Trying to build a query to have sum on sales column by month, 3 months, 6 months, 11 months and prior year 11 months. What are possible options to go about it.
I tried datediff and date related functions didn't get intended results.
Would like some suggestions on how to go about it?
This should get you started.
CREATE TABLE sales (
product varchar (1),
month int,
amount int
)
insert into sales values ('a',1,5); insert into sales values ('a',1,33);
insert into sales values ('a',2,32); insert into sales values ('b',1,12);
insert into sales values ('b',2,4); insert into sales values ('c',1,5);
insert into sales values ('c',2,11); insert into sales values ('c',2,13);
SELECT
product,
SUM(CASE WHEN month = 1 THEN amount END) AS Month1,
SUM(CASE WHEN month = 2 THEN amount END) AS Month2
FROM
sales
GROUP BY
product
output:
product | Month1 | Month2
--------------------------------
a | 38 | 32
b | 12 | 4
c | 5 | 24
Related
I would like to show the revenue for a specific year for all customers regardless of whether or not they have revenue data for the specific year. (in cases they dont have data for the specific year, a filler like 'no data' would work)
Sample Data looks like:
Table 1
Customer
Price
Quantity
Order Date
xxx
12
5
1990/03/25
yyy
15
7
1991/05/35
xxx
34
2
1990/08/21
Desired Output would look a little something like this:
Customer
Revenue (for 1990)
xxx
128
yyy
no data
Getting the total revenue for each would be:
SELECT Customer,
SUM(quantity*price) AS Revenue
but how would i go about listing it out for a specific year for all customers? (incl. customers that dont have data for that specific year)
We can use a CTE or a sub-query to create a list of all customers and another to get all years and the cross join them and left join onto revenue.
This gives an row for each customer for each year. If you add where y= you will only get the year requested.
CREATE TABLE revenue(
Customer varchar(10),
Price int,
Quantity int,
OrderDate date);
insert into revenue values
('xxx', 12,5,'2021-03-25'),
('yyy', 15,7,'2021-05-15'),
('xxx', 34,2,'2022-08-21');
with cust as
(select distinct customer c from revenue),
years as
(select distinct year(OrderDate) y from revenue)
select
y "year",
c customer ,
sum(price*quantity) revenue
from years
cross join cust
left join revenue r
on cust.c = r.customer and years.y = year(OrderDate)
group by
c,y,
year(OrderDate)
order by y,c
year | customer | revenue
---: | :------- | ------:
2021 | xxx | 60
2021 | yyy | 105
2022 | xxx | 68
2022 | yyy | null
db<>fiddle here
You would simply use group by and do the sum in a subquery and left join it to your customers table. ie:
select customers.Name, totals.Revenue
from Customers
Left join
( select customerId, sum(quantity*price) as revenue
from myTable
where year(orderDate) = 1990
group by customer) totals on customers.CustomerId = myTable.customerId;
I have table in Oracle SQL presents ID of clients and date with time of their login to application:
ID | LOGGED
----------------
11 | 2021-07-10 12:55:13.278
11 | 2021-08-10 13:58:13.211
11 | 2021-02-11 12:22:13.364
22 | 2021-01-10 08:34:13.211
33 | 2021-04-02 14:21:13.272
I need to select only these clients (ID) who has logged minimum 1 time in last month (August) and minimum 1 time in one month preceding August (June or July)
Currently we have September, so...
I need clients who has logged min 1 time in August
and min 1 time in July or Jun,
if logged in June -> not logg in July
if logged in July -> not logged in June
As a result I need like below:
ID
----
11
How can do that in Oracle SQL ? be aware that column "LOGGED" has Timestamp like: 2021-01-10 08:34:13.211
May be you consider this:
select id
from yourtable
group by id
having count(case
months_between(trunc(sysdate,'MM'),
trunc(logged,'MM')
) when 1 then 1 end
) >= 1
and count
(case when
months_between(trunc(sysdate,'MM') ,
trunc(logged,'MM')
) in (2,3) then 1 end
) = 1
I don't understand one thing:
You wrote :
minimum 1 time in one month preceding August (June or July)
and after then:
if logged in June -> not logg in July
if logged in July -> not logged in June
If you need EXACTLY one month- June or July
just consider my query above.
If you need minimum one logon in June and July, then:
select id
from yourtable
group by id
having count(case
months_between(trunc(sysdate,'MM'),
trunc(logged,'MM')
) when 1 then 1 end
) >= 1
and count
(case when
months_between(trunc(sysdate,'MM') ,
trunc(logged,'MM')
) in (2,3) then 1 end
) >= 1
Your question needs some clarification, but based on what you were describing I am seeing a couple of options.
The simplest one is probably using a combo of data densification (for generating a row for every month for each id) plus an analytical function (for enabling inter-row calculations. Here's a simple example of this:
rem create a dummy table with some more data (you do not seem to worry about the exact timestamp)
drop table logs purge;
create table logs (ID number, LOGGED timestamp);
insert into logs values (11, to_timestamp('2021-07-10 12:55:13.278','yyyy-mm-dd HH24:MI:SS.FF'));
insert into logs values (11, to_timestamp('2021-07-11 12:55:13.278','yyyy-mm-dd HH24:MI:SS.FF'));
insert into logs values (11, to_timestamp('2021-08-10 13:58:13.211','yyyy-mm-dd HH24:MI:SS.FF'));
insert into logs values (11, to_timestamp('2021-02-11 12:22:13.364','yyyy-mm-dd HH24:MI:SS.FF'));
insert into logs values (11, to_timestamp('2021-04-11 12:22:13.364','yyyy-mm-dd HH24:MI:SS.FF'));
insert into logs values (22, to_timestamp('2021-01-10 08:34:13.211','yyyy-mm-dd HH24:MI:SS.FF'));
insert into logs values (33, to_timestamp('2021-04-02 14:21:13.272','yyyy-mm-dd HH24:MI:SS.FF'));
commit;
The following SQL gets your data densified and lists the total count of logins for a month and the previous month on the same row so that you could do a comparative calculation. I have not done then, but I am hoping you get the idea.
with t as
(-- dummy artificial table just to create a time dimension for densification
select distinct to_char(sysdate - rownum,'yyyy-mm') mon
from dual connect by level < 300),
l_sparse as
(-- aggregating your login info per month
select id, to_char(logged,'yyyy-mm') mon, count(*) cnt
from logs group by id, to_char(logged,'yyyy-mm') ),
l_dense as
(-- densification with partition outer join
select t.mon, l.id, cnt from l_sparse l partition by (id)
right outer join t on (l.mon = t.mon)
)
-- final analytical function to list current and previous row info in same record
select mon, id
, cnt
, lag(cnt) over (partition by id order by mon asc) prev_cnt
from l_dense
order by id, mon;
parts of the result:
MON ID CNT PREV_CNT
------- ---------- ---------- ----------
2020-12 11
2021-01 11
2021-02 11 2
2021-03 11 2
2021-04 11 1
2021-05 11 1
2021-06 11
2021-07 11 3
2021-08 11 2 3
2021-09 11 2
2020-12 22
2021-01 22 2
2021-02 22 2
2021-03 22
2021-04 22
...
You can see for ID 11 that for 2021-08 you have logins for the current and previous month, so you can math on it. (Would require another subselect/with branch).
Alternatives to this would be:
interrow calculation plus time math between two logged timestamps
pattern matching
Did not drill into those, not enough info about your real requirement.
I have table Quota with columns 'Month Number', 'year','Goal' as below
I have other table Sales with columns 'id', 'Sale Date' as below.
I am joining both the tables on Month and year of 'sales date' from Sales table to 'Month Number' and 'year' from Quota Table to get the results and i am able to get results if i have sales for that particular month and year.Now for the month of may i have no sales so when i join on those columns i am not getting any results from quota table. how can i just display Quota table values if there are no corresponding sales in Sales table? I tried left joining but its not displaying any results.
Like already said, we don't know your desired output. But by using a left join you should retrieve the records from the quota table.
declare #quota table (monthnumber int, qyear int, goal int)
insert into #quota values
(2,2017,5),
(3,2017,10),
(4,2017,8),
(5,2017,8),
(6,2017,10)
declare #sales table (id int, salesdate date)
insert into #sales values
(101,'20170321'),
(102,'20170427'),
(103,'20170223'),
(105,'20170427'),
(108,'20170321'),
(109,null),
(111,null)
select q.*
from #quota as q
left outer join #sales as s
on year(s.salesdate) = q.qyear and
month(s.salesdate) = q.monthnumber
Returns
monthnumber qyear goal
--------------------------
2 2017 5
3 2017 10
3 2017 10
4 2017 8
4 2017 8
5 2017 8
6 2017 10
You can use month and year of function and do left join as below
select * from Quota q left join sales s
on q.year = year(s.saledate) and q.MonthNumber = month(s.saledate)
Despite you didn't specify what output you need or your effort so far, I made my attempt anyway and I guess this is what you want:
SELECT
Q.*,
SalesCount = (SELECT COUNT(*) FROM Sales S
WHERE YEAR(S."Sale Date") = Q.Year AND MONTH(S."Sale Date") = Q.MonthNumber)
FROM Quota Q
And this is the result:
MonthNumber Year Goal SalesCount
2 2017 5 1
3 2017 10 2
4 2017 8 2
5 2017 8 0
6 2017 10 0
I have a raw table recording customer ids coming to a store over a particular time period. Using Impala, I would like to calculate the number of distinct customer IDs coming to the store until each day. (e.g., on day 3, 5 distinct customers visited so far)
Here is a simple example of the raw table I have:
Day ID
1 1234
1 5631
1 1234
2 1234
2 4456
2 5631
3 3482
3 3452
3 1234
3 5631
3 1234
Here is what I would like to get:
Day Count(distinct ID) until that day
1 2
2 3
3 5
Is there way to easily do this in a single query?
Not 100% sure if will work on impala
But if you have a table days. Or if you have a way of create a derivated table on the fly on impala.
CREATE TABLE days ("DayC" int);
INSERT INTO days
("DayC")
VALUES (1), (2), (3);
OR
CREATE TABLE days AS
SELECT DISTINCT "Day"
FROM sales
You can use this query
SqlFiddleDemo in Postgresql
SELECT "DayC", COUNT(DISTINCT "ID")
FROM sales
cross JOIN days
WHERE "Day" <= "DayC"
GROUP BY "DayC"
OUTPUT
| DayC | count |
|------|-------|
| 1 | 2 |
| 2 | 3 |
| 3 | 5 |
UPDATE VERSION
SELECT T."DayC", COUNT(DISTINCT "ID")
FROM sales
cross JOIN (SELECT DISTINCT "Day" as "DayC" FROM sales) T
WHERE "Day" <= T."DayC"
GROUP BY T."DayC"
try this one:
select day, count(distinct(id)) from yourtable group by day
I have a database in SQL Server 2012 and there is a table with dates in D.M.YYYY format like below:
ID | Date(date type) | Amount(Numeric)
1 3.4.2013 16.00
1 12.4.2013 13.00
1 2.5.2013 9.50
1 18.5.2013 10.00
I need to sum the total amount for every month in a given year. For example:
ID | Month | TotalAmount
1 1 0.00
...
1 4 29.00
1 5 19.50
I thought what I needed was to determine the number of days in a month, so I created a function which is described in determine the number of days, and it worked. After that I tried to compare two dates(date type) and got stuck; there are some examples out there, but all of them about datetime.
Is this wrong? How can I accomplish this?
I think you just want an aggregation:
select id, month(date) as "month", sum(amount) as TotalAmount
from t
where year(date) = 2013
group by id, month(date)