It’s been another 9 months since my last blog post covering the Wikidata generated geo location maps that I have been tending to for a few years now. Writing this from a hammock, lets see what has noticeably changed in the last 9 months using a visual diff and my pretty reasonable eyes.
Over the years diagrams have appeared in a variety of forms covering various areas of the architecture of Wikidata. Now, as the current tech lead for Wikidata it is my turn.
Wikidata has slowly become a more and more complex system, including multiple extensions, services and storage backends. Those of us that work with it on a day to day basis have a pretty good idea of the full system, but it can be challenging for others to get up to speed. Hence, diagrams!
All diagrams can currently be found on Wikimedia Commons using this search, and are released under CC-BY-SA 4.0. The layout of the diagrams with extra whitespace is intended to allow easy comparison of diagrams that feature the same elements.
This overview shows the Wikidata website, running Mediawiki with the Wikibase extension in the left blue box. Various other extensions are also run such as WikibaseLexeme, WikibaseQualityConstraints, and PropertySuggester.
Wikidata is accessed through a Varnish caching and load balancing layer provided by the WMF. Users, tools and any 3rd parties interact with Wikidata through this layer.
Off to the right are various other external services provided by the WMF. Hadoop, Hive, Ooozie and Spark make up part of the WMF analytics cluster for creating pageview datasets. Graphite and Grafana provide live monitoring. There are many other general WMF services that are not listed in the diagram.
Finally we have our semi persistent and persistent storages which are used directly by Mediawiki and Wikibase. These include Memcached and Redis for caching, SQL(mariadb) for primary meta data, Blazegraph for triples, Swift for files and ElasticSearch for search indexing.
Continue readingIt’s was Wikidata’s 6th birthday on the 30th of October 2018. WMUK celebrated this with a meetup on the 7th of November. They also made this great post event video.
It has been another 6 months since my last post in the Wikidata Map series. In that time Wikidata has gained 4 million items, 1 property with the globe-coordinate data type (coordinates of geographic centre) and 1 million items with coordinates [1]. Each Wikidata item with a coordinate is represented on the map with a single dim pixel. Below you can see the areas of change between this new map and the once generated in March. To see the equivalent change in the previous 4 months take a look at the previous post.
Wikidata.org runs on MediaWiki with the Wikibase extension. But there is more to it than just that. The Wikibase extension itself is split into 3 different sections, being Lib, Repo and Client. There are also 6 other extensions all providing extra functionality to the site and it’s sisters. The extensions are also loaded on a different combination of Clients (such a Wikipedia) and the Repo itself (wikidata.org).
The title is a little wordy, but I hope you get the gist. I just spent 10 minutes staring at some data on a Grafana dashboard, comparing it with some other data, and finding the numbers didn’t add up. Here is the story in case it catches you out.
The dashboard in question is the Wikidata Edits dashboard hosted on the Wikimedia Grafana instance that is public for all to see. The top of the dashboard features a panel that shows the total number of edits on Wikidata in the past 7 days. The rest of the dashboard breaks these edits down further, including another general edits panel on the left of the second row.
Hue, or Hadoop User Experience is described by its documentation pages as “a Web application that enables you to easily interact with an Hadoop cluster”.
The Wikimedia Foundation has a Hue frontend for their Hadoop cluster, which contains various datasets including web requests, API usage and the MediaWiki edit history for all hosted sites. The install can be accessed at https://hue.wikimedia.org/ using Wikimedia LDAP for authentication.
Once logged in Hue can be used to write Hive queries with syntax highlighting, auto suggestions and formatting, as well as allowing users to save queries with names and descriptions, run queries from the browser and watch hadoop job execution state.
The Wikidata & maxlag bit
MediaWiki has a maxlag API parameter that can be passed alongside API requests in order to cause errors / stop writes from happening when the DB servers are lagging behind the master. Within MediaWiki this lag can also be raised when the JobQueue is very full. Recently Wikibase introduced the ability to raise this lag when the Dispatching of changes to client projects is also lagged behind. In order to see how effective this will be, we can take a look at previous API calls.
The Wikimedia Server Admin Log or SAL for short is a timestamped log of actions performed on the Wikimedia cluster by users such as roots and deployers. The log is stored on the WikiTech Wikimedia project and can be found at the following URL: https://wikitech.wikimedia.org/wiki/Server_Admin_Log
An example entry in the log could be:
|
1 |
09:04 addshore: addshore@terbium:~$ for i in {1..2500}; do echo Lexeme:L$i; done | mwscript purgePage.php --wiki wikidatawiki |
As well as the main cluster SAL there are also logs for release engineering (jenkins, zuul, and other CI things) and individual logs for each project that uses Wikimedia Cloud VPS.
A tool has been created for easy SAL navigation which can be found at https://tools.wmflabs.org/sal
Each SAL can be selected at the top of the tool, with ‘Other’ providing you with a list of all Cloud VPS SALs.
The search and date filters can then be used to find entries throughout history.
The Wikibase registry was one of the outcomes of the first in a series of Federated wikibase workshops organised in partnership with the European research council.
The aim of the registry is to act as a central point for details of public Wikibase installs hosted around the web. Data held about the installs currently includes the URL for the home page, Query frontend URL and SPARQL API endpoint URL (if a query service exists).
During the workshop an initial data set was added, and this can be easily seen using the timeline view of the query service and a query that is explained within this post.
It’s time for the first 2018 installation of the Wikidata Map. It has been roughly 4 months since the last post, which compared July 2017 to November 2017. Here we will compare November 2017 to March 2018. For anyone new to this series of posts you can check back at the progression of these maps by looking at the posts on the series page.
Each Wikidata Item with a Coordinate Location(P625)will have a single pixel dot. The more Items present, the more pixel dots and the more the map will glow in that area. The pixel dots are plotted on a totally black canvas, so any land mass outline simply comes from the mass of dots. You can find the raw data for these maps and all historical maps on Wikimedia Tool Labs.
Looking at the two maps below (the more recent map being on the right) it is hard to see the differences by eye, which is why I’ll use ImageMagik to generate a comparison image. Previous comparisons have used Resemble.js.
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