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I need to return row numbers for consecutive dates for each activity.
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I have tried row_number() over(partition by) but cannot seem to get the right row numbers against the consecutive dates for the activity type. This is what I am trying to return:
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On Synapse Analytics how do we - Convert a Time datatype column with values from hh:mm:ss.ffffff to hh:mm:ss:ff
Here are the samples:
Actual
00:00:00.9900000
00:26:10.0200000
00:00:03.9800000
00:22:41.0400000
00:00:00.9800000
00:22:09.0300000
00:00:00.9900000
00:25:34.0200000
00:19:26.9800000
00:03:45.0200000
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Trying to add address fields with comma at the end of the field , but if any one of the field is missing i am getting multiple comma's
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I am trying to retrieve the last 10 mentions of the text that's in cell B8.
For example, if B8 is "Tom Brady", I want to retrieve the last 10 results for Passing Yards (DB:M) that mention Tom Brady.
I got this formula but it displays the first 15 it seems.
=QUERY(DB!B:AZ,"select M where C = '"&B8&"' order by B desc limit 15")
https://docs.google.com/spreadsheets/d/12b9dxeSt4_F9hdgaqDzggNW-fbMyXesWaqT0JjqMVhk/edit?usp=sharing
Any help would be appreciated!
use:
=INDEX(SORT(SORTN(FILTER({D5:D, ROW(D5:D)}, D5:D<>""), 10, 0, 2, 0), 2, 1),,1)
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I want to display the only the highlighted values (They are 9 digits). Can we do this using RegExp?
You can use regexp_substr(column1, '[0-9]{9}'). Below is an example:
select regexp_substr(column1, '[0-9]{9}') nine_digits
from (values
(';**260488570**;1;13.25;20339=22.99')
,('1293=::info::0,;**297100755**;1;2.86;20339=4.49')
,('1293=::info::0,;**338010030**;3;6.71;20339=2.69')
,('1293=::info::0,;**260142941**;1;2.38;20339=4.59')
,('1293=::info::0,;**370039059**;1;2.86;20339=3.79')
);
Result:
COL2
260488570
297100755
338010030
260142941
370039059
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Should be an easy convert, but cast and convert are failing me.
The value I am trying to convert is: 1509180600
Other examples are 1572256200, 5150938920
I have a very large number of records and many fields where dates have been stored like this. The system is being replaced, which means thankfully, this problem will go. But need to know what the values are before wiping them!
This is probably a Unix timestamp. You can convert it by adding seconds to 1970-01-01:
select dateadd(second, col, '1970-01-01')
. . .