Download Oracle_ch11

Chapter 11
Group Functions
(up to p.420)
Jason C. H. Chen, Ph.D.
Professor of MIS
School of Business
Gonzaga University
Spokane, WA 99258 USA
[email protected]
Dr. Chen, Oracle Database System (Oracle)
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Objectives
• Differentiate between single-row and multiple-row
functions
• Use the SUM and AVG functions for numeric
calculations
• Use the COUNT function to return the number of
records containing non-NULL values
• Use COUNT(*) to include records containing
NULL values
• Use the MIN and MAX functions with
nonnumeric fields
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Objectives (continued)
• Determine when to use the GROUP BY clause to
group data
• Identify when the HAVING clause should be used
• List the order of precedence for evaluating
WHERE, 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 a
set of data, using the STDDEV and VARIANCE
functions
• Explain the concept of multidimensional analysis
• Perform enhanced aggregation grouping with the
GROUPING SETS, CUBE, and ROLLUP
• Use composite columns and concatenated
groupings in grouping operations
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Refresh the Database
• 1. Download chapter 11 files from Bb to
c:\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 rows
processed
• 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 numeric
column for a group of rows
Figure 11-2
Dr. Chen, Oracle Database System (Oracle)
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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Figure 11-4
Using the AVG function to calculate average profit
-- chapter 11, Figure 11-5(B); p.407
SELECT TO_CHAR(AVG( retail - cost), '$999.99') "Average Profit"
FROM books
WHERE category = 'COMPUTER';
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COUNT Function
• Two purposes
– Count non-NULL values
– Count total records, including those with NULL
values
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COUNT Function – Non-NULL Values
• Include column name in argument to count
number of occurrences
Figure 11-9
Dr. Chen, Oracle Database System (Oracle)
Using the COUNT function with the DISTINCT option
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COUNT Function – NULL Values
• Include asterisk in argument to count number of rows
Figure 11-11
Dr. Chen, Oracle Database System (Oracle)
Using the COUNT(*) function to include NULL values
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MAX Function
• Returns largest value
Figure 11-13
Dr. Chen, Oracle Database System (Oracle)
Using the MAX function on numeric data
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MIN Function
• Returns the smallest value
Figure 11-16
Dr. Chen, Oracle Database System (Oracle)
Using the MIN function on date data
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Datatypes
• The COUNT, MIN, and MAX functions
can be used on values with character,
numeric, and date datatypes
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Grouping Data
• GROUP BY clause
– Used to group data
– Must be used for any individual column in the
SELECT clause with a group function
– Cannot 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 is missing
a GROUP BY
clause for
nonaggregated
columns in the
SELECT
clause
Figure 11-17 Flawed query: Including both aggregate and
nonaggregate columns requires a GROUP BY clause
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It is an individual
record (just “Profit”
not “Highest Profit”)
Figure 11-19 Inappropriate use of GROUP BY
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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 eliminate certain groups from further consideration.
4 records are eliminated
Dr. Chen, Oracle Database System (Oracle)
Figure 11-21 Using a HAVING clause to restrict which groups are displayed
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Restricting Aggregated Output (continued)
• When included in the same SELECT
statement, the clauses are evaluated in the
order of:
– WHERE
– GROUP 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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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 11-25 Filtering
incorrectly with the HAVING
clauses
Dr. Chen, Oracle Database System (Oracle)
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.447)
Dr. Chen, Oracle Database System (Oracle)
7.
SELECT customer#, COUNT(*)
FROM orders
GROUP BY customer#;
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Homework - Hands-On Assignments
Upload the spooled file (*.txt) to the Bb (under
“Assignments & Projects”) by the deadline.
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 (ALL
EVEN problems; pp.446-448) on “Hands-on
Assignments”. Use appropriate COLUMN or other
SQL commands to produce readable outputs (or your
grade will be discounted –see a sample output on the Bb)
• 3. Execute and test one problem at a time and make sure
they are all running successfully.
• 4. When you done, spool the script files (see next slide for
spooling instructions) and UPLOAD the source (*.sql)
and spooled files (Oracle_ch11_Spool_Lname_Fname.txt)
to Bb by the midnight before the next class.
• 5. Turn in a hardcopy (*.txt) next class.
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How to Spool your Script and Output Files
After you tested the script file of Oracle_ch11_Lname_Fname.sql
successfully, follow the instructions below to spool both script and output
files:
Step 0. Run the following script file from SQL*Plus (since you have created
JLDB 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 the
SQL*PLUS
• 4. type Spool Off on the SQL>
The output should contain your personal information, all SQL commands and
their solution on the .txt file and saved in C: drive (oradata\ folder)
Upload the spooled file (*.txt) to the Bb (under
“Assignments & Projects”) by the deadline.
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Summary
• The AVG, SUM, STDDEV, and VARIANCE
functions are used only with numeric fields
• The COUNT, MAX, and MIN functions can be
applied to any datatype
• The AVG, SUM, MAX, MIN, STDDEV, and
VARIANCE 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 into
groups
• 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 specified
grouping. 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 perform
statistical analyses on a set of data
• GROUPING SETS operations can be used to perform multiple
GROUP 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
Dr. Chen, Oracle Database System (Oracle)
Using the STDDEV function
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VARIANCE Function
• Determines data dispersion within a group
Figure 11-28
Dr. Chen, Oracle Database System (Oracle)
Using the VARIANCE function
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Enhanced Aggregation for Reporting
• Oracle provides extensions to the GROUP BY
clause, which allow both aggregation across
multiple dimensions or the generation of
increasing levels of subtotals with a single
SELECT statement
• A dimension is a term used to describe any
category used in analyzing data, such as time,
geography, and product line
• Each dimension could contain various levels of
aggregation; for example, the time dimension may
include 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
REGION
CUSTOMER
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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 average
retail price for books in four groupings: 1) publisher (the
Name column) and category, 2) category, 3) publisher,
and 4) overall average.
-- chapter 11, Figure 11-32; p.427
Try without
SELECT name, category, COUNT(isbn),
GROUING
TO_CHAR(AVG(retail), '99.99') "Avg Retail"
SETS
FROM publisher JOIN books USING (pubid)
WHERE pubid IN (2,3,5)
GROUP BY GROUPING SETS (name, category, (name, category), ())
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Without GROUPING SETS
-- chapter 11, Figure 11-32(a); p.427
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 name, category;
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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 of
the specified columns (e.g., two columns: Name
(publisher name) and Category).
• The outputs matches Figure 11-32.
• If you need only a subset 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 identify subtotal rows in the results
(helpful in labeling sorting, and restricting output).
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CUBE
Figure 11-34
Dr. Chen, Oracle Database System (Oracle)
Using the CUBE extension of GROUP BY
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Figure 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 calculates
cumulative 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. A grand total is
also calculated.
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ROLLUP
Figure 11-37
Dr. Chen, Oracle Database System (Oracle)
Using the ROLLUP extension of GROUP BY
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Category is the
column outside the
ROLLUP and is
considered the
aggregate value.
A subtotal is
calculated for the
aggregate value as
well as for each
unique value of the
ROLLUP column in
the aggregate value
– i.e., by Category
and each Name in
each Category .
Figure 11-38
Dr. Chen, Oracle Database System (Oracle)
Using a partial ROLLUP
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