I have a table as follow:
id |minutes |sumOfMinutes|Date
_______________________________________
1 | 5 | | 20141106
1 | 7 | | 20141106
2 | 1 | | 20141106
2 | 9 | | 20141106
3 | 8 | | 20141106
How can I store sum of minutes in the third column for rows under the same month, so that i have:
id |minutes |sumOfMinutes| Date
_____________________________________
1 | 5 | 12 | 20141106
1 | 7 | 12 | 20141112
2 | 1 | 18 | 20141006
2 | 9 | 18 | 20141007
3 | 8 | 18 | 20141009
Use SUM() and Group by
SELECT table1.id, table1.minutes, SUM(monthTot.minutes), table1.Date
FROM table 1
JOIN table1 AS monthTot ON
MONTH(monthTot.date) = MONTH(table1.date)
GROUP BY table1.id, table1.minutes, table1.Date
sum with partition by option can be used to achieve this.
select id, [minutes],
sum([minutes]) over ( partition by month([date]) ) as sumOfMinutes,
[Date]
from Table1
Related
I am trying to create a view in postgreSQL with the requirements as below:
The table needs to show the same period last year data for every records.
Sample data:
date_sk | location_sk | division_sk | employee_type_sk | value
20180202 | 6 | 8 | 4 | 1
20180202 | 7 | 2 | 4 | 2
20190202 | 6 | 8 | 4 | 1
20190202 | 7 | 2 | 4 | 1
20200202 | 6 | 8 | 4 | 1
20200202 | 7 | 2 | 4 | 3
In the table, date_sk, location_sk, division_sk and employee_type_sk are super keys which form an unique record in the table.
You can check the required output as below:
date_sk | location_sk | division_sk | employee_type_sk | value | value_last_year
20180202 | 6 | 8 | 4 | 1 | NULL
20180203 | 7 | 2 | 4 | 2 | NULL
20190202 | 6 | 8 | 4 | 1 | 1
20190203 | 7 | 3 | 4 | 1 | NULL
20200202 | 6 | 8 | 4 | 1 | 1
20200203 | 7 | 3 | 4 | 3 | 1
The records start on 20180202, therefore, the data for the same period last year is unavailable. At the 4th record, there is a difference in division_sk comparing with the same period last year - hence, the head_count_last_year is NULL.
My current solution is to create a view from the sample data with an addition column as same_date_last_year then LEFT JOIN the same table. The SQL queries are below:
CREATE VIEW test_view AS
SELECT *,
CONCAT(LEFT(date_sk, 4) - 1, RIGHT(date_sk, 4)) AS same_date_last_year
FROM test_table
SELECT
test_view.date_sk,
test_view.location_sk,
test_view.division_sk,
test_view.employee_type_sk,
test_view.value,
test_table.value AS value_last_year
FROM test_view
LEFT JOIN test_table ON (test_view.same_date_last_year = test_table.date_sk)
We have a lot of data in the table. My solution above is unacceptable in terms of performance.
Is there a different query which yields the same result and might improve the performance ?
You could simply use a correlated subquery here which is likely best for performance:
select *,
(
select value from t t2
where t2.date_sk=t.date_sk - interval '1' year and
t2.location_sk=t.location_sk and
t2.division_sk=t.division_sk and
t2.employee_type_sk=t.employee_type_sk
) as value_last_year
from t
WITH CTE(DATE_SK,LOCATION_SK,DIVISION_SK,EMPLOYEE_TYPE_SK,VALUE)AS
(
SELECT CAST('20180202' AS DATE),6,8,4,1 UNION ALL
SELECT CAST('20180203'AS DATE),7,2,4,2 UNION ALL
SELECT CAST('20190202'AS DATE),6,8,4,1 UNION ALL
SELECT CAST('20190203'AS DATE),7,2,4,1 UNION ALL
SELECT CAST('20200202'AS DATE),6,8,4,1 UNION ALL
SELECT CAST('20200203'AS DATE),7,2,4,3
)
SELECT C.DATE_SK,C.LOCATION_SK,C.DIVISION_SK,C.EMPLOYEE_TYPE_SK,C.VALUE,
LAG(C.VALUE)OVER(PARTITION BY C.LOCATION_SK,C.DIVISION_SK,C.EMPLOYEE_TYPE_SK ORDER BY C.DATE_SK ASC)LAGG
FROM CTE AS C
ORDER BY C.DATE_SK ASC;
Could you please try if the above is suitable for you. I assume,DATE_SK is a date column or can be CAST to a date
consider we have a table with this columns
Id
fk_newsId
fk_NewsGroupId
fk_NewsZoneId
I need to select all records with same fk_NewsGroup and fk_NewsZone
something like this
+----+-----------+--------------+-------------+
| Id | fk_NewsId | fk_NewsGroup | fk_NewsZone |
+----+-----------+--------------+-------------+
| 1 | 60 | 5 | 8 |
| 2 | 30 | 5 | 8 |
| 3 | 31 | 9 | 20 |
| 4 | 5 | 9 | 20 |
| 5 | 12 | 9 | 20 |
| 6 | 1000 | 20 | 11 |
| 7 | 21 | 20 | 11 |
| 8 | 6 | 20 | 11 |
+----+-----------+--------------+-------------+
how can do that?
I tride group by like this
but it dosnt give desired output
select fk_NewsId, fk_NewsGroup,fk_NewsZone from tbl_test
group by fk_NewsGroup,fk_NewsZone,fk_NewsId
You can try to use COUNT with window function, to get the count by fk_NewsGroup and fk_NewsZone columns.
then get count greater than one.
SELECT *
FROM (
SELECT *,COUNT(*) OVER(PARTITION BY fk_NewsGroup,fk_NewsZone ORDER BY fk_NewsZone) cnt
FROM tbl_test
)t1
where t1.cnt > 1
dbfiddle
Not absolutely clear as to what you mean, but something like so:
SELECT t.Id, t.fk_NewsId, t.fk_NewsGroup, t.fk_NewsZone FROM tbl_test t
INNER JOIN (
SELECT fk_NewsGroup,fk_NewsZone, COUNT(*) AS Counted FROM tbl_test
GROUP BY fk_NewsGroup,fk_NewsZone
HAVING COUNT(*) > 1) g
ON t.fk_NewsGroup = g.fk_NewsGroup
AND t.fk_NewsZone = g.fk_NewsZone
DBFiddle example
I would use Group by and do it like:
select max(id) as Id, Max(fk_NewsId) as fk_NewsId, fk_NewsGroup,fk_NewsZone from #temp
group by fk_NewsGroup,fk_NewsZone
My table structure is as follows:
group_id | cust_id | ticket_num
------------------------------
60 | 12 | 1
60 | 12 | 2
60 | 12 | 3
60 | 12 | 4
60 | 30 | 5
60 | 30 | 6
60 | 31 | 7
60 | 31 | 8
65 | 02 | 1
I want to fetch all the data for group_id=60 and find the count of ticket_num for each customer in that group. My output should be like this:
cust_id | ticket_count | ticket_num
------------------------------
12 | 4 | 1
12 | | 2
12 | | 3
12 | | 4
30 | 2 | 5
30 | | 6
31 | 2 | 7
31 | | 8
I tried this query:
SELECT gd.cust_id, Count(gd.cust_id),gd.ticket_num
FROM Group_details gd
WHERE gd.group_id = 65
GROUP BY gd.cust_id;
But this query is not working.
You appear to want the ANSI/ISO standard row_number() functions and count() as a window function:
select gd.cust_id, count(*) over (partition by gd.cust_id) as num_tickets,
row_number() over (order by gd.cust_id) as ticket_seqnum
from group_details gd
where gd.group_id = 60;
use aggregate and subquery
select t2.*,t1.ticket_num from Group_details t1
inner join
(
SELECT gd.cust_id, Count(gd.ticket_num) as ticket_count
FROM Group_details gd where gd.group_id = 60
GROUP BY gd.cust_id
) t2 on t1.cust_id=t2.cust_id
http://sqlfiddle.com/#!9/dd718b/1
I have two SQL tables. Table 1 is as follows:
SALEREF
1 | 40303020
2 | 40303021
3 | 40303021
4 | 40303021
5 | 41210028
6 | 4120302701
7 | 41210030
8 | 4112700803
9 | 4112700803
10 | 41215030
11 | 41215026
12 | 41215026
13 | 41215026
14 | 41215026
15 | 41215026
16 | 41215026
17 | 41215026
18 | 41215027
19 | 41215027
20 | 41215027
Table 2 ("LEDGER") is as follows:
SALESREF SALEDATE
0 | 4081200201 | 20140804
1 | 40303020 | 20141015
2 | 40303021 | 20141017
3 | 40303021 | 20141017
4 | 40303021 | 20141017
5 | 41210028 | 20121214
6 | 4120302701 | 20130926
7 | 41210030 | 20130926
8 | 4112700803 | 20131107
9 | 4112700803 | 20131107
10 | 41215030 | 20120720
What I am looking for is a single line that outputs the following:
TotalDistinctSalesRefsInTable1 HighestSaleDateValueInTable2 (that has a matching value in table 1)
9 20141017
the total number of distinct SALESREF's in table 1 and the latest SALESDATE value from table 2.
I've tried selecting within a query but quickly found the limitation of my knowledge although I know I can get the latest overall sale date by doing:
SELECT MAX(LEDGER.SALEDATE) AS LAST_DATE FROM LEDGER
I just need help piecing the whole thing together.
you can use left join , count and max to get your desired result
select count(distinct t1.salesref) as TotalDistinctSalesRefsInTable1,
ifnull(max(l.saledate),0) as HighestSaleDateValueInTable
from table1 t1
left join ledger l
on t1.salesref = l.salesref
The question isn't very clear, but I'll illustrate what I mean, suppose my table is like such:
item_name | date added | val1 | val2
------------------------------------
1 | date+1 | 10 | 20
1 | date | 12 | 21
2 | date+1 | 5 | 6
3 | date+3 | 3 | 1
3 | date+2 | 5 | 2
3 | date | 3 | 1
And I want to select row 1, 3, 4 as they are the most recent entries for each item
Try this:
select *
from tableX t1
where t1.date_added = (select max(t2.date_added)
from tableX t2
where t2.item_name = t1.item_name )