Searching for indices of rows in a matrix with 10 million rows

I have a matrix with few million unique rows (let's call the number of rows n) and 7 columns. Each row respresents an ID and is (directionally) related to another ~ 10 rows. The relation is specified through some known operation on the row. I want to end up with a matrix with two columns where each row contains the indices of the rows in the original matrix which are related. However, this needs ~(n x 10) lookups in a matrix of size n which makes things pretty slow. I tried using hashmaps (quite uninitiated there) but MATLAB won't let me create a cell of size n which I intend to use as a set of keys. Is there a way to do this? Below is a representative example showing the input and desired output.

Input matrix:

[ 1 1 0;

0 1 1;

0 0 2;

1 0 1]

and let's assume (1 1 0) is related to (0 1 1) and (0 1 1), (0 1 1) to (0 0 2), (0 0 2) to (1 1 0) and (1 0 1) to (0 0 2).

The output then should be

[1 2;

1 3;

2 3;

3 4;

4 1]

[Luna]

What is the relation? How did you decide (1 1 0) is related to (0 1 1) and (0 1 1) ?

I recommend you to read about: Tall Arrays

[Sounak Kar]

Thanks for the link, Luna. I think this is relevant but I'm particularly looking for efficient row search in tall arrays.

The relation is determined by a given rule. In this case, I just know that (i, j, k) is related to (i-1, j, k+1) and (i, j-1, k+1) when i>0 and j>0. But I would say I'm more concerned with searching for a row in a tall array.