I have a requirement to print the corresponding highest year and highest quarter for a given column.
Input is in a table:
cityprogram year quarter
=========== ==== =======
Abc 1998 1
Abc 1999 4
Abc 1999 4
Abc 1998 3
xyz 1998 4
xyz 1998 1
xyz 2000 3
It should print
Abc 1999 4
xyz 2000 3
I tried many joins, max conditions, I seem to get quarter 4 and 4 for both of them :( thanks
Use a window function like ROW_NUMBER in a common-table-expression:
WITH CTE AS(
SELECT [cityprogram], [year], [quarter],
RN = ROW_NUMBER() OVER (
PARTITION BY [cityprogram]
ORDER BY [year] DESC, [quarter] DESC)
FROM dbo.TableName
)
SELECT [cityprogram], [year], [quarter]
FROM CTE
WHERE RN = 1
DEMO
CITYPROGRAM YEAR QUARTER
Abc 1999 4
xyz 2000 3
ROW_NUMBER returns only one row per group even if there are ties(cityprograms with the same highest year+quarter). If you then want to show all highest you can replace ROW_NUMBER with DENSE_RANK.
Related
I have a table with column cust_id, year_, month_, monthly_txn, monthly_bal. I need
to calculate the previous three month and previous six month avg(monthly_txn) and variance(monthly_bal) for each month. I have a query which returns avg and variance for last three and six month only for last month not for each month. I am not good in analytical function in Hive.
SELECT cust_id, avg(monthly_txn)y,variance(monthly_bal)x, FROM (
SELECT cust_id, monthly_txn,monthly_bal,
row_number() over (partition by cust_id order by year_,month_ desc) r
from mytable) b WHERE r <= 3 GROUP BY cust_id
But I want something like below.
input:
cust_id year_ month_ monthly_txn monthly_bal
1 2018 1 456 8979289
1 2018 2 675 4567
1 2018 3 645 4890
1 2017 1 342 44522
1 2017 2 378 9898900
1 2017 2 456 234492358
1 2017 4 3535 789
1 2017 5 456 345
1 2017 6 598 334
expecting output:
suppose for txn the quaterly and half yearly txn will be like this same for variance also
cust_id year_ month_ monthly_txn monthly_bal q_avg_txn h_avg_txn
1 2018 1 456 8979289 avg(456,598,4561) avg(456,598,4561,3535,4536,378)
1 2018 2 675 4567 avg(675,456,598) avg(675,456,3535,4561,598,4536)
1 2018 3 645 4890 avg(645,675,645) avg(645,675,645,3535,4561,598)
1 2017 1 342 44522 avg(342) avg(342)
1 2017 2 378 9898900 avg(378,342) avg(378,342)
1 2017 3 4536 234492358 avg(4536,372,342) avg(4536,378,342)
1 2017 4 3535 789 avg(3535,4536,378) avg(3535,4536,378,342)
1 2017 5 4561 345 avg(4561,3535,4536) avg(4561,3535,4536,342,378)
1 2017 6 598 334 avg(598,4561,3535) avg(598,4561,3535,4536,342,378)
use unbounded preceding analytic functions (/* to get the quarterly and half years values) and then use the subquery to get results.
What is ROWS UNBOUNDED PRECEDING used for in Teradata?
If you have data for every month of interest (i.e., no gaps), then this should work:
select t.*,
avg(monthly_bal) over (partition by cust_id
order by year_, month_
rows between 2 preceding and current row
) as avg_3,
avg(monthly_bal) over (partition by cust_id
order by year_, month_
rows between 5 preceding and current row
) as avg_6,
variance(monthly_bal) over (partition by cust_id
order by year_, month_
rows between 2 preceding and current row
) as variance_3,
variance(monthly_bal) over (partition by cust_id
order by year_, month_
rows between 5 preceding and current row
) as variance_6
from mytable t;
I need to count a value (M_Id) at each change of a date (RS_Date) and create a column grouped by the RS_Date that has an active total from that date.
So the table is:
Ep_Id Oa_Id M_Id M_StartDate RS_Date
--------------------------------------------
1 2001 5 1/1/2014 1/1/2014
1 2001 9 1/1/2014 1/1/2014
1 2001 3 1/1/2014 1/1/2014
1 2001 11 1/1/2014 1/1/2014
1 2001 2 1/1/2014 1/1/2014
1 2067 7 1/1/2014 1/5/2014
1 2067 1 1/1/2014 1/5/2014
1 3099 12 1/1/2014 3/2/2014
1 3099 14 2/14/2014 3/2/2014
1 3099 4 2/14/2014 3/2/2014
So my goal is like
RS_Date Active
-----------------
1/1/2014 5
1/5/2014 7
3/2/2014 10
If the M_startDate = RS_Date I need to count the M_id and then for
each RS_Date that is not equal to the start date I need to count the M_Id and then add that to the M_StartDate count and then count the next RS_Date and add that to the last active count.
I can get the basic counts with something like
(Case when M_StartDate <= RS_Date
then [m_Id] end) as Test.
But I am stuck as how to get to the result I want.
Any help would be greatly appreciated.
Brian
-added in response to comments
I am using Server Ver 10
If using SQL SERVER 2012+ you can use ROWS with your the analytic/window functions:
;with cte AS (SELECT RS_Date
,COUNT(DISTINCT M_ID) AS CT
FROM Table1
GROUP BY RS_Date
)
SELECT *,SUM(CT) OVER(ORDER BY RS_Date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS Run_CT
FROM cte
Demo: SQL Fiddle
If stuck using something prior to 2012 you can use:
;with cte AS (SELECT RS_Date
,COUNT(DISTINCT M_ID) AS CT
FROM Table1
GROUP BY RS_Date
)
SELECT a.RS_Date
,SUM(b.CT)
FROM cte a
LEFT JOIN cte b
ON a.RS_DAte >= b.RS_Date
GROUP BY a.RS_Date
Demo: SQL Fiddle
You need a cumulative sum, easy in SQL Server 2012 using Windowed Aggregate Functions. Based on your description this will return the expected result
SELECT p_id, RS_Date,
SUM(COUNT(*))
OVER (PARTITION BY p_id
ORDER BY RS_Date
ROWS UNBOUNDED PRECEDING)
FROM tab
GROUP BY p_id, RS_Date
It looks like you want something like this:
SELECT
RS_Date,
SUM(c) OVER (PARTITION BY M_StartDate ORDER BY RS_Date ROWS UNBOUNDED PRECEEDING)
FROM
(
SELECT M_StartDate, RS_Date, COUNT(DISTINCT M_Id) AS c
FROM my_table
GROUP BY M_StartDate, RS_Date
) counts
The inline view computes the counts of distinct M_Id values within each (M_StartDate, RS_Date) group (distinctness enforced only within the group), and the outer query uses the analytic version of SUM() to add up the counts within each M_StartDate.
Note that this particular query will not exactly reproduce your example results. It will instead produce:
RS_Date Active
-----------------
1/1/2014 5
1/5/2014 7
3/2/2014 8
3/2/2014 2
This is on account of some rows in your example data with RS_Date 3/2/2014 having a later M_StartDate than others. If this is not what you want then you need to clarify the question, which currently seems a bit inconsistent.
Unfortunately, analytic functions are not available until SQL Server 2012. In SQL Server 2010, the job is messier. It could be done like this:
WITH gc AS (
SELECT M_StartDate, RS_Date, COUNT(DISTINCT M_Id) AS c
FROM my_table
GROUP BY M_StartDate, RS_Date
)
SELECT
RS_Date,
(
SELECT SUM(c)
FROM gc2
WHERE gc2.M_StartDate = gc.M_StartDate AND gc2.RS_Date <= gc.RS_Date
) AS Active
FROM gc
If you are using SQL 2012 or newer you can use LAG to produce a running total.
https://msdn.microsoft.com/en-us/library/hh231256(v=sql.110).aspx
I am trying to write a query to select the total outbound usage of each pharmacy in my database table for each month.
Here is what I have so far, it outputs the correct data. But I want to eliminate the amount of rows selected
select pharmacyid, count(*) as usage, month(datecalled) as month
from outboundcalldata
where datepart(year, datecalled) = 2014
group by pharmacyid, YEAR(DateCalled), month(datecalled)
order by pharmacyid, month
example of output:
pharmacyid|usage| month
-----------------------
2220000006| 10 | 2
2220000006| 11 | 3
2220000006| 900 | 4
2220000006| 30 | 5
2220000007| 34 | 2
2220000007| 300 | 3
2220000007| 145 | 4
Instead I would like it to output 1 row per pharmacy and a column for each month.
;WITH CTE AS
(
select pharmacyid, count(*) as usage, month(datecalled) as [month]
from outboundcalldata
where datepart(year, datecalled) = 2014
group by pharmacyid, YEAR(DateCalled), month(datecalled)
)
SELECT *
FROM CTE C
PIVOT (SUM(usage)
FOR [month]
IN ([1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12])
)p
It was hard to come up with an understandable title for this question.
I'll try to explain with an example.
First I had a simple table INFO in Oracle DB:
year type message
---- ---- -------
2001 1 cakes are yammy
2003 2 apples are dangerous
2012 2 bananas are suspicious
2005 3 cats are tricky
And I need to select newest messages of certain types (for example type = 1 or type = 2):
2001 1 cakes are yammy
2012 2 bananas are suspicious
So I used the query:
select * from INFO i
where year = (select max(year) from INFO i_last where i.type = i_last.type)
and i.type in (1, 2)
But now I need to add a new "quarter" column to my INFO table. And select the newest records by year and quarter.
year quarter type message
---- ------- ---- -------
2001 2 1 cakes are yammy
2012 3 2 onions are cruel
2012 1 2 bananas are suspicious
2005 1 3 cats are tricky
The newest records with type 1 or 2 will be:
2001 2 1 cakes are yammy
2012 3 2 onions are cruel
How should such query look like?
Analytic functions are your friend:
SELECT MAX( year ) KEEP ( DENSE_RANK LAST ORDER BY year ASC, quarter ASC, message ASC ) AS year,
MAX( quarter ) KEEP ( DENSE_RANK LAST ORDER BY year ASC, quarter ASC, message ASC ) AS quarter,
MAX( message ) KEEP ( DENSE_RANK LAST ORDER BY year ASC, quarter ASC, message ASC ) AS message,
type
FROM info
GROUP BY type;
SQLFIDDLE
Give this a shot:
SELECT i.year, i.quarter, i.type, i.message
FROM INFO i
JOIN INFO iy
ON i.type = iy.type
JOIN INFO iq
ON iq.type = iy.type
WHERE i.type IN (1,2)
GROUP BY i.year, i.quarter, i.type, i.message
HAVING i.year = MAX(iy.year) AND i.quarter = MAX(iq.quarter)
Say I have a table
StoreID TotalSales Month Year
-- ---------- ----- ----
1 10 1 2012
2 2 1 2012
3 15 1 2012
1 4 2 2012
2 5 2 2012
I need: For each unique "Month/Year", grab the top two StoreID's with the highest Sales.
I'm at a loss on how to do this. I tried with a cross apply but that doesn't seem to work. This is all way over my head so hopefully someone can give me a nudge in the right direction.
This query uses Common Table Expression and Window Function to be able to get all the columns within the row. It works on SQL Server 2005 and up
WITH records
AS
(
SELECT StoreID, TotalSales , Month, Year,
DENSE_RANK() OVER (PARTITION BY Month, Year
ORDER BY TotalSales DESC) rn
FROM tableName
)
SELECT StoreID, TotalSales , Month, Year
FROM records
WHERE rn <= 2
SQLFiddle Demo