Convert Figma logo to code with AI

golang logogroupcache

groupcache is a caching and cache-filling library, intended as a replacement for memcached in many cases.

12,887
1,387
12,887
41

Top Related Projects

Go Memcached client library #golang

An in-memory key:value store/cache (similar to Memcached) library for Go, suitable for single-machine applications.

Efficient cache for gigabytes of data written in Go.

2,578

An in-memory cache library for golang. It supports multiple eviction policies: LRU, LFU, ARC

Quick Overview

Groupcache is a distributed caching and cache eviction library for Go. It is designed to provide a simple and efficient way to cache data across multiple servers, reducing the load on the backend and improving the overall performance of the application.

Pros

  • Distributed Caching: Groupcache allows you to cache data across multiple servers, making it easier to scale your application as the amount of data and traffic increases.
  • Efficient Eviction: Groupcache uses a sophisticated eviction algorithm to ensure that the most frequently accessed data is kept in the cache, improving the overall performance of the application.
  • Easy to Use: Groupcache provides a simple and intuitive API, making it easy to integrate into your existing Go application.
  • Fault Tolerance: Groupcache is designed to be fault-tolerant, with built-in mechanisms to handle server failures and network outages.

Cons

  • Limited to Go: Groupcache is a Go-specific library, which means that it can only be used in Go applications. This may limit its usefulness for applications that need to be language-agnostic.
  • Complexity: While Groupcache is relatively easy to use, the underlying implementation can be complex, which may make it difficult to understand and debug for some developers.
  • Limited Documentation: The Groupcache project has relatively limited documentation, which may make it difficult for new users to get started.
  • Potential Performance Overhead: Depending on the size and complexity of your application, the overhead of using Groupcache may outweigh the benefits, especially for small-scale applications.

Code Examples

Here are a few examples of how to use Groupcache in your Go application:

  1. Basic Usage:
import (
    "fmt"
    "github.com/golang/groupcache"
)

func main() {
    // Create a new group
    group := groupcache.NewGroup("mygroup", 64<<20, groupcache.GetterFunc(
        func(ctx groupcache.Context, key string, dest groupcache.Sink) error {
            // Fetch the data from the backend and store it in the dest
            dest.SetBytes([]byte("hello, world"))
            return nil
        }))

    // Get the data from the cache
    var data []byte
    err := group.Get(nil, "key", groupcache.StringSink(&data))
    if err != nil {
        fmt.Println("Error:", err)
        return
    }
    fmt.Println(string(data)) // Output: hello, world
}
  1. Distributed Caching:
import (
    "fmt"
    "github.com/golang/groupcache"
)

func main() {
    // Create a new group with a peer picker
    group := groupcache.NewGroup("mygroup", 64<<20, groupcache.GetterFunc(
        func(ctx groupcache.Context, key string, dest groupcache.Sink) error {
            // Fetch the data from the backend and store it in the dest
            dest.SetBytes([]byte("hello, world"))
            return nil
        }))

    // Create a new peer picker
    peerPicker := groupcache.NewHTTPPoolOpts("http://localhost:8080", &groupcache.HTTPPoolOptions{
        BasePath: "/groupcache/",
    })

    // Set the peer picker for the group
    group.RegisterPeerPicker(func() groupcache.PeerPicker { return peerPicker })

    // Get the data from the cache
    var data []byte
    err := group.Get(nil, "key", groupcache.StringSink(&data))
    if err != nil {
        fmt.Println("Error:", err)
        return
    }
    fmt.Println(string(data)) // Output: hello, world
}
  1. Eviction Policies:
import (
    "fmt"
    "github.com/golang/groupcache"
)

func main() {
    // Create a new group with a custom eviction policy
    group := groupcache.NewGroup("mygroup", 64<<20, groupcache.Getter

Competitor Comparisons

Go Memcached client library #golang

Pros of gomemcache

  • Simplicity: gomemcache is a lightweight and straightforward Memcache client library, making it easy to integrate into Go projects.
  • Compatibility: gomemcache is compatible with the Memcache protocol, allowing it to work with a wide range of Memcache servers.
  • Performance: gomemcache is designed to be efficient and performant, with a focus on minimizing overhead and maximizing throughput.

Cons of gomemcache

  • Limited Features: gomemcache is a basic Memcache client and may lack some of the more advanced features found in other caching libraries.
  • Lack of Clustering: gomemcache does not provide built-in support for Memcache clustering, which can be important for larger-scale deployments.
  • Maintenance: The gomemcache project is not actively maintained, with the last commit being over 5 years ago.

Code Comparison

gomemcache:

client := gomemcache.New("localhost:11211")
err := client.Set(&gomemcache.Item{
    Key:   "mykey",
    Value: []byte("myvalue"),
})
if err != nil {
    // handle error
}

groupcache:

group := groupcache.NewGroup("mygroup", 64<<20, groupcache.GetterFunc(
    func(ctx context.Context, key string, dest groupcache.Sink) error {
        // fetch data and populate dest
        return nil
    }
))
var value string
err := group.Get(ctx, "mykey", groupcache.StringSink(&value))
if err != nil {
    // handle error
}

An in-memory key:value store/cache (similar to Memcached) library for Go, suitable for single-machine applications.

Pros of go-cache

  • Simplicity: go-cache is a lightweight, in-memory cache library that is easy to use and integrate into Go projects.
  • Expiration: go-cache supports expiration of cache items, which can be useful for caching data that has a limited lifespan.
  • Concurrent Access: go-cache is thread-safe, allowing for concurrent access to the cache.

Cons of go-cache

  • Limited Functionality: go-cache is a basic cache implementation and may not provide the advanced features found in more comprehensive caching solutions like GroupCache.
  • No Distributed Caching: go-cache is a local, in-memory cache and does not support distributed caching across multiple nodes.

Code Comparison

GroupCache:

group := groupcache.NewGroup("myGroup", 64<<20, groupcache.GetterFunc(
    func(ctx context.Context, key string, dest groupcache.Sink) error {
        // Fetch the data for the given key and store it in dest.
        return nil
    },
))

go-cache:

cache := goCache.New(5*time.Minute, 10*time.Minute)
cache.Set("key", "value", goCache.DefaultExpiration)
value, found := cache.Get("key")

Efficient cache for gigabytes of data written in Go.

Pros of BigCache

  • BigCache is designed to be a high-performance, in-memory cache, optimized for speed and efficiency.
  • It provides a simple and easy-to-use API, making it straightforward to integrate into existing projects.
  • BigCache supports various cache eviction policies, allowing for more control over cache management.

Cons of BigCache

  • BigCache is a standalone cache implementation, while GroupCache is part of the Go standard library, which may make it more familiar and easier to use for some Go developers.
  • BigCache may have a higher learning curve compared to GroupCache, as it has more configuration options and features.
  • The performance benefits of BigCache may not be as significant for smaller-scale applications, where the overhead of using a separate cache library may outweigh the performance gains.

Code Comparison

GroupCache:

func main() {
    groupcache.NewGroup("myGroup", 64<<20, groupcache.GetterFunc(
        func(ctx context.Context, key string, dest groupcache.Sink) error {
            dest.SetBytes([]byte("hello world"))
            return nil
        }))
}

BigCache:

func main() {
    cache, _ := bigcache.NewBigCache(bigcache.DefaultConfig(10 * time.Minute))
    cache.Set("my-unique-key", []byte("hello world"))
    value, _ := cache.Get("my-unique-key")
    fmt.Println(string(value))
}
2,578

An in-memory cache library for golang. It supports multiple eviction policies: LRU, LFU, ARC

Pros of bluele/gcache

  • Expiration Policies: bluele/gcache provides more expiration policy options, such as LRU (Least Recently Used), LFU (Least Frequently Used), and TTL (Time-To-Live), allowing for more fine-grained control over cache eviction.
  • Concurrent Access: bluele/gcache is designed to be thread-safe, enabling concurrent access to the cache without the need for manual synchronization.
  • Callback Functions: bluele/gcache allows users to define callback functions for cache misses, enabling custom logic for fetching and storing data.

Cons of bluele/gcache

  • Complexity: bluele/gcache has a more complex API and configuration options compared to golang/groupcache, which may have a steeper learning curve for some users.
  • Dependency: bluele/gcache has a dependency on the golang.org/x/sync package, which may not be desirable for some projects that aim to minimize external dependencies.
  • Maturity: golang/groupcache has been around for longer and has a larger user base, potentially offering more stability and community support.

Code Comparison

golang/groupcache:

group := groupcache.NewGroup("myGroup", 64<<20, groupcache.GetterFunc(
    func(ctx context.Context, key string, dest groupcache.Sink) error {
        // Fetch the data for the given key and store it in the dest.
        return nil
    }
))

var data []byte
err := group.Get(ctx, "myKey", groupcache.AllocatingByteSliceSink(&data))
if err != nil {
    // Handle the error
}

bluele/gcache:

cache := gcache.New(100).LRU().Build()
cache.Set("myKey", "myValue")
value, _ := cache.Get("myKey")
fmt.Println(value) // Output: "myValue"

Convert Figma logo designs to code with AI

Visual Copilot

Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.

Try Visual Copilot

README

groupcache

Summary

groupcache is a distributed caching and cache-filling library, intended as a replacement for a pool of memcached nodes in many cases.

For API docs and examples, see http://godoc.org/github.com/golang/groupcache

Comparison to memcached

Like memcached, groupcache:

  • shards by key to select which peer is responsible for that key

Unlike memcached, groupcache:

  • does not require running a separate set of servers, thus massively reducing deployment/configuration pain. groupcache is a client library as well as a server. It connects to its own peers, forming a distributed cache.

  • comes with a cache filling mechanism. Whereas memcached just says "Sorry, cache miss", often resulting in a thundering herd of database (or whatever) loads from an unbounded number of clients (which has resulted in several fun outages), groupcache coordinates cache fills such that only one load in one process of an entire replicated set of processes populates the cache, then multiplexes the loaded value to all callers.

  • does not support versioned values. If key "foo" is value "bar", key "foo" must always be "bar". There are neither cache expiration times, nor explicit cache evictions. Thus there is also no CAS, nor Increment/Decrement. This also means that groupcache....

  • ... supports automatic mirroring of super-hot items to multiple processes. This prevents memcached hot spotting where a machine's CPU and/or NIC are overloaded by very popular keys/values.

  • is currently only available for Go. It's very unlikely that I (bradfitz@) will port the code to any other language.

Loading process

In a nutshell, a groupcache lookup of Get("foo") looks like:

(On machine #5 of a set of N machines running the same code)

  1. Is the value of "foo" in local memory because it's super hot? If so, use it.

  2. Is the value of "foo" in local memory because peer #5 (the current peer) is the owner of it? If so, use it.

  3. Amongst all the peers in my set of N, am I the owner of the key "foo"? (e.g. does it consistent hash to 5?) If so, load it. If other callers come in, via the same process or via RPC requests from peers, they block waiting for the load to finish and get the same answer. If not, RPC to the peer that's the owner and get the answer. If the RPC fails, just load it locally (still with local dup suppression).

Users

groupcache is in production use by dl.google.com (its original user), parts of Blogger, parts of Google Code, parts of Google Fiber, parts of Google production monitoring systems, etc.

Presentations

See http://talks.golang.org/2013/oscon-dl.slide

Help

Use the golang-nuts mailing list for any discussion or questions.