gatus/vendor/github.com/TwinProduction/gocache

gocache

gocache is an easy-to-use, high-performance, lightweight and thread-safe (goroutine-safe) in-memory key-value cache with support for LRU and FIFO eviction policies as well as expiration, bulk operations and even persistence to file.

Table of Contents

• Features
• Usage
  • Initializing the cache
  • Functions
  • Examples
    • Creating or updating an entry
    • Getting an entry
    • Deleting an entry
    • Complex example
• Persistence
  • Limitations
• Eviction
  • MaxSize
  • MaxMemoryUsage
• Expiration
• Server
• Running the server with Docker
• Performance
  • Summary
  • Results
• FAQ
  • How can I persist the data on application termination?
  • How can I automatically save the cache to a file every 5 minutes?
  • Why does the memory usage not go down?

Features

gocache supports the following cache eviction policies:

• First in first out (FIFO)
• Least recently used (LRU)

It also supports cache entry TTL, which is both active and passive. Active expiration means that if you attempt to retrieve a cache key that has already expired, it will delete it on the spot and the behavior will be as if the cache key didn't exist. As for passive expiration, there's a background task that will take care of deleting expired keys.

It also includes what you'd expect from a cache, like bulk operations, persistence and patterns.

While meant to be used as a library, there's a Redis-compatible cache server included. See the Server section. It may also serve as a good reference to use in order to implement gocache in your own applications.

Usage

go get -u github.com/TwinProduction/gocache

If you're interested in using gocache as a server rather than an embedded library, see Server

Initializing the cache

cache := gocache.NewCache().WithMaxSize(1000).WithEvictionPolicy(gocache.LeastRecentlyUsed)

If you're planning on using expiration (SetWithTTL or Expire) and you want expired entries to be automatically deleted in the background, make sure to start the janitor when you instantiate the cache:

cache.StartJanitor()

Functions

Function	Description
WithMaxSize	Sets the max size of the cache. gocache.NoMaxSize means there is no limit. If not set, the default max size is gocache.DefaultMaxSize.
WithMaxMemoryUsage	Sets the max memory usage of the cache. gocache.NoMaxMemoryUsage means there is no limit. The default behavior is to not evict based on memory usage.
WithEvictionPolicy	Sets the eviction algorithm to be used when the cache reaches the max size. If not set, the default eviction policy is gocache.FirstInFirstOut (FIFO).
WithForceNilInterfaceOnNilPointer	Configures whether values with a nil pointer passed to write functions should be forcefully set to nil. Defaults to true.
StartJanitor	Starts the janitor, which is in charge of deleting expired cache entries in the background.
StopJanitor	Stops the janitor.
Set	Same as SetWithTTL, but with no expiration (gocache.NoExpiration)
SetAll	Same as Set, but in bulk
SetWithTTL	Creates or updates a cache entry with the given key, value and expiration time. If the max size after the aforementioned operation is above the configured max size, the tail will be evicted. Depending on the eviction policy, the tail is defined as the oldest
Get	Gets a cache entry by its key.
GetByKeys	Gets a map of entries by their keys. The resulting map will contain all keys, even if some of the keys in the slice passed as parameter were not present in the cache.
GetAll	Gets all cache entries.
GetKeysByPattern	Retrieves a slice of keys that matches a given pattern.
Delete	Removes a key from the cache.
DeleteAll	Removes multiple keys from the cache.
Count	Gets the size of the cache. This includes cache keys which may have already expired, but have not been removed yet.
Clear	Wipes the cache.
TTL	Gets the time until a cache key expires.
Expire	Sets the expiration time of an existing cache key.
SaveToFile	Stores the content of the cache to a file so that it can be read using ReadFromFile. See persistence.
ReadFromFile	Populates the cache using a file created using SaveToFile. See persistence.

For further documentation, please refer to Go Reference

Examples

Creating or updating an entry

cache.Set("key", "value") 
cache.Set("key", 1)
cache.Set("key", struct{ Text string }{Test: "value"})
cache.SetWithTTL("key", []byte("value"), 24*time.Hour)

Getting an entry

value, exists := cache.Get("key")

You can also get multiple entries by using cache.GetByKeys([]string{"key1", "key2"})

Deleting an entry

cache.Delete("key")

You can also delete multiple entries by using cache.DeleteAll([]string{"key1", "key2"})

Complex example

package main

import (
    "fmt"
    "time"

    "github.com/TwinProduction/gocache"
)

func main() {
    cache := gocache.NewCache().WithEvictionPolicy(gocache.LeastRecentlyUsed).WithMaxSize(10000)
    cache.StartJanitor() // Passively manages expired entries

    cache.Set("key", "value")
    cache.SetWithTTL("key-with-ttl", "value", 60*time.Minute)
    cache.SetAll(map[string]interface{}{"k1": "v1", "k2": "v2", "k3": "v3"})

    value, exists := cache.Get("key")
    fmt.Printf("[Get] key=key; value=%s; exists=%v\n", value, exists)
    for key, value := range cache.GetByKeys([]string{"k1", "k2", "k3"}) {
        fmt.Printf("[GetByKeys] key=%s; value=%s\n", key, value)
    }
    for _, key := range cache.GetKeysByPattern("key*", 0) {
        fmt.Printf("[GetKeysByPattern] key=%s\n", key)
    }

    fmt.Println("Cache size before persisting cache to file:", cache.Count())
    err := cache.SaveToFile("cache.bak")
    if err != nil {
        panic(fmt.Sprintf("failed to persist cache to file: %s", err.Error()))
    }

    cache.Expire("key", time.Hour)
    time.Sleep(500*time.Millisecond)
    timeUntilExpiration, _ := cache.TTL("key")
    fmt.Println("Number of minutes before 'key' expires:", int(timeUntilExpiration.Seconds()))

    cache.Delete("key")
    cache.DeleteAll([]string{"k1", "k2", "k3"})

    fmt.Println("Cache size before restoring cache from file:", cache.Count())
    _, err = cache.ReadFromFile("cache.bak")
    if err != nil {
        panic(fmt.Sprintf("failed to restore cache from file: %s", err.Error()))
    }

    fmt.Println("Cache size after restoring cache from file:", cache.Count())
    cache.Clear()
    fmt.Println("Cache size after clearing the cache:", cache.Count())
}

Output

[Get] key=key; value=value; exists=true
[GetByKeys] key=k2; value=v2
[GetByKeys] key=k3; value=v3
[GetByKeys] key=k1; value=v1
[GetKeysByPattern] key=key
[GetKeysByPattern] key=key-with-ttl
Cache size before persisting cache to file: 5
Number of minutes before 'key' expires: 3599
Cache size before restoring cache from file: 1
Cache size after restoring cache from file: 5
Cache size after clearing the cache: 0

Persistence

While gocache is an in-memory cache, you can still save the content of the cache in a file and vice versa.

To save the content of the cache to a file:

err := cache.SaveToFile(TestCacheFile)

To retrieve the content of the cache from a file:

numberOfEntriesEvicted, err := newCache.ReadFromFile(TestCacheFile)

The numberOfEntriesEvicted will be non-zero only if the number of entries in the file is higher than the cache's configured MaxSize.

Limitations

While you can cache structs in memory out of the box, persisting structs to a file requires you to register the custom interfaces that your application uses with the gob package.

type YourCustomStruct struct {
    A string
    B int
}

// ...
cache.Set("key", YourCustomStruct{A: "test", B: 123})

To persist your custom struct properly:

gob.Register(YourCustomStruct{})
cache.SaveToFile("gocache.bak")

The same applies for restoring the cache from a file:

cache := NewCache()
gob.Register(YourCustomStruct{})
cache.ReadFromFile(TestCacheFile)
value, _ := cache.Get("key")
fmt.Println(value.(YourCustomStruct))

You only need to persist the struct once, so adding the following function in a file would suffice:

func init() {
    gob.Register(YourCustomStruct{})
}

Failure to register your custom structs will prevent gocache from persisting and/or parsing the value of each keys that use said custom structs.

That being said, assuming that you're using gocache as a cache, this shouldn't create any bugs on your end, because every key that cannot be parsed are not populated into the cache by ReadFromFile.

In other words, if you're falling back to a database or something similar when the cache doesn't have the key requested, you'll be fine.

Note that if you need to modify the type of a variable in a struct, you should change the name of that variable as well. For instance, if the struct has a CreatedAt variable with the type time.Time and that variable type is later modified to uint64, decoding the struct would fail, however, if you rename the variable to CreatedAtUnixTimeInMs, there won't be any decoding issues other than the loss of data for that field. You could also obviously handle the migration gracefully by keeping both variables, populating the CreatedAtUnixTimeInMs variable with the CreatedAt value and then removing the CreatedAt field.

Eviction

MaxSize

Eviction by MaxSize is the default behavior, and is also the most efficient.

The code below will create a cache that has a maximum size of 1000:

cache := gocache.NewCache().WithMaxSize(1000)

This means that whenever an operation causes the total size of the cache to go above 1000, the tail will be evicted.

MaxMemoryUsage

Eviction by MaxMemoryUsage is disabled by default, and is in alpha.

The code below will create a cache that has a maximum memory usage of 50MB:

cache := gocache.NewCache().WithMaxSize(0).WithMaxMemoryUsage(50*gocache.Megabyte)

This means that whenever an operation causes the total memory usage of the cache to go above 50MB, one or more tails will be evicted.

Unlike evictions caused by reaching the MaxSize, evictions triggered by MaxMemoryUsage may lead to multiple entries being evicted in a row. The reason for this is that if, for instance, you had 100 entries of 0.1MB each and you suddenly added a single entry of 10MB, 100 entries would need to be evicted to make enough space for that new big entry.

It's very important to keep in mind that eviction by MaxMemoryUsage is approximate.

The only memory taken into consideration is the size of the cache, not the size of the entire application. If you pass along 100MB worth of data in a matter of seconds, even though the cache's memory usage will remain under 50MB (or whatever you configure the MaxMemoryUsage to), the memory footprint generated by that 100MB will still exist until the next GC cycle.

As previously mentioned, this is a work in progress, and here's a list of the things you should keep in mind:

• The memory usage of structs are a gross estimation and may not reflect the actual memory usage.
• Native types (string, int, bool, []byte, etc.) are the most accurate for calculating the memory usage.
• Adding an entry bigger than the configured MaxMemoryUsage will work, but it will evict all other entries.

Expiration

There are two ways that the deletion of expired keys can take place:

• Active
• Passive

Active deletion of expired keys happens when an attempt is made to access the value of a cache entry that expired. Get, GetByKeys and GetAll are the only functions that can trigger active deletion of expired keys.

Passive deletion of expired keys runs in the background and is managed by the janitor. If you do not start the janitor, there will be no passive deletion of expired keys.

Server

For the sake of convenience, a ready-to-go cache server is available through the server package.

As an application

package main

import (
    "github.com/TwinProduction/gocache"
    gocacheserver "github.com/TwinProduction/gocache/server"
)

func main() {
    cache := gocache.NewCache().WithEvictionPolicy(gocache.LeastRecentlyUsed).WithMaxSize(100000)
    server := gocacheserver.NewServer(cache).WithPort(6379)
    // This is a blocking function, therefore, you are expected to run this on a goroutine
    server.Start()
}

The reason why the server is in a different package is because gocache limit its external dependencies to the strict minimum (e.g. boltdb for persistence), however, rather than re-inventing the wheel, the server implementation uses redcon, which is a very good Redis server framework for Go.

That way, those who desire to use gocache without the server will not add any extra dependencies as long as they don't import the server package.

If you'd like to run it through the CLI:

go run cmd/server/main.go

Any Redis client should be able to interact with the server, though only the following instructions are supported:

• GET
• SET
• DEL
• PING
• QUIT
• INFO
• EXPIRE
• SETEX
• TTL
• FLUSHDB
• EXISTS
• ECHO
• MGET
• MSET
• SCAN (kind of - cursor is not currently supported)
• KEYS

Running the server with Docker

docker run --name gocache-server -p 6379:6379 twinproduction/gocache-server

To build it locally, refer to the Makefile's docker-build and docker-run steps.

Performance

Summary

• Set: Both map and gocache have the same performance.
• Get: Map is faster than gocache.

This is because gocache keeps track of the head and the tail for eviction and expiration/TTL.

Ultimately, the difference is negligible.

We could add a way to disable eviction or disable expiration altogether just to match the map's performance, but if you're looking into using a library like gocache, odds are, you want more than just a map.

Results

key	value
goos	windows
goarch	amd64
cpu	i7-9700K
mem	32G DDR4

// Normal map
BenchmarkMap_Get
BenchmarkMap_Get-8                                                              46087372  26.7 ns/op
BenchmarkMap_Set                                                                   
BenchmarkMap_Set/small_value-8                                                   3841911   389 ns/op
BenchmarkMap_Set/medium_value-8                                                  3887074   391 ns/op
BenchmarkMap_Set/large_value-8                                                   3921956   393 ns/op
// Gocache                                                                         
BenchmarkCache_Get                                                                 
BenchmarkCache_Get/FirstInFirstOut-8                                            27273036  46.4 ns/op
BenchmarkCache_Get/LeastRecentlyUsed-8                                          26648248  46.3 ns/op
BenchmarkCache_Set                                                              
BenchmarkCache_Set/FirstInFirstOut_small_value-8                                 2919584   405 ns/op
BenchmarkCache_Set/FirstInFirstOut_medium_value-8                                2990841   391 ns/op
BenchmarkCache_Set/FirstInFirstOut_large_value-8                                 2970513   391 ns/op
BenchmarkCache_Set/LeastRecentlyUsed_small_value-8                               2962939   402 ns/op
BenchmarkCache_Set/LeastRecentlyUsed_medium_value-8                              2962963   390 ns/op
BenchmarkCache_Set/LeastRecentlyUsed_large_value-8                               2962928   394 ns/op
BenchmarkCache_SetUsingMaxMemoryUsage                                           
BenchmarkCache_SetUsingMaxMemoryUsage/small_value-8                              2683356   447 ns/op
BenchmarkCache_SetUsingMaxMemoryUsage/medium_value-8                             2637578   441 ns/op
BenchmarkCache_SetUsingMaxMemoryUsage/large_value-8                              2672434   443 ns/op
BenchmarkCache_SetWithMaxSize                                                   
BenchmarkCache_SetWithMaxSize/100_small_value-8                                  4782966   252 ns/op
BenchmarkCache_SetWithMaxSize/10000_small_value-8                                4067967   296 ns/op
BenchmarkCache_SetWithMaxSize/100000_small_value-8                               3762055   328 ns/op
BenchmarkCache_SetWithMaxSize/100_medium_value-8                                 4760479   252 ns/op
BenchmarkCache_SetWithMaxSize/10000_medium_value-8                               4081050   295 ns/op
BenchmarkCache_SetWithMaxSize/100000_medium_value-8                              3785050   330 ns/op
BenchmarkCache_SetWithMaxSize/100_large_value-8                                  4732909   254 ns/op
BenchmarkCache_SetWithMaxSize/10000_large_value-8                                4079533   297 ns/op
BenchmarkCache_SetWithMaxSize/100000_large_value-8                               3712820   331 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU                                             
BenchmarkCache_SetWithMaxSizeAndLRU/100_small_value-8                            4761732   254 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/10000_small_value-8                          4084474   296 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/100000_small_value-8                         3761402   329 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/100_medium_value-8                           4783075   254 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/10000_medium_value-8                         4103980   296 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/100000_medium_value-8                        3646023   331 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/100_large_value-8                            4779025   254 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/10000_large_value-8                          4096192   296 ns/op
BenchmarkCache_SetWithMaxSizeAndLRU/100000_large_value-8                         3726823   331 ns/op
BenchmarkCache_GetSetMultipleConcurrent                                         
BenchmarkCache_GetSetMultipleConcurrent-8                                         707142  1698 ns/op
BenchmarkCache_GetSetConcurrentWithFrequentEviction
BenchmarkCache_GetSetConcurrentWithFrequentEviction/FirstInFirstOut-8            3616256   334 ns/op
BenchmarkCache_GetSetConcurrentWithFrequentEviction/LeastRecentlyUsed-8          3636367   331 ns/op
BenchmarkCache_GetConcurrentWithLRU                                              
BenchmarkCache_GetConcurrentWithLRU/FirstInFirstOut-8                            4405557   268 ns/op
BenchmarkCache_GetConcurrentWithLRU/LeastRecentlyUsed-8                          4445475   269 ns/op
BenchmarkCache_WithForceNilInterfaceOnNilPointer
BenchmarkCache_WithForceNilInterfaceOnNilPointer/true_with_nil_struct_pointer-8  6184591   191 ns/op
BenchmarkCache_WithForceNilInterfaceOnNilPointer/true-8                          6090482   191 ns/op
BenchmarkCache_WithForceNilInterfaceOnNilPointer/false_with_nil_struct_pointer-8 6184629   187 ns/op
BenchmarkCache_WithForceNilInterfaceOnNilPointer/false-8                         6281781   186 ns/op
(Trimmed "BenchmarkCache_" for readability)
WithForceNilInterfaceOnNilPointerWithConcurrency
WithForceNilInterfaceOnNilPointerWithConcurrency/true_with_nil_struct_pointer-8  4379564   268 ns/op
WithForceNilInterfaceOnNilPointerWithConcurrency/true-8                          4379558   265 ns/op
WithForceNilInterfaceOnNilPointerWithConcurrency/false_with_nil_struct_pointer-8 4444456   261 ns/op
WithForceNilInterfaceOnNilPointerWithConcurrency/false-8                         4493896   262 ns/op

FAQ

How can I persist the data on application termination?

Because this library doesn't persist immediately after every write operations, persistence is instead expected to be done on a schedule, like for instance, every 10 minutes.

While this prevents you from losing all of your data, you may still lose some data if the application stopped 9 minutes after the previous "auto save".

To increase your odds of not losing any data, you can use Go's signal package, more specifically its Notify function which allows listening for termination signals like SIGTERM and SIGINT. Once a termination signal is caught, you can add the necessary logic for a graceful shutdown.

In the following example, the code that would usually be present in the main function is moved to a different function named Start which is launched on a different goroutine so that listening for a termination signals is what blocks the main goroutine instead:

package main

import (
    "log"
    "os"
    "os/signal"
    "syscall"

    "github.com/TwinProduction/gocache"
)

const CacheFile = "gocache.data"

var cache = gocache.NewCache()

func main() {
    // Load persisted data from file
    cache.ReadFromFile(CacheFile)
    // Start everything else on another goroutine to prevent blocking the main goroutine
    go Start()
    // Wait for termination signal
    sig := make(chan os.Signal, 1)
    done := make(chan bool, 1)
    signal.Notify(sig, os.Interrupt, syscall.SIGTERM)
    go func() {
        <-sig
        log.Println("Received termination signal, attempting to gracefully shut down")
        err := cache.SaveToFile(CacheFile)
        if err != nil {
            log.Println("Failed to save storage provider:", err.Error())
        }
        done <- true
    }()
    <-done
    log.Println("Shutting down")
}

Note that this won't protect you from a SIGKILL, as this signal cannot be caught.

How can I automatically save the cache to a file every 5 minutes?

Beside using the suggestion above, automatically persisting the cache on an interval will protect your application from sudden terminations triggered by signals that cannot be caught, such as the force kill signal received by an application being OOMKilled.

The simplest implementation could be something like this:

const CacheFile = "gocache.data"

func main() {
    cache := gocache.NewCache()
    cache.ReadFromFile(CacheFile)
    go autoSave(10*time.Minute)
    // ...
}

func autoSave(interval time.Duration) {
    for {
        err := cache.SaveToFile(CacheFile)
        if err != nil {
            log.Println("Failed to persist cache to file:", err.Error())
        }
        time.Sleep(interval)
    }
}

Why does the memory usage not go down?

Note

: As of Go 1.16, this no longer applies. See golang/go#42330

By default, Go uses MADV_FREE if the kernel supports it to release memory, which is significantly more efficient than using MADV_DONTNEED. Unfortunately, this means that RSS doesn't go down unless the OS actually needs the memory.

Technically, the memory is available to the kernel, even if it shows a high memory usage, but the OS will only use that memory if it needs to. In the case that the OS does need the freed memory, the RSS will go down and you'll notice the memory usage lowering.

reference

You can reproduce this by following the steps below:

• Start the server
• Note the memory usage
• Create 500k keys
• Note the memory usage
• Flush the cache
• Note that the memory usage has not decreased, despite the cache being empty.

Substituting gocache for a normal map will yield the same result.

If the released memory still appearing as used is a problem for you, you can set the environment variable GODEBUG to madvdontneed=1.