native english speaker here, I still cannot connect it either.

I had the same trouble. But if you pronounce "biyouvet" like "bee you vay" as you would in French, it sounds like "B of A", for Bank of America.

I wasn’t expecting the app to be that good! Great recommendation

This might be a good fit for roaring bitmaps [1] or Minimal Perfect Hashing

[1] http://roaringbitmap.org/

I haven't got a full comprehension of 1 and why it would compress a lot better. It would be interesting to take a look.

I did consider perfect hashing, however IIUC it will map a fixed set of entries to sequential integers, but it won't do something clever for items not in the set, so I couldn't find a way to make it work well for this problem. I did see someone talking about perfect bloom filters but to be honest I didn't quite understand it https://iswsa.acm.org/bloom.html

Pressure treated wood is kinda like that (it uses something other than tar).

[1]: https://www.homedepot.com/c/ab/types-of-pressure-treated-woo...

I’ve used lulu.com for this in the past for small one-off print jobs (I think it was 5$ for something around 80 pages)

I think you could do the pointerless version (the one using an int32 index) of this in go via unsafe casting.

I’ll try it out later

Yes, the problem is that you still need pointers, and furthermore, pointers to different kinds of objects, of different sizes. Also, Go’s garbage collector should know about the pointers.

You could represent the heap as an array, use array offsets instead of pointers, and do your own garbage collection, but that’s pretty low level and you might as well compile to WebAssembly.

Agreed, when you start to need these kind of optimizations, go might not be the best choice

I’ve used lulu.com in the past

This is actually pretty great thanks.

> we had to make release branches SOX-compliant, adhering to additional rules and constraints.

Does anyone have an example of what is required to make a branch SOX-compliant?

It is probably closer to something like avro, but with more features and less java focus.

Kafka works best when the data it is returning to consumers is in the page cache.

When consumers fall behind, they start to request data that might not be in the page cache, causing things to slow down.