Vague title for a complex problem.
There are two tables with data that's linked by a unique identifier, Option ID. Table A represents when options were granted and other specific values related to these grant dates. Table B represents a date when options were exercised.
INPUT
TABLE A (Granted)
| Option ID | Service Date | Total Options | Total Value |
| 01234 | 02/01/2015 | 200 | 1,000 |
| 01234 | 02/01/2016 | 200 | 1,500 |
| 01234 | 02/01/2017 | 200 | 1,400 |
| 01234 | 02/01/2018 | 200 | 1,300 |
TABLE B (Exercised)
| Employee ID | Option ID | Exercise Date | Total Options |
| 98765 | 01234 | 05/21/2017 | 500 |
From these two tables we can see that Employee ID 98765 has been granted a total of 800 options. On 5/21/2019 we see that 500 were exercised.
The goal is to find the sum of "Total Value" from Table A related to the exercising of these 500 options.
The rules in place would be as follows:
1. Exercised options will be attributed to the earliest service dates and count forward.
2. Each option at a specific date is equal in value. 100 options for 100 value on a specific date equals a value of 1 per option.
In this case, 500 exercised options would be attributed to:
| Option ID | Date | Total | Total Value |
| 01234 | 02/01/2015 | 200 | 1,000 |
| 01234 | 02/01/2016 | 200 | 1,500 |
| 01234 | 02/01/2017 | 100 | 700 |
The sum of Total Value is equal to 3,200.
The output would be very similar to Table B except instead of showing "Total Options" it should show the value related to those options.
OUTPUT
| Employee ID | Option ID | Exercise Date | Total Value |
| 98765 | 01234 | 05/21/2017 | 3,200 |
For regular usage, the input files will contain thousands of rows of data spanning numerous Employee IDs and Options. The output would list all of the exercised options and values related to those.
