Redis – basic summary of crazy God's theory of redis (end)
2021.6.12-2021.6.14: after learning and playing with the summary of Redis foundation in the Dragon Boat Festival, the more you learn, the more you feel the lack of knowledge.
Reference link: crazy talk Java – Redis summary: https://www.bilibili.com/video/BV1S54y1R7SB?p=1
Redis has five basic data types:
-
1.String string
OK 127.0.0.1:6380> set k1 1 OK 127.0.0.1:6380> INCR k1 2 127.0.0.1:6380> DECR k1 1 127.0.0.1:6380> keys * k1 127.0.0.1:6380> set k2 huyuqiao OK 127.0.0.1:6380> GETRANGE K2 0 3 127.0.0.1:6380> GETRANGE k2 0 3 huyu 127.0.0.1:6380> GETRANGE k2 0 -1 huyuqiao 127.0.0.1:6380> SETRANGE k2 1 XX 8 127.0.0.1:6380> get k2 hXXuqiao 127.0.0.1:6380> SETEX k3 30 "hello, world" #set exist: replace if it exists or does not exist OK 127.0.0.1:6380> ttl k3 28 127.0.0.1:6380> ttl k2 -1 127.0.0.1:6380> keys * k1 k2 127.0.0.1:6380> ttl k3 -2 127.0.0.1:6380> setnx mykey "redis" #set if not exist: set if it does not exist, set if it exists, set fails, or the original value 1 127.0.0.1:6380> ttl mykey -1 127.0.0.1:6380> setnx mykey "mongodb" 0 127.0.0.1:6380> get mykey redis 127.0.0.1:6380> ttl k2 #Permanent return - 1 -1 127.0.0.1:6380> ttl k3 #Expired return - 2 -2 127.0.0.1:6380> 127.0.0.1:6380> mset user:1:name huyuqiao user:1:age 22 OK 127.0.0.1:6380> mget user:1:name user:1:age huyuqiao 22 127.0.0.1:6380>
-
List
127.0.0.1:6380> FLUSHALL OK 127.0.0.1:6380> clear 127.0.0.1:6380> LPUSH list 1 1 127.0.0.1:6380> LPUSH list 2 2 127.0.0.1:6380> LPUSH list 3 3 127.0.0.1:6380> LRANGE list 0 -1 3 2 1 127.0.0.1:6380> RPUSH list a 4 127.0.0.1:6380> LPOP list 3 127.0.0.1:6380> LRANGE 0 -1 ERR wrong number of arguments for 'lrange' command 127.0.0.1:6380> LRANGE list 0 -1 2 1 a 127.0.0.1:6380> LINDEX list 0 2 127.0.0.1:6380> LLEN list 3 127.0.0.1:6380> FLUSHALL OK 127.0.0.1:6380> clear 127.0.0.1:6380> LPUSH list one 1 127.0.0.1:6380> LPUSH list two 2 127.0.0.1:6380> LPUSH list two 3 127.0.0.1:6380> LREM list 1 one #Remove an element equal to one in the list (remove the last element added) 1 127.0.0.1:6380> LRANGE list 0 -1 two two 127.0.0.1:6380> LREM list 2 one 0 127.0.0.1:6380> LREM list 2 two 2 127.0.0.1:6380> LRANGE list 0 -1 127.0.0.1:6380> FLUSHALL 127.0.0.1:6380> LPUSH list one 1 127.0.0.1:6380> LPUSH list two 2 127.0.0.1:6380> LPUSH list three 3 127.0.0.1:6380> LPUSH list four 4 127.0.0.1:6380> LTRIM list 1 2 OK 127.0.0.1:6380> LRANGE list 0 -1 three two 127.0.0.1:6380>
-
Set
127.0.0.1:6380> FLUSHALL OK 127.0.0.1:6380> SADD myset "hello" 1 127.0.0.1:6380> sadd myset "world" 1 127.0.0.1:6380> sadd myset "huyuqiao" 1 127.0.0.1:6380> smembers myset hello huyuqiao world 127.0.0.1:6380> SISMEMBER myset huyuqiao 1 127.0.0.1:6380> sadd myset "HYQ" 1 127.0.0.1:6380> SMEMBERS myset hello huyuqiao HYQ world 127.0.0.1:6380> SREM myset hello 1 127.0.0.1:6380> scard myset 3 127.0.0.1:6380> SMEMBERS myset huyuqiao HYQ world 127.0.0.1:6380> SRANDMEMBER myset world 127.0.0.1:6380> SRANDMEMBER myset huyuqiao 127.0.0.1:6380>
-
Hash
huyuqiao 127.0.0.1:6380> FLUSHALL OK 127.0.0.1:6380> clear 127.0.0.1:6380> hset myhash field1 huyuqiao 1 127.0.0.1:6380> hmset myhash field1 hello field2 world OK 127.0.0.1:6380> hmget myhash field1 field2 hello world 127.0.0.1:6380> hgetall myhash field1 hello field2 world 127.0.0.1:6380> hlen myhash 2 127.0.0.1:6380> HEXISTS myhash field1 1 127.0.0.1:6380> HKEYS myhash field1 field2 127.0.0.1:6380> HVALS myhash hello world 127.0.0.1:6380> HSETNX myhash field4 hello #hash settings 1 127.0.0.1:6380> HGETALL myhash field1 hello field2 world field4 hello 127.0.0.1:6380>
-
Zset
127.0.0.1:6380> zadd salary 100 huyuqiao 1 127.0.0.1:6380> zadd salary 200 HUYUQIAO 1 127.0.0.1:6380> zadd salary 300 HYQ 1 127.0.0.1:6380> ZRANGEBYSCORE salary -inf +inf huyuqiao HUYUQIAO HYQ 127.0.0.1:6380> zrange salary 0 -1 huyuqiao HUYUQIAO HYQ 127.0.0.1:6380> zrem salary huyuqiao 1 127.0.0.1:6380> ZRANGEBYSCORE salary -inf +inf HUYUQIAO HYQ
Redis has three special data types:
1.GeoSpatical
Applicable scenario: get the distance of nearby people, friends and online car Hailing positioning function.
# Add position latitude and longitude 127.0.0.1:6379> GEOADD china:city 116.41667 39.91667 Beijing (integer) 1 127.0.0.1:6379> GEOADD china:city 121.43333 31.23000 Shanghai (integer) 1 127.0.0.1:6379> GEOADD china:city 106.45000 29.56667 Chongqing (integer) 1 127.0.0.1:6379> GEOADD china:city 114.06667 22.61667 Shenzhen (integer) 1 127.0.0.1:6379> GEOADD china:city 120.20000 30.26667 Hangzhou (integer) 1 127.0.0.1:6379> GEOADD china:city 108.95000 34.26667 Xi'an (integer) 1 # View the latitude and longitude of different positions 127.0.0.1:6379> GEOPOS china:city Beijing Xi'an #View the distance between different positions (the default is m) 127.0.0.1:6379> GEODIST china:city Beijing Shanghai "1066981.1340" 127.0.0.1:6379> GEODIST china:city Beijing Shanghai km "1066.9811" 127.0.0.1:6379> GEODIST china:city Beijing Chongqing km "1465.8918" 127.0.0.1:6379> # View the places within the specified latitude and longitude (which can be spread to a specified number of friends within the specified range) 127.0.0.1:6379> GEORADIUS china:city 110 30 1000 km Chongqing Xi'an Shenzhen Hangzhou 127.0.0.1:6379> GEORADIUS china:city 110 30 500 km Chongqing Xi'an 127.0.0.1:6379> GEORADIUS china:city 110 30 500 km withdist #View all cities and distances of 500km around a certain latitude and longitude / km Chongqing 346.0548 Xi'an 484.7511 127.0.0.1:6379> GEORADIUS china:city 110 30 500 km withcoord #View all cities and longitude and latitude within 500km around a certain longitude and latitude Chongqing 106.4500012993812561 29.56666939001875249 Xi'an 108.95000249147415161 34.2666710302806834 127.0.0.1:6379> GEORADIUS china:city 110 30 500 km count 1 #View three cities 500 km around a certain latitude and longitude Chongqing 127.0.0.1:6379> GEORADIUS china:city 110 30 500 km count 3 #View three cities 500 km around a certain latitude and longitude Chongqing Xi'an 127.0.0.1:6379> #View all cities around the location (similar to location) 127.0.0.1:6379> GEORADIUSBYMEMBER china:city Beijing 1000 km Beijing Xi'an 127.0.0.1:6379> GEORADIUSBYMEMBER china:city Shanghai 1000 km Hangzhou Shanghai 127.0.0.1:6379> #Convert the two-dimensional longitude and latitude of the city into a one bit hash string 127.0.0.1:6379> GEOHASH china:city Beijing Chongqing wx4g14s53n0 wm78nq6w2f0 127.0.0.1:6379> #The bottom layer of GEO is zset, which can be operated by zset command 127.0.0.1:6379> zrange china:city 0 -1 #View all cities Chongqing Xi'an Shenzhen Hangzhou Shanghai Beijing 127.0.0.1:6379> zrem china:city Beijing #Delete the city of Beijing
2.Hyperloglog
Applicable scenario: website UV quantity. Set is traditionally used for statistics, but if there are a large number of user IDs, it will consume too much content and be troublesome. If it is only counting and the error rate is allowed (0.81%), it is feasible. Otherwise, set is still used for statistics
Cardinality: the number of non repeating elements in the collection. If {1, 3, 5, 5, 7} is {1, 3, 5, 7}, the base number is 4
[external link image transfer failed. The source station may have anti-theft chain mechanism. It is recommended to save the image and upload it directly (img-35mpjikm-1623665896982)( https://i.loli.net/2021/06/13/pDS495ifgXAVrxb.png )]
127.0.0.1:6379> clear 127.0.0.1:6379> PFADD mykey a b c d e f g h i j #Set mykey set (integer) 1 127.0.0.1:6379> PFCOUNT mykey #Count the cardinality of mykey set (integer) 10 127.0.0.1:6379> PFADD mykey2 i j z x c v b n m (integer) 1 127.0.0.1:6379> PFCOUNT mykey2 (integer) 9 127.0.0.1:6379> PFMERGE mykey3 mykey mykey2 #Union of two sets OK 127.0.0.1:6379> PFCOUNT mykey3 (integer) 15 127.0.0.1:6379>
3.Bitmaps
Applicable scenarios: judge and count the active and inactive, logged in and not logged in scenarios that are not 1 or 0
[external chain picture transfer failed. The source station may have anti-theft chain mechanism. It is recommended to save the picture and upload it directly (img-3npiwqsq-1623665896988)( https://i.loli.net/2021/06/13/F83vgB47L21XzMj.png )]
[root@VM-8-11-centos ~]# redis-cli -a root --raw 127.0.0.1:6379> setbit sign 0 1 #Set whether the sign user clocks in one day (integer) 0 127.0.0.1:6379> SETBIT sign 1 0 (integer) 0 127.0.0.1:6379> SETBIT sign 2 0 (integer) 0 127.0.0.1:6379> SETBIT sign 3 1 (integer) 0 127.0.0.1:6379> SETBIT sign 4 1 (integer) 0 127.0.0.1:6379> SETBIT sign 5 0 (integer) 0 127.0.0.1:6379> SETBIT sign 6 0 (integer) 0 127.0.0.1:6379> GETBIT sign 3 #Get the sign user's clocking in one day (integer) 1 127.0.0.1:6379> GETBIT sign 6
Redis transaction:
Redsi transaction: there is no concept of isolation level, that is, the transaction does not guarantee atomicity (there are multiple commands within the transaction, which may not necessarily achieve partial success and partial failure), but a single command ensures atomicity
1.Redis transaction process:
- Open transaction (multi)
- Order to join the team
- Execute transaction (exec)
#Start end transaction 127.0.0.1:6379> multi OK 127.0.0.1:6379> set k1 v1 QUEUED 127.0.0.1:6379> set k2 v2 QUEUED 127.0.0.1:6379> get k2 QUEUED 127.0.0.1:6379> set k3 v3 QUEUED 127.0.0.1:6379> exec OK OK v2 OK 127.0.0.1:6379> #Discard transaction: all previous queue codes are rolled back 127.0.0.1:6379> set k1 v1 QUEUED 127.0.0.1:6379> set k2 asdfasdf QUEUED 127.0.0.1:6379> DISCARD OK 127.0.0.1:6379> EXEC ERR EXEC without MULTI 127.0.0.1:6379> get k2 v2
2.Redis transaction is non atomic
The reason why transactions are non atomic is that there are two exceptions:
-
Compilation exception (checking exception): the code is wrong, and there is no statement, function, configuration file, etc
127.0.0.1:6379> MULTI OK 127.0.0.1:6379> set k1 v1 QUEUED 127.0.0.1:6379> set k2 v2 QUEUED 127.0.0.1:6379> gasdfa k3 #Statement error is equivalent to not executing, and an error occurs during compilation ERR unknown command 'gasdfa' 127.0.0.1:6379> set k4 v4 QUEUED 127.0.0.1:6379> EXEC EXECABORT Transaction discarded because of previous errors. 127.0.0.1:6379> get k4 127.0.0.1:6379> get k1
-
Runtime exception (non checking exception): no variable, no new for an object, etc. (not all rollback)
127.0.0.1:6379> set k1 "v1" OK 127.0.0.1:6379> multi OK 127.0.0.1:6379> incr k1 QUEUED 127.0.0.1:6379> set k2 v2 QUEUED 127.0.0.1:6379> get k2 QUEUED 127.0.0.1:6379> EXEC ERR value is not an integer or out of range OK v2 #The above error does not affect the execution of the following statements, so it is proved that redis transactions do not guarantee atomicity 127.0.0.1:6379>
Redis optimistic lock:
Optimistic lock: it will not be locked. Only when the data is updated will it be compared whether the version has been modified (if it has been modified in the redis transaction, the transaction will not be executed successfully)
Pessimistic lock: no matter what you do, you will lock it, which is inefficient but safe
In Redis transactions, < font color = red size = 3 > watch < / font > is used to realize optimistic locking. If it is modified halfway, resulting in version change, all transactions will not succeed
127.0.0.1:6379> set money 100 OK 127.0.0.1:6379> set out 0 OK 127.0.0.1:6379> watch money #Redis optimistic lock: watch monitor money OK 127.0.0.1:6379> MULTI #In another window, change money to 101 OK 127.0.0.1:6379> DECRBY money 10 QUEUED 127.0.0.1:6379> incrby out 10 QUEUED 127.0.0.1:6379> EXEC 127.0.0.1:6379> get money 101 127.0.0.1:6379>
Springboot - configure Redis source code
Jedis: direct connection, unsafe under multithreading, similar to BIO mode (eliminated after springboot 2. X)
Lettuce: Netty is adopted and shared under multithreading, which is similar to NIO mode
autoconfig->srping. redis related configuration found in factories
@Configuration(proxyBeanMethods = false)
@ConditionalOnClass(RedisOperations.class)
@EnableConfigurationProperties(RedisProperties.class)
@Import({ LettuceConnectionConfiguration.class, JedisConnectionConfiguration.class })
public class RedisAutoConfiguration {
@Bean
@ConditionalOnMissingBean(name = "redisTemplate")
public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory redisConnectionFactory)
throws UnknownHostException {
RedisTemplate<Object, Object> template = new RedisTemplate<>();
template.setConnectionFactory(redisConnectionFactory);
return template;
}
@Bean
@ConditionalOnMissingBean
public StringRedisTemplate stringRedisTemplate(RedisConnectionFactory redisConnectionFactory)
throws UnknownHostException {
StringRedisTemplate template = new StringRedisTemplate();
template.setConnectionFactory(redisConnectionFactory);
return template;
}
}
Springboot – customize RedisTemplate and RedisUtil
1.RedisTemplate serialization configuration
package com.empirefree.springboot.config;
import com.fasterxml.jackson.annotation.JsonAutoDetect;
import com.fasterxml.jackson.annotation.JsonTypeInfo;
import com.fasterxml.jackson.annotation.PropertyAccessor;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.jsontype.impl.LaissezFaireSubTypeValidator;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.Jackson2JsonRedisSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;
/**
* @program: springboot
* @description: RedisTemplate to configure
* @author: huyuqiao
* @create: 2021/06/13 16:05
*/
@Configuration
public class RedisConfig {
@Bean
@SuppressWarnings("all")
public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) {
RedisTemplate<String, Object> template = new RedisTemplate<String, Object>();
template.setConnectionFactory(factory);
// Json serialization configuration
Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class);
ObjectMapper om = new ObjectMapper();
om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
om.activateDefaultTyping(LaissezFaireSubTypeValidator.instance, ObjectMapper.DefaultTyping.NON_FINAL,
JsonTypeInfo.As.WRAPPER_ARRAY);
jackson2JsonRedisSerializer.setObjectMapper(om);
// Serialization of String
StringRedisSerializer stringRedisSerializer = new StringRedisSerializer();
// The key adopts the serialization method of String
template.setKeySerializer(stringRedisSerializer);
// The key of hash is also serialized by String
template.setHashKeySerializer(stringRedisSerializer);
// value serialization adopts jackson
template.setValueSerializer(jackson2JsonRedisSerializer);
// The value serialization method of hash adopts jackson
template.setHashValueSerializer(jackson2JsonRedisSerializer);
template.afterPropertiesSet();
return template;
}
}
2.RedisUtil configuration (CRUD operation string, map,list,set)
package com.empirefree.springboot.utils;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Component;
import org.springframework.util.CollectionUtils;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.TimeUnit;
/**
* @program: springboot
* @description: Redis Tool class
* @author: huyuqiao
* @create: 2021/06/13 16:14
*/
@Component
public final class RedisUtil {
@Autowired
private RedisTemplate<String, Object> redisTemplate;
// =============================common============================
/**
* Specify cache expiration time
* @param key key
* @param time Time (seconds)
*/
public boolean expire(String key, long time) {
try {
if (time > 0) {
redisTemplate.expire(key, time, TimeUnit.SECONDS);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Get expiration time according to key
* @param key Key cannot be null
* @return Time (seconds) returns 0, which means it is permanently valid
*/
public long getExpire(String key) {
return redisTemplate.getExpire(key, TimeUnit.SECONDS);
}
/**
* Determine whether the key exists
* @param key key
* @return true Exists false does not exist
*/
public boolean hasKey(String key) {
try {
return redisTemplate.hasKey(key);
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Delete cache
* @param key One or more values can be passed
*/
@SuppressWarnings("unchecked")
public void del(String... key) {
if (key != null && key.length > 0) {
if (key.length == 1) {
redisTemplate.delete(key[0]);
} else {
redisTemplate.delete((Collection<String>) CollectionUtils.arrayToList(key));
}
}
}
// ============================String=============================
/**
* Normal cache fetch
* @param key key
* @return value
*/
public Object get(String key) {
return key == null ? null : redisTemplate.opsForValue().get(key);
}
/**
* Normal cache put
* @param key key
* @param value value
* @return true Success false failure
*/
public boolean set(String key, Object value) {
try {
redisTemplate.opsForValue().set(key, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Normal cache put in and set time
* @param key key
* @param value value
* @param time Time (seconds) time should be greater than 0. If time is less than or equal to 0, the indefinite period will be set
* @return true Success false failure
*/
public boolean set(String key, Object value, long time) {
try {
if (time > 0) {
redisTemplate.opsForValue().set(key, value, time, TimeUnit.SECONDS);
} else {
set(key, value);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Increasing
* @param key key
* @param delta How many to add (greater than 0)
*/
public long incr(String key, long delta) {
if (delta < 0) {
throw new RuntimeException("The increment factor must be greater than 0");
}
return redisTemplate.opsForValue().increment(key, delta);
}
/**
* Diminishing
* @param key key
* @param delta How many to reduce (less than 0)
*/
public long decr(String key, long delta) {
if (delta < 0) {
throw new RuntimeException("Decrement factor must be greater than 0");
}
return redisTemplate.opsForValue().increment(key, -delta);
}
// ================================Map=================================
/**
* HashGet
* @param key Key cannot be null
* @param item Item cannot be null
*/
public Object hget(String key, String item) {
return redisTemplate.opsForHash().get(key, item);
}
/**
* Get all the corresponding hashKey values
* @param key key
* @return Corresponding multiple key values
*/
public Map<Object, Object> hmget(String key) {
return redisTemplate.opsForHash().entries(key);
}
/**
* HashSet
* @param key key
* @param map Corresponding to multiple key values
*/
public boolean hmset(String key, Map<String, Object> map) {
try {
redisTemplate.opsForHash().putAll(key, map);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* HashSet And set the time
* @param key key
* @param map Corresponding to multiple key values
* @param time Time (seconds)
* @return true Success false failure
*/
public boolean hmset(String key, Map<String, Object> map, long time) {
try {
redisTemplate.opsForHash().putAll(key, map);
if (time > 0) {
expire(key, time);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Put data into a hash table. If it does not exist, it will be created
*
* @param key key
* @param item term
* @param value value
* @return true Success false failure
*/
public boolean hset(String key, String item, Object value) {
try {
redisTemplate.opsForHash().put(key, item, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Put data into a hash table. If it does not exist, it will be created
*
* @param key key
* @param item term
* @param value value
* @param time Time (seconds): Note: if the existing hash table has time, the original time will be replaced here
* @return true Success false failure
*/
public boolean hset(String key, String item, Object value, long time) {
try {
redisTemplate.opsForHash().put(key, item, value);
if (time > 0) {
expire(key, time);
}
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Delete values in hash table
*
* @param key Key cannot be null
* @param item Item can make multiple non null able
*/
public void hdel(String key, Object... item) {
redisTemplate.opsForHash().delete(key, item);
}
/**
* Judge whether there is the value of this item in the hash table
*
* @param key Key cannot be null
* @param item Item cannot be null
* @return true Exists false does not exist
*/
public boolean hHasKey(String key, String item) {
return redisTemplate.opsForHash().hasKey(key, item);
}
/**
* hash If increment does not exist, it will create one and return the added value
*
* @param key key
* @param item term
* @param by How many to add (greater than 0)
*/
public double hincr(String key, String item, double by) {
return redisTemplate.opsForHash().increment(key, item, by);
}
/**
* hash Diminishing
*
* @param key key
* @param item term
* @param by To reduce (less than 0)
*/
public double hdecr(String key, String item, double by) {
return redisTemplate.opsForHash().increment(key, item, -by);
}
// ============================set=============================
/**
* Get all the values in the Set according to the key
* @param key key
*/
public Set<Object> sGet(String key) {
try {
return redisTemplate.opsForSet().members(key);
} catch (Exception e) {
e.printStackTrace();
return null;
}
}
/**
* Query from a set according to value whether it exists
*
* @param key key
* @param value value
* @return true Exists false does not exist
*/
public boolean sHasKey(String key, Object value) {
try {
return redisTemplate.opsForSet().isMember(key, value);
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Put data into set cache
*
* @param key key
* @param values Values can be multiple
* @return Number of successes
*/
public long sSet(String key, Object... values) {
try {
return redisTemplate.opsForSet().add(key, values);
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* Put set data into cache
*
* @param key key
* @param time Time (seconds)
* @param values Values can be multiple
* @return Number of successes
*/
public long sSetAndTime(String key, long time, Object... values) {
try {
Long count = redisTemplate.opsForSet().add(key, values);
if (time > 0)
expire(key, time);
return count;
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* Gets the length of the set cache
*
* @param key key
*/
public long sGetSetSize(String key) {
try {
return redisTemplate.opsForSet().size(key);
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* Remove with value
*
* @param key key
* @param values Values can be multiple
* @return Number of removed
*/
public long setRemove(String key, Object... values) {
try {
Long count = redisTemplate.opsForSet().remove(key, values);
return count;
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
// ===============================list=================================
/**
* Get the contents of the list cache
*
* @param key key
* @param start start
* @param end End 0 to - 1 represent all values
*/
public List<Object> lGet(String key, long start, long end) {
try {
return redisTemplate.opsForList().range(key, start, end);
} catch (Exception e) {
e.printStackTrace();
return null;
}
}
/**
* Gets the length of the list cache
*
* @param key key
*/
public long lGetListSize(String key) {
try {
return redisTemplate.opsForList().size(key);
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
/**
* Get the value in the list through the index
*
* @param key key
* @param index When index index > = 0, 0 header, 1 second element, and so on; When index < 0, - 1, footer, - 2, the penultimate element, and so on
*/
public Object lGetIndex(String key, long index) {
try {
return redisTemplate.opsForList().index(key, index);
} catch (Exception e) {
e.printStackTrace();
return null;
}
}
/**
* Put the list into the cache
*
* @param key key
* @param value value
*/
public boolean lSet(String key, Object value) {
try {
redisTemplate.opsForList().rightPush(key, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Put the list into the cache
* @param key key
* @param value value
* @param time Time (seconds)
*/
public boolean lSet(String key, Object value, long time) {
try {
redisTemplate.opsForList().rightPush(key, value);
if (time > 0)
expire(key, time);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Put the list into the cache
*
* @param key key
* @param value value
* @return
*/
public boolean lSet(String key, List<Object> value) {
try {
redisTemplate.opsForList().rightPushAll(key, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Put the list into the cache
*
* @param key key
* @param value value
* @param time Time (seconds)
* @return
*/
public boolean lSet(String key, List<Object> value, long time) {
try {
redisTemplate.opsForList().rightPushAll(key, value);
if (time > 0)
expire(key, time);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Modify a piece of data in the list according to the index
*
* @param key key
* @param index Indexes
* @param value value
* @return
*/
public boolean lUpdateIndex(String key, long index, Object value) {
try {
redisTemplate.opsForList().set(key, index, value);
return true;
} catch (Exception e) {
e.printStackTrace();
return false;
}
}
/**
* Remove N values as value
*
* @param key key
* @param count How many to remove
* @param value value
* @return Number of removed
*/
public long lRemove(String key, long count, Object value) {
try {
Long remove = redisTemplate.opsForList().remove(key, count, value);
return remove;
} catch (Exception e) {
e.printStackTrace();
return 0;
}
}
}
Redis – persistent
Persistence: store the memory data into the disk within the specified time interval, recover the data after power failure, and use the snapshot file to read it into the memory.
1.Redis – RDB (recommended by default)
-
Saving process: the parent process fork s a child process, which will persist the data into a temporary file. After the persistence is completed, it will replace the last RDB official file.
-
Trigger conditions:
- Save: the command save 900 1 will trigger RDB if it is modified once within 15 minutes.
- Execute the FlushAll command
- Exiting Redis will generate RDB files
-
Applicable scenario: suitable for large-scale data recovery and insensitive to data integrity.
2.Redis - AOF (after restart, the AOF is loaded first by default, because the data is more complete)
-
Save process: the parent process fork s a child process, records all instructions in the form of log (read operation is not recorded), then appends the data without rewriting to the AOF file, and then replaces the last AOF file
-
Trigger condition: appendfsync always/everysec/no command
-
Applicable scenario: strict requirements on the integrity of recovered data
-
Rewrite scenario: if the file is continuously appended to a threshold, the aof file will be rewritten
Redis – publish and subscribe
Publish and subscribe: you can push messages, chat rooms, etc
#Publisher: Send a message to a channel of Redis, and all subscribers can receive it 127.0.0.1:6379> PUBLISH huyuqiao "hello,world" 1 #Subscriber: subscribe to a channel in Redis 127.0.0.1:6379> SUBSCRIBE huyuqiao subscribe huyuqiao 1 message huyuqiao hello,world
Redis – master-slave replication (Master write slave read)
1.Linux configuration file
- Change no of daemon to yes
- port, pidfile, logfile and dbfilename are changed to the new redis name
- If redis has a password, you need to configure it in slave or remove it in master
#When the master is disconnected, the slave is still the slave of the original master. However, if the slave is disconnected, the master will not have a slave >>slaveof no one #Close the slave status and change to master >>shutdown #When redis is stopped, its slave state will stop. The next time it is started, it will become a master, and the redis under the original master will not be available redis-server redis80.conf #Start the 80redis window. kill -s 9 pid #Close a process
2. Replication principle
- Full replication: after the slave is started, send the sync synchronization command to the master, and then synchronize all data in the master
- Incremental replication: after the master writes data, the slave gets it in real time.
Redis - sentinel mode
The process is as follows: after starting the sentinel, close the 79 main service, vote 80 as the main service from 80 and 81, and then regard 79 and 80 as slave. Therefore, the next time 79 starts, it will be slave by default. In addition, because the data is copied incrementally, the data is well preserved in 80, and 79 is fully copied to 79 after startup
#Log in sentinel mode 8044:X 14 Jun 16:35:06.885 # WARNING: The TCP backlog setting of 511 cannot be enforced because /proc/sys/net/core/somaxconn is set to the lower value of 128. 8044:X 14 Jun 16:35:06.885 # Sentinel ID is c0ce22fc8365ff48663b7db710ce8c359529c3d9 8044:X 14 Jun 16:35:06.885 # +monitor master mymaster 127.0.0.1 6379 quorum 1 8044:X 14 Jun 16:35:51.556 # +sdown master mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.556 # +odown master mymaster 127.0.0.1 6379 #quorum 1/1 8044:X 14 Jun 16:35:51.556 # +new-epoch 1 8044:X 14 Jun 16:35:51.556 # +try-failover master mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.572 # +vote-for-leader c0ce22fc8365ff48663b7db710ce8c359529c3d9 1 8044:X 14 Jun 16:35:51.572 # +elected-leader master mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.572 # +failover-state-select-slave master mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.624 # +selected-slave slave 127.0.0.1:6380 127.0.0.1 6380 @ mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.624 * +failover-state-send-slaveof-noone slave 127.0.0.1:6380 127.0.0.1 6380 @ mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.684 * +failover-state-wait-promotion slave 127.0.0.1:6380 127.0.0.1 6380 @ mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.826 # +promoted-slave slave 127.0.0.1:6380 127.0.0.1 6380 @ mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.826 # +failover-state-reconf-slaves master mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:51.914 * +slave-reconf-sent slave 127.0.0.1:6381 127.0.0.1 6381 @ mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:52.831 * +slave-reconf-inprog slave 127.0.0.1:6381 127.0.0.1 6381 @ mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:52.831 * +slave-reconf-done slave 127.0.0.1:6381 127.0.0.1 6381 @ mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:52.912 # +failover-end master mymaster 127.0.0.1 6379 8044:X 14 Jun 16:35:52.912 # +switch-master mymaster 127.0.0.1 6379 127.0.0.1 6380 8044:X 14 Jun 16:35:52.912 * +slave slave 127.0.0.1:6381 127.0.0.1 6381 @ mymaster 127.0.0.1 6380 8044:X 14 Jun 16:35:52.912 * +slave slave 127.0.0.1:6379 127.0.0.1 6379 @ mymaster 127.0.0.1 6380
Redis – cache penetration, breakdown, avalanche
- Cache penetration: there is no data in the cache and database
- Solution: 1 Bloom filter 2 Store empty object: after the database is not found, an empty object is temporarily stored in redis
- Cache breakdown: a key value has expired and a large number of accesses have come
- Solution: 1 Never expire 2 Distributed lock: one thread obtains the lock while other threads wait
- Cache avalanche: a large number of key values have expired and a large number of accesses have come
- Solution: 1 Redis high availability: set up more redis 2 Current limiting degradation: after the cache fails, the number of read and write caches in the database is controlled by locking or queuing. 3 Data preheating: a large amount of data is loaded into the cache, and different expiration times are set according to different accesses