Blaze: Building A Foundation for Array-Oriented Computing in Python
Mark Wiebe
Matthew Rocklin
TJ Alumbaugh
Andy Terrel
Abstract
We present the motivation and architecture of Blaze, a library for
cross-backend data-oriented computation. Blaze provides a standard interface
to connect users familiar with NumPy and Pandas to other data analytics
libraries like SQLAlchemy and Spark. We motivate the use of these projects
through Blaze and discuss the benefits of standard interfaces on top of an
increasingly varied software ecosystem. We give an overview of the Blaze
architecture and then demonstrate its use on a typical problem. We use the
abstract nature of Blaze to quickly benchmark and compare the performance of a
variety of backends on a standard problem.
array programming, big data, numpy, scipy, pandas
DOI10.25080/Majora-14bd3278-00f