Tag Archives: talk
On November 6 2024 I presented a talk with the title: “The implementation of MariaDB parallel replication” at a local TeqHub meetup in Copenhagen.
In the talk I first presented how MariaDB replication works overall. I then described the central idea of optimistic parallel replication. Finally I described three details of the implementation: transaction scheduling; conflict detection; and efficient commit ordering. Here are the slides for the presentation.
I was very impressed by the level of the engagement of the audience. There were many questions that showed not only a deep interest in the subject, but also a deep understanding of the material I presented.
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So you heard about the interesting presentations at the MariaDB Server Fest, but didn’t have time to watch them when we were live? Or you have so far seen only a couple of the presentations, but would like some hints at which other presentations are worthy of taking a look at?
That’s the purpose of this blog entry: to help you pick and choose, suggesting what could be interesting for you. All the Server Fest presentations are available on YouTube, with subtitles and Q&A sessions!
Four tips
A first tip: Most presentations have a short five-minute Q&A session.
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For a large Open Source project to survive, it needs the right testing infrastructure in place. Because of this, the MariaDB Foundation made the whole build system a community shared resource. In this talk we will show how we have accomplished this and how the community can benefit.
MariaDB Day is part of FOSDEM Fringe and will be held on Sunday 2 February 2020. Attendance is free, but space is limited, so please RSVP on the Meetup page if you plan to attend.
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MariaDB has an Open Source engine called ColumnStore which provides columnar storage capabilities. During the MariaDB Day Andrew Hutchings (a.k.a. LinuxJedi) will hold a talk explaining what columnar storage is, how it works and the advantages / disadvantages of it. He will also talk about how you can use it to help with things such as your analytical workloads alongside your traditional OLTP workloads.
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