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- How redis gets data
- Redis provides the following ways to obtain data: GET: Get the value of the specified key. MGET: Get the values of multiple keys at the same time. HGET: Get the value of the specified field in the hash table. HGETALL: Get the values of all fields in the hash table. LINDEX: Gets the element at the specified index in the list. LRANGE: Get the elements in the specified range in the list.
- Redis 787 2024-04-20 01:12:19
- How to get all keys in redis
- Method to get all keys in Redis: KEYS command: Get all key names matching the specified pattern. SCAN command: iteratively obtain all key names. DUMP combined with the EVAL command: export the values of all keys and get the key names. Using the Redis client library: Use the keys() method provided by the corresponding library to obtain the key name.
- Redis 457 2024-04-20 01:09:27
- How to get data in redis
- Common ways to obtain data in Redis are: GET: directly obtain the value of the specified key. MGET: Get the values of multiple keys at the same time and return a list. HGET: Get the value of the specified field in the hash table. HMGET: Get the values of multiple fields in the hash table and return a list. LRANGE: Get the elements in the specified range in the list. ZRANGE: Gets elements within a specified range in an ordered collection. ZREVRANGE: Get the elements in the specified range in the ordered set, sorted from large to small.
- Redis 295 2024-04-20 01:03:39
- How does redis ensure consistency with the database
- To ensure data consistency between Redis and the database, the following methods can be used: Transactional updates: Encapsulate Redis and database updates into atomic transactions to avoid inconsistencies. Optimistic locking: monitor the key to be updated and check whether the key has been modified before updating to avoid concurrency conflicts. Publish-Subscribe: Use a Redis channel to publish messages, and subscribers update data to maintain consistency. Data replication: Replicate data between Redis instances through master-slave replication or sentinel mechanism to ensure data consistency. Batch update: Batch a large number of updates to reduce the number of communications and improve performance and consistency.
- Redis 624 2024-04-20 01:00:27
- 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 642 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 781 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 756 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 1011 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 583 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 661 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 558 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 927 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 545 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 849 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 1022 2024-04-20 00:09:15
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