The MODEL clause is a feature specific to Oracle SQL and is not supported by all DBMS. It is unique to Oracle and provides advanced, spreadsheet-like calculation capabilities within SQL queries, which is not a standard feature across other SQL databases.
Description
The MODEL clause in Oracle SQL is a feature that allows to perform inter-row and inter-column calculations in a spreadsheet-like fashion within a SQL query. It provides a way to define a multidimensional array and apply rules to it, enabling complex data manipulations and calculations.
Key Features of the MODEL Clause
Multidimensional Arrays: Treats query results as multidimensional arrays.
Rules-Based Calculations: Allows the definition of rules for calculations that can span across rows and columns.
Cell References: Supports references to other cells in the array, similar to how spreadsheet cells can reference each other.
Basic Syntax
Here is a simplified syntax of the MODEL clause:
SELECT ...FROM ...MODEL [ PARTITION BY (partition_clause) ] DIMENSION BY (dimension_clause) MEASURES (measure_clause) [ RULES (rule_clause) ];
PARTITION BY: Divides the data into partitions, similar to a GROUP BY clause.
DIMENSION BY: Specifies the dimensions of the array (e.g., rows or columns). In the context of the MODEL clause, dimensions act like rows in a spreadsheet
MEASURES: Defines the measures or the actual data values that will be manipulated. Measures act like the data cells in a spreadsheet that can be manipulated.
RULES: Contains the rules that define how calculations are performed.
Pseudo Keywords
ANY: This keyword refers to all members within a particular dimension. It's often used in conjunction with aggregate functions like SUM or AVG to calculate values across all elements in that dimension.
CURRENT: This keyword refers to the current row being processed within the model. It can be useful for calculations that depend on the values in the current row.
Pseudo Functions
CV() (Current Value): This function retrieves the value of a measure from the previous row within the same dimension partition. It's particularly helpful for calculations that involve comparisons or running totals.
DENSE_RANK() and RANK(): These functions assign ranking positions to members within a dimension, considering potential ties and gaps in the data. They can be used for calculations based on ranking or percentiles.
LAG() and LEAD(): These functions access values from previous or subsequent rows within the same dimension partition, allowing for calculations that depend on past or future values.
Example
Sample Data
select employee_id, first_name, last_name, salary, manager_id, department_id
from employees;
EMPLOYEE_ID FIRST_NAME LAST_NAME SALARY MANAGER_ID DEPARTMENT_ID
----------- -------------------- ------------------------- ---------- ---------- -------------
198 Donald OConnell 2600 124 50
199 Douglas Grant 2600 124 50
200 Jennifer Whalen 4400 101 10
201 Michael Hartstein 13000 100 20
202 Pat Fay 6000 201 20
203 Susan Mavris 6500 101 40
204 Hermann Baer 10000 101 70
205 Shelley Higgins 12008 101 110
206 William Gietz 8300 205 110
100 Steven King 24000 90
101 Neena Kochhar
Simple example with no calculations or modifications (rules) applied to the data.
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id ) -- employee_id is the dimension
MEASURES ( salary ) -- salary is the measure
( ) -- empty rules section
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY
Addressing a specific cell
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id )
MEASURES ( salary )
RULES ( salary[employee_id = 100]= salary[employee_id = 100]+ 1000 )
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY;
Addressing a range of cells (using a loop)
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id )
MEASURES ( salary )
RULES ( salary[
FOR employee_id FROM 100 TO 105 INCREMENT 1
]= 1000 )
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY;
Following query throws an error
select employee_id, salary
from employees
model
dimension by (employee_id)
measures (salary)
RULES (
salary[for employee_id from 100 to 105 INCREMENT 1] =
salary[for employee_id from 100 to 105 INCREMENT 1] + 1000
)
order by employee_id
fetch first 10 rows only;
select employee_id, salary
*
ERROR at line 1:
ORA-32622: illegal multi-cell reference
Use of pseudo function cv()
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id )
MEASURES ( salary )
RULES ( salary[
FOR employee_id FROM 100 TO 105 INCREMENT 1
]= salary[cv()]+ 1000 )
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY;
Addressing a range of cells (using a list of values)
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id )
MEASURES ( salary )
RULES ( salary[
FOR employee_id IN ( 100,
102,
104,
105 )
]= salary[cv()]+ 1000 )
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY;
Addressing a range of cells (using a subquery)
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id )
MEASURES ( salary )
RULES ( salary[
FOR employee_id IN (
SELECT
level + 99
FROM
dual
WHERE
level NOT IN ( 2, 4 )
CONNECT BY level <= 6
)
]= salary[cv()]+ 1000 )
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY;
The pseudo keyword ANY
-- Update all salaries by adding 1000 to the existing salary
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id )
MEASURES ( salary )
RULES ( salary[ANY]= salary[cv()]+ 1000 )
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY;
Addressing cells relative to the current cell
SELECT
employee_id,
salary
FROM
employees
MODEL
DIMENSION BY ( employee_id )
MEASURES ( salary )
RULES ( salary[ANY]
ORDER BY
employee_id ASC
= salary[cv()]+ salary[cv() + 1]+ salary[cv() + 3])
ORDER BY
employee_id
FETCH FIRST 10 ROWS ONLY;
Generating data
SELECT
criteria
FROM
dual
MODEL
DIMENSION BY ( 100 criteria )
MEASURES ( 0 x )
RULES ( x[
FOR criteria FROM 100 TO 105 INCREMENT 1
]= 0 );
Row returning behaviour
SELECT
employee_id
FROM
employees
MODEL RETURN UPDATED ROWS
DIMENSION BY ( employee_id )
MEASURES ( 0 x )
RULES ( x[
FOR employee_id FROM 1 TO 10 INCREMENT 1
]= 0 );
