How to get summary totals on unique IDs using analytics? - sql

Question

My repeating table has duplicate ids but I want summary statistics on unique ids.
Detail_id code book tree
----------- ------ ------ ------
1 BR54 COOK PINE
1 BR55 COOK PINE
1 BR51 COOK PINE
2 BR55 COOK MAPL
2 BR60 COOK MAPL
3 BR61 FORD PINE
3 BR54 FORD PINE
3 BR55 FORD PINE
Here's my query which is also on SQLFiddle
select count(case detail_book when 'COOK' THEN 1 else 0 end) as cook_total,
count(case detail_book when 'FORD' THEN 1 else 0 end) as ford_total,
count(case detail_tree when 'PINE' THEN 1 else 0 end) as pine_total,
count(case detail_book when 'MAPL' THEN 1 else 0 end) as mapl_total
from detail_records;
Desired results:
COOK_TOTAL FORD_TOTAL PINE_TOTAL MAPL_TOTL
---------- ---------- ---------- ----------
2 1 2 1

Answer 1

You could use analytic functions and an inline view to avoid the duplicate counting issue:
select sum(case when detail_book = 'COOK' and book_cntr = 1 then 1 else 0 end) as cook_total,
sum(case when detail_book = 'FORD' and book_cntr = 1 then 1 else 0 end) as ford_total,
sum(case when detail_tree = 'PINE' and tree_cntr = 1 then 1 else 0 end) as pine_total,
sum(case when detail_tree = 'MAPL' and tree_cntr = 1 then 1 else 0 end) as mapl_total
from (select d.*,
row_number() over(partition by detail_book, detail_id order by detail_book, detail_id) as book_cntr,
row_number() over(partition by detail_tree, detail_id order by detail_tree, detail_id) as tree_cntr
from detail_records d) v
Fiddle: http://sqlfiddle.com/#!4/889a8/31/0

Answer 2

I don't think you need analytic functions here:
SELECT COUNT(DISTINCT CASE WHEN detail_book = 'COOK' THEN detail_id END) AS cook_total
, COUNT(DISTINCT CASE WHEN detail_book = 'FORD' THEN detail_id END) AS ford_total
, COUNT(DISTINCT CASE WHEN detail_tree = 'PINE' THEN detail_id END) AS pine_total
, COUNT(DISTINCT CASE WHEN detail_tree = 'MAPL' THEN detail_id END) AS mapl_total
FROM detail_records;
The CASE statement returns NULL when the values don't match; those aren't counted.
Updated SQL Fiddle here. By the way, in your query you were trying to match detail_book to MAPL when I think you wanted to match detail_tree, and my query reflects that.

Answer 3

This answer is based on your example http://sqlfiddle.com/#!4/889a8/29 which you can use to avoid the duplicate ids by getting the distinct ids for detail_book and detail_tree
Kindly check the result here http://sqlfiddle.com/#!4/889a8/44
select sum(case detail_book
when 'COOK' THEN 1
else 0
end) as cook_total,
sum(case detail_book
when 'FORD' THEN 1
else 0
end) as ford_total,
sum(case detail_tree
when 'PINE' THEN 1
else 0
end) as pine_total,
sum(case detail_tree
when 'MAPL' THEN 1
else 0
end) as mapl_total
from
(select distinct detail_id,detail_book,detail_tree
from
detail_records);

Answer 4

You can modify your query to get what you want just by removing the else clause:
select count(case detail_book when 'COOK' THEN 1 end) as cook_total,
count(case detail_book when 'FORD' THEN 1 end) as ford_total,
count(case detail_tree when 'PINE' THEN 1 end) as pine_total,
count(case detail_book when 'MAPL' THEN 1 end) as mapl_total
from detail_records;
The default for case without an else is NULL, so the count() works. Personally, I prefer sum() for this type of aggregation:
select sum(case when detail_book = 'COOK' THEN 1 else 0 end) as cook_total,
sum(case when detail_book = 'FORD' THEN 1 else 0 end) as ford_total,
sum(case when detail_tree = 'PINE' THEN 1 else 0 end) as pine_total,
sum(case when detail_book = 'MAPL' THEN 1 else 0 end) as mapl_total
from detail_records;

Answer 5

Apart from analytical functions, I'd probably use an approach by first "flattening the table" (union all) and then pivoting the result:
select *
from (
select detail_book i
from detail_records
group by detail_id, detail_book
union all
select detail_tree
from detail_records
group by detail_id, detail_tree
)
pivot(count(i) for i in ('COOK', 'FORD', 'PINE', 'MAPL'))
;
sql fiddle

Answer 6

select *
from (
select decode(detail_book,'FORD','FORD_TOTAL','COOK','COOK_TOTAL','MAPL','MAPL_TOTAL','PINE','PINE_TOTAL','OTHER') i,
count(distinct detail_id) j
from detail_records
group by detail_book
union all
select DECODE(detail_tree,'FORD','FORD_TOTAL','COOK','COOK_TOTAL','MAPL','MAPL_TOTAL','PINE','PINE_TOTAL','OTHER') i,
count(distinct detail_id) j
from detail_records
group by detail_tree
)
pivot(sum(j) for i in ('COOK_TOTAL', 'FORD_TOTAL', 'PINE_TOTAL', 'MAPL_TOTAL','OTHER'))
;