The Software Heritage (SWH) dataset serves as a vast repository for open-source code, with the ambitious goal of preserving all publicly available open-source projects. Despite being designed to effectively archive project files, its size of nearly 1 petabyte presents challenges in efficiently supporting Big Data MapReduce or AI systems. To address this disparity and enable seamless custom analytics on the SWH dataset, we present the SWH-Analytics (SWHA) architecture. This development environment quickly and transparently runs custom analytic applications on open-source software data preserved over time by SWH.

The SWH-Analytics Framework

Alessia Antelmi
First
;
Marco Aldinucci
2023-01-01

Abstract

The Software Heritage (SWH) dataset serves as a vast repository for open-source code, with the ambitious goal of preserving all publicly available open-source projects. Despite being designed to effectively archive project files, its size of nearly 1 petabyte presents challenges in efficiently supporting Big Data MapReduce or AI systems. To address this disparity and enable seamless custom analytics on the SWH dataset, we present the SWH-Analytics (SWHA) architecture. This development environment quickly and transparently runs custom analytic applications on open-source software data preserved over time by SWH.
2023
The 2nd Italian Conference on Big Data and Data Science
Napoli, Italy
11-13 Settembre 2023
The 2nd Italian Conference on Big Data and Data Science (ITADATA 2023)
CEUR-WS
1
6
https://ceur-ws.org/Vol-3606/paper76.pdf
Software Heritage, Open-source Software, Large-scale analytics, License management
Alessia Antelmi, Massimo Torquati, Daniele Gregori, Francesco Polzella, Gianmarco Spinatelli, Marco Aldinucci
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1949562
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