SQL and XQuery tutorial for IBM DB2, appendix: Appendix A

All the tables in the Aroma database and their relationships with each other

Pat Moffatt (pmoffatt@ca.ibm.com), Information Management Program Manager, IBM Academic Initiative, IBM

Pat Moffatt is the Information Management Program Manager for the IBM Academic Initiative. Through the Academic Initiative program, she ensures that appropriate Information Management resources are made available to help faculty integrate Information Management software into their curriculum. To learn more about this program, visit www.ibm.com/university/data.

Bruce Creighton (bcreight@ca.ibm.com), Skills Segment Planner, IBM

Bruce Creighton is a Skills Segment Planner in the Information Management Education Planning and Development department. In this role, he plans investment in educational content and balances the investment between areas where IBM can attain revenue and those where the requirement for skills development are important enough to provide free education.

Jessica Cao, Training Tools Developer, IBM

Jessica Cao is an Arts and Science and Computer Science student at McMaster University. She expects to complete her combined honours degree in April 2009. Jessica is working in IBM Toronto lab's DB2 Information Management Skills Channel Planning and Enablement Program to take advantage of her interest in programming, editing, and writing.

Summary: Appendix A describes all of the tables in the Aroma database, which consists of two schemas: a simple star schema for retail sales information and a multistar schema for purchasing information. This appendix belongs to the SQL & XQuery Tutorial for IBM DB2 series.

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Date: 31 Aug 2006
Level: Intermediate
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About this appendix

Appendix A describes all of the tables in the Aroma database, which consists of two schemas -- a simple star schema for retail sales information and a multistar schema for purchasing information.

Most of the examples in this article use the tables in the retail schema. The purchasing tables are used in a few examples that require a more flexible schema for adequate illustration.

Connect to a database

You need to connect to a database before you can use SQL statements to query or manipulate data. The CONNECT statement associates a database connection with a username.

Find out from your instructor the database name that you need to be connected to. For this series, the database name is aromadb.

To connect to the aromadb database, type the following command in the DB2 command line processor:

CONNECT TO aromadb USER userid USING password

Replace the userid and password with the user ID and password that you received from your instructor. If no user ID and password are required, simply use the following command:

CONNECT TO aromadb

The following message tells you that you have made a successful connection:

Database Connection Information
Database server      = DB2/NT 9.0.0
SQL authorization ID = USERID
Local database alias = AROMADB

Once you are connected, you can start using the database.

Aroma database: Retail schema

Most of the examples in this guide are based on data from the basic Aroma database, which tracks daily retail sales in stores owned by the Aroma Coffee and Tea Company. The Figure 1 illustrates this basic schema.

Figure 1. Basic schema

The crow's-feet in this diagram indicate a one-to-many relationship between the two tables. For example, each distinct value in the Perkey column of the Period table can occur only once in that table but many times in the Sales table.

Basic aroma schema

The following tables make up the basic Aroma database:

Table	Description
Period	Defines time intervals such as days, months, and years.
Class	Defines classes of products sold at retail stores.
Product	Defines individual products sold at retail stores, including bulk and packaged coffee and tea, and coffee machines.
Market	Defines the geographical markets of the business.
Store	Defines individual retail stores owned and operated by the Aroma Coffee and Tea Company.
Promotion	Defines the types, durations, and values of promotions run on different products.
Sales	Contains the sales figures for Aroma products during time periods at various stores.
Gold	Contains customers who have purchased promotion cards.

The Period, Class, Product, Market, Store, Promotion, and Gold tables are examples of typical business dimensions. They are small and contain descriptive data that is familiar to users.

The Sales table is a good example of a fact table. It contains thousands of rows, and its largely additive information is accessed in queries by joins to the dimension tables it references.

Sample data from the Class and Product tables

Query

SELECT * FROM aroma.class;

Result

Classkey	Class_Type	Class_Desc
1	Bulk_beans	Bulk coffee products
2	Bulk_tea	Bulk tea products
3	Bulk_spice	Bulk spices
4	Pkg_coffee	Individually packaged coffee products
5	Pkg_tea	Individually packaged tea products
6	Pkg_spice	Individually packaged spice products
7	Hardware	Coffee mugs, teapots, spice jars, espresso machines
8	Gifts	Samplers, gift boxes, and baskets
12	Clothing	T-shirts and caps

Query

SELECT * FROM aroma.product;

Result

Classkey	Prodkey	Prod_Name	Pkg_Type
1	0	Veracruzano	No pkg
1	1	Xalapa Lapa	No pkg
1	10	Colombiano	No pkg
1	11	Expresso XO	No pkg
1	12	La Antigua	No pkg
1	20	Lotta Latte	No pkg
1	21	Cafe Au Lait	No pkg
1	22	NA Lite	No pkg
1	30	Aroma Roma	No pkg
1	31	Demitasse Ms	No pkg
2	0	Darjeeling Number 1	No pkg
2	1	Darjeeling Special	No pkg
2	10	Assam Grade A	No pkg
...

Class and Product tables

The Product table describes the products defined in the Aroma database. The Class table describes the classes to which those products belong.

Column descriptions: Class table

Column Name	Contents
classkey	Integer that identifies exactly one row in the Class table. Classkey is the primary key.
class_type	Character string that identifies a group of products.
class_desc	Character string that describes a group of products.

Column Descriptions: Product table

Column Name	Contents
classkey	Foreign-key reference to the Class table.
prodkey	Integer that combines with the Classkey value to identify exactly one row in the Product table. Classkey/prodkey is a two-column primary key.
prod_name	Character string that identifies a product. The database contains 59 products. A fully populated database would have many more. Although some Aroma products have the same name, they belong to different classes and have different package types.
pkg_type	Character string that identifies the type of packaging for each product.

Sample data from the store and market tables

Query

SELECT * FROM aroma.market;

Result

Mktkey	HQ_City	HQ_State	District	Region
1	Atlanta	GA	Atlanta	South
2	Miami	FL	Atlanta	South
3	New Orleans	LA	New Orleans	South
4	Houston	TX	New Orleans	South
5	New York	NY	New York	North
...

Query

SELECT * FROM aroma.store;

Result

Storekey	Mktkey	Store_Type	Store_Name	Street	City	State	Zip
1	14	Small	Roasters, Los Gatos	1234 University Ave	Los Gatos	CA	95032
2	14	Large	San Jose Roasting Company	5678 Bascom Ave	San Jose	CA	95156
3	14	Medium	Cupertino Coffee Supply	987 DeAnza Blvd	Cupertino	CA	97865
4	3	Medium	Moulin Rouge Roasting	898 Main Street	New Orleans	LA	70125
5	10	Small	Moon Pennies	98675 University Ave	Detroit	MI	48209
6	9	Small	The Coffee Club	9865 Lakeshore Blvd	Chicago	IL	06060
...

Market and Store tables

The Store table defines the Aroma Coffee and Tea Company stores. The Market table describes the U.S. markets to which each store belongs. Each market is identified by a major metropolitan city. The Market table is an outboard table, like the Class table.

Column descriptions: Market table

Column Name	Contents
Mktkey	Integer that identifies exactly one row in the Market table. Mktkey is the primary key.
hq_city	Character string that identifies a city. The Market table defines 17 cities. A fully populated database could have thousands.
State	Character string that identifies a state.
District	Character string that identifies a district based on a major metropolitan city. A global database would contain countries and nations or other geographic dimensions.
Region	Character string that identifies a region. The Market table defines only four regions for the entire United States. A comprehensive database would include numerous regions and probably more districts within a region.

Column descriptions: Store table

Column Name	Contents
storekey	Integer that identifies exactly one row in the Store table. Storekey is the primary key.
Mktkey	Foreign-key reference to the Market table.
store_type	Character string that identifies stores by size.
store_name	Character string that identifies a store by name.
street, city, state, zip	Columns that identify the address of each store.

Sample data from the Period table

Query

SELECT * FROM aroma.period;

Result

Perkey	Date	Day	Week	Month	Qtr	Year
1	2004-01-01	TH	1	JAN	Q1_04	2004
2	2004-01-02	FR	1	JAN	Q1_04	2004
3	2004-01-03	SA	1	JAN	Q1_04	2004
4	2004-01-04	SU	2	JAN	Q1_04	2004
5	2004-01-05	MO	2	JAN	Q1_04	2004
6	2004-01-06	TU	2	JAN	Q1_04	2004
7	2004-01-07	WE	2	JAN	Q1_04	2004
8	2004-01-08	TH	2	JAN	Q1_04	2004
9	2004-01-09	FR	2	JAN	Q1_04	2004
10	2004-01-10	SA	2	JAN	Q1_04	2004
11	2004-01-11	SU	3	JAN	Q1_04	2004
12	2004-01-12	MO	3	JAN	Q1_04	2004
13	2004-01-13	TU	3	JAN	Q1_04	2004
14	2004-01-14	WE	3	JAN	Q1_04	2004
15	2004-01-15	TH	3	JAN	Q1_04	2004
16	2004-01-16	FR	3	JAN	Q1_04	2004
17	2004-01-17	SA	3	JAN	Q1_04	2004
18	2004-01-18	SU	4	JAN	Q1_04	2004
19	2004-01-19	MO	4	JAN	Q1_04	2004
20	2004-01-20	TU	4	JAN	Q1_04	2004
...

Period table

The Period table defines daily, weekly, monthly, quarterly, and yearly time periods for 2004, 2005, and the first quarter of 2006.

Column descriptions

Column Name	Contents
Perkey	Integer that identifies exactly one row in the Period table. Perkey is the primary key.
Date	Date value that identifies each day from January 1, 1998 through March 31, 2000.
Day	Character-string abbreviation of the day of the week.
Week	Integer that identifies each week of each year by number (1 through 53, each new week starting on a Sunday).
Month	Character-string abbreviation of the name of each month.
Qtr	Character string that uniquely identifies each quarter (for example, Q1_98, Q3_99).
Year	Integer that identifies the year.

Sample data from the Promotion table

Query

SELECT * FROM aroma.promotion;

Result

Promokey	Promo_Type	Promo_Desc	Value	Start_Date	End_Date
0	1	No promotion	0.00	9999-01-01	9999-01-01
1	100	Aroma catalog coupon	1.00	2004-01-01	2004-01-31
2	100	Aroma catalog coupon	1.00	2004-02-01	2004-02-29
3	100	Aroma catalog coupon	1.00	2004-03-01	2004-03-31
4	100	Aroma catalog coupon	1.00	2004-04-01	2004-04-30
5	100	Aroma catalog coupon	1.00	2004-05-01	2004-05-31
6	100	Aroma catalog coupon	1.00	2004-06-01	2004-06-30
7	100	Aroma catalog coupon	1.00	2004-07-01	2004-07-31
8	100	Aroma catalog coupon	1.00	2004-08-01	2004-08-31
9	100	Aroma catalog coupon	1.00	2004-09-01	2004-09-30
10	100	Aroma catalog coupon	1.00	2004-10-01	2004-10-31
11	100	Aroma catalog coupon	1.00	2004-11-01	2004-11-30
12	100	Aroma catalog coupon	1.00	2004-12-01	2004-12-31
13	100	Aroma catalog coupon	1.00	2005-01-01	2005-01-31
14	100	Aroma catalog coupon	1.00	2005-02-01	2005-02-28
15	100	Aroma catalog coupon	1.00	2005-03-01	2005-03-31
16	100	Aroma catalog coupon	1.00	2005-04-01	2005-04-30
17	100	Aroma catalog coupon	1.00	2005-05-01	2005-05-31
18	100	Aroma catalog coupon	1.00	2005-06-01	2005-06-30
19	100	Aroma catalog coupon	1.00	2005-07-01	2005-07-31
20	100	Aroma catalog coupon	1.00	2005-08-01	2005-08-31
...

Promotion table

The Promotion table is a dimension table that describes promotions that are run on different products during different time periods. Promotion tables are sometimes referred to as condition tables because they indicate the conditions under which goods are sold.

Column descriptions

Column Name	Contents
promokey	Integer that identifies exactly one row in the Promotion table. Promokey is the primary key.
promo_type	Integer that identifies the promotion by number (or code).
promo_desc	Character string that describes the promotion type.
value	Decimal number that represents the dollar value of the promotion, such as a price reduction or the value of a coupon.
start_date, end_date	Date values that indicate when each promotion begins and ends.

Sample data from the Sales table

Query

SELECT * FROM aroma.sales;

Result

Perkey	Classkey	Prodkey	Storekey	Promokey	Quantity	Dollars
2	2	0	1	116	8	34.00
2	4	12	1	116	9	60.75
2	1	11	1	116	40	270.00
2	2	30	1	116	16	36.00
2	5	22	1	116	11	30.25
2	1	30	1	116	30	187.50
2	1	10	1	116	25	143.75
2	4	10	2	0	12	87.00
2	4	11	2	0	14	115.50
2	2	22	2	0	18	58.50
2	4	0	2	0	17	136.00
2	5	0	2	0	13	74.75
2	4	30	2	0	14	101.50
2	2	10	2	0	18	63.00
2	1	22	3	0	11	99.00
2	6	46	3	0	6	36.00
2	5	12	3	0	10	40.00
2	1	11	3	0	36	279.00
2	5	1	3	0	11	132.00
2	5	10	3	0	12	48.00
...

Sales table

Multipart primary key

The Sales table contains a multipart primary key: Each of its five columns is a foreign-key reference to the primary key of another table:

perkey, classkey, prodkey, storekey, promokey

This primary key links the Sales table data to the Period, Product, Store, and Promotion dimensions.

Joins with the Sales table are shown in examples throughout this tutorial series.

Column descriptions

Column Name	Contents
perkey	Foreign-key reference to the Period table.
classkey	Foreign-key reference to the Class table.
prodkey	Foreign-key reference to the Product table.
storekey	Foreign-key reference to the Store table.
promokey	Foreign-key reference to the Promotion table.
quantity	Integer that represents the total quantity sold (per day).
dollars	Decimal number that represents dollar sales figures (per day).

Sample data from the Gold table

Note: Participants will not find this table in the Aroma database upon initialization. It is meant to be created by participants in Part 6 of this series, Data Definition Language and Control Language (developerWorks, August 2006).

The following results table displays the table as it would be after "The INSERT Statement" section of Part 6.

Query

SELECT * FROM aroma.gold;

Result

Card_id	Storekey	Fname	Lname	Email	Status
1	1	Ada	Alexander	coffee_lover@hotmail.com	Active
2	1	Ben	Bowman	mmmcoffee@yahoo.com	Active
3	1	Cynthia	Chen	iheartcoffee@gmail.com	Active
4	1	David	Doyle	coffee_maniac@msn.com	Active
5	1	Emily	Enright	cupAday@hotmail.com	Active
6	1	Frank	Freeman	coffee_addict@gmail.com	Active

Gold table

The Gold table contains information about customers who have purchased a promotion card.

Column descriptions

Column Name	Contents
card_id	SMALLINT that identifies the customer with an unique card number.
storekey	Foreign-key reference to the Store table.
fname	Character string that stores the first name of the customer.
lname	Character string that stores the last name of the customer.
email	Character string that stores the email of the customer.
status	Character string that stores the status of the customer.

Purchasing schema of the Aroma database

A few of the examples in this tutorial series are based on tables used to track product orders that the Aroma Coffee and Tea Company receives from its suppliers. This purchasing schema uses the same Product, Class, and Period dimensions as the retail schema but has two dimensions of its own: Deal and Supplier. The Line_Items and Orders tables both contain facts, but the Orders table can also be queried as a dimension table referenced by the Line_Items table.

Figure 2 illustrates the tables in the purchasing schema.

Figure 2. Tables in purchasing schema

Multistar schema

The primary keys of the Line_Items and Orders tables do not match the set of their respective dimension-table foreign keys. Any given combination of dimension table primary keys can point to more than one row in these fact tables. This type of table is known as a multistar fact table or data list.

For example, multiple order numbers in the Orders table can refer to the same set of Supplier, Deal, and Period characteristics:

Order_No	Perkey	Supkey	Dealkey
3699	817	1007	0
3700	817	1007	0

Purchasing tables

The purchasing schema contains similar kinds of facts to those stored in the Sales table, prices, and quantities. The prices are dollar values representing amounts paid to suppliers for whole orders or specific line items within orders. The quantities represent units of a product ordered.

You can use this schema to ask interesting questions about the purchasing history of the Aroma Coffee and Tea Company, for example, which suppliers give the best deal on which products, or which suppliers have the best record for closing orders.

The Aroma Coffee and Tea Company sells the same products throughout its stores as it orders through its suppliers. Therefore, you can write queries that span both schemas to compare what was ordered with what was sold or to calculate simple profit margins.

The following tables make up the purchasing schema of the Aroma database:


Period	Defines time intervals such as days, months, and years.
Class	Defines classes of products, both sold at retail stores and ordered from suppliers.
Product	Defines individual products, both sold at retail stores and ordered from suppliers.
Supplier	Defines the suppliers of products ordered by the Aroma Coffee and Tea Company.
Deal	Defines the discount deals applied to orders by suppliers.
Line_Items	Contains the line item detail information for product orders, including the price and quantity of each item on each order.
Orders	Contains information about product orders, such as the full price of each order and the types of products ordered.

The Supplier and Deal tables are exclusive to the purchasing schema and are referenced by the Orders table.

	Tip: The purchasing schema contains data for the first quarter of 2000 only.

Sample data from the Supplier and Deal tables

Query

SELECT * FROM aroma.supplier;

Result

Supkey	Type	Name	Street	City	State	Zip
1001	Coffee/tea	CB Imports	100 Church Street	Mountain View	CA	94001
1002	Tea	Tea Makers, Inc.	1555 Hicks Rd.	San Jose	CA	95124
...

Query

SELECT * FROM aroma.deal;

Result

Dealkey	Deal_Type	Deal_Desc	Discount
0	1000	No deal	0.00
1	100	Orders over $10,000	100.00
2	100	Orders over $20,000	500.00
3	100	Supplier catalog coupon	50.00
4	100	Supplier catalog coupon	100.00
37	200	Supplier coffee special	75.00
38	200	Supplier coffee special	50.00
39	200	Supplier tea special	40.00
40	200	Supplier tea special	20.00

The supplier and deal tables

Column descriptions: Supplier table

Column Name	Contents
supkey	Integer that identifies exactly one row in the Supplier table. Supkey is the primary key.
type	Character string that indicates the type of products supplied.
name	Character string that identifies the supplier by name.
street, city, state, zip	Columns that identify the address of the supplier.

Column descriptions: Deal table

Column Name	Contents
dealkey	Integer that identifies exactly one row in the Deal table. Dealkey is the primary key.
deal_type	Integer that identifies the type of deal (a code number).
deal_desc	Character string that describes the type of deal.
discount	Decimal value that indicates the dollar amount of the deal applied to an order.

Shared dimensions

The purchasing schema shares the Period, Product, and Class tables with the retail schema.

As well as querying the retail and purchasing schemas independently, you can pose some interesting questions that involve tables from both schemas. For example, you can join the Sales and Line_Items tables to compare quantities of products ordered with quantities of products sold. A query like this uses the shared dimensions to constrain products and periods.

Sample data from the Orders and Line_Items tables

Query

SELECT * FROM aroma.orders;

Result

Order_No	Perkey	Supkey	Dealkey	Order_Type	Order_Desc	Close_Date	Price
3600	731	1001	37	Coffee	Whole coffee b	2006-01-07	1200.46
3601	732	1001	37	Coffee	Whole coffee b	2006-01-07	1535.94
3602	733	1001	0	Tea	Loose tea, bul	2006-01-07	780.00
3603	740	1001	39	Tea	Loose tea, bul	2006-01-21	956.45
3604	744	1005	0	Spice	Pre-packed spi	2006-01-16	800.66
3605	768	1003	2	Coffee	Whole-bean and	2006-02-12	25100.00
3606	775	1003	2	Coffee	Whole-bean and	2006-02-19	25100.00
3607	782	1003	2	Coffee	Whole-bean and	2006-02-25	25100.00
3608	789	1003	2	Coffee	Whole-bean and	2006-03-03	30250.00
3609	796	1003	2	Coffee	Whole-bean and	2006-03-15	25100.00
...

Query

SELECT * FROM aroma.line_items;

Result

Order_No	Line_Item	Perkey	Classkey	Prodkey	Receive_Date	Qty	Price
3600	1	731	1	1	2006-01-07	40	180.46
3600	2	731	2	10	2006-01-07	50	300.00
3600	3	731	2	11	2006-01-07	80	240.00
3600	4	731	2	12	2006-01-07	150	240.00
3600	5	731	1	20	2006-01-07	60	240.00
3601	1	732	1	0	2006-01-07	60	240.00
3601	2	732	1	1	2006-01-07	60	240.00
3601	3	732	1	10	2006-01-07	60	240.00
3601	4	732	1	11	2006-01-07	60	240.00
3601	5	732	1	12	2006-01-07	60	240.00
3601	6	732	1	31	2006-01-07	70	335.94
3602	1	733	2	0	2006-01-08	70	130.00
3602	2	733	2	1	2006-01-08	70	130.00
...

The Orders and Line_Items tables

The Orders and Line_Items tables contain the purchasing facts.

Column descriptions: Orders table

Column Name	Contents
order_no	Integer that identifies exactly one row in the Orders table. Order_No is the primary key.
perkey	Foreign-key reference to the Period table.
supkey	Foreign-key reference to the Supplier table.
dealkey	Foreign-key reference to the Deal table.
order_type	Character string that defines the types of products on the order.
order_desc	Character string that describes the type of order.
close_date	Date value that identifies when the order was completed or closed.
price	Decimal value that indicates the full cost of the order.

Column descriptions: Line_Items table

Column Name	Contents
order_no	Integer that identifies exactly one row in the Orders table. Order_No is the primary key.
line_item	Integer that identifies each item listed on the order by number.
perkey	Foreign-key reference to the Period table.
classkey	Foreign-key reference to the Class table.
prodkey	Foreign-key reference to the Product table.
receive_date	Date value that identifies when the line item was received.
quantity	Integer that indicates the quantity of products ordered for each line item.
price	Decimal value that indicates the cost of the line item.

Resources

Learn

"DB2 XML evaluation guide" (developerWorks, June 2006): Read a step-by-step tutorial introducing the reader to the DB2 Viper data server on Windows platforms using the XML storage and searching (SQL/XML, XQuery) capabilities available to support next-generation applications.
"Get off to a fast start with DB2 Viper" (developerWorks, March 2006): Learn how to create database objects for managing your XML data and how to populate your DB2 database with XML data.
"Query DB2 XML data with XQuery" (developerWorks, April 2006): Learn how to query data stored in XML columns using XQuery.
"Query DB2 XML data with SQL" (developerWorks, March 2006): Learn how to query data stored in XML columns using SQL and SQL/XML.
"IBM Systems Journal": Celebrate 10 years of XML.
"SQL Reference, Vol 1": Find information about relational database concepts, language elements, functions, and the forms of queries.
"SQL Reference, Vol 2": Find information about the syntax and semantics of SQL statements. for additional information.
Refer to the IBM DB2 Database for Linux, UNIX, and Windows Information Center for troubleshooting help.
Visit the DB2 XML technical enablement space for links to more than 25 papers on DB2 XML capabilities.
developerWorks Information Management zone: Learn more about DB2. Find technical documentation, how-to articles, education, downloads, product information, and more.
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