As far as distributed locks are concerned, a common problem is that if a service setnx is successful, but if there is a downtime or some special factors during unlocking, it cannot be unlocked. Then other services will fall into a deadlock state. Therefore, while using setnx, we want to use the expire instruction to perform an expiration operation on the lock. From the instructions, we can see that the setnx and expire instructions are separate. If there are special factors during the gap in the process, the instruction cannot continue. , will also lead to deadlock.
Solution:
import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.data.redis.core.StringRedisTemplate; import org.springframework.stereotype.Component; import org.springframework.util.StringUtils; @Component public class RedisLock { Logger logger = LoggerFactory.getLogger(this.getClass()); @Autowired private StringRedisTemplate redisTemplate; /** * 加锁 * @param key * @param value 当前时间 + 超时时间 * @return */ public boolean lock(String key, String value) { if (redisTemplate.opsForValue().setIfAbsent(key, value)) { // 这个其实就是setnx命令,只不过在java这边稍有变化,返回的是boolean // 设置个过期时间,当然如果在这中间的空隙过程中如果有特殊因素导致指令无法继续,也会导致死锁的产生,如果死锁出现,则后续代码会处理 redisTemplate.expire(key, lockTime, TimeUnit.SECONDS); return true; } // 避免死锁,且只让一个线程拿到锁 String currentValue = redisTemplate.opsForValue().get(key); // 如果锁过期了 if (!StringUtils.isEmpty(currentValue) && Long.parseLong(currentValue) < System.currentTimeMillis()) { //获取上一个锁的时间 String oldValues = redisTemplate.opsForValue().getAndSet(key, value); /* 只会让一个线程拿到锁 如果旧的value和currentValue相等,只会有一个线程达成条件,因为第二个线程拿到的oldValue已经和currentValue不一样了 */ if (!StringUtils.isEmpty(oldValues) && oldValues.equals(currentValue)) { return true; } } return false; } /** * 解锁 * @param key * @param value */ public void unlock(String key, String value) { try { String currentValue = redisTemplate.opsForValue().get(key); if (!StringUtils.isEmpty(currentValue) && currentValue.equals(value)) { redisTemplate.opsForValue().getOperations().delete(key); } } catch (Exception e) { logger.error("redis分布式锁解锁异常,{}", e); } } }
Call:
//加锁 long time = System.currentTimeMillis() + 1000 * lockTime //超时时间:10秒,最好设为常量 boolean isLock = redisLock.lock(...keyName, String.valueOf(time)); if(!isLock){ throw new RuntimeException("系统正忙"); } // doSomething... //解锁 redisLock.unlock(...keyName, String.valueOf(time));
For more Redis related knowledge, please visit the Redis usage tutorial column!
The above is the detailed content of Will redis cause deadlock problems?. For more information, please follow other related articles on the PHP Chinese website!

Redis is a powerful database solution because it provides fast performance, rich data structures, high availability and scalability, persistence capabilities, and a wide range of ecosystem support. 1) Extremely fast performance: Redis's data is stored in memory and has extremely fast read and write speeds, suitable for high concurrency and low latency applications. 2) Rich data structure: supports multiple data types, such as lists, collections, etc., which are suitable for a variety of scenarios. 3) High availability and scalability: supports master-slave replication and cluster mode to achieve high availability and horizontal scalability. 4) Persistence and data security: Data persistence is achieved through RDB and AOF to ensure data integrity and reliability. 5) Wide ecosystem and community support: with a huge ecosystem and active community,

Key features of Redis include speed, flexibility and rich data structure support. 1) Speed: Redis is an in-memory database, and read and write operations are almost instantaneous, suitable for cache and session management. 2) Flexibility: Supports multiple data structures, such as strings, lists, collections, etc., which are suitable for complex data processing. 3) Data structure support: provides strings, lists, collections, hash tables, etc., which are suitable for different business needs.

The core function of Redis is a high-performance in-memory data storage and processing system. 1) High-speed data access: Redis stores data in memory and provides microsecond-level read and write speed. 2) Rich data structure: supports strings, lists, collections, etc., and adapts to a variety of application scenarios. 3) Persistence: Persist data to disk through RDB and AOF. 4) Publish subscription: Can be used in message queues or real-time communication systems.

Redis supports a variety of data structures, including: 1. String, suitable for storing single-value data; 2. List, suitable for queues and stacks; 3. Set, used for storing non-duplicate data; 4. Ordered Set, suitable for ranking lists and priority queues; 5. Hash table, suitable for storing object or structured data.

Redis counter is a mechanism that uses Redis key-value pair storage to implement counting operations, including the following steps: creating counter keys, increasing counts, decreasing counts, resetting counts, and obtaining counts. The advantages of Redis counters include fast speed, high concurrency, durability and simplicity and ease of use. It can be used in scenarios such as user access counting, real-time metric tracking, game scores and rankings, and order processing counting.

Use the Redis command line tool (redis-cli) to manage and operate Redis through the following steps: Connect to the server, specify the address and port. Send commands to the server using the command name and parameters. Use the HELP command to view help information for a specific command. Use the QUIT command to exit the command line tool.

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

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.


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

SublimeText3 Linux new version
SublimeText3 Linux latest version

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

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function