使用Canal和Kafka解决MySQL与缓存的数据一致性问题

log-bin="HELONG-bin"
binlog_format=ROW     # 只能配置行模式， 因为 Cannal 不具备将SQL转化成数据的能力
binlog-do-db=aicloud    # 监控 AI Cloud 项目

binlog-do-db=aicloud
binlog-do-db=aicloud2
binlog-do-db=aicloud3

CREATE USER canal IDENTIFIED BY 'canal';  
GRANT SELECT, REPLICATION SLAVE, REPLICATION CLIENT ON *.* TO 'canal'@'%';
FLUSH PRIVILEGES;

canal.serverMode=kafka
canal.mq.servers=127.0.0.1:9092

canal.instance.mysql.slaveId=100   # 大于 1 即可
canal.instance.master.address=127.0.0.1:3306
canal.mq.topic=ai-cloud-canal-to-kafka

/**
 * 获取历史聊天记录(对话/绘图)
 *
 * @param type
 * @return {@link ResponseEntity }
 */
@RequestMapping("/list")
public ResponseEntity getHistoryList(Integer type, Integer model) {
    String listCacheKey = RedisUtil.getListCacheKey(SecurityUtil.getCurrentUser().getUid(), model, type);
    Object list = redisTemplate.opsForValue().get(listCacheKey);
    if (ObjectUtil.isNull(list)) {
        LambdaQueryWrapper<Answer> queryWrapper = new LambdaQueryWrapper<>();
        queryWrapper.eq(Answer::getUid, SecurityUtil.getCurrentUser().getUid());
        queryWrapper.eq(Answer::getType, type);
        queryWrapper.eq(Answer::getModel, model);
        queryWrapper.orderByDesc(Answer::getAid);
        List<Answer> answerList = answerService.list(queryWrapper);
        List<Long> userIds = answerList.stream().map(Answer::getUid).collect(Collectors.toList());
        Map<Long, User> userIdMap = userService.selectByIds(userIds).stream().collect(Collectors.toMap(User::getUid, Function.identity()));
        List<AnswerVo> answerVoList = answerList.stream().map(answer -> AnswerVoUtil.getListAnswerVo(answer, userIdMap)).collect(Collectors.toList());
        // 缓存 1 天
        redisTemplate.opsForValue().set(listCacheKey, answerVoList, 1, TimeUnit.DAYS);
        return ResponseEntity.success(answerVoList);
    } else {
        return ResponseEntity.success(list);
    }
}

/**
 * 查询列表存储 Redis 缓存
 *
 * @param uid
 * @param model
 * @param type
 * @return {@link String }
 */
public static String getListCacheKey(Long uid, Integer model, Integer type) {
    return "LIST_CACHE_KEY_" + uid + "_" + model + "_" + type;
}

/**
 * canal 监控 binlog 日志，将修改的数据存储 kafka topic 中
 * 监听 kafka topic 中的数据
 *
 * @param data
 * @param ack
 * @throws JsonProcessingException
 */
@KafkaListener(topics = {KafkaConstant.CANAL_TOPIC})
public void canalListen(String data, Acknowledgment ack) throws JsonProcessingException {
    HashMap<String, Object> map = objectMapper.readValue(data, HashMap.class);
    if (map.isEmpty()) {
        ack.acknowledge();
        return;
    }
    // 匹配上对应的数据库和数据表
    if (KafkaConstant.TARGET_DATABASE.equals(map.get(KafkaConstant.DATABASE_KEY).toString()) &&
            KafkaConstant.TARGET_TABLE.equals(map.get(KafkaConstant.TABLE_KEY).toString())) {
        // 更新缓存 
        List<Map<String, Object>> list = (List<Map<String, Object>>) map.get(KafkaConstant.DATA_KEY);
        if (!CollectionUtils.isEmpty(list)) {
            for (Map<String, Object> answerMap : list) {
                String answerListCacheKey = RedisUtil.getListCacheKey(
                        Long.valueOf(answerMap.get("uid").toString()),
                        Integer.parseInt(answerMap.get("model").toString()),
                        Integer.parseInt(answerMap.get("type").toString()));
                // 删除缓存，让下一次查询走数据库，并同步缓存
                redisTemplate.delete(answerListCacheKey);
            }
        }
    }
    //  手动确认应答
    ack.acknowledge();
}

/**
 * canal 同步数据到 kafka
 */
public static final String CANAL_TOPIC = "ai-cloud-canal-to-kafka";
 
 
/**
 * 数据库，缓存数据一致性的
 */
 
public static final String DATABASE_KEY = "database";
 
public static final String TABLE_KEY = "table";
 
public static final String DATA_KEY = "data";
 
public static final String TARGET_DATABASE = "aicloud";
 
public static final String TARGET_TABLE = "answer";

kafka:
  clusters:
    - name: kafka3_cluster
      bootstrapServers: 127.0.0.1:9092