Chapter 7

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# Chapter 7 - PowerPoint PPT Presentation

Chapter 7. Information Retrieval from Relational Databases. Chapter Learning Objectives. Identify and explain the purpose of the three primary relational algebra operators Identify and explain the primary components of a Structured Query Language (SQL) statement

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### Chapter 7

Information Retrieval from Relational Databases

Chapter Learning Objectives
• Identify and explain the purpose of the three primary relational algebra operators
• Identify and explain the primary components of a Structured Query Language (SQL) statement
• Identify the relational algebra operations achieved by a given SQL statement
• Create a SQL statement to retrieve requested information from a relational database
• Examine a SQL statement and the tables to which it will be applied and identify the query result
• Find errors in a SQL statement
• Create a Microsoft Query-by-Example (QBE) to retrieve information from relational tables
• Examine a Microsoft Access QBE query and the tables to which it applies and identify the query result
• Find errors in a Microsoft Access QBE query
Examples of Needs for Multiple Views of One Data Set
• Cash-basis versus Accrual Accounting
• Weighted Average versus FIFO or LIFO
• Double-Declining Balance Depreciation versus Straight Line
• Foreign Currency Translation

How do we get these multiple views???????

• What is Querying?
• It is asking questions about the data in the database and manipulating or combining the data in different ways
• We can isolate certain rows in tables, we can isolate certain columns in tables, we can join tables together, we can create calculations based on various data items, etc.
Querying/Information Retrieval

Several ingredients are necessary for effective querying

• A database that is well-designed
• If tables are not fully relational or incompletely specified, or if conceptual model has not been correctly converted into relational form, querying will be difficult or impossible
• A query developer who understands the table structures and the nature of the data in the tables
• A query developer who understands the desired query output
• A query developer who has good logic and reasoning skills
• A query developer who knows the querying language used to retrieve information from the enterprise database
Three Query Languages
• Relational Algebra
• Three main operators: Select, Project, Join
• Provides the conceptual basis for SQL and QBE
• Structured Query Language (SQL)
• The user enters commands according to a pre-defined syntax to retrieve desired data.
• Query By Example (QBE)
• The user starts with a sample of the table(s) columns and marks the fields he or she wants to include in the answer. Defaults are available for summarizing and manipulating the data.
Relational Algebra
• Select
• includes only certain rows from a database table in its “answer”.
• Project
• includes only certain columns from a database table in its “answer”
• Join
• combines two or more database tables on the basis of one or more common attributes
Relational Algebra SELECT

Find the cash receipts from Customer #2 (keeping all the details of those cash receipts)

Select Cash Receipt Where Customer Number = C-2 Giving Answer

Relational Algebra PROJECT

Find the customer number, name, and salesperson number for all customers

Project Customer Over (Customer#, Name, SP#) Giving Answer

Join Types
• Inner join
• includes only the records from both tables that have the exact same values in the fields that are joined
• I.e.,
• Outer join
• includes all records from one table, and matches those records from the other table for which values in the joined fields are equal
• I.e.,

Left Outer Join

Right Outer Join

Relational Algebra Inner Join

Find all details of all customers and all available details of each customer’s salesperson

Join Customer, Salesperson Where Customer.SP# = [Salesperson.Employee Number] Giving Answer

Relational Algebra Left Outer Join

Find all details of all sales and the cash receipt number and amount applied of any cash receipts related to those sales

Left Outer Join Sale, [Sale - CashRecDuality] Where [Sale.Sale#] = [Sale - CashRecDuality.Sale#] Giving Answer

SQL (Structured Query Language)
• Each query statement follows the same structure:SELECTattribute name(s)FROMtable name(s)WHERE criteria is met;
SQL Statements and Relational Algebra
• SQL’s SELECT component isolates columns
• i.e., relational algebra’s project
• SQL’s FROM component is used for identifying the table(s) involved
• if >1 table, helps accomplish relational algebra’s join (together with WHERE component that specifies equal fields)
• SQL’s WHERE component isolates rows
• i.e., relational algebra’s select
• also helps accomplish relational algebra’s join
• may be left blank for single-table queries that retrieve all rows
SQL and Relational Algebra SELECT

Find the cash receipts from Customer #2 (keeping all the details of those cash receipts)

Select *From [Cash Receipt]Where [Customer Number] = C-2;

(note: the brackets are needed because of spaces in the table and field names; also note * is a wild card indicating all columns should be included)

SQL and Relational Algebra PROJECT

Find the customer number, name, and salesperson number for all customers

Select Customer#, Name, SP# From Customer;

SQL and Relational Algebra Inner Join

Find all details of all customers and all available details of each customer’s salesperson

Select *From Customer, SalespersonWhere Customer.SP# = [Salesperson.Employee Number];

SQL and Relational Algebra Outer Join

Find all details of all sales and the cash receipt number and amount applied of any cash receipts related to those sales

Select *From Sale LeftJoin [Sale-CashRecDuality]Where [Sale.Sale#]=[Sale-CashRecDuality.Sale#];

Mathematical Comparison Operators
• SQL Queries may include mathematical comparison operators such as
• = equal to
• < less than
• <= less than or equal to
• > greater than
• >= greater than or equal to
• <> not equal to (or != in some software)
• Mathematical comparison operators are typically included in the WHERE clause of the SQL statement, and may be used on all types of fields
• For date fields, dates that are earlier in time are “less than” dates that are later in time.
• For text fields, A < B < C, etc.
SQL Mathematical Comparison Operators

Select Account#, BalanceFrom CashWhere Balance>=50000;

Select Sale#, AmountFrom SaleWhere SalesRep# <> E-10;

Queries with Logical Operators
• Queries may include logical operators AND, OR, and NOT
• AND accomplishes a set intersection – answer includes all instances that meet BOTH conditions
• OR accomplishes a set union – answer includes all instances that meet one condition and all instances that meet the other condition
• NOT identifies instances that do not meet one or more conditions
Queries with Special Operators
• BETWEEN is used to define the range limits.
• The end points of the range are included

Select Sale#, Amount, DateFrom SaleWhere Date BETWEEN 7/1 and 7/31;

Queries with Special Operators
• IS NULL is used to retrieve attributes for which the value is null.

Select *From CashWhere Balance IS NULL;

Queries with Special Operators

• EXISTS is used to retrieve attributes for which the value is not null.

Select *From CashWhere Balance EXISTS;

Aggregation Functions in Queries
• An aggregation function summarizes the data values within a field (column)
• COUNT summarizes the number of rows that contain a given value in the field
• AVERAGE computes the arithmetic mean value of all rows included in the answer
• SUM computes the arithmetic sum of all rows included in the answer
• MIN identifies the minimum (lowest) attribute value for the field
• MAX identifies the maximum (greatest) attribute value for the field
Queries with Horizontal Calculations
• “Horizontal” calculations mathematically combine values from different fields for each row
• Horizontal calculations should NOT be included in the same query as an aggregation function
• One query may perform a horizontal calculation and another query that builds on the first query may perform the aggregation function, or vice versa
• The “correct” order for the queries depends on the goal
Result

Relational Algebra SELECT in QBE Cash Receipts from Customer C-2

Result

Relational Algebra Inner Join in QBE: All details of customers and their salespeople

Result

Double-click on the join line

Relational Algebra Outer Join in QBE Details of all sales, related cash receipts

Click on appropriate join type

Click OK

Relational Algebra Outer Join in QBE Details of all sales, related cash receipts

Notice change in join line

Relational Algebra Outer Join in QBE Details of all sales, related cash receipts

AND operator in QBE: Sales made before July 31 by Sales Rep E-10

OR operator in QBE: Sales made before July 31 OR by Sales Rep E-10

Result

Bring only the fields you need into the query grid

Aggregation SUM and Special Operator BETWEEN in QBE: Total Sales between July 15 and July 31

Click on summation symbol to add “Total” line to query grid (used for aggregations)

Enter Criteria with BETWEEN operator

Aggregation SUM and Special Operator BETWEEN in QBE: Total Sales between July 15 and July 31

Total line defaults to “Group By” for each field; Change the Amount field to “Sum” and change the Date field to “Where”

Aggregation SUM and Special Operator BETWEEN in QBE: Total Sales between July 15 and July 31

Aggregation SUM and Special Operator BETWEEN in QBE: Total Sales between July 15 and July 31

Result

Save query so that fields will be available to the Expression Builder; then click on the magic wand to start the Expression Builder

Horizontal Calculation in QBE: Inventory-Sale Line Item Extension

Result

Querying Summary
• Querying provides the power of the relational database model
• Once you unlock the mystery of query construction, you can tap into the wealth of information that is at your fingertips in a well-designed relational database
• Querying requires organized thinking and logic
• You must understand the structure of the database tables and the nature of the data in those tables.
• You must identify which table(s) are needed for each query, and determine the appropriate manipulations that need to be made in the appropriate sequence
• Some people find it helpful to organize their thinking by considering what relational algebra operators are needed even though the relational algebra language is rarely used
• Manually calculating the query result using a representative data sample is also very helpful for identifying query errors
• Remember to separate horizontal calculations from vertical aggregations
• Comprehensive testing of queries is crucial before releasing queries for use by general users

End of Chapter