I have a table with thousands of executions that may have one of the following results in the state column:
OK
NOTOK
CANCELED
RUNNING
I need a query where i can sort the results so that the executions running appear on top, and the rest of the results are sorted by start date or ID, according to user preference.
example:
Table records:
ID - STATE - START_DATE
1 OK 12:00
2 RUNNING 12:10
3 NOTOK 12:30
4 RUNNING 12:45
5 OK 13:00
Expect result when sorted by START_DATE:
ID - STATE - START_DATE
4 RUNNING 12:45
2 RUNNING 12:10
5 OK 13:00
3 NOTOK 12:30
1 OK 12:00
This is the query i already have (simplified):
SELECT TOP (#ITEMS_PAGE) ID, START_DATE, STATE
FROM
(SELECT ROW_NUMBER() OVER (ORDER BY
CASE WHEN #ORDER = 'ID&ASC' THEN ID END ASC,
CASE WHEN #ORDER = 'ID&DESC' THEN ID END DESC,
CASE WHEN #ORDER = 'START_DATE&ASC' THEN START_DATE END ASC,
CASE WHEN #ORDER = 'START_DATE&DESC' THEN START_DATE END DESC,
CASE WHEN #ORDER = 'STATE&ASC' THEN STATE END ASC,
CASE WHEN #ORDER = 'STATE&DESC' THEN STATE END DESC,
CASE WHEN #ORDER IS NULL THEN ID END DESC
) AS ROWNUMBERS, *
FROM #TMPPAGING
WHERE (#RESULT is null or STATE = #RESULT)
) S
WHERE S.ROWNUMBERS > (#CURRENT_PAGE - 1) * #ITEMS_PAGE
#TMPPAGING contains the records.
You are making this much more complex than it needs to be. Here is your SQL for ordering by start_date:
with inputdata as ( select 1 as id, 'OK' as state, convert(datetime, '2018-01-10 12:00') as start_date
union all select 2 as id, 'RUNNING' as state, convert(datetime, '2018-01-10 12:10') as start_date
union all select 3 as id, 'NOTOK' as state, convert(datetime, '2018-01-10 12:30') as start_date
union all select 2 as id, 'RUNNING' as state, convert(datetime, '2018-01-10 12:45') as start_date
union all select 2 as id, 'OK' as state, convert(datetime, '2018-01-10 13:00') as start_date
)
select * from inputdata order by case when state='RUNNING' then 1 else 2 end, start_date
This results in:
id state start_date
2 RUNNING 2018-01-10 12:10:00.000
2 RUNNING 2018-01-10 12:45:00.000
1 OK 2018-01-10 12:00:00.000
3 NOTOK 2018-01-10 12:30:00.000
2 OK 2018-01-10 13:00:00.000
Related
I am trying to create a view that displays the time of employee stamps.
This is what the table looks like now:
Person
Person_Number
Date
Stamp_number
Time_Stamp
Paul
1
22-10-24
1
8:00
Paul
1
22-10-24
2
10:00
Paul
1
22-10-24
3
10:30
Paul
1
22-10-24
4
12:00
Jimmy
2
22-10-23
1
9:00
Jimmy
2
22-10-23
2
11:00
Jimmy
2
22-10-23
3
12:00
And I would like it to look like this using only a select query
Person
Person_Number
Date
Start
End
Duration
Paul
1
22-10-24
8:00
10:00
2:00
Paul
1
22-10-24
10:30
12:00
1:30
Jimmy
2
22-10-23
9:00
11:00
2:00
Jimmy
1
22-10-23
12:00
null
null
Is it possible ?
We can use conditional aggregation along with a ROW_NUMBER trick:
WITH cte AS (
SELECT *, ROW_NUMBER() OVER (PARTITION BY Person_Number, Date
ORDER BY Stamp_number) - 1 rn
FROM yourTable
)
SELECT Person, Person_Number, Date,
MAX(CASE WHEN rn % 2 = 0 THEN Time_Stamp END) AS [Start],
MAX(CASE WHEN rn % 2 = 1 THEN Time_Stamp END) AS [End],
DATEDIFF(MINUTE,
MAX(CASE WHEN rn % 2 = 0 THEN Time_Stamp END),
MAX(CASE WHEN rn % 2 = 1 THEN Time_Stamp END)) AS Duration
FROM cte
GROUP BY Person, Person_Number, Date, rn / 2
ORDER BY 2, 4;
Here is a working demo.
Try the following:
SELECT Person, Person_Number, Date, [Start], [End],
CONVERT(TIME(0), CONVERT(DATETIME, [End]) - CONVERT(DATETIME, [Start])) AS Duration
FROM
(
SELECT Person, Person_Number, Date, MIN(Time_Stamp) AS [Start],
CASE
WHEN MAX(Time_Stamp) <> MIN(Time_Stamp)
THEN MAX(Time_Stamp)
END AS [End] /* To select End as null when there is no End for a Start */
FROM table_name
GROUP BY Person, Person_Number, Date, (Stamp_number+1)/2
) T
ORDER BY Person_Number, Date, [Start]
See a demo.
I have a time series with a table like this
CarId
EventDateTime
Event
SessionFlag
CarId
EventDateTime
Event
SessionFlag
ExpectedKey
1
2022-01-01 7:00
Start
1
1-20220101-7
1
2022-01-01 7:05
Drive
1
1-20220101-7
1
2022-01-01 8:00
Park
1
1-20220101-7
1
2022-01-01 10:00
Drive
1
1-20220101-7
1
2022-01-01 18:05
End
0
1-20220101-7
1
2022-01-01 23:00
Start
1
1-20220101-23
1
2022-01-01 23:05
Drive
1
1-20220101-23
1
2022-01-02 2:00
Park
1
1-20220101-23
1
2022-01-02 3:00
Drive
1
1-20220101-23
1
2022-01-02 15:00
End
0
1-20220101-23
1
2022-01-02 16:00
Start
1
1-20220102-16
Other CarIds do exist.
What I am attempting to do is create the last column, ExpectedKey.
The problem I face though is midnight, as the same session can exist over two days.
The record above with ExpectedKey 1-20220101-23 is the prime example of what I'm trying to achieve.
I've played with using:
CASE
WHEN SessionFlag<> 0
AND
SessionFlag= LAG(SessionFlag) OVER (PARTITION BY Carid ORDER BY EventDateTime)
THEN FIRST_VALUE(CarId+'-'+Convert(CHAR(8),EventDateTime,112)+'-'+CAST(DATEPART(HOUR,EventDateTime)AS
VARCHAR))OVER (PARTITION BY CarId ORDER BY EventDateTime)
ELSE CarId+'-'+Convert(CHAR(8),EventDateTime,112)+'-'+CAST(DATEPART(HOUR,EventDateTime)AS VARCHAR) END AS SessionId
But can't seem to make it partition correctly overnight.
Can anyone off advice?
This is a classic gaps-and-islands problem. There are a number of solutions.
The simplest (if not that efficient) is partitioning over a windowed conditional count
WITH Groups AS (
SELECT *,
GroupId = COUNT(CASE WHEN t.Event = 'Start' THEN 1 END)
OVER (PARTITION BY t.CarId ORDER BY t.EventDateTime)
FROM YourTable t
)
SELECT *,
NewKey = CONCAT_WS('-',
t.CarId,
CONVERT(varchar(8), EventDateTime, 112),
FIRST_VALUE(DATEPART(hour, t.EventDateTime))
OVER (PARTITION BY t.CarId, t.GroupId ORDER BY t.EventDateTime
ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)
)
FROM Groups t;
db<>fiddle
using APPLY to get the Start event datetime and form the key with concat_ws
select *
from time_series t
cross apply
(
select top 1
ExpectedKey = concat_ws('-',
CarId,
convert(varchar(10), EventDateTime, 112),
datepart(hour, EventDateTime))
from time_series x
where x.Event = 'Start'
and x.EventDateTime <= t.EventDateTime
order by x.EventDateTime desc
) k
Example! I have a table with 4 columns. date format dd.MM.yy
id ban start end
1 1 01.01.15 31.12.18
1 1 02.02.15 31.12.18
1 1 05.04.15 31.12.17
In this case dates from rows 2 and 3 are included in dates from row 1
1 1 02.04.19 31.12.20
1 1 05.05.19 31.12.20
In this case dates from row 5 are included in dates from rows 4. Basically we have 2 periods that don't intersect.
01.01.15 31.12.18
and
02.04.19 31.12.20
Situation where a date starts in one period and ends in another are impossible. The end result should look like this
1 1 01.01.15 31.12.18
1 1 02.04.19 31.12.20
I tried using analitical functions(LAG)
select id
, ban
, case
when start >= nvl(lag(start) over (partition by id, ban order by start, end asc), start)
and end <= nvl(lag(end) over (partition by id, ban order by start, end asc), end)
then nvl(lag(start) over (partition by id, ban order by start, end asc), start)
else start
end as start
, case
when start >= nvl(lag(start) over (partition by id, ban order by start, end asc), start)
and end <= nvl(lag(end) over (partition by id, ban order by start, end asc), end)
then nvl(lag(end) over (partition by id, ban order by start, end asc), end)
else end
end as end
from table
Where I order rows and if current dates are included in previous I replace them. It works if I have just 2 rows. For example this
1 1 08.09.15 31.12.99
1 1 31.12.15 31.12.99
turns into this
1 1 08.09.15 31.12.99
1 1 08.09.15 31.12.99
which I can then group by all fields and get what I want, but if there are more
1 2 13.11.15 31.12.99
1 2 31.12.15 31.12.99
1 2 16.06.15 31.12.99
I get
1 2 16.06.15 31.12.99
1 2 16.06.15 31.12.99
1 2 13.11.15 31.12.99
I understand why this happens, but how do I work around it? Running the query multiple times is not an option.
This query looks promising:
-- test data
with t(id, ban, dtstart, dtend) as (
select 1, 1, date '2015-01-01', date '2015-03-31' from dual union all
select 1, 1, date '2015-02-02', date '2015-03-31' from dual union all
select 1, 1, date '2015-03-15', date '2015-03-31' from dual union all
select 1, 1, date '2015-08-05', date '2015-12-31' from dual union all
select 1, 2, date '2015-01-01', date '2016-12-31' from dual union all
select 2, 1, date '2016-01-01', date '2017-12-31' from dual),
-- end of test data
step1 as (select id, ban, dt, to_number(inout) direction
from t unpivot (dt for inout in (dtstart as '1', dtend as '-1'))),
step2 as (select distinct id, ban, dt, direction,
sum(direction) over (partition by id, ban order by dt) sm
from step1),
step3 as (select id, ban, direction, dt dt1,
lead(dt) over (partition by id, ban order by dt) dt2
from step2
where (direction = 1 and sm = 1) or (direction = -1 and sm = 0) )
select id, ban, dt1, dt2
from step3 where direction = 1 order by id, ban, dt1
step1 - unpivot dates and assign 1 for start date, -1 for end
date (column direction)
step2 - add cumulative sum for direction
step3 - filter only interesting dates, pivot second date using lead()
You can shorten this syntax, I divided it to steps to show what's going on.
Result:
ID BAN DT1 DT2
------ ---------- ----------- -----------
1 1 2015-01-01 2015-03-31
1 1 2015-08-05 2015-12-31
1 2 2015-01-01 2016-12-31
2 1 2016-01-01 2017-12-31
I assumed that for different (ID, BAN) we have to make calculations separately. If not - change partitioning and ordering in sum() and lead().
Pivot and unpivot works in Oracle 11 and later, for earlier versions you need case when.
BTW - START is reserved word in Oracle so in my example I changed slightly column names.
I like to do this by identifying the period starts, then doing a cumulative sum to define the group, and a final aggregation:
select id, ban, min(start), max(end)
from (select t.*, sum(start_flag) over (partition by id, bin order by start) as grp
from (select t.*,
(case when exists (select 1
from t t2
where t2.id = t.id and t2.ban = t.ban and
t.start <= t2.end and t.end >= t2.start and
t.start <> t2.start and t.end <> t2.end
)
then 0 else 1
end) as start_flag
from t
) t
) t
group by id, ban, grp;
I am trying to adjust the below code by adding a 2 week tolerance piece.
What it does it looks when the first time a customer (identifier) created a request and the first time it was completed and counts the days which happened in between.
However I am trying to add a tolerance piece. Which says count the number of NCO which occurred between those dates and if there were further requests past the completion date which happened within 2 weeks of the completion date then count those as well (part of the same request). Anything past 2 weeks of the completions date consider as a new request.
CREATE TABLE #temp
(
Identifier varchar(40)NOT NULL
,Created_Date DATETIME NOT NULL
,Completed_Date DATETIME NULL
,SN_Type varchar(20) NOT NULL
,SN_Status varchar(20) NOT NULL
)
;
INSERT INTO #temp
VALUES ('3333333','2017-02-14 15:00:40.000','2017-02-15 00:00:00.000','Re-Activattion', 'COMP');
INSERT INTO #temp
VALUES ('3333333','2017-05-24 16:41:04.000','2017-06-05 00:00:00.000','Re-Activattion', 'N-CO');
INSERT INTO #temp
VALUES ('3333333','2017-05-25 11:49:54.000','2017-05-26 00:00:00.000','Re-Activattion', 'COMP');
INSERT INTO #temp
VALUES ('3333333','2017-06-27 10:24:29.000',NULL,'Re-Activattion', 'ACC');
#Alex you code is accurate just I would like to be selecting the min date the record is created a 2nd time, so line 2 of the result should return min date to be 2017-05-24 16:41:04.000.
select identifier
,case
when sum(case when SN_STATUS='COMP' and SN_TYPE = 'Re-Activattion' then 1 else 0 end)>0
then str(datediff(day
,MIN(case
when SN_TYPE = 'Re-Activattion'
then Created_Date
else null
end
)
,min(case
when (SN_TYPE = 'Re-Activattion'
and SN_STATUS='COMP'
)
then Completed_Date
else null
end
)
)
)
when sum(case when SN_TYPE='Re-Activattion' then 1 else 0 end)>0
then 'NOT COMP'
else 'NO RE-ACT'
end
as RE_ACT_COMPLETION_TIME
,Sum(CASE WHEN SN_STATUS = 'N-CO' THEN 1 ELSE 0 END) as [RE-AN NCO #]
from #temp
group by identifier
;
RESULTS I AM AFTER:
Your table design is not optimal for these kinds of queries as there is no definitive record that specified order start and order end. Additionally multiple orders are stored with the same identifier.
To work around this you need to calculate/identify Order start and Order End records yourself.
One way to do it is using Common Table Expressions.
Note: I have added comments to code to explain what each section does.
-- calculate/identify Order start and Order End records
WITH cte AS
(
-- 1st Order start record i.e. earliest record in the table for a given "Identifier"
SELECT Identifier, MIN( Created_Date ) AS Created_Date, CONVERT( VARCHAR( 30 ), 'Created' ) AS RecordType, 1 AS OrderNumber
FROM #temp
GROUP BY Identifier
UNION ALL
-- All records with "COMP" status are treated as order completed events. Add 2 weeks to the completed date to create a "dummy" Order End Date
SELECT Identifier, DATEADD( WEEK, 2, Created_Date ) AS Created_Date, 'Completed' AS RecordType, ROW_NUMBER() OVER( PARTITION BY Identifier ORDER BY Created_Date ) AS OrderNumber
FROM #temp
WHERE SN_STATUS = 'COMP'
UNION ALL
-- Set the start period of the next order to be right after (3 ms) the previous Order End Date
SELECT Identifier, DATEADD( ms, 3, DATEADD( WEEK, 2, Created_Date )) AS Created_Date, 'Created' AS RecordType, ROW_NUMBER() OVER( PARTITION BY Identifier ORDER BY Created_Date ) + 1 AS OrderNumber
FROM #temp
WHERE SN_STATUS = 'COMP'
),
-- Combine Start / End records into one record
OrderGroups AS(
SELECT Identifier, OrderNumber, MIN( Created_Date ) AS OrderRangeStartDate, MAX( Created_Date ) AS OrderRangeEndDate
FROM cte
GROUP BY Identifier, OrderNumber
)
SELECT a.Identifier, a.OrderNumber, OrderRangeStartDate, OrderRangeEndDate,
case
when sum(case when SN_STATUS='COMP' and SN_TYPE = 'Re-Activattion' then 1 else 0 end)>0
then str(datediff(day
,MIN(case
when SN_TYPE = 'Re-Activattion'
then Created_Date
else null
end
)
,min(case
when (SN_TYPE = 'Re-Activattion'
and SN_STATUS='COMP'
)
then Completed_Date
else null
end
)
)
)
when sum(case when SN_TYPE='Re-Activattion' then 1 else 0 end)>0
then 'NOT COMP'
else 'NO RE-ACT'
end as RE_ACT_COMPLETION_TIME,
Sum(CASE WHEN SN_STATUS = 'N-CO' THEN 1 ELSE 0 END) as [RE-AN NCO #]
FROM OrderGroups AS a
INNER JOIN #Temp AS b ON a.Identifier = b.Identifier AND a.OrderRangeStartDate <= b.Created_Date AND b.Created_Date <= a.OrderRangeEndDate
GROUP BY a.Identifier, a.OrderNumber, OrderRangeStartDate, OrderRangeEndDate
Output:
Identifier OrderNumber OrderRangeStartDate OrderRangeEndDate RE_ACT_COMPLETION_TIME RE-AN NCO #
-------------- ------------- ----------------------- ----------------------- ---------------------- -----------
200895691 1 2016-01-27 14:25:00.000 2016-02-10 15:15:00.000 0 2
200895691 2 2016-02-10 15:15:00.003 2017-01-16 12:15:00.000 1 1
Output for the updated data set:
Identifier OrderNumber OrderRangeStartDate OrderRangeEndDate RE_ACT_COMPLETION_TIME RE-AN NCO #
------------ ------------ ----------------------- ----------------------- ---------------------- -----------
200895691 1 2017-01-11 00:00:00.000 2017-03-27 00:00:00.000 61 4
200895691 2 2017-03-27 00:00:00.003 2017-04-20 00:00:00.000 1 1
3333333 1 2017-01-27 00:00:00.000 2017-02-10 00:00:00.000 0 2
44454544 1 2017-01-27 00:00:00.000 2017-01-27 00:00:00.000 NOT COMP 1
7777691 1 2017-02-08 09:36:44.000 2017-02-22 09:36:44.000 63 1
Update 2017-10-05 in response to the comment
Input:
INSERT INTO #temp VALUES
('11111','20170203','20170203','Re-Activattion', 'COMP'),
('11111','20170206','20170202','Re-Activattion', 'N-CO');
Output:
Identifier OrderNumber OrderRangeStartDate OrderRangeEndDate RE_ACT_COMPLETION_TIME RE-AN NCO #
---------- ------------ ----------------------- ----------------------- ---------------------- -----------
11111 1 2017-02-03 00:00:00.000 2017-02-17 00:00:00.000 0 1
In Redshift, through SQL script want to consolidate monthly records as long as gap between the end date of first and the start date of the next record is 32 days or less (<=32) into single record with minimum startdate of continuous month as output startdate and maximum of end date of continuous month as output enddate.
The below input data refers to the table's data and also listed the expected output. The input data is listed ORDER BY ID,STARTDT,ENDDT in ASC.
For example, in below table, consider ID 100, the gab between the end of the first record and start of the next record <=32, however gap between the second record end date and third records start date falls more than 32 days, hence the first two records to be consolidate into one record i.e. (ID),MIN(STARTSDT),MAX(ENDDT) which corresponds to first record in the expected output. Similarly gab between 3 and 4 record in the input data falls within the 32 days and thus these 2 records to be consolidated into single records which corresponds to the second record in the expected output.
INPUT DATA:
ID STARTDT ENDDT
100 2000-01-01 2000-01-31
100 2000-02-01 2000-02-29
100 2000-05-01 2000-05-31
100 2000-06-01 2000-06-30
100 2000-09-01 2000-09-30
100 2000-10-01 2000-10-31
101 2012-06-01 2012-06-30
101 2012-07-01 2012-07-31
102 2000-01-01 2000-01-31
103 2013-03-01 2013-03-31
103 2013-05-01 2013-05-31
EXPECTED OUTPUT:
ID MIN_STARTDT MAX_END_DT
100 2000-01-01 2000-02-29
100 2000-05-01 2000-06-30
100 2000-09-01 2000-10-31
101 2012-06-01 2012-07-31
102 2000-01-01 2000-01-31
103 2013-03-01 2013-03-31
103 2013-05-01 2013-05-31
You can do this in steps:
Use a join to identify where two adjacent records should be combined.
Then do a cumulative sum to assign all such adjacent records a grouping identifier.
Aggregate.
It looks like:
select id, min(startdt), max(enddte)
from (select t.*,
count(case when tprev.id is null then 1 else 0 end) over
(partition by t.idid
order by t.startdt
rows between unbounded preceding and current row
) as grp
from t left join
t tprev
on t.id = tprev.id and
t.startdt = tprev.enddt + interval '1 day'
) t
group by id, grp;
The question is very similar to this one and my answer is also similar: Fetch rows based on condition
The gist of the idea is to use Window Functions to identify transitions between period (events which are less than 33 days apart), and then do some filtering to remove the rows within the period, and then Window Functions again.
Complete solution:
SELECT
id,
startdt AS period_start,
period_end
FROM (
SELECT
id,
startdt,
enddt,
lead(enddt, 1)
OVER (PARTITION BY id
ORDER BY enddt) AS period_end,
period_boundary
FROM (
SELECT
id,
startdt,
enddt,
CASE WHEN period_switch = 0 AND reverse_period_switch = 1
THEN 'start'
ELSE 'end' END AS period_boundary
FROM (
SELECT
id,
startdt,
enddt,
CASE WHEN datediff(days, enddt, lead(startdt, 1)
OVER (PARTITION BY id
ORDER BY enddt ASC)) > 32
THEN 1
ELSE 0 END AS period_switch,
CASE WHEN datediff(days, lead(enddt, 1)
OVER (PARTITION BY id
ORDER BY enddt DESC), startdt) > 32
THEN 1
ELSE 0 END AS reverse_period_switch
FROM date_test
)
AS sessioned
WHERE period_switch != 0 OR reverse_period_switch != 0
UNION
SELECT -- adding start rows without transition
id,
startdt,
enddt,
'start'
FROM (
SELECT
id,
startdt,
enddt,
row_number()
OVER (PARTITION BY id
ORDER BY enddt ASC) AS row_num
FROM date_test
) AS with_row_number
WHERE row_num = 1
UNION
SELECT -- adding end rows without transition
id,
startdt,
enddt,
'end'
FROM (
SELECT
id,
startdt,
enddt,
row_number()
OVER (PARTITION BY id
ORDER BY enddt desc) AS row_num
FROM date_test
) AS with_row_number
WHERE row_num = 1
) AS with_boundary -- data set containing start/end boundaries
) AS with_end -- data set where end date is propagated into the start row of the period
WHERE period_boundary = 'start'
ORDER BY id, startdt ASC;
Note that in your expected output, you had a row for 103 2013-05-01 2013-05-31, however its start date is 31 days apart from end date of the previous row, so this row should instead be merged with the previous row for id 103 according to your requirements.
So the output that I get looks like this:
id start end
100 2000-01-01 2000-02-29
100 2000-05-01 2000-06-30
100 2000-09-01 2000-10-31
101 2012-06-01 2012-07-31
102 2000-01-01 2000-01-31
103 2013-03-01 2013-05-31