joaovictortr

Did you benchmark GraphScope with GraphX or Giraph? How does it compare to these two?

It can filter out DNS requests in the whole network for ads/tracker domains if used as the DNS resolver on your network, which would also include other devices (e.g. phones). Most smartphone apps perform a lot of tracker requests, which makes this approach very effective IMHO.

What the network approach doesn't help with is when the ads are served from the same domain as the content. An extension like uBlock Origin solves this problem because it filters the content within the browser.

So I think both approaches are necessary to filter out ads/trackers, and they also complement each other, one at the network level (dnsmasq or Pi-Hole) and the other at the browser/content level (uBlock Origin, PrivacyBadger).

There is a presentation from EuroBSDCon 2019, that describes the techniques and hardware used to achieve that figure [0].

There is also a thread in HN if you're interested [1].

[0] https://people.freebsd.org/~gallatin/talks/euro2019.pdf

[1] https://news.ycombinator.com/item?id=21043765

Another very interesting resource on the subject is the book Introduction to Statistical Learning by Garet James et al [1].

The book introduces the foundational concepts of statistical learning (classification, regression, cross-validation) and algorithms such as support vector machines.

It is also available on PDF at the website [1].

[1] http://www-bcf.usc.edu/~gareth/ISL/

I'd also recommend Discourse [0], as others already have. You can see it live on the Julia [1] and Rust [2] language forums, for example.

[0] https://discourse.org/

[1] https://discourse.julialang.org/

[2] https://internals.rust-lang.org/