[Bug] There is a calculation logic error in the aggregate window query for overall standard deviation.
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Descrizione
### Search before asking
- [X] I searched in the [issues](https://github.com/apache/iotdb/issues) and found nothing similar.
### Version
version 1.3.3 (Build: ad95a7e)
### Describe the bug and provide the minimal reproduce step
```
DROP DATABASE root.db0
CREATE TIMESERIES root.db0.t1.c0 INT32;
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641024000000, 72), (1641024005000, 112), (1641024010000, 152), (1641024015000, 192), (1641024020000, 232), (1641024025000, 272), (1641024030000, 312), (1641024035000, 352), (1641024040000, 392), (1641024045000, 432), (1641024050000, 472), (1641024055000, 512), (1641024060000, 552), (1641024065000, 592), (1641024070000, 632), (1641024075000, 672), (1641024080000, 712), (1641024085000, 752), (1641024090000, 792), (1641024095000, 832), (1641024100000, 872), (1641024105000, 912), (1641024110000, 952), (1641024115000, 992), (1641024120000, 1032), (1641024125000, 1072), (1641024130000, 1112), (1641024135000, 1152), (1641024140000, null), (1641024145000, 1232);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641024150000, 1272), (1641024155000, 1312), (1641024160000, 1352), (1641024165000, 1392), (1641024170000, 1432), (1641024175000, 1472), (1641024180000, 1512), (1641024185000, 1552), (1641024190000, 1592), (1641024195000, 1632), (1641024200000, 1672), (1641024205000, 1712), (1641024210000, null), (1641024215000, 1792), (1641024220000, 1832), (1641024225000, 1872), (1641024230000, 1912), (1641024235000, 1952), (1641024240000, 1992), (1641024245000, 2032), (1641024250000, 2072), (1641024255000, 2112), (1641024260000, 2152), (1641024265000, 2192), (1641024270000, 2232), (1641024275000, 2272), (1641024280000, 2312), (1641024285000, 2352), (1641024290000, 2392), (1641024295000, 2432);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641024300000, 2472), (1641024305000, 2512), (1641024310000, 2552), (1641024315000, 2592), (1641024320000, 2632), (1641024325000, 2672), (1641024330000, 2712), (1641024335000, 2752), (1641024340000, 2792), (1641024345000, null), (1641024350000, 2872), (1641024355000, 2912), (1641024360000, 2952), (1641024365000, 2992), (1641024370000, 3032), (1641024375000, 3072), (1641024380000, 3112), (1641024385000, 3152), (1641024390000, 3192), (1641024395000, 3232), (1641024400000, 3272), (1641024405000, 3312), (1641024410000, 3352), (1641024415000, 3392), (1641024420000, 3432), (1641024425000, 3472), (1641024430000, 3512), (1641024435000, 3552), (1641024440000, 3592), (1641024445000, 3632);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641024450000, 3672), (1641024455000, null), (1641024460000, 3752), (1641024465000, null), (1641024470000, 3832), (1641024475000, 3872), (1641024480000, 3912), (1641024485000, 3952), (1641024490000, 3992), (1641024495000, 4032), (1641024500000, 4072), (1641024505000, 4112), (1641024510000, 4152), (1641024515000, 4192), (1641024520000, 4232), (1641024525000, 4272), (1641024530000, 4312), (1641024535000, 4352), (1641024540000, 4392), (1641024545000, 4432), (1641024550000, 4472), (1641024555000, 4512), (1641024560000, 4552), (1641024565000, 4592), (1641024570000, 4632), (1641024575000, 4672), (1641024580000, 4712), (1641024585000, 4752), (1641024590000, 4792), (1641024595000, 4832);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641024600000, 4872), (1641024605000, 4912), (1641024610000, 4952), (1641024615000, 4992), (1641024620000, 5032), (1641024625000, 5072), (1641024630000, 5112), (1641024635000, 5152), (1641024640000, 5192), (1641024645000, 5232), (1641024650000, 5272), (1641024655000, 5312), (1641024660000, 5352), (1641024665000, 5392), (1641024670000, 5432), (1641024675000, 5472), (1641024680000, 5512), (1641024685000, 5552), (1641024690000, 5592), (1641024695000, 5632), (1641024700000, 5672), (1641024705000, 5712), (1641024710000, 5752), (1641024715000, 5792), (1641024720000, 5832), (1641024725000, 5872), (1641024730000, 5912), (1641024735000, 5952), (1641024740000, 5992), (1641024745000, 6032);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641024750000, 6072), (1641024755000, 6112), (1641024760000, 6152), (1641024765000, 6192), (1641024770000, 6232), (1641024775000, 6272), (1641024780000, 6312), (1641024785000, 6352), (1641024790000, 6392), (1641024795000, 6432), (1641024800000, 6472), (1641024805000, 6512), (1641024810000, 6552), (1641024815000, 6592), (1641024820000, 6632), (1641024825000, 6672), (1641024830000, 6712), (1641024835000, 6752), (1641024840000, 6792), (1641024845000, 6832), (1641024850000, 6872), (1641024855000, 6912), (1641024860000, 6952), (1641024865000, 6992), (1641024870000, 7032), (1641024875000, 7072), (1641024880000, 7112), (1641024885000, 7152), (1641024890000, 7192), (1641024895000, 7232);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641024900000, 7272), (1641024905000, 7312), (1641024910000, 7352), (1641024915000, 7392), (1641024920000, null), (1641024925000, 7472), (1641024930000, 7512), (1641024935000, 7552), (1641024940000, 7592), (1641024945000, 7632), (1641024950000, 7672), (1641024955000, 7712), (1641024960000, 7752), (1641024965000, 7792), (1641024970000, 7832), (1641024975000, 7872), (1641024980000, 7912), (1641024985000, 7952), (1641024990000, 7992), (1641024995000, 8032), (1641025000000, 8072), (1641025005000, 8112), (1641025010000, 8152), (1641025015000, 8192), (1641025020000, 8232), (1641025025000, 8272), (1641025030000, 8312), (1641025035000, 8352), (1641025040000, 8392), (1641025045000, 8432);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641025050000, 8472), (1641025055000, 8512), (1641025060000, 8552), (1641025065000, 8592), (1641025070000, 8632), (1641025075000, 8672), (1641025080000, 8712), (1641025085000, 8752), (1641025090000, 8792), (1641025095000, 8832), (1641025100000, 8872), (1641025105000, 8912), (1641025110000, 8952), (1641025115000, 8992), (1641025120000, 9032), (1641025125000, 9072), (1641025130000, 9112), (1641025135000, 9152), (1641025140000, null), (1641025145000, 9232), (1641025150000, 9272), (1641025155000, 9312), (1641025160000, 9352), (1641025165000, 9392), (1641025170000, 9432), (1641025175000, 9472), (1641025180000, 9512), (1641025185000, 9552), (1641025190000, 9592), (1641025195000, 9632);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641025200000, 9672), (1641025205000, 9712), (1641025210000, 9752), (1641025215000, 9792), (1641025220000, 9832), (1641025225000, 9872), (1641025230000, 9912), (1641025235000, 9952), (1641025240000, 9992), (1641025245000, 10032), (1641025250000, 10072), (1641025255000, 10112), (1641025260000, 10152), (1641025265000, 10192), (1641025270000, 10232), (1641025275000, 10272), (1641025280000, 10312), (1641025285000, 10352), (1641025290000, 10392), (1641025295000, 10432), (1641025300000, 10472), (1641025305000, 10512), (1641025310000, 10552), (1641025315000, 10592), (1641025320000, 10632), (1641025325000, 10672), (1641025330000, 10712), (1641025335000, 10752), (1641025340000, 10792), (1641025345000, 10832);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641025350000, 10872), (1641025355000, 10912), (1641025360000, 10952), (1641025365000, 10992), (1641025370000, 11032), (1641025375000, 11072), (1641025380000, 11112), (1641025385000, 11152), (1641025390000, 11192), (1641025395000, 11232), (1641025400000, 11272), (1641025405000, 11312), (1641025410000, 11352), (1641025415000, 11392), (1641025420000, 11432), (1641025425000, 11472), (1641025430000, 11512), (1641025435000, 11552), (1641025440000, 11592), (1641025445000, 11632), (1641025450000, 11672), (1641025455000, 11712), (1641025460000, 11752), (1641025465000, 11792), (1641025470000, 11832), (1641025475000, 11872), (1641025480000, 11912), (1641025485000, 11952), (1641025490000, 11992), (1641025495000, 12032);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641025500000, 12072), (1641025505000, 12112), (1641025510000, 12152), (1641025515000, 12192), (1641025520000, 12232), (1641025525000, 12272), (1641025530000, 12312), (1641025535000, 12352), (1641025540000, 12392), (1641025545000, 12432), (1641025550000, 12472), (1641025555000, 12512), (1641025560000, 12552), (1641025565000, 12592), (1641025570000, 12632), (1641025575000, 12672), (1641025580000, 12712), (1641025585000, 12752), (1641025590000, 12792), (1641025595000, 12832), (1641025600000, 12872), (1641025605000, 12912), (1641025610000, 12952), (1641025615000, 12992), (1641025620000, 13032), (1641025625000, 13072), (1641025630000, 13112), (1641025635000, 13152), (1641025640000, 13192), (1641025645000, 13232);
INSERT INTO root.db0.t1(timestamp, c0) VALUES (1641025650000, null), (1641025655000, 13312), (1641025660000, 13352), (1641025665000, 13392), (1641025670000, null), (1641025675000, 13472), (1641025680000, 13512), (1641025685000, 13552), (1641025690000, 13592), (1641025695000, 13632), (1641025700000, 13672), (1641025705000, 13712), (1641025710000, 13752), (1641025715000, 13792), (1641025720000, 13832), (1641025725000, 13872), (1641025730000, 13912), (1641025735000, 13952);
# query 1
SELECT STDDEV_POP(c0) FROM root.db0.t1 GROUP BY ([1641023357064, 1641025073925),2545s,854s)
# query 2
SELECT STDDEV_POP(c0) FROM root.db0.t1 GROUP BY ([1641023357064, 1641025073925),2545s,1708s)
# query 3
SELECT STDDEV_POP(c0) FROM root.db0.t1 GROUP BY([1641025065064, 1641025073925),2545s)
```
### 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.
- 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!
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Direzione di ricerca
Inizia riproducendo le tre query di finestra STDDEV_POP dell’issue su IoTDB 1.3.3 e confronta i risultati della finestra finale con le aspettative indicate. Segui il percorso della deviazione standard della finestra di aggregazione e verifica che le finestre con un singolo valore restituiscano 0.0 senza overflow numerico o NaN; il lavoro è completato quando tutte e tre le query producono i risultati attesi.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Valutazione
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- data, databases
- Tipo di issue
- Bug
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