Count Consecutive Days where value greater than 0 - sql-server

Question

Using SQL Server 2012, I am trying create a query that provides me with, say, the top 10 longest wet (or dry) periods from a climate database.
My temp table provides the following data output:
select monthid as [id], date, rain_today
from #raindays
order by monthid asc, date asc
Output:
id date rain_today
-------------------------------
1 24 Dec 2014 2.4
1 25 Dec 2014 0
1 26 Dec 2014 8.7
1 27 Dec 2014 1.8
1 28 Dec 2014 0.3
1 29 Dec 2014 0
1 30 Dec 2014 0
1 31 Dec 2014 0.3
2 01 Jan 2015 0.3
2 02 Jan 2015 0.3
2 03 Jan 2015 18.3
2 04 Jan 2015 0.3
etc. etc.
I would like to return a ranked table that would count the period where rain_today is > 0, (or rain_today = 0) i.e:
Rank Start_Date End_Date Wet Period
----------------------------------------
1 31 Dec 2014 04 Jan 2015 5
2 26 Dec 2014 28 Dec 2014 3
...
The closest I have got from reviewing other similar queries is the following (this is for dry days):
select
#raindays.monthid as id,
min(#raindays.date) as [FirstDryDay],
max(#raindays.date) as [LatestDryDay],
count(*) as countdays
from
(select
monthid,
coalesce(max(case
when rain_today > '0'
then #raindays.date end), '19000101') as latestdry
from
#raindays
group by
monthid) g
join
#raindays on #raindays.monthid = g.monthid
and #raindays.date > g.latestdry
group by
#raindays.monthid
order by
countdays desc
Output:
id FirstDryDay LatestDryDay countdays
-----------------------------------------------
23 21 Oct 2016 31 Oct 2016 11
21 23 Aug 2016 31 Aug 2016 9
**15 23 Feb 2016 29 Feb 2016 7**
10 25 Sep 2015 30 Sep 2015 6
8 28 Jul 2015 31 Jul 2015 4
24 28 Nov 2016 30 Nov 2016 3
29 29 Apr 2017 30 Apr 2017 2
30 30 May 2017 31 May 2017 2
31 29 Jun 2017 30 Jun 2017 2
20 30 Jul 2016 31 Jul 2016 2
7 29 Jun 2015 30 Jun 2015 2
5 30 Apr 2015 30 Apr 2015 1
11 31 Oct 2015 31 Oct 2015 1
17 30 Apr 2016 30 Apr 2016 1
22 30 Sep 2016 30 Sep 2016 1
As you can see, I don't really want to group by id as I want to be able to span over different months and I'm missing other periods that occur earlier in the month. The actual count is working fine correctly it seems, checking above highlighted period:
id date rain_today
15 22 Feb 2016 3.9
15 23 Feb 2016 0
15 24 Feb 2016 0
15 25 Feb 2016 0
15 26 Feb 2016 0
15 27 Feb 2016 0
15 28 Feb 2016 0
15 29 Feb 2016 0
16 01 Mar 2016 3
Thanks in advance for any help!

Answer 1

Is this what you want???
IF OBJECT_ID('tempdb..#TestData', 'U') IS NOT NULL
DROP TABLE #TestData;
CREATE TABLE #TestData (
id INT NOT NULL ,
[Date] DATE NOT NULL,
Rain_Today DECIMAL(9,2) NOT NULL
);
INSERT #TestData (id, Date, Rain_Today) VALUES
(1, '24 Dec 2014', 2.4),
(1, '25 Dec 2014', 0),
(1, '26 Dec 2014', 8.7),
(1, '27 Dec 2014', 1.8),
(1, '28 Dec 2014', 0.3),
(1, '29 Dec 2014', 0),
(1, '30 Dec 2014', 0),
(1, '31 Dec 2014', 0.3),
(2, '01 Jan 2015', 0.3),
(2, '02 Jan 2015', 0.3),
(2, '03 Jan 2015', 18.3),
(2, '04 Jan 2015', 0.3);
--======================================
WITH
cte_AddRankGroup AS (
SELECT
td.id,
td.Date,
td.Rain_Today,
hr.HasRain,
RankGroup = DENSE_RANK() OVER (PARTITION BY td.id ORDER BY td.Date) -
DENSE_RANK() OVER (PARTITION BY td.id, hr.HasRain ORDER BY td.Date)
FROM
#TestData td
CROSS APPLY ( VALUES (IIF(td.Rain_Today = 0, 0, 1)) ) hr (HasRain)
)
SELECT
arg.id,
BegDate = MIN(arg.Date),
EndDate = MAX(arg.Date),
WetPeriod = IIF(arg.HasRain = 1, 'Wet', 'Dry'),
ConsecutiveDays = COUNT(1)
FROM
cte_AddRankGroup arg
GROUP BY
arg.id,
arg.HasRain,
arg.RankGroup
ORDER BY
arg.id,
MIN(arg.Date);
Results...
id BegDate EndDate WetPeriod ConsecutiveDays
----------- ---------- ---------- --------- ---------------
1 2014-12-24 2014-12-24 Wet 1
1 2014-12-25 2014-12-25 Dry 1
1 2014-12-26 2014-12-28 Wet 3
1 2014-12-29 2014-12-30 Dry 2
1 2014-12-31 2014-12-31 Wet 1
2 2015-01-01 2015-01-04 Wet 4
Edit: Code version using CASE expression in place of IIF...
--======================================
WITH
cte_AddRankGroup AS (
SELECT
td.id,
td.Date,
td.Rain_Today,
hr.HasRain,
RankGroup = DENSE_RANK() OVER (PARTITION BY td.id ORDER BY td.Date) -
DENSE_RANK() OVER (PARTITION BY td.id, hr.HasRain ORDER BY td.Date)
FROM
#TestData td
CROSS APPLY ( VALUES (CASE WHEN td.Rain_Today = 0 THEN 0 ELSE 1 END) ) hr (HasRain)
)
SELECT top 10
arg.id,
BegDate = MIN(arg.Date),
EndDate = MAX(arg.Date),
WetPeriod = CASE WHEN arg.HasRain = 1 THEN 'Wet' ELSE 'Dry' END,
ConsecutiveDays = COUNT(1)
FROM
cte_AddRankGroup arg
WHERE
arg.HasRain = '0' -- Top 10 Dry
--arg.HasRain = '1' -- Top 10 Wet
GROUP BY
arg.id,
arg.HasRain,
arg.RankGroup
ORDER BY
ConsecutiveDays desc, MIN(arg.Date);
Modified original script to produce the Top 10 by each period type which was my ultimate aim (output is from the full dataset):
id BegDate EndDate WetPeriod ConsecutiveDays
31 10 Jun 2017 26 Jun 2017 Dry 17
4 02 Mar 2015 14 Mar 2015 Dry 13
5 12 Apr 2015 24 Apr 2015 Dry 13
20 15 Jul 2016 26 Jul 2016 Dry 12
29 01 Apr 2017 11 Apr 2017 Dry 11
26 17 Jan 2017 27 Jan 2017 Dry 11
23 21 Oct 2016 31 Oct 2016 Dry 11
25 01 Dec 2016 09 Dec 2016 Dry 9
21 10 Aug 2016 18 Aug 2016 Dry 9
21 23 Aug 2016 31 Aug 2016 Dry 9

Answer 2

This problem can be resolved by recursion in this way:
-- this variable is needed to stop the recursion
declare #numrows int=(select count(1) from #raindays)
-- add a row number to the table creating a new table as "tabseq"
;WITH tabseq as (select row_number() over(order by date) as rownum, * from #raindays),
-- apply recursion to tabseq keeping a toggle running totals of wet and dry periods
CTE as
(
select *,
(case when rain_today=0 then 1 else 0 end) as dry,
(case when rain_today>0 then 1 else 0 end) as wet
from tabseq where rownum=1
union all
select s.*,
(case when s.rain_today=0 then cte.dry+1 else 0 end) as dry,
(case when s.rain_today>0 then cte.wet+1 else 0 end) as wet
from tabseq s
join cte on s.rownum=cte.rownum+1
where s.rownum<=#numrows
)
select * from cte
Once you have the table (cte) with the dry/wet accumulators you can order and select from it to suit your output requirements.
Please note that this is assuming consecutive days on the table, if there are gaps then instead of adding +1 on the case statement you may need to add a datediff to one side or the other depending how you consider the missing dates (wet or dry).