Here's some sample data from my table:
day_number daily_users_count
1 1
3 1
6 1
7 1
9 2
10 2
I need all day_number values, from 1 to max(day_number), and I want daily_users_count to be zero if it isn't mentioned in this table.
It should look something like this:
day_number daily_users_count
1 1
2 0
3 1
4 0
5 0
6 1
7 1
8 0
9 2
10 2
I think a left join with a table which has a number column with all integers from 1 to max(day_number) would work, if I put a default value for daily_users_count as 0.
What I don't get is how to create such a table where all integers within a certain range are present. Any alternate solutions or any ways to do this would be much appreciated.
You can do it with a recursive CTE which will return all the day_numbers including the missing ones and then a LEFT join to the table:
with cte as (
select min(day_number) day_number from tablename
union all
select day_number + 1 from cte
where day_number < (select max(day_number) from tablename)
)
select c.day_number,
coalesce(t.daily_users_count, 0) daily_users_count
from cte c left join tablename t
on t.day_number = c.day_number
See the demo.
Results:
| day_number | daily_users_count |
| ---------- | ----------------- |
| 1 | 1 |
| 2 | 0 |
| 3 | 1 |
| 4 | 0 |
| 5 | 0 |
| 6 | 1 |
| 7 | 1 |
| 8 | 0 |
| 9 | 2 |
| 10 | 2 |
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
I have below table where column names are Item, Point and IsCorrect.
Item | Point | IsCorrect | Not actual column, just logic
-----+-------+-----------+--------------------
1 | 5 | 0 | 5 >= 6
1 | 8 | 0 | 8 >= 6
1 | 9 | 0 | 9 >= 6
1 | 6 | 1 | 6 >= 6
2 | 8 | 0 | 8 >= 7
2 | 7 | 1 | 7 >= 7
2 | 8 | 0 | 8 >= 7
2 | 9 | 0 | 9 >= 7
3 | 2 | 0 | 2 >= 9
3 | 5 | 0 | 5 >= 9
3 | 8 | 0 | 8 >= 9
3 | 9 | 1 | 9 >= 9
I want to first group by Item, get a Point value where IsCorrect = 1, compare it with other point values (as shown in 4th column). If all condition matched within a group, then select that item. I am expecting following result.
Item | Point | IsCorrect
-----+-------+----------
2 | 8 | 0
2 | 7 | 1
2 | 8 | 0
2 | 9 | 0
I want to use partition, not group by. Thank you so much for your help.
Window functions come to mind:
select t.*
from (select t.*,
max(case when iscorrect = 1 then point end) over (partition by item) as point_correct,
min(point) over (partition by item) as min_point
from t
) t
where min_point >= point_correct;
You could also do this with a subquery. Something like this:
select t.*
from t
where t.item in (select t2.item
from t t2
group by t2.item
having min(t2.point) >= min(case when t2.iscorrect then point end)
);
That is, for each item, compare the minimum point value to the "correct" point value.
I wish SQL for SUM each column(IPO and UOR) in TOTAL in second last. And GRAND TOTAL(Sum IPO + UOR) in the last one. Thank you so much
No Code IPO UOR
----------------------
1 D173 1 0
2 D176 3 0
3 D184 1 1
4 D185B 1 0
5 D187 1 2
6 F042 3 0
7 ML004 12 3
8 TTPMC 2 0
9 Z00204 1 0
------------------
TOTAL (NOS) 25 6
-------------------------
GRAND TOTAL (NOS) 31
Here is my code, :
SELECT
SUM(CASE WHEN IPOType = 'IPO' THEN 1 ELSE 0 END) as IPO,
SUM(CASE WHEN IPOType = 'UOR' THEN 1 ELSE 0 END) as UOR
FROM IPO2018
GROUP BY OriProjNo
it can show like this
No Code IPO UOR
----------------------
1 D173 1 0
2 D176 3 0
3 D184 1 1
4 D185B 1 0
5 D187 1 2
6 F042 3 0
7 ML004 12 3
8 TTPMC 2 0
9 Z00204 1 0
------------------
Generally speaking, you want to leave totals and sub-totals to whatever tool you are presenting your data in, as they will be able to handle the formatting with significantly more ease. In addition, your desired output does not have the same number of columns (Grand Total row only has one numeric) so even if you did shoehorn this in to the same dataset, the column headings wouldn't make sense.
That said, you can return group totals via the with rollup statement. This will provide an additional row with the aggregate totals for the group. Where there is more than one group in your data, you will get a sub-total row for each group and a total row for the entire dataset:
declare #t table(c nvarchar(10),t nvarchar(3));
insert into #t values ('D173','IPO'),('D176','IPO'),('D176','IPO'),('D176','IPO'),('D184','IPO'),('D184','UOR'),('D185B','IPO'),('D187','IPO'),('D187','UOR'),('D187','UOR'),('F042','IPO'),('F042','IPO'),('F042','IPO'),('TTPMC','IPO'),('TTPMC','IPO'),('Z00204','IPO'),('ML004','UOR'),('ML004','UOR'),('ML004','UOR'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO'),('ML004','IPO');
select row_number() over (order by grouping(c),c) as n
,case when grouping(c) = 1 then 'TOTAL (NOS)' else c end as c
,sum(case when t = 'IPO' then 1 else 0 end) as IPO
,sum(case when t = 'UOR' then 1 else 0 end) as UOR
from #t
group by c
with rollup
order by grouping(c)
,c;
Output:
+----+-------------+-----+-----+
| n | c | IPO | UOR |
+----+-------------+-----+-----+
| 1 | D173 | 1 | 0 |
| 2 | D176 | 3 | 0 |
| 3 | D184 | 1 | 1 |
| 4 | D185B | 1 | 0 |
| 5 | D187 | 1 | 2 |
| 6 | F042 | 3 | 0 |
| 7 | ML004 | 12 | 3 |
| 8 | TTPMC | 2 | 0 |
| 9 | Z00204 | 1 | 0 |
| 10 | TOTAL (NOS) | 25 | 6 |
+----+-------------+-----+-----+
I have a theoretical question, so I'm not interested in alternative solutions. Sorry.
Q: Is it possible to get the window running function values for all previous rows, except current?
For example:
with
t(i,x,y) as (
values
(1,1,1),(2,1,3),(3,1,2),
(4,2,4),(5,2,2),(6,2,8)
)
select
t.*,
sum(y) over (partition by x order by i) - y as sum,
max(y) over (partition by x order by i) as max,
count(*) filter (where y > 2) over (partition by x order by i) as cnt
from
t;
Actual result is
i | x | y | sum | max | cnt
---+---+---+-----+-----+-----
1 | 1 | 1 | 0 | 1 | 0
2 | 1 | 3 | 1 | 3 | 1
3 | 1 | 2 | 4 | 3 | 1
4 | 2 | 4 | 0 | 4 | 1
5 | 2 | 2 | 4 | 4 | 1
6 | 2 | 8 | 6 | 8 | 2
(6 rows)
I want to have max and cnt columns behavior like sum column, so, result should be:
i | x | y | sum | max | cnt
---+---+---+-----+-----+-----
1 | 1 | 1 | 0 | | 0
2 | 1 | 3 | 1 | 1 | 0
3 | 1 | 2 | 4 | 3 | 1
4 | 2 | 4 | 0 | | 0
5 | 2 | 2 | 4 | 4 | 1
6 | 2 | 8 | 6 | 4 | 1
(6 rows)
It can be achieved using simple subquery like
select t.*, lag(y,1) over (partition by x order by i) as yy from t
but is it possible using only window function syntax, without subqueries?
Yes, you can. This does the trick:
with
t(i,x,y) as (
values
(1,1,1),(2,1,3),(3,1,2),
(4,2,4),(5,2,2),(6,2,8)
)
select
t.*,
sum(y) over w as sum,
max(y) over w as max,
count(*) filter (where y > 2) over w as cnt
from t
window w as (partition by x order by i
rows between unbounded preceding and 1 preceding);
The frame_clause selects just those rows from the window frame that you are interested in.
Note that in the sum column you'll get null rather than 0 because of the frame clause: the first row in the frame has no row before it. You can coalesce() this away if needed.
SQLFiddle
My objective is to make dynamic group of lines (of product by TYPE & COLOR in fact)
I don't know if it's possible just with one select query.
But : I want to create group of lines (A PRODUCT is a TYPE and a COLOR) as per the number_per_group column and I want to do this grouping depending on the date order (Order By DATE)
A single product with a NB_PER_GROUP number 2 is exclude from the final result.
Table :
-----------------------------------------------
NUM | TYPE | COLOR | NB_PER_GROUP | DATE
-----------------------------------------------
0 | 1 | 1 | 2 | ...
1 | 1 | 1 | 2 |
2 | 1 | 2 | 2 |
3 | 1 | 2 | 2 |
4 | 1 | 1 | 2 |
5 | 1 | 1 | 2 |
6 | 4 | 1 | 3 |
7 | 1 | 1 | 2 |
8 | 4 | 1 | 3 |
9 | 4 | 1 | 3 |
10 | 5 | 1 | 2 |
Results :
------------------------
GROUP_NUMBER | NUM |
------------------------
0 | 0 |
0 | 1 |
~~~~~~~~~~~~~~~~~~~~~~~~
1 | 2 |
1 | 3 |
~~~~~~~~~~~~~~~~~~~~~~~~
2 | 4 |
2 | 5 |
~~~~~~~~~~~~~~~~~~~~~~~~
3 | 6 |
3 | 8 |
3 | 9 |
If you have another way to solve this problem, I will accept it.
What about something like this?
select max(gn.group_number) group_number, ip.num
from products ip
join (
select date, type, color, row_number() over (order by date) - 1 group_number
from (
select op.num, op.type, op.color, op.nb_per_group, op.date, (row_number() over (partition by op.type, op.color order by op.date) - 1) % nb_per_group group_order
from products op
) sq
where sq.group_order = 0
) gn
on ip.type = gn.type
and ip.color = gn.color
and ip.date >= gn.date
group by ip.num
order by group_number, ip.num
This may only work if your nb_per_group values are the same for each combination of type and color. It may also require unique dates, but that could probably be worked around if required.
The innermost subquery partitions the rows by type and color, orders them by date, then calculates the row numbers modulo nb_per_group; this forms a 0-based count for the group that resets to 0 each time nb_per_group is exceeded.
The next-level subquery finds all of the 0 values we mapped in the lower subquery and assigns group numbers to them.
Finally, the outermost query ties each row in the products table to a group number, calculated as the highest group number that split off before this product's date.