今天在使用easyexcel进行导出时发现导出的excel中只有表头没有数据,经过本地调试发现List中是有数据的,由于List是有redis缓存,所以我直接将redis中的缓存删掉让他重新去数据库加载,发现从数据库加载出来的List是可以写入到excel中,但是后续从redis获取的List就无法写入excel,最终发现应该是反序列化没有配置好。
RedisConfig
import org.springframework.cache.annotation.CachingConfigurerSupport;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.StringRedisSerializer;
/**
* redis配置
*/
@Configuration
public class RedisConfig extends CachingConfigurerSupport
{
@Bean
@SuppressWarnings("all")
public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory connectionFactory)
{
RedisTemplate<Object, Object> template = new RedisTemplate<>();
template.setConnectionFactory(connectionFactory);
FastJson2JsonRedisSerializer serializer = new FastJson2JsonRedisSerializer(Object.class);
// 使用StringRedisSerializer来序列化和反序列化redis的key值
template.setKeySerializer(new StringRedisSerializer());
template.setValueSerializer(serializer);
// Hash的key也采用StringRedisSerializer的序列化方式
template.setHashKeySerializer(new StringRedisSerializer());
template.setHashValueSerializer(serializer);
template.afterPropertiesSet();
return template;
}
}
FastJson2JsonRedisSerializer
import com.alibaba.fastjson2.JSON;
import com.alibaba.fastjson2.JSONReader;
import com.alibaba.fastjson2.JSONWriter;
import com.alibaba.fastjson2.filter.Filter;
import org.springframework.data.redis.serializer.RedisSerializer;
import org.springframework.data.redis.serializer.SerializationException;
import java.nio.charset.Charset;
/**
* Redis使用FastJson序列化
*/
public class FastJson2JsonRedisSerializer<T> implements RedisSerializer<T>
{
/**
* 自动识别json对象白名单配置(仅允许解析的包名,范围越小越安全)
*/
public static final String[] JSON_WHITELIST_STR = { "org.springframework", "com.cntaiping.risk" };
public static final Charset DEFAULT_CHARSET = Charset.forName("UTF-8");
static final Filter AUTO_TYPE_FILTER = JSONReader.autoTypeFilter(JSON_WHITELIST_STR);
private Class<T> clazz;
public FastJson2JsonRedisSerializer(Class<T> clazz)
{
super();
this.clazz = clazz;
}
@Override
public byte[] serialize(T t) throws SerializationException
{
if (t == null)
{
return new byte[0];
}
return JSON.toJSONString(t, JSONWriter.Feature.WriteClassName).getBytes(DEFAULT_CHARSET);
}
@Override
public T deserialize(byte[] bytes) throws SerializationException
{
if (bytes == null || bytes.length <= 0)
{
return null;
}
String str = new String(bytes, DEFAULT_CHARSET);
return (T)JSON.parseObject(str, clazz, AUTO_TYPE_FILTER);
}
}
Redis工具类
import cn.hutool.core.bean.BeanUtil;
import com.alibaba.fastjson2.JSON;
import com.alibaba.fastjson2.TypeReference;
import org.apache.commons.collections4.ListUtils;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.BoundSetOperations;
import org.springframework.data.redis.core.Cursor;
import org.springframework.data.redis.core.HashOperations;
import org.springframework.data.redis.core.RedisCallback;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.ScanOptions;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.stereotype.Component;
import java.util.*;
import java.util.concurrent.TimeUnit;
/**
* spring redis 工具类
*
**/
@Component
public class RedisService
{
@Autowired
public RedisTemplate redisTemplate;
/**
* 缓存基本的对象,Integer、String、实体类等
*
* @param key 缓存的键值
* @param value 缓存的值
*/
public <T> void setCacheObject(final String key, final T value)
{
redisTemplate.opsForValue().set(key, value);
}
public <T> void increment(final String key, final int delta)
{
redisTemplate.opsForValue().increment(key,delta);
}
/**
* 缓存基本的对象,Integer、String、实体类等
*
* @param key 缓存的键值
* @param value 缓存的值
* @param timeout 时间
* @param timeUnit 时间颗粒度
*/
public <T> void setCacheObject(final String key, final T value, final Long timeout, final TimeUnit timeUnit)
{
redisTemplate.opsForValue().set(key, value, timeout, timeUnit);
}
/**
* 设置有效时间
*
* @param key Redis键
* @param timeout 超时时间
* @return true=设置成功;false=设置失败
*/
public boolean expire(final String key, final long timeout)
{
return expire(key, timeout, TimeUnit.SECONDS);
}
/**
* 设置有效时间
*
* @param key Redis键
* @param timeout 超时时间
* @param unit 时间单位
* @return true=设置成功;false=设置失败
*/
public boolean expire(final String key, final long timeout, final TimeUnit unit)
{
return redisTemplate.expire(key, timeout, unit);
}
/**
* 获取有效时间
*
* @param key Redis键
* @return 有效时间
*/
public long getExpire(final String key)
{
return redisTemplate.getExpire(key);
}
/**
* 判断 key是否存在
*
* @param key 键
* @return true 存在 false不存在
*/
public Boolean hasKey(String key)
{
return redisTemplate.hasKey(key);
}
/**
* 获得缓存的基本对象。
*
* @param key 缓存键值
* @return 缓存键值对应的数据
*/
public <T> T getCacheObject(final String key)
{
ValueOperations<String, T> operation = redisTemplate.opsForValue();
return operation.get(key);
}
/**
* 读取 setCacheObject 方法的值是一个List<Object>时反序列化的方法 否则序列化时会返回 JsonArray<JsonObject>
*/
public <T> T getCacheObject(final String key, TypeReference<T> typeReference) {
ValueOperations<String, T> operation = redisTemplate.opsForValue();
// 使用FastJson根据TypeReference反序列化
return JSON.parseObject(JSON.toJSONString(operation.get(key)), typeReference);
}
/**
* 删除单个对象
*
* @param key
*/
public boolean deleteObject(final String key)
{
return redisTemplate.delete(key);
}
/**
* 删除集合对象
*
* @param collection 多个对象
* @return
*/
public boolean deleteObject(final Collection collection)
{
return redisTemplate.delete(collection) > 0;
}
/**
* 缓存List数据
*
* @param key 缓存的键值
* @param dataList 待缓存的List数据
* @return 缓存的对象
*/
public <T> long setCacheList(final String key, final List<T> dataList)
{
Long count = redisTemplate.opsForList().rightPushAll(key, dataList);
return count == null ? 0 : count;
}
/**
* 缓存List数据
*
* @param key 缓存的键值
* @return 缓存的对象
*/
public <T> long setObjectToList(final String key,Object data)
{
Long count = redisTemplate.opsForList().rightPush(key, data);
return count == null ? 0 : count;
}
/**
* 缓存List数据
*
* @param key 缓存的键值
* @return 缓存的对象
*/
public <T> long getCacheListSize(final String key)
{
return redisTemplate.opsForList().size(key);
}
public <T> T popCacheList(final String key,Class<T> clazz)
{
Object value = redisTemplate.opsForList().leftPop(key);
return BeanUtil.toBean(value, clazz);
}
/**
* 获得缓存的list对象
*
* @param key 缓存的键值
* @return 缓存键值对应的数据
*/
public <T> List<T> getCacheList(final String key)
{
return redisTemplate.opsForList().range(key, 0, -1);
}
/**
* 缓存Set
*
* @param key 缓存键值
* @param dataSet 缓存的数据
* @return 缓存数据的对象
*/
public <T> BoundSetOperations<String, T> setCacheSet(final String key, final Set<T> dataSet)
{
BoundSetOperations<String, T> setOperation = redisTemplate.boundSetOps(key);
Iterator<T> it = dataSet.iterator();
while (it.hasNext())
{
setOperation.add(it.next());
}
return setOperation;
}
/**
* 获得缓存的set
*
* @param key
* @return
*/
public <T> Set<T> getCacheSet(final String key)
{
return redisTemplate.opsForSet().members(key);
}
/**
* 缓存Map
*
* @param key
* @param dataMap
*/
public <T> void setCacheMap(final String key, final Map<String, T> dataMap)
{
if (dataMap != null) {
redisTemplate.opsForHash().putAll(key, dataMap);
}
}
/**
* 获得缓存的Map
*
* @param key
* @return
*/
public <T> Map<String, T> getCacheMap(final String key)
{
return redisTemplate.opsForHash().entries(key);
}
/**
* 往Hash中存入数据
*
* @param key Redis键
* @param hKey Hash键
* @param value 值
*/
public <T> void setCacheMapValue(final String key, final String hKey, final T value)
{
redisTemplate.opsForHash().put(key, hKey, value);
}
/**
* 获取Hash中的数据
*
* @param key Redis键
* @param hKey Hash键
* @return Hash中的对象
*/
public <T> T getCacheMapValue(final String key, final String hKey)
{
HashOperations<String, String, T> opsForHash = redisTemplate.opsForHash();
return opsForHash.get(key, hKey);
}
/**
* 获取多个Hash中的数据
*
* @param key Redis键
* @param hKeys Hash键集合
* @return Hash对象集合
*/
public <T> List<T> getMultiCacheMapValue(final String key, final Collection<Object> hKeys)
{
return redisTemplate.opsForHash().multiGet(key, hKeys);
}
/**
* 删除Hash中的某条数据
*
* @param key Redis键
* @param hKey Hash键
* @return 是否成功
*/
public boolean deleteCacheMapValue(final String key, final String hKey)
{
return redisTemplate.opsForHash().delete(key, hKey) > 0;
}
/**
* 获得缓存的基本对象列表
*
* @param pattern 字符串前缀
* @return 对象列表
*/
public Set<String> keys(final String pattern)
{
return (Set<String>) redisTemplate.execute((RedisCallback<Set<String>>) connection -> {
Cursor<byte[]> cursor = connection.scan(ScanOptions.scanOptions().match(pattern).count(1000).build());
Set<String> keys = new HashSet<>();
if (cursor.hasNext()) {
keys.add(new String(cursor.next()));
}
return keys;
});
}
/**
* 删除缓存
*
* @param pattern 字符串前缀
* @return 对象列表
*/
public void delete(final String pattern)
{
Set<String> keys = new HashSet<>();
ScanOptions options = ScanOptions.scanOptions().match(pattern).build();
Cursor<byte[]> cursor = redisTemplate.getConnectionFactory().getConnection().scan(options);
while (cursor.hasNext()) {
keys.add(new String(cursor.next()));
}
// 分批删除,避免一次删除太多 key 导致阻塞
List<List<String>> partitionedKeys = ListUtils.partition(new ArrayList<>(keys), 500);
for (List<String> keyBatch : partitionedKeys) {
redisTemplate.delete(keyBatch);
}
}
}