Customizing dynamic rules.

Hello partners,
I am new to BI Beans, and I have followed some samples in BI Beans documentation regarding to how create and define rules fto format crosstab cells.
Now, I think that I need to use code to create a customized format criteria as follow:
We have a goal column with a value, now we want to change the colors of other cells following the next criteria:
-Put green color if the value for the other three columns is above to "goal" column.
-Put red color if the value for the other three columns is less than the 20% of "goal" column.
-Put yellow color if the value for the other three columns is until 20% less than "goal" column.
Any advice or example of how to accomplish with that, will be really appreciated.
Thanks in advance.
Best regards!!!!
Frank Mtz.

Hi,
I am trying to do something similar as was stated in this post such as
-Set the background color of a cell to green if the value of another cell is >= 75.
-Set the background color of the cell to red if the value of the other cell is <= 45.
-Set the background color of the cell to yellow if the value of the other cell is > 45 or < 75.
Does anyone have any helpful suggestions?
Thanks,
Barbara

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Hi,
We are trying to implement a dynamic rule based application in Oracle 9i. Its simple logic where we store expressions as case statments and actions seperated by commas as follows.
Rule: 'Age > 18 and Age <65'
True Action: 'Status = ''Valid'' , description = ''age in range'''
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Returning to your original question, first of all, there is a small flaw in the requirements, because if you apply all the rules to the same table/cols, than the table will have results of only last rule that was processed.
Suppose rule#1:
Rule: 'Age > 18 and Age <65'
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False Action: 'Status =''Invalid'', Description=''Age not in range'''
and Rule#2:
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Then after applying of rule#1 and rule#2, results of the rule#1 will be lost, because second rule will modify the results of the first rule.
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-- fist create two tables rules and data.
drop table rules;
drop table data;
create table rules( id number not null primary key, rule varchar(255), true_action varchar(255), false_action varchar(255) );
create table data( id integer not null primary key, name varchar(255), age number, status varchar(255), description varchar(255) );
-- populate this tables with information.
insert into rules
select rownum id
, 'Age > '||least(a,b)||' and Age < '||greatest(a,b) rule
, 'Status = ''Valid'', description = ''Age in Range''' true_action
, 'Status = ''Invalid'', description = ''Age not in Range''' false_action
from (
select mod(abs(dbms_random.random),60)+10 a, mod(abs(dbms_random.random),60)+10 b
from all_objects
where rownum <= 2
insert into data
select rownum, object_name, mod(abs(dbms_random.random),60)+10 age, null, null
from all_objects
commit;
-- this is method #1, evaluate rule against every record in the data and do the action
declare
eval number;
id number;
data_cursor sys_refcursor;
begin
execute immediate 'alter session set cursor_sharing=force';
for rules in ( select * from rules ) loop
open data_cursor for 'select case when '||rules.rule||' then 1 else 0 end eval, id from data';
loop
fetch data_cursor into eval, id;
exit when data_cursor%notfound;
if eval = 1 then
execute immediate 'update data set '||rules.true_action|| ' where id = :id' using id;
else
execute immediate 'update data set '||rules.false_action|| ' where id = :id' using id;
end if;
end loop;
end loop;
end;
-- this is method #2, evaluate rule against every record in the data and do the action in update, not in select
begin
execute immediate 'alter session set cursor_sharing=force';
for rules in ( select * from rules ) loop
execute immediate 'update data set '||rules.true_action|| ' where id in (
select id
from (
select case when '||rules.rule||' then 1 else 0 end eval, id
from data
where eval = 1 )';
execute immediate 'update data set '||rules.false_action|| ' where id in (
select id
from (
select case when '||rules.rule||' then 1 else 0 end eval, id
from data
where eval = 0 )';
end loop;
end;
Here are SQL_TRACE results for method#1:
call count cpu elapsed disk query current rows
Parse 37 0.01 0.04 0 0 0 0
Execute 78862 16.60 17.50 0 187512 230896 78810
Fetch 78884 3.84 3.94 2 82887 1 78913
total 157783 20.46 21.49 2 270399 230897 157723
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call count cpu elapsed disk query current rows
Parse 6 0.00 0.00 0 0 0 0
Execute 6 1.93 12.77 0 3488 170204 78806
Fetch 1 0.00 0.00 0 7 0 2
total 13 1.93 12.77 0 3495 170204 78808
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Hi,
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