Hello everyone,
It is my first time interacting in this mailing list, so I will be happy to receive
further feedbacks on how to better interact with the community :)
I am trying to access Wikipedia meta data in a streaming and time/resource sustainable
manner. By meta data I mean many of the voices that can be found in the statistics of a
wiki article, such as edits, editors list, page views etc.
I would like to do such for an online classifier type of structure: retrieve the data from
a big number of wiki pages every tot time and use it as input for predictions.
I tried to use the Wiki API, however it is time and resource expensive, both for me and
Wikipedia.
My preferred choice now would be to query the specific tables in the Wikipedia database,
in the same way this is done through the Quarry tool. The problem with Quarry is that I
would like to build a standalone script, without having to depend on a user interface like
Quarry. Do you think that this is possible? I am still fairly new to all of this and I
don't know exactly which is the best direction.
I saw [
1]<https://meta.wikimedia.org/wiki/Research:Data> that I could access wiki
replicas both through Toolforge and PAWS, however I didn't understand which one would
serve me better, could I ask you for some feedback?
Also, as far as I understood
[
2]<https://wikitech.wikimedia.org/wiki/Analytics/Data_Lake>ke>, directly accessing the
DB through Hive is too technical for what I need, right? Especially because it seems that
I would need an account with production shell access and I honestly don't think that I
would be granted access to it. Also, I am not interested in accessing sensible and private
data.
Last resource is parsing analytics dumps, however this seems less organic in the way of
retrieving and polishing the data. As also, it would be strongly decentralised and
physical-machine dependent, unless I upload the polished data online every time.
Sorry for this long message, but I thought it was better to give you a clearer picture
(hoping this is clear enough). If you could give me even some hint it would be highly
appreciated.
Best,
Cristina
[1]
https://meta.wikimedia.org/wiki/Research:Data
[2]
https://wikitech.wikimedia.org/wiki/Analytics/Data_Lake