This process typically involved days or weeks per iteration, and errors would occur translating the algorithms to operate on big data.

A primary goal of SystemML is to automatically scale an algorithm written in an R-like or Python-like language to operate on big data, generating the same answer without the error-prone, multi-iterative translation approach.

SystemML became publicly available on GitHub on August 27, 2015 and became an Apache Incubator project on November 2, 2015.

The following code snippet[1] does the Principal component analysis of input matrix

[2] Apache SystemDS welcomes contributions in code, question and answer, community building, or spreading the word.