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Grokking the Coding Interview Patterns in Python

Solution: Dot Product of Two Sparse Vectors

Explore how to calculate the dot product of two sparse vectors by implementing a SparseVector class that stores only nonzero elements using hash maps. Understand the method to multiply matching nonzero elements to achieve efficient computation. This lesson helps you grasp the time and space complexity benefits of this approach while practicing an important pattern for coding interviews.

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Statement

We must calculate the dot product of two given sparse vectors, nums1 and nums2.

Create a SparseVector class:

  • Constructor(): Initializes the object with the vector.

  • DotProduct(): Computes the dot product between the current instance of the vector and the other.

Note: A sparse vector is a vector that contains mostly zero values. Therefore, we should store the sparse vectors and calculate the dot product accordingly.

Constraints:

  • n==n == nums1.length ==== nums2.length

  • ...