dashmap
ristretto
dashmap | ristretto | |
---|---|---|
12 | 19 | |
2,751 | 5,354 | |
- | 1.4% | |
5.1 | 6.1 | |
28 days ago | about 2 months ago | |
Rust | Go | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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dashmap
- StupidAlloc: what if memory allocation was bad actually
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dashmap VS scalable-concurrent-containers - a user suggested alternative
2 projects | 13 Apr 2023
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Samsara, a safe Rust concurrent cycle collector
The problem is, every single one of these half-dozen crates has at least one known major issue (including UAF), exactly like C++ implementations (which isn't surprising since it's the kind of things where the ownership isn't clear and then the borrow checker can't help us).
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Rust vs Go
Deadlocks and leaks are easy as other languages.
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Shared mutable state is bad... so how do I create a global cache in a multi-threaded app?
Have you considered https://github.com/xacrimon/dashmap ?
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Announcing Leapfrog, a faster concurrent HashMap
Dashmap made some api changes compared to the stdlibs hashmap, which leads to some oddities, as highlighted here: https://github.com/xacrimon/dashmap/issues/175
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Writing a concurrent LRU cache
Some additional notes are in this slide deck and the implementation javadoc. You'd probably want to use something like DashMap for the hash table.
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HashMap-based cache for async programs
You can look at existing concurrent maps like Dashmap https://github.com/xacrimon/dashmap or Cashmap https://gitlab.redox-os.org/redox-os/chashmap
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How does one avoid lock of locks? or use the technique of latch crabbing of databases
Also dashmap
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Noteworthy concurrent data structures?
The only one I've used is Dashmap, it's a concurrent interior-mutability hashmap. Very convenient crate in the case you need that.
ristretto
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Otter, Fastest Go in-memory cache based on S3-FIFO algorithm
1. Unfortunately, ristretto has been showing hit ratio around 0 on almost all traces for a very long time now and the authors don't respond to this in any way. Vitess for example has already changed it to another cache. Here are two issues about it: https://github.com/dgraph-io/ristretto/issues/346 and https://github.com/dgraph-io/ristretto/issues/336. That is, ristretto shows such results even on its own benchmarks. You can see it just by running hit ratio benchmarks on a very simple zipf distribution from the ristretto repository: https://github.com/dgraph-io/ristretto/blob/main/stress_test.... On this test I got the following:
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S3 Express Is All You Need
That's exactly how Userify[0] used to work. (when it was Python; now that it's a Go app, we do the caching in memory using Ristretto[1]).
0. https://userify.com (team ssh key management/sudo authz)
1. https://github.com/dgraph-io/ristretto
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Theine - High performance in-memory cache
I also do some hit ratio benchmarks and Theine's results are much better than Ristretto. See results in README: https://github.com/Yiling-J/theine-go#hit-ratios
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Python deserves a good in-memory cache library!
If you know Caffeine(Java)/Ristretto(Go)/Moka(Rust), you know what Theine is. Python deserves a good in-memory cache library.
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VCache: A Simple In-Memory Cache Library
Thanks for sharing. There are a lot of options for embedded in-memory caches: https://github.com/dgraph-io/ristretto https://awesome-go.com/caches/ Do you have any comparisons or details on how your project has a different approach?
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Cacheme: Asyncio cache framework with multiple storages and thundering herd protection
I made Cacheme years ago, which support redis and synchronous API only. Then I switch to Go and found that there are some awesome cache projects in Go(ristretto, gocache...), I also made my own Cacheme go version: cacheme-go. After trying asyncio and type hint, I think it's time to rewrite my old Cacheme.
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Show HN: Zcached, in-memory key-value cache wire-compatible with memcached
zcached is an in-memory key-value cache exposing a memcached ASCII protocol-compatible interface, built on pluggable cache engines like Ristretto and freecache [0].
It's not performance-competitive with memcached, especially at higher thread counts. That said, it achieves about 1.1M ops/s, but at significantly higher P99 and P999 latency (as measured by memtier). See [1] and [2] for benchmark results from my 7950x-based workstation.
Disclaimer: This is a hobby project created for fun while hacking over the holidays. zcached is not a commercial product and never will be. Don't use it in production; consider this a technology demo more than anything.
I don't expect the source code to build outside of my environment, but for those interested in playing with it, binary artifacts are available at [3]. Try `zcached --address tcp:localhost:11211`.
[0] https://github.com/dgraph-io/ristretto, https://github.com/coocood/freecache
- What is the coolest Go open source projects you have seen?
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Quitting Dgraph Labs
While I never used dgraph, I do use badger and ristretto and am similarly in a bind over their long-term survival (moreso badger than ristretto)...
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Recommendation for Key/Value storage
There are also different packages used as a wrapper on top of the Go map based on what your requirements are (storing a lot of data) https://github.com/allegro/bigcache or (need performance) https://github.com/dgraph-io/ristretto. For basic use-cases, the standard Go map should be enough. Just keep in mind whether you need concurrent access to your data structure, in which case you should guard your map with a mutex .
What are some alternatives?
hashbrown - Rust port of Google's SwissTable hash map
go-cache-benchmark - Cache benchmark for Golang
moka - A high performance concurrent caching library for Rust
BigCache - Efficient cache for gigabytes of data written in Go.
HashMap - An open addressing linear probing hash table, tuned for delete heavy workloads
stretto - Stretto is a Rust implementation for Dgraph's ristretto (https://github.com/dgraph-io/ristretto). A high performance memory-bound Rust cache.
crossbeam - Tools for concurrent programming in Rust
leapfrog - Lock-free concurrent and single-threaded hash map implementations using Leapfrog probing. Currently the highest performance concurrent HashMap in Rust for certain use cases.
parquet-go - Go library to read/write Parquet files
megahash - A super-fast C++ hash table with Node.js wrapper, tested up to 1 billion keys.
IceFireDB - @IceFireLabs -> IceFireDB is a database built for web3.0 It strives to fill the gap between web2 and web3.0 with a friendly database experience, making web3 application data storage more convenient, and making it easier for web2 applications to achieve decentralization and data immutability.