SQL Server 2017

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CREATE TABLE elbat
             (column1 date,
              column2 integer,
              column3 integer);
INSERT INTO elbat
            (column1,
             column2)
            VALUES (convert(date, '04/07/2019', 101), 1),
                   (convert(date, '04/08/2019', 101), 2),
                   (convert(date, '04/09/2019', 101), 8),
                   (convert(date, '04/10/2019', 101), 9),
                   (convert(date, '04/11/2019', 101), 15),
                   (convert(date, '04/12/2019', 101), 16),
                   (convert(date, '04/13/2019', 101), 5),
                   (convert(date, '04/14/2019', 101), 6),
                   (convert(date, '04/15/2019', 101), 8),
                   (convert(date, '04/16/2019', 101), 9),
                   (convert(date, '04/17/2019', 101), 10),
                   (convert(date, '04/18/2019', 101), 11),
                   (convert(date, '04/19/2019', 101), 5),
                   (convert(date, '04/20/2019', 101), 5),
                   (convert(date, '04/21/2019', 101), 8),
                   (convert(date, '04/22/2019', 101), 8),
                   (convert(date, '04/23/2019', 101), 9),
                   (convert(date, '04/24/2019', 101), 10),
                   (convert(date, '04/25/2019', 101), 11),
                   (convert(date, '04/26/2019', 101), 12),
                   (convert(date, '04/27/2019', 101), 10);
21 rows affected

SET DATEFIRST 7;
UPDATE t1
       SET t1.column3 = t3.column3
       FROM elbat t1
            INNER JOIN (SELECT t2.column1,
                               sum(t2.column2) OVER (PARTITION BY datepart(week, t2.column1)) column3
                               FROM elbat t2) t3
                       ON t3.column1 = t1.column1;
21 rows affected

SELECT *
       FROM elbat;


column1
column2
column3


07/04/2019 00:00:00
1
56

08/04/2019 00:00:00
2
56

09/04/2019 00:00:00
8
56

10/04/2019 00:00:00
9
56

11/04/2019 00:00:00
15
56

12/04/2019 00:00:00
16
56

13/04/2019 00:00:00
5
56

14/04/2019 00:00:00
6
54

15/04/2019 00:00:00
8
54

16/04/2019 00:00:00
9
54

17/04/2019 00:00:00
10
54

18/04/2019 00:00:00
11
54

19/04/2019 00:00:00
5
54

20/04/2019 00:00:00
5
54

21/04/2019 00:00:00
8
68

22/04/2019 00:00:00
8
68

23/04/2019 00:00:00
9
68

24/04/2019 00:00:00
10
68

25/04/2019 00:00:00
11
68

26/04/2019 00:00:00
12
68

27/04/2019 00:00:00
10
68

column1	column2	column3
07/04/2019 00:00:00	1	56
08/04/2019 00:00:00	2	56
09/04/2019 00:00:00	8	56
10/04/2019 00:00:00	9	56
11/04/2019 00:00:00	15	56
12/04/2019 00:00:00	16	56
13/04/2019 00:00:00	5	56
14/04/2019 00:00:00	6	54
15/04/2019 00:00:00	8	54
16/04/2019 00:00:00	9	54
17/04/2019 00:00:00	10	54
18/04/2019 00:00:00	11	54
19/04/2019 00:00:00	5	54
20/04/2019 00:00:00	5	54
21/04/2019 00:00:00	8	68
22/04/2019 00:00:00	8	68
23/04/2019 00:00:00	9	68
24/04/2019 00:00:00	10	68
25/04/2019 00:00:00	11	68
26/04/2019 00:00:00	12	68
27/04/2019 00:00:00	10	68