I have the following MS SQL query which cross references three tables, (tTeam, tPlayer and tScores) to get the total "Net score", "Gross score" and "Position" ordered by Net score and Team.
SELECT TeamID, Team, NetScore, Gross,
CASE WHEN cnt > 1 THEN 'T' + CAST(rnk AS VARCHAR(5))
ELSE CAST(rnk AS VARCHAR(5))
END Pos
FROM (
SELECT tTeam.TeamID,
tTeam.Title AS Team,
SUM(CONVERT(INT, tScores.Net_Score)) AS NetScore,
SUM(CONVERT(INT, tScores.Out_Score) + CONVERT(int, tScores.In_Score)) AS Gross,
rank() OVER ( ORDER BY SUM(CONVERT(INT, tScores.Net_Score))) rnk,
COUNT(*) OVER ( PARTITION BY SUM(CONVERT(INT, tScores.Net_Score))) cnt
FROM tScores INNER JOIN tPlayer ON tScores.PlayerID = tPlayer.PlayerID INNER JOIN tTeam ON tPlayer.TeamID = tTeam.TeamID
WHERE tTeam.TournamentID = 13
GROUP BY tTeam.TeamID, tTeam.Title ) temp
ORDER BY NetScore, Team
The query works great but (and here is where i need some help), it is calculating all of the players Net and Gross scores by team when all I need it to do is calculate the "4 lowest Player's Net and Gross Scores" by team only.
I have spent the last day and a half pulling my hair out with this one and any help will be greatly appreciated.
Thanks in advance!
If I understood correctly that you want to sum four lowest scores per player only, you might use another set of row_numbers to isolate lowest scores. I don't think that rn_gross is necessary (based on rank() function) but I included it nevertheless. If there is no need for separate numbering remove conditionals from sums and add and lowestScores.rn_net <= 4 to where clause.
; with lowestScores as
(
select *,
ROW_NUMBER() over (PARTITION by PlayerID
order by CONVERT(INT, Net_Score)) rn_net,
ROW_NUMBER() over (PARTITION by PlayerID
order by CONVERT(INT, Net_Score) + CONVERT(int,In_Score)) rn_gross
from tScores
),
temp as
(
SELECT tTeam.TeamID,
tTeam.Title AS Team,
SUM(CASE WHEN rn_net <= 4 THEN CONVERT(INT, lowestScores.Net_Score) END) AS NetScore,
SUM(CASE WHEN rn_gross <= 4 THEN CONVERT(INT, lowestScores.Out_Score) END
+ CASE WHEN rn_gross <= 4 THEN CONVERT(int, lowestScores.In_Score) END) AS Gross,
rank() OVER ( ORDER BY SUM(CASE WHEN rn_net <= 4 THEN CONVERT(INT, lowestScores.Net_Score) END)) rnk,
COUNT(*) OVER ( PARTITION BY SUM(CASE WHEN rn_net <= 4 THEN CONVERT(INT, lowestScores.Net_Score) END)) cnt
FROM lowestScores
INNER JOIN tPlayer
ON lowestScores.PlayerID = tPlayer.PlayerID
INNER JOIN tTeam
ON tPlayer.TeamID = tTeam.TeamID
WHERE tTeam.TournamentID = 13
GROUP BY tTeam.TeamID, tTeam.Title
)
SELECT TeamID, Team, NetScore, Gross,
CASE WHEN cnt > 1
THEN 'T' + CAST(rnk AS VARCHAR(5))
ELSE CAST(rnk AS VARCHAR(5))
END Pos
FROM temp
ORDER BY NetScore, Team
Related
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
I have a table that has data like following.
attr |time
----------------|--------------------------
abc |2018-08-06 10:17:25.282546
def |2018-08-06 10:17:25.325676
pqr |2018-08-05 10:17:25.366823
abc |2018-08-06 10:17:25.407941
def |2018-08-05 10:17:25.449249
I want to group them and count by attr column row wise and also create additional columns in to show their counts per day and percentages as shown below.
attr |day1_count| day1_%| day2_count| day2_%
----------------|----------|-------|-----------|-------
abc |2 |66.6% | 0 | 0.0%
def |1 |33.3% | 1 | 50.0%
pqr |0 |0.0% | 1 | 50.0%
I'm able to display one count by using group by but unable to find out how to even seperate them to multiple columns. I tried to generate day1 percentage with
SELECT attr, count(attr), count(attr) / sum(sub.day1_count) * 100 as percentage from (
SELECT attr, count(*) as day1_count FROM my_table WHERE DATEPART(week, time) = DATEPART(day, GETDate()) GROUP BY attr) as sub
GROUP BY attr;
But this also is not giving me correct answer, I'm getting all zeroes for percentage and count as 1. Any help is appreciated. I'm trying to do this in Redshift which follows postgresql syntax.
Let's nail the logic before presenting:
with CTE1 as
(
select attr, DATEPART(day, time) as theday, count(*) as thecount
from MyTable
)
, CTE2 as
(
select theday, sum(thecount) as daytotal
from CTE1
group by theday
)
select t1.attr, t1.theday, t1.thecount, t1.thecount/t2.daytotal as percentofday
from CTE1 t1
inner join CTE2 t2
on t1.theday = t2.theday
From here you can pivot to create a day by day if you feel the need
I am trying to enhance the query #johnHC btw if you needs for 7days then you have to those days in case when
with CTE1 as
(
select attr, time::date as theday, count(*) as thecount
from t group by attr,time::date
)
, CTE2 as
(
select theday, sum(thecount) as daytotal
from CTE1
group by theday
)
,
CTE3 as
(
select t1.attr, EXTRACT(DOW FROM t1.theday) as day_nmbr,t1.theday, t1.thecount, t1.thecount/t2.daytotal as percentofday
from CTE1 t1
inner join CTE2 t2
on t1.theday = t2.theday
)
select CTE3.attr,
max(case when day_nmbr=0 then CTE3.thecount end) as day1Cnt,
max(case when day_nmbr=0 then percentofday end) as day1,
max(case when day_nmbr=1 then CTE3.thecount end) as day2Cnt,
max( case when day_nmbr=1 then percentofday end) day2
from CTE3 group by CTE3.attr
http://sqlfiddle.com/#!17/54ace/20
In case that you have only 2 days:
http://sqlfiddle.com/#!17/3bdad/3 (days descending as in your example from left to right)
http://sqlfiddle.com/#!17/3bdad/5 (days ascending)
The main idea is already mentioned in the other answers. Instead of joining the CTEs for calculating the values I am using window functions which is a bit shorter and more readable I think. The pivot is done the same way.
SELECT
attr,
COALESCE(max(count) FILTER (WHERE day_number = 0), 0) as day1_count, -- D
COALESCE(max(percent) FILTER (WHERE day_number = 0), 0) as day1_percent,
COALESCE(max(count) FILTER (WHERE day_number = 1), 0) as day2_count,
COALESCE(max(percent) FILTER (WHERE day_number = 1), 0) as day2_percent
/*
Add more days here
*/
FROM(
SELECT *, (count::float/count_per_day)::decimal(5, 2) as percent -- C
FROM (
SELECT DISTINCT
attr,
MAX(time::date) OVER () - time::date as day_number, -- B
count(*) OVER (partition by time::date, attr) as count, -- A
count(*) OVER (partition by time::date) as count_per_day
FROM test_table
)s
)s
GROUP BY attr
ORDER BY attr
A counting the rows per day and counting the rows per day AND attr
B for more readability I convert the date into numbers. Here I take the difference between current date of the row and the maximum date available in the table. So I get a counter from 0 (first day) up to n - 1 (last day)
C calculating the percentage and rounding
D pivot by filter the day numbers. The COALESCE avoids the NULL values and switched them into 0. To add more days you can multiply these columns.
Edit: Made the day counter more flexible for more days; new SQL Fiddle
Basically, I see this as conditional aggregation. But you need to get an enumerator for the date for the pivoting. So:
SELECT attr,
COUNT(*) FILTER (WHERE day_number = 1) as day1_count,
COUNT(*) FILTER (WHERE day_number = 1) / cnt as day1_percent,
COUNT(*) FILTER (WHERE day_number = 2) as day2_count,
COUNT(*) FILTER (WHERE day_number = 2) / cnt as day2_percent
FROM (SELECT attr,
DENSE_RANK() OVER (ORDER BY time::date DESC) as day_number,
1.0 * COUNT(*) OVER (PARTITION BY attr) as cnt
FROM test_table
) s
GROUP BY attr, cnt
ORDER BY attr;
Here is a SQL Fiddle.
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.
A "Case" in CRM has a field called "Status" with four options.
I'm trying to
build a report in CRM that fills a table with every week of the year (each row is a different week), and then counts the number of cases that have each Status option (the columns would be each of the Status options).
The table would look like this
Status 1 Status 2 Status 3
Week 1 3 55 4
Week 2 5 23 5
Week 3 14 11 33
So far I have the following:
SELECT
SUM(case WHEN status = 1 then 1 else 0 end) Status1,
SUM(case WHEN status = 2 then 1 else 0 end) Status2,
SUM(case WHEN status = 3 then 1 else 0 end) Status3,
SUM(case WHEN status = 4 then 1 else 0 end) Status4,
SUM(case WHEN status = 5 then 1 else 0 end) Status5
FROM [DB].[dbo].[Contact]
Which gives me the following:
Status 1 Status 2 Status 3
2 43 53
Now I need to somehow split this into 52 rows for the past year and filter these results by date (columns in the Contact table). I'm a bit new to SQL queries and CRM - any help here would be much appreciated.
Here is a SQLFiddle with my progress and sample data: http://sqlfiddle.com/#!2/85b19/1
Sounds like you want to group by a range. The trick is to create a new field that represents each range (for you one per year) and group by that.
Since it also seems like you want an infinite range of dates, marc_s has a good summary for how to do the group by trick with dates in a generic way: SQL group by frequency within a date range
So, let's break this down:
You want to make a report that shows, for each contact, a breakdown, week by week, of the number of cases registered to that contact, which is divided into three columns, one for each StateCode.
If this is the case, then you would need to have 52 date records (or so) for each contact. For calendar like requests, it's always good to have a separate calendar table that lets you query from it. Dan Guzman has a blog entry that creates a useful calendar table which I'll use in the query.
WITH WeekNumbers AS
(
SELECT
FirstDateOfWeek,
-- order by first date of week, grouping calendar year to produce week numbers
WeekNumber = row_number() OVER (PARTITION BY CalendarYear ORDER BY FirstDateOfWeek)
FROM
master.dbo.Calendar -- created from script
GROUP BY
FirstDateOfWeek,
CalendarYear
), Calendar AS
(
SELECT
WeekNumber =
(
SELECT
WeekNumber
FROM
WeekNumbers WN
WHERE
C.FirstDateOfWeek = WN.FirstDateOfWeek
),
*
FROM
master.dbo.Calendar C
WHERE
CalendarDate BETWEEN '1/1/2012' AND getutcdate()
)
SELECT
C.FullName,
----include the below if the data is necessary
--Cl.WeekNumber,
--Cl.CalendarYear,
--Cl.FirstDateOfWeek,
--Cl.LastDateOfWeek,
'Week: ' + CAST(Cl.WeekNumber AS VARCHAR(20))
+ ', Year: ' + CAST(Cl.CalendarYear AS VARCHAR(20)) WeekNumber
FROM
CRM.dbo.Contact C
-- use a cartesian join to produce a table list
CROSS JOIN
(
SELECT
DISTINCT WeekNumber,
CalendarYear,
FirstDateOfWeek,
LastDateOfWeek
FROM
Calendar
) Cl
ORDER BY
C.FullName,
Cl.WeekNumber
This is different from the solution Ben linked to because Marc's query only returns weeks where there is a matching value, whereas you may or may not want to see even the weeks where there is no activity.
Once you have your core tables of contacts split out week by week as in the above (or altered for your specific time period), you can simply add a subquery for each StateCode to see the breakdown in columns as in the final query below.
WITH WeekNumbers AS
(
SELECT
FirstDateOfWeek,
WeekNumber = row_number() OVER (PARTITION BY CalendarYear ORDER BY FirstDateOfWeek)
FROM
master.dbo.Calendar
GROUP BY
FirstDateOfWeek,
CalendarYear
), Calendar AS
(
SELECT
WeekNumber =
(
SELECT
WeekNumber
FROM
WeekNumbers WN
WHERE
C.FirstDateOfWeek = WN.FirstDateOfWeek
),
*
FROM
master.dbo.Calendar C
WHERE
CalendarDate BETWEEN '1/1/2012' AND getutcdate()
)
SELECT
C.FullName,
--Cl.WeekNumber,
--Cl.CalendarYear,
--Cl.FirstDateOfWeek,
--Cl.LastDateOfWeek,
'Week: ' + CAST(Cl.WeekNumber AS VARCHAR(20)) +', Year: ' + CAST(Cl.CalendarYear AS VARCHAR(20)) WeekNumber,
(
SELECT
count(*)
FROM
CRM.dbo.Incident I
INNER JOIN CRM.dbo.StringMap SM ON
I.StateCode = SM.AttributeValue
INNER JOIN
(
SELECT
DISTINCT ME.Name,
ME.ObjectTypeCode
FROM
CRM.MetadataSchema.Entity ME
) E ON
SM.ObjectTypeCode = E.ObjectTypeCode
WHERE
I.ModifiedOn >= Cl.FirstDateOfWeek
AND I.ModifiedOn < dateadd(day, 1, Cl.LastDateOfWeek)
AND E.Name = 'incident'
AND SM.AttributeName = 'statecode'
AND SM.LangId = 1033
AND I.CustomerId = C.ContactId
AND SM.Value = 'Active'
) ActiveCases,
(
SELECT
count(*)
FROM
CRM.dbo.Incident I
INNER JOIN CRM.dbo.StringMap SM ON
I.StateCode = SM.AttributeValue
INNER JOIN
(
SELECT
DISTINCT ME.Name,
ME.ObjectTypeCode
FROM
CRM.MetadataSchema.Entity ME
) E ON
SM.ObjectTypeCode = E.ObjectTypeCode
WHERE
I.ModifiedOn >= Cl.FirstDateOfWeek
AND I.ModifiedOn < dateadd(day, 1, Cl.LastDateOfWeek)
AND E.Name = 'incident'
AND SM.AttributeName = 'statecode'
AND SM.LangId = 1033
AND I.CustomerId = C.ContactId
AND SM.Value = 'Resolved'
) ResolvedCases,
(
SELECT
count(*)
FROM
CRM.dbo.Incident I
INNER JOIN CRM.dbo.StringMap SM ON
I.StateCode = SM.AttributeValue
INNER JOIN
(
SELECT
DISTINCT ME.Name,
ME.ObjectTypeCode
FROM
CRM.MetadataSchema.Entity ME
) E ON
SM.ObjectTypeCode = E.ObjectTypeCode
WHERE
I.ModifiedOn >= Cl.FirstDateOfWeek
AND I.ModifiedOn < dateadd(day, 1, Cl.LastDateOfWeek)
AND E.Name = 'incident'
AND SM.AttributeName = 'statecode'
AND SM.LangId = 1033
AND I.CustomerId = C.ContactId
AND SM.Value = 'Canceled'
) CancelledCases
FROM
CRM.dbo.Contact C
CROSS JOIN
(
SELECT
DISTINCT WeekNumber,
CalendarYear,
FirstDateOfWeek,
LastDateOfWeek
FROM
Calendar
) Cl
ORDER BY
C.FullName,
Cl.WeekNumber
I have a table containing the following line:
I'd like to create a view that displays the following result (without changing my original table) :
For each line having the same id,day,month and year I'd like to leave a single line with the cost and count and insert 0 in the others.
Here is a portable approach not requiring PARTITION. I have assumed you will not have the same datetimeIN value for more than one row in a group:
select t.id, t.day, t.month, t.year,
case when tm.id is null then 0 else t.cost end as cost,
case when tm.id is null then 0 else t.Count end as Count,
t.datetimeIN, t.datetimeOUT
from MyTable t
left outer join (
select id, day, month, year, min(datetimeIN) as minIN
from MyTable
group by id, day, month, year
) tm on t.id = tm.id
and t.day = tm.day
and t.month = tm.month
and t.year = tm.year
and t.datetimeIN = tm.minIN
You can do something like this:
SELECT id, day, month, year,
CASE WHEN nNum = 1 then cost else 0 end as cost,
CASE WHEN nNum = 1 then "Count" else 0 end as "Count",
datetimeIN, datetimeOUT
FROM (
SELECT id, day, month, year,
cost, "Count", datetimeIN, datetimeOUT,
row_number() OVER (PARTITION BY id, day, month, year
ORDER BY datetimeIN) as nNum
FROM TableName
) A
It uses row_number() to number the rows, and then a CASE statement to single out the first one and make it behave differently.
See it working on SQL Fiddle here.
or, using a common table expression:
with commonTableExp ([day], [month], [year], minDate) as (
select [day], [month], [year], min(datetimeIn)
from #temp
group by [day], [month], [year])
select id,
dt.[day],
dt.[month],
dt.[year],
case when datetimein = minDate then [cost] else 0 end,
case when datetimein = minDate then [count] else 0 end,
dateTimeIn
from #temp dt join commonTableExp cte on
dt.[day] = cte.[day] and
dt.[month] = cte.[month] and
dt.[year] = cte.[year]
order by dateTimeIn
Query
Select id, [day], [month], [year], Case When K.RowID = 1 Then [cost] Else 0 End as Cost, Case When K.RowID = 1 Then [count] Else 0 End as [count], [DateTimeIN], [DateTimeOut] From
(
select ROW_NUMBER() Over(Partition by id, [day], [month], [year] Order by ID ) as RowID, * From Testing
)K
Drop table Testing
Click here to see SQL Profiler details for Red Filter's Query
Click here to see SQL Profiler details for my Query
For More Information You can see SQL Fiddle