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Redis (I) principle and basic use

2022-06-25 10:05:00 【@@Mr.Fu】

List of articles

One 、Redis Core concept of

Concept
Redis Distributed cache , It can also be understood as an out of process cache .
Pictured ：

Two 、Redis Application scenarios of

Application scenarios
It is mainly used in cluster system .
- There is no need to use distributed cache for single projects , Using local cache can ; Pictured ：
  When the client initiates a request to the system , The system first goes to the local cache to query the data , If no data is queried, query the database , Save the found data to the local cache and return to the client ; When the second request comes to the system , The system first goes to the local cache to query the data , The data in the cache is returned to the client 【 The first request has saved the data to the local cache 】; The hit rate of his local cache is 50%;
- Using local cache to do distributed caching will have the defect of decreasing cache hit rate ; Pictured ：
  The client initiates a request to Nginx,Nginx Proxy requests to the system 1, System 1 Check that there is no qualified data in the local cache , Then go to the database to get the data, save it to the local cache, and then return it to the client ; When the client sends a request to Nginx,Nginx Proxy requests to the system 2, System 2 Check that there is no qualified data in the local cache , Then go to the database to get the data, save it to the local cache, and then return it to the client , Then, two requests are initiated and no data is obtained from the local cache , Then its cache hit rate is 0/2=0; If the cache hit rate decreases, it indicates that the overall query performance decreases .
- Solution to cache hit rate
  Bring together cached data , Use Redis Distributed cache , Pictured ：

3、 ... and 、Redis Project implementation

Conditions

Demo project

Redis 【 stay linux Deployment in China 】

Linux install

# install  wget  command 
yum -y install wget
# download 
wget http://download.redis.io/releases/redis-6.2.6.tar.gz
# decompression 
tar xzf redis-6.2.6.tar.gz
# Enter the unzip folder 
cd redis-6.2.6
# install  gcc
yum install gcc
# compile 
make
# Enter the src Catalog , Operation service 
src/redis-server

Demo Project configuration

step

install Redis Nuget package
```
StackExchange.Redis
```

Define an extension class

public static IServiceCollection AddRedis(this IServiceCollection serviceCollection) 
        {
            ConnectionMultiplexer connectionMultiplexer = ConnectionMultiplexer.Connect("IP: port ");
            serviceCollection.AddSingleton(connectionMultiplexer);  
            return serviceCollection;    
        }

StateUp Class registration 【 Wrote an extension method 】
```
services.AddRedis();
```

Redis Store and get

// Inject 
public readonly ConnectionMultiplexer connectionMultiplexer; 
public HomeController(ConnectionMultiplexer _connectionMultiplexer)
{ 
  connectionMultiplexer = _connectionMultiplexer;
}
//  obtain Redis value 
obj = connectionMultiplexer.GetDatabase(0).StringGet(Key).ToString();
// Storage Redis value   Key:Value
connectionMultiplexer.GetDatabase(0).StringSet(Key, Value);

Redis Store collections

// obtain Redis Whether there is 
RedisValue[] redisValues = connectionMultiplexer.GetDatabase(0).SetMembers("list");
 //Redis This data does not exist in 
 if (redisValues.Length == 0)
{
// Get... In the database 
 list = demoDbContext.Set<User>().ToList();
 List<RedisValue> rvList = new List<RedisValue>();
 foreach (User user in list)
 {
    obj = JsonConvert.SerializeObject(user);
    rvList.Add(obj);
 }
 // Add data to Redis in 
  connectionMultiplexer.GetDatabase(0).SetAdd("list", rvList.ToArray());       
 }

Redis Hash Dictionary storage

Use scenarios ： Modify a field in the database or a int Add one to the field data

// obtain HASH The data in the field 
 connectionMultiplexer.GetDatabase(0).HashGet( type , key).ToString();
 if (string.IsNullOrEmpty(obj))
 {
   // Get data from the database 
   u = demoDbContext.Set<User>().Where(p => p.useid == useid).FirstOrDefault();
   // Add data to Redis Hash In the dictionary 
   connectionMultiplexer.GetDatabase(0).HashSet( type , key,Value);
   // Set expiration time 
   connectionMultiplexer.GetDatabase(0).KeyExpire( type ,TimeSpan.FromSeconds(10));

  }
  // In the dictionary Value It's worth adding 1
  connectionMultiplexer.GetDatabase(0).HashIncrement( type , key);

Redis Business

// Query to get the value 
connectionMultiplexer.GetDatabase(0).HashGet( type , key).ToString();
// Create transaction 
ITransaction transaction = connectionMultiplexer.GetDatabase(0).CreateTransaction();
// add value 
transaction.HashSetAsync( type , key, value);
// Modified value 
// transaction.HashSetAsync( type , key, After modification Value);
// Commit transaction 
 bool commit = transaction.Execute();

Redis Mass storage of data

 // Create batch objects 
  var bach = connectionMultiplexer.GetDatabase(0).CreateBatch();
  // get data 
  List<User> list = new List<User>();
  list = demoDbContext.user.ToList();
  // Batch addition 
  for (int i = 0; i < list.Count; i++)
  {
    bach.HashSetAsync("bach_User_"+i, "state", list[i].usestate);
  }
  // Data submission 
  bach.Execute();

Redis Collection sorting

// get data 
RedisValue[] rv = connectionMultiplexer.GetDatabase(0).SetMembers("User");
 if (rv.Length == 0)
 {
   list = demoDbContext.Set<User>().ToList();
   List<RedisValue> rvList = new List<RedisValue>();
   // Batch add data 
   foreach (User u in list) 
   {
      var  data = JsonConvert.SerializeObject(u);  
      rvList.Add(data);
       // Data sorting 
       connectionMultiplexer.GetDatabase(0).SortedSetAdd("User", data, u.usestate);  // User :key  data:Value value   u.usestate： Sort field    Ascending 
  }

Redis Paging query

 List<User> list = new List<User>();
 // Get paging data   100 Is the number of rows ,1 Is the number of pages 
 RedisValue[] rv = connectionMultiplexer.GetDatabase(0).SetScan("User",100,0,1).ToArray();
 if (rv.Length == 0)
   {
      list = demoDbContext.Set<User>().ToList();
      List<RedisValue> rvList = new List<RedisValue>();
      foreach (User u in list) 
      { 
         var  data = JsonConvert.SerializeObject(u); 
         rvList.Add(data); 
       }
       // Add data to Redis in 
      connectionMultiplexer.GetDatabase(0).SetAdd("User", rvList.ToArray());
    }

Four 、Redis The principle of communication

Redis A simple model for handling events ： Multiplexing mechanism 【 One thread handles multiple connections 】【 Subscription publishing mechanism 】;

principle
Default by Socket Protocol to establish a connection , Server through Socket After four layers , After passing through the link layer, it will reach... Through four layers Redis Establishing a connection ; The link layer 【 Hardware level 】 Upon receipt of the request , operating system 【 producer 】 Send the request to the event collector through synchronous to asynchronous conversion 【MQ】 then Redis【 subscriber 】 Use a thread to process events through polling , This is the multiplexing mechanism .
Redis Three things to do ：
1、 Establishing a connection
2、 Store data to local cache
3、 Persist data to a file （ Start a new thread ）
Pictured ：

5、 ... and 、Redis Principle of data structure

principle
Redis Once the connection is established , Store data in memory through the interface .
Pictured ：
Data persistence
- Purpose
  To prevent data loss . Default store in AOP In file .
Redis Set Schematic diagram
Array +HASH surface , Pictured ：
HASH The role of ： Prevent data duplication , Use HASH Collision .
Redis HASH Dictionary principle
Array +HASH surface + Single item list .
- principle
  The fields stored in the dictionary go through hash Get the index of an array , Index according to key \ value Store in array , If the resulting index already exists key\value 了 , It won't cover , It will form a single linked list and continue to store .
  Pictured ：
- defects
  Completely based on memory , Can cause memory overflow . Not suitable for storing massive data .