使用多个聚合函数查找每组的最后一条记录-SQLite
我有一个表（"trds"），其中包含字段RefDate, Symbol, Timestamp, Sequence, Quantity, Price, SaleCondition, Pid,和Submkt（"select * from trds limit 100"）：
RefDate Symbol Timestamp Sequence Quantity Price SaleCondition Pid SubMkt
1 2015-08-03 AAPL 14400002 507 10 121.50 @ TI P
2 2015-08-03 AAPL 14400026 1017 100 121.39 T P
3 2015-08-03 AAPL 14400026 1018 520 121.39 T P
4 2015-08-03 AAPL 14400026 1019 100 121.40 T P
5 2015-08-03 AAPL 14400028 1020 100 121.49 T P
6 2015-08-03 AAPL 14400028 1021 2172 121.49 T P
7 2015-08-03 AAPL 14425890 1026 100 121.49 T P
8 2015-08-03 AAPL 14426989 1027 100 121.49 T P
9 2015-08-03 AAPL 14433658 1028 137 121.40 @FT P
10 2015-08-03 AAPL 14628998 1029 200 121.40 T P
11 2015-08-03 AAPL 14637576 1030 5328 121.40 @ T P
12 2015-08-03 AAPL 14637576 1031 200 121.45 @FT Q
13 2015-08-03 AAPL 15116858 1032 3040 121.40 T P
14 2015-08-03 AAPL 15129926 1034 1295 121.40 T P
15 2015-08-03 AAPL 15130128 1035 201 121.30 T P
16 2015-08-03 AAPL 15237959 1036 126 121.30 T P
17 2015-08-03 AAPL 15553155 1043 20 121.03 @ TI P
18 2015-08-03 AAPL 15646925 1044 80 121.03 @ TI P
19 2015-08-03 AAPL 15844129 1050 40 121.22 @FTI Q
20 2015-08-03 AAPL 16908849 1055 190 121.22 @FT Q
21 2015-08-03 AAPL 16998884 1056 260 121.22 @FT Q
22 2015-08-03 AAPL 17682717 1057 10 121.22 @FTI Q
23 2015-08-03 AAPL 17682717 1058 190 121.23 @FT Q
24 2015-08-03 AAPL 17736566 1059 100 121.23 @FT Q
25 2015-08-03 AAPL 18102786 1061 100 121.22 @FT Q
26 2015-08-03 AAPL 18102786 1062 100 121.22 @FT Q
27 2015-08-03 AAPL 18103386 1063 700 121.23 @FT Q
28 2015-08-03 AAPL 19170799 1064 200 121.22 @FT P
29 2015-08-03 AAPL 19171001 1065 40 121.22 @FTI P
30 2015-08-03 AAPL 19557088 1068 500 121.21 T P
31 2015-08-03 AAPL 19995780 1072 50 121.00 @FTI P
32 2015-08-03 AAPL 19995780 1073 450 121.00 @FT P
33 2015-08-03 AAPL 20110219 1074 100 121.00 @FT P
34 2015-08-03 AAPL 20131347 1075 100 121.00 @FT P
35 2015-08-03 AAPL 20288087 1076 50 121.01 @FTI P
36 2015-08-03 AAPL 20288282 1077 250 121.00 @FT P
37 2015-08-03 AAPL 20776851 1081 200 121.22 T P
38 2015-08-03 AAPL 20777052 1082 300 121.22 T P
39 2015-08-03 AAPL 21416707 1084 200 121.22 T P
40 2015-08-03 AAPL 21416907 1085 300 121.22 T P
41 2015-08-03 AAPL 21740935 1086 200 121.22 @FT P
42 2015-08-03 AAPL 21741136 1087 33 121.22 @FTI P
43 2015-08-03 AAPL 22289290 1088 50 121.22 @ TI P
44 2015-08-03 AAPL 22302889 1089 150 121.22 T P
45 2015-08-03 AAPL 22303093 1090 350 121.22 T P
46 2015-08-03 AAPL 22324450 1091 100 121.22 T P
47 2015-08-03 AAPL 22325298 1092 100 121.22 T P
48 2015-08-03 AAPL 22489509 1093 200 121.22 T P
49 2015-08-03 AAPL 22489711 1094 300 121.22 T P
50 2015-08-03 AAPL 22651416 1096 200 121.22 @FT P
51 2015-08-03 AAPL 22656656 1097 77 121.22 @ TI P
52 2015-08-03 AAPL 22656857 1098 10 121.23 @ TI P
53 2015-08-03 AAPL 22762084 1099 87 121.37 @FTI Q
54 2015-08-03 AAPL 22762084 1100 413 121.38 @FT Q
55 2015-08-03 AAPL 22956526 1103 20 121.20 @ TI P
56 2015-08-03 AAPL 22956727 1104 180 121.18 T P
57 2015-08-03 AAPL 23254802 1105 36 121.27 @ TI P
58 2015-08-03 AAPL 24077374 1110 144 121.27 T P
59 2015-08-03 AAPL 24077374 1111 50 121.29 @ TI P
60 2015-08-03 AAPL 24077374 1112 306 121.30 T P
61 2015-08-03 AAPL 24121832 1113 2 121.30 @ TI P
62 2015-08-03 AAPL 24164641 1116 1000 121.30 T P
63 2015-08-03 AAPL 24168414 1117 600 121.30 T P
64 2015-08-03 AAPL 24192881 1120 92 121.30 @ TI P
65 2015-08-03 AAPL 24192882 1121 408 121.38 @FT Q
66 2015-08-03 AAPL 24331392 1122 400 121.45 @ T P
67 2015-08-03 AAPL 24331392 1123 100 121.38 @FT Q
68 2015-08-03 AAPL 24336664 1124 79 121.38 @ TI P
69 2015-08-03 AAPL 24464675 1125 1000 121.40 T P
70 2015-08-03 AAPL 24587817 1126 496 121.38 T P
71 2015-08-03 AAPL 24588021 1127 504 121.39 T P
72 2015-08-03 AAPL 24600057 1128 500 121.38 T P
73 2015-08-03 AAPL 24667891 1130 500 121.37 T P
74 2015-08-03 AAPL 24723357 1131 50 121.39 @ TI P
75 2015-08-03 AAPL 24778654 1132 1000 121.39 T P
76 2015-08-03 AAPL 24908008 1133 200 121.39 T P
77 2015-08-03 AAPL 24908210 1134 300 121.40 T P
78 2015-08-03 AAPL 24912914 1135 1500 121.40 T P
79 2015-08-03 AAPL 25011487 1136 500 121.40 T P
80 2015-08-03 AAPL 25018982 1137 100 121.40 T P
81 2015-08-03 AAPL 25023375 1138 21 121.40 @ TI P
82 2015-08-03 AAPL 25064872 1139 600 121.40 T P
83 2015-08-03 AAPL 25111247 1140 500 121.40 T P
84 2015-08-03 AAPL 25112575 1141 200 121.40 T P
85 2015-08-03 AAPL 25139881 1142 200 121.40 T P
86 2015-08-03 AAPL 25140659 1143 79 121.40 @ TI P
87 2015-08-03 AAPL 25140869 1144 421 121.45 T P
88 2015-08-03 AAPL 25219916 1146 200 121.45 T P
89 2015-08-03 AAPL 25229789 1147 50 121.36 @FTI P
90 2015-08-03 AAPL 25229988 1148 29 121.35 @FTI P
91 2015-08-03 AAPL 25290394 1160 200 121.43 T P
92 2015-08-03 AAPL 25392283 1168 30 121.40 @ TI P
93 2015-08-03 AAPL 25421012 1169 300 121.40 T P
94 2015-08-03 AAPL 25755052 1173 2 121.45 @ TI P
95 2015-08-03 AAPL 25763189 1174 60 121.44 @ TI P
96 2015-08-03 AAPL 25942067 1182 200 121.46 @FT P
97 2015-08-03 AAPL 25942068 1183 100 121.47 @FT P
98 2015-08-03 AAPL 25942068 1184 100 121.47 @FT P
99 2015-08-03 AAPL 25942070 1185 100 121.47 @FT P
100 2015-08-03 AAPL 25948942 1186 1000 121.48 T
我需要创建一个查询，以每隔五分钟将所有交易分组在一起，并找到每组的最低/最高/平均价格和最后价格。 "Timestamp"是午夜以来的毫秒数（所以9:30是34200000），我只想在9:30到4:00之间添加。我用五分钟的间隔（300,000毫秒）除以timebucket来创建cast(timestamp/300e3) as int) as timebucket。
最终结果应如下所示：
我可以生成代码以获取最低/最高/平均价格，如下所示：
dbGetQuery(nqdb, statement = "select t.RefDate, t.Symbol, cast(t.Timestamp/300e3 as int) as timeBucket,
Min(time(t.timestamp/1000, 'unixepoch')) as startTime, Max(t.Price) as MaxPrice,
Min(t.Price) as MinPrice, Avg(t.Price) as AvgPrice
from trds t
where (t.Timestamp between 34200000 and 57600000) and
SaleCondition not glob '*[CGIHMNPQRTUVWZ47]*' group by timeBucket, symbol order by symbol ASC")
这有点接近，尽管StartTime在HH：MM：SS字段中有不应该的秒数，并且我已经尝试了从子查询到子选择的所有内容，并通过“ greatest- n-per-group”论坛以获取“ LastPrice”无效。输出如下：
RefDate Symbol timeBucket startTime MaxPrice MinPrice AvgPrice
1 2015-08-03 AAPL 114 09:30:00 121.5000 121.0500 121.22574
2 2015-08-03 AAPL 115 09:35:00 122.4700 121.2200 121.86515
3 2015-08-03 AAPL 116 09:40:00 122.5700 122.1000 122.37850
4 2015-08-03 AAPL 117 09:45:00 122.2000 121.8901 122.00520
5 2015-08-03 AAPL 118 09:50:00 122.2900 122.0000 122.10803
6 2015-08-03 AAPL 119 09:55:00 122.2100 121.7000 122.02053
7 2015-08-03 AAPL 120 10:00:00 121.8900 121.4100 121.73007
8 2015-08-03 AAPL 121 10:05:00 121.5500 121.2500 121.38513
9 2015-08-03 AAPL 122 10:10:00 121.6200 121.2550 121.48453
10 2015-08-03 AAPL 123 10:15:00 121.5200 121.2700 121.38975
11 2015-08-03 AAPL 124 10:20:00 121.3400 121.1500 121.25174
12 2015-08-03 AAPL 125 10:25:00 121.1600 120.7750 120.92567
13 2015-08-03 AAPL 126 10:30:00 121.0400 120.8100 120.90262
14 2015-08-03 AAPL 127 10:35:01 121.0000 120.7800 120.88182
15 2015-08-03 AAPL 128 10:40:00 121.0000 120.8600 120.91147
16 2015-08-03 AAPL 129 10:45:00 120.9083 120.7330 120.81935
17 2015-08-03 AAPL 130 10:50:00 120.8400 120.5500 120.71769
18 2015-08-03 AAPL 131 10:55:00 120.7200 120.5300 120.62324
19 2015-08-03 AAPL 132 11:00:00 120.8200 120.6500 120.71650
20 2015-08-03 AAPL 133 11:05:00 120.9900 120.6500 120.83935
21 2015-08-03 AAPL 134 11:10:00 121.1800 120.9100 121.02811
22 2015-08-03 AAPL 135 11:15:00 121.1700 120.9700 121.05849
23 2015-08-03 AAPL 136 11:20:01 121.1500 121.0480 121.09072
24 2015-08-03 AAPL 137 11:25:00 121.1500 120.9500 121.04811
25 2015-08-03 AAPL 138 11:30:00 121.1200 120.9200 121.02047
26 2015-08-03 AAPL 139 11:35:00 120.9900 120.6700 120.82496
27 2015-08-03 AAPL 140 11:40:00 120.8400 120.5600 120.68603
28 2015-08-03 AAPL 141 11:45:00 120.8600 120.6600 120.75718
29 2015-08-03 AAPL 142 11:50:00 120.6800 120.3300 120.46856
30 2015-08-03 AAPL 143 11:55:00 120.5155 120.4100 120.45356
31 2015-08-03 AAPL 144 12:00:00 120.5500 120.2200 120.32099
32 2015-08-03 AAPL 145 12:05:00 120.3000 120.1100 120.20832
33 2015-08-03 AAPL 146 12:10:00 120.1734 119.9000 120.02722
34 2015-08-03 AAPL 147 12:15:00 120.0600 119.8700 119.96583
35 2015-08-03 AAPL 148 12:20:00 119.9900 119.8100 119.89728
36 2015-08-03 AAPL 149 12:25:01 120.2200 119.8900 120.03213
37 2015-08-03 AAPL 150 12:30:00 120.1800 119.9200 120.03840
38 2015-08-03 AAPL 151 12:35:00 119.9756 119.7700 119.87204
39 2015-08-03 AAPL 152 12:40:00 119.9000 119.7500 119.82387
40 2015-08-03 AAPL 153 12:45:00 119.8353 118.7000 119.16163
41 2015-08-03 AAPL 154 12:50:00 118.9890 118.2600 118.66432
42 2015-08-03 AAPL 155 12:55:00 118.5000 117.5200 117.95536
43 2015-08-03 AAPL 156 13:00:00 118.4367 117.9500 118.15729
44 2015-08-03 AAPL 157 13:05:00 118.4500 117.7101 118.08337
45 2015-08-03 AAPL 158 13:10:00 118.1200 117.6700 117.87640
46 2015-08-03 AAPL 159 13:15:00 118.0100 117.6601 117.82184
47 2015-08-03 AAPL 160 13:20:00 118.1700 117.6100 117.98232
48 2015-08-03 AAPL 161 13:25:00 118.4400 118.0200 118.27480
49 2015-08-03 AAPL 162 13:30:00 118.4500 118.2000 118.33434
50 2015-08-03 AAPL 163 13:35:00 118.5500 118.3000 118.45115
51 2015-08-03 AAPL 164 13:40:00 118.6400 118.3200 118.50168
52 2015-08-03 AAPL 165 13:45:00 118.6800 118.4400 118.54192
53 2015-08-03 AAPL 166 13:50:00 118.8300 118.6000 118.74204
54 2015-08-03 AAPL 167 13:55:00 118.8400 118.6500 118.73936
55 2015-08-03 AAPL 168 14:00:00 118.7300 118.5200 118.60532
56 2015-08-03 AAPL 169 14:05:00 118.6500 118.4300 118.50543
57 2015-08-03 AAPL 170 14:10:00 118.5800 118.4300 118.49353
58 2015-08-03 AAPL 171 14:15:01 118.7100 118.4600 118.58022
59 2015-08-03 AAPL 172 14:20:00 118.5600 118.4000 118.48883
60 2015-08-03 AAPL 173 14:25:00 118.6500 118.3300 118.49131
61 2015-08-03 AAPL 174 14:30:00 118.6675 118.4900 118.56914
62 2015-08-03 AAPL 175 14:35:00 118.6500 118.4700 118.55887
63 2015-08-03 AAPL 176 14:40:00 118.8100 118.5600 118.69735
64 2015-08-03 AAPL 177 14:45:00 118.8000 118.6200 118.72279
65 2015-08-03 AAPL 178 14:50:00 118.7800 118.6200 118.71055
66 2015-08-03 AAPL 179 14:55:00 118.7500 118.5700 118.65656
67 2015-08-03 AAPL 180 15:00:00 118.8700 118.6500 118.72095
68 2015-08-03 AAPL 181 15:05:00 118.8700 118.6900 118.78130
69 2015-08-03 AAPL 182 15:10:00 118.7200 118.4600 118.61231
70 2015-08-03 AAPL 183 15:15:01 118.6000 118.3000 118.42988
71 2015-08-03 AAPL 184 15:20:03 118.4000 118.0700 118.23301
72 2015-08-03 AAPL 185 15:25:00 118.1000 117.8600 117.99564
73 2015-08-03 AAPL 186 15:30:00 118.1900 117.9600 118.08736
74 2015-08-03 AAPL 187 15:35:00 118.1700 117.8800 117.99449
75 2015-08-03 AAPL 188 15:40:00 118.2700 118.1000 118.16962
76 2015-08-03 AAPL 189 15:45:00 118.2000 117.9600 118.08088
77 2015-08-03 AAPL 190 15:50:00 118.1700 118.0000 118.07813
78 2015-08-03 AAPL 191 15:55:00 118.4500 118.0300 118.23987
79 2015-08-03 AMZN 114 09:30:00 538.5500 536.3200 537.61255
80 2015-08-03 AMZN 115 09:35:04 537.4600 535.7700 536.42177
81 2015-08-03 AMZN 116 09:40:01 538.3500 536.4000 537.68861
82 2015-08-03 AMZN 117 09:45:00 539.3500 536.2800 537.56732
83 2015-08-03 AMZN 118 09:50:00 539.9500 538.7100 539.45455
84 2015-08-03 AMZN 119 09:55:03 540.4400 538.8100 539.66087
85 2015-08-03 AMZN 120 10:00:00 540.2600 537.7100 539.01779
86 2015-08-03 AMZN 121 10:05:00 538.4050 536.5500 537.48823
87 2015-08-03 AMZN 122 10:10:03 537.6800 536.8000 537.21956
88 2015-08-03 AMZN 123 10:15:00 536.8000 534.1500 535.24578
89 2015-08-03 AMZN 124 10:20:01 535.0500 533.7700 534.51831
90 2015-08-03 AMZN 125 10:25:04 535.3900 534.1200 534.74367
91 2015-08-03 AMZN 126 10:30:13 534.9700 534.0110 534.64140
92 2015-08-03 AMZN 127 10:35:04 535.3500 534.5001 534.92485
93 2015-08-03 AMZN 128 10:40:04 535.1600 534.1000 534.57402
94 2015-08-03 AMZN 129 10:45:02 536.0000 534.5100 535.26481
95 2015-08-03 AMZN 130 10:50:00 536.3500 535.4500 535.93280
96 2015-08-03 AMZN 131 10:55:02 536.6500 535.2600 535.96416
97 2015-08-03 AMZN 132 11:00:01 536.6000 535.6800 536.24564
98 2015-08-03 AMZN 133 11:05:10 537.8900 536.4800 537.23168
99 2015-08-03 AMZN 134 11:10:00 538.5200 537.3500 537.94708
100 2015-08-03 AMZN 135 11:15:02 537.9400 537.3500 537.58755
101 2015-08-03 AMZN 136 11:20:05 537.9050 536.8600 537.31598
我猜想有比我以前使用的Min（time）工作更优雅的解决方案。但是主要的问题是如何每隔五分钟查找一次LastPrice？
更新-这是我做的一个单独的查询，它生成每五分钟一组的最后价格，但没有Min（{Price），Max（Price）和Avg（Price ）。我不知道如何在一个查询中组合所有这些内容。
dbGetQuery(nqdb, statement = "select t.RefDate, t.Symbol, cast(t.Timestamp/300e3 as int) as timeBucket,
time(t.timestamp/1000, 'unixepoch') as startTime,
t.price as LastPrice from trds t
where (t.Timestamp between 34200000 and 57600000) and
SaleCondition not glob '*[CGIHMNPQRTUVWZ47]*' group by timeBucket, symbol order by symbol ASC")
RefDate Symbol timeBucket startTime LastPrice
1 2015-08-03 AAPL 114 09:34:00 121.2300
2 2015-08-03 AAPL 115 09:39:00 122.4400
3 2015-08-03 AAPL 116 09:44:00 122.1800
4 2015-08-03 AAPL 117 09:49:00 122.0500
5 2015-08-03 AAPL 118 09:54:00 122.0700
6 2015-08-03 AAPL 119 09:59:00 121.7700
7 2015-08-03 AAPL 120 10:04:00 121.5400
8 2015-08-03 AAPL 121 10:09:00 121.2600
9 2015-08-03 AAPL 122 10:14:00 121.5140
10 2015-08-03 AAPL 123 10:19:00 121.2700
11 2015-08-03 AAPL 124 10:24:00 121.1600
12 2015-08-03 AAPL 125 10:29:00 121.0200
13 2015-08-03 AAPL 126 10:34:00 120.9200
14 2015-08-03 AAPL 127 10:39:00 120.9900
15 2015-08-03 AAPL 128 10:44:00 120.8600
16 2015-08-03 AAPL 129 10:49:00 120.7800
17 2015-08-03 AAPL 130 10:54:00 120.6200
18 2015-08-03 AAPL 131 10:59:00 120.6500
19 2015-08-03 AAPL 132 11:04:00 120.6900
20 2015-08-03 AAPL 133 11:09:00 120.9600
21 2015-08-03 AAPL 134 11:14:00 121.0237
22 2015-08-03 AAPL 135 11:19:00 121.0899
23 2015-08-03 AAPL 136 11:24:00 121.1010
24 2015-08-03 AAPL 137 11:29:00 120.9954
25 2015-08-03 AAPL 138 11:34:00 120.9895
26 2015-08-03 AAPL 139 11:39:00 120.6750
27 2015-08-03 AAPL 140 11:44:00 120.8200
28 2015-08-03 AAPL 141 11:49:00 120.6750
29 2015-08-03 AAPL 142 11:54:00 120.4500
30 2015-08-03 AAPL 143 11:59:00 120.4900
31 2015-08-03 AAPL 144 12:04:00 120.2449
32 2015-08-03 AAPL 145 12:09:00 120.1600
33 2015-08-03 AAPL 146 12:14:00 120.0200
34 2015-08-03 AAPL 147 12:19:00 119.8700
35 2015-08-03 AAPL 148 12:24:00 119.9400
36 2015-08-03 AAPL 149 12:29:00 120.1770
37 2015-08-03 AAPL 150 12:34:00 119.9505
38 2015-08-03 AAPL 151 12:39:00 119.8400
39 2015-08-03 AAPL 152 12:44:00 119.8400
40 2015-08-03 AAPL 153 12:49:00 118.9400
41 2015-08-03 AAPL 154 12:54:00 118.4900
42 2015-08-03 AAPL 155 12:59:00 118.0000
43 2015-08-03 AAPL 156 13:04:00 118.4300
44 2015-08-03 AAPL 157 13:09:00 117.7286
45 2015-08-03 AAPL 158 13:14:00 117.9173
46 2015-08-03 AAPL 159 13:19:00 117.6700
47 2015-08-03 AAPL 160 13:24:00 118.1200
48 2015-08-03 AAPL 161 13:29:00 118.3601
49 2015-08-03 AAPL 162 13:34:00 118.4400
50 2015-08-03 AAPL 163 13:39:00 118.3000
更新：在时间戳问题上，每个@Parfait都可以正常运行，但是其中一个输出关闭了一个Symbol。同样仍然无法解决找到每五分钟组的最后价格以及最低/最高/平均水平的问题：
157 2015-08-03 DAVE 114 09:30:00 17.9600 17.9300 17.94500
158 2015-08-03 DAVE 115 09:37:00 17.9994 17.9100 17.95470
159 2015-08-03 DAVE 116 09:40:00 17.8700 17.8700 17.87000
160 2015-08-03 DAVE 118 09:50:00 17.7350 17.6950 17.71500
161 2015-08-03 DAVE 120 10:04:00 17.6900 17.6700 17.68000
162 2015-08-03 DAVE 121 10:08:00 17.5600 17.5600 17.56000
163 2015-08-03 DAVE 122 10:14:00 17.5600 17.5600 17.56000
164 2015-08-03 DAVE 124 10:24:00 17.6500 17.6500 17.65000
165 2015-08-03 DAVE 126 10:30:00 17.6000 17.5200 17.56000
166 2015-08-03 DAVE 127 10:39:00 17.4800 17.4800 17.48000
167 2015-08-03 DAVE 128 10:40:00 17.6100 17.4900 17.55000
168 2015-08-03 DAVE 129 10:47:00 17.4400 17.4400 17.44000
169 2015-08-03 DAVE 130 10:54:00 17.5600 17.5600 17.56000
170 2015-08-03 DAVE 131 10:55:00 17.4300 17.3800 17.40500
171 2015-08-03 DAVE 132 11:00:00 17.3400 17.2620 17.30720
172 2015-08-03 DAVE 133 11:09:00 17.2800 17.2700 17.27500
173 2015-08-03 DAVE 135 11:17:00 17.2700 17.2300 17.25000
174 2015-08-03 DAVE 136 11:23:00 17.3200 17.3000 17.31000
175 2015-08-03 DAVE 137 11:25:00 17.4000 17.3750 17.38875
176 2015-08-03 DAVE 139 11:39:00 17.4400 17.4400 17.44000
177 2015-08-03 DAVE 141 11:49:00 17.4200 17.4200 17.42000
178 2015-08-03 DAVE 142 11:51:00 17.4200 17.4200 17.42000
179 2015-08-03 DAVE 143 11:59:00 17.3900 17.3900 17.39000
180 2015-08-03 DAVE 144 12:01:00 17.4350 17.3600 17.39750
181 2015-08-03 DAVE 146 12:13:00 17.3700 17.3600 17.36500
182 2015-08-03 DAVE 147 12:17:00 17.3600 17.3500 17.35333
183 2015-08-03 DAVE 148 12:20:00 17.4000 17.3700 17.38500
184 2015-08-03 DAVE 149 12:25:00 17.3700 17.3700 17.37000
185 2015-08-03 DAVE 150 12:31:00 17.3300 17.3300 17.33000
186 2015-08-03 DAVE 153 12:49:00 17.3800 17.3800 17.38000
187 2015-08-03 DAVE 154 12:50:00 17.3900 17.3900 17.39000
188 2015-08-03 DAVE 155 12:55:00 17.3300 17.3300 17.33000
189 2015-08-03 DAVE 158 13:12:00 17.3400 17.3100 17.32500
190 2015-08-03 DAVE 159 13:15:00 17.3600 17.3400 17.35000
191 2015-08-03 DAVE 160 13:22:00 17.3700 17.3700 17.37000
192 2015-08-03 DAVE 162 13:34:00 17.3504 17.3504 17.35040
193 2015-08-03 DAVE 163 13:35:00 17.3300 17.3100 17.32000
194 2015-08-03 DAVE 165 13:49:00 17.3200 17.3200 17.32000
195 2015-08-03 DAVE 171 14:15:00 17.3500 17.2700 17.31563
196 2015-08-03 DAVE 172 14:20:00 17.4000 17.3500 17.36667
197 2015-08-03 DAVE 175 14:37:00 17.3900 17.3900 17.39000
198 2015-08-03 DAVE 176 14:40:00 17.4000 17.3500 17.37125
199 2015-08-03 DAVE 177 14:45:00 17.4100 17.3500 17.38300
200 2015-08-03 DAVE 178 14:51:00 17.4500 17.4500 17.45000
201 2015-08-03 DAVE 181 15:05:00 17.5800 17.5300 17.55700
202 2015-08-03 DAVE 182 15:10:00 17.5600 17.5200 17.54223
203 2015-08-03 DAVE 184 15:23:00 17.6900 17.6200 17.65500
204 2015-08-03 DAVE 186 15:30:00 17.6900 17.6900 17.69000
205 2015-08-03 DAVE 189 15:46:00 17.7500 17.7200 17.74000
以下是问题Symbol“ DAVE”的时间，以秒为单位：
RefDate Symbol timeBucket startTime MaxPrice MinPrice AvgPrice
1 2015-08-03 DAVE 114 34200708 17.9600 17.9300 17.94500
2 2015-08-03 DAVE 115 34628936 17.9994 17.9100 17.95470
3 2015-08-03 DAVE 116 34807939 17.8700 17.8700 17.87000
4 2015-08-03 DAVE 118 35415342 17.7350 17.6950 17.71500
5 2015-08-03 DAVE 120 36250083 17.6900 17.6700 17.68000
6 2015-08-03 DAVE 121 36528404 17.5600 17.5600 17.56000
7 2015-08-03 DAVE 122 36850085 17.5600 17.5600 17.56000
8 2015-08-03 DAVE 124 37450198 17.6500 17.6500 17.65000
9 2015-08-03 DAVE 126 37892189 17.6000 17.5200 17.56000
10 2015-08-03 DAVE 127 38389126 17.4800 17.4800 17.48000
11 2015-08-03 DAVE 128 38400053 17.6100 17.4900 17.55000
12 2015-08-03 DAVE 129 38861146 17.4400 17.4400 17.44000
13 2015-08-03 DAVE 130 39250319 17.5600 17.5600 17.56000
14 2015-08-03 DAVE 131 39301007 17.4300 17.3800 17.40500
15 2015-08-03 DAVE 132 39704588 17.3400 17.2620 17.30720
16 2015-08-03 DAVE 133 40150085 17.2800 17.2700 17.27500
17 2015-08-03 DAVE 135 40668185 17.2700 17.2300 17.25000
18 2015-08-03 DAVE 136 41026622 17.3200 17.3000 17.31000
19 2015-08-03 DAVE 137 41125827 17.4000 17.3750 17.38875
20 2015-08-03 DAVE 139 41950078 17.4400 17.4400 17.44000
21 2015-08-03 DAVE 141 42550193 17.4200 17.4200 17.42000
22 2015-08-03 DAVE 142 42704053 17.4200 17.4200 17.42000
23 2015-08-03 DAVE 143 43150086 17.3900 17.3900 17.39000
24 2015-08-03 DAVE 144 43439310 17.4350 17.3600 17.39750
25 2015-08-03 DAVE 146 44086864 17.3700 17.3600 17.36500
26 2015-08-03 DAVE 147 44250485 17.3600 17.3500 17.35333
27 2015-08-03 DAVE 148 44416744 17.4000 17.3700 17.38500
28 2015-08-03 DAVE 149 44748677 17.3700 17.3700 17.37000
29 2015-08-03 DAVE 150 45087379 17.3300 17.3300 17.33000
30 2015-08-03 DAVE 153 46149940 17.3800 17.3800 17.38000
31 2015-08-03 DAVE 154 46236704 17.3900 17.3900 17.39000
32 2015-08-03 DAVE 155 46513141 17.3300 17.3300 17.33000
33 2015-08-03 DAVE 158 47589401 17.3400 17.3100 17.32500
34 2015-08-03 DAVE 159 47706529 17.3600 17.3400 17.35000
35 2015-08-03 DAVE 160 48134567 17.3700 17.3700 17.37000
36 2015-08-03 DAVE 162 48856648 17.3504 17.3504 17.35040
37 2015-08-03 DAVE 163 48943090 17.3300 17.3100 17.32000
38 2015-08-03 DAVE 165 49755204 17.3200 17.3200 17.32000
39 2015-08-03 DAVE 171 51379248 17.3500 17.2700 17.31563
40 2015-08-03 DAVE 172 51622647 17.4000 17.3500 17.36667
41 2015-08-03 DAVE 175 52636324 17.3900 17.3900 17.39000
42 2015-08-03 DAVE 176 52921459 17.4000 17.3500 17.37125
43 2015-08-03 DAVE 177 53132520 17.4100 17.3500 17.38300
44 2015-08-03 DAVE 178 53516691 17.4500 17.4500 17.45000
45 2015-08-03 DAVE 181 54350810 17.5800 17.5300 17.55700
46 2015-08-03 DAVE 182 54749749 17.5600 17.5200 17.54223
47 2015-08-03 DAVE 184 55476188 17.6900 17.6200 17.65500
48 2015-08-03 DAVE 186 55804762 17.6900 17.6900 17.69000
49 2015-08-03 DAVE 189 56789594 17.7500 17.7200 17.74000
50 2015-08-03 DAVE 190 57274050 17.7800 17.6600 17.73333
51 2015-08-03 DAVE 191 57557752 17.7000 17.6300 17.66265
1 个答案:
答案 0 :(得分：1)
请考虑使用模运算符%，将其余数减去最近的分钟（即60秒）：
Min(time(t.timestamp/1000 - (t.timestamp/1000) % 60, 'unixepoch')) as startTime
此外，要查找第一个或最后一个价格，请使用时间戳运行多个聚合，然后将聚合加入主查询。下面使用CTE，它应该在最新的SQLite版本中可用。将整个查询包装在R字符串中，它应该返回最后一个SELECT结果集作为数据帧。
以下使用新的 five_min_grp 并运行聚合查询的自连接，但与主体级查询在不同的时间戳上连接。
with unit as
(select t.RefDate, t.Symbol, cast(t.Timestamp/300e3 as int) as timeBucket,
time(t.timestamp/1000 - (t.timestamp/1000) % 300, 'unixepoch') as five_min_grp,
time(t.timestamp/1000 - (t.timestamp/1000) % 60, 'unixepoch') as startTime,
t.price as Price
from trds t
where (t.Timestamp between 34200000 and 57600000)
and (t.SaleCondition not glob '*[CGIHMNPQRTUVWZ47]*')
),
agg as
(select u.RefDate, u.Symbol, u.five_min_grp,
min(u.startTime) as first_startTime,
max(u.startTime) as last_startTime
from unit u
group by u.RefDate, u.Symbol, u.five_min_grp
),
select u.RefDate, u.Symbol, u.five_min_grp,
avg(u.price) as AvgPrice,
min(u.price) as MinPrice,
max(u.price) as MaxPrice,
min(case when first.first_startTime is not null
then u.price
else null
end) as FirstPrice,
max(case when last.last_startTime is not null
then u.price
else null
end) as LastPrice
from unit u
left join agg first
on first.RefDate = u.RefDate
and first.Symbol = u.Symbol
and first.five_min_grp = u.five_min_grp
and first.first_startTime = u.startTime
left join agg last
on last.RefDate = u.RefDate
and last.Symbol = u.Symbol
and last.five_min_grp = u.five_min_grp
and last.last_startTime = u.startTime
group by u.RefDate, u.Symbol, u.five_min_grp
order by u.symbol
DB Fiddle Demo-不使用CTE，因为其SQLite版本已过时
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