Structured Query Language (SQL) Part A. KSE 521 Topic 10 Mun Yi

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1 Structured Query Language (SQL) Part A KSE 521 Topic 10 Mun Yi 1

2 Agenda SQL Background Cape Codd Outdoor Sports SQL Select Statement Syntax Joining Tables 2

3 Structured Query Language Structured Query Language (SQL) was developed by the IBM Corporation in the late 1970s. SQL was endorsed as a United States national standard by the American National Standards Institute (ANSI) in 1992 [SQL-92]. SQL is ubiquitous in enterprise-class DBMS products. 3

4 SQL DDL and DML SQL statements can be divided into two categories: Data definition language (DDL) statements Used for creating tables, relationships, and other structures. Data manipulation language (DML) statements. Used for data retrieval and data modification 4

5 Cape Codd Retail Sales Structure Cape Codd Outdoor Sports is a fictitious company based on an actual outdoor retail equipment vendor. 5

6 Cape Codd Retail Sales Data Extraction The Cape Codd marketing department needs an analysis of in-store sales. The entire database is not needed for this, only an extraction of retail sales data. The data is extracted by the IS department from the operational database into a separate, off-line database for use by the marketing department. Three tables are used: RETAIL_ORDER, ORDER_ITEM, and SKU_DATA (SKU = Stock Keeping Unit). The extracted data is converted as necessary: Into a different DBMS MS SQL Server Into different columns OrderDate becomes OrderMonth and OrderYear 6

7 Extracted Retail Sales Data Format 7

8 Retail Sales Extract Tables 8

9 The SQL SELECT Statement The fundamental framework for SQL query states is the SQL SELECT statement: SELECT FROM WHERE {ColumnName(s)} {TableName(s)} {Conditions} All SQL statements end with a semicolon (;). 9

10 Specific Columns on One Table SELECT FROM Department, Buyer SKU_DATA; 10

11 Specifying Column Order SELECT FROM Buyer, Department SKU_DATA; 11

12 The DISTINCT Keyword SELECT FROM DISTINCT Buyer, Department SKU_DATA; 12

13 Selecting All Columns: The Asterisk (*) Keyword SELECT * FROM SKU_DATA; 13

14 Specific Rows from One Table SELECT * FROM SKU_DATA WHERE Department = 'Water Sports'; NOTE: SQL wants a plain ASCII single quote: 14

15 Specific Columns and Rows from One Table SELECT FROM WHERE SKU_Description, Buyer SKU_DATA Department = 'Climbing'; 15

16 Sorting the Results: ORDER BY SELECT * FROM ORDER_ITEM ORDER BY OrderNumber, Price; 16

17 Sort Order: Ascending and Descending SELECT * FROM ORDER_ITEM ORDER BY Price DESC, OrderNumber; NOTE: The default sort order is ASC does not have to be specified. 17

18 WHERE Clause Options: AND SELECT * FROM SKU_DATA WHERE Department = 'Water Sports' AND Buyer = 'Nancy Meyers'; 18

19 WHERE Clause Options: OR SELECT * FROM SKU_DATA WHERE Department = 'Camping' OR Department = 'Climbing'; 19

20 WHERE Clause Options: IN SELECT * FROM SKU_DATA WHEREBuyer IN ('Nancy Meyers', 'Cindy Lo', 'Jerry Martin'); 20

21 WHERE Clause Options: NOT IN SELECT * FROM SKU_DATA WHEREBuyer NOT IN ('Nancy Meyers', 'Cindy Lo', 'Jerry Martin'); 21

22 WHERE Clause Options: Ranges with BETWEEN SELECT * FROM ORDER_ITEM WHERE ExtendedPrice BETWEEN 100 AND 200; 22

23 WHERE Clause Options: Ranges with Math Symbols SELECT * FROM ORDER_ITEM WHERE ExtendedPrice >= 100 AND ExtendedPrice <= 200; 23

24 WHERE Clause Options: LIKE and Wildcards The SQL keyword LIKE can be combined with wildcard symbols: SQL 92 Standard (SQL Server, Oracle, Teradata): _ = Exactly one character % = Any set of zero or more characters MS Access (based on MS DOS)? * = Exactly one character = Any set of one or more characters 24

25 WHERE Clause Options: LIKE and Wildcards (Continued) SELECT * FROM SKU_DATA WHERE Buyer LIKE 'Pete%'; 25

26 WHERE Clause Options: LIKE and Wildcards (Continued) SELECT * FROM SKU_DATA WHERE SKU_Description LIKE '%Tent%'; 26

27 WHERE Clause Options: LIKE and Wildcards SELECT * FROM SKU_DATA WHERE SKU LIKE '%2 '; 27

28 SQL Built-in Functions There are five SQL Built-in Functions: COUNT SUM AVG MIN MAX You cannot combine a table column name with a built-in function without GROUP BY. You cannot use a built-in function in a WHERE clause. 28

29 SQL Built-in Functions (Continued) SELECT SUM (ExtendedPrice) AS Order3000Sum FROM ORDER_ITEM WHERE OrderNumber = 3000; 29

30 SQL Built-in Functions (Continued) SELECT FROM SUM (ExtendedPrice) AS OrderItemSum, AVG (ExtendedPrice) AS OrderItemAvg, MIN (ExtendedPrice) AS OrderItemMin, MAX (ExtendedPrice) AS OrderItemMax ORDER_ITEM; 30

31 SQL Built-in Functions (Continued) SELECT FROM COUNT(*) AS NumRows ORDER_ITEM; 31

32 SQL Built-in Functions (Continued) SELECT FROM COUNT (DISTINCT Department) AS DeptCount SKU_DATA; 32

33 Arithmetic in SELECT Statements SELECT FROM Quantity * Price AS EP, ExtendedPrice ORDER_ITEM; 33

34 The SQL keyword GROUP BY SELECT FROM GROUP BY Department, Buyer, COUNT(*) AS Dept_Buyer_SKU_Count SKU_DATA Department, Buyer; 34

35 The SQL keyword GROUP BY (Continued) In general, place WHERE before GROUP BY. Some DBMS products do not require that placement, but to be safe, always put WHERE before GROUP BY. The HAVING operator restricts the groups that are presented in the result. There is an ambiguity in statements that include both WHERE and HAVING clauses. The results can vary, so to eliminate this ambiguity SQL always applies WHERE before HAVING. When using GROUP BY, only the column(s) in the GROUP BY expression and the SQL built-in functions can be used in the SELECT expression. 35

36 The SQL keyword GROUP BY (Continued) SELECT Department, COUNT(*) AS Dept_SKU_Count FROM SKU_DATA WHERE SKU <> GROUP BY Department HAVING COUNT (*) > 1 ORDER BY Dept_SKU_Count; 36

37 The SQL keyword GROUP BY (Continued) Any SQL built-in function can be used in the having clause. For example, SELECT COUNT(*) AS SKU_Count, SUM(Price) AS TotalRev, SKU FROM ORDER_ITEM GROUP BY SKU HAVING SUM(Price) = 100; 37

38 Querying Multiple Tables: Subqueries SELECT FROM WHERE SUM (ExtendedPrice) AS Revenue ORDER_ITEM SKU IN (SELECT SKU FROM SKU_DATA WHERE Department = 'Water Sports'); Note: The second SELECT statement is a subquery. 38

39 Querying Multiple Tables: Subqueries (Continued) SELECT FROM WHERE Buyer SKU_DATA SKU IN (SELECT SKU FROM WHERE ORDER_ITEM OrderNumber IN (SELECT OrderNumber FROM RETAIL_ORDER WHERE OrderMonth = 'January' AND OrderYear = 2004)); 39

40 Querying Multiple Tables: Joins SELECT FROM WHERE Buyer, ExtendedPrice SKU_DATA, ORDER_ITEM SKU_DATA.SKU = ORDER_ITEM.SKU; 40

41 Querying Multiple Tables: Joins (Continued) SELECT FROM WHERE GROUP BY ORDER BY Buyer, SUM(ExtendedPrice) AS BuyerRevenue SKU_DATA, ORDER_ITEM SKU_DATA.SKU = ORDER_ITEM.SKU Buyer BuyerRevenue DESC; 41

42 Querying Multiple Tables: Joins (Continued) SELECT Buyer, ExtendedPrice, OrderMonth FROM SKU_DATA, ORDER_ITEM, RETAIL_ORDER WHERE SKU_DATA.SKU = ORDER_ITEM.SKU AND ORDER_ITEM.OrderNumber = RETAIL_ORDER.OrderNumber; 42

43 Subqueries versus Joins Subqueries and joins both process multiple tables. A subquery can only be used to retrieve data from the top table. A join can be used to obtain data from any number of tables, including the top table of the subquery. 43

Database Processing: Fundamentals, Design, and Implementation

David M. Kroenke s Database Processing: Fundamentals, Design, and Implementation Chapter Two: Introduction to Structured Query Language Part One 2-1 Structured Query Language Structured Query Language