Redis將數據存儲到內存的,速度快。能夠解決請求mysql數據庫過多而致使mysql崩潰的問題。java
SpringData是專門用來控制Redis的工具,使用SpringData來操做Redis。mysql
注意:在使用了Redis後,修改數據須要將Redis中的數據刪除,以後再查的時候在賦值。redis
<dependencies> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>4.9</version> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring-context</artifactId> <version>4.2.4.RELEASE</version> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring-beans</artifactId> <version>4.2.4.RELEASE</version> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring-context-support</artifactId> <version>4.2.4.RELEASE</version> </dependency> <dependency> <groupId>org.springframework</groupId> <artifactId>spring-test</artifactId> <version>4.2.4.RELEASE</version> </dependency> <dependency> <groupId>redis.clients</groupId> <artifactId>jedis</artifactId> <version>2.8.1</version> </dependency> <dependency> <groupId>org.springframework.data</groupId> <artifactId>spring-data-redis</artifactId> <version>1.7.2.RELEASE</version> </dependency> </dependencies>
<?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:p="http://www.springframework.org/schema/p" xmlns:context="http://www.springframework.org/schema/context" xmlns:dubbo="http://code.alibabatech.com/schema/dubbo" xmlns:mvc="http://www.springframework.org/schema/mvc" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd http://www.springframework.org/schema/mvc http://www.springframework.org/schema/mvc/spring-mvc.xsd http://code.alibabatech.com/schema/dubbo http://code.alibabatech.com/schema/dubbo/dubbo.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context.xsd"> <context:property-placeholder location="classpath*:*.properties" /> <!-- redis 相關配置 --> <bean id="poolConfig" class="redis.clients.jedis.JedisPoolConfig"> <property name="maxIdle" value="${redis.maxIdle}" /> <property name="maxWaitMillis" value="${redis.maxWait}" /> <property name="testOnBorrow" value="${redis.testOnBorrow}" /> </bean> <bean id="JedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory" p:host-name="${redis.host}" p:port="${redis.port}" p:password="${redis.pass}" p:pool-config-ref="poolConfig"/> <bean id="redisTemplate" class="org.springframework.data.redis.core.RedisTemplate"> <property name="connectionFactory" ref="JedisConnectionFactory" /> </bean> </beans>
redis.host=192.168.200.128 redis.port=6379 redis.pass= redis.database=0 redis.maxIdle=300 redis.maxWait=3000 redis.testOnBorrow=true
@RunWith(SpringJUnit4ClassRunner.class) @ContextConfiguration(locations={"classpath:applicationContext-redis.xml"}) public class TestString { @Autowired private RedisTemplate redisTemplate; //放數據 @Test public void testSet(){ redisTemplate.boundValueOps("testKey").set("0708java"); } //取數據 @Test public void get(){ String testKey = (String)redisTemplate.boundValueOps("testKey").get(); System.out.println(testKey); } @Test public void del(){ redisTemplate.delete("testKey"); } @Test public void hashPut(){ redisTemplate.boundHashOps("testHash").put("001","左青龍"); redisTemplate.boundHashOps("testHash").put("002","右白虎"); redisTemplate.boundHashOps("testHash").put("003","掃地僧"); redisTemplate.boundHashOps("testHash").put("004","滅霸"); } @Test public void hashGetOne(){ String testHash = (String)redisTemplate.boundHashOps("testHash").get("001"); System.out.println(testHash); } @Test public void hashGetAll(){ Map<String,String> testHash = redisTemplate.boundHashOps("testHash").entries(); Set<Map.Entry<String, String>> entries = testHash.entrySet(); for (Map.Entry<String, String> entry : entries) { System.out.println("key"+entry.getKey()+" value"+entry.getValue()); } } @Test public void hashDel(){ redisTemplate.boundHashOps("testHash").delete("001"); } @Test public void hashDelAll(){ redisTemplate.delete("testHash"); } //list @Test public void listLeftPush(){ redisTemplate.boundListOps("001").leftPush("趙敏"); redisTemplate.boundListOps("001").leftPush("周芷若"); redisTemplate.boundListOps("001").leftPush("小昭"); } @Test public void listRightPush(){ redisTemplate.boundListOps("001").rightPush("張無忌"); } @Test public void listGet(){ List<String> range = redisTemplate.boundListOps("001").range(0, 10); for (String s : range) { System.out.println(s); } } @Test public void listDel(){ redisTemplate.delete("001"); } }
在分佈式項目中。Redis就是一個緩存數據庫,速度快,不會形成mysql的數據訪問量過大。spring
# Redis settings # server IP redis.host=192.168.200.128 # server port redis.port=6379 # server pass redis.pass= # use dbIndex redis.database=0 # \u63A7\u5236\u4E00\u4E2Apool\u6700\u591A\u6709\u591A\u5C11\u4E2A\u72B6\u6001\u4E3Aidle(\u7A7A\u95F2\u7684)\u7684jedis\u5B9E\u4F8B redis.maxIdle=300 # \u8868\u793A\u5F53borrow(\u5F15\u5165)\u4E00\u4E2Ajedis\u5B9E\u4F8B\u65F6\uFF0C\u6700\u5927\u7684\u7B49\u5F85\u65F6\u95F4\uFF0C\u5982\u679C\u8D85\u8FC7\u7B49\u5F85\u65F6\u95F4(\u6BEB\u79D2)\uFF0C\u5219\u76F4\u63A5\u629B\u51FAJedisConnectionException\uFF1B redis.maxWait=3000 # \u5728borrow\u4E00\u4E2Ajedis\u5B9E\u4F8B\u65F6\uFF0C\u662F\u5426\u63D0\u524D\u8FDB\u884Cvalidate\u64CD\u4F5C\uFF1B\u5982\u679C\u4E3Atrue\uFF0C\u5219\u5F97\u5230\u7684jedis\u5B9E\u4F8B\u5747\u662F\u53EF\u7528\u7684 redis.testOnBorrow=true
public List<Content> findByCategoryIdFromRedis(Long categoryId) { //一、根據分類的id到redis中取數據 List<Content> list=(List<Content>)redisTemplate.boundHashOps(Constants.CONTENT_LIST_REDIS).get(categoryId); //2.若是redis中沒有數據,到數據庫中取 if(list==null){ list=findByCategoryId(categoryId); //三、數據庫中獲取到數據,將數據存入redis中一份 redisTemplate.boundHashOps(Constants.CONTENT_LIST_REDIS).put(categoryId,list); } return list; }