@Tilman: Yes, some people are using Wikihadoop to convert dumps from XML to JSON. I have added code recently and maintain it.
On Wed, May 18, 2016 at 4:22 PM, Tilman Bayer tbayer@wikimedia.org wrote:
Yes, of course *processing* the entire history (even with text) has been done before - but perhaps not storing or indexing it.
BTW is anyone still using "Wikihadoop"?
https://blog.wikimedia.org/2011/11/21/do-it-yourself-analytics-with-wikipedi... https://github.com/whym/wikihadoop
On Wed, May 18, 2016 at 3:09 AM, Dan Andreescu dandreescu@wikimedia.org wrote:
Hi Tilman, thanks for pointing to this research. We have indeed worked on this kind of project, for both ORES and the WikiCredit system. There are many challenges like memory and processing time. Loading the entire history without text is what we're working on right now for our Wikistats 2.0 project. Even this has many challenges.
As far as I can tell right now, any simple attempt to handle all the data in one way or one place is going to run into some sort of limit. If anybody finds otherwise, it would be useful to our work.
*From: *Tilman Bayer *Sent: *Tuesday, May 17, 2016 02:54 *To: *A mailing list for the Analytics Team at WMF and everybody who has an interest in Wikipedia and analytics. *Reply To: *A mailing list for the Analytics Team at WMF and everybody who has an interest in Wikipedia and analytics. *Cc: *A public mailing list about Wikimedia Search and Discovery projects *Subject: *[Analytics] University project to make entire English Wikipedia history searchable on Hadoop using Solr
Detailed technical report on an undergraduate student project at Virginia Tech (work in progress) to import the entire English Wikipedia history dump into the university's Hadoop cluster and index it using Apache Solr, to "allow researchers and developers at Virginia Tech to benchmark configurations and big data analytics software":
Steven Stulga, "English Wikipedia on Hadoop Cluster" https://vtechworks.lib.vt.edu/handle/10919/70932 (CC BY 3.0)
IIRC this has rarely or never been attempted due to the large size of the dataset - 10TB uncompressed. And it looks like the author here encountered an out of memory error that he wasn't able to solve before the end of term...
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