How to write a SQL statement to sum data using group by the same day of every two neighboring months - sql

Question

I have a data table like this:
datetime data
-----------------------
...
2017/8/24 6.0
2017/8/25 5.0
...
2017/9/24 6.0
2017/9/25 6.2
...
2017/10/24 8.1
2017/10/25 8.2
I want to write a SQL statement to sum the data using group by the 24th of every two neighboring months in certain range of time such as : from 2017/7/20 to 2017/10/25 as above.
How to write this SQL statement? I'm using SQL Server 2008 R2.
The expected results table is like this:
datetime_range data_sum
------------------------------------
...
2017/8/24~2017/9/24 100.9
2017/9/24~2017/10/24 120.2
...

Answer 1

One conceptual way to proceed here is to redefine a "month" as ending on the 24th of each normal month. Using the SQL Server month function, we will assign any date occurring after the 24th as belonging to the next month. Then we can aggregate by the year along with this shifted month to obtain the sum of data.
WITH cte AS (
SELECT
data,
YEAR(datetime) AS year,
CASE WHEN DAY(datetime) > 24
THEN MONTH(datetime) + 1 ELSE MONTH(datetime) END AS month
FROM yourTable
)
SELECT
CONVERT(varchar(4), year) + '/' + CONVERT(varchar(2), month) +
'/25~' +
CONVERT(varchar(4), year) + '/' + CONVERT(varchar(2), (month + 1)) +
'/24' AS datetime_range,
SUM(data) AS data_sum
FROM cte
GROUP BY
year, month;
Note that your suggested ranges seem to include the 24th on both ends, which does not make sense from an accounting point of view. I assume that the month includes and ends on the 24th (i.e. the 25th is the first day of the next accounting period.
Demo

Answer 2

I would suggest dynamically building some date range rows so that you can then join you data to those for aggregation, like this example:
+----+---------------------+---------------------+----------------+
| | period_start_dt | period_end_dt | your_data_here |
+----+---------------------+---------------------+----------------+
| 1 | 24.04.2017 00:00:00 | 24.05.2017 00:00:00 | 1 |
| 2 | 24.05.2017 00:00:00 | 24.06.2017 00:00:00 | 1 |
| 3 | 24.06.2017 00:00:00 | 24.07.2017 00:00:00 | 1 |
| 4 | 24.07.2017 00:00:00 | 24.08.2017 00:00:00 | 1 |
| 5 | 24.08.2017 00:00:00 | 24.09.2017 00:00:00 | 1 |
| 6 | 24.09.2017 00:00:00 | 24.10.2017 00:00:00 | 1 |
| 7 | 24.10.2017 00:00:00 | 24.11.2017 00:00:00 | 1 |
| 8 | 24.11.2017 00:00:00 | 24.12.2017 00:00:00 | 1 |
| 9 | 24.12.2017 00:00:00 | 24.01.2018 00:00:00 | 1 |
| 10 | 24.01.2018 00:00:00 | 24.02.2018 00:00:00 | 1 |
| 11 | 24.02.2018 00:00:00 | 24.03.2018 00:00:00 | 1 |
| 12 | 24.03.2018 00:00:00 | 24.04.2018 00:00:00 | 1 |
+----+---------------------+---------------------+----------------+
DEMO
declare #start_dt date;
set #start_dt = '20170424';
select
period_start_dt, period_end_dt, sum(1) as your_data_here
from (
select
dateadd(month,m.n,start_dt) period_start_dt
, dateadd(month,m.n+1,start_dt) period_end_dt
from (
select #start_dt start_dt ) seed
cross join (
select 0 n union all
select 1 union all
select 2 union all
select 3 union all
select 4 union all
select 5 union all
select 6 union all
select 7 union all
select 8 union all
select 9 union all
select 10 union all
select 11
) m
) r
-- LEFT JOIN YOUR DATA
-- ON yourdata.date >= r.period_start_dt and data.date < r.period_end_dt
group by
period_start_dt, period_end_dt
Please don't be tempted to use "between" when it comes to joining to your data. Follow the note above and use yourdata.date >= r.period_start_dt and data.date < r.period_end_dt otherwise you could double count information as between is inclusive of both lower and upper boundaries.

Answer 3

I think the simplest way is to subtract 25 days and aggregate by the month:
select year(dateadd(day, -25, datetime)) as yr,
month(dateadd(day, -25, datetime)) as mon,
sum(data)
from t
group by dateadd(day, -25, datetime);
You can format yr and mon to get the dates for the specific ranges, but this does the aggregation (and the yr/mon columns might be sufficient).

Answer 4

Step 0: Build a calendar table. Every database needs a calendar table eventually to simplify this sort of calculation.
In this table you may have columns such as:
Date (primary key)
Day
Month
Year
Quarter
Half-year (e.g. 1 or 2)
Day of year (1 to 366)
Day of week (numeric or text)
Is weekend (seems redundant now, but is a huge time saver later on)
Fiscal quarter/year (if your company's fiscal year doesn't start on Jan. 1)
Is Holiday
etc.
If your company starts its month on the 24th, then you can add a "Fiscal Month" column that represents that.
Step 1: Join on the calendar table
Step 2: Group by the columns in the calendar table.
Calendar tables sound weird at first, but once you realize that they are in fact tiny even if they span a couple hundred years they quickly become a major asset.
Don't try to cheap out on disk space by using computed columns. You want real columns because they are much faster and can be indexed if necessary. (Though honestly, usually just the PK index is enough for even wide calendar tables.)