How to use caching to improve audio and video processing performance in Golang?

In recent years, with the rapid development of the Internet and mobile Internet and the popularization of 5G networks, the demand for audio and video processing has become higher and higher, and Golang, as an efficient programming language, is adopted by more and more developers. Using cache to improve audio and video processing performance has become a classic problem in Golang development. This article will introduce how to use caching technology in Golang to improve audio and video processing performance.

1. What is caching technology?

Caching technology is a way to optimize data access, with the goal of speeding up data reading and writing. In programming, caches are commonly used to store frequently used data for quick access. The cache can be regarded as an intermediary storage layer for data. When data needs to be obtained, the cache is accessed first. If the required data is in the cache, it is returned directly. Otherwise, the data is obtained from the data source and stored in the cache for next time. Quick access.

2. Bottlenecks in audio and video processing

One of the most common bottlenecks in audio and video processing is the IO bottleneck. Due to the large amount of audio and video data, processing is very time-consuming. Data often needs to be read from disk or network, and these IO operations are very time-consuming. Therefore, the performance of IO operations is usually the main factor affecting audio and video processing efficiency.

3. How to use caching to improve audio and video processing performance?

In order to optimize audio and video processing performance, we can use caching technology to reduce IO operations to improve audio and video processing efficiency. Specifically, memory cache or disk cache can be used to accelerate audio and video processing.

3.1. Memory cache

Memory cache can greatly reduce the number of IO operations, thereby improving audio and video processing efficiency. In Golang, we can use sync.Map or LRU cache to implement memory caching. Among them, sync.Map is a thread-safe hash table that supports concurrent reading and writing, while LRU cache is a caching method based on the least recently used principle (Least Recently Used), which is suitable for large amounts of data but difficult access. Relatively low frequency application scenarios.

Below, we take video screenshots as an example to illustrate how to use sync.Map to implement memory caching:

import "sync"
var cache sync.Map
func GetThumbnailFromCache(videoID string) ([]byte, error) {
    if v, ok := cache.Load(videoID); ok {
        return v.([]byte), nil
    } else {
        thumbnail, err := GetThumbnailFromVideo(videoID)
        if err != nil {
            return nil, err
        }
        cache.Store(videoID, thumbnail)
        return thumbnail, nil
    }
}

In the above code, we first try to get the video screenshots in the cache. If Once obtained, return directly, otherwise, obtain the video screenshot from the video file and store it in the cache for subsequent quick access.

3.2. Disk cache

When the memory capacity is insufficient, we can use disk cache to expand the cache. Disk cache stores data on the hard disk, which can effectively avoid data loss and memory leak problems, but compared to memory cache, disk cache has slower access speed. If the access frequency is high, it is recommended to use memory cache. If the access frequency is low, disk cache can be used.

In Golang, we can use go-cache or bigcache to implement disk caching. Among them, go-cache is a general memory and disk caching library, and most data types can be cached. Bigcache is specially used to cache structures and other complex types, and has higher performance.

Below, we take video transcoding as an example to illustrate how to use go-cache to implement disk caching:

import (
    "github.com/patrickmn/go-cache"
    "os"
)
var c = cache.New(24*time.Hour, 24*time.Hour)
func Transcode(videoID string) error {
    var result error
    if v, ok := c.Get(videoID); ok {
        result = DoTranscode(v.([]byte))
    } else {
        videoFile, err := os.Open("path/to/video")
        if err != nil {
            return err
        }
        defer videoFile.Close()
        videoData, err := ioutil.ReadAll(videoFile)
        if err != nil {
            return err
        }
        result = DoTranscode(videoData)
        c.Set(videoID, videoData, cache.DefaultExpiration)
    }
    return result
}

In the above code, we first try to obtain the video data in the cache, If it is obtained, it will be transcoded directly. Otherwise, the data will be read from the video file and transcoded. Finally, the transcoded result will be stored in the cache for subsequent quick access.

4. Summary

Caching technology is a way to optimize data access, which can effectively improve audio and video processing efficiency. In Golang, we can use sync.Map, LRU cache, go-cache, bigcache and other tools to implement memory or disk caching. Which method to choose needs to be evaluated based on the actual situation. Finally, I hope this article can help Golang developers improve audio and video processing performance.

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