RedisTemplate的配置和讲解以及和StringRedisTemplate的区别

2023-11-30 07:12
文章标签 配置 讲解 区别 redistemplate stringredistemplate

本文主要是介绍RedisTemplate的配置和讲解以及和StringRedisTemplate的区别，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

本文主要讲redisTempalte的几种常用的序列化方式

  • string，我们大部分情况下都希望存入redis的数据可读性强一些，并且value也不总是一个规则的类型，所以这里也是不用json序列化的原因，可以更自由方便，下边提供配置方法 
    package sca.pro.core.redis.configuration;import cn.hutool.core.convert.Convert;
import org.apache.commons.pool2.impl.GenericObjectPoolConfig;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.cache.annotation.EnableCaching;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisPassword;
import org.springframework.data.redis.connection.RedisStandaloneConfiguration;
import org.springframework.data.redis.connection.lettuce.LettuceClientConfiguration;
import org.springframework.data.redis.connection.lettuce.LettuceConnectionFactory;
import org.springframework.data.redis.connection.lettuce.LettucePoolingClientConfiguration;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.RedisSerializer;
import org.springframework.data.redis.serializer.StringRedisSerializer;import java.time.Duration;@Configuration
@EnableCaching
public class RedisTemplateConfig {@Value("${spring.redis.database}")private int database;@Value("${spring.redis.host}")private String host;@Value("${spring.redis.password}")private String password;@Value("${spring.redis.port}")private String port;@Value("${spring.redis.timeout}")private String timeout;@Value("${spring.redis.lettuce.pool.max-idle}")private String maxIdle;@Value("${spring.redis.lettuce.pool.min-idle}")private String minIdle;@Value("${spring.redis.lettuce.pool.max-active}")private String maxActive;@Value("${spring.redis.lettuce.pool.max-wait}")private String maxWait;@Beanpublic LettuceConnectionFactory lettuceConnectionFactory() {GenericObjectPoolConfig genericObjectPoolConfig = new GenericObjectPoolConfig();genericObjectPoolConfig.setMaxIdle(Convert.toInt(maxIdle));genericObjectPoolConfig.setMinIdle(Convert.toInt(minIdle));genericObjectPoolConfig.setMaxTotal(Convert.toInt(maxActive));genericObjectPoolConfig.setMaxWaitMillis(Convert.toLong(maxWait));genericObjectPoolConfig.setTimeBetweenEvictionRunsMillis(100);RedisStandaloneConfiguration redisStandaloneConfiguration = new RedisStandaloneConfiguration();redisStandaloneConfiguration.setDatabase(database);redisStandaloneConfiguration.setHostName(host);redisStandaloneConfiguration.setPort(Convert.toInt(port));redisStandaloneConfiguration.setPassword(RedisPassword.of(password));LettuceClientConfiguration clientConfig = LettucePoolingClientConfiguration.builder().commandTimeout(Duration.ofMillis(Convert.toLong(timeout))).poolConfig(genericObjectPoolConfig).build();LettuceConnectionFactory factory = new LettuceConnectionFactory(redisStandaloneConfiguration, clientConfig);return factory;}@Beanpublic RedisTemplate<String, String> redisTemplate(LettuceConnectionFactory factory) {// 配置redisTemplateRedisTemplate<String, String> redisTemplate = new RedisTemplate<>();redisTemplate.setConnectionFactory(factory);redisTemplate.setKeySerializer(new StringRedisSerializer());//key序列化redisTemplate.setValueSerializer(new StringRedisSerializer());//value序列化//设置hash的key的序列化方式redisTemplate.setHashKeySerializer(new StringRedisSerializer());//设置hash的value的序列化方式redisTemplate.setHashValueSerializer(new StringRedisSerializer());redisTemplate.afterPropertiesSet();//使上面参数生效return redisTemplate;}
}

其实如果key和value都是string，那就等效于我们直接引入StringRedisTemplate 

  • 如果使用字节数组的形式序列化，redistemplate默认使用的jdk的序列化方式，但是jdk的序列化后的字节数组不仅重，而且序列化和反序列化我们用的是protobuf，如下

   pom

<!-- 工具库 -->
<dependency><groupId>com.google.guava</groupId><artifactId>guava</artifactId><version>18.0</version>
</dependency><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-redis</artifactId>
</dependency><!-- 序列化 -->
<dependency><groupId>com.dyuproject.protostuff</groupId><artifactId>protostuff-core</artifactId><version>1.1.3</version>
</dependency>
<dependency><groupId>com.dyuproject.protostuff</groupId><artifactId>protostuff-runtime</artifactId><version>1.1.3</version>
</dependency>

2.自己编写序列化工具

@Slf4j
public class ProtoStuffUtil {/*** 序列化对象** @param obj* @return*/public static <T> byte[] serialize(T obj) {if (obj == null) {log.error("Failed to serializer, obj is null");throw new RuntimeException("Failed to serializer");}@SuppressWarnings("unchecked") Schema<T> schema = (Schema<T>) RuntimeSchema.getSchema(obj.getClass());LinkedBuffer buffer = LinkedBuffer.allocate(1024 * 1024);byte[] protoStuff;try {protoStuff = ProtostuffIOUtil.toByteArray(obj, schema, buffer);} catch (Exception e) {log.error("Failed to serializer, obj:{}", obj, e);throw new RuntimeException("Failed to serializer");} finally {buffer.clear();}return protoStuff;}/*** 反序列化对象** @param paramArrayOfByte* @param targetClass* @return*/public static <T> T deserialize(byte[] paramArrayOfByte, Class<T> targetClass) {if (paramArrayOfByte == null || paramArrayOfByte.length == 0) {log.error("Failed to deserialize, byte is empty");throw new RuntimeException("Failed to deserialize");}T instance;try {instance = targetClass.newInstance();} catch (InstantiationException | IllegalAccessException e) {log.error("Failed to deserialize", e);throw new RuntimeException("Failed to deserialize");}Schema<T> schema = RuntimeSchema.getSchema(targetClass);ProtostuffIOUtil.mergeFrom(paramArrayOfByte, instance, schema);return instance;}/*** 序列化列表** @param objList* @return*/public static <T> byte[] serializeList(List<T> objList) {if (objList == null || objList.isEmpty()) {log.error("Failed to serializer, objList is empty");throw new RuntimeException("Failed to serializer");}@SuppressWarnings("unchecked") Schema<T> schema =(Schema<T>) RuntimeSchema.getSchema(objList.get(0).getClass());LinkedBuffer buffer = LinkedBuffer.allocate(1024 * 1024);byte[] protoStuff;ByteArrayOutputStream bos = null;try {bos = new ByteArrayOutputStream();ProtostuffIOUtil.writeListTo(bos, objList, schema, buffer);protoStuff = bos.toByteArray();} catch (Exception e) {log.error("Failed to serializer, obj list:{}", objList, e);throw new RuntimeException("Failed to serializer");} finally {buffer.clear();try {if (bos != null) {bos.close();}} catch (IOException e) {e.printStackTrace();}}return protoStuff;}/*** 反序列化列表** @param paramArrayOfByte* @param targetClass* @return*/public static <T> List<T> deserializeList(byte[] paramArrayOfByte, Class<T> targetClass) {if (paramArrayOfByte == null || paramArrayOfByte.length == 0) {log.error("Failed to deserialize, byte is empty");throw new RuntimeException("Failed to deserialize");}Schema<T> schema = RuntimeSchema.getSchema(targetClass);List<T> result;try {result = ProtostuffIOUtil.parseListFrom(new ByteArrayInputStream(paramArrayOfByte), schema);} catch (IOException e) {log.error("Failed to deserialize", e);throw new RuntimeException("Failed to deserialize");}return result;}}

3.RedisTemplate的工具类方法

@Component
public class RedisClient {private final RedisTemplate<String, String> redisTemplate;@Autowiredpublic RedisClient(RedisTemplate<String, String> redisTemplate) {this.redisTemplate = redisTemplate;}/*** get cache** @param field* @param targetClass* @param <T>* @return*/public <T> T get(final String field, Class<T> targetClass) {byte[] result = redisTemplate.execute((RedisCallback<byte[]>) connection -> connection.get(field.getBytes()));if (result == null) {return null;}return ProtoStuffUtil.deserialize(result, targetClass);}/*** put cache** @param field* @param obj* @param <T>* @return*/public <T> void set(String field, T obj) {final byte[] value = ProtoStuffUtil.serialize(obj);redisTemplate.execute((RedisCallback<Void>) connection -> {connection.set(field.getBytes(), value);return null;});}/*** put cache with expire time** @param field* @param obj* @param expireTime 单位: s* @param <T>*/public <T> void setWithExpire(String field, T obj, final long expireTime) {final byte[] value = ProtoStuffUtil.serialize(obj);redisTemplate.execute((RedisCallback<Void>) connection -> {connection.setEx(field.getBytes(), expireTime, value);return null;});}/*** get list cache** @param field* @param targetClass* @param <T>* @return*/public <T> List<T> getList(final String field, Class<T> targetClass) {byte[] result = redisTemplate.execute((RedisCallback<byte[]>) connection -> connection.get(field.getBytes()));if (result == null) {return null;}return ProtoStuffUtil.deserializeList(result, targetClass);}/*** put list cache** @param field* @param objList* @param <T>* @return*/public <T> void setList(String field, List<T> objList) {final byte[] value = ProtoStuffUtil.serializeList(objList);redisTemplate.execute((RedisCallback<Void>) connection -> {connection.set(field.getBytes(), value);return null;});}/*** put list cache with expire time** @param field* @param objList* @param expireTime* @param <T>* @return*/public <T> void setListWithExpire(String field, List<T> objList, final long expireTime) {final byte[] value = ProtoStuffUtil.serializeList(objList);redisTemplate.execute((RedisCallback<Void>) connection -> {connection.setEx(field.getBytes(), expireTime, value);return null;});}/*** get h cache** @param key* @param field* @param targetClass* @param <T>* @return*/public <T> T hGet(final String key, final String field, Class<T> targetClass) {byte[] result = redisTemplate.execute((RedisCallback<byte[]>) connection -> connection.hGet(key.getBytes(), field.getBytes()));if (result == null) {return null;}return ProtoStuffUtil.deserialize(result, targetClass);}/*** put hash cache** @param key* @param field* @param obj* @param <T>* @return*/public <T> boolean hSet(String key, String field, T obj) {final byte[] value = ProtoStuffUtil.serialize(obj);return redisTemplate.execute((RedisCallback<Boolean>) connection -> connection.hSet(key.getBytes(), field.getBytes(), value));}/*** put hash cache** @param key* @param field* @param obj* @param <T>*/public <T> void hSetWithExpire(String key, String field, T obj, long expireTime) {final byte[] value = ProtoStuffUtil.serialize(obj);redisTemplate.execute((RedisCallback<Void>) connection -> {connection.hSet(key.getBytes(), field.getBytes(), value);connection.expire(key.getBytes(), expireTime);return null;});}/*** get list cache** @param key* @param field* @param targetClass* @param <T>* @return*/public <T> List<T> hGetList(final String key, final String field, Class<T> targetClass) {byte[] result = redisTemplate.execute((RedisCallback<byte[]>) connection -> connection.hGet(key.getBytes(), field.getBytes()));if (result == null) {return null;}return ProtoStuffUtil.deserializeList(result, targetClass);}/*** put list cache** @param key* @param field* @param objList* @param <T>* @return*/public <T> boolean hSetList(String key, String field, List<T> objList) {final byte[] value = ProtoStuffUtil.serializeList(objList);return redisTemplate.execute((RedisCallback<Boolean>) connection -> connection.hSet(key.getBytes(), field.getBytes(), value));}/*** get cache by keys** @param key* @param fields* @param targetClass* @param <T>* @return*/public <T> Map<String, T> hMGet(String key, Collection<String> fields, Class<T> targetClass) {List<byte[]> byteFields = fields.stream().map(String::getBytes).collect(Collectors.toList());byte[][] queryFields = new byte[byteFields.size()][];byteFields.toArray(queryFields);List<byte[]> cache = redisTemplate.execute((RedisCallback<List<byte[]>>) connection -> connection.hMGet(key.getBytes(), queryFields));Map<String, T> results = new HashMap<>(16);Iterator<String> it = fields.iterator();int index = 0;while (it.hasNext()) {String k = it.next();if (cache.get(index) == null) {index++;continue;}results.put(k, ProtoStuffUtil.deserialize(cache.get(index), targetClass));index++;}return results;}/*** set cache by keys** @param field* @param values* @param <T>*/public <T> void hMSet(String field, Map<String, T> values) {Map<byte[], byte[]> byteValues = new HashMap<>(16);for (Map.Entry<String, T> value : values.entrySet()) {byteValues.put(value.getKey().getBytes(), ProtoStuffUtil.serialize(value.getValue()));}redisTemplate.execute((RedisCallback<Void>) connection -> {connection.hMSet(field.getBytes(), byteValues);return null;});}/*** get caches in hash** @param key* @param targetClass* @param <T>* @return*/public <T> Map<String, T> hGetAll(String key, Class<T> targetClass) {Map<byte[], byte[]> records = redisTemplate.execute((RedisCallback<Map<byte[], byte[]>>) connection -> connection.hGetAll(key.getBytes()));Map<String, T> ret = new HashMap<>(16);for (Map.Entry<byte[], byte[]> record : records.entrySet()) {T obj = ProtoStuffUtil.deserialize(record.getValue(), targetClass);ret.put(new String(record.getKey()), obj);}return ret;}/*** list index** @param key* @param index* @param targetClass* @param <T>* @return*/public <T> T lIndex(String key, int index, Class<T> targetClass) {byte[] value =redisTemplate.execute((RedisCallback<byte[]>) connection -> connection.lIndex(key.getBytes(), index));return ProtoStuffUtil.deserialize(value, targetClass);}/*** list range** @param key* @param start* @param end* @param targetClass* @param <T>* @return*/public <T> List<T> lRange(String key, int start, int end, Class<T> targetClass) {List<byte[]> value = redisTemplate.execute((RedisCallback<List<byte[]>>) connection -> connection.lRange(key.getBytes(), start, end));return value.stream().map(record -> ProtoStuffUtil.deserialize(record, targetClass)).collect(Collectors.toList());}/*** list left push** @param key* @param obj* @param <T>*/public <T> void lPush(String key, T obj) {final byte[] value = ProtoStuffUtil.serialize(obj);redisTemplate.execute((RedisCallback<Long>) connection -> connection.lPush(key.getBytes(), value));}/*** list left push** @param key* @param objList* @param <T>*/public <T> void lPush(String key, List<T> objList) {List<byte[]> byteFields = objList.stream().map(ProtoStuffUtil::serialize).collect(Collectors.toList());byte[][] values = new byte[byteFields.size()][];redisTemplate.execute((RedisCallback<Long>) connection -> connection.lPush(key.getBytes(), values));}/*** 精确删除key** @param key*/public void deleteCache(String key) {redisTemplate.delete(key);}/*** 排行榜的存入** @param redisKey* @param immutablePair*/public void zAdd(String redisKey, ImmutablePair<String, BigDecimal> immutablePair) {final byte[] key = redisKey.getBytes();final byte[] value = immutablePair.getLeft().getBytes();redisTemplate.execute((RedisCallback<Boolean>) connection -> connection.zAdd(key, immutablePair.getRight().doubleValue(), value));}/*** 获取排行榜低->高排序** @param redisKey 要进行排序的类别* @param start* @param end* @return*/public List<ImmutablePair<String, BigDecimal>> zRangeWithScores(String redisKey, int start, int end) {Set<RedisZSetCommands.Tuple> items = redisTemplate.execute((RedisCallback<Set<RedisZSetCommands.Tuple>>) connection -> connection.zRangeWithScores(redisKey.getBytes(), start, end));return items.stream().map(record -> ImmutablePair.of(new String(record.getValue()), BigDecimal.valueOf(record.getScore()))).collect(Collectors.toList());}/*** 获取排行榜高->低排序** @param redisKey 要进行排序的类别* @param start* @param end* @return*/public List<ImmutablePair<String, BigDecimal>> zRevRangeWithScores(String redisKey, int start, int end) {Set<RedisZSetCommands.Tuple> items = redisTemplate.execute((RedisCallback<Set<RedisZSetCommands.Tuple>>) connection -> connection.zRevRangeWithScores(redisKey.getBytes(), start, end));return items.stream().map(record -> ImmutablePair.of(new String(record.getValue()), BigDecimal.valueOf(record.getScore()))).collect(Collectors.toList());}
}
  • 最推荐的一种序列化方式GenericJackson2JsonRedisSerializer，org.springframework.data.redis.serializer.GenericJackson2JsonRedisSerializer 使用Jackson 实现JSON的序列化方式，Generic单词翻译过来表示：通用的意思，可以看出，是支持所有类。
@Bean@ConditionalOnMissingBean(name = "redisTemplate")public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory){RedisTemplate<String, Object> template = new RedisTemplate<>();template.setConnectionFactory(factory);//String的序列化方式StringRedisSerializer stringRedisSerializer = new StringRedisSerializer();// 使用GenericJackson2JsonRedisSerializer 替换默认序列化(默认采用的是JDK序列化)GenericJackson2JsonRedisSerializer genericJackson2JsonRedisSerializer = new GenericJackson2JsonRedisSerializer();//key序列化方式采用String类型template.setKeySerializer(stringRedisSerializer);//value序列化方式采用jackson类型template.setValueSerializer(genericJackson2JsonRedisSerializer);//hash的key序列化方式也是采用String类型template.setHashKeySerializer(stringRedisSerializer);//hash的value也是采用jackson类型template.setHashValueSerializer(genericJackson2JsonRedisSerializer);template.afterPropertiesSet();return template;}}

运行下边的测试类测试GenericJackson2JsonRedisSerializer，发现不管是字符串还是对象还是数组都很通用

@Test
void redisTemplateSerializeTest() {String redisTemplateStringKey = "redisTemplateStringKey";String redisTemplateUserObjectKey = "redisTemplateUserObjectKey";String redisTemplateUserArrayObjectKey = "redisTemplateUserArrayObjectKey";String redisTemplateJSONObjectKey = "redisTemplateJSONObjectKey";String redisTemplateJSONArrayKey = "redisTemplateJSONArrayKey";//序列化String类型和反序列化String类型redisTemplate.opsForValue().set(redisTemplateStringKey, "austin");String austin = (String) redisTemplate.opsForValue().get(redisTemplateStringKey);System.out.println("stringGet: " + austin);//序列化Object对象类型和反序列化Object对象类型 (User对象)User user = new User("123", "austin", 25);redisTemplate.opsForValue().set(redisTemplateUserObjectKey, user);User userGet = (User) redisTemplate.opsForValue().get(redisTemplateUserObjectKey);System.out.println("userGet: " + userGet);//序列化Object对象数组类型和反序列化Object对象数组类型 (User[]对象数组)User user1 = new User("1", "austin1", 25);User user2 = new User("2", "austin2", 25);User[] userArray = new User[]{user1, user2};redisTemplate.opsForValue().set(redisTemplateUserArrayObjectKey, userArray);User[] userArrayGet = (User[]) redisTemplate.opsForValue().get(redisTemplateUserArrayObjectKey);System.out.println("userArrayGet: " + userArrayGet);//序列化JSONObject对象类型和反序列化JSONObject对象类型JSONObject jsonObject = new JSONObject();jsonObject.put("id", "123");jsonObject.put("name", "austin");jsonObject.put("age", 25);redisTemplate.opsForValue().set(redisTemplateJSONObjectKey, jsonObject);JSONObject jsonObjectGet = (JSONObject) redisTemplate.opsForValue().get(redisTemplateJSONObjectKey);System.out.println("jsonObjectGet: " + jsonObjectGet);//序列化JSONArray对象类型和反序列化JSONArray对象类型JSONArray jsonArray = new JSONArray();JSONObject jsonObject1 = new JSONObject();jsonObject1.put("id", "1");jsonObject1.put("name", "austin1");jsonObject1.put("age", 25);JSONObject jsonObject2 = new JSONObject();jsonObject2.put("id", "1");jsonObject2.put("name", "austin2");jsonObject2.put("age", 25);jsonArray.add(jsonObject1);jsonArray.add(jsonObject2);redisTemplate.opsForValue().set(redisTemplateJSONArrayKey, jsonArray);JSONArray jsonArrayGet = (JSONArray) redisTemplate.opsForValue().get(redisTemplateJSONArrayKey);System.out.println("jsonArrayGet: " + jsonArrayGet);
}

key- value ：

字符串类型
Key: redisTemplateStringKey
Value: "austin"


对象类型
Key: redisTemplateUserObjectKey
Value:
{
    "@class": "com.example.jedisserializefrombytestojson.User",
    "id": "123",
    "name": "austin",
    "age": 25
}
 
对象数组类型
Key: redisTemplateUserArrayObjectKey
Value: 
[
    "[Lcom.example.jedisserializefrombytestojson.User;",
    [
        {
            "@class": "com.example.jedisserializefrombytestojson.User",
            "id": "1",
            "name": "austin1",
            "age": 25
        },
        {
            "@class": "com.example.jedisserializefrombytestojson.User",
            "id": "2",
            "name": "austin2",
            "age": 25
        }
    ]
]
 

JSONObject类型
Key: redisTemplateJSONObjectKey
Value:
{
    "@class": "com.alibaba.fastjson.JSONObject",
    "name": "austin",
    "id": "123",
    "age": 25
}


JSONArray类型
Key: redisTemplateJSONArrayKey
Value: 
[
    "com.alibaba.fastjson.JSONArray",
    [
        {
            "@class": "com.alibaba.fastjson.JSONObject",
            "name": "austin1",
            "id": "1",
            "age": 25
        },
        {
            "@class": "com.alibaba.fastjson.JSONObject",
            "name": "austin2",
            "id": "1",
            "age": 25
        }
    ]
]

这篇关于RedisTemplate的配置和讲解以及和StringRedisTemplate的区别的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！


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《kotlin中const和val的区别及使用场景分析》在Kotlin中,const和val都是用来声明常量的,但它们的使用场景和功能有所不同,下面给大家介绍kotlin中const和val的区别,... 目录kotlin中const 和val的区别1. val:2. const:二 代码示例1 Java
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CSS Padding 和 Margin 区别全解析

CSS Padding 和 Margin 区别全解析

《CSSPadding和Margin区别全解析》CSS中的padding和margin是两个非常基础且重要的属性，它们用于控制元素周围的空白区域，本文将详细介绍padding和... 目录css Padding 和 Margin 全解析1. Padding: 内边距2. Margin: 外边距3. Padd
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Python基础文件操作方法超详细讲解(详解版)

Python基础文件操作方法超详细讲解(详解版)

《Python基础文件操作方法超详细讲解(详解版)》文件就是操作系统为用户或应用程序提供的一个读写硬盘的虚拟单位,文件的核心操作就是读和写,：本文主要介绍Python基础文件操作方法超详细讲解的相... 目录一、文件操作1. 文件打开与关闭1.1 打开文件1.2 关闭文件2. 访问模式及说明二、文件读写1.
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Springboot @Autowired和@Resource的区别解析

Springboot @Autowired和@Resource的区别解析

《Springboot@Autowired和@Resource的区别解析》@Resource是JDK提供的注解,只是Spring在实现上提供了这个注解的功能支持,本文给大家介绍Springboot@... 目录【一】定义【1】@Autowired【2】@Resource【二】区别【1】包含的属性不同【2】@
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