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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

Formatting Your SQL Statement

Formatting your SQL statement sounds like an obvious statement; as obvious as it may sound, it is worth mentioning. There are several things that a newcomer to SQL will probably not take into consideration when building a SQL statement. The following sections discuss the listed considerations; some are common sense, others are not so obvious:

  • Formatting SQL statements for readability
  • The order of tables in the FROM clause
  • The placement of the most restrictive conditions in the WHERE clause
  • The placement of join conditions in the WHERE clause

Formatting a Statement for Readability

Formatting a SQL statement for readability is pretty obvious, but many SQL statements have not been written neatly. Although the neatness of a statement does not affect the actual performance (the database does not care how neat the statement appears), careful formatting is the first step in tuning a statement. When you look at a SQL statement with tuning intentions, making the statement readable is always the first thing to do. How can you determine whether the statement is written well if it is difficult to read?

Some basic rules for making a statement readable include:

  • Always begin a new line with each clause in the statement— For example, place the FROM clause on a separate line from the SELECT clause. Place the WHERE clause on a separate line from the FROM clause, and so on.
  • Use tabs or spaces for indentation when arguments of a clause in the statement exceed one line.
  • Use tabs and spaces consistently.
  • Use table aliases when multiple tables are used in the statement— The use of the full table name to qualify each column in the statement quickly clutters the statement and makes reading it difficult.
  • Use remarks sparingly in SQL statements if they are available within your specific implementation— Remarks are great for documentation, but too many of them clutter a statement.
  • Begin a new line with each column name in the SELECT clause if many columns are being selected.
  • Begin a new line with each table name in the FROM clause if many tables are being used.
  • Begin a new line with each condition of the WHERE clause— You can easily see all conditions of the statement and the order in which they are used.

The following is an example of an unreadable statement:

   input_icon.gif

   SELECT CUSTOMER_TBL.CUST_ID, CUSTOMER_TBL.CUST_NAME,

   CUSTOMER_TBL.CUST_PHONE, ORDERS_TBL.ORD_NUM, ORDERS_TBL.QTY

   FROM CUSTOMER_TBL, ORDERS_TBL

   WHERE CUSTOMER_TBL.CUST_ID = ORDERS_TBL.CUST_ID

   AND ORDERS_TBL.QTY > 1 AND CUSTOMER_TBL.CUST_NAME LIKE 'G%'

   ORDER BY CUSTOMER_TBL.CUST_NAME;

   output_icon.gif
CUST_ID    CUST_NAME                      CUST_PHONE ORD_NUM           QTY
---------- ------------------------------ ---------- ----------------- ---
287        GAVINS PLACE                   3172719991 18D778             10

1 row selected.

The following is an example of a reformatted statement for improved readability:

   input_icon.gif

   SELECT C.CUST_ID,
       
   C.CUST_NAME,
       
   C.CUST_PHONE,
       
   O.ORD_NUM,
       
   O.QTY

   FROM ORDERS_TBL O,
     
   CUSTOMER_TBL C

   WHERE O.CUST_ID = C.CUST_ID
  
   AND O.QTY > 1
  
   AND C.CUST_NAME LIKE 'G%'

   ORDER BY 2;

   output_icon.gif
CUST_ID    CUST_NAME                      CUST_PHONE ORD_NUM           QTY
---------- ------------------------------ ---------- ----------------- ---
287        GAVINS PLACE                   3172719991 18D778             10

1 row selected.

Both statements are exactly the same, but the second statement is much more readable. The second statement has been greatly simplified by using table aliases, which have been defined in the query's FROM clause. Spacing has been used to align the elements of each clause, making each clause stand out.

Again, making a statement more readable does not directly improve its performance, but it assists you in making modifications and debugging a lengthy and otherwise complex statement. Now you can easily identify the columns being selected, the tables being used, the table joins being performed, and the conditions being placed on the query.

Proper Arrangement of Tables in the FROM Clause

The arrangement or order of tables in the FROM clause may make a difference, depending on how the optimizer reads the SQL statement. For example, it may be more beneficial to list the smaller tables first and the larger tables last. Some users with lots of experience have found that listing the larger tables last in the FROM clause proves to be more efficient.

The following is an example FROM clause:

FROM SMALLEST TABLE, 
     LARGEST TABLE

Proper Order of Join Conditions

As you learned in Hour 13, "Joining Tables in Queries," most joins use a BASE TABLE to link tables that have one or more common columns on which to join. The BASE TABLE is the main table that most or all tables are joined to in a query. The column from the BASE TABLE is normally placed on the right side of a join operation in the WHERE clause. The tables being joined to the BASE TABLE are normally in order from smallest to largest, similar to the tables listed in the FROM clause.

Should there not be a BASE TABLE, the tables should be listed from smallest to largest, with the largest tables on the right side of the join operation in the WHERE clause. The join conditions should be in the first position(s) of the WHERE clause followed by the filter clause(s), as shown in the following:

FROM TABLE1,                                 Smallest Table 
     TABLE2,                                 to
     TABLE3                                  Largest Table, also BASE TABLE
WHERE TABLE1.COLUMN = TABLE3.COLUMN          Join condition
  AND TABLE2.COLUMN = TABLE3.COLUMN          Join condition
[ AND CONDITION1 ]                           Filter condition
[ AND CONDITION2 ]                           Filter condition

In this example, TABLE3 is used as the BASE TABLE. TABLE1 and TABLE2 are joined to TABLE3 for both simplicity and proven efficiency.

The Most Restrictive Condition

The most restrictive condition is typically the driving factor in achieving optimal performance for a SQL query. What is the most restrictive condition? The condition in the WHERE clause of a statement that returns the fewest rows of data. Conversely, the least restrictive condition is the condition in a statement that returns the most rows of data. This hour is concerned with the most restrictive condition simply because it is this condition that filters the data that is to be returned by the query the most.

It should be your goal for the SQL optimizer to evaluate the most restrictive condition first because a smaller subset of data is returned by the condition, thus reducing the query's overhead. The effective placement of the most restrictive condition in the query requires knowledge of how the optimizer operates. The optimizers, in some cases, seem to read from the bottom of the WHERE clause up. Therefore, you would want to place the most restrictive condition last in the WHERE clause, which is the condition that is first read by the optimizer.

FROM TABLE1,                              Smallest Table 
     TABLE2,                              to
     TABLE3                               Largest Table, also BASE TABLE
WHERE TABLE1.COLUMN = TABLE3.COLUMN       Join condition
  AND TABLE2.COLUMN = TABLE3.COLUMN       Join condition
[ AND CONDITION1 ]                        Least restrictive
[ AND CONDITION2 ]                        Most restrictive

The following is an example using a phony table:

Table:

TEST

Row count:

95,867

Conditions:

WHERE LAST_NAME = 'SMITH'

returns 2,000 rows

WHERE CITY = 'INDIANAPOLIS'

returns 30,000 rows

Most restrictive condition is:

WHERE LAST_NAME = 'SMITH'

QUERY1: 
input_icon.gif

   SELECT COUNT(*)

   FROM TEST

   WHERE LAST_NAME = 'SMITH'
  
   AND CITY = 'INDIANAPOLIS';

   output_icon.gif
  COUNT(*)
----------
     1,024
QUERY2: 
input_icon.gif

   SELECT COUNT(*)

   FROM TEST

   WHERE CITY = 'INDIANAPOLIS'
  
   AND LAST_NAME = 'SMITH';

   output_icon.gif
  COUNT(*)
----------
     1,024

Suppose that QUERY1 completed in 20 seconds, whereas QUERY2 completed in 10 seconds. Because QUERY2 returned faster results and the most restrictive condition was listed last in the WHERE clause, it would be safe to assume that the optimizer reads the WHERE clause from the bottom up.

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