BUSINESS INTELLIGENCE ENHANCEMENTS

Question

제품 : SQL*PLUS
작성날짜 : 2004-05-17
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BUSINESS INTELLIGENCE ENHANCEMENTS
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PURPOSE
Oracle 9i에서 강화된 BUSINESS INTELLIGENCE 관련 내용을 요약해 본다.
Explanation
아래의 내용에 대해 설명될 것이다.
- enhanced된 Oracle9i analytical functions
- Use grouping sets
- Create SQL statements with the new WITH clause
Example
1. enhanced된 Oracle9i analytical functions
1) Inverse percentile functions (역백분위수 함수)
: 특정 percent에 해당하는 값을 찾는데 사용된다.
percentile_disc : 특정 백분위수에 가까운 값을 return하는 함수.
percentile_cont : linear interpolation을 사용하여 연속적인
백분위수를 계산하는 함수
ex) 1999년 11월달의 distribution channel당 판매량의 50%에 가까운
discrete value을 찾아라.
select c.channel_desc, avg(s.quantity_sold), percentile_disc(0.5)
within group
(order by s.quantity_sold desc) percentile_50
from sales s, channels c
where c.channel_id = s.channel_id
and time_id between '01-NOV-1999' and '30-NOV-1999'
group by c.channel_desc;
2) What-if rank and distribution functions
: 만약 어떤 data가 add된다면 이 data가 어느정도의 rank나 percenage에
속하는지를 찾는데 사용한다. what if analysis에 해당한다.
RANK : 그룹에서의 순위
DENSE_RANK : 중복값을 배제한 순위
PERCENT_RANK
CUME_DIST
ex) 새로운 사람이 고용되어 $10000 을 받는다면 부서당 salary을 비교할때
어느 정도 rank인가?
select department_id, round(avg(salary)) avg_salary,
rank(10000) within group (order by salary desc) rank,
dense_rank(10000) within group (order by salary desc) dense
from employees
group by department_id ;
3) FIRST/LAST aggregate functions
: 각 그룹의 첫번째나 마지막 값을 나타낼때 사용한다.
ex) manager당 commission을 가장 많이 받는 사람과 적게 받는 사람을 구하라.
select manager_id,
min(salary) keep (dense_rank first order by commission_pct)
as low_comm,
max(salary) keep (dense_rank last order by commission_pct)
as high_comm
from employees
where commission_pct is not null
group by manager_id;
4) WIDTH_BUCKET function
: with_bucket은 oracle 8i의 ntile과 비슷하다. 차이점은 ntile은 있는 모든
값을 그냥 정해진 bucket의 수로 나누는 것이고. with_bucket은 최소,최상
값을 정할 수 있다는 점이 다르다.
만약의 시험성적을 저장하고 있는 테이블이 있으면 각 점수별 분포를 확인
할때 사용할 수 있다.
With_bucket(expression, 0, 100,10)
그러면 10점 단위로 bucket이 생성되고 각 점수별 해당 bucket이 return된다.
ex) Low boundary value = 3000
High boundary value = 13000
Number of buckets = 5
select last_name, salary ,
width_bucket(salary,3000,13000,5) as sal_hist
from employees ;
5) Grouping sets
: group by절에 사용되며 소계나 특정 level의 소계등을 구할때 쓰인다.
2. Use grouping sets
1) 아래의 세개의 그룹에 대한, product가 10,20,45이고 1999년 11월의 1,2일에
해당하는 값을 구하라.
Time, Channel, Product
Time, Channel
Channel, Product
select time_id, channel_id, prod_id, round(sum(quantity_sold)) as cost
from sales
where (time_id = '01-DEC-1999' or time_id = '02-DEC-1999')
and prod_id in (10,20,30)
group by grouping sets
((time_id,channel_id,prod_id),(time_id,channel_id),(channel_id,prod_id)) ;
2) GROUPING SETS vs. CUBE and ROLLUP (참고 bul#11914)
CUBE나 ROLLUP은 필요한 group만 볼수 없지만 9i에서는 1)와 같이 원하는
group만을 볼수 있다.
select time_id, channel_id, prod_id,
round(sum(quantity_sold)) as quantity_sum
from sales
where (time_id = '01-DEC-1999' or time_id = '02-DEC-1999')
and prod_id in (10,20,45)
group by cube(time_id, channel_id, prod_id);
3) GROUPING SETS vs UNION ALL
Grouping sets절 대신에 union all을 사용하는 것은 table을 더 많이
scan하게 되고 문장을 구사하기가 비효율적이다.
아래의 두 문장은 같은 결과를 return한다.
select time_id, channel_id, prod_id,
round(sum(quantity_sold)) as quantity_sum
from sales
where (time_id = '01-DEC-1999' or time_id = '02-DEC-1999')
and prod_id in (10,20,45)
group by grouping sets (time_id, channel_id, prod_id);
select to_char(time_id,'DD-MON-YY'),
round(sum(quantity_sold)) as quantity_sum
from sales
where (time_id = '01-DEC-1999' or time_id = '02-DEC-1999')
and prod_id in (10,20,45)
group by time_id
union all
select channel_id ,
round(sum(quantity_sold)) as quantity_sum
from sales
where (time_id = '01-DEC-1999' or time_id = '02-DEC-1999')
and prod_id in (10,20,45)
group by channel_id
union all
select to_char(prod_id) ,
round(sum(quantity_sold)) as quantity_sum
from sales
where (time_id = '01-DEC-1999' or time_id = '02-DEC-1999')
and prod_id in (10,20,45)
group by prod_id;
4) Composite Columns
아래의 세개의 그룹에 대한 product가 10,20,45이고 1999년 11월의 1,2일에
해당하는 값을 구하라.
Product
Product, Channel,Time
Grand Total
select prod_id, channel_id, time_id
, round(sum(quantity_sold)) as sales
from sales
where (time_id='01-DEC-1999' or time_id='02-DEC-1999')
and prod_id in (10,20,45)
group by rollup(prod_id,(channel_id, time_id))
3. Create SQL statements with the new WITH clause
복잡한 query의 Select절에서 같은 block을 한번 이상 query를 할때 쓰인다.
Query block의 값은 user의 temporary tablespace에 저장한다.
Perfoemance의 향상을 기대할 수 있다.
1) 전체 회사의 총 salary의 1/8보다 많은 부서를 구하라.
with
summary as (
select department_name, sum(salary) as dept_total
from employees, departments
where employees.department_id = departments.department_id
group by department_name)
select department_name, dept_total
from summary
where dept_total > (select sum(dept_total) * 1/8 from summary)
order by dept_total desc ;
2) 1)을 예전 version에서는 아래와 같이 구현하였다.
select department_name, sum(salary) as dept_total
from employees,departments
where employees.department_id=departments.department_id
group by department_name
having sum(salary) > ( select sum(salary) * 1/8
from employees, departments
where
employees.department_id=departments.department_id)
order by sum(salary) desc;
4. Benefits
Improved query speed
Enhanced developer productivity
Minimized learning effort
Standardized syntax
Reference Ducumment
Oracle 9i New features for Developer

Answer 1

Hi Rajasheker,
Without knowing the exact scenario it is hard to give you an answer but I hope the following broad guidelines might help you.
1) There must be some thing in common or it may be a case of wrong architecture/missing buseness requirements. Identify the relationship between these two.
2) Or, do they have a 100% parallel relationship by design? In this casse you need to create a high level common object (dummy) to facilitate the consolidatation process (for example company code or worst scheario sys-id) and enhance both cube as well as ODS.
3) Or, if it is a complex situation: Introduce a new object which can build a bridge between these two. Ask the business about the rules.
If it doesn't help, pl give more details.
Bala