July 26, 2021 at 2:10 pm
SELECT count(*)
,DATENAME(dw, [myDateTime]) as DOW
FROM [myDatabase].[dbo].[myTable]
group by DATENAME(dw, [myDateTime])
this gets me what i need for like a total for day of week but what would i need to do in order to get like a grouping by month, DOW, Count and a grpuping of Year, DOW, count
currently i get
DOW, Count but would also like to get
Month, DOW, Count and
Year, DOW, Count
July 26, 2021 at 2:26 pm
You didn't provide any sample data, so I can't test my code, but something like this should do what you need:
SELECT COUNT(*) AS DayCount
,YEAR(myDateTime) AS Year
,MONTH(myDateTime) AS Month
,DATENAME(dw, [myDateTime]) as DOW
FROM [myDatabase].[dbo].[myTable]
GROUP BY DATENAME(dw, [myDateTime]), YEAR(myDateTime), MONTH(myDateTime) WITH ROLLUP
SQL DBA,SQL Server MVP(07, 08, 09) "It's a dog-eat-dog world, and I'm wearing Milk-Bone underwear." "Norm", on "Cheers". Also from "Cheers", from "Carla": "You need to know 3 things about Tortelli men: Tortelli men draw women like flies; Tortelli men treat women like flies; Tortelli men's brains are in their flies".
July 26, 2021 at 2:36 pm
Works like a charm. thank you
I have follow up question though. (we always do) i made a minor change to get the month name but basically same results.
why am i getting the year,null and null,null records
SELECT COUNT(*) AS DayCount
,YEAR(myDateTime) AS Year
,DATENAME(month, [myDateTime]) AS Monthly
,DATENAME(dw, [myDateTime]) as DOW
FROM [myDatabase].[dbo].[myTable]
GROUP BY DATENAME(dw, [myDateTime]), YEAR([myDateTime]),DATENAME(month, [myDateTime]) WITH ROLLUP
DayCount Year Monthly DOW
631 2021 July Friday
173 2021 June Friday
3 2021 May Friday
807 2021 NULL Friday
807 NULL NULL Friday
1 2021 April Monday
493 2021 July Monday
229 2021 June Monday
2 2021 March Monday
1 2021 May Monday
726 2021 NULL Monday
726 NULL NULL Monday
39 2021 July Saturday
13 2021 June Saturday
52 2021 NULL Saturday
52 NULL NULL Saturday
761 2021 July Sunday
266 2021 June Sunday
1027 2021 NULL Sunday
1027 NULL NULL Sunday
1 2021 January Thursday
743 2021 July Thursday
181 2021 June Thursday
2 2021 March Thursday
927 2021 NULL Thursday
927 NULL NULL Thursday
1 2021 April Tuesday
679 2021 July Tuesday
229 2021 June Tuesday
1 2021 May Tuesday
910 2021 NULL Tuesday
910 NULL NULL Tuesday
2 2021 April Wednesday
554 2021 July Wednesday
377 2021 June Wednesday
2 2021 May Wednesday
935 2021 NULL Wednesday
935 NULL NULL Wednesday
5384 NULL NULL NULL
July 26, 2021 at 2:59 pm
That's from the ROLLUP.
The one with NULL, NULL is the global dayname total, so all Mondays, Tuesdays, etc., regardless of year, month.
The one with NULL, YEAR is supposed to be monthly total, but it doesn't look like it's working. If you can post sample data, I'll correct the code.
SQL DBA,SQL Server MVP(07, 08, 09) "It's a dog-eat-dog world, and I'm wearing Milk-Bone underwear." "Norm", on "Cheers". Also from "Cheers", from "Carla": "You need to know 3 things about Tortelli men: Tortelli men draw women like flies; Tortelli men treat women like flies; Tortelli men's brains are in their flies".
July 26, 2021 at 4:03 pm
customer, myDateTime
1854
2020-06-17 11:09:04.000
262
2020-08-14 06:20:39.000
157
2020-08-21 11:05:44.000
319
2020-08-27 08:39:22.000
262
2020-08-28 04:52:56.000
1217
2020-09-03 17:11:48.000
262
2020-09-04 05:50:05.000
157
2020-09-04 16:59:15.000
157
2020-09-08 08:13:37.000
262
2020-09-11 06:35:46.000
262
2020-09-18 07:02:56.000
1640
2020-09-22 06:36:18.000
2376
2020-09-23 07:33:50.000
2376
2020-09-23 07:40:58.000
2376
2020-09-23 07:56:15.000
334
2020-09-23 17:03:36.000
1701
2020-09-24 07:50:25.000
1701
2020-09-24 07:51:56.000
122
2020-09-24 16:55:29.000
72
2020-09-27 09:27:27.000
510
2020-09-27 23:59:38.000
80
2020-09-28 12:27:36.000
2014
2020-09-28 13:42:17.000
1854
2020-09-28 14:51:29.000
733
2020-09-28 15:07:27.000
733
2020-09-28 15:08:52.000
334
2020-09-28 17:03:46.000
1898
2020-09-29 07:52:32.000
1898
2020-09-29 07:55:02.000
282
2020-09-29 10:55:37.000
114
2020-09-29 13:48:00.000
827
2020-09-30 08:26:14.000
661
2020-09-30 22:55:12.000
346
2020-10-01 10:27:23.000
1181
2020-10-01 17:30:01.000
1279
2020-10-05 11:29:15.000
968
2020-10-05 21:09:56.000
303
2020-10-06 17:40:59.000
1506
2020-10-06 17:43:31.000
1506
2020-10-06 19:28:13.000
1712
2020-10-07 06:22:33.000
734
2020-10-08 07:46:38.000
185
2020-10-08 14:14:03.000
185
2020-10-08 14:20:43.000
1293
2020-10-08 16:03:19.000
481
2020-10-08 17:08:56.000
1691
2020-10-09 07:37:46.000
1279
2020-10-09 08:00:22.000
734
2020-10-09 17:21:07.000
734
2020-10-09 17:22:44.000
1488
2020-10-09 17:24:13.000
72
2020-10-10 10:43:41.000
1712
2020-10-12 05:56:42.000
133
2020-10-12 16:59:06.000
133
2020-10-13 17:04:26.000
157
2020-10-14 16:46:04.000
133
2020-10-15 17:01:53.000
185
2020-10-16 06:44:43.000
1599
2020-10-16 08:12:31.000
157
2020-10-16 08:14:17.000
1599
2020-10-19 10:38:32.000
242
2020-10-19 17:13:11.000
1657
2020-10-20 07:14:19.000
1599
2020-10-20 08:44:22.000
1985
2020-10-20 17:27:33.000
157
2020-10-21 08:28:51.000
1477
2020-10-21 15:33:41.000
1455
2020-10-21 17:03:38.000
1899
2020-10-21 21:24:20.000
157
2020-10-22 08:02:38.000
202
2020-10-23 12:35:47.000
157
2020-10-23 16:46:05.000
610
2020-10-23 17:20:06.000
157
2020-10-26 07:35:00.000
133
2020-10-26 17:02:04.000
1150
2020-10-28 06:57:11.000
1599
2020-10-28 08:26:40.000
612
2020-10-28 16:16:35.000
746
2020-10-28 16:33:18.000
1150
2020-10-28 17:01:55.000
1599
2020-10-29 08:24:01.000
1150
2020-10-29 10:42:03.000
1150
2020-10-29 13:38:17.000
846
2020-10-29 15:35:46.000
846
2020-10-29 15:36:29.000
454
2020-10-29 16:06:04.000
1130
2020-10-29 16:11:14.000
1130
2020-10-29 16:16:41.000
1130
2020-10-29 16:18:45.000
1625
2020-10-29 16:25:18.000
612
2020-10-29 16:26:13.000
1139
2020-10-29 16:33:21.000
1937
2020-10-29 16:39:59.000
1870
2020-10-29 16:40:09.000
1077
2020-10-29 16:41:59.000
1139
2020-10-29 16:42:34.000
1937
2020-10-29 16:48:04.000
1284
2020-10-29 16:50:10.000
490
2020-10-29 16:50:18.000
1311
2020-10-29 16:52:01.000
554
2020-10-29 16:58:00.000
359
2020-10-29 17:00:48.000
605
2020-10-29 17:01:45.000
699
2020-10-29 17:02:17.000
393
2020-10-29 17:06:29.000
439
2020-10-29 17:12:19.000
129
2020-10-29 17:14:33.000
1470
2020-10-29 17:16:07.000
193
2020-10-29 17:16:41.000
507
2020-10-29 17:16:55.000
1532
2020-10-29 17:21:46.000
1870
2020-10-29 17:24:02.000
1351
2020-10-29 17:48:51.000
1883
2020-10-29 17:50:31.000
533
2020-10-29 17:55:57.000
243
2020-10-29 17:59:01.000
714
2020-10-29 18:01:50.000
501
2020-10-29 18:04:04.000
104
2020-10-29 18:05:39.000
758
2020-10-29 18:30:16.000
345
2020-10-29 18:49:43.000
895
2020-10-29 18:54:23.000
1651
2020-10-29 19:43:51.000
213
2020-10-29 19:47:10.000
627
2020-10-29 20:28:38.000
1307
2020-10-30 02:22:15.000
2733
2020-10-30 02:23:35.000
2350
2020-10-30 02:26:59.000
2336
2020-10-30 02:27:04.000
2693
2020-10-30 02:27:33.000
2715
2020-10-30 02:27:47.000
2257
2020-10-30 02:28:52.000
2275
2020-10-30 02:32:06.000
2393
2020-10-30 02:32:34.000
2036
2020-10-30 02:33:05.000
2686
2020-10-30 02:35:46.000
2746
2020-10-30 02:35:46.000
2676
2020-10-30 02:35:46.000
2271
2020-10-30 02:40:16.000
2436
2020-10-30 02:40:23.000
2398
2020-10-30 02:42:05.000
2413
2020-10-30 02:42:12.000
752
2020-10-30 02:42:41.000
2406
2020-10-30 02:42:49.000
856
2020-10-30 05:00:14.000
127
2020-10-30 05:08:59.000
4
2020-10-30 05:18:02.000
1265
2020-10-30 05:18:29.000
1960
2020-10-30 05:19:28.000
1745
2020-10-30 05:20:08.000
1074
2020-10-30 05:20:49.000
2099
2020-10-30 05:20:52.000
1991
2020-10-30 05:21:28.000
1822
2020-10-30 05:23:38.000
882
2020-10-30 05:24:50.000
1271
2020-10-30 05:27:56.000
119
2020-10-30 05:31:10.000
58
2020-10-30 05:32:01.000
2106
2020-10-30 05:32:12.000
2269
2020-10-30 05:32:21.000
2134
2020-10-30 05:32:23.000
2035
2020-10-30 05:32:38.000
134
2020-10-30 05:32:45.000
2166
2020-10-30 06:00:42.000
1544
2020-10-30 06:10:48.000
794
2020-10-30 06:21:31.000
638
2020-10-30 06:23:02.000
1121
2020-10-30 06:26:10.000
2315
2020-10-30 06:28:40.000
441
2020-10-30 06:31:32.000
475
2020-10-30 06:35:54.000
220
2020-10-30 06:40:01.000
185
2020-10-30 06:46:56.000
370
2020-10-30 06:47:34.000
600
2020-10-30 06:58:07.000
593
2020-10-30 07:00:28.000
230
2020-10-30 07:02:37.000
665
2020-10-30 07:04:35.000
1559
2020-10-30 07:05:28.000
128
2020-10-30 07:06:05.000
1986
2020-10-30 07:06:57.000
774
2020-10-30 07:08:04.000
415
2020-10-30 07:08:31.000
341
2020-10-30 07:11:25.000
549
2020-10-30 07:13:41.000
1484
2020-10-30 07:16:06.000
1685
2020-10-30 07:16:21.000
371
2020-10-30 07:16:35.000
2414
2020-10-30 07:19:43.000
186
2020-10-30 07:21:09.000
684
2020-10-30 07:21:47.000
317
2020-10-30 07:23:33.000
232
2020-10-30 07:25:23.000
1599
2020-10-30 07:28:18.000
294
2020-10-30 07:29:33.000
2228
2020-10-30 07:32:18.000
250
2020-10-30 07:32:48.000
1010
2020-10-30 07:35:43.000
2043
2020-10-30 07:37:25.000
254
2020-10-30 07:44:16.000
July 26, 2021 at 4:34 pm
Hmm, decent start, but I can't query against it.
I need an actual INSERT statement, that works, like this:
CREATE TABLE #data ( customer int NOT NULL, myDateTime datetime NULL );
INSERT INTO #data VALUES
(1854,'2020-06-17 11:09:04.000'),
(262, '2020-08-14 06:20:39.000'),
...,
...,
...
SQL DBA,SQL Server MVP(07, 08, 09) "It's a dog-eat-dog world, and I'm wearing Milk-Bone underwear." "Norm", on "Cheers". Also from "Cheers", from "Carla": "You need to know 3 things about Tortelli men: Tortelli men draw women like flies; Tortelli men treat women like flies; Tortelli men's brains are in their flies".
July 26, 2021 at 6:19 pm
sorry had a meeting to attend
SET ANSI_NULLS ON
GO
SET QUOTED_IDENTIFIER ON
GO
CREATE TABLE [dbo].[myTable](
[customer] [int] NOT NULL,
[myDateTime] [datetime] NOT NULL,
CONSTRAINT [PK_myTable] PRIMARY KEY CLUSTERED
(
[customer] ASC,
[myDateTime] ASC
)WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]
) ON [PRIMARY]
GO
there is create will gather up insert
July 26, 2021 at 6:40 pm
INSERT INTO [dbo].[myTable]
([customer]
,[myDateTime]
VALUES
(1 ,'2020-11-20 17:29:56')
(1 ,'2021-01-04 17:27:34')
(1 ,'2021-01-08 17:33:16')
(1 ,'2021-02-04 17:34:35')
(1 ,'2021-02-11 17:19:47')
(1 ,'2021-02-12 07:13:43')
(1 ,'2021-02-12 07:16:53')
(1 ,'2021-03-09 17:27:57')
(1 ,'2021-03-30 17:26:59')
(1 ,'2021-04-09 17:13:36')
(1 ,'2021-04-30 17:37:40')
(1 ,'2021-06-29 17:51:59')
(1 ,'2021-07-12 17:24:59')
(1 ,'2021-07-22 13:42:57')
(2 ,'2020-11-09 18:31:15')
(2 ,'2021-01-10 14:13:26')
(2 ,'2021-02-03 11:15:14')
(2 ,'2021-03-12 18:44:32')
(2 ,'2021-05-19 17:51:05')
(2 ,'2021-06-07 15:35:39')
(2 ,'2021-06-08 13:29:20')
(2 ,'2021-06-08 13:34:16')
(2 ,'2021-06-08 13:39:00')
(2 ,'2021-06-08 13:41:24')
(2 ,'2021-06-08 13:53:14')
(4 ,'2020-10-30 05:18:02')
(4 ,'2020-11-01 03:03:31')
(4 ,'2020-11-08 03:05:29')
(4 ,'2020-11-08 14:44:41')
(4 ,'2020-11-15 03:03:49')
(4 ,'2020-11-22 03:03:57')
(4 ,'2020-11-29 03:03:47')
(4 ,'2020-11-29 14:52:51')
(4 ,'2020-12-27 03:03:23')
(4 ,'2021-01-03 03:03:54')
(4 ,'2021-01-10 15:35:26')
(4 ,'2021-01-24 17:11:20')
(4 ,'2021-01-28 21:13:06')
(4 ,'2021-01-29 00:02:30')
(4 ,'2021-01-31 03:03:16')
(4 ,'2021-02-07 03:07:04')
(4 ,'2021-02-14 03:03:20')
(4 ,'2021-02-21 03:05:04')
(4 ,'2021-02-28 03:03:41')
(4 ,'2021-03-07 03:03:15')
(4 ,'2021-03-14 03:04:05')
(4 ,'2021-03-21 03:04:06')
(4 ,'2021-03-28 03:03:01')
(4 ,'2021-03-30 20:54:50')
(4 ,'2021-04-04 03:03:04')
(4 ,'2021-04-11 03:03:11')
(4 ,'2021-04-18 03:04:18')
(4 ,'2021-04-25 03:03:14')
(4 ,'2021-04-26 21:19:02')
(4 ,'2021-05-02 03:03:29')
(4 ,'2021-05-09 03:03:32')
(4 ,'2021-05-16 03:03:23')
(4 ,'2021-05-23 03:03:04')
(4 ,'2021-05-30 03:03:04')
(4 ,'2021-06-06 03:02:53')
(4 ,'2021-06-13 03:02:58')
(4 ,'2021-06-20 03:03:04')
(4 ,'2021-06-27 03:03:06')
(4 ,'2021-07-04 03:03:10')
(4 ,'2021-07-11 03:03:27')
(4 ,'2021-07-18 03:03:08')
(5 ,'2020-11-01 03:05:40')
(5 ,'2020-11-08 03:04:15')
(5 ,'2020-11-08 14:32:24')
(5 ,'2020-11-15 03:03:13')
(5 ,'2020-11-22 03:03:16')
(5 ,'2020-11-29 03:04:05')
(5 ,'2020-11-29 14:22:11')
(5 ,'2020-12-27 03:04:41')
(5 ,'2021-01-24 03:04:59')
(5 ,'2021-01-24 14:56:55')
(5 ,'2021-01-24 17:06:31')
(5 ,'2021-01-28 21:07:49')
(5 ,'2021-01-28 22:29:45')
(5 ,'2021-01-31 03:03:12')
(5 ,'2021-02-07 03:08:21')
(5 ,'2021-02-14 03:03:02')
(5 ,'2021-02-21 03:03:41')
(5 ,'2021-02-28 03:03:07')
(5 ,'2021-03-07 03:22:17')
(5 ,'2021-03-14 03:15:06')
(5 ,'2021-03-21 04:02:24')
(5 ,'2021-03-28 03:14:32')
(5 ,'2021-03-30 21:00:47')
(5 ,'2021-03-30 21:49:28')
(5 ,'2021-04-04 03:15:01')
(5 ,'2021-04-11 03:13:11')
(5 ,'2021-04-18 03:45:45')
(5 ,'2021-04-25 03:23:32')
(5 ,'2021-04-26 21:44:52')
(5 ,'2021-05-02 03:03:32')
(5 ,'2021-05-09 03:05:52')
(5 ,'2021-05-23 03:43:47')
(5 ,'2021-05-30 03:02:54')
(5 ,'2021-06-06 03:04:51')
(5 ,'2021-06-13 03:02:56')
(5 ,'2021-06-20 03:02:36')
(5 ,'2021-06-27 03:02:41')
(5 ,'2021-07-04 03:03:20')
(5 ,'2021-07-11 03:02:39')
(5 ,'2021-07-18 03:03:07')
(6 ,'2020-11-17 17:46:54')
(6 ,'2021-01-28 16:38:48')
(6 ,'2021-02-02 17:02:18')
(6 ,'2021-02-03 17:15:32')
(6 ,'2021-02-08 15:44:16')
(6 ,'2021-02-09 17:23:38')
(6 ,'2021-02-24 17:30:50')
(6 ,'2021-03-03 17:25:59')
(6 ,'2021-03-26 17:10:56')
(6 ,'2021-03-26 17:51:54')
(6 ,'2021-03-31 16:19:12')
(6 ,'2021-04-01 07:35:42')
(6 ,'2021-04-05 10:50:49')
(6 ,'2021-04-09 17:20:22')
(6 ,'2021-04-09 17:20:50')
(6 ,'2021-04-10 07:26:56')
(6 ,'2021-04-15 11:03:36')
(6 ,'2021-05-07 14:58:46')
(6 ,'2021-05-13 17:47:21')
(6 ,'2021-05-13 17:47:50')
(6 ,'2021-05-28 17:13:50')
(6 ,'2021-06-04 17:19:39')
(6 ,'2021-06-04 17:19:46')
(6 ,'2021-06-22 11:07:52')
(6 ,'2021-07-07 17:26:58')
(6 ,'2021-07-09 17:13:53')
(6 ,'2021-07-15 13:40:28')
(6 ,'2021-07-20 17:47:08')
(7 ,'2020-11-13 07:21:39')
(7 ,'2021-01-25 07:51:27')
(7 ,'2021-01-29 07:39:20')
(7 ,'2021-02-24 17:22:00')
(7 ,'2021-03-01 07:24:17')
(7 ,'2021-03-30 07:30:48')
(7 ,'2021-03-31 08:57:02')
(7 ,'2021-03-31 08:57:10')
(7 ,'2021-04-08 07:17:24')
(7 ,'2021-04-08 07:19:44')
(7 ,'2021-04-14 07:09:45')
(7 ,'2021-04-26 07:16:34')
(7 ,'2021-05-03 07:34:41')
(7 ,'2021-05-04 07:31:05')
(7 ,'2021-05-07 06:59:33')
(7 ,'2021-05-19 07:29:41')
(7 ,'2021-05-20 13:39:14')
(7 ,'2021-06-08 06:53:54')
(7 ,'2021-06-08 06:54:01')
(7 ,'2021-06-08 06:58:13')
(7 ,'2021-07-02 07:21:20')
(8 ,'2020-11-03 18:39:27')
(8 ,'2020-11-03 18:40:50')
(8 ,'2020-11-03 18:42:34')
(8 ,'2020-11-03 18:42:42')
(8 ,'2021-02-01 08:09:32')
(8 ,'2021-02-01 08:39:24')
(8 ,'2021-02-01 10:17:45')
(8 ,'2021-02-02 07:54:48')
(8 ,'2021-02-02 07:57:43')
(8 ,'2021-02-02 07:57:55')
(8 ,'2021-02-02 08:45:20')
(8 ,'2021-04-13 20:15:59')
(8 ,'2021-04-19 08:04:21')
(8 ,'2021-04-19 10:32:59')
(8 ,'2021-04-19 10:43:10')
(8 ,'2021-04-19 10:45:57')
(8 ,'2021-04-19 10:50:22')
(8 ,'2021-04-19 10:54:41')
(8 ,'2021-04-19 11:09:42')
(8 ,'2021-04-26 08:40:55')
(8 ,'2021-04-29 13:32:23')
(8 ,'2021-04-29 14:33:24')
(8 ,'2021-04-29 14:33:41')
(8 ,'2021-04-29 14:55:13')
(8 ,'2021-04-29 15:14:10')
(8 ,'2021-04-29 15:15:56')
(8 ,'2021-05-25 21:53:34')
(8 ,'2021-06-16 13:06:24')
(8 ,'2021-06-16 18:17:16')
(9 ,'2020-11-04 12:49:46')
(9 ,'2020-11-04 12:49:59')
(10 ,'2021-02-22 10:24:43')
(10 ,'2021-02-22 10:29:30')
(10 ,'2021-02-22 15:46:09')
(10 ,'2021-02-22 16:03:06')
(10 ,'2021-03-15 07:53:38')
(10 ,'2021-04-16 07:55:21')
(10 ,'2021-06-04 07:54:20')
(10 ,'2021-07-21 07:50:50')
(11 ,'2020-10-30 07:59:40')
(11 ,'2020-11-09 08:04:17')
(11 ,'2020-11-12 08:01:01')
(11 ,'2020-11-16 07:58:31')
(11 ,'2020-11-17 08:04:33')
(11 ,'2020-11-30 08:07:52')
GO
July 26, 2021 at 7:49 pm
Thanks for the test data! Sorry if I seemed difficult, but I help on up to dozens qs a day, and I just don't have to do data prep for all the qs.
See if this gives you something better:
SELECT
COUNT(*) AS DayCount
,ISNULL(myYear, 'All') AS Year
,ISNULL(myMonth, 'All') AS Month
,DOW
FROM dbo.MyTable
CROSS APPLY (
SELECT CAST(YEAR(myDateTime) AS varchar(5)) AS myYear,
CAST(MONTH(myDateTime) AS varchar(5)) AS myMonth,
DATENAME(dw, [myDateTime]) as DOW
) AS ca1
GROUP BY DOW, myYear, myMonth WITH ROLLUP
HAVING GROUPING(DOW) = 0
ORDER BY DOW, myYear, myMonth
SQL DBA,SQL Server MVP(07, 08, 09) "It's a dog-eat-dog world, and I'm wearing Milk-Bone underwear." "Norm", on "Cheers". Also from "Cheers", from "Carla": "You need to know 3 things about Tortelli men: Tortelli men draw women like flies; Tortelli men treat women like flies; Tortelli men's brains are in their flies".
July 26, 2021 at 7:52 pm
Personally I think I'd rather see the days as columns in the same row, i.e. a column for Monday, a column for Tuesday, etc.., with one per month and one row per year. But that's just my personal preference, of course, so use whatever format you like/need.
SQL DBA,SQL Server MVP(07, 08, 09) "It's a dog-eat-dog world, and I'm wearing Milk-Bone underwear." "Norm", on "Cheers". Also from "Cheers", from "Carla": "You need to know 3 things about Tortelli men: Tortelli men draw women like flies; Tortelli men treat women like flies; Tortelli men's brains are in their flies".
July 26, 2021 at 10:53 pm
as for the format of this data i am going to be using it for a bar/line chart.
basically 3 different ways.
bar chart with just sunday thru saturday and totals for each day.
then another line chart with left axis as months of the year (no year needed) and again bottom axis as sun - sat
next chart is left axis years and bottom axis sun - sat.
our clients can run a particular process whenever they want and we gather that info back and mgmt was asking for when does this occur the most during the week and if it was different for various months/years
by the way that newest query gives me all the info i need now i can just tweek it as needed. so thank you very much
July 26, 2021 at 11:00 pm
... and using that same datetime column i am going to do same with the time of day part grouping into 0 - 24 hour 1 hour increments by DOW, Month, Years
basically they are looking at any trends by clients so we can best determine when we should be making any changes to our ftp server or when not to try anything.
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