Oracle_ch11.pptx

8/10/2019 Oracle_ch11.pptx

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Dr. Chen, Oracle Database System (Oracle) 1

Chapter 11Group Functions

(up to p.402)

Jason C. H. Chen,Ph.D.

Professor of MIS

School of Business

Gonzaga University

Spokane, WA 99258 USA

[email protected]


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Objectives

Differentiate between single-row and multiple-rowfunctions

Use the SUM and AVG functions for numericcalculations

Use the COUNT function to return the number ofrecords containing non-NULL values

Use COUNT(*) to include records containingNULL values

Use the MIN and MAX functions withnonnumeric fields


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Objectives (continued)

Determine when to use the GROUP BY clause togroup data

Identify when the HAVING clause should be used

List the order of precedence for evaluatingWHERE, GROUP BY, and HAVING clauses

State the maximum depth for nesting group

functions

Nest a group function inside of a single-row

function


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Objectives (continued)

Calculate the standard deviation and variance of aset of data, using the STDDEV and VARIANCEfunctions

Explain the concept of multidimensional analysis

Perform enhanced aggregation grouping with theGROUPING SETS, CUBE, and ROLLUP

Use composite columns and concatenatedgroupings in grouping operations


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Refresh the Database

1. Download chapter 11 files from Bb toc:\oradata\chapter11\

2. Run the following script file

Start c:\oradata\chapter11\JLDB_Build_11.sql


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Group Functions

Return one result per group of rowsprocessed

Are also called multiple-row and aggregate

functions All group functions ignore NULL values

except COUNT(*)

Use DISTINCT to suppress duplicate values


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Added Clauses

Figure 11-1 SELECT statement syntax


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SUM Function

Calculates total amount stored in a numericcolumn for a group of rows

Figure 11-2 Using the SUM function to calculate order profit


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AVG Function

Calculates the average of numeric values in a

specified column

Figure 11-4 Using the AVG function to calculate average profit


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-- chapter 11, Figure 11-5(B); p.389

SELECT TO_CHAR(AVG( retail - cost), '$999.99') "Average Profit"

FROM books

WHERE category = 'COMPUTER';

Figure 11-4 Using the AVG function to calculate average profit


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COUNT Function

Two purposesCount non-NULL values

Count total records, including those with NULL

values


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COUNT FunctionNon-NULL Values

Include column name in argument to countnumber of occurrences

Figure 11-9 Using the COUNT function with the DISTINCT option


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COUNT FunctionNULL Values

Include asterisk in argument to count number of rows

Figure 11-11 Using the COUNT(*) function to include NULL values


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MAX Function

Returns largest value

Figure 11-13 Using the MAX function on numeric data


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MIN Function

Returns the smallest value

Figure 11-16 Using the MIN function on date data


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Datatypes

The COUNT, MIN, and MAX functionscan be used on values with character,

numeric, and date datatypes


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Grouping Data

GROUP BY clauseUsed to group data

Must be used for any individual column in the

SELECT clause with a group functionCannot reference column aliases


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GROUP BY Example

Figure 11-18 Adding the GROUP BY clause


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Common Error

A common

error ismissing a

GROUP BY

clause for

nonaggregate

d columns in

the SELECT

clause

Figure 11-17 Flawed query: Including both aggregateand

nonaggregate columns requires a GROUP BY clause


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Figure 11-19 Inappropriate use of GROUP BY

It is an individual

record (just Profit

not Highest Profit)


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Figure 11-20 Calculate

the total amount due by

each customer and

order


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Restricting Aggregated Output

HAVING clause serves as the WHERE clause for grouped data.

It is used to eliminatecertain groups from further consideration.

Figure 11-21 Using a HAVING clause to restrict which groups are displayed

4 records are eliminated


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Restricting Aggregated Output (continued)

When included in the same SELECTstatement, the clauses are evaluated in the

order of:

WHEREGROUP BY

HAVING


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Restricting Aggregated Output (continued)

Figure 11-22 Using the WHERE, GROUP BY, and HAVING clauses


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Figure 11-23 Using a HAVING clause to

restrict grouped output


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Figure 11-24 Filtering correctly

with the WHERE and HAVING

clauses


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Figure 11-25 Filtering

incorrectly with the HAVING

clauses

It is quite inefficient and

considered poor SQL

programming practice. The

statement must process

ALL rows in the BOOKS

table with the aggregated

calculation and then

eliminate categories.

Figure 11-24 Filtering correctly with the WHERE and HAVING clauses


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Nesting Functions

Inner function is resolved first

Maximum nesting depth: 2

Figure 11-26 Nesting group functions


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Exercises

Practice all the examples in the text. A Script file is available on the Bb (file

name: ch11Queries.sql)

After completing all examples, do the HW.

In-class Exercise

#7 (p.424)


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Homework - Hands-On Assignments

Read and Practice all examples on Chapters 11

1. Run the script files (in the folder \oradata\chapter11\):

JLDB_Build_11.sql 2. Read Oracle assignment and create a script file

Oracle_ch11_Lname_Fname.sql for questions (ALLEVEN problems; pp.424-425) on Hands-onAssignments. Use appropriate COLUMN or otherSQL commands to produce readable outputs (or yourgrade wil l be discountedsee a sample output on the Bb)

3. Execute and test one problem at a time and make surethey are all running successfully.

4. When you done, spool the script files (see next slide forspooling instructions) and email the file(Oracle_ch11_Spool_Lname_Fname.txt) to me by themidnight before the next class.

Email me with one attachment

(Oracle_ch11_Spool_Lname_Fname.) to:

[email protected] subject title of

bmis441_Oracle_ch11


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How to Spool your Script and Output FilesAfter you tested the script file of Oracle_ch11_Lname_Fname.sql

successfully, follow the instructions below to spool both script and outputfiles:

Step 0. Run the following script file from SQL*Plus (since you have createdJLDB tables)

Start c:\oradata\chapter11\JLDB_Build_11.sql

1. type the following on SQL> Spool c:\oradata\Oracle_ch11_Spool_Lname_Fname.txt(make sure your name is

entered) 2. open Oracle_ch11_Lname_Fname.sql that you already tested

3. copy and paste all the SQL commands (including all comments) to theSQL*PLUS

4. type Spool Off on the SQL>

The output should contain your personal information, all SQL commands andtheir solution on the .txt file and saved in C: drive (oradata\ folder)Email me with the spooled file (.txt) with attachment to:

[email protected]

with subject title of

bmis441_Oracle_ch11


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Summary

The AVG, SUM, STDDEV, and VARIANCEfunctions are used only with numeric fields

The COUNT, MAX, and MIN functions can beapplied to any datatype

The AVG, SUM, MAX, MIN, STDDEV, andVARIANCE functions all ignore NULL values

By default, the AVG, SUM, MAX, MIN,COUNT, STDDEV, and VARIANCE functions

include duplicate values


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Summary (continued)

The GROUP BY clause is used to divide table data intogroups

If a SELECT clause contains both an individual field name

and a group function, the field name must also be included in

a GROUP BY clause The HAVING clause is used to restrict groups in a group

function

Group functions can be nested to a depth of only two. The

inner function is always performed first, using the specifiedgrouping. The results of the inner function are used as input

for the outer function.


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Summary (continued)

The STDDEV and VARIANCE functions are used to performstatistical analyses on a set of data

GROUPING SETS operations can be used to perform multipleGROUP BY aggregations with a single query

The CUBE extension of the GROUP BY calculates aggregations

for all possible combinations or groupings of columns included The ROLLUP extension of the GROUP BY calculates increasing

levels of accumulated subtotals for the column list provided

Composite columns and concatenated groupings can be used in

GROUPING SETS, CUBE, and ROLLUP operations

The GROUP_ID function helps eliminate duplicate grouping

results


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STDDEV Function

Figure 11-27 Using the STDDEV function


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VARIANCE Function

Determines data dispersion within a group

Figure 11-28 Using the VARIANCE function


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Enhanced Aggregation for Reporting

Oracle provides extensions to the GROUP BYclause, which allow both aggregationacrossmultiple dimensions or thegenerationofincreasing levels of subtotals with a singleSELECT statement

A dimensionis a term used to describe anycategory used in analyzing data, such as time,geography, and product line

Each dimension could contain various levels of

aggregation; for example, the time dimension mayinclude aggregation by month, quarter, and year;the product dimension may include product type,sales, store, region and month.


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Figure Slicing a data cube

CUSTOMER

REGION


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Excel Pivot Table Example

Figure 11-30 A pivot table with two dimensions on a row


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Excel Pivot Table Example (continued)

Figure 11-31 A pivot table with one row and one column dimension


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GROUPING SETS

The grouping sets expression is the component on which

the other GROUP BY extensions, ROLLUP and CUBE,are built.

With this extension, you can use a single query statement

to perform multiple GROUP BY clauses.

The single query in Figure 11-32 produces the averageretail price for books infourgroupings: 1) publisher (the

Name column) and category, 2) category, 3) publisher,

and 4) overall average.

-- chapter 11, Figure 11-32; p.408

SELECT name, category, COUNT(isbn),

TO_CHAR(AVG(retail), '99.99') "Avg Retail"

FROM publisher JOIN books USING (pubid)

WHERE pubid IN (2,3,5)

GROUP BY GROUPING SETS (name, category, (name, category), ())

Try withoutGROUING

SETS


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Without GROUPING SETS

-- chapter 11, Figure 11-32(a); p.408SELECT name, category, COUNT(isbn),

TO_CHAR(AVG(retail), '99.99') "Avg Retail"

FROM publisher JOIN books USING (pubid)

WHERE pubid IN (2,3,5)

GROUP BY name, category;

G i S


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Grouping Sets

Figure 11-32 Using a GROUPING SETS expression in a GROUP BY clause


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The CUBE Extension

The CUBE extension of GROUP BY instructs Oracle to

perform aggregations for all possible combinations ofthe specified columns (e.g., two columns: Name

(publisher name) and Category).

The outputs matches Figure 11-32.

If you need only asubset of the four aggregate levels

calculated, you must use the GROUPING SETS

expression because the CUBE extension always

performs all aggregation levels.

Adding a GROUPING function to the CUBE extension

(Fig. 11-35) to identifysubtotalrows in the results

(helpful in labeling sorting, and restricting output).


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CUBE

Figure 11-34 Using the CUBE extension of GROUP BY


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Dr. Chen, Oracle Database System (Oracle) 46Figure 11-35 The GROUPING function returns a 1 to identify subtotal rows


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The ROLLUP Extension

The ROLLUP extension of GROUP BY calculatescumulative subtotals for the specified columns.

If multiple columns are indicated, subtotals are

performed for each column in the argument list,

except the one on the far right. Agrandtotal is

also calculated.

ROLLUP


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ROLLUP

Figure 11-37 Using the ROLLUP extension of GROUP BY


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Figure 11-38 Using a partial ROLLUP

Category is the

column outside the

ROLLUPand is

considered the

aggregate value.A subtotal is

calculated for the

aggregate value as

well as for each

unique value of the

ROLLUP column inthe aggregate value

i.e., by Category

and each Name in

each Category .

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