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GPT-5.2

https://openai.com/index/introducing-gpt-5-2/
255•atgctg•1h ago•219 comments

Litestream VFS

https://fly.io/blog/litestream-vfs/
93•emschwartz•1h ago•29 comments

Going Through Snowden Documents, Part 1

https://libroot.org/posts/going-through-snowden-documents-part-1/
44•libroot•56m ago•14 comments

Show HN: Sim – Apache-2.0 n8n alternative

https://github.com/simstudioai/sim
44•waleedlatif1•2h ago•6 comments

Craft software that makes people feel something

https://rapha.land/craft-software-that-makes-people-feel-something/
149•lukeio•6h ago•66 comments

Pop!_OS 24.04 LTS with Cosmic Desktop Environment Released

https://blog.system76.com/post/pop-os-letter-from-our-founder/
46•onnnon•44m ago•3 comments

An Orbital House of Cards: Frequent Megaconstellation Close Conjunctions

https://arxiv.org/abs/2512.09643
65•rapnie•4h ago•34 comments

Show HN: I've asked Claude to improve codebase quality 200 times

https://gricha.dev/blog/the-highest-quality-codebase
293•Gricha•2d ago•224 comments

Launch HN: BrowserBook (YC F24) – IDE for deterministic browser automation

44•cschlaepfer•4h ago•26 comments

Prove It All Night: With no fame or fortune, what keeps a band onstage? (1999)

https://chicagoreader.com/news/prove-it-all-night/
20•NaOH•1w ago•1 comments

Things I want to say to my boss

https://www.ithoughtaboutthatalot.com/2025/the-things-i-want-to-say-to-my-boss
177•casca•3h ago•146 comments

Auto-grading decade-old Hacker News discussions with hindsight

https://karpathy.bearblog.dev/auto-grade-hn/
538•__rito__•1d ago•240 comments

Rivian Unveils Custom Silicon, R2 Lidar Roadmap, and Universal Hands Free

https://riviantrackr.com/news/rivian-unveils-custom-silicon-r2-lidar-roadmap-universal-hands-free...
78•doctoboggan•1h ago•96 comments

Days since last GitHub incident

https://github-incidents.pages.dev/
163•AquiGorka•2h ago•88 comments

Deprecate like you mean it

https://entropicthoughts.com/deprecate-like-you-mean-it
27•todsacerdoti•3h ago•70 comments

Show HN: Local Privacy Firewall-blocks PII and secrets before ChatGPT sees them

https://github.com/privacyshield-ai/privacy-firewall
85•arnabkarsarkar•2d ago•33 comments

Getting a Gemini API key is an exercise in frustration

https://ankursethi.com/blog/gemini-api-key-frustration/
768•speckx•23h ago•294 comments

Patterns.dev

https://www.patterns.dev/
516•handfuloflight•18h ago•119 comments

Kicking Robots

https://harpers.org/archive/2025/12/kicking-robots-james-vincent-humanoids/
25•Hooke•4d ago•2 comments

Golang optimizations for high‑volume services

https://packagemain.tech/p/golang-optimizations-for-highvolume
6•der_gopher•3d ago•0 comments

A “frozen” dictionary for Python

https://lwn.net/SubscriberLink/1047238/25c270b077849dc0/
172•jwilk•9h ago•121 comments

Oldest attestation of Austronesian language: Đông Yên Châu inscription

https://en.wikipedia.org/wiki/%C4%90%C3%B4ng_Y%C3%AAn_Ch%C3%A2u_inscription
55•teleforce•5d ago•13 comments

Helldivers 2 on-disk size 85% reduction

https://store.steampowered.com/news/app/553850/view/491583942944621371
201•SergeAx•1w ago•193 comments

Show HN: An endless scrolling word search game

https://endless-wordsearch.com
3•marcusdev•5h ago•0 comments

The Cost of a Closure in C

https://thephd.dev/the-cost-of-a-closure-in-c-c2y
166•ingve•12h ago•66 comments

Show HN: GPULlama3.java Llama Compilied to PTX/OpenCL Now Integrated in Quarkus

15•mikepapadim•3h ago•1 comments

Pop Goes the Population Count?

https://xania.org/202512/11-pop-goes-the-weasel-er-count
35•hasheddan•5h ago•8 comments

Giant of the Attic: On the Majesty of Alan Moore

https://www.metropolitanreview.org/p/giant-of-the-attic
16•CharlesW•1w ago•5 comments

Size of Life

https://neal.fun/size-of-life/
2423•eatonphil•1d ago•270 comments

How the Brain Parses Language

https://www.quantamagazine.org/the-polyglot-neuroscientist-resolving-how-the-brain-parses-languag...
105•mylifeandtimes•3d ago•57 comments
Open in hackernews

Garbage collection of object storage at scale

https://www.warpstream.com/blog/taking-out-the-trash-garbage-collection-of-object-storage-at-massive-scale
96•ko_pivot•7mo ago

Comments

juancn•7mo ago
Another possible mechanism for doing GC at scale (a variation on Asynchronous Reconciliation in the article) in some file/object store, is doing a probabilistic mark and sweep using bloom filters.

The mark phase can be done in parallel building many bloom filters for the files/objects found.

Then the bloom filters are merged (or'ed together essentially) and then a parallel sweep phase can use the bloom filter to answer the question: is this file/object live?

The bloom filter then answers either "No" with 100% certainty or "Maybe" with some probability p that depends on the parameters used for the bitset and the hash function family.

cogman10•7mo ago
What does the bloom filter solve?

The expensive portion of the mark and sweep for the object store is the mark phase, not the storage of what's been marked. 100s, 1000s, or even millions of live objects wouldn't hardly take any space to keep in a remembered set.

On the other hand, querying the S3 bucket to list those 1M objects would be expensive no matter how you store the results.

But this does tickle my brain. Perhaps something akin to the generational hypotheses can be applied? Maybe it's the case that very old, very young, or very untouched objects are more likely to be garbage than not. If there's some way to divide the objects up and only look at objects whose are in "probably need to be collected" regions, then you could do minor fast sweeps semi frequently and schedule more expensive "really delete untracked stuff" infrequently.

Cicero22•7mo ago
I was thinking they could use something like cloudwatch events, or something, to trigger sweeps and significantly reduce scheduled sweeps.

They could even use cost allocation tags to predict if a bucket or group of buckets should be scanned if it's growing unexpectedly. Cost isn't a perfect metric but there's definitely signal there.

juancn•7mo ago
Building the set of used files or objects (which is what mark does in a mark/sweep).

Sometimes it's too expensive to mark in place, even if it's a bit that you need to write to disk and keeping a set of references may be prohibitive (or the structure holding the references is mostly/effectively immutable).

If it's all memory and mutable it doesn't (normally) really matter, but when it's not, you ideally would have some mechanism to move the code to where the data is, rather than stream the data to where the compute is (it is really wasteful for large scale data processing).

In any case, you would not be moving/scanning the files themselves, but the metadata is what you want to read for the mark phase.

The article if I understood correctly implies that the files and the metadata of the files (Kafka queues and so on) are separate, so presumably, the metadata is much much smaller than the data itself, but still potentially large.

For example if you had a large scale content addressed store (think a massive version of git's blob storage), you typically add to something like that and keep a few mutable root references to start your GC from to seed a mark/sweep.

Following the git example, the roots would be the branches, tags and reflogs, and the metadata you scan the transitive closur of the trees that are reachable from those (simplifying a bit) but not the file blobs themselves.

I use git as an example because a a CAS lends itself very well to large scale distributed systems because you can reason about it as an immutable data structure, but you can still change it effectively with sane semantics.

donavanm•7mo ago
If you like big beautiful storage and probabilistic structures check out https://www.usenix.org/conference/osdi14/technical-sessions/.... The coho data folks ended up in AWS S3 a few years later.
juancn•7mo ago
Thanks! I hadn't seen it and it may come handy!
deathanatos•7mo ago
> Why Not Just Use a Bucket Policy?

I've heard these words so many times, it's refreshing to see someone dig into why bucket policies aren't a cure-all.

As for "Why not use synchronous deletion?" — regarding the pitfall there, what about a WAL? I.e., you WAL the deletions you want to perform into an object in the object store, perform the deletions, and then delete the WAL. If you crash and find a WAL file, you repeat the delete commands contained in the WAL.

(I've used this to handle this problem where some of the deletions are mixed: i.e., some in an object store, some in a SQL DB, etc. The object store is essentially being used as strongly consistent storage.)

(Perhaps this is essentially the same as your "delayed queue"? All I've got is an object store though, not a queue, and it's pretty useful hammer.)

telotortium•7mo ago
> HN Disclaimer: WarpStream sells a drop-in replacement for Apache Kafka built directly on-top of object storage.

First time I’ve seen one of these. That’s actually a better way to advertise your product than putting it at the end.

hencq•7mo ago
Yes, though I think they meant to say disclosure instead of disclaimer.
siscia•7mo ago
What I see working extremely well, arguably in a setting where cost was not really an issue was a much simpler approach.

Keep compacting files at some regular cadence `t` and keep a bucket policy to delete files older than `t+delta+buffer`.

Then have an alarm for files older than `t+buffer`