I am trying to do a 12 month rolling calculation, but I get a syntax error at "rows", here is what I have so far:
(SUM(YTDValue) OVER (ORDER BY PerformanceDate ROWS BETWEEN 11 PRECEDING AND CURRENT ROW)) / 12 AS Yearly_YTDValue
It might be your RDMBS doesn't support that syntax, because at first glance it looks correct to me.
This method will only work if you are guaranteed to have exactly 12 PerformanceDates, so sometimes I prefer this method because it does not require me to aggregate the data to monthly levels first.
WITH BASIC_OFFSET_7DAY AS (
SELECT
A.DATE,
SUM(B.YTDValue) as Yearly_YTDValue
FROM
UserActivity A
JOIN UserActivity B
WHERE
B.DATE >= DATEADD(year, -12, A.DATE)
AND B.DATE <= A.DATE
GROUP BY A.DATE
)
SELECT
src.*,
BASIC_OFFSET_7DAY.Yearly_YTDValue
FROM
UserActivity src
LEFT OUTER JOIN BASIC_OFFSET_7DAY ON BASIC_OFFSET_7DAY.DATE = src.DATE
Related
I am pulling transactions that happen on an attribute (attribute ID 4205 in table 1235) by the date that a change happened to the attribute (found in the History table) and counting up the number of changes that occurred by month. So far I have
SELECT TOP(100) PERCENT MONTH(H.transactiondate) AS Month, COUNT(*) AS Count
FROM hsi.rmObjectInstance1235 AS O LEFT OUTER JOIN
hsi.rmObjectHistory AS H ON H.objectID = O.objectID
WHERE H.attributeid = 4205) AND Year(H.transaction date) = '2020'
GROUP BY MONTH(H.transactiondate)
And I get
Month Count
---------------
1 9
2 4
3 11
4 14
5 1
I need to display a zero for months June - December instead of excluding those months.
One option uses a recursive query to generate the dates, and then brings the original query with a left join:
with all_dates as (
select cast('2020-01-01' as date) dt
union all
select dateadd(month, 1, dt) from all_dates where dt < '2020-12-01'
)
select
month(d.dt) as month,
count(h.objectid) as cnt
from all_dates d
left join hsi.rmobjecthistory as h
on h.attributeid = 4205
and h.transaction_date >= d.dt
and h.transaction_date < dateadd(month, 1, d.dt)
and exists (select 1 from hsi.rmObjectInstance1235 o where o.objectID = h.objectID)
group by month(d.dt)
I am quite unclear about the intent of the table hsi.rmObjectInstance1235 in the query, as none of its column are used in the select and group by clauses; it it is meant to filter hsi.rmobjecthistory by objectID, then you can rewrite this as an exists condition, as shown in the above solution. Possibly, you might as well be able to just remove that part of the query.
Also, note that
top without order by does not really make sense
top (100) percent is a no op
As a consequence, I removed that row-limiting clause.
I have user logins by date. My requirement is to track the number of users that have been logged in during the past 90 days window.
I am new to both SQL in general and Teradata specifically and I can't get the window functionality to work as I need.
I need the following result, where ACTIVE is a count of the unique USER_IDs that appear in the previous 90 day window the DATE.
DATES ACTIVE_IN_WINDOW
12/06/2018 20
13/06/2018 45
14/06/2018 65
15/06/2018 73
17/06/2018 24
18/06/2018 87
19/06/2018 34
20/06/2018 51
Currently my script is as follows.
It is this line here that I cant get right
COUNT ( USER_ID) OVER (PARTITION BY USER_ID ORDER BY EVT_DT ROWS BETWEEN 90 PRECEDING AND 0 FOLLOWING)
I suspect I need a different set of functions to make this work.
SELECT b.DATES , a.ACTIVE_IN_WINDOW
FROM
(
SELECT
CAST(CALENDAR_DATE AS DATE) AS DATES FROM SYS_CALENDAR.CALENDAR
WHERE DATES BETWEEN ADD_MONTHS(CURRENT_DATE, - 10) AND CURRENT_DATE
) b
LEFT JOIN
(
SELECT USER_ID , EVT_DT
, COUNT ( USER_ID) OVER (PARTITION BY USER_ID ORDER BY EVT_DT ROWS BETWEEN 90 PRECEDING AND 0 FOLLOWING) AS ACTIVE_IN_WINDOW
FROM ENV0.R_ONBOARDING
) a
ON a.EVT_DT = b.DATES
ORDER BY b.DATES
Thank you for any assistance.
The logic is similar to Gordon', but a non-equi-Join instead of a Correlated Scalar Subquery is usually more efficient on Teradata:
SELECT b.DATES , Count(DISTINCT USER_ID)
FROM
(
SELECT CALENDAR_DATE AS DATES
FROM SYS_CALENDAR.CALENDAR
WHERE DATES BETWEEN Add_Months(Current_Date, - 10) AND Current_Date
) b
LEFT JOIN
( -- apply DISTINCT before aggregation to reduce intermediate spool
SELECT DISTINCT USER_ID, EVT_DT
FROM ENV0.R_ONBOARDING
) AS a
ON a.EVT_DT BETWEEN Add_Months(b.DATES,-3) AND b.DATES
GROUP BY 1
ORDER BY 1
Of course this will require a large spool and much CPU.
Edit:
Switching to weeks reduces the overhead, I'm using dates instead of week numbers (it's easier to modify for other ranges):
SELECT b.Week , Count(DISTINCT USER_ID)
FROM
( -- Return only Mondays instead of DISTINCT over all days
SELECT calendar_date AS Week
FROM SYS_CALENDAR.CALENDAR
WHERE CALENDAR_DATE BETWEEN Add_Months(Current_Date, -9) AND Current_Date
AND day_of_week = 2 -- 2 = Monday
) b
LEFT JOIN
(
SELECT DISTINCT USER_ID,
-- td_monday returns the previous Monday, but we need the following monday
-- covers the previous Tuesday up to the current Monday
Td_Monday(EVT_DT+6) AS PERIOD_WEEK
FROM ENV0.R_ONBOARDING
-- You should add another condition to limit the actually covered date range, e.g.
-- where EVT_DT BETWEEN Add_Months(b.DATES,-13) AND b.DATES
) AS a
ON a.PERIOD_WEEK BETWEEN b.Week-(12*7) AND b.Week
GROUP BY 1
ORDER BY 1
Explain should duplicate the calendar as preparation for the product join, if not you might need to materialize the dates in a Volatile Table. Better don't use sys_calendar, there are no statistics, e.g. optimizer doesn't know about how many days per week/month/year, etc. Check your system, there should be a calendar table designed for you company needs (with stats on all columns)
If your data is not too big, a subquery might be the simplest method:
SELECT c.dte,
(SELECT COUNT(DISTINCT o.USER_ID)
FROM ENV0.R_ONBOARDING o
WHERE o.EVT_DT > ADD_MONTHS(dte, -3) AND
o.EVT_DT <= dte
) as three_month_count
FROM (SELECT CAST(CALENDAR_DATE AS DATE) AS dte
FROM SYS_CALENDAR.CALENDAR
WHERE CALENDAR_DATE BETWEEN ADD_MONTHS(CURRENT_DATE, - 10) AND CURRENT_DATE
) c;
You might want to start on a shorter timeframe then 3 months to see how the query performs.
I have been running a query of the format below
SELECT b.date as Date,COUNT(DISTINCT user_id) AS NewUsers FROM (
SELECT user_id,MIN(date) as min_date
FROM tableA
WHERE date >= '2018-10-10'
AND filter1 = "XYZ"
GROUP BY ) a
CROSS JOIN (
SELECT date FROM tableB
WHERE date >= '2018-10-19' AND date <= CURRENT_DATE()
GROUP BY 1) b
WHERE a.date >= DATE_SUB(b.date, INTERVAL 6 DAY) AND a.date <= b.date
GROUP BY 1
Let's say the above is result1
SELECT b.date as Date,COUNT(DISTINCT user_id) AS NewUsers FROM (
SELECT user_id,MIN(date) as min_date
FROM tableA
WHERE date >= '2018-07-10'
AND filter1 = "XYZ"
GROUP BY ) a
CROSS JOIN (
SELECT date FROM tableB
WHERE date >= '2018-07-19' AND date <= CURRENT_DATE()
GROUP BY 1) b
WHERE a.date >= DATE_SUB(b.date, INTERVAL 6 DAY) AND a.date <= b.date
GROUP BY 1
The above is result2
Here 2018-07-19 is the launch date.
Since I have the data till 2018-10-19, I want to run the query from the later date to optimize the cost and the data consumption by the query....but some how, I am getting incorrect data.
But, if I run the same query from the launch date, I am getting the correct results.
I mean the NewUsers from result1 for the corresponding dates (like date >= 2018-10-19) are more than the NewUsers from result2.
No sure, where I am missing something.
Any help would be greatly appreciated.
Thanks
I think - it is because of use of 'MIN(date)' - You see shift in counts because you restricted dates so those users who were first seen in earlier dates - now those same "old" users are counted for recent days - thus the confusion
I have a table like so
And With this code I get the 5 latest values for each domainId
;WITH grp AS
(
SELECT DomainId, [Date],Passed, DatabasePerformance,ServerPerformance,
rn = ROW_NUMBER() OVER
(PARTITION BY DomainId ORDER BY [Date] DESC)
FROM dbo.DomainDetailDataHistory H
)
SELECT g.DomainId, g.[Date],g.Passed, g.ServerPerformance, g.DatabasePerformance
FROM grp g
INNER JOIN #Latest T ON T.DomainId = g.DomainId
WHERE rn < 7 AND t.date != g.[Date]
ORDER BY DomainId, [Date] DESC
What I Want
Well I would like to know how many tickets were sold for each of these 5 latest rows but with the following condition:
Each of these rows come with their own date which differs.
for each date I want to check how many were sold the last 15minutes AND how many were sold the last 30mns.
Example:
I get these 5 rows for each domainId
I want to extend the above with two columns, "soldTicketsLast15" and "soldTicketsLast30"
The date column contains all the dates I need and for each of these dates I want to go back 15 min and go back 30min to and get how many tickets were sold
Example:
SELECT MAX(SoldTickets) FROM DomainDetailDataHistory
WHERE [Date] >= DATEADD(minute, -15, '2016-04-12 12:10:28.2270000')
SELECT MAX(SoldTickets) FROM DomainDetailDataHistory
WHERE [Date] >= DATEADD(minute, -30, '2016-04-12 12:10:28.2270000')
How can i accomplish this?
I'd use OUTER APPLY or CROSS APPLY.
;WITH grp AS
(
SELECT
DomainId, [Date], Passed, DatabasePerformance, ServerPerformance,
rn = ROW_NUMBER() OVER (PARTITION BY DomainId ORDER BY [Date] DESC)
FROM dbo.DomainDetailDataHistory H
)
SELECT
g.DomainId, g.[Date],g.Passed, g.ServerPerformance, g.DatabasePerformance
,A15.SoldTicketsLast15
,A30.SoldTicketsLast30
FROM
grp g
INNER JOIN #Latest T ON T.DomainId = g.DomainId
OUTER APPLY
(
SELECT MAX(H.SoldTickets) - MIN(H.SoldTickets) AS SoldTicketsLast15
FROM DomainDetailDataHistory AS H
WHERE
H.DomainId = g.DomainId AND
H.[Date] >= DATEADD(minute, -15, g.[Date])
) AS A15
OUTER APPLY
(
SELECT MAX(H.SoldTickets) - MIN(H.SoldTickets) AS SoldTicketsLast30
FROM DomainDetailDataHistory AS H
WHERE
H.DomainId = g.DomainId AND
H.[Date] >= DATEADD(minute, -30, g.[Date])
) AS A30
WHERE
rn < 7
AND T.[date] != g.[Date]
ORDER BY DomainId, [Date] DESC;
To make the correlated APPLY queries efficient there should be an appropriate index, like the following:
CREATE NONCLUSTERED INDEX [IX_DomainId_Date] ON [dbo].[DomainDetailDataHistory]
(
[DomainId] ASC,
[Date] ASC
)
INCLUDE ([SoldTickets])
This index may also help to make the main part of your query (grp) efficient.
If I understood your question correctly, you want to get the tickets sold from one of your dates (in the Date column) going back 15 minutes and 30 minutes. Assuming that you are using your DATEADD function correctly, the following should work:
SELECT MAX(SoldTickets) FROM DomainDetailDataHistory
WHERE [Date] BETWEEN [DATE] AND DATEADD(minute, -15, '2016-04-12 12:10:28.2270000') GROUP BY [SoldTickets]
The between operator allows you to retrieve results between two date parameters. In the SQL above, we also need a group by since you are using a GROUPING function (MAX). The group by would depend on what you want to group by but I think in your case it would be SoldTickets.
The SQL above will give you the ones between the date and 15 minutes back. You could do something similar with the 30 minutes back.
Hi I am trying to write a query that will track daily changes of a column which isn't populated on weekends/holidays.
First my data looks something like this :
Date Value
11/5/2015 10
11/6/2015 11
11/9/2015 12
11/10/2015 12
11/11/2015 11
so i want my query to give me result of the value change each date vs. the previous business day to return something like this:
Date Change in Value since previous business day
11/5/2015 -
11/6/2015 1
11/9/2015 1
11/10/2015 0
11/11/2015 -1
how do i write a write a query in MS Access which tracks daily changes over a business day? Currently i have written the following which only returns daily change over a calendar day as opposed to a biz day. so it won't return anything on Mondays.
SELECT A.Date, A.Value, ( A.Value - B.Value) as [Daily change]
FROM Table as A INNER JOIN Table as B on (A.date = B.date+1)
=============================================================================
thanks guys I've tried all 3 suggestions but they didn't work unfortunately :( there's another column called product ID and perhaps that is why? in other words, on each day, each product ID will have their own distinct values. there is a total of 100 product IDs so on each date there are 100 different values and I would like to track daily changes (business day basis) for each of the 100 product IDs. could anyone kindly help here? :(
It's hacky, but why not:
Join on 3 days ago also
use iif to say "if the 1 day ago diff is null then show the 3 days ago diff"
SELECT
A.Date, A.Value,
iif (isNull( A.Value - B.Value), ( A.Value - C.Value), ( A.Value - B.Value) ) as [change since last biz day]
FROM [Table] as A
left JOIN [Table] as B on ( A.Date = B.Date + 1 )
left JOIN [Table] as C on ( A.Date = C.Date + 3 )
Sometimes I just say it many times in English and the SQL follows. You want it where B equals the maximum date that is less than A.
SELECT A.Date,
A.Value,
A.Value - B.Value as [Daily Change]
FROM MyTable as A
INNER JOIN MyTable as B
ON B.date = (SELECT MAX(C.date) FROM MyTable C WHERE C.Date < A.Date)
ORDER BY A.Date