I have the following table:
visitorId visitNumber DATE
1 1 20180101
1 2 20180101
1 3 20180105
2 1 20171230
2 2 20180106
What I would like to return is:
visitorId totalVisits max_visits_in_1_day
1 3 2
2 2 1
I manage to get everything working without max_visits_in_1_day using:
SELECT visitorId,
MAX(visitNumber) - MIN(visitNumber) + 1 as totalVisits,
GROUP BY visitorId
What I need to do is improve the code such that max_visits_in_1_day gets added. Something like MAX(COUNT(GROUP BY(DATE)))
I first tried adding MAX(COUNT(DATE)), but this aggregates all dates, and doesn't actually look for maximum unique date. In a sense, I would need to do a GROUP BY on DATE and the sum the counts then.
I tried adding GROUP BY visitorId, DATE but this creates extra rows.
You will have to take two steps like this:
SELECT visitorId, SUM(perDay) AS totalVisits, MAX(perDay) AS max_visits_in_1_day
FROM
(SELECT visitorId, COUNT(visitNumber) AS perDay, DATE
FROM myTable
GROUP BY visitorId, DATE) A
GROUP BY visitorId
You can try the following query -
SELECT visitorId
,COUNT(visitNumber) totalVisits
,mv1d.count max_visits_in_1_day
FROM YOUR_TABLE YT
INNER JOIN (SELECT visitorId, MAX(COUNT(DATE)) count
FROM YOUR_TABLE YT1)
ON YT.visitorId = YT1.visitorId
GROUP BY visitorId
Related
I have a hard struggle with this problem.
I have the following table:
TicketNumber
OpenTicketDate YYYY_MM
ClosedTicketDate YYYY_MM
1
2018-1
2020-1
2
2018-2
2021-2
3
2019-1
2020-6
4
2020-7
2021-1
I would like to create an extra column which would monitor the open tickets at the given OpenTicketDate.
So the new table would look like this:
TicketNumber
OpenTicketDate YYYY_MM
ClosedTicketDate YYYY_MM
OpenTicketsLookingBackwards
1
2018-1
2020-1
1
2
2018-2
2021-2
2
3
2019-1
2020-6
3
4
2020-7
2021-1
2
The logic behind the 4th (extra) column is that it looks at the previous records & current record where the ClosedTicketsDate > OpenTicketDate.
For example ticketNumber 4 has '2' open tickets because there are only 2 ClosedTicketDate records where ClosedTicketDate > OpenTicketDate.
The new column only fills data based on looking at prevoius records. It is backward looking not forward.
Is there anyone who can help me out?
You could perform a self join and aggregate as the following:
Select T.TicketNumber, T.OpenTicketDate, T.ClosedTicketDate,
Count(*) as OpenTicketsLookingBackwards
From table_name T Left Join table_name D
On Cast(concat(T.OpenTicketDate,'-1') as Date) < Cast(concat(D.ClosedTicketDate,'-1') as Date)
And T.ticketnumber >= D.ticketnumber
Group By T.TicketNumber, T.OpenTicketDate, T.ClosedTicketDate
Order By T.TicketNumber
You may also try with a scalar subquery as the following:
Select T.TicketNumber, T.OpenTicketDate, T.ClosedTicketDate,
(
Select Count(*) From table_name D
Where Cast(concat(T.OpenTicketDate,'-1') as Date) <
Cast(concat(D.ClosedTicketDate,'-1') as Date)
And T.ticketnumber >= D.ticketnumber
) As OpenTicketsLookingBackwards
From table_name T
Order By T.TicketNumber
Mostly, joins tend to outperform subqueries.
See a demo.
My goal is something like following table:
Key | Count since date X | Count total
1 | 4 | 28
With two simple selects I could gain this values: (the key of the table consists of 3 columns [t$ncmp, t$trav, t$seqn])
1. SELECT COUNT(*) FROM db.table WHERE t$date >= sysdate-2 GROUP BY t$ncmp, t$trav, t$seqn
2. SELECT COUNT(*) FROM db.table GROUP BY t$ncmp, t$trav, t$seqn
How can I join these statements?
What I tried:
SELECT n.t$trav, COUNT(n.t$trav), m.total FROM db.table n
LEFT JOIN (SELECT t$ncmp, t$trav, t$seqn, COUNT(*) as total FROM db.table
GROUP BY t$ncmp, t$trav, t$seqn) m
ON (n.t$ncmp = m.t$ncmp AND n.t$trav = m.t$trav AND n.t$seqn = m.t$seqn)
WHERE n.t$date >= sysdate-2
GROUP BY n.t$ncmp, n.t$trav, n.t$seqn
I tried different variantes, but always got errors like 'group by is missing' or 'unknown qualifier'.
Now this at least executes, but total is always 2.
T$TRAV COUNT(N.T$TRAV) TOTAL
4 2 2
29 3 2
51 1 2
62 2 2
16 1 2
....
If it matter, I will run this as an OPENQUERY from MSSQLSERVER to Oracle-DB.
I'd try
GROUP BY n.t$trav, m.total
You typically GROUP BY the same columns as you SELECT - except those who are arguments to set functions.
My goal is something like following table:
If so, you seem to want conditional aggregation:
select key, count(*) as total,
sum(case when datecol >= date 'xxxx-xx-xx' then 1 else 0 end) as total_since_x
from t
group by key;
I'm not sure how this relates to your sample queries. I simply don't see the relationship between that code and your question.
I have a table with 3 fields like this sample table Tbl1
Person Cost FromDate
1 10 2009-1-1
1 20 2010-1-1
2 10 2009-1-1
I want to query it and get back the 3 fields and a generated field called ToDate that defaults to 2099-1-1 unless there is an actual ToDate implied from another entry for the person in the table.
select Person,Cost,FromDate,ToDate From Tbl1
Person Cost FromDate ToDate
1 10 2009-1-1 2010-1-1
1 20 2010-1-1 2099-1-1
2 10 2009-1-1 2099-1-1
You can select the minimum date from all dates that are after the record's date. If there is none you get NULL. With COALESCE you change NULL into the default date:
select
Person,
Cost,
FromDate,
coalesce((select min(FromDate) from Tbl1 later where later.FromDate > Tbl1.FromDate), '2099-01-01') as ToDate
From Tbl1
order by Person, FromDate;
Although Thorsten's answer is perfectly fine, it would be more efficient to use window-functions to match the derived end-dates.
;WITH nbrdTbl
AS ( SELECT Person, Cost, FromDate, row_nr = ROW_NUMBER() OVER (PARTITION BY Person ORDER BY FromDate ASC)
FROM Tbl1)
SELECT t.Person, t.Cost, t.FromDate, derived_end_date = COALESCE(nxt.FromDate, '9991231')
FROM nbrdTbl t
LEFT OUTER JOIN nbrdTbl nxt
ON nxt.Person = t.Person
AND nxt.row_nr = t.row_nr + 1
ORDER BY t.Person, t.FromDate
Doing a test on a 2000-records table it's about 3 times as efficient according to the Execution plan (78% vs 22%).
I have a table with the following structure
ID Person LOG_TIME
-----------------------------------
1 1 2012-05-21 13:03:11.550
2 1 2012-05-22 13:09:37.050 <--- this is duplicate
3 1 2012-05-28 13:09:37.183
4 2 2012-05-20 15:09:37.230
5 2 2012-05-22 13:03:11.990 <--- this is duplicate
6 2 2012-05-24 04:04:13.222 <--- this is duplicate
7 2 2012-05-29 11:09:37.240
I have some application job that fills this table with data.
There is a business rule that each person should have only 1 record in every 7 days.
From the above example, records # 2,5 and 6 are considered duplicates while 1,3,4 and 7 are OK.
I want to have a SQL query that checks if there are records for the same person in less than 7 days.
;WITH cte AS
(
SELECT ID, Person, LOG_TIME,
DATEDIFF(d, MIN(LOG_TIME) OVER (PARTITION BY Person), LOG_TIME) AS diff_date
FROM dbo.Log_time
)
SELECT *
FROM cte
WHERE diff_date BETWEEN 1 AND 6
Demo on SQLFiddle
Please see my attempt on SQLFiddle here.
You can use a join based on DATEDIFF() to find records which are logged less than 7 days apart:
WITH TooClose
AS
(
SELECT
a.ID AS BeforeID,
b.ID AS AfterID
FROM
Log a
INNER JOIN Log b ON a.Person = b.Person
AND a.LOG_TIME < b.LOG_TIME
AND DATEDIFF(DAY, a.LOG_TIME, b.LOG_TIME) < 7
)
However, this will include records which you don't consider "duplicates" (for instance, ID 3, because it is too close to ID 2). From what you've said, I'm inferring that a record isn't a "duplicate" if the record it is too close to is itself a "duplicate".
So to apply this rule and get the final list of duplicates:
SELECT
AfterID AS ID
FROM
TooClose
WHERE
BeforeID NOT IN (SELECT AfterID FROM TooClose)
Please take a look at this sample.
Reference: SQLFIDDLE
Query:
select person,
datediff(max(log_time),min(log_time)) as diff,
count(log_time)
from pers
group by person
;
select y.person, y.ct
from (
select person,
datediff(max(log_time),min(log_time)) as diff,
count(log_time) as ct
from pers
group by person) as y
where y.ct > 1
and y.diff <= 7
;
PERSON DIFF COUNT(LOG_TIME)
1 1 3
2 8 3
PERSON CT
1 3
declare #Count int
set #count=(
select COUNT(*)
from timeslot
where (( (TimeFrom<#Timefrom and TimeTo >#Timefrom)
or (TimeFrom<#Timeto and TimeTo >#Timeto))
or (TimeFrom=#Timefrom or TimeTo=#Timeto)))
I have a table with rows that symbolize order dates:
2009-05-15 13:31:47.713
2009-05-15 22:09:32.227
2009-05-16 02:38:36.027
2009-05-16 12:06:49.743
2009-05-16 16:20:26.680
2009-05-17 01:36:19.480
2009-05-18 09:44:46.993
2009-05-18 14:06:12.073
2009-05-18 15:25:47.540
2009-05-19 10:28:24.150
I would like have query that returns the following:
2009-05-15 2
2009-05-16 5
2009-05-17 6
2009-05-18 9
2009-05-19 10
Basically it keeps a running total of all the orders placed by the end of the day of the date indicated. The orders are not the orders on that day but all the orders since the earliest dates in the table.
This is MSSQL 2000 and the datatype in the first table is just datetime, in the second it could be datetime or string, it doesn't really matter for my purposes.
I got this to work on SQL Server 2005. I think it should work with 2000, as well.
SELECT dt, count(q2.YourDate)
FROM (SELECT DISTINCT CONVERT(varchar,YourDate,101) dt FROM YourTable) t1
JOIN YourTable q2 ON DATEADD(d,-1,CONVERT(varchar,YourDate,101)) < dt
GROUP BY dt
This will query the table twice, but at least gives correct output.
I recommend a 2 query solution. This is slow, but I use this method almost daily. The important thing is to NOT join the 2 tables in the first query. You want the duplication of each order for every date in your lookup table.
You will need a Lookup table with 1 row for each date of the time period you're interested in. Let's call it dboDateLookup. Here's what it will look like:
DtIndex
2009-05-15
2009-05-16
2009-05-17
2009-05-18
2009-05-19
Let's also assume the order table, dboOrders has 2 columns, ordernumber and orderdate.
ordernumber orderdate
2009-05-15 13:31:47.713 1
2009-05-15 22:09:32.227 2
2009-05-16 02:38:36.027 3
2009-05-16 12:06:49.743 4
2009-05-16 16:20:26.680 5
Query1:
SELECT
Format([ordernumber],"yyyy-mm-dd") AS ByDate,
ordernumber,
(If Format([orderdate],"yyyy-mm-dd")<=[DtIndex],1,0) AS NumOrdersBefore
FROM [dboOrders], [dboDateLookUp];
Query2:
Select
[ByDate],
sum([NumOrdersBefore]) as RunningTotal
from [Query1];
Try this (returns string dates):
SELECT
LEFT(CONVERT(char(23),YourDate,121),10) AS Date
,COUNT(*) AS CountOf
FROM YourTable
GROUP BY LEFT(CONVERT(char(23),YourDate,121),10)
ORDER BY 1
this will table scan. if it is too slow, consider using a persistant computed column with an index for the date, that will run much faster. However, I'mnot sure if you can do all that in SQL 2000.
EDIT read the question better, try this:
SELECT
d.YourDate
,SUM(dt.CountOf) AS CountOf
FROM (SELECT
LEFT(CONVERT(char(23),YourDate,121),10) AS Date
,COUNT(*) AS CountOf
FROM YourTable
GROUP BY LEFT(CONVERT(char(23),YourDate,121),10)
) dt
INNER JOIN (SELECT
DISTINCT LEFT(CONVERT(char(23),YourDate,121),10) AS Date
FROM YourTable
) d ON dt.Date<=LEFT(CONVERT(char(23),d.YourDate,121),10)
GROUP BY d.YourDate
ORDER BY d.YourDate
I have another one
It is not so fancy
I ran it on Access so syntax may differ little bit.
But it seems to work.
P.S. Im relatively new to SQL
Data:
ID F1 F2
1 15/05/2009 13:31:47.713
2 15/05/2009 22:09:32.227
3 16/05/2009 02:38:36.027
4 16/05/2009 12:06:49.743
5 16/05/2009 16:20:26.680
6 17/05/2009 01:36:19.480
7 18/05/2009 09:44:46.993
8 18/05/2009 14:06:12.073
9 18/05/2009 15:25:47.540
10 19/05/2009 10:28:24.150
Query:
SELECT Table1.F1 AS Dates, SUM(REPLACE(Len(Table1.F2), Len(Table1.F2), 1)) AS Occurred
FROM Table1
GROUP BY Table1.F1;
Result:
Dates Occurred
15/05/2009 2
16/05/2009 3
17/05/2009 1
18/05/2009 3
19/05/2009 1
SELECT Count(*), LEFT(CONVERT(char(23),YourDate,121),10) AS Date FROM
(SELECT
DISTINCT LEFT(CONVERT(char(23),YourDate,121),10) AS Date
FROM YourTable
GROUP BY LEFT(CONVERT(char(23),YourDate,121),10)) x //Gets the distinct dates.
INNER JOIN YourTable y on x.Date >= y.Date
GROUP BY LEFT(CONVERT(char(23),YourDate,121),10)
It's going to be slow. REALLY REALLY slow. I hate to think what run times would be.