RVS_Generic_Swift_Tool VS RoaringBitmap

[0] https://github.com/RiftValleySoftware/RVS_Generic_Swift_Tool...

[1] https://github.com/RiftValleySoftware/RVS_Generic_Swift_Tool...

[2] https://github.com/RiftValleySoftware/RVS_Generic_Swift_Tool...

[3] https://developer.apple.com/library/archive/documentation/Co...

Ole Begemann and Chris Eidhoff wrote Advanced Swift, and, in there, described a really efficient FIFO queue.

I implemented a variant ofit, in my Generic Swift Toolbox Package[0]. It’s lightning fast.

[0] https://github.com/RiftValleySoftware/RVS_Generic_Swift_Tool...

Found it, but it's not what I need.

I need a target to be a playground; not a project.

The idea is to be able to assign resources, files, and SPM modules to a playground, so they are available to the code running in the playground (an example might be an SPM module like my Generic Swift Toolbox Module[0]). I can then work with the code I'm prototyping in a lightweight text file.

[0] https://github.com/RiftValleySoftware/RVS_Generic_Swift_Tool...

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.