前言
本文将提供一个redis的工具类,可以用在Spring boot以及Spring Cloud项目中,本工具类主要整合了将Redis作为NoSql DB使用时的常用方法,以StringRedisTemplate实例为基础,封装了读取、写入、批量写入多个Redis hash等方法,降低了Redis学习成本,使业务代码更加高效、简洁、优雅。
一.pom.xml引入所需依赖
本依赖主要用于使用HashMultimap,该hashmap是java中的HashMap增强版,可以允许键值对中的key重复,此种特性可以用于Redis批量更新hash。后文详细讲述。
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>30.0-jre</version>
</dependency>
二.RedisUtils工具类
直接上源码,CV工程师必备,新建个Class,将其命名为RedisUtils ,后将首行包名修改下即可使用。
package com.xxx.utils;
import com.google.common.collect.HashMultimap;
import org.springframework.dao.DataAccessException;
import org.springframework.data.redis.connection.RedisConnection;
import org.springframework.data.redis.core.*;
import java.util.*;
import java.util.concurrent.TimeUnit;
public class RedisUtils {
private StringRedisTemplate redisTemplate;
public RedisUtils(StringRedisTemplate redisTemplate) {
this.redisTemplate = redisTemplate;
}
public boolean set(final String key, String value) {
boolean result = false;
try {
ValueOperations<String, String> operations = redisTemplate.opsForValue();
operations.set(key, value);
result = true;
} catch (Exception e) {
e.printStackTrace();
}
return result;
}
public boolean set(final String key, String value, Long expireTime) {
boolean result = false;
try {
ValueOperations<String, String> operations = redisTemplate.opsForValue();
operations.set(key, value);
redisTemplate.expire(key, expireTime, TimeUnit.SECONDS);
result = true;
} catch (Exception e) {
e.printStackTrace();
}
return result;
}
public void removeByKeys(final String... keys) {
for (String key : keys) {
remove(key);
}
}
public void removePattern(final String pattern) {
Set<String> keys = redisTemplate.keys(pattern);
if (keys != null && keys.size() > 0)
redisTemplate.delete(keys);
}
public void remove(final String key) {
if (exists(key)) {
redisTemplate.delete(key);
}
}
public Boolean exists(final String key) {
return redisTemplate.hasKey(key);
}
public String get(final String key) {
String result = null;
ValueOperations<String, String> operations = redisTemplate.opsForValue();
result = operations.get(key);
return result;
}
public void hmSet(String key, String hashKey, String value) {
HashOperations<String, String, String> hash = redisTemplate.opsForHash();
hash.put(key, hashKey, value);
}
public String hmGet(String key, String hashKey) {
HashOperations<String, String, String> hash = redisTemplate.opsForHash();
return hash.get(key, hashKey);
}
public boolean hmHasKey(String key, String hashKey) {
HashOperations<String, String, String> hash = redisTemplate.opsForHash();
return hash.hasKey(key, hashKey);
}
public long hmRemove(String key, String... hashKeys) {
HashOperations<String, String, String> hash = redisTemplate.opsForHash();
return hash.delete(key, hashKeys);
}
public Map<String, String> hashMapGet(String key) {
HashOperations<String, String, String> hash = redisTemplate.opsForHash();
return hash.entries(key);
}
public void hashMapSet(String key, Map<String, String> map) {
HashOperations<String, String, String> hash = redisTemplate.opsForHash();
hash.putAll(key, map);
}
public void lPush(String key, String value) {
ListOperations<String, String> list = redisTemplate.opsForList();
list.rightPush(key, value);
}
public List<String> lRange(String key, long start, long end) {
ListOperations<String, String> list = redisTemplate.opsForList();
return list.range(key, start, end);
}
public void add(String key, String value) {
SetOperations<String, String> set = redisTemplate.opsForSet();
set.add(key, value);
}
public Set<String> setMembers(String key) {
SetOperations<String, String> set = redisTemplate.opsForSet();
return set.members(key);
}
public void zAdd(String key, String value, double score) {
ZSetOperations<String, String> zSet = redisTemplate.opsForZSet();
zSet.add(key, value, score);
}
public Set<String> rangeByScore(String key, double startScore, double endScore) {
ZSetOperations<String, String> zset = redisTemplate.opsForZSet();
return zset.rangeByScore(key, startScore, endScore);
}
public Set<String> keys(String pattern) {
return redisTemplate.keys(pattern);
}
public List hashMapList(Collection<String> keySet) {
return redisTemplate.executePipelined(new SessionCallback<String>() {
@Override
public <K, V> String execute(RedisOperations<K, V> operations) throws DataAccessException {
HashOperations hashOperations = operations.opsForHash();
for (String key : keySet) {
hashOperations.entries(key);
}
return null;
}
});
}
public void batchHashMapSet(HashMultimap<String, Map<String, String>> batchMap) {
// 设置5秒超时时间
redisTemplate.expire("max", 25, TimeUnit.SECONDS);
redisTemplate.executePipelined(new RedisCallback<List<Map<String, String>>>() {
@Override
public List<Map<String, String>> doInRedis(RedisConnection connection) throws DataAccessException {
Iterator<Map.Entry<String, Map<String, String>>> iterator = batchMap.entries().iterator();
while (iterator.hasNext()) {
Map.Entry<String, Map<String, String>> hash = iterator.next();
// 哈希名,即表名
byte[] hashName = redisTemplate.getStringSerializer().serialize(hash.getKey());
Map<String, String> hashValues = hash.getValue();
Iterator<Map.Entry<String, String>> it = hashValues.entrySet().iterator();
// 将元素序列化后缓存,即表的多条哈希记录
Map<byte[], byte[]> hashes = new HashMap<byte[], byte[]>();
while (it.hasNext()) {
// hash中一条key-value记录
Map.Entry<String, String> entry = it.next();
byte[] key = redisTemplate.getStringSerializer().serialize(entry.getKey());
byte[] value = redisTemplate.getStringSerializer().serialize(entry.getValue());
hashes.put(key, value);
}
// 批量保存
connection.hMSet(hashName, hashes);
}
return null;
}
});
}
public void batchHashMapSet(Map<String, Map<String, String>> dataMap) {
// 设置5秒超时时间
redisTemplate.expire("max", 25, TimeUnit.SECONDS);
redisTemplate.executePipelined(new RedisCallback<List<Map<String, String>>>() {
@Override
public List<Map<String, String>> doInRedis(RedisConnection connection) throws DataAccessException {
Iterator<Map.Entry<String, Map<String, String>>> iterator = dataMap.entrySet().iterator();
while (iterator.hasNext()) {
Map.Entry<String, Map<String, String>> hash = iterator.next();
// 哈希名,即表名
byte[] hashName = redisTemplate.getStringSerializer().serialize(hash.getKey());
Map<String, String> hashValues = hash.getValue();
Iterator<Map.Entry<String, String>> it = hashValues.entrySet().iterator();
// 将元素序列化后缓存,即表的多条哈希记录
Map<byte[], byte[]> hashes = new HashMap<byte[], byte[]>();
while (it.hasNext()) {
// hash中一条key-value记录
Map.Entry<String, String> entry = it.next();
byte[] key = redisTemplate.getStringSerializer().serialize(entry.getKey());
byte[] value = redisTemplate.getStringSerializer().serialize(entry.getValue());
hashes.put(key, value);
}
// 批量保存
connection.hMSet(hashName, hashes);
}
return null;
}
});
}
public void batchHashMapListSet(List<Map<String, Map<String, String>>> list) {
// 设置5秒超时时间
redisTemplate.expire("max", 25, TimeUnit.SECONDS);
redisTemplate.executePipelined(new RedisCallback<List<Map<String, String>>>() {
@Override
public List<Map<String, String>> doInRedis(RedisConnection connection) throws DataAccessException {
for (Map<String, Map<String, String>> dataMap : list) {
Iterator<Map.Entry<String, Map<String, String>>> iterator = dataMap.entrySet().iterator();
while (iterator.hasNext()) {
Map.Entry<String, Map<String, String>> hash = iterator.next();
// 哈希名,即表名
byte[] hashName = redisTemplate.getStringSerializer().serialize(hash.getKey());
Map<String, String> hashValues = hash.getValue();
Iterator<Map.Entry<String, String>> it = hashValues.entrySet().iterator();
// 将元素序列化后缓存,即表的多条哈希记录
Map<byte[], byte[]> hashes = new HashMap<byte[], byte[]>();
while (it.hasNext()) {
// hash中一条key-value记录
Map.Entry<String, String> entry = it.next();
byte[] key = redisTemplate.getStringSerializer().serialize(entry.getKey());
byte[] value = redisTemplate.getStringSerializer().serialize(entry.getValue());
hashes.put(key, value);
}
// 批量保存
connection.hMSet(hashName, hashes);
}
}
return null;
}
});
}
}
三.如何使用工具类
// 1.注入StringRedisTemplate
@Autowired
private StringRedisTemplate stringRedisTemplate
// 2.new一个工具类对象
RedisUtils redisUtils = new RedisUtils(stringRedisTemplate);
// 3.开心的调用工具类任意方法
Map<String, String> map = redisUtils.hashMapGet(redisKey);
四.工具类中批量更新Redis Hash详解
工具类中batchHashMapSet()重载的方法有两个,特别的是,其中一个方法是支持key值重复的,也就说可以同时更新或写入Redis 键名相同的两个hash,后写入的hash会把先写入的数据覆盖,适合一些实时往Redis同步数据的业务场景。
使用方法:
HashMultimap<String, Map<String, String>> batchMap = HashMultimap.create();
redisUtils.batchHashMapSet(batchMap);
总结
本文提供了支持RedisUtils工具类,可以满足大多数场景把Redis作为NoSQL DB来使用的操作。
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