https://bugzilla.wikimedia.org/show_bug.cgi?id=53485

--- Comment #14 from Alvaro <[email protected]> ---
Quim, I have already the queries to get this information. Now we need to format
it a report. You have always the last SQL database in:

http://korma.wmflabs.org/browser/data/db/

In this case, we need the reviews database so:

acs@lenovix:/tmp$ wget
http://korma.wmflabs.org/browser/data/db/reviews.mysql.7z
acs@lenovix:/tmp$ 7zr x reviews.mysql.7z 
acs@lenovix:/tmp$ mysqladmin -u root create wikimedia_gerrit
acs@lenovix:/tmp$ mysql -u root wikimedia_gerrit < reviews.mysql


And now time to play SQL:

**** Who is contributing merged code each quarter?

acs@lenovix:/tmp$ mysql -u root wikimedia_gerrit
SELECT total, name, email, quarter, year 
FROM 
 (SELECT COUNT(i.id) AS total, upeople_id, p.id, name, email, user_id,
QUARTER(submitted_on) as quarter, YEAR(submitted_on) year 
  FROM issues i, people p , people_upeople pup 
  WHERE i.submitted_by=p.id AND pup.people_id=p.id AND status='merged' 
  GROUP BY upeople_id,year,quarter ORDER BY year,quarter,total DESC
 ) t 
WHERE total>50;

With this query you get a list ordered in time for all quarters of contributors
that have merged more than 50 contributions.

We can create queries, one for each quarter, in order to get the 25 top
"mergers". But with just one query we can get the full picture.

And for organizations it is pretty similar. But in this case with this query we
get just 60 rows so it is usable without working in specific queries for each
quarter.

SELECT COUNT(i.id) AS total, c.name, QUARTER(submitted_on) as quarter,
YEAR(submitted_on) year 
FROM issues i, people p , people_upeople pup, 
     acs_cvsanaly_mediawiki_2029_1.upeople_companies upc,
acs_cvsanaly_mediawiki_2029_1.companies c
WHERE i.submitted_by=p.id AND pup.people_id=p.id 
 AND pup.upeople_id = upc.upeople_id AND upc.company_id = c.id
 AND status='merged'
GROUP BY year, quarter, c.id ORDER BY year, quarter, total DESC

Quim, I have attached to this issue the people-quarters.txt and
orgs-quarters.csv with the results of this queries.

With this results we can generate HTML tables.

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