Detailed explanation of distributed counter implementation in Redis
With the rapid development of the Internet, the number of concurrent visits to Web applications is also increasing. How to quickly respond to concurrent requests has become an important issue in Web application design. Among them, distributed counters are widely used in scenarios such as flow control and current limiting. This article will introduce in detail how Redis implements distributed counters.
- Introduction to Redis
Redis is a high-performance cache database that supports rich data structures, such as strings, hash tables, lists, sets, etc. At the same time, Redis also provides some advanced features, such as publish/subscribe, transactions, etc., supporting a variety of application scenarios. Redis has the following characteristics:
1.1 High performance
Redis adopts a memory-based data storage method and can provide high-speed reading and writing performance. In addition, Redis also supports persistence operations on data and can cope with data loss under abnormal circumstances.
1.2 Distributed
Redis provides support for distributed databases and can achieve high availability of data through master-slave replication, sentinels, etc.
1.3 Multi-language support
Redis provides client libraries in multiple languages, supporting multiple programming languages such as Java, Python, PHP, and Ruby, so developers can easily develop.
- Redis distributed counter
2.1 Implementation method
There are two main ways for Redis to implement distributed counter:
2.1 .1 Loop competition counter
The implementation of loop competition counter is relatively simple. The basic idea is to use the atomic operation of Redis to realize the self-increment operation of the counter. The bottleneck of this method is competition. High concurrency environments will cause too much competition, which will affect the performance of the entire system. Therefore, this method is suitable for low concurrency scenarios, and other methods should be used for high concurrency scenarios.
2.1.2 Redis Lua script
Redis Lua script is a lightweight scripting language based on Redis atomic operations and supports multiple data types and operations. In Redis, Lua scripts are widely used to implement distributed locks, current limiting, counters and other functions. Below we will implement distributed counters based on Redis Lua script.
2.2 Redis Lua script implementation
The basic execution method of Redis Lua script is "atomic transaction", which ensures the uniqueness and consistency of the operation. According to the characteristics of the counter, we use the INCRBY command of Redis to encapsulate the counter's self-increment operation through a Lua script. The following is the specific implementation code:
local count = redis.call("INCRBY", KEYS[1], ARGV[1]) if tonumber(count) == tonumber(ARGV[2]) then redis.call("EXPIRE", KEYS[1], ARGV[3]) end return count
Among them, KEYS[i] and ARGV[i] represent the parameters of the Lua script and the Redis key value respectively. The code flow is as follows:
- Use the INCRBY command to increment the counter.
- Determine whether the counter value is equal to the preset value. If equal, set the counter's expiration time to the preset time.
- Return the latest value of the counter.
In this way, we can implement distributed counters based on Redis. Among them, the expiration time setting of the counter is to prevent the counter from accumulating all the time, which will bring performance and memory risks.
- Summary
This article introduces in detail how Redis implements distributed counters, including the basic concepts of Redis, the implementation of distributed counters, Redis Lua script implementation and requirements Attention to details etc. How to use distributed counters effectively requires comprehensive consideration based on specific business scenarios and performance requirements.
The above is the detailed content of Detailed explanation of distributed counter implementation in Redis. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



Redis cluster mode deploys Redis instances to multiple servers through sharding, improving scalability and availability. The construction steps are as follows: Create odd Redis instances with different ports; Create 3 sentinel instances, monitor Redis instances and failover; configure sentinel configuration files, add monitoring Redis instance information and failover settings; configure Redis instance configuration files, enable cluster mode and specify the cluster information file path; create nodes.conf file, containing information of each Redis instance; start the cluster, execute the create command to create a cluster and specify the number of replicas; log in to the cluster to execute the CLUSTER INFO command to verify the cluster status; make

How to clear Redis data: Use the FLUSHALL command to clear all key values. Use the FLUSHDB command to clear the key value of the currently selected database. Use SELECT to switch databases, and then use FLUSHDB to clear multiple databases. Use the DEL command to delete a specific key. Use the redis-cli tool to clear the data.

Using the Redis directive requires the following steps: Open the Redis client. Enter the command (verb key value). Provides the required parameters (varies from instruction to instruction). Press Enter to execute the command. Redis returns a response indicating the result of the operation (usually OK or -ERR).

Using Redis to lock operations requires obtaining the lock through the SETNX command, and then using the EXPIRE command to set the expiration time. The specific steps are: (1) Use the SETNX command to try to set a key-value pair; (2) Use the EXPIRE command to set the expiration time for the lock; (3) Use the DEL command to delete the lock when the lock is no longer needed.

To read a queue from Redis, you need to get the queue name, read the elements using the LPOP command, and process the empty queue. The specific steps are as follows: Get the queue name: name it with the prefix of "queue:" such as "queue:my-queue". Use the LPOP command: Eject the element from the head of the queue and return its value, such as LPOP queue:my-queue. Processing empty queues: If the queue is empty, LPOP returns nil, and you can check whether the queue exists before reading the element.

Redis uses hash tables to store data and supports data structures such as strings, lists, hash tables, collections and ordered collections. Redis persists data through snapshots (RDB) and append write-only (AOF) mechanisms. Redis uses master-slave replication to improve data availability. Redis uses a single-threaded event loop to handle connections and commands to ensure data atomicity and consistency. Redis sets the expiration time for the key and uses the lazy delete mechanism to delete the expiration key.

The best way to understand Redis source code is to go step by step: get familiar with the basics of Redis. Select a specific module or function as the starting point. Start with the entry point of the module or function and view the code line by line. View the code through the function call chain. Be familiar with the underlying data structures used by Redis. Identify the algorithm used by Redis.

Redis, as a message middleware, supports production-consumption models, can persist messages and ensure reliable delivery. Using Redis as the message middleware enables low latency, reliable and scalable messaging.
