Is there a way to join the below 2 queries - sql

Question

I'm trying to join the below 2 queries.. though both of the below queries use the same tables, I'm unable to get the correct result..
In this query I'm checking for entries present in table 1 which would satisfy the condition m1.condition is 1, and for that entry a query is made to table 2 where even after 5 minutes there is no entry in table 2,then get the count of that entries.
The date check you see for 30 min is to get all the entries in table which are processed half an hour before.
SELECT count(*) AS TOTALCOUNT,
SELECT TO_CHAR(amount, '$999,999,999,999,999.99') AS TOTALVALUE
from table1 m1
LEFT JOIN table2 m ON m.id=m1.id
where m1.condition='1'
and amount BETWEEN 1000 and 25000
and (m1.DATE <= (select to_char((select systimestamp - interval '0 00:05' day to minute from dual),'dd-MON-yy HH.MI.SS AM TZD') from dual))
and m1.DATE <= (select to_char((select systimestamp - interval '0 00:30' day to minute from dual),'dd-MON-yy HH.MI.SS AM TZD') from dual)
and m1.DATE <= systimestamp
similarly in below query in table 2 there are some conditions.. so based on that I'm performing some actions.
SELECT COALESCE(SUM (CASE when m.f = 'Converted' then 1 else 0 END),0) AS CCOUNT,
COALESCE(SUM (CASE when m.f = 'Do Not Convert' then 1 else 0 END),0) AS NCOUNT,
count(m. id) AS TOTALCOUNT,
TO_CHAR(COALESCE (SUM(CASE when m.f = 'C' then (amount) END),0), '$999,999,999,999,999.99') AS CONVERTED,
TO_CHAR(COALESCE (SUM(CASE when m.f = 'D' then (amount) END),0), '$999,999,999,999,999.99') AS NONCONVERTED,
TO_CHAR(COALESCE (SUM(CASE when m.f <> '0' then (amount) END),0), '$999,999,999,999,999.99') AS TOTAL
FROM table1 ml
JOIN table2 m ON m.id=ml.id
and amount BETWEEN 1000 and 25000
and m1.DATE <= (select to_char((select systimestamp - interval '0 30:00' day to minute from dual),'dd-MON-yy HH.MI.SS AM TZD') from dual)
and m1.DATE < systimestamp;
I have to combine both the above queries.. but I'm unable to do.

Answer 1

The only real difference between filters is that m1.condition = '1', so just add
count(case condition when '1' then 1 end) as condition_1_totalcount,
sum(case condition when '1' then amount end) as condition_1_totalvalue
to your second query. In my short test it looks OK:
-- sample data
with
table1(id, date_, condition) as (
select 1, date '1990-02-19', '1' from dual union all
select 2, date '1990-02-19', '7' from dual union all
select 3, date '1990-02-19', '1' from dual union all
select 4, date '1990-02-19', '1' from dual ),
table2(id, f, amount) as (
select 1, 'C', 3000 from dual union all
select 2, 'D', 3500 from dual union all
select 3, 'D', 4000 from dual union all
select 4, 'D', 5000 from dual )
-- query
select sum (case when m.f = 'Converted' then 1 else 0 end) ccount,
sum (case when m.f = 'Do Not Convert' then 1 else 0 end) as ncount,
count(m.id) as totalcount,
sum(case when m.f = 'C' then (amount) end) as converted,
sum(case when m.f = 'D' then (amount) end) as nonconverted,
sum(case when m.f <> '0' then (amount) end) as total,
count(case condition when '1' then 1 end) as condition_1_totalcount,
sum(case condition when '1' then amount end) as condition_1_totalvalue
from table1 ml
join table2 m on m.id = ml.id
where ml.date_ <= systimestamp - interval '30' minute
and amount between 1000 and 25000
I do not fully understand why is this 5 min part in first query. Rows older than 30 minutes are also older than 5 min, so it is superfluous as pointed in comments. And older than current timestamp. If you need to differentiate values this way you can also place this condition in case whens.