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Efficient GitHub Crawling Using the GraphQL API

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Computational Science and Its Applications – ICCSA 2022 Workshops (ICCSA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13381))

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Abstract

The number of publicly accessible software repositories on online platforms is growing rapidly. With more than 128 million public repositories (as of March 2020), GitHub is the world’s largest platform for hosting and managing software projects. Where it used to be necessary to merge various data sources, it is now possible to access a wealth of data using the GitHub API alone. However, collecting and analyzing this data is not an easy endeavor. In this paper, we present Prometheus, a system for crawling and storing software repositories from GitHub. Compared to existing frameworks, Prometheus follows an event-driven microservice architecture. By separating functionality on the service level, there is no need to understand implementation details or use existing frameworks to extend or customize the system, only data. Prometheus consists of two components, one for fetching GitHub data and one for data storage which serves as a basis for future functionality. Unlike most existing crawling approaches, the Prometheus fetching service uses the GitHub GraphQL API. As a result, Prometheus can significantly outperform alternatives in terms of throughput in some scenarios.

We want to thank the anonymous reviewers for their valuable feedback to improve this article. This work is part of the “Software-DNA” project, which is funded by the European Regional Development Fund (ERDF or EFRE in German) and the State of Brandenburg (ILB). This work is part of the KMU project “KnowhowAnalyzer” (Förderkennzeichen 01IS20088B), which is funded by the German Ministry for Education and Research (Bundesministerium für Bildung und Forschung).

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Authors and Affiliations

  1. Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Potsdam, Germany

    Adrian Jobst, Daniel Atzberger, Tim Cech, Willy Scheibel, Matthias Trapp & Jürgen Döllner

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  1. Adrian Jobst
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Correspondence to Adrian Jobst .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Østfold University College, Halden, Norway

    Sanjay Misra

  4. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  5. University of Cagliari, Cagliari, Italy

    Chiara Garau

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Jobst, A., Atzberger, D., Cech, T., Scheibel, W., Trapp, M., Döllner, J. (2022). Efficient GitHub Crawling Using the GraphQL API. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13381. Springer, Cham. https://doi.org/10.1007/978-3-031-10548-7_48

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  • DOI: https://doi.org/10.1007/978-3-031-10548-7_48

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