Popular 4k columnar tables

A set of relational tables stored in a columnar format such as Apache ORC, which is particularly suited for scale-out analyses on data lakes and big data processing ecosystems such as the Hadoop environment.

Comments

This teaser dataset contains a subset of 4000 popular repositories from GitHub, GitLab.com, PyPI and Debian. The selection criteria to pick the software origins was the following:

  • The 1000 most popular GitHub projects (by number of stars)
  • The 1000 most popular GitLab.com projects (by number of stars)
  • The 1000 most popular PyPI projects (by usage statistics, according to the Top PyPI Packages database),
  • The 1000 most popular Debian packages (by "votes" according to the Debian Popularity Contest database)
Dataset size
27 GB
Export date
Teaser of
Graph export in columnar tables [2018-09-25]
S3 URL
s3://softwareheritage/graph/2019-01-28-popular-4k/parquet/
SWH Annex URL
https://annex.softwareheritage.org/public/dataset/graph/2019-01-28-popular-4k/parquet/
Deprecated
False

Download the dataset

The HTTP links point to directories listing all available files. For Amazon S3 links, you'll need to install either awscli or swh.datasets.

aws s3 cp --recursive --no-sign-request s3://softwareheritage/graph/2019-01-28-popular-4k/parquet/ 2019-01-28-popular-4k-parquet
wget --recursive --no-parent --reject "index.html*" https://annex.softwareheritage.org/public/dataset/graph/2019-01-28-popular-4k/parquet/

By accessing the datasets, you agree with the Software Heritage Ethical Charter for using the archive data, the terms of use for bulk access, and the Software Heritage principles for large language models.

To learn how to use the datasets read the documentation.

If you use these datasets for research purposes, please cite the following paper: Antoine Pietri, Diomidis Spinellis, Stefano Zacchiroli. The Software Heritage Graph Dataset: Public software development under one roof. In proceedings of MSR 2019: The 16th International Conference on Mining Software Repositories, May 2019, Montreal, Canada. Co-located with ICSE 2019. preprint, bibtex