best way for persistence in redis

Redis distributed locks in the right way (Java version) Distributed locks generally have three kinds of implementation methods: 1. Database optimistic lock; 2. Distributed lock based on Redis; 3. Distributed locks based on zookeeper. This blog will introduce the second way to implement distributed locks based on

The two-way linked list implemented by Redis is easy to understand. Its implementation principle is classic and the code is neat and clear. The following is a part of the translation of its source code comments and my comments. If you are biased, please note: * adlist. h The two-way linked list implemented by Redis is

Flask Configuring RedisFirst download the Flask cache plugin Flask-cache, using pip to download.sudo pip install flask_cacheExtend Flask_cache for AppsApp = Flask (__name__)1Config = {2 'Cache_type':'Redis',3 'Cache_redis_host':'127.0.0.1',4 'Cache_redis_port': 6379,5 'cache_redis_db':"',6 'Cache_redis_password':"'7 }8 9 app.config.from_object (config)TenCache.init_app (App,config)1@app. Route ('/')2@cache. Cached (timeout=60*2)3 defindex ()

obtained in 2nd step, for example: Host_list[n] Connect the host acquired in step 3rd, place k1 = "V1" In the server's memory The code is implemented as follows: 123 mc=memcache.Client([(‘1.1.1.1:12000‘,1), (‘1.1.1.2:12000‘,2), (‘1.1.1.3:12000‘,1)], debug=True)mc.set(‘k1‘,‘v1‘) 4. Add (KeyName, value)Obj.add (' K1 ', ' v1 ') obj.add (' K1 ', ' v1 ') v1 = obj.get (' K1 ') print (' v1: ', v1) out:MemCached:while expecting ' STORED ', got une xpected response ' no