Feign VS RoaringBitmap

A new, Feign client, to make the get request to https://example.com/themes. This client will expose a get() method.

The actual project for feign is OpenFeign https://github.com/OpenFeign/feign . Spring comes with it's own starter . Add below dependency to the project

Find a community/project that interests you, I've gone with feign. Head on into the issues tab, and you'll see all the potential contributions you could make. Starting out, it's a good idea to search for tags like "bug", or "good first issue".

Feign has support for what you're looking for. https://github.com/OpenFeign/feign/tree/master/jaxrs2

feign-spring4 gives you a type safe client proxy of an interface annotated with Spring MVC annotations.

At the risk of doxxing myself, I'm a contributer attempting to fix this issue with this pr. The project has existed for a while now, and since I'm not part of the openfeign team, so the final solution they end up using isn't up to me. So there's technical debt to deal with (how the project is built and tested currently) and whether or not multi-release jars are the best solution in this case.

I was recently reading about Roaring https://roaringbitmap.org/ which is a highly optimized compressed bitset implementation. I reccomend reading about it if you are interested in this sort of thing. The talk at https://roaringbitmap.org/talks/ is especially good.

However, I would love compressed (not just packed) bitsets too, which is something different to me. I would make it another class with a similar interface, based on something like roaring. It doesn't need to be in the standard, but it would be nice if the API was a such that one could easily swap implementations.

As an aside if you find yourself having to compute them on the fly, know that the Roaring Bitmaps libraries is the way to go [1]. The bitmaps are compressed, and can be streamed directly into SIMD computations (batching XORs and popcnts 256 bits wide!). The Jaccard index is just intersection_len / union_len [2] away

[1] https://roaringbitmap.org/

[2] https://roaringbitmap.readthedocs.io/en/latest/#roaringbitma...

Use a two stage approach, with a bloom/cuckoo filter stored as a https://roaringbitmap.org/ in memory. Then a secondary key/value store on disk (bolt or anything else).

As an aside, if you're dealing with large bit sets, you might also want to evaluate Roaring Bitmaps.

Sidetracking a bit the conversation. What a coincidence that the author (Lemire) is also represented on Today's #1 "Ask HN: What are some cool but obscure data structures you know about?" as he is the main contributor of RoaringBitmap https://github.com/RoaringBitmap/RoaringBitmap and one of the main authors of the data structure.