Sparse Matrix Multiplication

Given two sparse matrices A and B, return the result of AB.

You may assume that A's column number is equal to B's row number.

Example:

A = [
  [ 1, 0, 0],
  [-1, 0, 3]
]

B = [
  [ 7, 0, 0 ],
  [ 0, 0, 0 ],
  [ 0, 0, 1 ]
]

     |  1 0 0 |   | 7 0 0 |   |  7 0 0 |
AB = | -1 0 3 | x | 0 0 0 | = | -7 0 3 |
                  | 0 0 1 |

 1 public class Solution {
 2     public int[][] multiply(int[][] A, int[][] B) {
 3         int m = A.length, n = A[0].length, nB = B[0].length;
 4         int[][] C = new int[m][nB];
 5
 6         for (int row = 0; row < m; row++) {
 7             for (int col = 0; col < n; col++) {
 8                 if (A[row][col] != 0) {
 9                     for (int j = 0; j < nB; j++) {
10                         if (B[col][j] != 0) {
11                             C[row][j] += A[row][col] * B[col][j];
12                         }
13                     }
14                 }
15             }
16         }
17         return C;
18     }
19 }

 public class Solution {
     public int[][] multiply(int[][] A, int[][] B) {
         if (A == null || A[] == null || B == null || B[] == null) return null;
         int rowA = A.length, colA = A[].length, colB = B[].length;
         int[][] C = new int[rowA][colB];

         //Map<row, Map<col, val>>
         Map<Integer, Map<Integer, Integer>> tableB = new HashMap<>();

         // For each row in matrix B, if there is a non-zero value, put it in the hashMap.
         for (int row = ; row < colA; row++) {
             tableB.put(row, new HashMap<Integer, Integer>());
             for (int col = ; col < colB; col++) {
                 if (B[row][col] != ) {
                     tableB.get(row).put(col, B[row][col]);
                 }
             }
         }

         for (int row = ; row < rowA; row++) {
             for (int col = ; col < colA; col++) {
                 if (A[row][col] != ) {
                     for (Integer j : tableB.get(col).keySet()) {
                         C[row][j] += A[row][col] * tableB.get(col).get(j);
                     }
                 }
             }
         }
         return C;
     }
 }