Memcached's skills and experience sharing in high -concurring scenes

Title: Use MEMCACHED skills and experience in high concurrent scenes to share Abstract: Memcached is a commonly used memory cache system that is widely used to improve the system performance in high concurrency scenes.This article will share some techniques and experiences using Memcached in high concurrency environments, covering a description of related configuration and complete programming code. --- introduction: In today's highly concurrent environment, performance is usually one of the important considerations of system design.In order to meet user needs and provide excellent user experience, it is crucial to efficiently handle concurrent requests.As a distributed memory cache system as a distributed memory cache system, MEMCACHED provides excellent performance and scalability. It can significantly reduce the load of the back -end storage of databases, thereby improving the overall performance of the system. This article will introduce some techniques and experiences of MEMCACHED in high -concurrent scenes, and provide corresponding programming code and configuration descriptions to help readers better understand and apply Memcached. 1. Basic configuration and use 1. Installation and deployment MEMCACHED Before using MEMCACHED, you first need to install and deploy the MEMCACHED server.For specific steps, please refer to the official MEMCACHHED documentation. 2. Connect and set Memcached It is very simple to connect and set MEMCACHED in applications. Usually, the client library of Memcached is used to implement.The following is a simple Python code example: python import memcache # mc = memcache.Client(['127.0.0.1:11211']) # 缓 缓 mc.set('key', 'value', time=3600) # Get the cache data data = mc.get('key') In the above example, we connect to the Memcached server through the `Memcache.client` class, set the cache data with the` set` method, and use the `Get` method to obtain the cache data. Two, use skills 1. Cache hot data In high -concurrency scenes, certain data may be requested frequently, and these data can be called hot data.Slowly existing these hot data in MEMCACHED can greatly reduce loads such as database storage.When setting the cache data, you can set the appropriate expiration time to ensure the timely update of the data. 2. Use the appropriate cache strategy According to the actual needs of the application, choosing an appropriate cache strategy is essential to improve the performance of the system.Common cache strategies include time -based expiration strategies, LRU -based strategies (recently used) strategies.According to specific circumstances, you can reasonably configure the cache strategy of Memcached. 3. Use multiple MEMCACHED nodes In high -concurrency scenes, in order to improve the availability and performance of the system, multiple MEMCACHED nodes can be used for load balancing.By configured the address of multiple MEMCACHED nodes in the code, the distribution and load balancing of the request can be achieved. Third, optimization skills 1. Flexible use the CAS command MEMCACHED provides CAS (Compare and Set) command to support the optimistic lock mechanism.In the high -concurrency scene, when multiple requests update the same cache data at the same time, using the CAS command can avoid data conflict and update lost problems. python # Use CAS command to update the cache data mc.cas('key', 'old_value', 'new_value') In the above examples, the `Cas` method accepts three parameters, which are keys, old and new values of cache data.Only when the old value of the cache data is matched with the old value in the CAS command, the update operation will be performed. 2. Reasonably set the cache expiration time When setting the cache data, it is important to set the expiration time reasonably.Too short expiration time will cause frequent cache failures and increase in access pressure at the back -end storage. If the expiration time is too long, it may cause the data to be used after the expiration of the data, which affects the real -time nature of the data.According to the actual needs of the application, weighing the appropriate expiration time. Fourth, conclusion This article introduces some techniques and experiences of using MEMCACHED in the high -concurrency scene.By reasonable configuration and use of MEMCACHHHED, the performance and scalability of the system can be improved and loads stored in the rear -end storage.In practical applications, choosing appropriate cache strategies and optimization skills according to specific needs will help improve the performance and user experience of the system. (Complete programming code and related configurations can be implemented and adjusted according to the needs of specific projects) references: 1. MEMCACHED official document: https://memcached.org/ 2. MEMCACHED Python client library: https://github.com/linsomniac/Python-Memcached