Given is a table of stock values for entities saved every day. I would like to get:
Give all entities which are out of stock (Qty = 0) today and were not out of stock the day before.
And this for the day before yesterday compared to the day before the day beford yesterday. And so on.
My approach works, but I have to create the part in the WHERE condition manually.
How about a query for the whole year 2019?
#standardSQL
WITH
TableStockDaily AS (
SELECT TIMESTAMP('2019-10-10 00:00:00 UTC') AS ExportDate, 1001 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-10 00:00:00 UTC') AS ExportDate, 1002 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-10 00:00:00 UTC') AS ExportDate, 1003 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-11 00:00:00 UTC') AS ExportDate, 1001 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-11 00:00:00 UTC') AS ExportDate, 1002 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-11 00:00:00 UTC') AS ExportDate, 1003 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-12 00:00:00 UTC') AS ExportDate, 1001 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-12 00:00:00 UTC') AS ExportDate, 1002 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-12 00:00:00 UTC') AS ExportDate, 1003 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-13 00:00:00 UTC') AS ExportDate, 1001 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-13 00:00:00 UTC') AS ExportDate, 1002 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-13 00:00:00 UTC') AS ExportDate, 1003 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-14 00:00:00 UTC') AS ExportDate, 1001 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-14 00:00:00 UTC') AS ExportDate, 1002 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-14 00:00:00 UTC') AS ExportDate, 1003 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-15 00:00:00 UTC') AS ExportDate, 1001 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-15 00:00:00 UTC') AS ExportDate, 1002 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-15 00:00:00 UTC') AS ExportDate, 1003 AS EntityId, 0 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-16 00:00:00 UTC') AS ExportDate, 1001 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-16 00:00:00 UTC') AS ExportDate, 1002 AS EntityId, 1 as Qty UNION ALL
SELECT TIMESTAMP('2019-10-16 00:00:00 UTC') AS ExportDate, 1003 AS EntityId, 1 as Qty
)
SELECT
sd1.ExportDate AS DateOutOfStock,
sd2.ExportDate AS DateNotOutOfStock,
sd1.EntityId AS EntityId,
sd1.Qty AS Qty1,
sd2.Qty AS Qty2
FROM
TableStockDaily sd1
LEFT JOIN
TableStockDaily sd2
ON
sd1.EntityId = sd2.EntityId
WHERE
sd1.Qty = 0
AND sd2.Qty > 0
AND sd1.ExportDate > sd2.ExportDate
AND
(
(
DATE(sd1.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -1 DAY)
AND DATE(sd1.ExportDate) >= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -2 DAY)
AND DATE(sd2.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -2 DAY)
AND DATE(sd2.ExportDate) > DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -3 DAY)
)
OR
(
DATE(sd1.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -2 DAY)
AND DATE(sd1.ExportDate) >= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -3 DAY)
AND DATE(sd2.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -3 DAY)
AND DATE(sd2.ExportDate) > DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -4 DAY)
)
OR
(
DATE(sd1.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -3 DAY)
AND DATE(sd1.ExportDate) >= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -4 DAY)
AND DATE(sd2.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -4 DAY)
AND DATE(sd2.ExportDate) > DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -5 DAY)
)
OR
(
DATE(sd1.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -4 DAY)
AND DATE(sd1.ExportDate) >= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -5 DAY)
AND DATE(sd2.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -5 DAY)
AND DATE(sd2.ExportDate) > DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -6 DAY)
)
OR
(
DATE(sd1.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -5 DAY)
AND DATE(sd1.ExportDate) >= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -6 DAY)
AND DATE(sd2.ExportDate) <= DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -6 DAY)
AND DATE(sd2.ExportDate) > DATE_ADD(DATE(CURRENT_TIMESTAMP()), INTERVAL -7 DAY)
)
)
I think that you are looking for LAG(). This window function can be used to recover the value of a given column within a group of recrods (here, records sharing the same EntityID) and according to a sorting criteria (here ExportDate):
SELECT *
FROM (
SELECT
EntityId,
ExportDate AS DateOutOfStock,
Qty AS QtyOutOfStock,
LAG(ExportDate) OVER(PARTITION BY EntityId ORDER BY ExportDate) AS DateNotOutOfStock,
LAG(Qty) OVER(PARTITION BY EntityId ORDER BY ExportDate) AS QtyNotOutOfStock
FROM
TableStockDaily sd1
) x
WHERE QtyOutOfStock = 0 AND QtyNotOutOfStock > 0
Related
I need to build a query to check if there are records in the database of 6 consecutive 'Sundays'
SELECT DISTINCT ST1.DATAPU, ST1.NUMCAD, TO_CHAR(ST1.DATAPU, 'DAY') AS DIA
FROM SENIOR.R066SIT ST1
WHERE ST1.DATAPU BETWEEN '01/01/22' AND '23/11/22'
AND ST1.NUMCAD = 10
AND TO_CHAR(ST1.DATAPU, 'FMDAY') = 'DOMINGO' -->which is SUNDAY in English
ORDER BY ST1.DATAPU ASC
With this query above, I get the result of the records as shown in the image below
From Oracle 12, you can use MATCH_RECOGNIZE to perform row-by-row pattern analysis:
SELECT *
FROM (
SELECT DISTINCT
TRUNC(DATAPU) AS datapu,
NUMCAD,
TO_CHAR(DATAPU,'DAY') AS DIA
FROM SENIOR.R066SIT
WHERE DATAPU BETWEEN DATE '2022-01-01' AND DATE '2022-11-23'
AND NUMCAD = 10
AND TRUNC(DATAPU) - TRUNC(DATAPU, 'IW') = 6 -- Sunday
)
MATCH_RECOGNIZE(
ORDER BY datapu
ALL ROWS PER MATCH
PATTERN (first_week consecutive_week{5,})
DEFINE
consecutive_week AS PREV(datapu) + INTERVAL '7' DAY = datapu
)
Which, for the sample data:
CREATE TABLE senior.r066sit(numcad, datapu) AS
SELECT 10, DATE '2022-01-01' + LEVEL - 1 FROM DUAL CONNECT BY LEVEL <= 5*7
UNION ALL
SELECT 10, DATE '2022-04-01' + LEVEL - 1 FROM DUAL CONNECT BY LEVEL <= 7*7
UNION ALL
SELECT 10, DATE '2022-08-01' + LEVEL - 1 FROM DUAL CONNECT BY LEVEL <= 7*7;
Outputs:
DATAPU
NUMCAD
DIA
2022-04-03 00:00:00
10
SUNDAY
2022-04-10 00:00:00
10
SUNDAY
2022-04-17 00:00:00
10
SUNDAY
2022-04-24 00:00:00
10
SUNDAY
2022-05-01 00:00:00
10
SUNDAY
2022-05-08 00:00:00
10
SUNDAY
2022-05-15 00:00:00
10
SUNDAY
2022-08-07 00:00:00
10
SUNDAY
2022-08-14 00:00:00
10
SUNDAY
2022-08-21 00:00:00
10
SUNDAY
2022-08-28 00:00:00
10
SUNDAY
2022-09-04 00:00:00
10
SUNDAY
2022-09-11 00:00:00
10
SUNDAY
2022-09-18 00:00:00
10
SUNDAY
Before Oracle 12, you can use multiple analytic functions in nested sub-queries:
SELECT datapu, numcad,
TO_CHAR(datapu, 'fmDAY') AS dia
FROM (
SELECT datapu, numcad,
COUNT(*) OVER (PARTITION BY grp) AS grp_size
FROM (
SELECT datapu, numcad,
SUM(consecutive) OVER (ORDER BY datapu) AS grp
FROM (
SELECT datapu, numcad,
CASE datapu - LAG(datapu) OVER (ORDER BY datapu)
WHEN 7
THEN 0
ELSE 1
END AS consecutive
FROM (
SELECT DISTINCT
TRUNC(DATAPU) AS datapu,
NUMCAD
FROM SENIOR.R066SIT
WHERE DATAPU BETWEEN DATE '2022-01-01' AND DATE '2022-11-23'
AND NUMCAD = 10
AND TRUNC(DATAPU) - TRUNC(DATAPU, 'IW') = 6 -- Sunday
)
)
)
)
WHERE grp_size >= 6;
fiddle
I'm trying to count the records in my table and grouping them by hour, i'm getting results with my query but I want it to return every hour even if there are no records.
My current query is,
SELECT nvl(count(*),0) AS transactioncount, trunc(date_modified, 'HH') as TRANSACTIONDATE
FROM TABLE
WHERE date_modified between to_date('23-JAN-19 07:00:00','dd-MON-yy hh24:mi:ss') and to_date('24-Jan-19 06:59:59','dd-MON-yy hh24:mi:ss')
group by trunc(date_modified, 'HH');
This returns a result like this,
TRANSACTIONCOUNT | TRANSACTIONDATE
43 | 23-Jan-19 07:00:00
47 | 23-Jan-19 08:00:00
156 | 23-Jan-19 14:00:00
558 | 23-Jan-19 15:00:00
What I want is for it to return every hour between my 2 dates so,
TRANSACTIONCOUNT | TRANSACTIONDATE
43 | 23-Jan-19 07:00:00
47 | 23-Jan-19 08:00:00
0 | 23-Jan-19 09:00:00
0 | 23-Jan-19 10:00:00
0 | 23-Jan-19 11:00:00
0 | 23-Jan-19 12:00:00
0 | 23-Jan-19 13:00:00
156 | 23-Jan-19 14:00:00
558 | 23-Jan-19 15:00:00
--......
0 | 24-Jan-19 00:00:00
0 | 24-Jan-19 01:00:00
0 | 24-Jan-19 02:00:00
--and so on
To fill the holes in the transaction hours you create first a complete table of hours.
You may use Recursive Subquery Factoring to do it
WITH hour_table(TRANSACTIONDATE) AS (
SELECT to_date('23-JAN-19 07:00:00','dd-MON-yy hh24:mi:ss') /* init hour here */
FROM DUAL
UNION ALL
SELECT TRANSACTIONDATE + 1/24
FROM hour_table
WHERE TRANSACTIONDATE + 1/24 < to_date('24-JAN-19 06:59:59','dd-MON-yy hh24:mi:ss') /* limit here */
)
select * from hour_table;
TRANSACTIONDATE
-------------------
23.01.2019 07:00:00
23.01.2019 08:00:00
...
24.01.2019 05:00:00
24.01.2019 06:00:00
Note that you use the staring and ending date in this query, the starting date must be exact an hour.
Next step is as simple as to outer join this hour table to your aggregation and set the default value for the missing hours with NVL.
with hour_table(TRANSACTIONDATE) AS (
SELECT to_date('23-JAN-19 07:00:00','dd-MON-yy hh24:mi:ss') /* init hour here */
FROM DUAL
UNION ALL
SELECT TRANSACTIONDATE + 1/24
FROM hour_table
WHERE TRANSACTIONDATE + 1/24 < to_date('24-JAN-19 06:59:59','dd-MON-yy hh24:mi:ss') /* limit */
),
agg as (
SELECT nvl(count(*),0) AS transactioncount, trunc(date_modified, 'HH') as TRANSACTIONDATE
FROM "TABLE"
WHERE date_modified between to_date('23-JAN-19 07:00:00','dd-MON-yy hh24:mi:ss') and to_date('24-Jan-19 06:59:59','dd-MON-yy hh24:mi:ss')
group by trunc(date_modified, 'HH')
)
select t.TRANSACTIONDATE, nvl(transactioncount,0) transactioncount
from hour_table t
left outer join agg a
on t.TRANSACTIONDATE = a.TRANSACTIONDATE
order by 1;
You might consider using the following with CONNECT BY level logic :
SELECT sum(transactioncount) as transactioncount, transactiondate
FROM
(
with "TABLE"(date_modified) as
(
SELECT timestamp'2019-01-23 08:00:00' FROM dual union all
SELECT timestamp'2019-01-23 08:30:00' FROM dual union all
SELECT timestamp'2019-01-23 09:00:00' FROM dual union all
SELECT timestamp'2019-01-24 05:01:00' FROM dual
)
SELECT nvl(count(*),0) AS transactioncount, trunc(date_modified, 'hh24') as transactiondate
FROM "TABLE" t
GROUP BY trunc(date_modified, 'HH24')
UNION ALL
SELECT 0, timestamp'2019-01-23 07:00:00' + ( level - 1 )/24
FROM dual
CONNECT BY level <= 24 * extract( day from
timestamp'2019-01-24 06:59:59'-
timestamp'2019-01-23 07:00:00') +
extract( hour from
timestamp'2019-01-24 06:59:59'-
timestamp'2019-01-23 07:00:00') + 1
)
GROUP BY transactiondate
ORDER BY transactiondate
Rextester Demo
I`m stuck a bit with understanding of my further actions while performing queries.
I have two tables "A"(date, response, b_id) and "B"(id, country). I need to count hourly ratio of a number of entries where response exists to the total number of entries on a specific date. The final selection should consist of columns "hour", "ratio".
SELECT COUNT(*) FROM A WHERE RESPONSE IS NOT NULL//counting entries with response
SELECT COUNT(*) FROM A//counting total number of entries
How to count the ratio? Should I create a separate variable for it?
How to count for each hour on a day? Should I make smth like a loop? + How can I get the "hour" part of a date?
What is the best way to select the hours and counted ratio? Should I make a separate table for it?
I`m rather new to make complex queries, so I woud be happy for every kind of help
You can do this as:
select to_char(datecol, 'HH24') as hour,
count(response) as has_response, count(*) as total,
count(response) / count(*) as ratio
from a
where datecol >= date '2018-09-18' and datecol < date '2018-09-19'
group by to_char(datecol, 'HH24');
You can also do this using avg() -- which is also fun:
select to_char(datecol, 'HH24'),
avg(case when response is not null then 1.0 else 0 end) as ratio
from a
where datecol >= date '2018-09-18' and datecol < date '2018-09-19'
group by to_char(datecol, 'HH24')
In this case, that requires more typing, though.
SQL Fiddle
Oracle 11g R2 Schema Setup:
CREATE TABLE A ( dt, response, b_id ) AS
SELECT DATE '2018-09-18' + INTERVAL '00:00' HOUR TO MINUTE, NULL, 1 FROM DUAL UNION ALL
SELECT DATE '2018-09-18' + INTERVAL '00:10' HOUR TO MINUTE, 'A', 1 FROM DUAL UNION ALL
SELECT DATE '2018-09-18' + INTERVAL '00:20' HOUR TO MINUTE, 'B', 1 FROM DUAL UNION ALL
SELECT DATE '2018-09-18' + INTERVAL '01:00' HOUR TO MINUTE, 'C', 1 FROM DUAL UNION ALL
SELECT DATE '2018-09-18' + INTERVAL '01:10' HOUR TO MINUTE, 'D', 1 FROM DUAL UNION ALL
SELECT DATE '2018-09-18' + INTERVAL '02:00' HOUR TO MINUTE, NULL, 1 FROM DUAL UNION ALL
SELECT DATE '2018-09-18' + INTERVAL '03:00' HOUR TO MINUTE, 'E', 1 FROM DUAL UNION ALL
SELECT DATE '2018-09-18' + INTERVAL '05:10' HOUR TO MINUTE, 'F', 1 FROM DUAL;
Query 1:
SELECT b_id,
TO_CHAR( TRUNC( dt, 'HH' ), 'YYYY-MM-DD HH24:MI:SS' ) AS hour,
COUNT(RESPONSE) AS total_response_per_hour,
COUNT(*) AS total_per_hour,
total_response_per_day,
total_per_day,
COUNT(response) / total_response_per_day AS ratio_for_responses,
COUNT(*) / total_per_day AS ratio
FROM (
SELECT A.*,
COUNT(RESPONSE) OVER ( PARTITION BY b_id, TRUNC( dt ) ) AS total_response_per_day,
COUNT(*) OVER ( PARTITION BY b_id, TRUNC( dt ) ) AS total_per_day
FROM A
)
GROUP BY
b_id,
total_per_day,
total_response_per_day,
TRUNC( dt, 'HH' )
ORDER BY
TRUNC( dt, 'HH' )
Results:
| B_ID | HOUR | TOTAL_RESPONSE_PER_HOUR | TOTAL_PER_HOUR | TOTAL_RESPONSE_PER_DAY | TOTAL_PER_DAY | RATIO_FOR_RESPONSES | RATIO |
|------|---------------------|-------------------------|----------------|------------------------|---------------|---------------------|-------|
| 1 | 2018-09-18 00:00:00 | 2 | 3 | 6 | 8 | 0.3333333333333333 | 0.375 |
| 1 | 2018-09-18 01:00:00 | 2 | 2 | 6 | 8 | 0.3333333333333333 | 0.25 |
| 1 | 2018-09-18 02:00:00 | 0 | 1 | 6 | 8 | 0 | 0.125 |
| 1 | 2018-09-18 03:00:00 | 1 | 1 | 6 | 8 | 0.16666666666666666 | 0.125 |
| 1 | 2018-09-18 05:00:00 | 1 | 1 | 6 | 8 | 0.16666666666666666 | 0.125 |
SELECT withResponses.hour,
withResponses.cnt AS withResponse,
alls.cnt AS AllEntries,
(withResponses.cnt / alls.cnt) AS ratio
FROM
( SELECT to_char(d, 'DD-MM-YY - HH24') || ':00 to :59 ' hour,
count(*) AS cnt
FROM A
WHERE RESPONSE IS NOT NULL
GROUP BY to_char(d, 'DD-MM-YY - HH24') || ':00 to :59 ' ) withResponses,
( SELECT to_char(d, 'DD-MM-YY - HH24') || ':00 to :59 ' hour,
count(*) AS cnt
FROM A
GROUP BY to_char(d, 'DD-MM-YY - HH24') || ':00 to :59 ' ) alls
WHERE alls.hour = withResponses.hour ;
SQLFiddle: http://sqlfiddle.com/#!4/c09b9/2
I have a table with Items with
Item_id, Item_time, Item_numbers
1 2017-01-01 18:00:00 2
2 2017-01-01 18:10:00 2
3 2017-01-01 19:10:00 3
I want to group the items by hourly for some specific time (between 9 to 3 for each day) and in case if there is no entry for the particular hours then it should it be a 0.
Desired Output:
Item_time Item_numbers
2017-01-01 18:00:00 4
2017-01-01 19:00:00 3
2017-01-01 20:00:00 0
with hour_items as (select date_trunc('hour', item_time) "hour",
avg(item_numbers) as value from items where item_id=2 and
fact_time::date= '2017-01-01' group by hour) select hour, value from
hour_items where EXTRACT(HOUR FROM hour) >= '9' and EXTRACT(HOUR FROM
> hour) < '15'.
The above query groups them correctly but the where the hour is missing, there is no entry. Though it should be an entry with a 0 as stated in the desired output.
This should do.
We get all the distinct days (CTE dates), then we generate hours for each of those dates (CTE hours) and finally we left join our data on "per our" basis.
with sample_data as (
select 1 as item_id, '2018-01-01 12:03:15'::timestamp as item_time, 2 as item_numbers
union all
select 2 as item_id, '2018-01-01 12:41:15'::timestamp as item_time, 1 as item_numbers
union all
select 3 as item_id, '2018-01-01 17:41:15'::timestamp as item_time, 2 as item_numbers
union all
select 4 as item_id, '2018-01-01 19:41:15'::timestamp as item_time, 2 as item_numbers
),
dates as (
select distinct item_time::date
from sample_data
),
hours as (
select item_time + interval '1 hour' * a as hour
from dates
cross join generate_series(0,23) a
)
select h.hour, sum(coalesce(sd.item_numbers,0))
from hours h
left join sample_data sd on h.hour = date_trunc('hour', sd.item_time)
where extract(hour from hour) between 9 and 17
group by h.hour
order by h.hour
I would like to get a table of months between two dates with a fraction of each month that the two dates cover.
For example with a start date of 15/01/2017 and end date of 01/03/2017 it would output:
01/2017 : 0.5483..
02/2017 : 1
03/2017: 0.0322..
where for January and March the calculations are 17/31 and 1/31 respectively. I currently have the query:
WITH dates_between as (SELECT ADD_MONTHS(TRUNC(TO_DATE(:givenStartDate,'dd/mm/yyyy'), 'MON'), ROWNUM - 1) date_out
FROM DUAL
CONNECT BY ADD_MONTHS(TRUNC(TO_DATE(:givenStartDate,'dd/mm/yyyy'), 'MON'), ROWNUM - 1)
<= TRUNC(TO_DATE(:givenEndDate,'dd/mm/yyyy'), 'MON')
)
select * from dates_between
This outputs each month between two dates and formats it to the start of the month. I just need another column to give me the fraction the start and end dates cover. I'm not sure of a way to do this without it getting messy.
The months_between() function "calculates the fractional portion of the result based on a 31-day month". That means that if your range starts or ends in a month that doesn't have 31 days, the fraction you get might not be quite what you expect:
select months_between(date '2017-04-02', date '2017-04-01') as calc from dual
CALC
----------
.0322580645
... which is 1/31, not 1/30. To get 0.0333... instead you'd need to calculate the number of days in each month, at least for the first and last month. This uses a recursive CTE (11gR2+) to get the months, using a couple of date ranges provided by another CTE as a demo to show the difference (you can use a hierarchical query too of course):
with ranges (id, start_date, end_date) as (
select 1, date '2017-01-15', date '2017-03-01' from dual
union all select 2, date '2017-01-31', date '2017-03-01' from dual
union all select 3, date '2017-02-28', date '2017-04-01' from dual
),
months (id, month_start, month_days, range_start, range_end) as (
select id,
trunc(start_date, 'MM'),
extract(day from last_day(start_date)),
start_date,
end_date
from ranges
union all
select id,
month_start + interval '1' month,
extract(day from last_day(month_start + interval '1' month)),
range_start,
range_end
from months
where month_start < range_end
)
select id,
to_char(month_start, 'YYYY-MM-DD') as month_start,
month_days,
case when month_start = trunc(range_start, 'MM')
then month_days - extract(day from range_start) + 1
when month_start = trunc(range_end, 'MM')
then extract(day from range_end)
else month_days end as range_days,
(case when month_start = trunc(range_start, 'MM')
then month_days - extract(day from range_start) + 1
when month_start = trunc(range_end, 'MM')
then extract(day from range_end)
else month_days end) / month_days as fraction
from months
order by id, month_start;
which gets:
ID MONTH_STAR MONTH_DAYS RANGE_DAYS FRACTION
------ ---------- ---------- ---------- --------
1 2017-01-01 31 17 0.5483
1 2017-02-01 28 28 1
1 2017-03-01 31 1 0.0322
2 2017-01-01 31 1 0.0322
2 2017-02-01 28 28 1
2 2017-03-01 31 1 0.0322
3 2017-02-01 28 1 0.0357
3 2017-03-01 31 31 1
3 2017-04-01 30 1 0.0333
The first CTE ranges is just the demo data. The second, recursive, CTE months generates the start and number of days in each month, while keeping track of the original range dates too. The final query just calculates the fractions based on the number of days in the month in the range against the number of days in that month overall.
The month_days and range_days are only shown in the output so you can see what the calculation is based on, you can obviously omit those from your actual result, and format the month start date however you want.
With your original single pair of bind variables the equivalent would be:
with months (month_start, month_days, range_start, range_end) as (
select trunc(to_date(:givenstartdate, 'DD/MM/YYYY'), 'MM'),
extract(day from last_day(to_date(:givenstartdate, 'DD/MM/YYYY'))),
to_date(:givenstartdate, 'DD/MM/YYYY'),
to_date(:givenenddate, 'DD/MM/YYYY')
from dual
union all
select month_start + interval '1' month,
extract(day from last_day(month_start + interval '1' month)),
range_start,
range_end
from months
where month_start < range_end
)
select to_char(month_start, 'MM/YYYY') as month,
(case when month_start = trunc(range_start, 'MM')
then month_days - extract(day from range_start) + 1
when month_start = trunc(range_end, 'MM')
then extract(day from range_end)
else month_days end) / month_days as fraction
from months
order by month_start;
MONTH FRACTION
------- --------
01/2017 0.5483
02/2017 1
03/2017 0.0322
Here's how I would do it (n.b. I have expanded your dates_between to work against multiple rows, purely for demonstration purposes. If you're only working with a single set of parameters, you wouldn't need to do that):
WITH params AS (SELECT 1 ID, '15/01/2017' givenstartdate, '01/03/2017' givenenddate FROM dual UNION ALL
SELECT 2 ID, '15/01/2017' givenstartdate, '23/01/2017' givenenddate FROM dual UNION ALL
SELECT 3 ID, '01/01/2017' givenstartdate, '07/04/2017' givenenddate FROM dual),
dates_between AS (SELECT ID,
to_date(givenstartdate, 'dd/mm/yyyy') givenstartdate,
to_date(givenenddate, 'dd/mm/yyyy') givenenddate,
add_months(trunc(to_date(givenstartdate, 'dd/mm/yyyy'), 'MON'), LEVEL - 1) start_of_month,
last_day(add_months(trunc(to_date(givenstartdate, 'dd/mm/yyyy'), 'MON'), LEVEL - 1)) end_of_month
FROM params
CONNECT BY add_months(trunc(to_date(givenstartdate, 'dd/mm/yyyy'), 'MON'), LEVEL - 1) <=
trunc(to_date(givenenddate, 'dd/mm/yyyy'), 'MON')
AND PRIOR ID = ID
AND PRIOR sys_guid() IS NOT NULL)
SELECT ID,
givenstartdate,
givenenddate,
start_of_month date_out,
end_of_month,
months_between(LEAST(givenenddate, end_of_month) + 1, GREATEST(start_of_month, givenstartdate))
FROM dates_between;
ID GIVENSTARTDATE GIVENENDDATE DATE_OUT END_OF_MONTH DIFF
1 15/01/2017 01/03/2017 01/01/2017 31/01/2017 0.54838709
1 15/01/2017 01/03/2017 01/02/2017 28/02/2017 1
1 15/01/2017 01/03/2017 01/03/2017 31/03/2017 0.03225806
2 15/01/2017 23/01/2017 01/01/2017 31/01/2017 0.29032258
3 01/01/2017 07/04/2017 01/01/2017 31/01/2017 1
3 01/01/2017 07/04/2017 01/02/2017 28/02/2017 1
3 01/01/2017 07/04/2017 01/03/2017 31/03/2017 1
3 01/01/2017 07/04/2017 01/04/2017 30/04/2017 0.22580645
N.B. You may need to add a case statement to decide whether you want to add 1 or not to the diff calculation, based on your requirements.
Try this
For first month, I have calculated remaining days / total days and for last month, I subtracted it by 1 to get days passed / total days.
DBFiddle Demo
WITH tbl AS
(SELECT date '2017-01-15' AS givenStartDate
,date '2017-03-01' AS givenEndDate
FROM dual
)
SELECT ADD_MONTHS(TRUNC(givenStartDate, 'MON'), ROWNUM - 1) AS date_out ,
CASE
WHEN
rownum - 1 = 0
THEN months_between(last_day(givenStartDate), givenStartDate)
WHEN ADD_MONTHS(TRUNC(givenStartDate, 'MON'), ROWNUM - 1) = TRUNC(givenEndDate, 'MON')
THEN 1 - (months_between(last_day(givenEndDate), givenEndDate))
ELSE 1
END AS perc
FROM tbl
CONNECT BY ADD_MONTHS(TRUNC(givenStartDate, 'MON'), ROWNUM - 1)
<= TRUNC(givenEndDate, 'MON');
Output
+-----------+-------------------------------------------+
| DATE_OUT | PERC |
+-----------+-------------------------------------------+
| 01-JAN-17 | .5161290322580645161290322580645161290323 |
| 01-FEB-17 | 1 |
| 01-MAR-17 | .0322580645161290322580645161290322580645 |
+-----------+-------------------------------------------+