Before understanding vectors, let's focus on what a point is. A point is just a set of numbers. This set of numbers or coordinates defines the point's position in space. The number of coordinates determines the dimensions of the space.
We can visualize space with up to three dimensions. A space with more than three dimensions is called hyperspace. Let's put this spatial metaphor to use.
Let's start with a house. A house may have the following dimensions:
- Area
- Lot size
- Number of rooms
We are working in three-dimensional space here. Thus, the interpretation of point (4500, 41000, 4) would be 4500 sq. ft area, 41k sq. ft lot size, and four rooms.
Points and vectors are the same thing. Dimensions in vectors are called features. In another way, we can define a feature as an individual measurable property of a phenomenon being observed.
Spark has local vectors and matrices and also distributed matrices. A distributed matrix is backed by one or more RDDs. A local vector has...