Table of contents [ hide ] Basic theory CAP States that any distributed data store can provide only two of the following three guarantees. Consistency Every read receives the most recent write or an error. Availability Every request receives a (non-error) response, without the guarantee that it contains the most recent write. Partition tolerance The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes. Typical architecture of distributed systems When a network partition failure happens, it must be decided whether to do one of the following: CP: cancel the operation and thus decrease the availability but ensure consistency AP: proceed with the operation and thus provide availability but risk inconsistency. BASE Basically-available, soft-state, eventual consistency. Base theory is the practical application of CAP theory, that is, under the premise of the existence of partitions and copies, through certain syste
Table of contents [ hide ] Redis To improve response time and avoid the burden on the database, caching is a commonly used tool, and Redis is the most famous and best caching tool. Basic Operation SRING Save string, integer or double. LIST Linked list, we can prune nodes like list or queue. SET Like HashSet, the values in the set are unique. HASH Often objects with multiple properties are saved. ZSET Same as linked hashmap, with orderliness. Advanced Operation Math operation. Element operations, such as union and heteroset. Key operations such as checking existence or getting all keys. Key expire operation. Backup RDB Snapshot of all data, fast recovery. AOF Operation log appending, recovery is slow. Backup thread operations save: the operation will stop the client threads. bgsave: the operation add new a thread to do backup. After redis4.0, you can use rewrite Aof with Rdb + Aof to reduce recovery time and save volume. Usage Single Testing or basic use of small machines. Mast