Information about the extents allocated for database objects can be found in the data dictionary view USER EXTENTS.

A special type of segments are rollback segments. They don’t contain a database object, but contain a “before image” of modified data for which the modifying transaction has not yet been committed. Modifications are undone using rollback segments. Oracle uses rollback segments in order to maintain read consistency among multiple users. Furthermore, rollback segments are used to restore the “before image” of modified tuples in the event of a rollback of the modifying transaction.

Typically, an extra tablespace (RBS) is used to store rollback segments. This tablespace can be defined during the creation of a database. The size of this tablespace and its segments depends on the type and size of transactions that are typically performed by application programs.

A database typically consists of a SYSTEM tablespace containing the data dictionary and further internal tables, procedures etc., and a tablespace for rollback segments. Additional tablespaces include a tablespace for user data (USERS), a tablespace for temporary query results and tables (TEMP), and a tablespace used by applications such as SQL*Forms (TOOLS).

6.3 Physical Database Structure

The physical database structure of an Oracle database is determined by files and data blocks:

Data Files A tablespace consists of one or more operating system files that are stored on disk.

Thus a database essentially is a collection of data files that can be stored on different storage devices (magnetic tape, optical disks etc.). Typically, only magnetic disks are used. Multiple data files for a tablespace allows the server to distribute a database object over multiple disks (depending on the size of the object).

Blocks An extent consists of one or more contiguous Oracle data blocks. A block determines the finest level of granularity of where data can be stored. One data block corresponds to a specific number of bytes of physical database space on disk. A data block size is specified for each Oracle database when the database is created. A database uses and allocates free database space in Oracle data blocks. Information about data blocks can be retrieved from the data dictionary views USER SEGMENTS and USER EXTENTS. These views show how many blocks are allocated for a database object and how many blocks are available (free) in a segment/extent.

As mentioned in Section 6.1, aside from datafiles three further types of files are associated with a database instance:

Redo-Log Files Each database instance maintains a set of redo-log files. These files are used to record logs of all transactions. The logs are used to recover the database’s transactions in their proper order in the event of a database crash (the recovering operations are called roll forward). When a transaction is executed, modifications are entered in the redo-log buffer, while the blocks affected by the transactions are not immediately written back to disk, thus allowing optimizing the performance through batch writes.

Control Files Each database instance has at least one control file. In this file the name of the database instance and the locations (disks) of the data files and redo-log files are recorded. Each time an instance is started, the data and redo-log files are determined by using the control file(s).

Archive/Backup Files If an instance is running in the archive-log mode, the ARCH process archives the modifications of the redo-log files in extra archive or backup files. In contrast to redo-log files, these files are typically not overwritten.

The following ER schema illustrates the architecture of an Oracle database instance and the relationships between physical and logical database structures (relationships can be read as

“consists of”).

redo−log file database control file datafile block tablespace segment table index cluster rollback seg.

extent

Figure 5: Relationships between logical and physical database structures

6.4 Steps in Processing an SQL Statement

In the following we sketch how an SQL statement is processed by the Oracle server and which processes and buffers involved.

1. Assume a user (working with SQL*Plus) issues an update statement on the table TAB such that more than one tuple is affected by the update. The statement is passed to the server by the USER process. Then the server (or rather the query processor) checks whether this statement is already contained in the library cache such that the corresponding information (parse tree, execution plan) can be used. If the statement can not be found, it is parsed and after verifying the statement (user privileges, affected tables and columns) using data from the dictionary cache, a query execution plan is generated by the query optimizer. Together with the parse tree, this plan is stored in the library cache.

2. For the objects affected by the statement (here the table TAB) it is checked, whether the corresponding data blocks already exist in the database buffer. If not, the USER process reads the data blocks into the database buffer. If there is not enough space in the buffer, the least recently used blocks of other objects are written back to the disk by the DBWR process.

3. The modifications of the tuples affected by the update occurs in the database buffer.

Before the data blocks are modified, the “before image” of the tuples is written to the rollback segments by the DBWR process.

4. While the redo-log buffer is filled during the data block modifications, the LGWR process writes entries from the redo-log buffer to the redo-log files.

5. After all tuples (or rather the corresponding data blocks) have been modified in the database buffer, the modifications can be committed by the user using the commit command.

6. As long as no commit has been issued by the user, modifications can be undone using the rollback statement. In this case, the modified data blocks in the database buffer are overwritten by the original blocks stored in the rollback segments.

7. If the user issues a commit, the space allocated for the blocks in the rollback segments is deallocated and can be used by other transactions. Furthermore, the modified blocks in the database buffer are unlocked such that other users now can read the modified blocks.

The end of the transaction (more precisely the commit) is recorded in the redo-log files.

The modified blocks are only written to the disk by the DBWR process if the space allocated for the blocks is needed for other blocks.

6.5 Creating Database Objects

For database objects (tables, indexes, clusters) that require their own storage area, a segment in a tablespace is allocated. Since the system typically does not know what the size of the

database object will be, some default storage parameters are used. The user, however, has the possibility to explicitly specify the storage parameters using a storage clause in, e.g., the create table statement. This specification then overwrites the system parameters and allows the user to specify the (expected) storage size of the object in terms of extents.

Suppose the following table definition that includes a storage clause: create table STOCKS

(ITEM varchar2(30),

QUANTITY number(4)) storage (initial 1M next 400k minextents 1 maxextents 20 pctincrease 50); initial and next specify the size of the first and next extents, respectively. In the definition above, the initial extent has a size of 1MB, and the next extent has a size of 400KB. The parameter minextents specifies the total number of extents allocated when the segment is created. This parameter allows the user to allocate a large amount of space when an object is created, even if the space available is not contiguous. The default and minimum value is 1. The parameter maxextents specifies the admissible number of extents. The parameter pctincrease specifies the percent by which each extent after the second grows over the previous extent. The default value is 50, meaning that each subsequent extent is 50% larger than the preceding extent. Based on the above table definition, we thus would get the following logical database structure for the table STOCKS (assuming that four extents have already been allocated): initial 1M 400k 600k 900k

1. Extent 2. Extent 3. Extent 4. Extent

Figure 6: Logical Storage Structure of the Table STOCKS

If the space required for a database object is known before creation, already the initial extent should be big enough to hold the database object. In this case, the Oracle server (more precisely the resource manager) tries to allocate contiguous data blocks on disks for this object, thus the defragmentation of data blocks associated with a database object can be prevented.

For indexes a storage clause can be specified as well create index STOCK IDX on STOCKS(ITEM) storage (initial 200k next 100k minextents 1 maxextents 5);

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Publicitate

Oracle/SQL Tutorial

Michael Gertz

Database and Information Systems Group

Department of Computer Science

University of California, Davis [email protected]

http://www.db.cs.ucdavis.edu

Contents

1 SQL – Structured Query Language

1.1

Tables

1.2

Queries (Part I)

1.3

Data Definition in SQL

1.4

Data Modifications in SQL

1.5

Queries (Part II)

1.6

Views

2 SQL*Plus

Introduction

A Minimal User Guide

Editor Commands

SQL*Plus Help System and Other Useful Commands

Formatting the Output

3 Oracle Data Dictionary

3.1

Data Dictionary Tables

3.2

Data Dictionary Views

4 Application Programming

4.1

PL/SQL

4.2

Embedded SQL and Pro*C

5 Integrity Constraints and Triggers

5.1

Integrity Constraints

5.2

Triggers

6 System Architecture

6.1

Storage Management and Processes

System Global Area (SGA)

6.2

Logical Database Structures

6.3

Physical Database Structure

6.4

Steps in Processing an SQL Statement

6.5

Creating Database Objects

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