On Fri, May 3, 2013 at 5:39 AM, Nilesh Chakraborty <nilesh(a)nileshc.com>wrote;wrote:
I am currently drafting my proposal, I shall submit within a few hours once
the initial version is complete.
I installed mediawiki-vagrant on my PC and it went quite smoothly. I could
do all the usual things through the browser; I logged into the mysql server
to examine the database schema.
I also began to clone the
But it seems that the 'git submodule update --init' part would take a long
time - if I'm not mistaken, it's a huge download (excluding the vagrant up
command, which alone takes around 1.25 hours to download everything). I
wanted to clarify something before downloading it all.
Since the entity suggester will be working with wikidata, it'll obviously
need to access the whole live dataset from the database (not the xml dump)
to make the recommendations. I tried searching for database access APIs or
high-level REST APIs for wikidata, but couldn't figure out how I to do
that. Could you point me to the proper documentation?
One of the best examples of a MediaWiki extension interacting with a Java
service is how Solr is used. Solr is still pretty new at Wikimedia,
though. It is used with the GeoData extension and then Solr is used by
geodata api modules.
I think Solr gets updated via a cronjob (solrupdate.php) which creates jobs
in the job queue. Not 100% sure of the exact details.
I do not think direct access to the live database is very practical. I
think anyway the data (json blobs) would need indexing in some particular
way to support what the entity selector needs to do.
The Translate extension also uses Solr in some way, though I am not very
familiar with the details.
On the operations side, puppet is used to configure everything. The puppet
git repo is available to see how things are done.
And also, what is the best way to add a few .jar files to wikidata and
execute them with custom commands (nohup java blah.jar --blah blah -->
running as daemons)? I can of course set it up on my development box inside
virtualbox - I want to know how to "integrate" it into the system so that
any other user can download vagrant and wikidata and have the jars all
ready and running? What is the proper development workflow for this?
wikidata-vagrant is maintained in github, though I think might not work
perfectly right now. We need to update it and it's on our to-do, and
perhaps could be moved to gerrit. I do not know about integrating the
jars, but should be possible.
[answering from this email, as I am not subscribed to wikitech-l on my
On Sun, Apr 28, 2013 at 3:01 AM, Nilesh Chakraborty <nilesh(a)nileshc.com
Awesome. Got it.
I see what you mean, great, thank you. :)
On Apr 28, 2013 2:56 AM, "Lydia Pintscher" <lydia.pintscher(a)wikimedia.de
> On Sat, Apr 27, 2013 at 11:14 PM, Nilesh Chakraborty <
> > Hi Lydia,
> > That helps a lot, and makes it way more interesting. Rather than
> > one-size-fits-all solution, as it seems
to me, each property or each
> > of property (eg. different relationships) will need individual
> > and different methods/metrics for
> > The examples you gave, like continents, sex, relations like
> > uncle/aunt/spouse, or place-oriented
properties like place of birth,
> > country of citizenship, ethnic group etc. - each type has a certain
> > to it (if a person was born in the US, US should be one of the
> countries he
> > was a citizen of; US census/ethnicity statistics may be used to
> > ethnic group etc.) I'm already
starting to chalk out a few patterns
they can be used for recommendation. In my
proposal, should I go into
details regarding these? Or should I just give a few examples and
how the algorithms would work, to explain the
Give some examples and how you'd handle them. You definitely don't
need to have it for all properties. What's important is giving an idea
about how you'd tackle the problem. Give the reader the impression
that you know what you are talking about and can handle the larger
Also: Don't make the system too intelligent like it knowing about US
census data for example. Keep it simple and stupid for now. Things
like "property A is usually used with value X, Y or Z" should cover a
lot already and are likely enough for most cases.
Lydia Pintscher - http://about.me/lydia.pintscher
Community Communications for Technical Projects
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