How to detect database changes when redis is caching

The steps for troubleshooting and repairing Redis master-slave replication failures include: 1. Check the network connection and use ping or telnet to test connectivity; 2. Check the Redis configuration file to ensure that the replicaof and repl-timeout are set correctly; 3. Check the Redis log file and find error information; 4. If it is a network problem, try to restart the network device or switch the alternate path; 5. If it is a configuration problem, modify the configuration file; 6. If it is a data synchronization problem, use the SLAVEOF command to resync the data.

The quick location and processing steps for Redis cluster node failure are as follows: 1. Confirm the fault: Use the CLUSTERNODES command to view the node status. If the fail is displayed, the node will fail. 2. Determine the cause: Check the network, hardware, and configuration. Common problems include memory limits exceeding. 3. Repair and restore: Take measures based on the reasons, such as restarting the service, replacing the hardware or modifying the configuration. 4. Notes: Ensure data consistency, select appropriate failover policies, and establish monitoring and alarm systems.

Effective solutions to the problem of split brain in Redis cluster include: 1) Network configuration optimization to ensure connection stability; 2) Node monitoring and fault detection, real-time monitoring with tools; 3) Failover mechanism, setting high thresholds to avoid multiple master nodes; 4) Data consistency guarantee, using replication function to synchronize data; 5) Manual intervention and recovery, and manual processing if necessary.

Redis and RabbitMQ each have their own advantages in performance and joint application scenarios. 1.Redis performs excellently in data reading and writing, with a latency of up to microseconds, suitable for high concurrency scenarios. 2.RabbitMQ focuses on messaging, latency at milliseconds, and supports multi-queue and consumer models. 3. In joint applications, Redis can be used for data storage, RabbitMQ handles asynchronous tasks, and improves system response speed and reliability.

Methods to improve Redis persistence performance through configuration include: 1. Adjust the save parameters of RDB to reduce the snapshot generation frequency; 2. Set the appendfsync parameter of AOF to everysec; 3. Use AOF and RDB in combination; 4. Use no-appendfsync-on-rewrite parameters to optimize AOF rewrite performance; 5. Enable hybrid persistence mode. These configurations can improve performance while ensuring data security.

The Redis collection is selected to implement data deduplication because it supports quick insertion and search, and it automatically deduplication. 1) The Redis collection is based on an ordered collection structure without repeat elements, and is suitable for scenarios where quick insertion and query are required. 2) But you need to pay attention to its memory usage, because each element occupies memory. 3) It can be optimized for use through shard storage, regular cleaning and combined with other storage.

To realize text error correction and syntax optimization with AI, you need to follow the following steps: 1. Select a suitable AI model or API, such as Baidu, Tencent API or open source NLP library; 2. Call the API through PHP's curl or Guzzle and process the return results; 3. Display error correction information in the application and allow users to choose whether to adopt it; 4. Use php-l and PHP_CodeSniffer for syntax detection and code optimization; 5. Continuously collect feedback and update the model or rules to improve the effect. When choosing AIAPI, focus on evaluating accuracy, response speed, price and support for PHP. Code optimization should follow PSR specifications, use cache reasonably, avoid circular queries, review code regularly, and use X

Through tools such as redis-cli, RedisInsight, Prometheus and Grafana, as well as focusing on memory usage, number of connections, cluster node status, data consistency and performance indicators, the health status of the Redis cluster can be effectively monitored.