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Tag: wikidata query service

Testing WDQS Blazegraph data load performance

February 10, 2021 / / 1 Comment

Toward the end of 2020 I spent some time blackbox testing data load times for WDQS and Blazegraph to try and find out which possible setting tweaks might make things faster.

I didn’t come to any major conclusions as part of this effort but will write up the approach and data nonetheless incase it is useful for others.

I expect the next step toward trying to make this go faster would be via some whitebox testing, consulting with some of the original developers or with people that have taken a deep dive into the code (which I started but didn’t complete).

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Faster munging for the Wikidata Query Service using Hadoop

October 14, 2020 / / 3 Comments

The Wikidata query service is a public SPARQL endpoint for querying all of the data contained within Wikidata. In a previous blog post I walked through how to set up a complete copy of this query service. One of the steps in this process is the munge step. This performs some pre-processing on the RDF dump that comes directly from Wikidata.

Back in 2019 this step took 20 hours and now takes somewhere between 1-2 days as Wikidata has continued to grow. The original munge step (munge.sh) makes use of only a single CPU. The WMF has been experimenting for some time with performing this step in their Hadoop cluster as part of their modern update mechanism (streaming updater). An additional patch has now also made this useful for the current default load process (using loadData.sh).

This post walks through using the new Hadoop based munge step with the latest Wikidata TTL dump on Google clouds Dataproc service. This cuts the munge time down from 1-2 days to just 2 hours using an 8 worker cluster. Even faster times can be expected with more workers, all the way down to ~20 minutes.

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Using OpenRefine with Wikidata for the first time

July 7, 2020 / / 2 Comments

I have long known about OpenRefine (previously Google Refine) which is a tool for working with data, manipulating and cleaning it. As of version 3.0 (May 2018), OpenRefine included a Wikidata extension, allowing for extra reconciliation and also editing of Wikidata directly (as far as I understand it). You can find some documentation on this topic on Wikidata itself.

This post serves as a summary of my initial experiences with OpenRefine, including some very basic reconciliation from a Wikidata Query Service SPARQL query, and making edits on Wikidata.

In order to follow along you should already know a little about what Wikidata is.

Starting OpenRefine

I tried out OpenRefine in two different setups both of which were easy to set up following the installation docs. The setups were on my actual machine and in a VM. For the VM I also had to use the -i option to make the service listen on a different IP. refine -i 172.23.111.140

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Changing the concept URI of an existing Wikibase with data

November 5, 2019 / / 4 Comments

Many users of Wikibase find themselves in a position where they need to change the concept URI of an existing Wikibase for one or more reasons, such as a domain name update or desire to have https concept URIs instead of HTTP.

Below I walk through a minimal example of how this can be done using a small amount of data and the Wikibase Docker images. If you are not using the Docker images the steps should still work, but you do not need to worry about copying files into and out of containers or running commands inside containers.

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Your own Wikidata Query Service, with no limits

October 23, 2019 / / 13 Comments

The Wikidata Query Service allows anyone to use SPARQL to query the continuously evolving data contained within the Wikidata project, currently standing at nearly 65 millions data items (concepts) and over 7000 properties, which translates to roughly 8.4 billion triples.

Screenshot of the Wikidata Query Service home page including the example query which returns all Cats on Wikidata.

You can find a great write up introducing SPARQL, Wikidata, the query service and what it can do here. But this post will assume that you already know all of that.

Guide

Here we will focus on creating a copy of the query service using data from one of the regular TTL data dumps and the query service docker image provided by the wikibase-docker git repo supported by WMDE.

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