Related
Hello I am trying to calculate the time difference of 2 consecutive rows for Date (either in hours or Days), as attached in the image
Highlighted in Yellow is the result I want which is basically the difference of the date in that row and 1 above.
How can we achieve it in the SQL? Attached is my complex code which has the rest of the fields in it
with cte
as
(
select m.voucher_no, CONVERT(VARCHAR(30),CONVERT(datetime, f.action_Date, 109),100) as action_date,f.col1_Value,f.col3_value,f.col4_value,f.comments,f.distr_user,f.wf_status,f.action_code,f.wf_user_id
from attdetailmap m
LEFT JOIN awftaskfin f ON f.oid = m.oid and f.client ='PC'
where f.action_Date !='' and action_date between '$?datef' and '$?datet'
),
.*select *, ROW_NUMBER() OVER(PARTITION BY action_Date,distr_user,wf_Status,wf_user_id order by action_Date,distr_user,wf_Status,wf_user_id ) as row_no_1 from cte
cte2 as
(
select *, ROW_NUMBER() OVER(PARTITION BY voucher_no,action_Date,distr_user,wf_Status,wf_user_id order by voucher_no ) as row_no_1 from cte
)
select distinct(v.dim_value) as resid,c.voucher_no,CONVERT(datetime, c.action_Date, 109) as action_Date,c.col4_value,c.comments,c.distr_user,v.description,c.wf_status,c.action_code, c.wf_user_id,v1.description as name,r.rel_value as pay_office,r1.rel_value as site
from cte2 c
LEFT OUTER JOIN aagviuserdetail v ON v.user_id = c.distr_user
LEFT OUTER JOIN aagviuserdetail v1 ON v1.user_id = c.wf_user_id
LEFT OUTER JOIN ahsrelvalue r ON r.resource_id = v.dim_Value and r.rel_Attr_id = 'P1' and r.period_to = '209912'
LEFT OUTER JOIN ahsrelvalue r1 ON r1.resource_id = v.dim_Value and r1.rel_Attr_id = 'Z1' and r1.period_to = '209912'
where c.row_no_1 = '1' and r.rel_value like '$?site1' and voucher_no like '$?trans'
order by voucher_no,action_Date
The key idea is lag(). However, date/time functions vary among databases. So, the idea is:
select t.*,
(date - lag(date) over (partition by transaction_no order by date)) as diff
from t;
I should note that this exact syntax might not work in your database -- because - may not even be defined on date/time values. However, lag() is a standard function and should be available.
For instance, in SQL Server, this would look like:
select t.*,
datediff(second, lag(date) over (partition by transaction_no order by date), date) / (24.0 * 60 * 60) as diff_days
from t;
I have some prices for the month of January.
Date,Price
1,100
2,100
3,115
4,120
5,120
6,100
7,100
8,120
9,120
10,120
Now, the o/p I need is a non-overlapping date range for each price.
price,from,To
100,1,2
115,3,3
120,4,5
100,6,7
120,8,10
I need to do this using SQL only.
For now, if I simply group by and take min and max dates, I get the below, which is an overlapping range:
price,from,to
100,1,7
115,3,3
120,4,10
This is a gaps-and-islands problem. The simplest solution is the difference of row numbers:
select price, min(date), max(date)
from (select t.*,
row_number() over (order by date) as seqnum,
row_number() over (partition by price, order by date) as seqnum2
from t
) t
group by price, (seqnum - seqnum2)
order by min(date);
Why this works is a little hard to explain. But if you look at the results of the subquery, you will see how the adjacent rows are identified by the difference in the two values.
SELECT Lag.price,Lag.[date] AS [From], MIN(Lead.[date]-Lag.[date])+Lag.[date] AS [to]
FROM
(
SELECT [date],[Price]
FROM
(
SELECT [date],[Price],LAG(Price) OVER (ORDER BY DATE,Price) AS LagID FROM #table1 A
)B
WHERE CASE WHEN Price <> ISNULL(LagID,1) THEN 1 ELSE 0 END = 1
)Lag
JOIN
(
SELECT [date],[Price]
FROM
(
SELECT [date],Price,LEAD(Price) OVER (ORDER BY DATE,Price) AS LeadID FROM [#table1] A
)B
WHERE CASE WHEN Price <> ISNULL(LeadID,1) THEN 1 ELSE 0 END = 1
)Lead
ON Lag.[Price] = Lead.[Price]
WHERE Lead.[date]-Lag.[date] >= 0
GROUP BY Lag.[date],Lag.[price]
ORDER BY Lag.[date]
Another method using ROWS UNBOUNDED PRECEDING
SELECT price, MIN([date]) AS [from], [end_date] AS [To]
FROM
(
SELECT *, MIN([abc]) OVER (ORDER BY DATE DESC ROWS UNBOUNDED PRECEDING ) end_date
FROM
(
SELECT *, CASE WHEN price = next_price THEN NULL ELSE DATE END AS abc
FROM
(
SELECT a.* , b.[date] AS next_date, b.price AS next_price
FROM #table1 a
LEFT JOIN #table1 b
ON a.[date] = b.[date]-1
)AA
)BB
)CC
GROUP BY price, end_date
The following query displays duplicates in a table with the qty alias showing the total count, eg if there are five duplicates then all five will have the same qty = 5.
select s.*, t.*
from [Migrate].[dbo].[Table1] s
join (
select [date] as d1, [product] as h1, count(*) as qty
from [Migrate].[dbo].[Table1]
group by [date], [product]
having count(*) > 1
) t on s.[date] = t.[d1] and s.[product] = t.[h1]
ORDER BY s.[product], s.[date], s.[id]
Is it possible to amend the count(*) as qty to show an incremental count so that five duplicates would display 1,2,3,4,5?
The answer to your question is row_number(). How you use it is rather unclear, because you provide no guidance, such as sample data or desired results. Hence this answer is rather general:
select s.*, t.*,
row_number() over (partition by s.product order by s.date) as seqnum
from [Migrate].[dbo].[Table1] s join
(select [date] as d1, [product] as h1, count(*) as qty
from [Migrate].[dbo].[Table1]
group by [date], [product]
having count(*) > 1
) t
on s.[date] = t.[d1] and s.[product] = t.[h1]
order by s.[product], s.[date], s.[id];
The speculation is that the duplicates are by product. This enumerates them by date. Some combination of the partition by and group by is almost certainly what you need.
I have a large table of users (as a guid), some associated values, and a time stamp of when each row was inserted. A user might be associated with many rows in this table.
guid | <other columns> | insertdate
I want to count for each month: how many unique new users were inserted. It's easy to do manually:
select count(distinct guid)
from table
where insertdate >= '20060201' and insertdate < '20060301'
and guid not in (select guid from table where
insertdate >= '20060101' and insertdate < '20060201')
How could this be done for each successive month in sql?
I thought to use a rank function to associate clearly each guid with a month:
select guid,
,dense_rank() over ( order by datepart(YYYY, insertdate),
datepart(m, t.TransactionDateTime)) as MonthRank
from table
and then iterate upon each rank value:
declare #no_times int
declare #counter int = 1
set #no_times = select count(distinct concat(datepart(year, t.TransactionDateTime),
datepart(month, t.TransactionDateTime))) from table
while #no_times > 0 do
(
select count(*), #counter
where guid not in (select guid from table where rank = #counter)
and rank = #int + 1
#counter += 1
#no_times -= 1
union all
)
end
I know this strategy is probably the wrong way to go about things.
Ideally, I would like a result set to look like this:
MonthRank | NoNewUsers
I would be extremely interested and grateful if a sql wizard could point me in the right direction.
SELECT
DATEPART(year,t.insertdate) AS YearNum
,DATEPART(mm,t.insertdate) as MonthNum
,COUNT(DISTINCT guid) AS NoNewUsers
,DENSE_RANK() OVER (ORDER BY COUNT(DISTINCT t.guid) DESC) AS MonthRank
FROM
table t
LEFT JOIN table t2
ON t.guid = t2.guid
AND t.insertdate > t2.insertdate
WHERE
t2.guid IS NULL
GROUP BY
DATEPART(year,t.insertdate)
,DATEPART(mm,t.insertdate)
Use a left join to see if the table ever existed as a prior insert date and if they didn't then count them using aggregation like you normally would. If you want to add a rank to see which month(s) have the highest number of new users then you can use your DENSE_RANK() function but because you are already grouping by want you want you do not need a partition clause.
If you want the first time that a guid entered, then your query doesn't exactly work. You can get the first time with two aggregations:
select year(first_insertdate), month(first_insertdate), count(*)
from (select t.guid, min(insertdate) as first_insertdate
from t
group by t.guid
) t
group by year(first_insertdate), month(first_insertdate)
order by year(first_insertdate), month(first_insertdate);
If you are looking for counting guids each time they skip a month, then you can use lag():
select year(insertdate), month(insertdate), count(*)
from (select t.*,
lag(insertdate) over (partition by guid order by insertdate) as prev_insertdate
from t
) t
where prev_insertdate is null or
datediff(month, prev_insertdate, insertdate) >= 2
group by year(insertdate), month(insertdate)
order by year(insertdate), month(insertdate);
I solved it with the terrible while loop, then a friend helped me to solve it more efficiently in another way.
The loop version:
--ranked by month
select t.TransactionID
,t.BuyerUserID
,concat(datepart(year, t.InsertDate), datepart(month,
t.InsertDate)) MonthRankName
,dense_rank() over ( order by datepart(YYYY, t.InsertDate),
datepart(m, t.InsertDate)) as MonthRank
into #ranked
from table t;
--iteratate
declare #counter int = 1
declare #no_times int
select #no_times = count(distinct concat(datepart(year, t.InsertDate),
datepart(month, t.InsertDate))) from table t;
select count(distinct r.guid) as NewUnique, r.Monthrank into #results
from #ranked r
where r.MonthRank = 1 group by r.MonthRank;
while #no_times > 1
begin
insert into #results
select count(distinct rt.guid) as NewUnique, #counter + 1 as MonthRank
from #ranked r
where rt.guid not in
(
select rt2.guid from #ranked rt2
where rt2.MonthRank = #counter
)
and rt.MonthRank = #counter + 1
set #counter = #counter+1
set #no_times = #no_times-1
end
select * from #results r
This turned out to run pretty slowly (as you might expect)
What turned out to be faster by a factor of 10 was this method:
select t.guid,
cast (concat(datepart(year, min(t.InsertDate)),
case when datepart(month, min(t.InsertDate)) < 10 then
'0'+cast( datepart(month, min(t.InsertDate)) as varchar(10))
else cast (datepart(month, min(t.InsertDate)) as varchar(10)) end
) as int) as MonthRankName
into #NewUnique
from table t
group by t.guid;
select count(1) as NewUniques, t.MonthRankName from #NewUnique t
group by t.MonthRankName
order by t.MonthRankName
Simply identifying the very first month each guid appears, then counting the number of these occurring each month. With a bit of a hack to get YearMonth formatted nicely (this seems to be more efficient than format([date], 'yyyyMM') but need to experiment more on that.
This question already has answers here:
Get top 1 row of each group
(19 answers)
Closed 6 years ago.
We're currently working on a query for a report that returns a series of data. The customer has specified that they want to receive 5 rows total, with the data from the previous 5 days (as defined by a start date and an end date variable). For each day, they want the data from the row that's closest to 4am.
I managed to get it to work for a single day, but I certainly don't want to union 5 separate select statements simply to fetch these values. Is there any way to accomplish this via CTEs?
select top 1
'W' as [RecordType]
, [WellIdentifier] as [ProductionPtID]
, t.Name as [Device Name]
, t.RecordDate --convert(varchar, t.RecordDate, 112) as [RecordDate]
, TubingPressure as [Tubing Pressure]
, CasingPressure as [Casing Pressure]
from #tTempData t
Where cast (t.recorddate as time) = '04:00:00.000'
or datediff (hh,'04:00:00.000',cast (t.recorddate as time)) < -1.2
order by Name, RecordDate desc
assuming that the #tTempData only contains the previous 5 days records
SELECT *
FROM
(
SELECT *, rn = row_number() over
(
partition by convert(date, recorddate)
order by ABS ( datediff(minute, convert(time, recorddate) , '04:00' )
)
FROM #tTempData
)
WHERE rn = 1
You can use row_number() like this to get the top 5 last days most closest to 04:00
SELECT TOP 5 * FROM (
select t.* ,
ROW_NUMBER() OVER(PARTITION BY t.recorddate
ORDER BY abs(datediff (minute,'04:00:00.000',cast (t.recorddate as time))) rnk
from #tTempData t)
WHERE rnk = 1
ORDER BY recorddate DESC
You can use row_number() for this purpose:
select t.*
from (select t.*,
row_number() over (partition by cast(t.recorddate as date)
order by abs(datediff(ms, '04:00:00.000',
cast(t.recorddate as time)
))
) seqnum
from #tTempData t
) t
where seqnum = 1;
You can add an appropriate where clause in the subquery to get the dates that you are interested in.
Try something like this:
select
'W' as [RecordType]
, [WellIdentifier] as [ProductionPtID]
, t.Name as [Device Name]
, t.RecordDate --convert(varchar, t.RecordDate, 112) as [RecordDate]
, TubingPressure as [Tubing Pressure]
, CasingPressure as [Casing Pressure]
from #tTempData t
Where exists
(select 1 from #tTempData t1 where
ABS(datediff (hh,'04:00:00.000',cast (t.recorddate as time))) <
ABS(datediff (hh,'04:00:00.000',cast (t1.recorddate as time)))
and GETDATE(t.RecordDate) = GETDATE(t1.RecordDate)
)dt
and t.RecordDate between YOURDATERANGE
order by Name, RecordDate desc;