springboot-整合redis
springboot学习笔记-4 整合Druid数据源和使用@Cache简化redis配置
一.整合Druid数据源
Druid是一个关系型数据库连接池,是阿里巴巴的一个开源项目,Druid在监控,可扩展性,稳定性和性能方面具有比较明显的优势.通过Druid提供的监控功能,可以实时观察数据库连接池和SQL查询的工作情况.使用Druid在一定程度上可以提高数据库的访问技能.
1.1 在pom.xml中添加依赖
<dependency> <groupId>com.alibaba</groupId> <artifactId>druid</artifactId> <version>1.0.18</version> </dependency>
1.2 Druid数据源配置
在application.properties中,去书写Druid数据源的配置信息.
##Druid## spring.datasource.type=com.alibaba.druid.pool.DruidDataSource spring.datasource.driver-class-name=com.mysql.jdbc.Driver spring.datasource.url=jdbc:mysql://localhost:3306/test?characterEncoding=UTF-8 spring.datasource.username=root spring.datasource.password=root spring.datasource.initialSize=5 spring.datasource.minIdle=5 spring.datasource.maxActive=20 spring.datasource.maxWait=60000 spring.datasource.timeBetweenEvictionRunsMillis=60000 spring.datasource.minEvictableIdleTimeMillis=300000 spring.datasource.validationQuery=SELECT 1 FROM DUAL spring.datasource.testWhileIdle=true spring.datasource.testOnBorrow=false spring.datasource.testOnReturn=false spring.datasource.poolPreparedStatements=true spring.datasource.maxPoolPreparedStatementPerConnectionSize=20 spring.datasource.filters=stat,wall,log4j spring.datasource.connectionProperties=druid.stat.mergeSql=true;druid.stat.slowSqlMillis=5000 spring.datasource.useGlobalDataSourceStat=true
1.3 建立DruidConfiguration配置类,配置过滤信息
@Configuration public class DruidConfiguration { @Bean public ServletRegistrationBean statViewServle(){ ServletRegistrationBean servletRegistrationBean = new ServletRegistrationBean(new StatViewServlet(),"/druid/*"); //白名单: servletRegistrationBean.addInitParameter("allow","192.168.1.218,127.0.0.1"); //IP黑名单 (存在共同时,deny优先于allow) : 如果满足deny的即提示:Sorry, you are not permitted to view this page. servletRegistrationBean.addInitParameter("deny","192.168.1.100"); //登录查看信息的账号密码. servletRegistrationBean.addInitParameter("loginUsername","druid"); servletRegistrationBean.addInitParameter("loginPassword","12345678"); //是否能够重置数据. servletRegistrationBean.addInitParameter("resetEnable","false"); return servletRegistrationBean; } @Bean public FilterRegistrationBean statFilter(){ FilterRegistrationBean filterRegistrationBean = new FilterRegistrationBean(new WebStatFilter()); //添加过滤规则. filterRegistrationBean.addUrlPatterns("/*"); //添加不需要忽略的格式信息. filterRegistrationBean.addInitParameter("exclusions","*.js,*.gif,*.jpg,*.png,*.css,*.ico,/druid/*"); return filterRegistrationBean; } }
1.4 配置数据源的信息
告诉springboot采用Druid数据源:
@Bean(name = "dataSource") @Primary @ConfigurationProperties(prefix = "spring.datasource") public DataSource dataSource(){ return DataSourceBuilder.create().type(com.alibaba.druid.pool.DruidDataSource.class).build(); }
接下来就可以通过localhost:8080/druid/index.html去打开控制台,观察过滤信息了!
二.使用@Cache简化redis配置
在实体类比较简单的时候(例如:没有一对多,多对多这类复杂的关系,不是List,Map这类数据类型,只是一个Pojo类),可以使用@Cache去替代书写BeanRedis注入RedisTemplate的方式去访问Redis数据库.
2.1 建立RoleService.采用@Cacheable和@CachePut去访问Redis
实体类的主要属性如下:
2.1 建立Redis配置类,需要去配置Redis的注解
@ConfigurationProperties("application.properties") @Configuration @EnableCaching public class RedisConfig extends CachingConfigurerSupport { @Value("${spring.redis.hostName}") private String hostName; @Value("${spring.redis.port}") private Integer port; @Bean public RedisConnectionFactory redisConnectionFactory() { JedisConnectionFactory cf = new JedisConnectionFactory(); cf.setHostName(hostName); cf.setPort(port); cf.afterPropertiesSet(); return cf; } //配置key的生成 @Bean public KeyGenerator simpleKey(){ return new KeyGenerator() { @Override public Object generate(Object target, Method method, Object... params) { StringBuilder sb = new StringBuilder(); sb.append(target.getClass().getName()+":"); for (Object obj : params) { sb.append(obj.toString()); } return sb.toString(); } }; } //配置key的生成 @Bean public KeyGenerator objectId(){ return new KeyGenerator() { @Override public Object generate(Object target, Method method, Object... params){ StringBuilder sb = new StringBuilder(); sb.append(target.getClass().getName()+":"); try { sb.append(params[0].getClass().getMethod("getId", null).invoke(params[0], null).toString()); }catch (NoSuchMethodException no){ no.printStackTrace(); }catch(IllegalAccessException il){ il.printStackTrace(); }catch(InvocationTargetException iv){ iv.printStackTrace(); } return sb.toString(); } }; } //配置注解 @Bean public CacheManager cacheManager(@SuppressWarnings("rawtypes") RedisTemplate redisTemplate) { RedisCacheManager manager = new RedisCacheManager(redisTemplate); manager.setDefaultExpiration(43200);//12小时 return manager; } //对于复杂的属性仍然使用RedisTemplate @Bean public RedisTemplate<String, String> redisTemplate( RedisConnectionFactory factory) { StringRedisTemplate template = new StringRedisTemplate(factory); Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class); ObjectMapper om = new ObjectMapper(); om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY); om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL); jackson2JsonRedisSerializer.setObjectMapper(om); template.setValueSerializer(jackson2JsonRedisSerializer); template.afterPropertiesSet(); return template; } }
2.2
- 编写redis的service类操作edis数据库
package cn.springboot.mybatis.service;
import java.io.Serializable;
import java.util.List;
import java.util.Set;
import java.util.concurrent.TimeUnit;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.HashOperations;
import org.springframework.data.redis.core.ListOperations;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.SetOperations;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.data.redis.core.ZSetOperations;
import org.springframework.stereotype.Service;
@Service
public class RedisService {
@Autowired
private RedisTemplate redisTemplate;
/**
* 写入缓存
* @param key
* @param value
* @return
*/
public boolean set(final String key, Object value) {
boolean result = false;
try {
ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
operations.set(key, value);
result = true;
} catch (Exception e) {
e.printStackTrace();
}
return result;
}
/**
* 写入缓存设置时效时间
* @param key
* @param value
* @return
*/
public boolean set(final String key, Object value, Long expireTime) {
boolean result = false;
try {
ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
operations.set(key, value);
redisTemplate.expire(key, expireTime, TimeUnit.SECONDS);
result = true;
} catch (Exception e) {
e.printStackTrace();
}
return result;
}
/**
* 批量删除对应的value
* @param keys
*/
public void remove(final String... keys) {
for (String key : keys) {
remove(key);
}
}
/**
* 批量删除key
* @param pattern
*/
public void removePattern(final String pattern) {
Set<Serializable> keys = redisTemplate.keys(pattern);
if (keys.size() > 0)
redisTemplate.delete(keys);
}
/**
* 删除对应的value
* @param key
*/
public void remove(final String key) {
if (exists(key)) {
redisTemplate.delete(key);
}
}
/**
* 判断缓存中是否有对应的value
* @param key
* @return
*/
public boolean exists(final String key) {
return redisTemplate.hasKey(key);
}
/**
* 读取缓存
* @param key
* @return
*/
public Object get(final String key) {
Object result = null;
ValueOperations<Serializable, Object> operations = redisTemplate.opsForValue();
result = operations.get(key);
return result;
}
/**
* 哈希 添加
* @param key
* @param hashKey
* @param value
*/
public void hmSet(String key, Object hashKey, Object value){
HashOperations<String, Object, Object> hash = redisTemplate.opsForHash();
hash.put(key,hashKey,value);
}
/**
* 哈希获取数据
* @param key
* @param hashKey
* @return
*/
public Object hmGet(String key, Object hashKey){
HashOperations<String, Object, Object> hash = redisTemplate.opsForHash();
return hash.get(key,hashKey);
}
/**
* 列表添加
* @param k
* @param v
*/
public void lPush(String k,Object v){
ListOperations<String, Object> list = redisTemplate.opsForList();
list.rightPush(k,v);
}
/**
* 列表获取
* @param k
* @param l
* @param l1
* @return
*/
public List<Object> lRange(String k, long l, long l1){
ListOperations<String, Object> list = redisTemplate.opsForList();
return list.range(k,l,l1);
}
/**
* 集合添加
* @param key
* @param value
*/
public void add(String key,Object value){
SetOperations<String, Object> set = redisTemplate.opsForSet();
set.add(key,value);
}
/**
* 集合获取
* @param key
* @return
*/
public Set<Object> setMembers(String key){
SetOperations<String, Object> set = redisTemplate.opsForSet();
return set.members(key);
}
/**
* 有序集合添加
* @param key
* @param value
* @param scoure
*/
public void zAdd(String key,Object value,double scoure){
ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
zset.add(key,value,scoure);
}
/**
* 有序集合获取
* @param key
* @param scoure
* @param scoure1
* @return
*/
public Set<Object> rangeByScore(String key,double scoure,double scoure1){
ZSetOperations<String, Object> zset = redisTemplate.opsForZSet();
return zset.rangeByScore(key, scoure, scoure1);
}
}
2.3 controller测试
@RestController
public class MessageController {
@Autowired
private RedisService redisService;
/* @RequestMapping(value = "/message",method = RequestMethod.GET)
@ResponseBody
public List<String> greeting(String user) {
List<String> messages = cacheService.listMessages(user);
return messages;
}*/
@RequestMapping(value = "/message1",method = RequestMethod.GET)
@ResponseBody
public String saveGreeting(String user,String message) {
String usestrr="hello";
String message1="world";
redisService.set("002", message1);
return "OK";
}
}
补充:
使用@Cache简化redis配置
在实体类比较简单的时候(例如:没有一对多,多对多这类复杂的关系,不是List,Map这类数据类型,只是一个Pojo类),可以使用@Cache去替代书写BeanRedis注入RedisTemplate的方式去访问Redis数据库.
2.1 建立RoleService.采用@Cacheable和@CachePut去访问Redis
实体类的主要属性如下:
本例子没用使用该方法赶兴趣的可以试一下下面是源码
@Service public class RoleService { @Autowired private RoleRepository roleRepository; @Autowired private RoleRedis roleRedis; @Cacheable(value = "mysql:findById:role", keyGenerator = "simpleKey") public Role findById(Long id) { System.out.println("从数据库中查询"); return roleRepository.findOne(id); } @CachePut(value = "mysql:findById:role", keyGenerator = "objectId") public Role create(Role role) { System.out.println("************在数据库中创建************"); return roleRepository.save(role); } //简单的操作使用注解的形式 @CachePut(value = "mysql:findById:role", keyGenerator = "objectId") public Role update(Role role) { System.out.println("************在数据库中更新************"); return roleRepository.save(role); } @CacheEvict(value = "mysql:findById:role", keyGenerator = "simpleKey") public void delete(Long id) { System.out.println("************在数据库中销毁************"); roleRepository.delete(id); } public List<Role> findAll(){ List<Role> roleList = roleRedis.getList("mysql:findAll:role"); if(roleList == null) { roleList = roleRepository.findAll(); if(roleList != null) roleRedis.add("mysql:findAll:role", 5L, roleList); } return roleList; } //复杂的依然使用RedisTemplate的形式 public Page<Role> findPage(RoleQo roleQo){ Pageable pageable = new PageRequest(roleQo.getPage(), roleQo.getSize(), new Sort(Sort.Direction.ASC, "id")); PredicateBuilder pb = new PredicateBuilder(); if (!StringUtils.isEmpty(roleQo.getName())) { pb.add("name","%" + roleQo.getName() + "%", LinkEnum.LIKE); } Page<Role> pages = roleRepository.findAll(pb.build(), Operator.AND, pageable); return pages; } }
本文章参考一下两篇博客
1
http://www.cnblogs.com/hlhdidi/p/6350306.html
2
http://www.cnblogs.com/haitao-xie/p/6323423.html