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The expected result set for Query 1 is: 2489.867388014679 1987.3425863588686 0.0
The expected result set for Query 2 is: 2489.867388014679 0.0
The expected result set for Query 3 is: 0.0
What did you see instead?
The actual result set returned by Query 1 is: 2489.867388014679 1987.3425863588686 NaN
The actual result set returned by Query 2 is: 2489.867388014679 3.1714797501871533E-4
The actual result set returned by Query 3 is: 0.0
Anything else?
Dear IoTDB team, In the three queries above, we perform standard deviation window aggregation on the root.db0.t1.c1 time series.
Query 1 has an aggregation start time of 1641023357064 and an end time of 1641025073925, with each aggregation window size being 2545s and a window sliding distance of 854s.
Query 2 uses the same aggregation time range as Query 1 but doubles the sliding distance of Query 1.
Query 3 changes the start time to 1641025065064 (1641025065064 = 1641023357064 + 854000 + 854000).
By analyzing the actual result sets returned by the three queries, we found discrepancies in the aggregation values of the last window. Additionally, Query 1 triggered a numeric overflow error.
Are you willing to submit a PR?
I'm willing to submit a PR!
The text was updated successfully, but these errors were encountered:
Search before asking
Version
version 1.3.3 (Build: ad95a7e)
Describe the bug and provide the minimal reproduce step
What did you expect to see?
The expected result set for Query 1 is: 2489.867388014679 1987.3425863588686 0.0
The expected result set for Query 2 is: 2489.867388014679 0.0
The expected result set for Query 3 is: 0.0
What did you see instead?
The actual result set returned by Query 1 is: 2489.867388014679 1987.3425863588686 NaN
The actual result set returned by Query 2 is: 2489.867388014679 3.1714797501871533E-4
The actual result set returned by Query 3 is: 0.0
Anything else?
Dear IoTDB team, In the three queries above, we perform standard deviation window aggregation on the
root.db0.t1.c1
time series.1641023357064
and an end time of1641025073925
, with each aggregation window size being2545s
and a window sliding distance of854s
.1641025065064
(1641025065064 = 1641023357064 + 854000 + 854000
).By analyzing the actual result sets returned by the three queries, we found discrepancies in the aggregation values of the last window. Additionally, Query 1 triggered a numeric overflow error.
Are you willing to submit a PR?
The text was updated successfully, but these errors were encountered: