How to use redis to perform queue operations? Summary of redis operation example code

How to use Redis for queue operations

Reids is a relatively advanced open source key-value storage system, implemented in ANSI C. It is similar to memcached, but supports persistent data storage, and value supports multiple types: String (same as value in memcached), list, set, ordered Set (OrderSet) and Hash. All value types support atomic operations, such as appending and popping elements to lists, inserting and removing elements from collections, etc. Most of the data in Rdids is located in memory, and its read and write efficiency is very high. It provides two persistence methods: AOF (append operation record file) and DUMP (regular data backup). Redis supports a customized VM (virtual memory) mechanism. When the data capacity exceeds the memory, part of the Value can be stored in a file. At the same time, Redis supports the Master-Slave mechanism, which can perform data replication.
You can use the list structure of Redis as a queue.
From the above scenarios and functions of Redis, for our current development activities, in which scenarios can we introduce Redis instead of using such a good thing? What about the tragic situation that has evolved into "Redis for the sake of using Redis"? Of course, it is really important to analyze specific issues in detail.
cache? Distributed cache? queue? Distributed queue?
Certain system applications (for example, telecommunications, banking and large-scale Internet applications, etc.) will use it. Of course, the now popular memcache is a good proof; but from a certain aspect, can memcache include both Which, and can do better (no practical application, so just throwing it out). But from Redis, I can feel that Redis can include both queues and caches, and will not cause trouble in a concurrent environment, because the operations in Redis are all atomic operations.
There is no need to comment on which one is better or worse, existence is the reason, and choosing the one that suits you is the best.
Let’s start playing with the queue (distributed) design YY in Redis. Please give me some advice.
Scenario:
Current projects are deployed on multiple servers or multiple IPs, and the frontend is distributed through F5, so it is impossible to determine which server the user's request falls on. of. For the project, there is a flash kill design. This kind of deployment was not considered at the beginning. At the same time, it was also the easiest way to deal with it, directly locking row records in the database table (on Oracle). It can be said that for different application deployments and only one database server, this concurrency problem can be solved "easily". So now consider whether to move it to the application to prevent the database server from being involved in the business.
For example, there are currently 2 application servers and 1 database server. The idea is to deploy Redis on the database server. When the two servers operate concurrent cache or queue, they first obtain the proxy objects on the two application servers from the Redis server, and then add them to the list. operation.
Look at the code implementation (PHP)
Enqueue operation file list_push.php

The code is as follows:

<?php 
$redis = getRedisInstance();//从Redis服务器拿到redis实例 
$redis->connect(&#39;Redis服务器IP&#39;, 6379); 
while (true) { 
$redis->lPush(&#39;list1&#39;, &#39;A_&#39;.date(&#39;Y-m-d H:i:s&#39;)); 
sleep(rand()%3); 
} 
?>

Execute # php list_push.php &
Dequeue The code to operate the list_pop.php file

is as follows:

<?php 
$redis = getRedisInstance();//从Redis服务器拿到redis实例 
$redis->pconnect(&#39;Redis服务器IP&#39;, 6379); 
while(true) { 
try { 
var_export( $redis->blPop(&#39;list1&#39;, 10) ); 
} catch(Exception $e) { 
//echo $e; 
} 
}

Implementation method (Python)
1. Enter the queue (write.py)

The code is as follows:

#!/usr/bin/env python 
import time 
from redis import Redis 
redis = Redis(host='127.0.0.1', port=6379) 
while True: 
now = time.
strftime("%Y/%m/%d %H:%M:%S") 
redis.lpush('test_queue', now) 
time.sleep(1)

2. Dequeue (read.py)

The code is as follows:

#!/usr/bin/env python 
import sys 
from redis import Redis 
redis = Redis(host='127.0.0.1', port=6379) 
while True: 
res = redis.rpop('test_queue') 
if res == None: 
pass 
else: 
print str(res)

Sample code:

1. Enqueue operation

<?php
$redis = new Redis();
$redis->connect(&#39;127.0.0.1&#39;,6379);
while(True){
  try{
    $value = &#39;value_&#39;.date(&#39;Y-m-d H:i:s&#39;);
    $redis->LPUSH(&#39;key1&#39;,$value);
    sleep(rand()%3);
    echo $value."\n";
  }catch(Exception $e){
    echo $e->getMessage()."\n";
  }
}
?>

2. Dequeue operation

<?php
$redis = new Redis();
$redis->pconnect(&#39;127.0.0.1&#39;,6379);
while(True){
  try{
    echo $redis->LPOP(&#39;key1&#39;)."\n";
  }catch(Exception $e){
  echo $e->getMessage()."\n";
  }
  sleep(rand()%3);
}
?>

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