Redis cluster is a distributed, fault-tolerant Redis implementation. The functions that can be used by the cluster are a subset of the functions that can be used by ordinary stand-alone Redis. (subset).
There is no central node or proxy node in the Redis cluster. One of the main design goals of the cluster is to achieve linear scalability.
Redis Cluster provides a way to run Redis where data is automatically partitioned across multiple Redis nodes. Redis Cluster also provides a level of availability during partitioning, which is the ability to continue running even if some nodes fail or cannot communicate. However, if a major failure occurs (for example, when most masters are unavailable), the cluster will stop functioning.
Redis cluster is a distributed implementation of Redis. It is a mesh structure, and each node is connected to every other node through a TCP connection.
Now let’s take a look at what goals the Redis cluster has achieved?
Still performs well with 1000 nodes and the scalability is linear. Asynchronous replication is used between clusters, and there is no merge operation.
Acceptable write safety (Write safety) level: The system attempts to save all write operations performed by clients connected to the majority of nodes. However, a small portion of writes will still be lost.
Availability: The vast majority of master nodes are reachable, and for every unreachable master node there is at least one reachable slave node. In this case, the Redis cluster can still perform partition operations.
So is there any functional difference between the Redis cluster environment and the non-distributed Redis environment?
The database of the cluster has only 0 and does not support SELECT.
Since the cluster distributes keys in different slots, copy operations involving multi-key values are not supported, such as unions and intersections in set.
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Redis's database methods include in-memory databases and key-value storage. 1) Redis stores data in memory, and reads and writes fast. 2) It uses key-value pairs to store data, supports complex data structures such as lists, collections, hash tables and ordered collections, suitable for caches and NoSQL databases.

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


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