The method and practical guide to optimize access performance using MEMCACHED

Method and practical guide to optimize access performance with Memcached introduction: When dealing with a large amount of data and high interviews, optimizing access performance is essential for websites and applications.MEMCACHED is a high -performance distributed memory object cache system that can significantly improve access speed and reduce database loads.This article will introduce methods and practical guidelines to optimize access performance using MEMCACHED. 1. Installation and configuration MEMCACHED To use Memcached, we need to install and configure it on the server.The following is the step of installing Memcached on Ubuntu: 1. Open the terminal and use the following commands to install Memcached: sudo apt-get update sudo apt-get install memcached 2. After the installation is complete, edit the configuration file of Memcached.Open the `/etc/memcached.conf` file and perform the necessary configuration changes.You can change parameters such as monitoring address, listening port, cache size.Save and close the file. 3. Restart the MEMCACHED service to make the configuration change to take effect: sudo systemctl restart memcached Second, use MEMCACHED cache data Next, we need to store data in Memcached for cache.The following is a sample code fragment for storing and obtaining data: python import memcache # cache = memcache.Client(['localhost:11211']) # Store data to the cache cache.set('key1', 'value1') cache.set ('key2', 'value2', time = 3600) # Set the expiration time of 1 hour # Get data from the cache data1 = cache.get('key1') data2 = cache.get('key2') Print (data1) # Output: Value1 Print (data2) # Output: Value2 In this example, we use the `Memcache` module to connect to the local MEMCACHED server.We use the `set ()` method to store the key values into the cache, and use the `Get ()` method to obtain data from the cache.You can also set the expiration time for the method of `set ()` to ensure that the data in the cache will expire automatically after a period of time. Third, cache data query results In terms of database query, we can use the Memcached cache query results to reduce the database load.Here are a sample code fragment that uses the MEMCACHED cache query results: python import memcache import MySQLdb # cache = memcache.Client(['localhost:11211']) # Treatment query logic def query_data_from_database(query): # Check whether there is a query result in the cache result = cache.get(query) if not result: # Database query operation db = MySQLdb.connect(host="localhost", user="username", passwd="password", db="database") cursor = db.cursor() cursor.execute(query) result = cursor.fetchall() # Store query results to cache cache.set(query, result, time=3600) # Close database connection cursor.close() db.close() return result # Query data and print results query = "SELECT * FROM products WHERE category='electronics'" data = query_data_from_database(query) print(data) In this example, we first check whether there are query results in the cache.If there is no result in the cache, perform the database query operation and store the results into the cache.At the same time, we set the expiration time of the query results for 1 hour.If there is a query result in the cache, get the result directly from the cache.This can avoid repeated database query operations, improve access performance and reduce the database load. in conclusion: By using MEMCACHED, we can effectively optimize access performance.In practice, we need to correctly install and configure MEMCACHED, and store the data into the cache to reduce the database load.At the same time, we can use Memcached cache query results to avoid repeated database query operations.These methods and practical guidelines can significantly improve the access speed of websites and applications and improve user experience.