I have a table with the following data that I generated with a date table
date day_num (DAY_NUM % 7)
2019-07-09 0 0
2019-07-10 1 1
2019-07-11 2 2
2019-07-12 3 3
2019-07-13 4 4
2019-07-14 5 5
2019-07-15 6 6
2019-07-16 7 0
I basically want to get a week number that restarts at 0 and I need help figuring out the last part
The final output would look like this
date day_num (DAY_NUM % 7) week num
2019-07-09 0 0 1
2019-07-10 1 1 1
2019-07-11 2 2 1
2019-07-12 3 3 1
2019-07-13 4 4 1
2019-07-14 5 5 1
2019-07-15 6 6 1
2019-07-16 7 0 2
This is the sql I have so far
select
SUB.*,
DAY_NUM%7
FROM(
SELECT
DISTINCT
id_date,
row_number() over(order by id_date) -1 as day_num
FROM schema.date_tbl
WHERE Id_date BETWEEN "2019-07-09" AND date_add("2019-07-09",146)
Building on your query:
select SUB.*, DAY_NUM%7,
DENSE_RANK() OVER (ORDER BY FLOOR(DAY_NUM / 7)) as weeknum
FROM (SELECT DISTINCT id_date,
row_number() over(order by id_date) -1 as day_num
FROM schema.date_tbl
WHERE Id_date BETWEEN "2019-07-09" AND date_add("2019-07-09", 146)
) x
Related
Date Amt ytd mtd
01-Jan-21 1 2 2
01-Jan-21 1 2 2
02-Jan-21 1 3 3
03-Jan-21 1 4 4
01-Feb-21 1 5 1
02-Feb-21 1 6 2
03-Feb-21 1 7 3
04-Feb-21 1 8 4
05-Feb-21 1 9 5
01-Mar-21 1 10 1
02-Mar-21 1 11 2
03-Mar-21 1 12 3
04-Mar-21 1 13 4
01-Apr-21 1 14 1
02-Apr-21 1 15 2
03-Apr-21 1 16 3
01-May-21 1 17 1
02-May-21 1 18 2
03-May-21 1 19 3
04-May-21 1 20 4
05-May-21 1 21 5
06-May-21 1 22 6
I have the first two columns (Date, Amt) and i need the YTD and MTD columns in MS SQL so that i can show the above table.
Seems like a rolling COUNT OVER was used to calculate the ytd & mtd in the Oracle source.
(Personally, I would prefere RANK or DENSE_RANK)
And since Oracle datestamps can be casted to a DATE as-is.
SELECT [Date], Amt
, ytd = COUNT(*) OVER (ORDER BY CAST([Date] AS DATE))
, mtd = COUNT(*) OVER (PARTITION BY EOMONTH(CAST([Date] AS DATE)) ORDER BY CAST([Date] AS DATE))
FROM your_table
ORDER BY CAST([Date] AS DATE)
Date
Amt
ytd
mtd
01-Jan-21
1
2
2
01-Jan-21
1
2
2
02-Jan-21
1
3
3
03-Jan-21
1
4
4
01-Feb-21
1
5
1
02-Feb-21
1
6
2
03-Feb-21
1
7
3
04-Feb-21
1
8
4
05-Feb-21
1
9
5
db<>fiddle here
I have a table like this:
date
user_id
revenue
2021-10-01
1
2
2021-10-02
1
3
2021-10-05
1
2
2021-10-09
1
3
2021-10-15
1
3
2021-10-01
2
2
2021-10-04
2
2
2021-10-10
2
1
2021-10-11
2
3
2021-10-11
2
3
2021-10-20
2
5
And I want to add column with median revenue for the last 5 days group by user_id. Desired output should looks like this:
date
user_id
revenue
median_last_5_days
2021-10-01
1
2
NULL
2021-10-02
1
3
2
2021-10-05
1
2
2.5
2021-10-09
1
3
2
2021-10-16
1
3
NULL
2021-10-01
2
2
NULL
2021-10-02
2
3
2
2021-10-03
2
3
2.5
2021-10-04
2
2
3
2021-10-10
2
1
NULL
2021-10-11
2
3
1
2021-10-11
2
3
2
2021-10-20
2
5
NULL
Can I produce this with SQL BigQuery?
Thanks for helping me)
Use of PERCENTILE_CONT or PERCENTILE_DISC to get the median will not work on these conditions as window_frame_clause are not allowed in Navigation functions.
Try this approach,
CREATE TEMP FUNCTION MEDIAN(arr ANY TYPE) AS ((
SELECT
IF(
MOD(ARRAY_LENGTH(arr), 2) = 0,
(arr[OFFSET(DIV(ARRAY_LENGTH(arr), 2) - 1)] + arr[OFFSET(DIV(ARRAY_LENGTH(arr), 2))]) / 2,
arr[OFFSET(DIV(ARRAY_LENGTH(arr), 2))]
)
FROM (SELECT ARRAY_AGG(x ORDER BY x) AS arr FROM UNNEST(arr) AS x)
));
SELECT
date,
user_id,
revenue,
MEDIAN(
ARRAY_AGG(revenue) OVER (PARTITION BY user_id
ORDER BY datetime_diff(date, date('2000-01-01'), day)
RANGE BETWEEN 4 PRECEDING AND 1 PRECEDING)
) AS median_last_5_days
FROM `my-project.my-dataset.my-table`
GROUP BY date, user_id, revenue
ORDER BY user_id;
Sample data:
Output:
I need a script that will give me a total sum of amounts per sort for the past 3 days and upcoming week.
I have made a script (link to dbfiddle.uk) that will sum the amount of the grouped date and sort types. However I am unclear on how to move forward at this point.
I want the past 3 days and upcoming 7 days of the today's date (dynamically), not just the dates found in my table.
I also want to show all the sort types.
So if there are no records for the date and sort type, show 0 as result.
plannings table
id date cell_id farmer_id
1 2020-04-21 1 1
2 2020-04-22 1 1
3 2020-04-24 1 1
4 2020-04-21 2 1
5 2020-04-22 2 1
6 2020-04-23 1 1
7 2020-04-25 1 1
8 2020-04-26 1 1
9 2020-04-22 4 1
10 2020-04-21 4 1
11 2020-04-23 4 1
planning_amounts table
id planning_id sort_type_id amount
2 1 1 43
3 1 3 34
4 2 1 54
5 3 1 45
6 4 1 90
7 5 3 45
8 5 1 99
9 6 1 66
10 7 1 999
11 8 3 90
12 9 1 23
13 10 1 43
14 11 1 55
sort_types table
id name description
1 Fijn Fijn
2 Middel Middel
3 Reuze Reuze
4 Industrie Industrie
The expected result would look like this. (this obviously for the past 3 + upcomming 7 days)
amount description date
176 Fijn 2020-04-21
34 Reuze 2020-04-21
0 Middel 2020-04-21
0 Industrie 2020-04-21
176 Fijn 2020-04-22
45 Reuze 2020-04-22
0 Middel 2020-04-22
0 Industrie 2020-04-22
121 Fijn 2020-04-23
0 Reuze 2020-04-23
0 Middel 2020-04-23
0 Industrie 2020-04-23
Query
SELECT SUM(amount) as amount, a.date, c.description
FROM planning_amounts b
join plannings a ON b.planning_id = a.id
join (SELECT * from sort_types) c ON b.sort_type_id = c.id
group by date, c.description
order by date
Hope I understood your question a bit better now:
WITH DesiredDates AS
(SELECT CAST(DATEADD(dd,-3,GETDATE()) as DATE) AS DesiredDate UNION ALL
SELECT CAST(DATEADD(dd,-2,GETDATE()) as DATE) UNION ALL
SELECT CAST(DATEADD(dd,-1,GETDATE()) as DATE) UNION ALL
SELECT CAST(GETDATE() as DATE) UNION ALL
SELECT CAST(DATEADD(dd,1,GETDATE()) as DATE) UNION ALL
SELECT CAST(DATEADD(dd,2,GETDATE()) as DATE) UNION ALL
SELECT CAST(DATEADD(dd,3,GETDATE()) as DATE) UNION ALL
SELECT CAST(DATEADD(dd,4,GETDATE()) as DATE) UNION ALL
SELECT CAST(DATEADD(dd,5,GETDATE()) as DATE) UNION ALL
SELECT CAST(DATEADD(dd,6,GETDATE()) as DATE) UNION ALL
SELECT CAST(DATEADD(dd,7,GETDATE()) as DATE)
), DesiredDatesAndSortTypes AS (
SELECT * FROM DesiredDates CROSS JOIN (select id from sort_types) t
)
SELECT SUM(ISNULL(Amount,0)) as Amount, DesiredDate, c.Description
FROM planning_amounts b
join plannings a ON b.planning_id = a.id
right join DesiredDatesAndSortTypes ddst ON CAST(a.date as DATE)=ddst.DesiredDate and b.sort_type_id=ddst.id
join sort_types c ON ddst.id = c.id
GROUP BY ddst.DesiredDate,c.Description
ORDER BY DesiredDate,Description
Here's the fiddle:
https://dbfiddle.uk/?rdbms=sqlserver_2019&fiddle=c508639ba4ec5bd49b49c9afe0692c9f
If I missunderstood yet again, please clarify where :)
I want to create a select query in SQL Server where I group the rows by a column (BaseId) and also order them by Status, RTime and Version. I want to add a column "isFirst" that has the value 1 if the BaseId value is the first in the group, and 0 if it's not.
My sample table:
Table name: Head
Id BaseId Name RTime Status Version
2 2 abc 04-12 12:34 1 1
3 3 xyz 04-12 13:10 9 1
4 2 abc 04-13 14:25 0 2
5 3 xyz 04-14 12:34 0 2
6 3 xyz 04-14 13:10 9 3
7 3 xyz 04-16 14:25 1 4
8 2 abc 04-16 17:40 1 3
9 9 sql 04-17 02:23 9 1
10 9 sql 04-17 07:31 0 2
Expected result:
isFirst Id BaseId Name RTime Status Version
1 10 9 sql 04-17 07:31 0 2
0 9 9 sql 04-17 02:23 9 1
1 5 3 xyz 04-14 12:34 0 2
0 7 3 xyz 04-16 14:25 1 4
0 6 3 xyz 04-14 13:10 9 3
0 3 3 xyz 04-12 13:10 9 1
1 4 2 abc 04-13 14:25 0 2
0 8 2 abc 04-16 17:40 1 3
0 2 2 abc 04-12 12:34 1 1
My query now looks like this:
SELECT *
FROM Head
ORDER BY BaseId desc, Status, RTime desc, Version desc
I think I should use CASE to create the isFirst column, but I've had no luck so far. Anyone could help me?
You can use row_number() and a case expression:
select
case when row_number() over(
partition by BaseId
order by Status, RTime desc, Version desc
) = 1
then 1
else 0
end isFirst,
h.*
from head h
order by BaseId desc, Status, RTime desc, Version desc
I have a set of data that looks like below
Name Time Perc Group Mode Control Cancelled
A 10:52 10.10 10 0 1 0
B 09:00 10.23 10 1 1 1
C 12:02 12.01 12 0 1 1
D 10:45 12.12 12 1 7 1
E 12:54 12.56 12 1 3 0
F 01:01 13.90 13 0 11 1
G 02:45 13.23 13 1 12 1
H 09:10 13.21 13 1 1 0
I need an output like below;
Group Perc Cancelled
10 20.33 1
12 36.69 2
13 40.34 2
What I'm getting was something like;
Group Perc Cancelled
10 20.33 5
12 36.69 5
13 40.34 5
I don't know what to call this, I have something in my mind to call it like CTE?, but I really can't figure it out.
Here's my source;
SELECT Group, SUM(Perc), Cancelled FROM
(SELECT Group, Perc, (SELECT COUNT(*) FROM tblName WHERE Cancelled=1) AS Cancelled FROM tblName WHERE 1=1 AND Group>=10)dt
GROUP BY Group, Cancelled
From your example, you don't need the nested query, any recursion, etc...
SELECT
Group,
SUM(Perc) AS total_perc,
SUM(cancelled) AS total_cancelled
FROM
tblName
WHERE
1=1
AND Group >= 10
GROUP BY
Group
If you did have some different data, then you might want to use something like...
SUM(CASE WHEN cancelled > 0 THEN 1 ELSE 0 END) AS total_cancelled