Sql Server iterative select/update

I have table with storage. There is 20 columns for "amount" which can be zero or greater (can not be null).

IDCity | Amount0 | Amount1 | ... Amount19
---------------------------------------------------
ABC    |      25 |       7 | ...
...          ...       ...   ...
XYZ    |      10 |       6 | ...

And table for consumption & production. There is 20 columns for input "amount" a 20 columns for "output" amount. The "OrderNumber" column has values from 1 to "N". The values are continuous.

IDCity | OrderNumber | InAmount0 | InAmount1 | OutAmount0 | OutAmount1 | ...
----------------------------------------------------------------------------
ABC    |           1 |         0 |         0 |         10 |          0 | ...
ABC    |           2 |        30 |         0 |          0 |         16 | ...
ABC    |           3 |         0 |        14 |          7 |          0 | ...
...
XYZ    |           1 |         0 |         9 |         21 |          0 | ...
XYZ    |           2 |         9 |         0 |          0 |         19 | ...
XYZ    |           3 |         2 |         0 |          0 |          4 | ...
...

I need iterate the rows in "consumption & production" and update the amounts in storage in every city. I开发者_JAVA技巧 want decrease values by "InAmount" columns and increment values by "OutAmount" columns.

However if InAmount1 < Amount1 OR InAmount2 < Amount2 OR ... the row must be ignored.

The results from sample should be:

IDCity | Amount0 | Amount1 | ... Amount19
---------------------------------------------------
ABC    |      12 |       9 | ...
...          ...       ...   ...
XYZ    |       1 |      25 | ...

The row "XYZ - 1" is ignored because InAmount1 = 9 AND Amount1 = 6 => input is greater than storage.

The row "XYZ - 3" is ignored because InAmount0 = 2 AND Amount0 = 10 - 9 = 1 => input is greater than storage.

I need results fast, but I can allocate a lot of memory. The average row count will be ~10K in storage table and ~25K in consumption&production table.

I guess the CTE will be the right solution, but I didn't be able do it right.

EDIT: The source data can be available in key-value form:

Storage table:

IDCity | Kind | Amount
ABC    |    0 |     25
ABC    |    1 |      7
...
XYZ    |    0 |     10
XYZ    |    1 |     6

Consumption & production table:

IDCity | OrderNumber | InKind1 | InAmount1 | InKind2 | InAmount2 | OutKind | OutAmount
ABC    |           1 |    NULL |      NULL |    NULL |      NULL |       0 |        10
ABC    |           2 |       0 |        30 |    NULL |      NULL |       1 |        16
ABC    |           3 |       1 |        14 |    NULL |      NULL |       0 |         7
...