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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

The GROUP BY Clause

The GROUP BY clause is used in collaboration with the SELECT statement to arrange identical data into groups. The GROUP BY clause follows the WHERE clause in a SELECT statement and precedes the ORDER BY clause.

The position of the GROUP BY clause in a query is as follows:

SELECT 
FROM
WHERE
GROUP BY
ORDER BY

The GROUP BY clause must follow the conditions in the WHERE clause and must precede the ORDER BY clause if one is used.

The following is the SELECT statement's syntax, including the GROUP BY clause:

   syntax_icon.gif
SELECT COLUMN1, COLUMN2
FROM TABLE1, TABLE2
WHERE CONDITIONS
GROUP BY COLUMN1, COLUMN2
ORDER BY COLUMN1, COLUMN2

The following sections give examples and explanations of the GROUP BY clause's use in a variety of situations.

Grouping Selected Data

Grouping data is a simple process. The selected columns (the column list following the SELECT keyword in a query) are the columns that can be referenced in the GROUP BY clause. If a column is not found in the SELECT statement, it cannot be used in the GROUP BY clause. This is logical if you think about it—how can you group data on a report if the data is not displayed?

If the column name has been qualified, the qualified name must go into the GROUP BY clause. The column name can also be represented by a number, which is discussed later in this hour. When grouping the data, the order of columns grouped does not have to match the column order in the SELECT clause.

Group Functions

Typical group functions—those that are used with the GROUP BY clause to arrange data in groups—include AVG, MAX, MIN, SUM, and COUNT. These are the aggregate functions that you learned about during Hour 9, "Summarizing Data Results from a Query." Remember that the aggregate functions were used for single values in Hour 9; now, you use the aggregate functions for group values.

Creating Groups and Using Aggregate Functions

There are conditions that the SELECT clause has that must be met when using GROUP BY. Specifically, whatever columns are selected must appear in the GROUP BY clause, except for any aggregate values. The columns in the GROUP BY clause do not necessarily have to be in the same order as they appear in the SELECT clause. Should the columns in the SELECT clause be qualified, the qualified names of the columns must be used in the GROUP BY clause. The following are some examples of syntax for the GROUP BY clause:

Example

SELECT EMP_ID, CITY

FROM EMPLOYEE_TBL

GROUP BY CITY, EMP_ID;

analysis_icon.gif

The SQL statement selects the EMP_ID and the CITY from the EMPLOYEE_TBL and groups the data returned by the CITY and then EMP_ID.

Example

SELECT EMP_ID, SUM(SALARY)

FROM EMPLOYEE_PAY_TBL

GROUP BY SALARY, EMP_ID;

analysis_icon.gif

This SQL statement returns the EMP_ID and the total of the salary groups, as well as groups both the salaries and employee IDs.

Example

SELECT SUM(SALARY)

FROM EMPLOYEE_PAY_TBL;

analysis_icon.gif

This SQL statement returns the total of all the salaries from the EMPLOYEE_PAY_TBL.

Example

SELECT SUM(SALARY)

FROM EMPLOYEE_PAY_TBL

GROUP BY SALARY;

analysis_icon.gif

This SQL statement returns the totals for the different groups of salaries.

Practical examples using real data follow. In this first example, you can see that there are three distinct cities in the EMPLOYEE_TBL table.

   input_icon.gif

   SELECT CITY

   FROM EMPLOYEE_TBL;

   output_icon.gif
CITY
-------------
GREENWOOD
INDIANAPOLIS
WHITELAND
INDIANAPOLIS
INDIANAPOLIS
INDIANAPOLIS

6 rows selected.

In the following example, you select the city and a count of all records for each city. You see a count on each of the three distinct cities because you are using a GROUP BY clause.

   input_icon.gif

   SELECT CITY, COUNT(*)

   FROM EMPLOYEE_TBL

   GROUP BY CITY;

   output_icon.gif
CITY           COUNT(*)
-------------- --------
GREENWOOD             1
INDIANAPOLIS          4
WHITELAND             1

3 rows selected.

The following is a query from a temporary table created based on EMPLOYEE_TBL and EMPLOYEE_PAY_TBL. You will soon learn how to join two tables for a query.

   input_icon.gif

   SELECT *

   FROM EMP_PAY_TMP;

   output_icon.gif
CITY         LAST_NAM FIRST_NA   PAY_RATE     SALARY
------------ -------- ---------- ------------ ------
GREENWOOD    STEPHENS TINA                     30000
INDIANAPOLIS PLEW     LINDA         14.75
WHITELAND    GLASS    BRANDON                  40000
INDIANAPOLIS GLASS    JACOB                    20000
INDIANAPOLIS WALLACE  MARIAH           11
INDIANAPOLIS SPURGEON TIFFANY          15

6 rows selected.

In the following example, you retrieve the average pay rate and salary on each distinct city using the aggregate function AVG. There is no average pay rate for GREENWOOD or WHITELAND because no employees living in those cities are paid hourly.

   input_icon.gif

   SELECT CITY, AVG(PAY_RATE), AVG(SALARY)

   FROM EMP_PAY_TMP

   GROUP BY CITY;

   output_icon.gif
CITY         AVG(PAY_RATE) AVG(SALARY)
------------ ------------- -----------
GREENWOOD                        30000
INDIANAPOLIS    13.5833333       20000
WHITELAND                        40000

3 rows selected.

In the next example, you combine the use of multiple components in a query to return grouped data. You still want to see the average pay rate and salary, but only for INDIANAPOLIS and WHITELAND. You group the data by CITY, of which you have no choice because you are using aggregate functions on the other columns. Lastly, you want to order the report by 2, and then 3, which is the average pay rate and then average salary, respectively. Study the following details and output:

   input_icon.gif

   SELECT CITY, AVG(PAY_RATE), AVG(SALARY)

   FROM EMP_PAY_TMP

   WHERE CITY IN ('INDIANAPOLIS','WHITELAND')

   GROUP BY CITY

   ORDER BY 2,3;

   output_icon.gif
CITY         AVG(PAY_RATE) AVG(SALARY)
------------ ------------- -----------
INDIANAPOLIS    13.5833333       20000
WHITELAND                        40000

Values are sorted before NULL values; therefore, the record for INDIANAPOLIS was displayed first. GREENWOOD was not selected, but if it were, its record would have been displayed before WHITELAND's record because GREENWOOD's average salary is $30,000 (the second sort in the ORDER BY clause was on average salary).

The last example in this section shows the use of the MAX and MIN aggregate functions with the GROUP BY clause.

   input_icon.gif

   SELECT CITY, MAX(PAY_RATE), MIN(SALARY)

   FROM EMP_PAY_TMP

   GROUP BY CITY;

   output_icon.gif
CITY         MAX(PAY_RATE) MIN(SALARY)
------------ ------------- -----------
GREENWOOD                        30000
INDIANAPOLIS            15       20000
WHITELAND                        40000

3 rows selected.

Representing Column Names with Numbers

Unlike the ORDER BY clause, the GROUP BY clause cannot be ordered by using an integer to represent the column name except when using a UNION and the column names are different. The following is an example of representing column names with numbers:

   mysql_icon.gif
SELECT EMP_ID, SUM(SALARY)
FROM EMPLOYEE_PAY_TBL
UNION
SELECT EMP_ID, SUM(PAY_RATE)
FROM EMPLOYEE_PAY_TBL
GROUP BY 2, 1;

This SQL statement returns the employee ID and the group totals for the salaries. When using the UNION operator, the results of the two SELECT statements are merged into one result set. The GROUP BY is performed on the entire result set. The order for the groupings is 2 representing salary, and 1 representing EMP_ID.

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