dbp10 ch02 01 - csuohio.educis.csuohio.edu/~sschung/IST331/dbp10_ch02_01.pdfMicrosoft PowerPoint -...
Transcript of dbp10 ch02 01 - csuohio.educis.csuohio.edu/~sschung/IST331/dbp10_ch02_01.pdfMicrosoft PowerPoint -...
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
2-1
David M. Kroenke’s
Chapter Two:
Introduction to
Structured Query Language
Part One
Database Processing:Fundamentals, Design, and Implementation
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
2-2
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].
• A newer version [SQL3] exists and incorporates
some object-oriented concepts, but is not widely
used in commercial DBMS products.
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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SQL as a Data Sublanguage
• SQL is not a full featured programming language as are C, C#, and Java.
• SQL is a data sublanguage for creating and processing database data and metadata.
• SQL is ubiquitous in enterprise-class DBMS products.
• SQL programming is a critical skill.
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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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.
• Covered in Chapter Seven.
– Data manipulation language (DML)statements.
• Used for queries and data modification
• Covered in this chapter (Chapter Two)
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
2-5
Cape Codd Outdoor Sports
• Cape Codd Outdoor Sports is a fictitious
company based on an actual outdoor retail
equipment vendor.
• Cape Codd Outdoor Sports:
– Has 15 retail stores in the United States and Canada.
– Has an on-line Internet store.
– Has a (postal) mail order department.
• All retail sales recorded in an Oracle database.
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
2-6
Cape Codd Retail Sales Structure
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
2-7
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
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
2-8
Extracted Retail
Sales Data Format
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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Retail Sales Extract Tables
[in MS SQL Server]
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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The SQL SELECT Statement
• The fundamental framework for SQL query states is the SQL SELECT statement:
– SELECT {ColumnName(s)}
– FROM {TableName(s)}
– WHERE {Conditions}
• All SQL statements end with a semi-colon (;).
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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Specific Columns on One Table
SELECT Department, Buyer
FROM SKU_DATA;
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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Specifying Column Order
SELECT Buyer, Department
FROM SKU_DATA;
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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The DISTINCT Keyword
SELECT DISTINCT Buyer, Department
FROM SKU_DATA;
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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Selecting All Columns:
The Asterisk (*) Keyword
SELECT *
FROM SKU_DATA;
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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Specific Rows from One Table
SELECT *
FROM SKU_DATA
WHERE Department = 'Water Sports';
NOTE: SQL wants a plain ASCII single quote: ' NOT ‘ !
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
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Specific Columns and Rows from
One Table
SELECT SKU_Description, Buyer
FROM SKU_DATA
WHERE Department = 'Climbing';
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DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall
2-17
David M. Kroenke’s
Database Processing Fundamentals, Design, and Implementation
(10th Edition)
End of Presentation:Chapter Two Part One