- Statically Typed - 100% statically typed using code generation. Drop-in replacement, no reflect/type-assertion.
- Scale Efficiently - thundering herd protection via pub/sub.
- Cluster Support - same API for redis & redis cluster.
- Memoize - dynamic key params based on code generation.
- Versioning - cache versioning for better management.
- Pipeline - reduce io cost by redis pipeline.
🌀 Read this first: Caches, Promises and Locks. This is how caching part works in cacheme.
🌀 Real world example with Echo and Ent: https://github.com/Yiling-J/echo-ent-cacheme-example
// old
id, err := strconv.ParseInt(c.Param("id"), 10, 64)
comment, err := ent.Comment.Get(context.Background(), int(id))
// new
comment, err := cacheme.CommentCacheStore.Get(c.Request().Context(), c.Param("id"))
go get github.com/Yiling-J/cacheme-go/cmd
After installing cacheme-go
codegen, go to the root directory(or the directory you think cacheme should stay) of your project, and run:
go run github.com/Yiling-J/cacheme-go/cmd init
The command above will generate cacheme
directory under current directory:
└── cacheme
├── fetcher
  │  └── fetcher.go
└── schema
└── schema.go
It's up to you where the cacheme directory should be, just remember to use the right directory in Store Generation step.
Edit schema.go
and add some schemas:
package schema
import (
"time"
cacheme "github.com/Yiling-J/cacheme-go"
)
var (
// default prefix for redis keys
Prefix = "cacheme"
// store schemas
Stores = []*cacheme.StoreSchema{
{
Name: "Simple",
Key: "simple:{{.ID}}",
To: "",
Version: 1,
TTL: 5 * time.Minute,
Singleflight: false,
MetaData: false,
},
}
)
More details here
Run code generation from the root directory of the project as follows:
# this will use default schema path ./cacheme/schema
go run github.com/Yiling-J/cacheme-go/cmd generate
Or you can use custom schema path:
go run github.com/Yiling-J/cacheme-go/cmd generate ./yours/cacheme/schema
This produces the following files:
└── cacheme
  ├── fetcher
  │  └── fetcher.go
├── schema
│  └── schema.go
├── store
│ ├── base.go
│ └── simple.go
└── store.go
If you update schema, just run generate
again.
Each cache store can provide a fetch function in fetcher.go
, you should call this Setup
function before create client:
import "your/cacheme/store"
func Setup() {
store.SimpleCacheStore.Fetch = func(ctx context.Context, ID string) (string, error) {
return ID, nil
}
}
You can setup fetch functions in any place, using any pattern, not restricted to this file. Just make sure you have a fetch function when using store.
import (
"your_project/cacheme"
"your_project/cacheme/fetcher"
)
func main() {
// setup fetcher
fetcher.Setup()
// create client
client := cacheme.New(
redis.NewClient(&redis.Options{
Addr: "localhost:6379",
Password: "",
DB: 0,
}),
)
// or cluster client
client := cacheme.NewCluster(
redis.NewClusterClient(&redis.ClusterOptions{
Addrs: []string{
":7000",
":7001",
":7002"},
}),
)
}
Get cached result. If not in cache, call fetch function and store data to Redis.
// "foo" is the {{.ID}} part of the schema
result, err := client.SimpleCacheStore.Get(ctx, "foo")
Get multiple keys from multiple stores using pipeline. For each key, if not in cache, call fetch function and store data to Redis.
- single store
pipeline := client.NewPipeline()
ids := []string{"1", "2", "3", "4"}
var ps []*store.SimplePromise
for _, i := range ids {
promise, err := client.SimpleCacheStore.GetP(ctx, pipeline, i)
ps = append(ps, promise)
}
err = pipeline.Execute(ctx)
fmt.Println(err)
for _, promise := range ps {
r, err := promise.Result()
fmt.Println(r, err)
}
Consider using GetM
API for single store, see GetM
example below.
- multiple stores
// same pipeline for different stores
pipeline := client.NewPipeline()
ids := []string{"1", "2", "3", "4"}
var ps []*store.SimplePromise // cache string
var psf []*store.FooPromise // cache model.Foo struct
for _, i := range ids {
promise, err := client.SimpleCacheStore.GetP(ctx, pipeline, i)
ps = append(ps, promise)
}
for _, i := range ids {
promise, err := client.FooCacheStore.GetP(ctx, pipeline, i)
psf = append(psf, promise)
}
// execute only once
err = pipeline.Execute(ctx)
// simple store results
for _, promise := range ps {
r, err := promise.Result()
fmt.Println(r, err)
}
// foo store results
for _, promise := range psf {
r, err := promise.Result()
fmt.Println(r, err)
}
Get multiple keys from same store, also using Redis pipeline. For each key, if not in cache, call fetch function and store data to Redis.
qs, err := client.SimpleCacheStore.GetM("foo").GetM("bar").GetM("xyz").Do(ctx)
// qs is a queryset struct, support two methods: GetSlice and Get
// GetSlice return ordered results slice
r, err := qs.GetSlice() // r: {foo_result, bar_result, xyz_result}
// Get return result of given param
r, err := qs.Get("foo") // r: foo_result
r, err := qs.Get("bar") // r: bar_result
r, err := qs.Get("fake") // error, because "fake" not in queryset
You can also initialize a getter using MGetter
getter := client.SimpleCacheStore.MGetter()
for _, id := range ids {
getter.GetM(id)
}
qs, err := getter.Do(c.Request().Context())
err := client.SimpleCacheStore.Invalid(ctx, "foo")
err := client.SimpleCacheStore.Update(ctx, "foo")
Only works when you enable MetaData
option in schema.
// invalid all version 1 simple cache
client.SimpleCacheStore.InvalidAll(ctx, "1")
Each schema has 5 fields:
- Name - store name, will be struct name in generated code, capital first.
- Key - key with variable using go template syntax, Variable name will be used in code generation.
- To - cached value, type of value will be used in code generation. Examples:
- string:
""
- int:
1
- struct:
model.Foo{}
- struct pointer:
&model.Foo{}
- slice:
[]model.Foo{}
- map:
map[model.Foo]model.Bar{}
- string:
- Version - version interface, can be
string
,int
, or callablefunc() string
. - TTL - redis ttl using go time.
- Singleflight - bool, if
true
, concurrent requests to same key on same executable will call Redis only once - MetaData - bool, if
true
, each store will save all generated keys to a Redis Set, soInvalidAll
method can work.
- Duplicate name/key is not allowed.
- Everytime you update schema, run code generation again.
- Not all store API support
Singleflight
option:Get
: support.GetM
: support. singleflight key will be the combination of all keys, order by alphabetical.
// these two will use same singleflight group key store.GetM("foo").GetM("bar").GetM("xyz").Do(ctx) Store.GetM("bar").GetM("foo").GetM("xyz").Do(ctx)
GetP
: not support.
Version
callable can help you managing version better. Example:// models.go const FooCacheVersion = "1" type Foo struct {} const BarCacheVersion = "1" type Bar struct {Foo: Foo}
// schema.go // version has 3 parts: foo version & bar version & global version number // if you change struct, update FooCacheVersion or BarCacheVersion // if you change fetcher function or ttl or something else, change global version number { Name: "Bar", Key: "bar:{{.ID}}:info", To: model.Bar{}, Version: func() string {return model.FooCacheVersion + model.BarCacheVersion + "1"}, TTL: 5 * time.Minute, },
- If set
Singleflight
totrue
, CachemeGet
command will be wrapped in a singleflight, so concurrent requests to same key will callRedis
only once. Let's use some example to explain this:- you have some products to sell, and thousands people will view the detail at same time, so the product key
product:1:info
may be hit 100000 times per second. Now you should turn on singleflight, and the actually redis hit may reduce to 5000. - you have cache for user shopping cart
user:123:cart
, only the user himself can see that. Now no need to use singleflight, becauese there shouldn't be concurrent requests to that key. - you are using serverless platform, AWS Lambda or similar. So each request runs in isolated environment, can't talk to each other through channels. Then singleflight make no sense.
- you have some products to sell, and thousands people will view the detail at same time, so the product key
- Full redis key has 3 parts: prefix + schema key + version.
Schema Key
category:{{.categoryID}}:book:{{.bookID}}
with prefixcacheme
, version 1 will generate key:Also you will seecacheme:category:1:book:3:v1
categoryID
andbookID
in generated code, as fetch func params.
You can use custom logger with cacheme, your logger should implement cacheme logger interface:
type Logger interface {
Log(store string, key string, op string)
}
Here store
is the store tag, key
is cache key without prefix, op
is operation type.
Default logger is NOPLogger
, just return and do nothing.
logger := &YourCustomLogger{}
client.SetLogger(logger)
- HIT: cache hit to redis, if you enable singleflight, grouped requests only log once.
- MISS: cache miss
- FETCH: fetch data from fetcher
Parallel benchmarks of Cacheme
- params: 10000/1000000 hits, 10 keys loop, TTL 10s,
SetParallelism(100)
, singleflight on
cpu: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
BenchmarkCachemeGetParallel-12 10000 198082 ns/op
BenchmarkCachemeGetParallel-12 1000000 9501 ns/op