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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

Compound Query Operators

The compound query operators vary among database vendors. The ANSI standard includes the UNION, UNION ALL, EXCEPT, and INTERSECT operators, all of which are discussed in the following sections.

The UNION Operator

The UNION operator is used to combine the results of two or more SELECT statements without returning any duplicate rows. In other words, if a row of output exists in the results of one query, the same row is not returned, even though it exists in the second query that combined with a UNION operator. To use UNION, each SELECT must have the same number of columns selected, the same number of column expressions, the same data type, and have them in the same order—but they do not have to be the same length.

The syntax is as follows:

   syntax_icon.gif
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]
UNION
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]

Look at the following example:

   mysql_icon.gif
SELECT EMP_ID FROM EMPLOYEE_TBL
UNION
SELECT EMP_ID FROM EMPLOYEE_PAY_TBL;

analysis_icon.gif

Those employee IDs that are in both tables appear only once in the results.

This hour's examples begin with a simple SELECT from two tables:

   input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TBL;

   output_icon.gif
PROD_DESC
-----------------------
WITCHES COSTUME
PLASTIC PUMPKIN 18 INCH
FALSE PARAFFIN TEETH
LIGHTED LANTERNS
ASSORTED COSTUMES
CANDY CORN
PUMPKIN CANDY
PLASTIC SPIDERS
ASSORTED MASKS
KEY CHAIN
OAK BOOKSHELF

11 rows selected.
input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TMP;

   output_icon.gif
PROD_DESC
--------------------
WITCHES COSTUME
PLASTIC PUMPKIN 18 INCH
FALSE PARAFFIN TEETH
LIGHTED LANTERNS
ASSORTED COSTUMES
CANDY CORN
PUMPKIN CANDY
PLASTIC SPIDERS
ASSORTED MASKS
KEY CHAIN
OAK BOOKSHELF


11 rows selected.

Now, combine the same two queries with the UNION operator, making a compound query.

   mysql_icon.gif
   input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TBL

   UNION

   SELECT PROD_DESC FROM PRODUCTS_TMP;

   output_icon.gif
PROD_DESC
-----------------------
ASSORTED COSTUMES
ASSORTED MASKS
CANDY CORN
FALSE PARAFFIN TEETH
LIGHTED LANTERNS
PLASTIC PUMPKIN 18 INCH
PLASTIC SPIDERS
PUMPKIN CANDY
WITCHES COSTUME
KEY CHAIN
OAK BOOKSHELF

11 rows selected.

In the first query, nine rows of data were returned, and six rows of data were returned from the second query. Nine rows of data are returned when the UNION operator combines the two queries. Only nine rows are returned because duplicate rows of data are not returned when using the UNION operator.

The next example shows an example of combining two unrelated queries with the UNION operator:

   mysql_icon.gif
   input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TBL

   UNION

   SELECT LAST_NAME FROM EMPLOYEE_TBL;

   output_icon.gif
PROD_DESC
-----------------------
ASSORTED COSTUMES
ASSORTED MASKS
CANDY CORN
FALSE PARAFFIN TEETH
GLASS
KEY CHAIN
LIGHTED LANTERNS
OAK BOOKSHELF
PLASTIC PUMPKIN 18 INCH
PLASTIC SPIDERS
PLEW
PUMPKIN CANDY
SPURGEON
STEPHENS
WALLACE
WITCHES COSTUME

16 rows selected.

The PROD_DESC and LAST_NAME values are listed together, and the column heading taken is from the column name in the first query.

The UNION ALL Operator

The UNION ALL operator is used to combine the results of two SELECT statements including duplicate rows. The same rules that apply to UNION apply to the UNION ALL operator. The UNION and UNION ALL operators are the same, although one returns duplicate rows of data where the other does not.

The syntax is as follows:

   syntax_icon.gif
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]
UNION ALL
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]

Look at the following example:

   mysql_icon.gif
SELECT EMP_ID FROM EMPLOYEE_TBL
UNION ALL
SELECT EMP_ID FROM EMPLOYEE_PAY_TBL

analysis_icon.gif

The preceding SQL statement returns all employee IDs from both tables and shows duplicates.

The following is the same compound query in the previous section with the UNION ALL operator:

   mysql_icon.gif
   input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TBL

   UNION ALL

   SELECT PROD_DESC FROM PRODUCTS_TMP;

   output_icon.gif
PROD_DESC
-----------------------
WITCHES COSTUME
PLASTIC PUMPKIN 18 INCH
FALSE PARAFFIN TEETH
LIGHTED LANTERNS
ASSORTED COSTUMES
CANDY CORN
PUMPKIN CANDY
PLASTIC SPIDERS
ASSORTED MASKS
KEY CHAIN
OAK BOOKSHELF
WITCHES COSTUME
PLASTIC PUMPKIN 18 INCH
FALSE PARAFFIN TEETH
LIGHTED LANTERNS
ASSORTED COSTUMES
CANDY CORN
PUMPKIN CANDY
PLASTIC SPIDERS
ASSORTED MASKS
KEY CHAIN
OAK BOOKSHELF

22 rows selected.

Notice that there were 22 rows returned in this query (9+6) because duplicate records are retrieved with the UNION ALL operator.

The INTERSECT Operator

The INTERSECT operator is used to combine two SELECT statements, but returns only rows from the first SELECT statement that are identical to a row in the second SELECT statement. Just as with the UNION operator, the same rules apply when using the INTERSECT operator.

The syntax is as follows:

   syntax_icon.gif
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]
INTERSECT
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]

Look at the following example:

   mysql_icon.gif
SELECT CUST_ID FROM CUSTOMER_TBL
INTERSECT
SELECT CUST_ID FROM ORDERS_TBL;

analysis_icon.gif

The preceding SQL statement returns the customer identification for those customers who have placed an order.

The following example illustrates the INTERSECT using the two original queries in this hour:

   mysql_icon.gif
   input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TBL

   INTERSECT

   SELECT PROD_DESC FROM PRODUCTS_TMP;

   output_icon.gif
PROD_DESC
--------------------
ASSORTED COSTUMES
ASSORTED MASKS
CANDY CORN
FALSE PARAFFIN TEETH
KEY CHAIN
LIGHTED LANTERNS
OAK BOOKSHELF
PLASTIC PUMPKIN 18 INCH
PLASTIC SPIDERS
PUMPKIN CANDY
WITCHES COSTUME

11 rows selected.

Only eleven rows are returned because only eleven rows were identical between the output of the two single queries.

The EXCEPT Operator

The EXCEPT operator combines two SELECT statements and returns rows from the first SELECT statement that are not returned by the second SELECT statement. Once again, the same rules that apply to the UNION operator also apply to the EXCEPT operator.

The syntax is as follows:

   syntax_icon.gif
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]
EXCEPT
SELECT COLUMN1 [, COLUMN2 ]
FROM TABLE1 [, TABLE2 ]
[ WHERE ]

Study the following example:

   mysql_icon.gif
   input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TBL

   EXCEPT

   SELECT PROD_DESC FROM PRODUCTS_TMP;

   output_icon.gif
PROD_DESC
-----------------------
PLASTIC PUMPKIN 18 INCH
PLASTIC SPIDERS
PUMPKIN CANDY

3 rows selected.

According to the results, there were three rows of data returned by the first query that were not returned by the second query.

   mysql_icon.gif
   input_icon.gif

   SELECT PROD_DESC FROM PRODUCTS_TBL

   MINUS

   SELECT PROD_DESC FROM PRODUCTS_TMP;

   output_icon.gif
PROD_DESC
-----------------------
PLASTIC PUMPKIN 18 INCH
PLASTIC SPIDERS
PUMPKIN CANDY

3 rows selected.

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