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https://github.com/viney-shih/go-cache
A flexible multi-layer Go caching library to deal with in-memory and shared cache by adopting Cache-Aside pattern.
https://github.com/viney-shih/go-cache
cache cache-aside cachemanager caching caching-library distributed go go-cache golang memory-cache multi-layer-cache multi-level-cache tinylfu
Last synced: about 2 months ago
JSON representation
A flexible multi-layer Go caching library to deal with in-memory and shared cache by adopting Cache-Aside pattern.
- Host: GitHub
- URL: https://github.com/viney-shih/go-cache
- Owner: viney-shih
- License: apache-2.0
- Created: 2022-05-24T05:44:24.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2023-08-30T13:59:10.000Z (over 1 year ago)
- Last Synced: 2024-07-31T20:48:48.224Z (5 months ago)
- Topics: cache, cache-aside, cachemanager, caching, caching-library, distributed, go, go-cache, golang, memory-cache, multi-layer-cache, multi-level-cache, tinylfu
- Language: Go
- Homepage:
- Size: 961 KB
- Stars: 136
- Watchers: 2
- Forks: 9
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Security: SECURITY.md
Awesome Lists containing this project
- awesome-go - go-cache - A flexible multi-layer Go caching library to deal with in-memory and shared cache by adopting Cache-Aside pattern. (Database / Caches)
- awesome-go-extra - go-cache - layer Go caching library to deal with in-memory and shared cache by adopting Cache-Aside pattern.|70|5|1|2022-05-24T05:44:24Z|2022-07-11T02:04:43Z| (Generators / Caches)
README
# go-cache
[](https://pkg.go.dev/github.com/viney-shih/go-cache?tab=doc)
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[](http://www.apache.org/licenses/LICENSE-2.0)
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[](https://github.com/avelino/awesome-go#caches)
Photo by Ashley McNamara, via ashleymcnamara/gophers (CC BY-NC-SA 4.0)
A flexible multi-layered caching library interacts with **private (in-memory) cache** and **shared cache** (i.e. Redis) in Go. It provides `Cache-Aside` strategy when dealing with both, and maintains the consistency of private cache between distributed systems by `Pub-Sub` pattern.
Caching is a common technique that aims to improve the performance and scalability of a system. It does this by temporarily copying frequently accessed data to fast storage close to the application. Distributed applications typically implement either or both of the following strategies when caching data:
- Using a **private cache**, where data is held locally on the computer that's running an instance of an application or service.
- Using a **shared cache**, serving as a common source that can be accessed by multiple processes and machines.
Ref: [https://docs.microsoft.com/en-us/azure/architecture/best-practices/images/caching/caching3.png](https://docs.microsoft.com/en-us/azure/architecture/best-practices/images/caching/caching3.png "Using a local private cache with a shared cache")
Considering the flexibility, efficiency and consistency, we starts to build up our own framework.
## Features
- **Easy to use** : provide a friendly interface to deal with both caching mechnaism by simple configuration. Limit the size of memory on single instance (pod) as well.
- **Maintain consistency** : evict keys between distributed systems by `Pub-Sub` pattern.
- **Data compression** : provide customized marshal and unmarshal functions.
- **Fix concurrency issue** : prevent data racing happened on single instance (pod).
- **Metric** : provide callback functions to measure the performance. (i.e. hit rate, private cache usage, ...)
## Data flow
### Load the cache with `Cache-Aside` strategy
```mermaid
sequenceDiagram
participant APP as Application
participant M as go-cache
participant L as Local Cache
participant S as Shared Cache
participant R as Resource (Microservice / DB)
APP ->> M: Cache.Get() / Cache.MGet()
alt Local Cache hit
M ->> L: Adapter.MGet()
L -->> M: {[]Value, error}
M -->> APP: return
else Local Cache miss but Shared Cache hit
M ->> L: Adapter.MGet()
L -->> M: cache miss
M ->> S: Adapter.MGet()
S -->> M: {[]Value, error}
M ->> L: Adapter.MSet()
M -->> APP: return
else All miss
M ->> L: Adapter.MGet()
L -->> M: cache miss
M ->> S: Adapter.MGet()
S -->> M: cache miss
M ->> R: OneTimeGetterFunc() / MGetterFunc()
R -->> M: return from getter
M ->> S: Adapter.MSet()
M ->> L: Adapter.MSet()
M -->> APP: return
end
```
### Evict the cache
```mermaid
sequenceDiagram
participant APP as Application
participant M as go-cache
participant L as Local Cache
participant S as Shared Cache
participant PS as PubSub
APP ->> M: Cache.Del()
M ->> S: Adapter.Del()
S -->> M: return error if necessary
M ->> L: Adapter.Del()
L -->> M: return error if necessary
M ->> PS: Pubsub.Pub() (broadcast key eviction)
M -->> APP: return nil or error
```
## Installation
```sh
go get github.com/viney-shih/go-cache
```
## Get Started
### Basic usage: Set-And-Get
By adopting `Singleton` pattern, initialize the *Factory* in main.go at the beginning, and deliver it to each package or business logic.
```go
// Initialize the Factory in main.go
tinyLfu := cache.NewTinyLFU(10000)
rds := cache.NewRedis(redis.NewRing(&redis.RingOptions{
Addrs: map[string]string{
"server1": ":6379",
},
}))
cacheFactory := cache.NewFactory(rds, tinyLfu)
```
Treat it as a common **key:value** store like Redis. But more advanced, it coordinated the usage between multi-layered caching mechanism inside.
```go
type Object struct {
Str string
Num int
}
func Example_setAndGetPattern() {
// We create a group of cache named "set-and-get".
// It uses the shared cache only. Each key will be expired within ten seconds.
c := cacheFactory.NewCache([]cache.Setting{
{
Prefix: "set-and-get",
CacheAttributes: map[cache.Type]cache.Attribute{
cache.SharedCacheType: {TTL: 10 * time.Second},
},
},
})
ctx := context.TODO()
// set the cache
obj := &Object{
Str: "value1",
Num: 1,
}
if err := c.Set(ctx, "set-and-get", "key", obj); err != nil {
panic("not expected")
}
// read the cache
container := &Object{}
if err := c.Get(ctx, "set-and-get", "key", container); err != nil {
panic("not expected")
}
fmt.Println(container) // Output: Object{ Str: "value1", Num: 1}
// read the cache but failed
if err := c.Get(ctx, "set-and-get", "no-such-key", container); err != nil {
fmt.Println(err) // Output: errors.New("cache key is missing")
}
// Output:
// &{value1 1}
// cache key is missing
}
```
### Advanced usage: `Cache-Aside` strategy
`GetByFunc()` is the easier way to deal with the cache by implementing the **getter function** in the parameter. When the cache is missing, it is going to refill the cache automatically.
```go
func ExampleCache_GetByFunc() {
// We create a group of cache named "get-by-func".
// It uses the local cache only with TTL of ten minutes.
c := cacheFactory.NewCache([]cache.Setting{
{
Prefix: "get-by-func",
CacheAttributes: map[cache.Type]cache.Attribute{
cache.LocalCacheType: {TTL: 10 * time.Minute},
},
MarshalFunc: msgpack.Marshal, // msgpack is from "github.com/vmihailenco/msgpack/v5"
UnmarshalFunc: msgpack.Unmarshal,
},
})
ctx := context.TODO()
container2 := &Object{}
if err := c.GetByFunc(ctx, "get-by-func", "key2", container2, func() (interface{}, error) {
// The getter is used to generate data when cache missed, and refill the cache automatically..
// You can read from DB or other microservices.
// Assume we read from MySQL according to the key "key2" and get the value of Object{Str: "value2", Num: 2}
return Object{Str: "value2", Num: 2}, nil
}); err != nil {
panic("not expected")
}
fmt.Println(container2) // Object{ Str: "value2", Num: 2}
// Output:
// &{value2 2}
}
```
`MGetter` is another approaching way to do this. Set this function durning registering the *Setting*.
```go
func ExampleService_Create_mGetter() {
// We create a group of cache named "mgetter".
// It uses both shared and local caches with separated TTL of one hour and ten minutes.
c := cacheFactory.NewCache([]cache.Setting{
{
Prefix: "mgetter",
CacheAttributes: map[cache.Type]cache.Attribute{
cache.SharedCacheType: {TTL: time.Hour},
cache.LocalCacheType: {TTL: 10 * time.Minute},
},
MGetter: func(keys ...string) (interface{}, error) {
// The MGetter is used to generate data when cache missed, and refill the cache automatically..
// You can read from DB or other microservices.
// Assume we read from MySQL according to the key "key3" and get the value of Object{Str: "value3", Num: 3}
// HINT: remember to return as a slice, and the item order needs to consist with the keys in the parameters.
return []Object{{Str: "value3", Num: 3}}, nil
},
MarshalFunc: cache.Marshal,
UnmarshalFunc: cache.Unmarshal,
},
})
ctx := context.TODO()
container3 := &Object{}
if err := c.Get(ctx, "mgetter", "key3", container3); err != nil {
panic("not expected")
}
fmt.Println(container3) // Object{ Str: "value3", Num: 3}
// Output:
// &{value3 3}
}
```
[More examples](./example_advanced_test.go)
## References
- https://docs.microsoft.com/en-us/azure/architecture/best-practices/caching
- https://github.com/vmihailenco/go-cache-benchmark
- https://github.com/go-redis/cache
## License
[Apache-2.0](https://opensource.org/licenses/Apache-2.0)
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