data mapping is used to map complex data into a single value
the idea is if an object has complet data to process, like (object, value1, value2, value3,value4....), we can mapping (object, value1, value2, value3,value4....) into a single value X, then we process only X to make it faster
here is an use case:
we have two 2D data arrays with 5 columns, the first column is the name of object, the other fours are the differents value of this object
Data ArrayA:
| object | value1 | value2 | value3 | value4 |
| ------ | ------ | ------ | ------ | ------ |
| X | 1 | 2 | 3 | 4 |
| Y | 5 | 6 | 7 | 8 |
| Z | 9 | 10 | 11 | 12 |
Data ArrayB:
| object | value1 | value2 | value3 | value4 |
| ------ | ------ | ------ | ------ | ------ |
| X | 1 | 2 | 3 | 4 |
| Y | 5 | 8 | 7 | 8 |
| Z | 9 | 10 | 192 | 12 |
now we need to compare data array A to data array B to find which object inside A has different value.
without data mapping, we need to compare each object's 4 values, the complexity is O(2^n)
with data mapping:
we map those values:
(X, 1, 2, 3, 4) ==> 1
(Y, 5, 6, 7, 8) ==> 2
(Z, 9, 10, 11,12) ==>3
(Y, 5, 8, 7, 8) ==> 4
(Z, 9, 10, 192, 12) ==> 5
Data ArrayA:
| object |
| ------ |
| 1 |
| 2 |
| 3 |
Data ArrayB:
| object |
| ------ |
| 1 |
| 4 |
| 5 |
then compare 1D array is fast, the complexity is O(n)
