refactor(iot): 重构客流计数器为增量累加模式，支持 people_out
- 删除旧 TrafficCounterBaseRedisDAO（基准值模式），新增 TrafficCounterRedisDAO 支持阈值计数器（达标后重置）和当日累积统计（用于报表） - TrafficThresholdRuleProcessor 改为增量原子累加，消除基准值校准逻辑 - CleanRuleProcessorManager 路由增加 people_out 支持 - TrafficCounterBaseResetJob 改为每日清除阈值计数器，持久化职责移交 Ops 模块 - 使用 SCAN 替代 KEYS 避免阻塞 Redis Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
@@ -0,0 +1,42 @@
|
||||
package com.viewsh.module.ops.dal.dataobject.dto;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
import lombok.Data;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
import java.util.Map;
|
||||
|
||||
/**
|
||||
* 工单业务日志响应 DTO
|
||||
*
|
||||
* @author lzh
|
||||
*/
|
||||
@Schema(description = "管理后台 - 工单业务日志 Response DTO")
|
||||
@Data
|
||||
public class OpsOrderBusinessLogRespDTO {
|
||||
|
||||
@Schema(description = "日志ID", requiredMode = Schema.RequiredMode.REQUIRED, example = "1")
|
||||
private Long id;
|
||||
|
||||
@Schema(description = "日志类型（system=系统/user=用户）", requiredMode = Schema.RequiredMode.REQUIRED, example = "system")
|
||||
private String type;
|
||||
|
||||
@Schema(description = "日志标题", requiredMode = Schema.RequiredMode.REQUIRED, example = "工单自动创建")
|
||||
private String title;
|
||||
|
||||
@Schema(description = "日志内容", example = "蓝牙信标触发自动创建保洁工单")
|
||||
private String content;
|
||||
|
||||
@Schema(description = "操作人", requiredMode = Schema.RequiredMode.REQUIRED, example = "系统")
|
||||
private String operator;
|
||||
|
||||
@Schema(description = "日志时间", requiredMode = Schema.RequiredMode.REQUIRED, example = "2026-01-23 14:30:25")
|
||||
private LocalDateTime time;
|
||||
|
||||
@Schema(description = "工单状态", example = "PENDING")
|
||||
private String status;
|
||||
|
||||
@Schema(description = "扩展数据", example = "{}")
|
||||
private Map<String, Object> extra;
|
||||
|
||||
}
|
||||
@@ -0,0 +1,23 @@
|
||||
package com.viewsh.module.ops.dal.dataobject.dto;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
import lombok.Data;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* 工单业务日志列表响应 DTO
|
||||
*
|
||||
* @author lzh
|
||||
*/
|
||||
@Schema(description = "管理后台 - 工单业务日志列表 Response DTO")
|
||||
@Data
|
||||
public class OpsOrderBusinessLogsRespDTO {
|
||||
|
||||
@Schema(description = "工单ID", requiredMode = Schema.RequiredMode.REQUIRED, example = "10001")
|
||||
private Long orderId;
|
||||
|
||||
@Schema(description = "日志列表", requiredMode = Schema.RequiredMode.REQUIRED)
|
||||
private List<OpsOrderBusinessLogRespDTO> logs;
|
||||
|
||||
}
|
||||
@@ -0,0 +1,62 @@
|
||||
package com.viewsh.module.ops.dal.dataobject.statistics;
|
||||
|
||||
import com.baomidou.mybatisplus.annotation.KeySequence;
|
||||
import com.baomidou.mybatisplus.annotation.TableId;
|
||||
import com.baomidou.mybatisplus.annotation.TableName;
|
||||
import com.viewsh.framework.tenant.core.db.TenantBaseDO;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
|
||||
/**
|
||||
* 客流统计小时汇总 DO
|
||||
* <p>
|
||||
* 用于 Ops 业务报表统计，数据来源于 IoT 设备的客流计数器
|
||||
*
|
||||
* @author AI
|
||||
*/
|
||||
@TableName("ops_traffic_statistics")
|
||||
@KeySequence("ops_traffic_statistics_seq")
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
@Builder
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
public class OpsTrafficStatisticsDO extends TenantBaseDO {
|
||||
|
||||
/**
|
||||
* 主键
|
||||
*/
|
||||
@TableId
|
||||
private Long id;
|
||||
|
||||
/**
|
||||
* 设备ID（数据来源）
|
||||
*/
|
||||
private Long deviceId;
|
||||
|
||||
/**
|
||||
* 区域ID（主查询维度）
|
||||
*/
|
||||
private Long areaId;
|
||||
|
||||
/**
|
||||
* 统计小时（精确到小时，如 2026-02-03 10:00:00）
|
||||
*/
|
||||
private LocalDateTime statHour;
|
||||
|
||||
/**
|
||||
* 进入人数
|
||||
*/
|
||||
private Integer peopleIn;
|
||||
|
||||
/**
|
||||
* 离开人数
|
||||
*/
|
||||
private Integer peopleOut;
|
||||
|
||||
}
|
||||
@@ -0,0 +1,36 @@
|
||||
package com.viewsh.module.ops.dal.mysql.statistics;
|
||||
|
||||
import com.viewsh.framework.mybatis.core.mapper.BaseMapperX;
|
||||
import com.viewsh.module.ops.dal.dataobject.statistics.OpsTrafficStatisticsDO;
|
||||
import org.apache.ibatis.annotations.Mapper;
|
||||
import org.apache.ibatis.annotations.Param;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
|
||||
/**
|
||||
* 客流统计小时汇总 Mapper
|
||||
*
|
||||
* @author AI
|
||||
*/
|
||||
@Mapper
|
||||
public interface OpsTrafficStatisticsMapper extends BaseMapperX<OpsTrafficStatisticsDO> {
|
||||
|
||||
/**
|
||||
* 插入或更新统计记录
|
||||
* <p>
|
||||
* 使用 INSERT ... ON DUPLICATE KEY UPDATE 实现 upsert
|
||||
* 注意：方法名改为 upsert 避免与 MyBatis Plus BaseMapper.insertOrUpdate() 冲突
|
||||
*
|
||||
* @param record 统计记录
|
||||
*/
|
||||
void upsert(@Param("record") OpsTrafficStatisticsDO record);
|
||||
|
||||
/**
|
||||
* 删除指定时间之前的统计记录
|
||||
*
|
||||
* @param beforeTime 截止时间
|
||||
* @return 删除的记录数
|
||||
*/
|
||||
int deleteByStatHourBefore(@Param("beforeTime") LocalDateTime beforeTime);
|
||||
|
||||
}
|
||||
@@ -0,0 +1,50 @@
|
||||
package com.viewsh.module.ops.service.job;
|
||||
|
||||
import com.viewsh.module.ops.dal.mysql.statistics.OpsTrafficStatisticsMapper;
|
||||
import com.xxl.job.core.handler.annotation.XxlJob;
|
||||
import jakarta.annotation.Resource;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.stereotype.Component;
|
||||
|
||||
import java.time.LocalDateTime;
|
||||
|
||||
/**
|
||||
* 客流统计清理任务
|
||||
* <p>
|
||||
* 每月 1 日凌晨 2 点执行，删除 30 天前的客流统计记录
|
||||
*
|
||||
* @author AI
|
||||
*/
|
||||
@Slf4j
|
||||
@Component
|
||||
public class TrafficStatisticsCleanupJob {
|
||||
|
||||
@Resource
|
||||
private OpsTrafficStatisticsMapper trafficStatisticsMapper;
|
||||
|
||||
/**
|
||||
* 清理过期的客流统计记录
|
||||
* <p>
|
||||
* XxlJob 配置：
|
||||
* - Cron: 0 0 2 1 * ? (每月 1 日凌晨 2 点)
|
||||
*
|
||||
* @return 执行结果
|
||||
*/
|
||||
@XxlJob("trafficStatisticsCleanupJob")
|
||||
public String execute() {
|
||||
log.info("[TrafficStatisticsCleanupJob] 开始执行客流统计清理任务");
|
||||
|
||||
try {
|
||||
LocalDateTime beforeTime = LocalDateTime.now().minusDays(30);
|
||||
int deletedCount = trafficStatisticsMapper.deleteByStatHourBefore(beforeTime);
|
||||
|
||||
log.info("[TrafficStatisticsCleanupJob] 客流统计清理完成：删除 {} 条记录（截止时间={}）",
|
||||
deletedCount, beforeTime);
|
||||
return "清理完成：删除 " + deletedCount + " 条记录";
|
||||
|
||||
} catch (Exception e) {
|
||||
log.error("[TrafficStatisticsCleanupJob] 客流统计清理失败", e);
|
||||
return "清理失败: " + e.getMessage();
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,310 @@
|
||||
package com.viewsh.module.ops.service.job;
|
||||
|
||||
import com.viewsh.module.ops.dal.dataobject.statistics.OpsTrafficStatisticsDO;
|
||||
import com.viewsh.module.ops.dal.mysql.statistics.OpsTrafficStatisticsMapper;
|
||||
import com.viewsh.module.ops.service.area.OpsBusAreaService;
|
||||
import com.xxl.job.core.handler.annotation.XxlJob;
|
||||
import jakarta.annotation.Resource;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import org.springframework.data.redis.core.Cursor;
|
||||
import org.springframework.data.redis.core.ScanOptions;
|
||||
import org.springframework.data.redis.core.StringRedisTemplate;
|
||||
import org.springframework.stereotype.Component;
|
||||
|
||||
import java.time.LocalDate;
|
||||
import java.time.LocalDateTime;
|
||||
import java.time.LocalTime;
|
||||
import java.time.format.DateTimeFormatter;
|
||||
import java.util.HashSet;
|
||||
import java.util.Map;
|
||||
import java.util.Set;
|
||||
import java.util.concurrent.TimeUnit;
|
||||
|
||||
/**
|
||||
* 客流统计持久化任务
|
||||
* <p>
|
||||
* 每小时整点执行，将 IoT 模块 Redis 中的当日累积统计数据写入 Ops 业务库
|
||||
* <p>
|
||||
* 通过对比 Redis 中的 lastPersistedIn/lastPersistedOut 与 totalIn/totalOut，
|
||||
* 计算本小时的增量并写入 ops_traffic_statistics 表
|
||||
*
|
||||
* @author AI
|
||||
*/
|
||||
@Slf4j
|
||||
@Component
|
||||
public class TrafficStatisticsPersistJob {
|
||||
|
||||
private static final DateTimeFormatter DATE_FORMATTER = DateTimeFormatter.ofPattern("yyyyMMdd");
|
||||
private static final String LOCK_KEY = "ops:traffic:persist:lock";
|
||||
private static final int LOCK_TTL_SECONDS = 300; // 5分钟锁超时
|
||||
|
||||
@Resource
|
||||
private StringRedisTemplate stringRedisTemplate;
|
||||
|
||||
@Resource
|
||||
private OpsTrafficStatisticsMapper trafficStatisticsMapper;
|
||||
|
||||
@Resource
|
||||
private OpsBusAreaService areaService;
|
||||
|
||||
/**
|
||||
* 每小时持久化客流统计数据
|
||||
* <p>
|
||||
* XxlJob 配置：
|
||||
* - Cron: 0 0 * * * ? (每小时整点)
|
||||
*
|
||||
* @return 执行结果
|
||||
*/
|
||||
@XxlJob("trafficStatisticsPersistJob")
|
||||
public String execute() {
|
||||
log.info("[TrafficStatisticsPersistJob] 开始执行客流统计持久化任务");
|
||||
|
||||
// P0修复1: 获取分布式锁，防止并发执行导致双重计数
|
||||
Boolean locked = stringRedisTemplate.opsForValue()
|
||||
.setIfAbsent(LOCK_KEY, String.valueOf(System.currentTimeMillis()),
|
||||
LOCK_TTL_SECONDS, TimeUnit.SECONDS);
|
||||
|
||||
if (Boolean.FALSE.equals(locked)) {
|
||||
log.warn("[TrafficStatisticsPersistJob] 任务已在其他节点执行中，跳过本次执行");
|
||||
return "任务已在其他节点执行";
|
||||
}
|
||||
|
||||
try {
|
||||
// P1修复3: 使用 SCAN 替代 KEYS，避免阻塞 Redis
|
||||
Set<String> dailyKeys = scanDailyKeys();
|
||||
if (dailyKeys.isEmpty()) {
|
||||
log.info("[TrafficStatisticsPersistJob] 无统计数据需要持久化");
|
||||
return "无数据";
|
||||
}
|
||||
|
||||
int successCount = 0;
|
||||
int errorCount = 0;
|
||||
int skippedCount = 0;
|
||||
|
||||
for (String key : dailyKeys) {
|
||||
try {
|
||||
PersistResult result = persistSingleDevice(key);
|
||||
if (result == PersistResult.SUCCESS) {
|
||||
successCount++;
|
||||
} else if (result == PersistResult.SKIPPED) {
|
||||
skippedCount++;
|
||||
} else {
|
||||
errorCount++;
|
||||
}
|
||||
} catch (Exception e) {
|
||||
errorCount++;
|
||||
log.error("[TrafficStatisticsPersistJob] 持久化失败：key={}", key, e);
|
||||
}
|
||||
}
|
||||
|
||||
String result = String.format("持久化完成：成功=%d, 跳过=%d, 失败=%d",
|
||||
successCount, skippedCount, errorCount);
|
||||
log.info("[TrafficStatisticsPersistJob] {}", result);
|
||||
return result;
|
||||
|
||||
} catch (Exception e) {
|
||||
log.error("[TrafficStatisticsPersistJob] 持久化任务执行失败", e);
|
||||
return "执行失败: " + e.getMessage();
|
||||
} finally {
|
||||
// 释放分布式锁
|
||||
stringRedisTemplate.delete(LOCK_KEY);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 使用 SCAN 扫描所有当日统计 key
|
||||
*/
|
||||
private Set<String> scanDailyKeys() {
|
||||
Set<String> keys = new HashSet<>();
|
||||
ScanOptions options = ScanOptions.scanOptions()
|
||||
.match("iot:clean:traffic:daily:*")
|
||||
.count(100)
|
||||
.build();
|
||||
|
||||
try (Cursor<String> cursor = stringRedisTemplate.scan(options)) {
|
||||
cursor.forEachRemaining(keys::add);
|
||||
} catch (Exception e) {
|
||||
log.error("[TrafficStatisticsPersistJob] SCAN 扫描失败", e);
|
||||
}
|
||||
|
||||
return keys;
|
||||
}
|
||||
|
||||
/**
|
||||
* 持久化单个设备的统计数据
|
||||
*/
|
||||
private PersistResult persistSingleDevice(String key) {
|
||||
Long deviceId = parseDeviceIdFromKey(key);
|
||||
LocalDate date = parseDateFromKey(key);
|
||||
if (deviceId == null || date == null) {
|
||||
log.warn("[TrafficStatisticsPersistJob] 解析 key 失败：key={}", key);
|
||||
return PersistResult.ERROR;
|
||||
}
|
||||
|
||||
// 读取 Redis Hash 数据
|
||||
Map<Object, Object> data = stringRedisTemplate.opsForHash().entries(key);
|
||||
long totalIn = parseLong(data.get("totalIn"));
|
||||
long totalOut = parseLong(data.get("totalOut"));
|
||||
long lastPersistedIn = parseLong(data.get("lastPersistedIn"));
|
||||
long lastPersistedOut = parseLong(data.get("lastPersistedOut"));
|
||||
|
||||
// 计算本次需要持久化的增量
|
||||
long deltaIn = totalIn - lastPersistedIn;
|
||||
long deltaOut = totalOut - lastPersistedOut;
|
||||
|
||||
// P1修复5: 处理负增量（计数器重置场景）
|
||||
if (deltaIn < 0 || deltaOut < 0) {
|
||||
log.warn("[TrafficStatisticsPersistJob] 检测到计数器重置：deviceId={}, date={}, " +
|
||||
"totalIn={}, lastPersistedIn={}, totalOut={}, lastPersistedOut={}",
|
||||
deviceId, date, totalIn, lastPersistedIn, totalOut, lastPersistedOut);
|
||||
|
||||
// 重置已持久化标记，从当前值重新开始计数
|
||||
stringRedisTemplate.opsForHash().put(key, "lastPersistedIn", String.valueOf(totalIn));
|
||||
stringRedisTemplate.opsForHash().put(key, "lastPersistedOut", String.valueOf(totalOut));
|
||||
|
||||
log.info("[TrafficStatisticsPersistJob] 已重置持久化标记：deviceId={}, date={}", deviceId, date);
|
||||
return PersistResult.SKIPPED;
|
||||
}
|
||||
|
||||
if (deltaIn <= 0 && deltaOut <= 0) {
|
||||
log.debug("[TrafficStatisticsPersistJob] 无新增数据：deviceId={}, date={}", deviceId, date);
|
||||
return PersistResult.SKIPPED;
|
||||
}
|
||||
|
||||
// P1修复7: 检查 int 溢出
|
||||
if (deltaIn > Integer.MAX_VALUE || deltaOut > Integer.MAX_VALUE) {
|
||||
log.error("[TrafficStatisticsPersistJob] 增量值溢出：deviceId={}, date={}, deltaIn={}, deltaOut={}",
|
||||
deviceId, date, deltaIn, deltaOut);
|
||||
return PersistResult.ERROR;
|
||||
}
|
||||
|
||||
// 获取区域ID（从区域设备关系中查询）
|
||||
Long areaId = getAreaIdForDevice(deviceId);
|
||||
|
||||
// P1修复4: 处理缺失区域关联场景
|
||||
if (areaId == null) {
|
||||
log.warn("[TrafficStatisticsPersistJob] 设备无区域关联，更新持久化标记避免数据累积：deviceId={}", deviceId);
|
||||
|
||||
// 更新 lastPersisted，避免下次累积错误数据
|
||||
stringRedisTemplate.opsForHash().put(key, "lastPersistedIn", String.valueOf(totalIn));
|
||||
stringRedisTemplate.opsForHash().put(key, "lastPersistedOut", String.valueOf(totalOut));
|
||||
|
||||
// TODO: 将数据存入死信队列，等待区域关联修复后重试
|
||||
return PersistResult.SKIPPED;
|
||||
}
|
||||
|
||||
// P0修复2: 修复小时分桶逻辑
|
||||
LocalDateTime statHour = calculateStatHour(date);
|
||||
|
||||
OpsTrafficStatisticsDO record = OpsTrafficStatisticsDO.builder()
|
||||
.deviceId(deviceId)
|
||||
.areaId(areaId)
|
||||
.statHour(statHour)
|
||||
.peopleIn((int) deltaIn)
|
||||
.peopleOut((int) deltaOut)
|
||||
.build();
|
||||
|
||||
trafficStatisticsMapper.upsert(record);
|
||||
|
||||
// 更新 Redis 已持久化的值
|
||||
stringRedisTemplate.opsForHash().put(key, "lastPersistedIn", String.valueOf(totalIn));
|
||||
stringRedisTemplate.opsForHash().put(key, "lastPersistedOut", String.valueOf(totalOut));
|
||||
|
||||
log.debug("[TrafficStatisticsPersistJob] 持久化成功：deviceId={}, areaId={}, statHour={}, deltaIn={}, deltaOut={}",
|
||||
deviceId, areaId, statHour, deltaIn, deltaOut);
|
||||
|
||||
return PersistResult.SUCCESS;
|
||||
}
|
||||
|
||||
/**
|
||||
* P0修复2: 计算正确的统计小时
|
||||
* <p>
|
||||
* 规则：
|
||||
* - 如果是今天的数据，归属到当前小时
|
||||
* - 如果是昨天的数据（跨日执行），归属到昨天的23点
|
||||
* - 如果是更早的数据（延迟执行），归属到当天的23点
|
||||
*/
|
||||
private LocalDateTime calculateStatHour(LocalDate dataDate) {
|
||||
LocalDate today = LocalDate.now();
|
||||
int currentHour = LocalDateTime.now().getHour();
|
||||
|
||||
if (dataDate.equals(today)) {
|
||||
// 今天的数据，归属到当前小时
|
||||
return LocalDateTime.of(dataDate, LocalTime.of(currentHour, 0));
|
||||
} else {
|
||||
// 历史数据（昨天或更早），归属到当天的23点
|
||||
return LocalDateTime.of(dataDate, LocalTime.of(23, 0));
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取设备关联的区域ID
|
||||
*/
|
||||
private Long getAreaIdForDevice(Long deviceId) {
|
||||
try {
|
||||
// 通过 OpsBusAreaService 查询设备关联的区域
|
||||
return areaService.getAreaIdByDeviceId(deviceId);
|
||||
} catch (Exception e) {
|
||||
log.error("[TrafficStatisticsPersistJob] 查询设备区域失败：deviceId={}", deviceId, e);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析 Redis key 中的设备ID
|
||||
* key 格式：iot:clean:traffic:daily:{deviceId}:{date}
|
||||
*/
|
||||
private Long parseDeviceIdFromKey(String key) {
|
||||
String[] parts = key.split(":");
|
||||
if (parts.length >= 6) {
|
||||
try {
|
||||
return Long.parseLong(parts[4]);
|
||||
} catch (NumberFormatException e) {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析 Redis key 中的日期
|
||||
* key 格式：iot:clean:traffic:daily:{deviceId}:{date}
|
||||
*/
|
||||
private LocalDate parseDateFromKey(String key) {
|
||||
String[] parts = key.split(":");
|
||||
if (parts.length >= 6) {
|
||||
try {
|
||||
return LocalDate.parse(parts[5], DATE_FORMATTER);
|
||||
} catch (Exception e) {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析 Long 值
|
||||
*/
|
||||
private long parseLong(Object value) {
|
||||
if (value == null) {
|
||||
return 0L;
|
||||
}
|
||||
if (value instanceof Number) {
|
||||
return ((Number) value).longValue();
|
||||
}
|
||||
try {
|
||||
return Long.parseLong(value.toString());
|
||||
} catch (NumberFormatException e) {
|
||||
return 0L;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 持久化结果枚举
|
||||
*/
|
||||
private enum PersistResult {
|
||||
SUCCESS, // 成功
|
||||
SKIPPED, // 跳过（无数据、重置等）
|
||||
ERROR // 错误
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,20 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
|
||||
<mapper namespace="com.viewsh.module.ops.dal.mysql.statistics.OpsTrafficStatisticsMapper">
|
||||
|
||||
<insert id="upsert">
|
||||
INSERT INTO ops_traffic_statistics (device_id, area_id, stat_hour, people_in, people_out, tenant_id)
|
||||
VALUES (#{record.deviceId}, #{record.areaId}, #{record.statHour}, #{record.peopleIn}, #{record.peopleOut}, #{record.tenantId})
|
||||
ON DUPLICATE KEY UPDATE
|
||||
people_in = people_in + VALUES(people_in),
|
||||
people_out = people_out + VALUES(people_out),
|
||||
update_time = NOW()
|
||||
</insert>
|
||||
|
||||
<delete id="deleteByStatHourBefore">
|
||||
DELETE FROM ops_traffic_statistics
|
||||
WHERE stat_hour < #{beforeTime}
|
||||
AND deleted = 0
|
||||
</delete>
|
||||
|
||||
</mapper>
|
||||
Reference in New Issue
Block a user