I have a code to count every route from bus by departure date, but i need to count the day before of the departure on weekdays: Wednesday, Friday and Sunday.
For example if there is 1 bus on the route 148 and date: "Tuesday, 2019-02-05" , i expecting this number count in "Wednesday, 2019-02-06" with the count of this day.
This is the normal input to count by date:
Select departureDate, countif(Route)
from table
group by departureDate
this query gives me the actual Results:
departureDate countif(Route)
Mon 04-feb-19 1
Tue 05-feb-19 1
Wed 06-feb-19 2
Thu 07-feb-19 1
Fri 08-feb-19 1
Sat 09-feb-19 2
Sun 10-feb-19 2
But i am expecting these results:
departureDate countif(Route) explanation
Mon 04-feb-19 0 No count
Tue 05-feb-19 0 No count
Wed 06-feb-19 3 1 + 1 + 2
Thu 07-feb-19 0 No count
Fri 08-feb-19 2 1 + 1
Sat 09-feb-19 0 No count
Sun 10-feb-19 4 2 + 2
Below is for BigQuery Standard SQL
#standardSQL
SELECT
departureDate,
IF(EXTRACT(DAYOFWEEK FROM departureDate) IN (1, 4, 6), ANY_VALUE(cnt), 0) cnt
FROM (
SELECT
departureDate,
COUNT(1) OVER(ORDER BY UNIX_DATE(departureDate) RANGE BETWEEN 1 PRECEDING AND CURRENT ROW) cnt
FROM `project.dataset.table`
WHERE Route = 148
)
GROUP BY departureDate
Should be good start for you
You can test, play with above using sample data as in below dummy example that attempts to resemble your example
#standardSQL
WITH `project.dataset.table` AS (
SELECT DATE '2019-02-04' departureDate, 148 route UNION ALL
SELECT '2019-02-05', 148 UNION ALL
SELECT '2019-02-06', 148 UNION ALL
SELECT '2019-02-06', 148 UNION ALL
SELECT '2019-02-07', 148 UNION ALL
SELECT '2019-02-08', 148 UNION ALL
SELECT '2019-02-09', 148 UNION ALL
SELECT '2019-02-09', 148 UNION ALL
SELECT '2019-02-10', 148 UNION ALL
SELECT '2019-02-10', 148
)
SELECT
departureDate,
IF(EXTRACT(DAYOFWEEK FROM departureDate) IN (1, 4, 6), ANY_VALUE(cnt), 0) cnt
FROM (
SELECT
departureDate,
COUNT(1) OVER(ORDER BY UNIX_DATE(departureDate) RANGE BETWEEN 1 PRECEDING AND CURRENT ROW) cnt
FROM `project.dataset.table`
WHERE Route = 148
)
GROUP BY departureDate
-- ORDER BY departureDate
with result
Row departureDate cnt
1 2019-02-04 0
2 2019-02-05 0
3 2019-02-06 3
4 2019-02-07 0
5 2019-02-08 2
6 2019-02-09 0
7 2019-02-10 4
Related
I have a dataset within a date range which has three columns, Product_type, date and metric. For a given product_type, data is not available for all days. For the missing rows, we would like to do a forward date fill for next n days using the last value of the metric.
Product_type
date
metric
A
2019-10-01
10
A
2019-10-02
12
A
2019-10-03
15
A
2019-10-04
5
A
2019-10-05
5
A
2019-10-06
5
A
2019-10-16
12
A
2019-10-17
23
A
2019-10-18
34
Here, the data from 2019-10-04 to 2019-10-06, has been forward filled. There might be bigger gaps in the dates, but we only want to fill the first n days.
Here, n=2, so rows 5 and 6 has been forward filled.
I am not sure how to implement this logic in SQL.
Here's one option. Read comments within code.
Sample data:
SQL> WITH
2 test (product_type, datum, metric)
3 AS
4 (SELECT 'A', DATE '2019-10-01', 10 FROM DUAL
5 UNION ALL
6 SELECT 'A', DATE '2019-10-02', 12 FROM DUAL
7 UNION ALL
8 SELECT 'A', DATE '2019-10-03', 15 FROM DUAL
9 UNION ALL
10 SELECT 'A', DATE '2019-10-04', 5 FROM DUAL
11 UNION ALL
12 SELECT 'A', DATE '2019-10-16', 12 FROM DUAL
13 UNION ALL
14 SELECT 'A', DATE '2019-10-18', 23 FROM DUAL),
Query begins here:
15 temp
16 AS
17 -- CB_FWD_FILL = 1 if difference between two consecutive dates is larger than 1 day
18 -- (i.e. that's the gap to be forward filled)
19 (SELECT product_type,
20 datum,
21 metric,
22 LEAD (datum) OVER (PARTITION BY product_type ORDER BY datum)
23 next_datum,
24 CASE
25 WHEN LEAD (datum)
26 OVER (PARTITION BY product_type ORDER BY datum)
27 - datum >
28 1
29 THEN
30 1
31 ELSE
32 0
33 END
34 cb_fwd_fill
35 FROM test)
36 -- original data from the table
37 SELECT product_type, datum, metric FROM test
38 UNION ALL
39 -- DATUM is the last date which is OK; add LEVEL pseudocolumn to it to fill the gap
40 -- with PAR_N number of rows
41 SELECT product_type, datum + LEVEL, metric
42 FROM (SELECT product_type, datum, metric
43 FROM (-- RN = 1 means that that's the first gap in data set - that's the one
44 -- that has to be forward filled
45 SELECT product_type,
46 datum,
47 metric,
48 ROW_NUMBER ()
49 OVER (PARTITION BY product_type ORDER BY datum) rn
50 FROM temp
51 WHERE cb_fwd_fill = 1)
52 WHERE rn = 1)
53 CONNECT BY LEVEL <= &par_n
54 ORDER BY datum;
Result:
Enter value for par_n: 2
PRODUCT_TYPE DATUM METRIC
--------------- ---------- ----------
A 2019-10-01 10
A 2019-10-02 12
A 2019-10-03 15
A 2019-10-04 5
A 2019-10-05 5 --> newly added
A 2019-10-06 5 --> rows
A 2019-10-16 12
A 2019-10-18 23
8 rows selected.
SQL>
Another solution:
WITH test (product_type, datum, metric) AS
(
SELECT 'A', DATE '2019-10-01', 10 FROM DUAL
UNION ALL
SELECT 'A', DATE '2019-10-02', 12 FROM DUAL
UNION ALL
SELECT 'A', DATE '2019-10-03', 15 FROM DUAL
UNION ALL
SELECT 'A', DATE '2019-10-04', 5 FROM DUAL
UNION ALL
SELECT 'A', DATE '2019-10-16', 12 FROM DUAL
UNION ALL
SELECT 'A', DATE '2019-10-18', 23 FROM DUAL
),
minmax(mindatum, maxdatum) AS (
SELECT MIN(datum), max(datum) from test
),
alldates (datum, product_type) AS
(
SELECT mindatum + level - 1, t.product_type FROM minmax,
(select distinct product_type from test) t
connect by mindatum + level <= (select maxdatum from minmax)
),
grouped as (
select a.datum, a.product_type, t.metric,
count(t.product_type) over(partition by a.product_type order by a.datum) as grp
from alldates a
left join test t on t.datum = a.datum
),
final_table as (
select g.datum, g.product_type, g.grp, g.rn,
last_value(g.metric ignore nulls) over(partition by g.product_type order by g.datum) as metric
from (
select g.*, row_number() over(partition by product_type, grp order by datum) - 1 as rn
from grouped g
) g
)
select datum, product_type, metric
from final_table
where rn <= &par_n
order by datum
;
I'm working with Oracle and I have a table with a column of type TIMESTAMP. I was wondering how can I extract the records from last 4 weeks of activity on the database, partitioned by week.
Following rows are inserted on week 1
kc 2 04-10-2021
vc 3 06-10-2021
vk 4 07-10-2021
Following rows are inserted on week2
cv 1 12-10-2021
ck 5 14-10-2021
Following rows are inserted on week3
vv 7 19-10-2021
Following rows are inserted on week4
vx 7 29-10-2021
Table now has
SQL>select * from tab;
NAME VALUE TIMESTAMP
-------------------- ----------
kc 2 04-10-2021
vc 3 06-10-2021
vk 4 07-10-2021
cv 1 12-10-2021
ck 5 14-10-2021
vv 7 19-10-2021
vx 7 29-10-2021
I would like a query which would give me the number of rows added each week, in the last 4 weeks.
This is what I would like to see
numofrows week
--------- -----
3 1
2 2
1 3
1 4
One option is to use to_char function and its iw parameter:
SQL> with test (name, datum) as
2 (select 'kc', date '2021-10-04' from dual union all
3 select 'vc', date '2021-10-06' from dual union all
4 select 'vk', date '2021-10-07' from dual union all
5 select 'cv', date '2021-10-12' from dual union all
6 select 'ck', date '2021-10-14' from dual union all
7 select 'vv', date '2021-10-19' from dual union all
8 select 'vx', DATE '2021-10-29' from dual
9 )
10 select to_char(datum, 'iw') week,
11 count(*)
12 from test
13 where datum >= add_months(sysdate, -1) --> the last month
14 group by to_char(datum, 'iw');
WE COUNT(*)
-- ----------
42 1
43 1
40 3
41 2
SQL>
Line #13: I intentionally used "one month" instead of "4 weeks" as I thought (maybe wrongly) that you, actually, want that (you know, "a month has 4 weeks" - not exactly, but close, sometimes not close enough).
If you want 4 weeks, what is that, then? Sysdate minus 28 days (as every week has 7 days)? Then you'd modify line #13 to
where datum >= trunc(sysdate - 4*7)
Or, maybe it is really the last 4 weeks:
SQL> with test (name, datum) as
2 (select 'kc', date '2021-10-04' from dual union all
3 select 'vc', date '2021-10-06' from dual union all
4 select 'vk', date '2021-10-07' from dual union all
5 select 'cv', date '2021-10-12' from dual union all
6 select 'ck', date '2021-10-14' from dual union all
7 select 'vv', date '2021-10-19' from dual union all
8 select 'vx', DATE '2021-10-29' from dual
9 ),
10 temp as
11 (select to_char(datum, 'iw') week,
12 count(*) cnt,
13 row_number() over (order by to_char(datum, 'iw') desc) rn
14 from test
15 group by to_char(datum, 'iw')
16 )
17 select week, cnt
18 from temp
19 where rn <= 4
20 order by week;
WE CNT
-- ----------
40 3
41 2
42 1
43 1
SQL>
Now you have several options, see which one fits the best (if any).
I "simulated" missing data (see TEST CTE), created a calendar (calend) and ... did the job. Read comments within code:
SQL> with test (name, datum) as
2 -- sample data
3 (select 'vv', date '2021-10-19' from dual union all
4 select 'vx', DATE '2021-10-29' from dual
5 ),
6 calend as
7 -- the last 31 days; 4 weeks are included, obviously
8 (select max_datum - level + 1 datum
9 from (select max(a.datum) max_datum from test a)
10 connect by level <= 31
11 ),
12 joined as
13 -- joined TEST and CALEND data
14 (select to_char(c.datum, 'iw') week,
15 t.name
16 from calend c left join test t on t.datum = c.datum
17 ),
18 last4 as
19 -- last 4 weeks
20 (select week, count(name) cnt,
21 row_number() over (order by week desc) rn
22 from joined
23 group by week
24 )
25 select week, cnt
26 from last4
27 where rn <= 4
28 order by week;
WE CNT
-- ----------
40 0
41 0
42 1
43 1
SQL>
I have a table from which I am trying to return the quantity per day that the article was in the system.
Example is in table Bestand the are multiple palletes of a different articles that each have a Booking In and Out date; I am try to find out the Min and Max amount of stock that was in the system per article and month.
My thinking is that if I can return the stock quantity for each day and then read out the Min and Max values.
The Timespan would be set at the time of running the SQL and the articles would be fixed.
To find out the quantity for each day I have used the following SQL:
SELECT DISTINCT
a.artbez1 AS Artikelbezeichnung,
b.artikelnr AS Artikelnummer,
SUM(CASE WHEN TO_DATE('2019-11-01 00:00:00', 'YYYY-MM-DD HH24:MI:SS') BETWEEN b.neu_datum AND b.aender_datum THEN 1 * b.menge_ist ELSE 0 END) AS "01 Nov 2019"
FROM
artikel a, bestand b
WHERE
b.artikelnr IN ('273632002', .... (huge long list of numbers) ....)
AND b.artikelnr = a.artikelnr
GROUP BY
a.artbez1, b.artikelnr;
This returns for example:
ARTIKELBEZEICHNUNG
ARTIKELNUMMER
01 Nov 2019
SC-4400.CW
220450002
39
S-320.FK120
220502004
0
H-595.FK120
220800004
35
AC-548.FK209
220948032
0
AS-6800.CW
221355002
20
I would like return this for each day of the Month and then from that return the Min and Max Value for each Article
I have the following SQL to return the days of a given Month and was wondering if anyone had any ideas on how they could be combined (If at all possible):
SELECT to_date('01.11.2019','dd.mm.yyyy')+LEVEL-1
FROM dual
CONNECT BY LEVEL <= TO_CHAR(LAST_DAY(to_date('01.11.2019','dd.mm.yyyy')),'DD')
DATES
2019-11-01 00:00:00
2019-11-02 00:00:00
2019-11-03 00:00:00
2019-11-04 00:00:00
2019-11-05 00:00:00
2019-11-06 00:00:00
2019-11-07 00:00:00
The result i am try to get would be something like:
ARTIKELBEZEICHNUNG
ARTIKELNUMMER
Nov 19 Min
Nov 19 Max
SC-4400.CW
220450002
5
39
S-320.FK120
220502004
0
15
H-595.FK120
220800004
2
35
AC-548.FK209
220948032
0
0
AS-6800.CW
221355002
10
20
Is this at all possible in SQL?
Thanks for taking the time to read my post.
JeRi
You can use a partitioned outer join:
WITH calendar ( day ) AS (
SELECT DATE '2019-11-01'
FROM DUAL
UNION ALL
SELECT day + INTERVAL '1' DAY
FROM calendar
WHERE day < LAST_DAY( DATE '2019-11-01' )
),
daily_totals ( artbez1, Artikelnr, Day, total_menge_ist ) AS (
SELECT MAX( ab.artbez1 ),
ab.artikelnr,
c.day,
COALESCE( SUM( ab.menge_ist ), 0 )
FROM calendar c
LEFT OUTER JOIN
( SELECT a.artikelnr,
a.artbez1,
b.neu_datum,
b.aender_datum,
b.menge_ist
FROM artikel a
LEFT JOIN bestand b
ON ( a.artikelnr = b.artikelnr )
-- WHERE b.artikelnr IN ('273632002', .... (huge long list of numbers) ....)
) ab
PARTITION BY ( ab.artikelnr, ab.artbez1 )
ON ( c.day BETWEEN ab.neu_datum AND ab.aender_datum )
GROUP BY ab.artikelnr, c.day
)
SELECT MAX( artbez1 ) AS Artikelbezeichnung,
artikelnr AS Artikelnummer,
TRUNC( day, 'MM' ) AS month,
MIN( total_menge_ist ) AS min_total_menge_ist,
MAX( total_menge_ist ) AS max_total_menge_ist
FROM daily_totals
GROUP BY artikelnr, TRUNC( day, 'MM' );
Which, for the sample data:
CREATE TABLE artikel ( artikelnr, artbez1 ) AS
SELECT 220450002, 'SC-4400.CW' FROM DUAL UNION ALL
SELECT 220502004, 'S-320.FK120' FROM DUAL UNION ALL
SELECT 220800004, 'H-595.FK120' FROM DUAL UNION ALL
SELECT 220948032, 'AC-548.FK209' FROM DUAL UNION ALL
SELECT 221355002, 'AS-6800.CW' FROM DUAL;
CREATE TABLE bestand ( artikelnr, neu_datum, aender_datum, menge_ist ) AS
SELECT 220450002, DATE '2019-10-30', DATE '2019-11-01', 20 FROM DUAL UNION ALL
SELECT 220450002, DATE '2019-11-01', DATE '2019-11-05', 19 FROM DUAL UNION ALL
SELECT 220502004, DATE '2019-11-05', DATE '2019-11-03', 5 FROM DUAL UNION ALL
SELECT 220800004, DATE '2019-11-01', DATE '2019-11-15', 35 FROM DUAL UNION ALL
SELECT 221355002, DATE '2019-10-20', DATE '2019-11-05', 5 FROM DUAL UNION ALL
SELECT 221355002, DATE '2019-10-25', DATE '2019-11-10', 5 FROM DUAL UNION ALL
SELECT 221355002, DATE '2019-10-28', DATE '2019-11-13', 5 FROM DUAL UNION ALL
SELECT 221355002, DATE '2019-10-30', DATE '2019-11-15', 5 FROM DUAL UNION ALL
SELECT 221355002, DATE '2019-11-05', DATE '2019-11-20', 5 FROM DUAL;
Outputs:
ARTIKELBEZEICHNUNG | ARTIKELNUMMER | MONTH | MIN_TOTAL_MENGE_IST | MAX_TOTAL_MENGE_IST
:----------------- | ------------: | :------------------ | ------------------: | ------------------:
SC-4400.CW | 220450002 | 2019-11-01 00:00:00 | 0 | 39
S-320.FK120 | 220502004 | 2019-11-01 00:00:00 | 0 | 0
AC-548.FK209 | 220948032 | 2019-11-01 00:00:00 | 0 | 0
H-595.FK120 | 220800004 | 2019-11-01 00:00:00 | 0 | 35
AS-6800.CW | 221355002 | 2019-11-01 00:00:00 | 0 | 25
db<>fiddle here
I need data for all 24 months of data even with missing months.
sample data
id custname reportdate sales
1 xx 31-JAN-17 1256
1 xx 31-MAR-17 3456
1 xx 30-JUN-17 5678
1 xx 31-DEC-17 6785
2 xx 31-JAN-17 1223
2 xx 31-APR-17 3435
2 xx 30-JUN-17 6777
2 xx 31-DEC-17 9643
what i need as a output
id custname reportdate sales
1 xx JAN-17 1256
1 xx FEB-17 <null>
1 xx MAR-17 3456
.....................................
.....................................
1 xx DEC-17 6785
And similarly for id 2 ....
Tried something like this without any luck
select CUSTNAME, reportdate, sales from
(
select TRIM( LEADING '0' FROM TO_CHAR( statementdate, 'YYYY-MM') ) AS REPORTDATE mm, CUSTNAME
froM MYTABLE) SALES,
(
select to_char(date '2017-01-01' + numtoyminterval(level,'month'), 'mm') MonthName
--i actually need format as MON-Last 2 digit of year eg:JAN-17
from dual
connect by level <= 24) ALLMONTHS
where mm = MonthName(+)
also tried with CTE and i cant use my_year.year_month CTE with outer join
my_year as (
select date '2017-01-31' start_date,date '2018-12-31' end_date from dual
)
select (to_char(add_months(trunc(start_date,'mm'),level - 1),'yyyy')||'-'||(to_char(add_months(trunc(start_date,'mm'),level - 1),'mm'))) year_month
from my_year
connect by trunc(end_date,'mm') >= add_months(trunc(start_date,'mm'),level - 1);
select id, customername, reportdate, sales,
TRIM( LEADING '0' FROM TO_CHAR( reportdate, 'YYYY-MM') ) AS stmntdate
from my_oracle_tbl a
where a.stmntdate = my_year.year_month (+)
also tried this as recommended by #Littlefoot, which isnt working
WITH mydates AS (
select LAST_DAY(add_months(date '2017-01-01', level - 1)) as mth, min_id,min_custname
from (
select min(id) as min_id, min(CUSTNAME) as min_custname
from my_oracle_tbl
)
connect by level <= 24)
select
nvl(t.id, a.min_id)id,
nvl(t.CUSTNAME,a.min_custname)CUSTNAME, a.mth, t.sales
from mydates a left join my_oracle_tbl t on a.mth= LAST_DAY(t.reporttdate)
where
t.id=2
;
You can use some old school tricks (UNION ALL IN COMBINATION WITH ADD_MONTHS FUNCTION AND SUM):
select id, custname,month,
decode(sum(sales),0,null,sum(sales)) sales from
(select id, custname, to_char(reportdate, 'mon-rrrr')
month,sales from my_oracle_tbl
UNION ALL
select a.*,b.*,0 sales from
(select distinct id, custname from my_oracle_tbl) a,
(
select to_char(sysdate,'mon')||'-2017' month from dual
UNION ALL
select ,to_char(add_months(sysdate,1),'mon')||'-2017' month from dual
UNION ALL
select ,to_char(add_months(sysdate,2),'mon')||'-2017' from dual
.......
UNION ALL
select ,to_char(add_months(sysdate,11),'mon')||'-2017' from dual) b
)
group by id, custname,month;
This is what i came up with do u see any concerns? is there a better way to write this? I need to get order by lowest to largest dates?? how can i achieve this. As of now it repeats order like this 12-2018,12-2017,11-2018,11-2017. I want 2017 dates first and then 2018
select CUSTNAME, reportdate, sum(sales), mth
from ( select to_char(add_months(date '2017-01-01', level - 1), 'mmyyyy') mth
from dual
connect by level <= 24)mo
left outer join oracle_tbl dc on mo.mth = to_char(reportdate, 'mmyyyy')
group by CUSTNAME, reportdate,mth
order by mth
Here's an example; see if it helps. It displays 12 months (you'd substitute it with 24 in line #21).
SQL> alter session set nls_date_format = 'dd.mm.yyyy';
Session altered.
SQL> with test (id, custname, reportdate, sales) as
2 (select 1, 'xx', date '2017-01-31', 1256 from dual union all
3 select 1, 'xx', date '2017-03-31', 3456 from dual union all
4 select 1, 'xx', date '2017-06-30', 5678 from dual union all
5 --
6 select 2, 'xx', date '2017-03-31', 1223 from dual union all
7 select 2, 'xx', date '2017-07-31', 3435 from dual union all
8 select 2, 'xx', date '2017-09-30', 6777 from dual
9 ),
10 all_dates as
11 (select add_months(min_repdate, column_value - 1) c_mon,
12 min_id,
13 min_custname
14 from (select min(reportdate) min_repdate,
15 id min_id,
16 min(custname) min_custname
17 from test
18 group by id
19 ),
20 table(cast(multiset(select level from dual
21 connect by level <= 12
22 ) as sys.odcinumberlist))
23 )
24 select nvl(t.id, a.min_id) id,
25 nvl(t.custname, a.min_custname) custname,
26 a.c_mon,
27 t.sales
28 from all_dates a left join test t on a.min_id = t.id and a.c_mon = t.reportdate
29 order by id, a.c_mon;
ID CU C_MON SALES
---------- -- ---------- ----------
1 xx 31.01.2017 1256
1 xx 28.02.2017
1 xx 31.03.2017 3456
1 xx 30.04.2017
1 xx 31.05.2017
1 xx 30.06.2017 5678
1 xx 31.07.2017
1 xx 31.08.2017
1 xx 30.09.2017
1 xx 31.10.2017
1 xx 30.11.2017
1 xx 31.12.2017
2 xx 31.03.2017 1223
2 xx 30.04.2017
2 xx 31.05.2017
2 xx 30.06.2017
2 xx 31.07.2017 3435
2 xx 31.08.2017
2 xx 30.09.2017 6777
2 xx 31.10.2017
2 xx 30.11.2017
2 xx 31.12.2017
2 xx 31.01.2018
2 xx 28.02.2018
24 rows selected.
SQL>
For each id, I want to flag records for the next 3 days. For any record not within 3 days, it starts with 1 again.
I don't want to use loops as it might slow down the performance.
My table is as below
Id Date Flag
-------------------------------------------
1 Jan 1st 1 (starting record for id 1. Any record with Jan 2nd - Jan 4th will be set to 0)
1 Jan 3rd 0 (From Jan 1st, it is within 3 days)
1 Jan 5th 1 (From Jan 1st, it is NOT within 3 days. So flag as 1.
Any record with Jan 6th - Jan 8th will be set to 0)
1 Jan 6th 0 (From Jan 5th, it is within 3 days)
2 Jan 15th 1 (Starting record for id 2)
2 Jan 17th 0 (From Jan 15th, it is within 3 days)
2 Jan 19th 1 (From Jan 15th, it is NOT within 3 days. So flag as 1)
EDIT: this answer is not correct
Test Case 1:
with src as (
select 1 as id, date '2014-01-01' as d, 1 as test from dual
union all select 1, date '2014-01-03', 0 from dual
union all select 1, date '2014-01-05', 1 from dual
union all select 1, date '2014-01-06', 0 from dual
union all select 2, date '2014-01-15', 1 from dual
union all select 2, date '2014-01-17', 0 from dual
union all select 2, date '2014-01-19', 1 from dual)
,q as (
select src.*
,first_value(d)
over (partition by id
order by d
range numtodsinterval(3, 'day') preceding
) as d1
from src)
select q.id, to_char(q.d,'DD/MM/YYYY') as d
,case when q.d1 =
lag(q.d1)
over (partition by id order by d)
then 0
else 1
end as flag
,test
from q
order by id, d;
Result (test passed):
id d flag test
== ========== ==== ====
1 01/01/2014 1 1
1 03/01/2014 0 0
1 05/01/2014 1 1
1 06/01/2014 0 0
2 15/01/2014 1 1
2 17/01/2014 0 0
2 19/01/2014 1 1
Test Case 2:
with src as (
select 1 as id, date '2014-01-12' as d, 1 as test from dual
union all select 1, date '2014-01-13', 0 from dual
union all select 1, date '2014-01-15', 0 from dual
union all select 1, date '2014-01-18', 1 from dual
union all select 1, date '2014-01-21', 0 from dual
union all select 1, date '2014-02-02', 1 from dual
union all select 1, date '2014-02-03', 0 from dual
union all select 1, date '2014-02-09', 1 from dual
union all select 1, date '2014-02-10', 0 from dual
union all select 1, date '2014-02-11', 0 from dual
union all select 1, date '2014-02-18', 1 from dual
union all select 1, date '2014-02-21', 0 from dual)
,q as (
select src.*
,first_value(d)
over (partition by id
order by d
range numtodsinterval(3, 'day') preceding
) as d1
from src)
select q.id, to_char(q.d,'DD/MM/YYYY') as d
,case when q.d1 =
lag(q.d1)
over (partition by id order by d)
then 0
else 1
end as flag
,test
from q
order by id, d;
Result (test failed):
id d flag test
== ========== ==== ====
1 12/01/2014 1 1
1 13/01/2014 0 0
1 15/01/2014 0 0
1 18/01/2014 1 1
1 21/01/2014 1 0 <--- test failed
1 02/02/2014 1 1
1 03/02/2014 0 0
1 09/02/2014 1 1
1 10/02/2014 0 0
1 11/02/2014 0 0
1 18/02/2014 1 1
1 21/02/2014 0 0