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📄 Contents

  1. Sams Teach Yourself SQL in 24 Hours, Third Edition
  2. Table of Contents
  3. Copyright
  4. About the Authors
  5. Acknowledgments
  6. Tell Us What You Think!
  7. Introduction
  8. Part I: A SQL Concepts Overview
  9. Hour 1. Welcome to the World of SQL
  10. SQL Definition and History
  11. SQL Sessions
  12. Types of SQL Commands
  13. An Introduction to the Database Used in This Book
  14. Summary
  15. Q&A
  16. Workshop
  17. Part II: Building Your Database
  18. Hour 2. Defining Data Structures
  19. What Is Data?
  20. Basic Data Types
  21. Summary
  22. Q&A
  23. Workshop
  24. Hour 3. Managing Database Objects
  25. What Are Database Objects?
  26. What Is a Schema?
  27. A Table: The Primary Storage for Data
  28. Integrity Constraints
  29. Summary
  30. Q&A
  31. Workshop
  32. Hour 4. The Normalization Process
  33. Normalizing a Database
  34. Summary
  35. Q&A
  36. Workshop
  37. Hour 5. Manipulating Data
  38. Overview of Data Manipulation
  39. Populating Tables with New Data
  40. Updating Existing Data
  41. Deleting Data from Tables
  42. Summary
  43. Q&A
  44. Workshop
  45. Hour 6. Managing Database Transactions
  46. What Is a Transaction?
  47. What Is Transactional Control?
  48. Transactional Control and Database Performance
  49. Summary
  50. Q&A
  51. Workshop
  52. Part III: Getting Effective Results from Queries
  53. Hour 7. Introduction to the Database Query
  54. What Is a Query?
  55. Introduction to the <tt>SELECT</tt> Statement
  56. Examples of Simple Queries
  57. Summary
  58. Q&amp;A
  59. Workshop
  60. Hour 8. Using Operators to Categorize Data
  61. What Is an Operator in SQL?
  62. Comparison Operators
  63. Logical Operators
  64. Conjunctive Operators
  65. Negating Conditions with the <tt>NOT</tt> Operator
  66. Arithmetic Operators
  67. Summary
  68. Q&amp;A
  69. Workshop
  70. Hour 9. Summarizing Data Results from a Query
  71. What Are Aggregate Functions?
  72. Summary
  73. Q&amp;A
  74. Workshop
  75. Hour 10. Sorting and Grouping Data
  76. Why Group Data?
  77. The <tt>GROUP BY</tt> Clause
  78. <tt>GROUP BY</tt> Versus <tt>ORDER BY</tt>
  79. The <tt>HAVING</tt> Clause
  80. Summary
  81. Q&amp;A
  82. Workshop
  83. Hour 11. Restructuring the Appearance of Data
  84. The Concepts of ANSI Character Functions
  85. Various Common Character Functions
  86. Miscellaneous Character Functions
  87. Mathematical Functions
  88. Conversion Functions
  89. The Concept of Combining Character Functions
  90. Summary
  91. Q&amp;A
  92. Workshop
  93. Hour 12. Understanding Dates and Times
  94. How Is a Date Stored?
  95. Date Functions
  96. Date Conversions
  97. Summary
  98. Q&amp;A
  99. Workshop
  100. Part IV: Building Sophisticated Database Queries
  101. Hour 13. Joining Tables in Queries
  102. Selecting Data from Multiple Tables
  103. Types of Joins
  104. Join Considerations
  105. Summary
  106. Q&amp;A
  107. Workshop
  108. Hour 14. Using Subqueries to Define Unknown Data
  109. What Is a Subquery?
  110. Embedding a Subquery Within a Subquery
  111. Summary
  112. Q&A
  113. Workshop
  114. Hour 15. Combining Multiple Queries into One
  115. Single Queries Versus Compound Queries
  116. Why Would I Ever Want to Use a Compound Query?
  117. Compound Query Operators
  118. Using an <tt>ORDER BY</tt> with a Compound Query
  119. Using <tt>GROUP BY</tt> with a Compound Query
  120. Retrieving Accurate Data
  121. Summary
  122. Workshop
  123. Q&amp;A
  124. Part V: SQL Performance Tuning
  125. Hour 16. Using Indexes to Improve Performance
  126. What Is an Index?
  127. How Do Indexes Work?
  128. The <tt>CREATE INDEX</tt> Command
  129. Types of Indexes
  130. When Should Indexes Be Considered?
  131. When Should Indexes Be Avoided?
  132. Summary
  133. Q&amp;A
  134. Workshop
  135. Hour 17. Improving Database Performance
  136. What Is SQL Statement Tuning?
  137. Database Tuning Versus SQL Tuning
  138. Formatting Your SQL Statement
  139. Full Table Scans
  140. Other Performance Considerations
  141. Performance Tools
  142. Summary
  143. Q&amp;A
  144. Workshop
  145. Part VI: Using SQL to Manage Users and Security
  146. Hour 18. Managing Database Users
  147. Users Are the Reason
  148. The Management Process
  149. Tools Utilized by Database Users
  150. Summary
  151. Q&amp;A
  152. Workshop
  153. Hour 19. Managing Database Security
  154. What Is Database Security?
  155. How Does Security Differ from User Management?
  156. What Are Privileges?
  157. Controlling User Access
  158. Controlling Privileges Through Roles
  159. Summary
  160. Q&amp;A
  161. Workshop
  162. Part VII: Summarized Data Structures
  163. Hour 20. Creating and Using Views and Synonyms
  164. What Is a View?
  165. Creating Views
  166. Dropping a View
  167. What Is a Synonym?
  168. Summary
  169. Q&amp;A
  170. Workshop
  171. Hour 21. Working with the System Catalog
  172. What Is the System Catalog?
  173. How Is the System Catalog Created?
  174. What Is Contained in the System Catalog?
  175. Examples of System Catalog Tables by Implementation
  176. Querying the System Catalog
  177. Updating System Catalog Objects
  178. Summary
  179. Q&amp;A
  180. Workshop
  181. Part VIII: Applying SQL Fundamentals in Today's World
  182. Hour 22. Advanced SQL Topics
  183. Advanced Topics
  184. Cursors
  185. Stored Procedures and Functions
  186. Triggers
  187. Dynamic SQL
  188. Call-Level Interface
  189. Using SQL to Generate SQL
  190. Direct Versus Embedded SQL
  191. Summary
  192. Q&amp;A
  193. Workshop
  194. Hour 23. Extending SQL to the Enterprise, the Internet, and the Intranet
  195. SQL and the Enterprise
  196. Accessing a Remote Database
  197. Accessing a Remote Database Through a Web Interface
  198. SQL and the Internet
  199. SQL and the Intranet
  200. Summary
  201. Q&amp;A
  202. Workshop
  203. Hour 24. Extensions to Standard SQL
  204. Various Implementations
  205. Examples of Extensions from Some Implementations
  206. Interactive SQL Statements
  207. Summary
  208. Q&amp;A
  209. Workshop
  210. Part IX: Appendixes
  211. Appendix A. Common SQL Commands
  212. SQL Statements
  213. SQL Clauses
  214. Appendix B. Using MySQL for Exercises
  215. Windows Installation Instructions
  216. Linux Installation Instructions
  217. Appendix C. Answers to Quizzes and Exercises
  218. Hour 1, "Welcome to the World of SQL"
  219. Hour 2, "Defining Data Structures"
  220. Hour 3, "Managing Database Objects"
  221. Hour 4, "The Normalization Process"
  222. Hour 5, "Manipulating Data"
  223. Hour 6, "Managing Database Transactions"
  224. Hour 7, "Introduction to the Database Query"
  225. Hour 8, "Using Operators to Categorize Data"
  226. Hour 9, "Summarizing Data Results from a Query"
  227. Hour 10, "Sorting and Grouping Data"
  228. Hour 11, "Restructuring the Appearance of Data"
  229. Hour 12, "Understanding Dates and Time"
  230. Hour 13, "Joining Tables in Queries"
  231. Hour 14, "Using Subqueries to Define Unknown Data"
  232. Hour 15, "Combining Multiple Queries into One"
  233. Hour 16, "Using Indexes to Improve Performance"
  234. Hour 17, "Improving Database Performance"
  235. Hour 18, "Managing Database Users"
  236. Hour 19, "Managing Database Security"
  237. Hour 20, "Creating and Using Views and Synonyms"
  238. Hour 21, "Working with the System Catalog"
  239. Hour 22, "Advanced SQL Topics"
  240. Hour 23, "Extending SQL to the Enterprise, the Internet, and the Intranet"
  241. Hour 24, "Extensions to Standard SQL"
  242. Appendix D. <tt>CREATE TABLE</tt> Statements for Book Examples
  243. <tt>EMPLOYEE_TBL</tt>
  244. <tt>EMPLOYEE_PAY_TBL</tt>
  245. <tt>CUSTOMER_TBL</tt>
  246. <tt>ORDERS_TBL</tt>
  247. <tt>PRODUCTS_TBL</tt>
  248. Appendix E. <tt>INSERT</tt> Statements for Data in Book Examples
  249. <tt>INSERT</tt> Statements
  250. Appendix F. Glossary
  251. Appendix G. Bonus Exercises
Recommended Book

A Table: The Primary Storage for Data

The table is the primary storage object for data in a relational database. A table consists of row(s) and column(s), both of which hold the data. A table takes up physical space in a database and can be permanent or temporary.

Fields and Columns

A field, also called a column in a relational database, is part of a table that is assigned a specific data type; a field should be named to correspond with the type of data that will be entered into that column. Columns can be specified as NULL or NOT NULL, meaning that if a column is NOT NULL, something must be entered. If a column is specified as NULL, nothing has to be entered.

Every database table must consist of at least one column. Columns are those elements within a table that hold specific types of data, such as a person's name or address. For example, a valid column in a customer table may be the customer's name.

Generally, a name must be one continuous string. An object name must typically be one continuous string and can be limited to the number of characters used according to each implementation of SQL. It is typical to use underscores with names to provide separations between characters. For example, a column for the customer's name can be named CUSTOMER_NAME instead of CUSTOMERNAME.

Additionally, data can be stored as either uppercase or lowercase for character-defined fields. The case that you use for data is simply a matter of preference, which should be based on how the data will be used. In many cases, data is stored in uppercase for simplicity and consistency. However, if data is stored in different case types throughout the database (uppercase, lowercase, and mixedcase), functions can be applied to convert the data to either uppercase or lowercase if needed. These functions will be covered in Hour 11, "Restructuring the Appearance of Data."

Rows

A row is a record of data in a database table. For example, a row of data in a customer table might consist of a particular customer's identification number, name, address, phone number, fax number, and so on. A row is comprised of fields that contain data from one record in a table. A table can contain as little as one row of data and up to as many as millions of rows of data or records.

The CREATE TABLE Statement

The CREATE TABLE statement in SQL is used to create a table. Although the very act of creating a table is quite simple, much time and effort should be put into planning table structures before the actual execution of the CREATE TABLE statement.

Some elementary questions need to be answered when creating a table:

  • What type of data will be entered into the table?
  • What will be the table's name?
  • What column(s) will compose the primary key?
  • What names shall be given to the columns (fields)?
  • What data type will be assigned to each column?
  • What will be the allocated length for each column?
  • Which columns in a table can be left blank?

After these questions are answered, the actual CREATE TABLE statement is simple.

The basic syntax to create a table is as follows:

   syntax_icon.gif
CREATE TABLE TABLE_NAME
( FIELD1  DATA TYPE  [ NOT NULL ],
  FIELD2  DATA TYPE  [ NOT NULL ],
  FIELD3  DATA TYPE  [ NOT NULL ],
  FIELD4  DATA TYPE  [ NOT NULL ],
  FIELD5  DATA TYPE  [ NOT NULL ] );

A semicolon is the last character in the previous statement. Most SQL implementations have some character that terminates a statement or submits a statement to the database server. Oracle and MySQL use the semicolon. Transact-SQL uses the GO statement. This book uses the semicolon.

Create a table called EMPLOYEE_TBL in the following example:

   input_icon.gif

   CREATE TABLE EMPLOYEE_TBL

   (EMP_ID        CHAR(9)        NOT NULL,

   EMP_NAME       VARCHAR (40)   NOT NULL,

   EMP_ST_ADDR    VARCHAR (20)   NOT NULL,

   EMP_CITY       VARCHAR (15)   NOT NULL,

   EMP_ST         CHAR(2)        NOT NULL,

   EMP_ZIP        INTEGER(5)      NOT NULL,

   EMP_PHONE      INTEGER(10)     NULL,

   EMP_PAGER      INTEGER(10)     NULL);

Eight different columns make up this table. Notice the use of the underscore character to break the column names up into what appears to be separate words (EMPLOYEE ID is stored as EMP_ID). This is a technique that is used to make a table or column name more readable. Each column has been assigned a specific data type and length, and by using the NULL/NOT NULL constraint, you have specified which columns require values for every row of data in the table. The EMP_PHONE is defined as NULL, meaning that NULL values are allowed in this column because there may be individuals without a telephone number. The information concerning each column is separated by a comma, with parentheses surrounding all columns (a left parenthesis before the first column and a right parenthesis following the information on the last column) .

Each record, or row of data, in this table would consist of the following:

EMP_ID, EMP_NAME, EMP_ST_ADDR, EMP_CITY, EMP_ST, EMP_ZIP, EMP_PHONE, EMP_PAGER 

In this table, each field is a column. The column EMP_ID could consist of one employee's identification number or many employees' identification numbers, depending on the requirements of a database query or transactions. The column is a vertical entity in a table, whereas a row of data is a horizontal entity.

STORAGE Clause

Some form of a STORAGE clause is available in many relational database implementations of SQL. The STORAGE clause in a CREATE TABLE statement is used for initial table sizing and is usually done at table creation. The syntax of a STORAGE clause as used in one implementation is shown in the following example:

   mysql_icon.gif
CREATE TABLE EMPLOYEE_TBL
(EMP_ID        CHAR(9)         NOT NULL,
EMP_NAME       VARCHAR(40)     NOT NULL,
EMP_ST_ADDR    VARCHAR(20)     NOT NULL,
EMP_CITY       VARCHAR(15)     NOT NULL,
EMP_ST         CHAR(2)         NOT NULL,
EMP_ZIP        INTEGER(5)       NOT NULL,
EMP_PHONE      INTEGER(10)      NULL,
EMP_PAGER      INTEGER(10)      NULL)
STORAGE
    (INITIAL     20M
     NEXT        1M );

In some implementations, there are several options available in the STORAGE clause. INITIAL allocates a set amount of space in bytes, kilobytes, and so on, for the initial amount of space to be used by a table. The NEXT part of the STORAGE identifies the amount of additional space that should be allocated to the table if it should grow beyond the space allocated for the initial allocation. You will find that there are other options available with the STORAGE clause, and remember that these options vary from implementation to implementation. If the STORAGE clause is omitted from most major implementations, there are default storage parameters invoked, which may not be the best for the application. Default storage values are set by the DBA. If default storage values are not set by the DBA, then the default storage values, which are usually very low, are set by the database itself.

Notice the neatness of the CREATE TABLE statement. This is for ease of reading and error resolution. Indentation has been used to help.

Naming Conventions

When selecting names for objects, specifically tables and columns, the name should reflect the data that is to be stored. For example, the name for a table pertaining to employee information could be named EMPLOYEE_TBL. Names for columns should follow the same logic. When storing an employee's phone number, an obvious name for that column would be PHONE_NUMBER.

The ALTER TABLE Command

A table can be modified through the use of the ALTER TABLE command after that table's creation. You can add column(s), drop column(s), change column definitions, add and drop constraints, and, in some implementations, modify table STORAGE values. The standard syntax for the ALTER TABLE command follows:

   syntax_icon.gif
ALTER TABLE TABLE_NAME [MODIFY] [COLUMN COLUMN_NAME][DATATYPE|NULL NOT NULL]
[RESTRICT|CASCADE]
                       [DROP]   [CONSTRAINT CONSTRAINT_NAME]
                       [ADD]    [COLUMN] COLUMN DEFINITION

Modifying Elements of a Table

newterm_icon.gif

The attributes of a column refer to the rules and behavior of data in a column. You can modify the attributes of a column with the ALTER TABLE command. The word attributes here refers to the following:

  • The data type of a column
  • The length, precision, or scale of a column
  • Whether the column can contain NULL values

The following example uses the ALTER TABLE command on EMPLOYEE_TBL to modify the attributes of the column EMP_ID:

   mysql_icon.gif
   input_icon.gif

   ALTER TABLE EMPLOYEE_TBL MODIFY (EMP_ID VARCHAR (10));

The MySQL version of the previous ALTER TABLE statement would appear as follows:

ALTER TABLE EMPLOYEE_TBL CHANGE 
EMP_ID EMP_ID VARCHAR(10);
output_icon.gif
Table altered.

The column was already defined as data type VARCHAR2 (a varying-length character), but you increased the maximum length from 9 to 10.

Adding Mandatory Columns to a Table

One of the basic rules for adding columns to an existing table is that the column you are adding cannot be defined as NOT NULL if data currently exists in the table. NOT NULL means that a column must contain some value for every row of data in the table. So, if you are adding a column defined as NOT NULL, you are contradicting the NOT NULL constraint right off the bat if the preexisting rows of data in the table do not have values for the new column.

There is, however, a way to add a mandatory column to a table:

  1. Add the column and define it as NULL (the column does not have to contain a value).
  2. Insert a value into the new column for every row of data in the table.
  3. After ensuring that the column contains a value for every row of data in the table, you can alter the table to change the column's attribute to NOT NULL.

Modifying Columns

There are many things to take into consideration when modifying existing columns of a table.

Common rules for modifying columns:

  • The length of a column can be increased to the maximum length of the given data type.
  • The length of a column can be decreased only if the largest value for that column in the table is less than or equal to the new length of the column.
  • The number of digits for a number data type can always be increased.
  • The number of digits for a number data type can be decreased only if the value with the most number of digits for that column is less than or equal to the new number of digits specified for the column.
  • The number of decimal places for a number data type can either be increased or decreased.
  • The data type of a column can normally be changed.

Some implementations may actually restrict you from using certain ALTER TABLE options. For example, you may not be allowed to drop columns from a table. To do this, you would have to drop the table itself, and then rebuild the table with the desired columns. You could run into problems by dropping a column in one table that is dependent on a column in another table, or a column that is referenced by a column in another table. Be sure to refer to your specific implementation documentation.

Creating a Table from an Existing Table

A copy of an existing table can be created using a combination of the CREATE TABLE statement and the SELECT statement. The new table has the same column definitions. All columns or specific columns can be selected. New columns that are created via functions or a combination of columns automatically assume the size necessary to hold the data. The basic syntax for creating a table from another table is as follows:

   syntax_icon.gif
CREATE TABLE NEW_TABLE_NAME AS
SELECT [ *|COLUMN1, COLUMN2 ]
FROM TABLE_NAME
[ WHERE ]

Notice some new keywords in the syntax, particularly the SELECT keyword. SELECT is a database query, and is discussed in more detail later. However, it is important to know that you can create a table based on the results from a query.

First, we do a simple query to view the data in the PRODUCTS_TBL table.

   input_icon.gif

   SELECT * FROM PRODUCTS_TBL;

   output_icon.gif
PROD_ID    PROD_DESC                      COST
---------- ----------------------------- ------
11235      WITCHES COSTUME               29.99
222        PLASTIC PUMPKIN 18 INCH        7.75
13         FALSE PARAFFIN TEETH           1.1
90         LIGHTED LANTERNS              14.5
15         ASSORTED COSTUMES             10
9          CANDY CORN                     1.35
6          PUMPKIN CANDY                  1.45
87         PLASTIC SPIDERS                1.05
119        ASSORTED MASKS                 4.95

Next, create a table called PRODUCTS_TMP based on the previous query:

   input_icon.gif

   CREATE TABLE PRODUCTS_TMP AS

   SELECT * FROM PRODUCTS_TBL;

   output_icon.gif
Table created.

Now, if you run a query on the PRODUCTS_TMP table, your results appear the same as if you had selected data from the original table.

   input_icon.gif

   SELECT *

   FROM PRODUCTS_TMP;

   output_icon.gif
PROD_ID    PROD_DESC                      COST
---------- ----------------------------- ------
11235      WITCHES COSTUME               29.99
222        PLASTIC PUMPKIN 18 INCH        7.75
13         FALSE PARAFFIN TEETH           1.1
90         LIGHTED LANTERNS              14.5
15         ASSORTED COSTUMES             10
9          CANDY CORN                     1.35
6          PUMPKIN CANDY                  1.45
87         PLASTIC SPIDERS                1.05
119        ASSORTED MASKS                 4.95

Dropping Tables

Dropping a table is actually one of the easiest things to do. When the RESTRICT option is used and the table is referenced by a view or constraint, the DROP statement returns an error. When the CASCADE option is used, the drop succeeds and all referencing views and constraints are dropped. The syntax to drop a table follows:

   syntax_icon.gif
DROP TABLE TABLE_NAME [ RESTRICT|CASCADE ]

In the following example, you drop the table that you just created:

   input_icon.gif

   DROP TABLE PRODUCTS.TMP;

   output_icon.gif
Table dropped.

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Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020