hamt
pyroscope
hamt | pyroscope | |
---|---|---|
7 | 56 | |
261 | 7,382 | |
- | - | |
6.9 | 9.6 | |
3 months ago | about 1 year ago | |
C | Go | |
MIT License | GNU Affero General Public License v3.0 |
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hamt
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Visual Introduction to Hash-Array Mapped Tries (HAMTs)
This isn't a very good explanation. The wikipedia article isn't great either. I like this description:
https://github.com/mkirchner/hamt#persistent-hash-array-mapp...
The name does tell you quite a bit about what these are:
* Hash - rather than directly using the keys to navigate the structure, the keys are hashed, and the hashes are used for navigation. This turns potentially long, poorly-distributed keys into short, well-distributed keys. However, that does mean you have to compute a hash on every access, and have to deal with hash collisions. The mkirchner implementation above calls collisions "hash exhaustion", and deals with them using some generational hashing scheme. I think i'd fall back to collision lists until that was conclusively proven to be too slow.
* Trie - the tree is navigated by indexing nodes using chunks of the (hash of the) key, rather than comparing the keys in the node
* Array mapped - sparse nodes are compressed, using a bitmap to indicate which logical slots are occupied, and then only storing those. The bitmaps live in the parent node, rather than the node itself, i think? Presumably helps with fetching.
A HAMT contains a lot of small nodes. If every entry is a bitmap plus a pointer, then it's two words, and if we use five-bit chunks, then each node can be up to 32 entries, but i would imagine the majority are small, so a typical node might be 64 bytes. I worry that doing a malloc for each one would end up with a lot of overhead. Are HAMTs often implemented with some more custom memory management? Can you allocate a big block and then carve it up?
Could you do a slightly relaxed HAMT where nodes are not always fully compact, but sized to the smallest suitable power of two entries? That might let you use some sort of buddy allocation scheme. It would also let you insert and delete without having to reallocate the node. Although i suppose you can already do that by mapping a few empty slots.
- Show HN: A hash array-mapped trie implementation in C
- Ask HN: What are some 'cool' but obscure data structures you know about?
pyroscope
- Grafana Phlare, open source database for continuous profiling at scale
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The pros and cons of eBPF profiling in K8s
What do you mean? pyroscope.io was slow for you? or the blog?
- Go garbage collector doesn't release memory
- Pyroscope - Continuous profiling platform
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Ask HN: What are some 'cool' but obscure data structures you know about?
Tries (or prefix trees).
We use them a lot at Pyroscope for compressing strings that have common prefixes. They are also used in databases (e.g indexes in Mongo) or file formats (e.g debug symbols in macOS/iOS Mach-O format are compressed using tries).
We have an article with some animations that go into details about tries in case anyone's interested [0].
[0] https://github.com/pyroscope-io/pyroscope/blob/main/docs/sto...
- How to add dynamic tags/labels to Java profiles (example)
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Question: How do you handle oversized heap analysis?
You could use continuous profiling with Pyroscope which uses async-profiler under the hood, but with the added functionality that you can add relevant tags to your VMs (example).
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JFR (Java Flight Recorder) Parser written in Go
Java Flight Recorder (JFR) is a format for collecting diagnostic and profiling data from Java applications. A while back someone created an issue for Pyroscope , an open source continuous profiler written in Go, to support ingesting profiles in JFR format, but there were no existing parsers that were also written in Go.
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flamegraph.com - a new website for uploading, analyzing, and sharing pprof profiles
This cloud version is actually a slimmed-down version of Pyroscope which is open source and so you can run it locally.
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We created flamegraph.com - A website for uploading, analyzing, and sharing flamegraphs
At Pyroscope (open source continuous profiling) we use flamegraphs extensively to visualize and analyze profiling data. However, one of the worst parts about using flamegraphs for analysis is that they are kind of annoying to share.
What are some alternatives?
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