这一篇主要是redis操作工具类以及基本配置文本储存
首先我们需要定义一个redisUtil去操作底层redis数据库：
1 package com.lcc.cache.redis; 2 3 import java.util.Date; 4 import java.util.Map; 5 6 import org.joda.time.LocalDate; 7 import org.springframework.dao.DataAccessException; 8 import org.springframework.data.redis.core.RedisOperations; 9 import org.springframework.data.redis.core.RedisTemplate; 10 import org.springframework.data.redis.core.SessionCallback; 11 12 public class RedisUtil { 13 private RedisTemplate<String, Object> redisTemplate; 14 15 public Map<Object, Object> getHashValue(String key) { 16 return redisTemplate.opsForHash().entries(key); 17 } 18 19 public <V> void setHashValue(String key, String hashKey, V value, Date date) { 20 if (date == null) { 21 date = LocalDate.now().plusDays(1).toDate(); 22 } 23 Date expire = date; 24 redisTemplate.executePipelined(new SessionCallback<Object>() { 25 @Override 26 public <String, V> Object execute(RedisOperations<String, V> operations) throws DataAccessException { 27 operations.opsForHash().put((String) key, hashKey, value.toString()); 28 operations.expireAt((String) key, expire); 29 return null; 30 } 31 }); 32 } 33 34 public void setHashValue(String key, Map<Object, Object> values, Date date) { 35 if (date == null) { 36 date = LocalDate.now().plusDays(1).toDate(); 37 } 38 Date expire = date; 39 redisTemplate.executePipelined(new SessionCallback<Object>() { 40 @Override 41 public <String, V> Object execute(RedisOperations<String, V> operations) throws DataAccessException { 42 for (Object hashKey : values.keySet()) { 43 operations.opsForHash().put((String) key, hashKey, values.get(hashKey).toString()); 44 operations.expireAt((String) key, expire); 45 } 46 return null; 47 } 48 }); 49 } 50 51 public void delete(String key) { 52 redisTemplate.delete(key); 53 } 54 55 public RedisTemplate<String, Object> getRedisTemplate() { 56 return redisTemplate; 57 } 58 59 public void setRedisTemplate(RedisTemplate<String, Object> redisTemplate) { 60 this.redisTemplate = redisTemplate; 61 } 62 63 }
上面是基本的增删查操作，以及设置key的过期时间，该工具类是基于hash操作的。
工具类有了，我们自然要有一个业务逻辑去具体处理这些数据，接下来我们就建一个RedisService:
1 package com.lcc.cache.redis; 2 3 import java.io.IOException; 4 import java.math.BigDecimal; 5 import java.util.ArrayList; 6 import java.util.Date; 7 import java.util.HashMap; 8 import java.util.List; 9 import java.util.Map; 10 11 import org.joda.time.LocalDate; 12 import org.joda.time.LocalDateTime; 13 14 import com.alibaba.dubbo.common.utils.StringUtils; 15 import com.fasterxml.jackson.core.JsonParseException; 16 import com.fasterxml.jackson.core.JsonProcessingException; 17 import com.fasterxml.jackson.databind.JsonMappingException; 18 import com.fasterxml.jackson.databind.ObjectMapper; 19 import com.lcc.api.dto.TruckCacheDto; 20 21 public class RedisService { 22 23 private RedisUtil redisUtil; 24 25 private int cacheDay = 1; 26 27 private String prefix = "truckCache:"; 28 29 public TruckCacheDto getTruckById(String id) throws JsonParseException, JsonMappingException, IOException { 30 Map<Object, Object> map = redisUtil.getHashValue(prefix + id); 31 map.put("id", id); 32 TruckCacheDto dto = new TruckCacheDto(); 33 prepareDto(map, dto); 34 return dto; 35 } 36 37 private void prepareDto(Map<Object, Object> map, TruckCacheDto dto) 38 throws JsonParseException, JsonMappingException, IOException { 39 dto.setId(map.get("id").toString()); 40 if (map.get("lat") != null) { 41 dto.setLat(Double.parseDouble(map.get("lat").toString())); 42 } 43 if (map.get("lng") != null) { 44 dto.setLng(Double.parseDouble(map.get("lng").toString())); 45 } 46 if (map.get("temp") != null) { 47 ObjectMapper co = new ObjectMapper(); 48 String temp = map.get("temp").toString(); 49 List tList = co.readValue(temp, List.class); 50 List<Double> tempList = new ArrayList(); 51 if (tList == null) { 52 tList = new ArrayList(); 53 } 54 for (Object o : tList) { 55 if (o != null) { 56 tempList.add(new BigDecimal(o.toString()).doubleValue()); 57 } 58 } 59 dto.setTempList(tempList); 60 } 61 if (map.get("time") != null) { 62 dto.setTime(new Date(Long.valueOf(map.get("time").toString()))); 63 } 64 if (map.get("address") != null) { 65 dto.setAddress(map.get("address").toString()); 66 } 67 } 68 69 public void setLocation(String id, Double lat, Double lng, String address) { 70 Map<Object, Object> map = new HashMap<Object, Object>(); 71 map.put("lat", lat); 72 map.put("lng", lng); 73 map.put("time", LocalDateTime.now().toDate().getTime()); 74 if (StringUtils.isNotEmpty(address)) { 75 map.put("address", address); 76 } 77 redisUtil.setHashValue(prefix + id, map, getExpireDate()); 78 } 79 80 public <T> void setTemp(String id, List<T> tempList) throws JsonProcessingException { 81 Map<Object, Object> map = new HashMap<Object, Object>(); 82 ObjectMapper co = new ObjectMapper(); 83 String temp = co.writeValueAsString(tempList); 84 map.put("temp", temp); 85 map.put("time", LocalDateTime.now().toDate().getTime()); 86 redisUtil.setHashValue(prefix + id, map, getExpireDate()); 87 } 88 89 public <T> void setTempAndLocation(String id, Double lat, Double lng, List<T> tempList, String address) 90 throws JsonProcessingException { 91 Map<Object, Object> map = new HashMap<Object, Object>(); 92 map.put("lat", lat); 93 map.put("lng", lng); 94 ObjectMapper co = new ObjectMapper(); 95 String temp = co.writeValueAsString(tempList); 96 map.put("temp", temp); 97 map.put("time", LocalDateTime.now().toDate().getTime()); 98 if (StringUtils.isNotEmpty(address)) { 99 map.put("address", address); 100 } 101 redisUtil.setHashValue(prefix + id, map, getExpireDate()); 102 } 103 104 public void delete(String id) { 105 redisUtil.delete(prefix + id); 106 } 107 108 private Date getExpireDate() { 109 return LocalDate.now().plusDays(cacheDay).toDate(); 110 } 111 112 public RedisUtil getRedisUtil() { 113 return redisUtil; 114 } 115 116 public void setRedisUtil(RedisUtil redisUtil) { 117 this.redisUtil = redisUtil; 118 } 119 120 public int getCacheDay() { 121 return cacheDay; 122 } 123 124 public void setCacheDay(int cacheDay) { 125 this.cacheDay = cacheDay; 126 } 127 128 }
此时，我们的一个service就写好了，我们在接口层面或者service层面可以随时调用这个RedisService了。
很显然，有了上面的工具类和service还是不够了，我们需要在xml文件里面去配置，因为我们是基于spring的，可以建一个applicationContext_redisCache.xml.
1 <?xml version="1.0" encoding="UTF-8" standalone="no"?> 2 <beans xmlns="http://www.springframework.org/schema/beans" 3 xmlns:aop="http://www.springframework.org/schema/aop" 4 xmlns:context="http://www.springframework.org/schema/context" 5 xmlns:jee="http://www.springframework.org/schema/jee" xmlns:p="http://www.springframework.org/schema/p" 6 xmlns:tx="http://www.springframework.org/schema/tx" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" 7 xmlns:rabbit="http://www.springframework.org/schema/rabbit" 8 xsi:schemaLocation="http://www.springframework.org/schema/aop 9 http://www.springframework.org/schema/aop/spring-aop-3.0.xsd 10 http://www.springframework.org/schema/beans 11 http://www.springframework.org/schema/beans/spring-beans-3.0.xsd 12 http://www.springframework.org/schema/context 13 http://www.springframework.org/schema/context/spring-context-3.0.xsd 14 http://www.springframework.org/schema/jee 15 http://www.springframework.org/schema/jee/spring-jee-3.0.xsd 16 http://www.springframework.org/schema/tx 17 http://www.springframework.org/schema/tx/spring-tx-3.0.xsd 18 http://www.springframework.org/schema/rabbit 19 http://www.springframework.org/schema/rabbit/spring-rabbit-1.0.xsd"> 20 21 22 <bean class="com.lcc.cache.redis.RedisService" id="redisService"> 23 <property name="redisUtil" ref="redisUtil"/> 24 <property name="cacheDay" value="${truckCache.redis.cacheDay}"/> 25 </bean> 26 27 <bean class="com.lcc.cache.redis.RedisUtil" id="redisUtil"> 28 <property name="redisTemplate" ref="truckkCacheRedisJdkSerializationTemplate"/> 29 </bean> 30 31 <bean class="org.springframework.data.redis.core.RedisTemplate" 32 id="truckkCacheRedisJdkSerializationTemplate" p:connection-factory-ref="truckCacheRedisConnectionFactory"> 33 <property name="keySerializer"> 34 <bean 35 class="org.springframework.data.redis.serializer.StringRedisSerializer"/> 36 </property> 37 <property name="valueSerializer"> 38 <bean 39 class="org.springframework.data.redis.serializer.StringRedisSerializer"/> 40 </property> 41 </bean> 42 43 <bean id="truckCacheRedisConnectionFactory" 44 class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory" 45 p:host-name="${truckCache.redis.host}" p:port="${truckCache.redis.port}"> 46 <constructor-arg index="0" ref="jedisPoolConfig"/> 47 </bean> 48 49 <bean id="jedisPoolConfig" class="redis.clients.jedis.JedisPoolConfig"> 50 <property name="maxTotal" value="60"/> 51 <property name="maxIdle" value="15"/> 52 <property name="testOnBorrow" value="true"/> 53 </bean> 54 55 </beans>
此时我们的xml配置就完成了，这里是配置一些redis数据库配置和注入类。
到此我们还差一个数据，就是redis服务器数据，我们可以建一个properties文件，这样子方便我们对项目的数据进行修改，redis.properties:
truckCache.redis.host = localhost
truckCache.redis.port = 6379
truckCache.redis.cacheDay = 1
我们的RedisService在springxml文件里配置完成了，在接口层面我们可以利用spring框架的自动注入功能注入RedisService了，进而对redis数据库进行各种操作了。