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according to value Select non blocking delete , Only will keys from keyspace Delete from metadata , The real deletion will be done asynchronously later

unlink <key>

by key Set expiration time （ Time unit ： second ）

expire <key> 10

See how many seconds are left to expire ,-1 Never expire ,-2 Indicates that it has expired

ttl <key>

Switch database

select 15

Check the... Of the current database key The number of

dbsize

Empty the current library

flushdb

Empty all libraries

flushall

character string （String）

String yes Redis Basic data types ,Redis Middle string value At most 512M. It's binary safe , in other words Redis Of String Can contain any data , such as jpg Picture or serialized object .

Redis in ,String The data structure of is a simple dynamic string , Is a string that can be modified , The internal structure is similar to java Of ArrayList, Reduce the frequent allocation of memory by pre allocating redundant space .

Add key value pair （ same key To cover ）

set <key> <value>

Query the corresponding key value

get <key>

Will be given value Append to the end of the original value , Return string length

append <key> <value>

Get the length of the value

strlen <key>

When key When there is no , Set up key Value

setnx <key> <value>

take key Increase the value of the number stored in 1, Can only operate on numeric values , If it is empty , The new value added is 1, Returns the result value

incr <key>

take key The number stored in minus 1, Can only operate on numeric values , If it is empty , The new value added is -1, Returns the result value

decr <key>

take key Increase or decrease the number value stored in . Custom step size

incrby/decrby <key> < step >

Set one or more... At the same time value

mset <key1> <value1> <key2> <value2> <key3> <value3>

Set one or more... At the same time key-value Yes , If and only if all given key It doesn't exist

msetnx <key1> <value1> <key2> <value2> <key3> <value3>

Get one or more at the same time value

mget <key1> <key2> <key3>

Get content in scope

getrange <key> < The starting position > < End position >

use value overwrite key String value stored

setrange <key> < The starting position > <value>

While setting the key value , Set expiration time （ Company ： second ）

setex <key> < Expiration time > <value>

Set the new value and get the old value

getset <key> <value>

list （List）

Redis The middle list is a simple string list , Sort by insertion order , You can add an element to the head of the list （ On the left ） Or tail （ On the right ）. Its bottom layer is actually a two-way linked list , High performance on both ends , The performance of the nodes in the middle of the index subscript operation will be poor .

First, in the case of fewer list elements will use a block of continuous memory storage , This structure is ziplist, That is, compressed list . It stores all the elements next to each other , Allocated is a continuous block of memory . When there is a large amount of data, it will be changed to quicklist. Because the use of a two-way list , Two extra pointers will be used prev、next, This will cause great spatial redundancy , Will be multiple ziplist Use two-way pointer string to use , Fast insertion and deletion performance , There will not be too much space redundancy .

From the left / Insert one or more values... To the right

lpush/rpush <key> <value1> <value2> <value3>

From the left / Spit out a value on the right ,（ It's like getting out of the stack ）

After all elements are out of the stack, use ttl Look at the expiration time of the key , by -2, namely “ Value at key at , The value of the light key ”.

lpop/rpop <key>

from key1 Spit a value on the right side of the list , insert key2 To the left of the list

If key2 non-existent , Automatically create .

rpoplpush <key1> <key2>

Get elements according to index subscript （ From left to right ）

lrange <key> < Start subscript > < End subscript >

Get elements according to index subscript （ From left to right ）

lindex <key> <value>

Get list length

llen <key>

stay value In front of / Insert... At the back newvalue Insert value

linsert <key> before/after <value> <newValue>

Delete from the left n individual value（ From left to right ）

lrem <key> <value>

Will list key Subscript to be index Replace the value of with value

lset <key> <index> <value>

aggregate （Set）

Set The data structure is a dictionary , Dictionaries are implemented with hash tables .

Set The functions and List List like functions , What's special is Set Yes. Automatic weight removal Of , When you need to store a list of data , You don't want duplicate data ,Set Is a good choice , also Set Provides a way to determine whether a member is in a Set Important interfaces within a collection , This is also List What cannot be provided .

Redis Of Set yes String Unordered collection of type . The bottom of it is actually a value by null Of hash surface , So add the , Delete , The complexity of searching is O(1). An algorithm , As data increases , The length of execution , If it is O(1), Data increase , The time to find the data remains the same .

Put one or more member Elements are added to the collection key in , What already exists member Elements will be ignored

sadd <key> <value1> <value2> <value3>

Take all the values of the set

smembers <key>

Judgment set key Whether it contains the value value , There is a return 1, No return 0

sismember <key> <value>

Returns the number of elements in the collection

scard <key>

Delete elements from the collection

srem <key> <value1> <value2>

Spit a value out of the set at random

spop <key>

Randomly take... From the set n It's worth , Will not be removed from the collection

srandmember <key> <n>

Move a value in a set from one set to another

smove <key1> <key2> <value>

Returns the intersection element of two sets

sinter <key1> <key2>

Returns the union element of two sets

sunion <key1> <key2>

Returns the difference set element of two sets （key1 There is ,key2 There is no ）

sdiff <key1> <key2>

Hash （Hash）

Hash There are two kinds of data structures corresponding to types ：ziplist（ Compressed list ）,hashtable（ Hashtable ）. When field-value When the length is short and the number is small , Use ziplist, Otherwise use hashtable.

Redis hash It's a String Type of field and value Mapping table ,hash Ideal for storing objects .

to key In the collection field Key assignment value

hset <key> <field> <value>

Batch settings hash Value

hmset <key1> <value1> <key2> <value2> <key3> <value3>

Hash table key In the domain field Is set to value , If and only if domain field non-existent

hsetnx <key> <field> <value>

from key aggregate field Take out value

hget <key> <field>

Look at the hash table key in , Given domain field Whether there is

hexists <key> <field>

List the hash All of the collection field

hkeys <key>

List the hash All of the collection value

hvals <key>

Hash table key In the domain field Plus the increment （ Value must be numeric ）, Minus is plus a negative number

hincrby <key> <field> <increment>

Ordered set （Zset）

Redis Ordered set zset With the common set set Very similar , Is a collection of strings without repeating elements .

zset yes Redis A very special data structure provided , On the one hand, it is equivalent to Java Data structure of Map<String, Double>, You can give each element value Give a weight score, On the other hand, it is similar to TreeSet, Internal elements are weighted score Sort , You can get the rank of each element , You can also use score To get a list of elements .

zset The bottom layer uses two data structures

hash,hash The role of is to associate elements value And weight score, Guarantee elements value Uniqueness , You can use the element value Find the appropriate score value
Skip list , The purpose of jump tables is to give elements value Sort , according to score Scope get element list for

Put one or more elements and their score Value added to ordered set key among

zadd <key> <score1> <value1> <score2> <value2>

Return to ordered set key in , The subscript is min、max Between the elements

zrange <key> <min> <max>

If you add withscores, Then the score will be displayed together

zrange <key> <min> <max> withscores

Return to ordered set key in , all score The value is between min and max Between （ Including equal to min or max ） Members of , Press score Value increment （ From small to large ） Order

zrangebyscore <key> <min> <max>

Sort from large to small

zrevrangebyscore <key> <max> <min>

For the elements score Plus the increment

zincrby <key> <increment> <value>

Delete... Under this collection , The element that specifies the value

zrem <key> <value>

Count the set , The number of elements in the fraction range

zcount <key> <min> <max>

Returns the rank of the value in the collection , from 0 Start

zrank <key> <value>

Bitmap （bitmap）

Bitmap （bitmap） It also belongs to string data type . Each string consists of multiple bytes , Each byte is again composed of 8 individual Bit A composition . The bitmap structure uses “ position ” To realize the storage of , It sets the bit to 0 or 1 To achieve the purpose of data access , This greatly increases value Storage quantity , Its storage limit is 2^32.

Set or clear the value on a bit , The return value is the value stored in the original bit

key In the initial state, all bits are 0,offset Represents the offset , from 0 Start .

setbit <key> <offset> <value>

Get the value of a bit

When the offset offset The length of the string is larger than , Or when key When there is no , return 0.

getbit <key> <offset>

Statistics refers to the positioning interval , The value is 1 The number of

bitcount <key>

You can also specify start and end Parameters , Count on bytes in a specific range .

bitcount <key> start end

Intersection of bitmaps 、 Combine 、 Not 、 Exclusive or operation

and Find the intersection 、or Union 、not Non operational 、xor Exclusive or operation , The results are stored in destkey in . For multiple key To operate .

bitop and/or/not/xor <destkey> <key1> <key2> <key3>

HyperLogLog

stay Redis The content occupied by each key in is 12K, The theoretical storage is close to 2^64 It's worth , This is an algorithm based on cardinality estimation , We can only estimate the cardinality more accurately , A small amount of fixed memory can be used to store and identify unique elements in the collection . But the base of this estimate is not necessarily accurate , It's one with 0.81% Approximate value of standard error .

Any number of elements are added to the specified HyperLogLog Inside

pfadd <key> <element1> <element2>

Calculation HyperLogLog The approximate cardinality of

Multiple... Can be calculated HyperLogLog, Just add... At the end key that will do

pfcount <key>

Merge one or more HyperLogLog The result of is stored in another HyperLogLog in

destkey Store the merged results

pfmerge <destkey> <key1> <key2>

Geographical space （geospatial）

This type is the two-dimensional coordinates of the element , On the map is latitude and longitude . This type provides the setting of longitude and latitude 、 Inquire about 、 Range queries 、 Distance inquiry 、 Longitude and latitude Hash And so on .

Add geographic location information

geoadd <key> < longitude > < latitude > <name>

Get the corresponding geographic location information

geopos <key> <name>

Get the straight-line distance between two positions

geodist <key> <name1> <name2>

The distance unit can be added after the command , rice ：m, km ：km, miles ：mi, feet ：ft, The default is meters

geodist <key> <name1> <name2> km

Centered on a given latitude and longitude , Find the elements in a certain radius

georadius <key> < longitude > < latitude > < distance > < Distance units >

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Redis6 data type and operation summary

key operation