Query Optimization to reduce multiple joins statements - sql

Question

Here is the table:
CREATE TABLE ABC
(
key NUMBER(5),
orders NUMBER(5),
cost NUMBER(5),
dat DATE
);
insert into ABC (key, orders, cost, dat) values (1, 3, 5, to_date('10-11-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 5, 2, to_date('02-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 6, 1, to_date('03-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 7, 2, to_date('05-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 8, 3, to_date('07-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 3, 4, to_date('08-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 3, 6, to_date('02-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 3, 9, to_date('01-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 2 ,5, to_date('03-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 3, 2, to_date('05-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 1, 1, to_date('06-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 4, 12, to_date('10-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 3, 9, to_date('01-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 2 ,5, to_date('05-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 3, 2, to_date('06-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 1, 1, to_date('07-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 4, 12, to_date('11-10-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost, dat) values (1, 3, 5, to_date('10-01-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 5, 2, to_date('02-17-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 6, 1, to_date('03-18-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 7, 2, to_date('05-14-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 8, 3, to_date('07-13-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (1, 3, 4, to_date('08-12-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 3, 6, to_date('02-11-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 3, 9, to_date('01-15-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 2 ,5, to_date('03-14-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 3, 2, to_date('05-18-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (2, 1, 1, to_date('06-19-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 4, 12, to_date('10-11-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 3, 9, to_date('01-12-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 2 ,5, to_date('05-16-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 3, 2, to_date('06-17-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 1, 1, to_date('07-12-
2017', 'mm-dd-yyyy'));
insert into ABC (key, orders, cost,dat) values (3, 4, 12, to_date('12-21-
2017', 'mm-dd-yyyy'));
Not sure why my results are repeating.
Here is my query:
with qone as
(select a.key, a.max_price, max(t.dat) as qo_dat from ABC t
JOIN
(select key, max(cost) as max_price from ABC
where dat >= to_date('01-01-2017', 'mm-dd-yyyy') and dat < to_date('04-01-
2017', 'mm-dd-yyyy')
group by key) a on a.key = t.key and a.max_price = t.cost
group by a.key, a.max_price),
qtwo as
(select a.key, a.max_price, max(t.dat) as qt_dat from ABC t
JOIN
(select key, max(cost) as max_price from ABC
where dat >= to_date('04-01-2017', 'mm-dd-yyyy') and dat < to_date('07-01-
2017', 'mm-dd-yyyy')
group by key) a on a.key = t.key and a.max_price = t.cost
group by a.key, a.max_price),
qthree as
(select a.key, a.max_price, max(t.dat) as qth_dat from ABC t
JOIN
(select key, max(cost) as max_price from ABC
where dat >= to_date('07-01-2017', 'mm-dd-yyyy') and dat < to_date('10-01-
2017', 'mm-dd-yyyy')
group by key) a on a.key = t.key and a.max_price = t.cost
group by a.key, a.max_price),
qfour as
(select a.key, a.max_price, max(t.dat) as qf_dat from ABC t
JOIN
(select key, max(cost) as max_price from ABC
where dat >= to_date('10-01-2017', 'mm-dd-yyyy') and dat < to_date('01-01-
2018', 'mm-dd-yyyy')
group by key) a on a.key = t.key and a.max_price = t.cost
group by a.key, a.max_price)
select qo.key, qo.max_price as max_q1, qo.qo_dat, qt.max_price as max_q2,
qt.qt_dat, qth.max_price as max_q3, qth.qth_dat, qf.max_price as max_q4,
qf.qf_dat from qone qo
join qtwo qt on qt.key = qo.key
join qthree qth on qth.key = qth.key
join qfour qf on qf.key = qf.key
order by keyenter code here
I want to know if there is a way to reduce the lines.
How I did it? I find the Max Price and Max Date for each quarter, I define the quarters using where statement.
I use Divide and Conquer technique, I find the Max price and the respective date for all four quarters and join them on the key. Sample of one self-defined quarter below.
`select a.key, a.max_price, max(t.dat) as qo_dat from ABC t
JOIN
(select key, max(cost) as max_price from ABC
where dat >= to_date('01-01-2017', 'mm-dd-yyyy') and dat < to_date('04-01-
2017', 'mm-dd-yyyy')
group by key) a on a.key = t.key and a.max_price = t.cost
group by a.key, a.max_price`
Output:
Possible optimized solution: but I m figuring out a way to add a corresponding date next to it
select
t.key,
max( case when t.dat >= Tmp.Q1From and t.dat < Tmp.Q1End then t.cost
else 0 end ) as Q1Tot,
max( case when t.dat >= Tmp.Q1End and t.dat < Tmp.Q2End then t.cost else
0 end ) as Q2Tot,
max( case when t.dat >= Tmp.Q2End and t.dat < Tmp.Q3End then t.cost else
0 end ) as Q3Tot,
max( case when t.dat >= Tmp.Q3End and t.dat < Tmp.Q4End then t.cost else
0 end ) as Q4Tot
from
ABC t,
( select
to_date('01-01-2017', 'mm-dd-yyyy') Q1From,
to_date('04-01-2017', 'mm-dd-yyyy') Q1End,
to_date('07-01-2017', 'mm-dd-yyyy') Q2End,
to_date('10-01-2017', 'mm-dd-yyyy') Q3End,
to_date('01-01-2018', 'mm-dd-yyyy') Q4End
from
dual ) Tmp
where
t.dat >= to_date('01-01-2017', 'mm-dd-yyyy')
and t.dat < to_date('01-01-2018', 'mm-dd-yyyy')
group by
t.key

Answer 1

Instead of using JOINs or cross joins, consider using the analytical function NTH_VALUE (see documentation) for displaying the required values for the 4 quarters side by side.
NTH_VALUE returns the measure_expr value of the nth row in the window
defined by the analytic_clause.
First step: find the "max costs" and their corresponding dates for all keys (and quarters).
select *
from (
select key, dat, to_char( dat, 'Q' ) quarter
, max( cost ) over ( partition by key, to_char( dat, 'Q' ) order by cost desc ) maxcost_
, max( dat ) over ( partition by key, to_char( dat, 'Q' ) order by cost desc ) maxdat_
, row_number() over ( partition by key, to_char( dat, 'Q' ) order by cost desc ) rownum_
from abc
)
where rownum_ = 1
-- result
KEY DAT QUARTER MAXCOST_ MAXDAT_ ROWNUM_
1 17-FEB-17 1 2 17-FEB-17 1
1 14-MAY-17 2 2 14-MAY-17 1
1 12-AUG-17 3 4 12-AUG-17 1
1 01-OCT-17 4 5 11-OCT-17 1
2 10-JAN-17 1 9 15-JAN-17 1
2 10-MAY-17 2 2 18-MAY-17 1
3 10-JAN-17 1 9 12-JAN-17 1
3 10-MAY-17 2 5 16-MAY-17 1
3 10-JUL-17 3 1 12-JUL-17 1
3 10-NOV-17 4 12 21-DEC-17 1
10 rows selected.
Final query: use the first query as an INLINE VIEW, and call NTH_VALUE for retrieving the values for each quarter.
select unique key
, nth_value( maxcost_, 1 ) from first over ( partition by key ) q1max
, nth_value( maxdat_, 1 ) from first over ( partition by key ) q1date
, nth_value( maxcost_, 2 ) from first over ( partition by key ) q2max
, nth_value( maxdat_, 2 ) from first over ( partition by key ) q2date
, nth_value( maxcost_, 3 ) from first over ( partition by key ) q3max
, nth_value( maxdat_, 3 ) from first over ( partition by key ) q3date
, nth_value( maxcost_, 4 ) from first over ( partition by key ) q4max
, nth_value( maxdat_, 4 ) from first over ( partition by key ) q4date
from (
select *
from (
select key, dat, to_char( dat, 'Q' ) quarter
, max( cost ) over ( partition by key, to_char( dat, 'Q' ) order by cost desc ) maxcost_
, max( dat ) over ( partition by key, to_char( dat, 'Q' ) order by cost desc ) maxdat_
, row_number() over ( partition by key, to_char( dat, 'Q' ) order by cost desc ) rownum_
from abc
)
where rownum_ = 1
) -- inline view (no name required)
order by key
;
-- result
KEY Q1MAX Q1DATE Q2MAX Q2DATE Q3MAX Q3DATE Q4MAX Q4DATE
1 2 17-FEB-17 2 14-MAY-17 4 12-AUG-17 5 11-OCT-17
2 9 15-JAN-17 2 18-MAY-17 NULL NULL NULL NULL
3 9 12-JAN-17 5 16-MAY-17 1 12-JUL-17 12 21-DEC-17

Answer 2

Maybe you could rewrite it in a shorter way, as in SQL Fiddle:
select a.key, qtr, a.max_price, max(t.dat) as qo_dat
from ABC t
join (
select key, to_char(dat, 'Q') as qtr, max(cost) as max_price
from ABC
where dat >= to_date('01-01-2017', 'mm-dd-yyyy')
and dat < to_date('01-01-2018', 'mm-dd-yyyy')
group by key, to_char(dat, 'Q')
) a on a.key = t.key and a.max_price = t.cost and a.qtr = to_char(t.dat, 'Q')
group by a.key, a.qtr, a.max_price
order by a.key, a.qtr, a.max_price
The output is a little bit different, but it shows what you want. Doesn't it?

Answer 3

select a.key, a.q1tot, b.dat, a.q2tot, c.dat, a.q3tot, d.dat, a.q4tot, e.dat from (
select
t.key,
max( case when t.dat >= Tmp.Q1From and t.dat < Tmp.Q1End then t.cost else 0 end ) as Q1Tot,
max( case when t.dat >= Tmp.Q1End and t.dat < Tmp.Q2End then t.cost else 0 end ) as Q2Tot,
max( case when t.dat >= Tmp.Q2End and t.dat < Tmp.Q3End then t.cost else 0 end ) as Q3Tot,
max( case when t.dat >= Tmp.Q3End and t.dat < Tmp.Q4End then t.cost else 0 end ) as Q4Tot
from
ABC t,
( select
to_date('01-01-2017', 'mm-dd-yyyy') Q1From,
to_date('04-01-2017', 'mm-dd-yyyy') Q1End,
to_date('07-01-2017', 'mm-dd-yyyy') Q2End,
to_date('10-01-2017', 'mm-dd-yyyy') Q3End,
to_date('01-01-2018', 'mm-dd-yyyy') Q4End
from
dual ) Tmp
where
t.dat >= to_date('01-01-2017', 'mm-dd-yyyy')
and t.dat < to_date('01-01-2018', 'mm-dd-yyyy')
group by
t.key) a
join
( select key, cost, dat from ABC
where dat < to_date('04-01-2017', 'mm-dd-yyyy')) b
on a.key = b.key and a.Q1tot = b.cost
join
( select key, cost, dat from ABC
where dat >= to_date('04-01-2017', 'mm-dd-yyyy') and dat < to_date('07-01-2017',
'mm-dd-yyyy')) c
on a.key = c.key and a.Q1tot = c.cost
join
( select key, cost, dat from ABC
where dat >= to_date('07-01-2017', 'mm-dd-yyyy') and dat < to_date('10-01-2017',
'mm-dd-yyyy')) d
on a.key = d.key and a.Q1tot = d.cost
join
( select key, cost, dat from ABC
where dat >= to_date('10-01-2017', 'mm-dd-yyyy') and dat < to_date('01-01-2018', 'mm-dd-yyyy')) e
on a.key = e.key and a.Q1tot = e.cost
This is my code, But the above two queries perform faster