Stream Analytics Aggregation Window - azure-eventhub

Question

I need help \ advice on how to ignore old events when performing aggregation over an extended window. I have sale data that is streaming into Event Hub.
Event hub is used as as Input stream. I need to produce two metrices
- 30 sec aggregation ( tumbling )
- Whole day aggregated sales value i.e. from Gate open
Gate open time is variable (dynamic) hence I read reference dataset off the blob; and join the Gateopen datetime to sales stream.
The 30 sec aggregation over the tumbling window works fine.
Given the gate open is variable; I am currently using 12 hour Hopping window with 30 sec hop and trying to limit the event to be aggregated by using EventProcessDatetime > GateOpen logic.
SELECT
Dateadd(ss,-30,System.Timestamp ) AS TimeSliceUTCStart
, System.Timestamp AS TimeSliceUTCEnd
, p.Section AS Section
, SUM(CASE WHEN p.Classification = 'Retail'
AND p.ActivityDateTime > p.GateOpen THEN p.[sales_amt_gross] ELSE 0 END) AS SaleTotalRetail
FROM FilteredBase p
GROUP BY
p.Section
, HoppingWindow(Duration(Hour, 12), hop(second, 30),Offset(millisecond, -1))
Problem: I am getting sales aggregated from the previous day\timeslice.
Overall the outcome I am trying to achieve is simple. The store could be open for 5,8,10 or 12 hour max. We want to be able to know sales as in Live stream, for each section as the day progresses. Any advise or tip will be much appreciated.

Answer 1

Intuitively the query looks good, but what happens under the cover is that Azure Stream Analytics is using the reference data file that was valid at the time of each time window. Then, when it sees the even of the previous day, it will use the reference data present at that time (which may make the comparison p.ActivityDateTime > p.GateOpen True for the previous opening time).
I modified the query as followed (supposing you have 1 open event per day per section). Let me know if it works for you. If it doesn't, can you send some sample data so I can modify the query accordingly. We will investigate to see how to make these queries easier to write.
WITH thirdtysecReporting AS
(
SELECT
p.Section Section,
DATETIMEFROMPARTS(DATEPART(year, System.Timestamp), DATEPART(month, System.Timestamp), DATEPART(day, System.Timestamp), 0, 0, 0, 0) as date,
System.Timestamp Windowend,
SUM(p.sales_amt_gross) thirtysecSales
FROM input TIMESTAMP BY p.ActivityDateTime
GROUP BY TumblingWindow(second, 30), p.Section
)
,hopping AS
(
SELECT
Section,
System.Timestamp HopEnd,
date,
SUM(thirtysecSales) SumSales
FROM thirdtysecReporting
GROUP BY HoppingWindow(second, 86400, 30), Section, date -- Hopping on 24 hours, reported every 30 second
)
,filtered as -- This step ignores data from the previous day
(
SELECT
Section,
HopEnd,
date,
SUMQt = CASE
WHEN DAY(HopEnd) = DAY(date) OR DATEPART(hour, HopEnd) = DATEPART(hour, date) THEN SumSales
ELSE 0
END
FROM hopping
)
SELECT Section, -- Final query
HopEnd,
MAX(SUMQt) AS SumQt
FROM filtered
GROUP BY TumblingWindow(hour, 1), Section, hopend
Thanks,
JS - Azure Stream Analytics