New Collaboration with Marco Behler

As you may have guessed from the venue of my Big OOPs talk (https://www.youtube.com/watch?v=wo84LFzx5nI), I traveled to Europe over the summer. While in Stockholm, I met with Marco Behler (https://x.com/MarcoBehler) from JetBrains (https://www.jetbrains.com/) for this interview: One of the things Marco mentions during the interview is the One Billion Row Challenge (https://github.com/gunnarmorling/1brc), a recent popular Java benchmark. It’s actually quite similar to the Haversine distance problem we use as a recurring example in the Performance Aware Programming series (https://www.computerenhance.com/i/99218768/performance-aware-programming-series): it involves computing a small number of numerical results from a large amount of data stored in a text file. After the interview was over, Marco floated the idea of doing a collaboration based on the One Billion Row Challenge. He would write some Java code to solve the challenge, and I would give advice on how to improve its performance. We’d do this a few times, and see how far it would get him toward having a competitive solution. This sounded like a great idea to me, because not only does it mesh well with what we do here on Computer Enhance, but it would also give me a chance to see first-hand the performance issues that arise when working with Java, a language I don’t generally work with. So we’re doing it! You can start watching it right now, in fact: And if you like it, there’s a playlist (https://www.youtube.com/playlist?list=PLIRBoI92yMam5ubzfdzoyLOW51cb3W72F) that will have new episodes as they are posted. Since there’s a lot to talk about with anything performance-related, from time to time I may also do some follow-up videos here where I go further into some of the details of the challenge. I don’t expect I’ll do any actual Java code - I’ll leave that to Marco - but there are plenty of things that come up during our discussions that would make for good stand-alone posts here on Computer Enhance. So stay tuned for those as well. Until then, happy viewing everyone! — Casey