On The Soundness of a Language for Large and Distributed Graph Processing
Alpha Mouhamadou Diop, Cheikh BA · 2024
Data in the form of graph become very omnipresent. When this mass of data is very voluminous, the most common solution is the use of a cluster of machines, for a distributed storage and a parallel processing. Several platforms exist and can help in transparently processing these distributed data. But their programming paradigms are still low level. In this work, we depend on a graph rewriting based language - initially designed for non-distributed graphs - and we show how to translate its constructs into low-level platforms. The set of constructs of this language is minimal and can compute any computable program on graphs, hence it is sufficient to guarantee the soundness of our proposal.