# Linear algebra in Spark

From Spark In Action

Linear algebra is a branch of mathematics focusing on vector spaces and linear operations and mappings between them expressed mainly by matrices.

Linear algebra is essential for understanding the math behind most machine-learning algorithms, so if you don’t know much about vectors and matrices.

**Matrices and vectors (MLLib DataTypes) in Spark can be manipulated locally (in the driver or executor processes) or in a distributed manner. Implementations of distributed matrices in Spark enable you to perform linear algebra operations on huge amounts of data, spanning numerous machines.** For local linear algebra operations, Spark uses the very fast Breeze and jblas libraries (and NumPy in Python), and it has its own implementations of distributed ones.
