1570. Dot Product of Two Sparse Vectors

https://leetcode.com/problems/dot-product-of-two-sparse-vectors

Description

Given two sparse vectors, compute their dot product.

Implement class SparseVector:

• SparseVector(nums) Initializes the object with the vector nums

• dotProduct(vec) Compute the dot product between the instance of SparseVector and vec

A sparse vector is a vector that has mostly zero values, you should store the sparse vector efficiently and compute the dot product between two SparseVector.

**Follow up:**What if only one of the vectors is sparse?

Example 1:

**Input:** nums1 = [1,0,0,2,3], nums2 = [0,3,0,4,0]
**Output:** 8
**Explanation:** v1 = SparseVector(nums1) , v2 = SparseVector(nums2)
v1.dotProduct(v2) = 1*0 + 0*3 + 0*0 + 2*4 + 3*0 = 8

Example 2:

**Input:** nums1 = [0,1,0,0,0], nums2 = [0,0,0,0,2]
**Output:** 0
**Explanation:** v1 = SparseVector(nums1) , v2 = SparseVector(nums2)
v1.dotProduct(v2) = 0*0 + 1*0 + 0*0 + 0*0 + 0*2 = 0

Example 3:

**Input:** nums1 = [0,1,0,0,2,0,0], nums2 = [1,0,0,0,3,0,4]
**Output:** 6

Constraints:

• n == nums1.length == nums2.length

• 1 <= n <= 10^5

• 0 <= nums1[i], nums2[i] <= 100

ac

class SparseVector {
    private Map<Integer, Integer> indexToVal = new HashMap<>();
    
    SparseVector(int[] nums) {
        for (int i = 0; i < nums.length; i++) {
            if (nums[i] == 0) continue;
            indexToVal.put(i, nums[i]);
        }
    }
    
	// Return the dotProduct of two sparse vectors
    public int dotProduct(SparseVector vec) {
        if (vec.getValueSize() < indexToVal.size()) {
            return vec.dotProduct(this);
        }
        
        Map<Integer, Integer> other = vec.getValues();
        
        int sum = 0;
        for (int k : indexToVal.keySet()) {
            if (other.containsKey(k)) {
                sum += indexToVal.get(k) * other.get(k);
            }
        }
        
        return sum;
    }
    
    public Map<Integer, Integer> getValues() {
        return indexToVal;
    }
    
    public int getValueSize() {
        return indexToVal.size();
    }
}

// Your SparseVector object will be instantiated and called as such:
// SparseVector v1 = new SparseVector(nums1);
// SparseVector v2 = new SparseVector(nums2);
// int ans = v1.dotProduct(v2);