一、操作string 、list 、map 对象1、引入jar:jedis-2.1.0.jar 2、代码/** * @param args */ public static void main(String[] args) { //连接redis服务 Jedis jedis = new Jedis(192.168.88.15,6379); //密码验证-如果你没有设置redis密码可不验证即可使用
一、操作string 、list 、map 对象 1、引入jar: jedis-2.1.0.jar 2、代码 /** * @param args */ public static void main(String[] args) { //连接redis服务 Jedis jedis = new Jedis("192.168.88.15",6379); //密码验证-如果你没有设置redis密码可不验证即可使用相关命令 // jedis.auth("abcdefg"); //简单的key-value 存储 jedis.set("redis", "myredis"); System.out.println(jedis.get("redis")); //在原有值得基础上添加,如若之前没有该key,则导入该key //之前已经设定了redis对应"myredis",此句执行便会使redis对应"myredisyourredis" jedis.append("redis", "yourredis"); jedis.append("content", "rabbit"); //mset 是设置多个key-value值 参数(key1,value1,key2,value2,...,keyn,valuen) //mget 是获取多个key所对应的value值 参数(key1,key2,key3,...,keyn) 返回的是个list jedis.mset("name1","yangw","name2","demon","name3","elena"); System.out.println(jedis.mget("name1","name2","name3")); //map Map1、自定义pojo 实现Serializable 接口: package cn.mingyuan.redis; import java.io.Serializable; /** * 测试用pojo,实现了Serializable,以便进行系列化操作 * * @author mingyuan * */ public class Person implements Serializable { private static final long serialVersionUID = -3562550857760039655L; private String name; private int age; public Person(){} public Person(String name, int age) { super(); this.name = name; this.age = age; } public String getName() { return name; } public void setName(String name) { this.name = name; } public int getAge() { return age; } public void setAge(int age) { this.age = age; } @Override public String toString() { return "Person [name=" + name + ", age=" + age + "]"; } } 2、测试类: package cn.mingyuan.redis; import java.io.ByteArrayInputStream; import java.io.ByteArrayOutputStream; import java.io.IOException; import java.io.ObjectInputStream; import java.io.ObjectOutputStream; import redis.clients.jedis.Jedis; public class Test { /** * @param args * @throws IOException * @throws ClassNotFoundException */ public static void main(String[] args) throws IOException, ClassNotFoundException { // Jedis redis = new Jedis("192.168.88.15"); Jedis redis = new Jedis("192.168.88.15", 6379); // connect可以不要,因为在执行set操作的时候会先进行判断客户端是否于服务器端建立了连接,若无,则启动连接过程 redis.connect(); String set = redis.set("mingyuan", "1"); System.out.println(" set result \t" + set); redis.incr("mingyuan"); String string = redis.get("mingyuan"); System.out.println(" get result of key 'mingyuan' \t" + string); // 下面是对对象进行存储的测试代码 ByteArrayOutputStream bos = new ByteArrayOutputStream(); ObjectOutputStream oos = new ObjectOutputStream(bos); Person person = new Person("liudehua" ,22); oos.writeObject(person); byte[] byteArray = bos.toByteArray(); oos.close(); bos.close(); String setObjectRet = redis.set("mingyuan".getBytes(), byteArray); System.out.println(" set object return \t" + setObjectRet); byte[] bs = redis.get("mingyuan".getBytes()); ByteArrayInputStream bis = new ByteArrayInputStream(bs); ObjectInputStream inputStream = new ObjectInputStream(bis); Person readObject = (Person) inputStream.readObject(); System.out.println(" read object \t" + readObject.toString()); inputStream.close(); bis.close(); redis.disconnect(); } }

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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