The Analytics Data Lake contains a number of editing datasets.
To access this data, log into
stat1007.eqiad.wmnet and run
hive. Here you can
use wmf and query the tables described below. For recipes that work with lots of data, see Analytics/Data Lake/Cookbook.
In comparison to the traffic ones, those datasets are not continuously updated. They are regularly updated by fully re-importing/re-building them, creating a new
snapshot notion is key when querying the Edits datasets, since including multiple snapshots doesn't make sense for most queries. As of 2017-04, snapshots are provided monthly. When we import, we grab all the data available from all tables except the
revision table, for which we filter by
where rev_timestamp <= <<snapshot-date>>. If the snapshot is a little late because of processing problems, then by the time it finishes it may have more data in tables like logging, archive, etc. These should not affect history reconstruction because we base everything on revisions, but they'll affect any queries you may run on those tables separately.
The pipeline used to generate these datasets is described at Analytics/Systems/Data Lake/Edits/Pipeline.
Raw Mediawiki data
These are unprocessed copies of the MariaDB application tables (most of them publicly available) that back our MediaWiki installations. They are stored in the
wmf_raw database. Main difference with the original tables in databases is that the import bundle all wikis together in every table, facilitating cross-wiki queries. This means every table contains a new field
wiki_db allowing to choose the wikis to query. Another thing to notice about this field is that it is a partition in the sense of hive tables, so a restriction on that field will make the queries a lot faster for not having to read every wiki data.
mediawiki_cu_changes(from the CheckUser extension)
Those are preprocessed data, usually stored in Parquet format and sometimes containing additional fields. Those tables can be found in the
mediawiki_history: fully denormalized dataset containing user, page and revision processed data
mediawiki_user_history: a subset of
mediawiki_historycontaining only user events
mediawiki_page_history: a subset of
mediawiki_historycontaining only page events
mediawiki_metrics: Dataset providing precomputed metrics over edits data (e.g. monthly new registered users or daily edits by anonymous users)
- Geowiki: Private, until we figure out how to sanitize and publish, counts of editors by project by country at different activity levels. This is being migrated to Hadoop, and the old system is explained in detail at Analytics/Systems/Geowiki.
mediawiki_history_reduced: Dataset providing a reduced version of the
mediawiki_historyone, with less fields and specific precomputed events so that the datastore druid can compute by-page and by-user activity levels.
mediawiki_wikitext_history: Parquet version of revision-full-history XML-Dumps (updated monthly, late in the month). It contains the text of each non-deleted revision as well as page and user information.
Limitations of the historical datasets
Users of this data should be aware that the reconstruction process is not perfect. The resulting data is not 100% complete throughout all wiki-history. In some specific slices/dices of the data set, some fields may be missing (null) or approximated (inferred value).
- MediaWiki databases are not meant to store history (revisions yes, of course; but not user history or page history). They hold part of the history in the logging table, but it's incomplete and formatted in many different ways depending on the software version. This makes the reconstruction of MediaWiki history a really complex task. Even sometimes the data is not there, and can not be reconstructed.
- The size of the data is considerably large. The reconstruction algorithm needs to reprocess the whole database(s) at every run since the beginning of time, because MediaWiki constantly updates the old records of the logging table. This presents hard performance challenges to the reconstruction job, which made the code much more complex. We need to balance the complexity of the job with the data quality, at some point we need to add a lot of complexity to "maybe" improve quality for a small percentage of data. For example, if only 0.5% of pages have field X missing and getting the info to fix the field would make reconstruction twice as complex, it will not be corrected but rather documented as not present. This is a balance of requirements so you always let us know whether we are missing something there.
How much/Which data is missing?
After vetting the data for some time we approximated that the recoverable data that we did not make to recover represented less than 1%. We also saw that this data corresponded mostly to the earlier years of reconstructed history (2007-2009), and especially related to deleted pages. We do not have yet an in-depth analysis of the completeness of the data, it's in our backlog, see: phab:T155507
Will there be improvements in the future to correct this missing data?
Yes, if we know that the improvement will have enough benefit. The mentioned task would help in measuring that.
History of deleted pages that are (re)created: Correctly identifying a page as deleted and recreated might be straightforward for small sets of pages. It might also be simplified by "recreated" not meaning the page was undeleted by an administrator. As mentioned above, how MediaWiki logs data changes over time. This further complicates the identification process, particularly on a scale of "across all wikis". You might therefore find examples of pages that were recreated with the same page ID, namespace, and title. This can result in their creation and deletion timestamps in the history table appearing to be incorrect. If you're looking to run analysis on those kind of cases, further narrowing of the dataset (e.g. by time) might allow for correct processing of those.