Sum of values from 3rd previous month - sql

Question

I'm having difficulty grabbing rows from December (anything from the 3rd previous month). I'm attempting to count the amount of products sold within a certain time period. This is my current query:
SELECT
a.id,
a.default_code,
(
SELECT SUM(product_uom_qty)
AS
"Total Sold"
FROM
sale_order_line c
WHERE
c.product_id = a.id
),
(
SELECT SUM(product_uom_qty)
AS
"Month 3"
FROM sale_order_line c
WHERE
c.product_id = a.id
AND
MONTH(c.create_date) = MONTH(CURRENT_DATE - INTERVAL '3 Months')
AND
YEAR(c.create_date) = YEAR(CURRENT_DATE - INTERVAL '3 Months')
)
FROM
product_product a
This is what the DB looks like:
sale_order_line
product_id product_uom_qty create_date
33 230 2014-07-01 16:47:45.294313
product_product
id default_code
33 WHDXEB33
Here's the error I'm receiving:
ERROR: function month(timestamp without time zone) does not exist
LINE 21: MONTH(c.create_date) = MONTH(CURRENT_DATE - INTERVAL
Any help pointing me in the right direction?

Answer 1

Use date_trunc() to calculate timestamp bounds:
SELECT id, default_code
, (SELECT SUM(product_uom_qty)
FROM sale_order_line c
WHERE c.product_id = a.id
) AS "Total Sold"
, (SELECT SUM(product_uom_qty)
FROM sale_order_line c
WHERE c.product_id = a.id
AND c.create_date >= date_trunc('month', now()) - interval '2 month'
AND c.create_date < date_trunc('month', now()) - interval '1 month'
) AS "Month 3"
FROM product_product a;
To get December (now being February), use these expressions:
AND c.create_date >= date_trunc('month', now()) - interval '2 month'
AND c.create_date < date_trunc('month', now()) - interval '1 month'
date_trunc('month', now()) yields '2015-02-01 00:00', after subtracting 2 months, you get '2014-12-01 00:00'. So, "3 months" can be deceiving.
Also, be sure to use sargable expressions like demonstrated for faster performance and to allow index usage.
Alternatives
Depending on your actual DB design and data distribution, this may be faster:
SELECT a.id, a.default_code, c."Total Sold", c."Month 3"
FROM product_product a
LEFT JOIN (
SELECT product_id AS id
, SUM(product_uom_qty) AS "Total Sold"
, SUM(CASE WHEN c.create_date >= date_trunc('month', now()) - interval '2 month'
AND c.create_date < date_trunc('month', now()) - interval '1 month'
THEN product_uom_qty ELSE 0 END) AS "Month 3"
FROM sale_order_line
GROUP BY 1
) c USING (id);
Since you are selecting all rows, this is probably faster than correlated subqueries. While being at it, aggregate before you join, that's cheaper, yet.
When selecting a single or few products, this may actually be slower, though! Compare:
Aggregate a single column in query with many columns
Optimize GROUP BY query to retrieve latest record per user
Or with the FILTER clause in Postgres 9.4+:
...
, SUM(product_uom_qty)
FILTER (WHERE c.create_date >= date_trunc('month', now()) - interval '2 month'
AND c.create_date < date_trunc('month', now()) - interval '1 month'
) AS "Month 3"
...
Details:
Select multiple row values into single row with multi-table clauses

Answer 2

This will avoid the costly correlated subquery
select
pp.id, pp.default_code,
sum(sol.product_uom_qty) as "Total Sold",
sum((
date_trunc('month', pp.create_date) =
date_trunc('month', current_date) - interval '3 months'
)::int * sol.product_uom_qty
) as "Month 3"
from
product_product pp
left join
sale_order_line sol on pp.id = sol.product_id
group by 1, 2
The cast from boolean to integer results in 0 or 1 which is convenient to be multiplied by the value to be summed