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- How to ensure consistency between redis and mysql
- Methods to ensure consistency between Redis and MySQL include direct writing to MySQL and transaction compensation mechanism: direct writing to MySQL: synchronizing MySQL data changes to Redis through triggers, ensuring consistency but lower performance; transaction compensation mechanism: writing to Redis first , while recording compensation transactions, tolerating short-term unavailability, but with slightly lower consistency and higher system complexity.
- Redis 643 2024-04-20 00:57:18
- How to solve the inconsistency between redis cache and database double write
- To solve the double-write inconsistency problem between the Redis cache and the database, the following methods can be used: Use queues: Put the data update request into the queue, ensuring that it is written to the database first and then the cache is updated. Use optimistic locking: Check whether the data has been modified when updating. If it has been modified, cancel the update and notify to try again. Use event mechanism: When the database is updated, an event is triggered to notify the application to update the cache, and the application needs to listen to the database update event. Use pessimistic locking: Lock related records before writing to the database to prevent other processes from updating the same record at the same time. Use eventual consistency: Allow the cache and database to be temporarily inconsistent and rely on the application's eventual consistency mechanism to ensure eventual consistency.
- Redis 782 2024-04-20 00:54:41
- How to solve redis cache breakdown
- Methods to solve Redis cache breakdown: Use distributed locks to prevent concurrent cache queries, allowing lock-holding requests to obtain data and update the cache; limit current to reduce database pressure and prevent too many concurrent queries; cache null values to prevent direct access to the database , and force retry later; preload hotspot data in advance to ensure availability; start asynchronous tasks to load data asynchronously to avoid simultaneous database access.
- Redis 757 2024-04-20 00:49:14
- How redis avoids cache penetration
- Redis uses the following methods to avoid cache penetration: 1. Use Bloom filters; 2. Set default values; 3. Use empty objects; 4. Use expiration time. Through these methods, Redis can effectively prevent requests from penetrating directly to the database, thereby reducing database pressure.
- Redis 1012 2024-04-20 00:45:27
- How to test redis cache
- Redis cache testing methods include: Using Redis CLI commands to check cache status Using third-party libraries (such as Lettuce, Jedis) for more complex tests Test content involves: Functional testing: Check basic functions (setting, getting key-value pairs, expiration time, batch Operations) Performance testing: Evaluates throughput, latency, memory usage Stability testing: Checks for concurrency, network failures, data corruption Integration testing: Evaluates cache integration with the application (hit rate, invalidations, data consistency)
- Redis 584 2024-04-20 00:38:57
- How to solve redis cache penetration
- Redis cache penetration means that keys that do not exist in the cache will be directly queried in the database every time. The following measures can be taken to solve this problem: 1. Use Bloom filters to quickly determine whether the key exists; 2. Use null value cache to cache values that do not exist. ; 3. Apply cache penetration protection algorithm (funnel algorithm, sliding window counter) to limit query frequency; 4. Optimize database query statements; 5. Strengthen data verification to avoid illegal key query cache.
- Redis 662 2024-04-20 00:33:16
- How to implement redis lock
- Redis lock uses the Redis database to implement a mutex lock: the key is set atomically through the SETNX command, and no operation is performed if the key exists. Use the EXPIRE command to set the key expiration time. Delete the key after acquiring the lock to release the lock.
- Redis 560 2024-04-20 00:27:43
- How to solve redis cache penetration
- Cache penetration refers to malicious users constantly querying data that does not exist in the database, resulting in performance degradation. Solutions include: setting default values, using bloom filters, using verification code mechanisms to limit traffic, slow query log analysis, and strengthening data verification.
- Redis 928 2024-04-20 00:26:18
- What is redis cache penetration
- Cache penetration means that data not stored in the cache directly accesses the database, which can be solved through bloom filters, null value caching, and circuit breaker mechanisms.
- Redis 546 2024-04-20 00:18:31
- The operation of redis is multi-threaded
- The multi-threading of Redis enables the Redis server to handle requests from multiple threads at the same time, improving concurrent processing capabilities and reducing latency. Redis achieves multi-threading by using I/O multiplexing technology, allowing a single thread to monitor multiple socket file descriptors and handle requests from multiple sockets at the same time.
- Redis 850 2024-04-20 00:12:23
- Are redis operations atomic?
- Atomic operations: INCR, DECR, INCRBY, DECRBY, GETSET, SETNX. They are uninterruptible and either execute completely or not at all. Non-atomic operations: SET, SETEX, DEL. They may be interrupted, causing data inconsistency. Atomicity is crucial to guarantee data consistency, especially when multiple clients access the same data at the same time.
- Redis 1023 2024-04-20 00:09:15
- The relationship between redis and database
- Redis and database are different data storage systems. Redis is an in-memory database that emphasizes high-performance reading and writing and flexible data structures, while the database is a persistent database that emphasizes data persistence and structured queries. Therefore, they can be used complementary, with Redis serving as a cache or temporary storage to accelerate database read and write operations and reduce database pressure.
- Redis 1113 2024-04-20 00:08:50
- redis delete cached code
- Redis provides the following methods to delete the cache: DEL command: delete the cache value corresponding to the specified key UNLINK command: mark the key as deleted and delete it on the next restart FLUSHALL command: delete the cache value corresponding to all keys in the database FLUSHDB command: delete the cache value in the current database Cache values corresponding to all keys
- Redis 328 2024-04-20 00:00:31
- How to solve the problem of redis deletion cache failure
- For the problem of Redis cache deletion failure, the reasons and solutions are as follows: The key does not exist: Use the EXISTS command to check whether the key exists. Wrong key type: Make sure the key is a string key. This can be checked using the TYPE command. Internal server error: Check the Redis log for troubleshooting. Connection error: Check if the Redis server is running and accessible. Timeout exception: Increase the timeout period of the DEL command. Client errors: Check client code and network. Access control: Make sure the client has delete permission. Cluster partitioning: ensures that all nodes are in sync with data. Other suggestions: Use transactions for efficiency, regularly clean up expired keys, monitor the Redis server, and enable logging for troubleshooting
- Redis 386 2024-04-19 23:54:27
- What to do if redis fails to delete cache
- Reasons for Redis cache deletion failure include: key does not exist, key is locked, server is busy, network problems, configuration errors, data corruption, insufficient permissions. The countermeasures are: confirm the existence of the key, wait for the lock to be released, try again later or relieve the load, check the network connection, check the configuration, repair the data or restore the backup, and grant deletion permission. If the above measures don't work, you can check the Redis logs or contact the Redis support team.
- Redis 533 2024-04-19 23:53:03
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