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https://github.com/hypermodeinc/ristretto
A high performance memory-bound Go cache
https://github.com/hypermodeinc/ristretto
cache go golang library performance
Last synced: about 3 hours ago
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A high performance memory-bound Go cache
- Host: GitHub
- URL: https://github.com/hypermodeinc/ristretto
- Owner: hypermodeinc
- License: apache-2.0
- Created: 2019-02-12T18:07:00.000Z (almost 6 years ago)
- Default Branch: main
- Last Pushed: 2025-02-05T14:22:59.000Z (about 14 hours ago)
- Last Synced: 2025-02-05T14:28:42.906Z (about 14 hours ago)
- Topics: cache, go, golang, library, performance
- Language: Go
- Homepage: https://dgraph.io/blog/post/introducing-ristretto-high-perf-go-cache/
- Size: 1.46 MB
- Stars: 5,830
- Watchers: 71
- Forks: 381
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS
Awesome Lists containing this project
README
# Ristretto
[](https://pkg.go.dev/github.com/dgraph-io/ristretto/v2)
[](https://github.com/hypermodeinc/ristretto/actions/workflows/ci-ristretto-tests.yml)
[](https://github.com/hypermodeinc/ristretto/actions/workflows/ci-ristretto-lint.yml)
[](https://coveralls.io/github/hypermodeinc/ristretto?branch=main)
[](https://goreportcard.com/report/github.com/hypermodeinc/ristretto)
Ristretto is a fast, concurrent cache library built with a focus on performance and correctness.
The motivation to build Ristretto comes from the need for a contention-free cache in [Dgraph][].
[Dgraph]: https://github.com/hypermodeinc/dgraph
## Features
- **High Hit Ratios** - with our unique admission/eviction policy pairing, Ristretto's performance
is best in class.
- **Eviction: SampledLFU** - on par with exact LRU and better performance on Search and Database
traces.
- **Admission: TinyLFU** - extra performance with little memory overhead (12 bits per counter).
- **Fast Throughput** - we use a variety of techniques for managing contention and the result is
excellent throughput.
- **Cost-Based Eviction** - any large new item deemed valuable can evict multiple smaller items
(cost could be anything).
- **Fully Concurrent** - you can use as many goroutines as you want with little throughput
degradation.
- **Metrics** - optional performance metrics for throughput, hit ratios, and other stats.
- **Simple API** - just figure out your ideal `Config` values and you're off and running.
## Status
Ristretto is production-ready. See [Projects using Ristretto](#projects-using-ristretto).
## Getting Started
### Installing
To start using Ristretto, install Go 1.21 or above. Ristretto needs go modules. From your project,
run the following command
```sh
go get github.com/dgraph-io/ristretto/v2
```
This will retrieve the library.
#### Choosing a version
Following these rules:
- v1.x.x is the first version used in most programs with Ristretto dependencies.
- v2.x.x is the new version with support for generics, for which it has a slightly different
interface. This version is designed to solve compatibility problems of programs using the old
version of Ristretto. If you start writing a new program, it is recommended to use this version.
## Usage
```go
package main
import (
"fmt"
"github.com/dgraph-io/ristretto/v2"
)
func main() {
cache, err := ristretto.NewCache(&ristretto.Config[string, string]{
NumCounters: 1e7, // number of keys to track frequency of (10M).
MaxCost: 1 << 30, // maximum cost of cache (1GB).
BufferItems: 64, // number of keys per Get buffer.
})
if err != nil {
panic(err)
}
defer cache.Close()
// set a value with a cost of 1
cache.Set("key", "value", 1)
// wait for value to pass through buffers
cache.Wait()
// get value from cache
value, found := cache.Get("key")
if !found {
panic("missing value")
}
fmt.Println(value)
// del value from cache
cache.Del("key")
}
```
## Benchmarks
The benchmarks can be found in
https://github.com/dgraph-io/benchmarks/tree/master/cachebench/ristretto.
### Hit Ratios for Search
This trace is described as "disk read accesses initiated by a large commercial search engine in
response to various web search requests."
.svg)
### Hit Ratio for Database
This trace is described as "a database server running at a commercial site running an ERP
application on top of a commercial database."
.svg)
### Hit Ratio for Looping
This trace demonstrates a looping access pattern.
.svg)
### Hit Ratio for CODASYL
This trace is described as "references to a CODASYL database for a one hour period."
.svg)
### Throughput for Mixed Workload
### Throughput ffor Read Workload
.svg)
### Through for Write Workload
.svg)
## Projects Using Ristretto
Below is a list of known projects that use Ristretto:
- [Badger](https://github.com/hypermodeinc/badger) - Embeddable key-value DB in Go
- [Dgraph](https://github.com/hypermodeinc/dgraph) - Horizontally scalable and distributed GraphQL
database with a graph backend
## FAQ
### How are you achieving this performance? What shortcuts are you taking?
We go into detail in the
[Ristretto blog post](https://blog.dgraph.io/post/introducing-ristretto-high-perf-go-cache/), but in
short: our throughput performance can be attributed to a mix of batching and eventual consistency.
Our hit ratio performance is mostly due to an excellent
[admission policy](https://arxiv.org/abs/1512.00727) and SampledLFU eviction policy.
As for "shortcuts," the only thing Ristretto does that could be construed as one is dropping some
Set calls. That means a Set call for a new item (updates are guaranteed) isn't guaranteed to make it
into the cache. The new item could be dropped at two points: when passing through the Set buffer or
when passing through the admission policy. However, this doesn't affect hit ratios much at all as we
expect the most popular items to be Set multiple times and eventually make it in the cache.
### Is Ristretto distributed?
No, it's just like any other Go library that you can import into your project and use in a single
process.