The GitHub Archive dataset was updated as well. Example BigQuery to get the Top Repositories from 2015-2016 YTD, by the number of Stars given during that time:
SELECT repo.id, repo.name, COUNT(*) as num_stars
FROM TABLE_DATE_RANGE([githubarchive:day.], TIMESTAMP('2015-01-01'), TIMESTAMP('2016-12-31'))
WHERE type = "WatchEvent"
GROUP BY repo.id, repo.name
ORDER BY num_stars DESC
LIMIT 1000
SELECT
CONCAT("https://github.com/",repo_name,"/blob/master/",path) AS file_url,
FROM
[bigquery-public-data:github_repos.files]
WHERE
id IN (SELECT id FROM [bigquery-public-data:github_repos.contents]
WHERE NOT binary AND LOWER(content) CONTAINS 'easter egg')
and path not like "%.csv"
GROUP BY 1
LIMIT 1000
36s elapsed, 1.79 TB (so not free). Using github_repos.sample_files and github_repos.sample_contents only costs 31 GB (free) but not as many easter eggs :)
Since the query only hits 3 columns, it only uses 15.4GB of data (out of a 1TB allowance)
More information on the GitHub Archive changes: https://medium.com/@hoffa/github-archive-fully-updated-notic...