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Do you mean a hash map for each array in N?

Well, the complexity is O(x*N) no matter what the matrix contains. what if the matrix is sparse? i.e. you don't have the check every element?
what we want to find is the array k'th from N given arrays which contains most of the elements.
An alternative solution whose worst case is O(x*N) but a lot faster for sparse matrix:
1. Create x arrays containing the values
2. Create a count array 'C' of size N.
3. for every element in the test array 't', access the x arrays and increment the count in array 'C'.
Ex:

given 5 arrays containing elements 1 to 9
arr1: 1,5,3,2 
arr2: 2,8,3,4
arr3: 4,6,2,7,1
arr4: 5,1,4
arr5: 7,8,9
testArray: 2,4,6
1. create 9 arrays
x1  x2  x3  x4  x5  x6  x7  x8  x9
1   1   1   2   1   3   3   2   5
3   2   2   3   4       5   5
4   3       4

2. create count array C of size N: [0,0,0,0,0]

3. for each element in test array count. 
    for first element '2'. access x2. increment C[x2[...]]  --> C: [1,1,1,0,0]
    next element '4', access x4 increment C[x4[...]]  -->     C: [1,2,2,1,0]
    next element '6', access x6 increment C[x6[...]]  -->     C: [1,2,3,1,0]
    max(C) --> 3 i.e. 'arr3'  is the closest to test array which is true
    so, in this case we are only accessing 7 elements from the 'x' arrays
if we do a two dimensional matrix approach then we would access 9*5 = 45 elements

Thanks.

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