Do It Yourself Analytics with Wikipedia

As you probably know, we publish on a regular basis backups of the different Wikimedia projects, containing their complete editing history. As time progresses, these backups grow larger and larger and become increasingly harder to analyze. To help the community, researchers and other interested people, we have developed a number of analytic tools to assist you in analyzing these large datasets. Today, we want to update you about these new tools, what they do and where you can find them. And please remember they are all still in development:

• Wikihadoop
• Diffdb
• WikiPride

Wikihadoop

Wikihadoop makes it possible to use MapReduce jobs using Hadoop on the compressed XML dump files. What this means is that we can embarrassingly easy parallelize the processing of our XML files and this means that we don’t have to wait for days or weeks to finish a job.
We used Wikihadoop to create the diffs for all edits from the English XML dump that was generated in April of this year.

DiffDB

DiffIndexer and DiffSearcher are the two components of the DiffDB. The DiffIndexer takes as raw input the diffs generated by Wikihadoop and creates a Lucene-based index. The DiffSearcher allows you to query the index so you can answer questions such as:

• Who has added template X in the last month?
• Who added more than 2000 characters to user talk pages in 2008?

WikiPride

Finally, WikiPride allows you to visualize the breakdown of a Wikipedia community by age of account and by the volume of contributed content. You need a Toolserver account to run this, but you will be able to generate cool charts.
If you are having trouble getting Wikihadoop to run, then please contact me at dvanliere at wikimedia dot org and I am happy to point you in the right direction! Let the data crunching begin!
Diederik van Liere, Analytics Team