SQL Join Inventory Count Table to Date table - mysql

Question

I have a running inventory table of different products that records the inventory count after every transaction. Transactions do not happen every day, so the table does not have a running daily count.
I need to have all dates listed for each product so that I can sum and average the counts over a period of time.
inventory
DATE ID Qty Count
2014-05-13 123 12 12
2014-05-19 123 -1 11
2014-05-28 123 -1 10
2014-05-29 123 -3 7
2014-05-10 124 5 5
2014-05-15 124 -1 4
2014-05-21 124 -1 3
2014-05-23 124 -3 0
I have a table that includes dates for a Join, but I am not sure how to make the missing dates join over multiple products.
I need the query as follows. It needs to to return the counts over the a period selected, but also include dates inbetween.
DATE ID Qty Count
2013-05-01 123 0 0
2013-05-02 123 0 0
2013-05-03 123 0 0
2013-05-04 123 0 0
2013-05-05 123 0 0
2013-05-06 123 0 0
2013-05-07 123 0 0
2013-05-08 123 0 0
2013-05-09 123 0 0
2013-05-10 123 0 0
2013-05-11 123 0 0
2013-05-12 123 0 0
2014-05-13 123 12 12
2013-05-14 123 0 12
2013-05-15 123 0 12
2013-05-16 123 0 12
2013-05-17 123 0 12
2013-05-18 123 0 12
2014-05-19 123 -1 11
2013-05-20 123 0 11
2013-05-21 123 0 11
2013-05-22 123 0 11
2013-05-23 123 0 11
2013-05-24 123 0 11
2013-05-25 123 0 11
2013-05-26 123 0 11
2013-05-27 123 0 11
2014-05-28 123 -1 10
2014-05-29 123 -3 7
2013-05-30 123 0 7
2013-05-31 123 0 7
2013-05-01 124 0 0
2013-05-02 124 0 0
2013-05-03 124 0 0
2013-05-04 124 0 0
2013-05-05 124 0 0
2013-05-06 124 0 0
2013-05-07 124 0 0
2013-05-08 124 0 0
2013-05-09 124 0 0
2014-05-10 124 5 5
2014-05-11 124 0 5
2014-05-12 124 0 5
2014-05-13 124 0 5
2014-05-14 124 0 5
2014-05-15 124 -1 4
2014-05-16 124 0 4
2014-05-17 124 0 4
2014-05-18 124 0 4
2014-05-19 124 0 4
2014-05-20 124 0 4
2014-05-21 124 -1 3
2014-05-22 124 0 3
2014-05-23 124 -3 0
2014-05-24 124 0 0
2014-05-25 124 0 0
2014-05-26 124 0 0
2014-05-27 124 0 0
2014-05-28 124 0 0
2014-05-29 124 0 0
2014-05-30 124 0 0
2014-05-31 124 0 0

Answer 1

Use inv join inv to build up at least 31 rows and construct a table of 31 days. Then join the ids, and finally the original table.
select a.d, a.id, a.qty,
if(a.id=#lastid, #count:=#count+a.qty, #count:=a.count) `count`,
#lastid:=a.id _lastid
from (
select a.d, b.id, ifnull(c.qty, 0) qty, ifnull(c.count, 0) `count`
from (
select adddate('2014-05-01', #row) d, #row:=#row+1 i
from inv a
join inv b
join (select #row := 0) c
limit 31) a
join (
select distinct id
from inv) b
left join inv c on a.d = c.date and b.id = c.id
order by b.id, a.d) a
join (select #count := 0, #lastid := 0) b;
fiddle

Answer 2

Here are the steps needed:
Get all dates between the two given dates.
Get the initial stock per ID. This is: get the first date on or after the given start date for that ID, read this record's stock and subtract its transaction quantity.
For every date get the previous stock. If there is a record for this date, then add its transaction quantity and compare the result with its stock quantity. Throw an error if values don't match. (This is because you store data redundantly; a record's quantity must equal the quantity of the previous record plus its own transaction quantity. But data can always be inconsistent, so better check it.) Show the new stock and the difference to the previous stock.
All this would typically be achieved with a recursive CTE for the dates, a derived table for all initial stocks at best using a KEEP DENSE_RANK function, and the LAG function to look into the previous record.
MySQL doesn't support recursive CTEs - or CTEs at all for that matter. You can emulate this with a big enough table and a variable.
MySQL doesn't support the KEEP DENSE_RANK function. You can work with another derived table instead to find the minimum date per ID first.
MySQL doesn't support the LAG function. You can work with a variable in MySQL instead.
Having said this, I suggest to use a programming language instead (Java, C#, PHP, whatever). You would just select the raw data with SQL, use a loop and simply do all processiong on a per record base. This is much more convenient (and readable) than building a very complex query that does all that's needed. You can do this in SQL, even MySQL; I just don't recommend it.

Answer 3

The SQL I ended up using to resolve this question used a combination of #Fabricators answer (which really was a correct answer) and my edits.
I ended up using an existing table to create the date rows instead of a cross join. The cross join had poor performance for how many products I was working with.
SELECT
POSTDATE,
IF(#PROD_ID = PRODUCT_ID, #NEW := 0, #NEW := 1) AS New_Product,
(#PROD_ID := PRODUCT_ID) AS PRODUCT_ID,
QUANTITY,
IF(#NEW = 1, #INVENTORY := QUANTITY, #INVENTORY := #INVENTORY+QUANTITY) AS 'Count'
FROM (
(
SELECT
POSTDATE,
PRODUCT_ID,
QUANTITY
FROM
inventory
)
UNION ALL
(
SELECT
dateslist_sub.TransDate AS POSTDATE,
productlist_sub.PRODUCT_ID,
0 AS QUANTITY,
FROM
(
SELECT
TransDate
FROM
(
SELECT
adddate('2013-05-01', #row) AS TransDate,
#row:=#row+1 i
FROM
any_table,
(SELECT #row := 0) row
) datestable
WHERE
TransDate <= CURDATE()
) dateslist_sub
cross join (
SELECT
PRODUCT_ID
FROM
products_table
ORDER BY
PRODUCT_ID ASC
) productlist_sub
ORDER BY
productlist_sub.PRODUCT_ID ASC,
dateslist_sub.TransDate ASC
)
ORDER BY
PRODUCT_ID ASC,
POSTDATE ASC
) daily_rows_sub