Yedalog: Exploring Knowledge at Scale
Venue
1st Summit on Advances in Programming Languages (SNAPL 2015), Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, pp. 63-78
Publication Year
2015
Authors
Brian Chin, Daniel von Dincklage, Vuk Ercegovac, Peter Hawkins, Mark S. Miller, Franz Och, Chris Olston, Fernando Pereira
BibTeX
Abstract
With huge progress on data processing frameworks, human programmers are frequently
the bottleneck when analyzing large repositories of data. We introduce Yedalog, a
declarative programming language that allows programmers to mix data-parallel
pipelines and computation seamlessly in a single language. By contrast, most
existing tools for data-parallel computation embed a sublanguage of data-parallel
pipelines in a general-purpose language, or vice versa. Yedalog extends Datalog,
incorporating not only computational features from logic programming, but also
features for working with data structured as nested records. Yedalog programs can
run both on a single machine, and distributed across a cluster in batch and
interactive modes, allowing programmers to mix different modes of execution easily.
