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CORS (cross origin resource sharing) cross-domain resource sharing , which allows cross-site resource requests. The client needs to use a specific method to request resources (such as xmlhttprequest) and needs to bring specific header information. The server must also support cross-domain resource requests
memcache can utilize multi-threading, has high throughput, and is suitable for large visits
memcache only supports simple key/value structures
memcache cannot persist data and cannot be backed up. It can only be used for caching. Data will be lost after restarting.
Because memcache supports multiple Thread operation, so the issue of data consistency must be considered, and cas (check and set) optimistic locking is used
Since redis is single-formed, it can ensure the orderliness of operations
Redis supports a variety of data structures, key/value, list, set, zset, dict, etc.
Redis data can be stored persistently. Store the data in the disk and can read it out when restarting again
redis supports data backup, that is, data backup in master-slave mode
Static html, statically use commonly used but rarely updated data
Separate image servers to avoid Affects the application server. At the same time, individual configuration optimization, cache settings, etc. can be performed for the picture server.
Database cluster, library table hash
Database cluster can realize reading and writing separation and improve the database response speed. It is generally one master and multiple slaves, or x master and y slave. For example, when writing less and reading more, one server is dedicated to writing operations, and other servers are used for reading operations. This can avoid the impact of read-write locks. However, after the write operation is completed, the data needs to be synchronized.
Another benefit of a database cluster is that when one database server goes down, there is still complete data on other servers
In a distributed database, there are multiple nodes in the system, and each node performs different functions. If a node dies, the corresponding function cannot be completed.
The difference between database cluster and distributed database. Suppose a task takes one hour to complete on one node, and there are now 10 such tasks and 10 nodes. The distributed database can split the task into 10 tasks. Each node completes a different task, regardless of the dependencies of the subtasks. All tasks will be completed after an hour. Each node in the database cluster can complete a complete task. It can average 10 tasks to each node, so that all tasks are completed after one hour.
sql optimization
If there is too much data in the table, you can consider splitting the table and then using hash mapping
Index optimization
Cache
Mirror, used to improve access speed
Load balancing, solving high concurrency and massive access problems
CDN, allowing users to access the nearest cdn server and get the fastest response
Data compression
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