Redis common sense

disk ：

（1） Addressing ms （2） bandwidth （ How much data flow per unit time ）ns

Memory ：

（1） Addressing ns The disk is slower than the internal address 10w times

I/O buffer： The question of cost

A disk has tracks and sectors ： One sector 512Byte The cost of indexing increases

When formatting the disk, there is a 4K alignment ： Read less than 4K Of , return 4K

No matter how much you read from the disk , It's all the least 4K

The data in the file , As the file gets bigger , Slow down （ The file gets bigger , Hard disk （i/o） Become a bottleneck ） 

data page （ size 4K）

Index building , Speed up

Create tables for relational databases , Must give schema（ Columns of the table , The type of each column ）, The width of each row of data is fixed , Prefer row level storage .

There is one in memory B+ Trees , leaf （data page）, The trunk is also in memory

SQL Of where In the condition of , Just hit the index , Inquire about B+ The tree will walk the trunk , Find the leaves , Read from disk to memory .

（ Index in memory , It will cause insufficient memory , So the index and data are on disk ）

The table of the database is very large , Performance will become lower ？

If the table has an index , Add, delete and change will slow down .

Queries are slower ？

（1）1 One or a few queries are still very fast

（2） When the concurrency is large, the speed will be affected by the bandwidth of the hard disk

Large amount of data , How to quickly query the database  

（ disk 、 Memory compromise ） cache ：memcached、redis

Computer system 2 Infrastructure ： The hardware of von Neumann system 、 Ethernet and TCP/IP Network of

The volume of disk and memory are different ： There is no pointer concept in the disk  

Redis It's open source （BSD The license ） Of , Data structure storage system in memory , It can be used as a database 、 Caching and message middleware .

It supports multiple types of data structures , Such as character string （strings）, hash （hashes）, list （lists）, aggregate （sets）, Ordered set （sorted sets） And scope query , bitmaps,hyperloglogs and Geographical space （geospatial） Index radius query . 

Redis Built in Copy （replication）,LUA Script （Lua scripting）, LRU Driving events （LRU eviction）, Business （transactions） And different levels of Disk persistence （persistence）, And pass Redis sentry （Sentinel） And automatic Partition （Cluster） Provide high availability （high availability）.

Redis：

key：

value：String（ Character type 、 value type ）、hashes、lists、sets、sorted sets、bitmaps

Client fetch v One of the elements in ,redis Of server There are methods for each type in （index()、lpop）

memcached（key,value）：value There is no concept of type

Client fetch v One of the elements in , return value All data to client（ adopt server  network card IO）, The client should have the code you implement to save code