perf(wms): 优化钢卷质量改判原因查询性能

- 在WmsCoilQualityRejudgeMapper中新增原生SQL查询方法selectMapsBySql
- 添加对应的XML映射配置执行动态SQL查询
- 将原有的Java端分组逻辑改为数据库端SQL聚合查询
- 使用内连接和子查询直接获取每个钢卷的最新改判原因
- 避免大量数据传输和客户端分组处理，提升查询效率

klp-wms/src/main/java/com/klp/mapper/WmsCoilQualityRejudgeMapper.java

@@ -3,6 +3,10 @@ package com.klp.mapper;
 import com.klp.domain.WmsCoilQualityRejudge;
 import com.klp.domain.vo.WmsCoilQualityRejudgeVo;
 import com.klp.common.core.mapper.BaseMapperPlus;
+import org.apache.ibatis.annotations.Param;
+
+import java.util.List;
+import java.util.Map;
 
 /**
  * 钢卷质量改判记录Mapper接口
@@ -12,4 +16,12 @@ import com.klp.common.core.mapper.BaseMapperPlus;
  */
 public interface WmsCoilQualityRejudgeMapper extends BaseMapperPlus<WmsCoilQualityRejudgeMapper, WmsCoilQualityRejudge, WmsCoilQualityRejudgeVo> {
 
+    /**
+     * 执行原生SQL查询，返回Map列表
+     *
+     * @param sql 原生SQL语句
+     * @return Map列表
+     */
+    List<Map<String, Object>> selectMapsBySql(@Param("sql") String sql);
+
 }

klp-wms/src/main/java/com/klp/service/impl/WmsMaterialCoilServiceImpl.java

@@ -5318,28 +5318,29 @@ public class WmsMaterialCoilServiceImpl implements IWmsMaterialCoilService {
             }
         }
 
-        // 4. 批量查询改判原因（最新的一条）
+        // 4. 批量查询改判原因(最新的一条) - 使用SQL优化
         Map<Long, String> rejudgeReasonMap = new HashMap<>();
         if (!coilIds.isEmpty()) {
-            LambdaQueryWrapper<WmsCoilQualityRejudge> rejudgeQuery = new LambdaQueryWrapper<>();
+            // 使用原生SQL查询每个钢卷的最新改判原因，避免Java分组处理
-            rejudgeQuery.in(WmsCoilQualityRejudge::getCoilId, coilIds);
+            String coilIdsStr = coilIds.stream().map(String::valueOf).collect(Collectors.joining(","));
-            rejudgeQuery.eq(WmsCoilQualityRejudge::getDelFlag, "0");
+            String sql = "SELECT t1.coil_id, t1.rejudge_reason " +
-            rejudgeQuery.orderByDesc(WmsCoilQualityRejudge::getCreateTime);
+                        "FROM wms_coil_quality_rejudge t1 " +
-            List<WmsCoilQualityRejudge> allRejudges = wmsCoilQualityRejudgeMapper.selectList(rejudgeQuery);
+                        "INNER JOIN (" +
+                        "    SELECT coil_id, MAX(create_time) as max_time " +
+                        "    FROM wms_coil_quality_rejudge " +
+                        "    WHERE coil_id IN (" + coilIdsStr + ") " +
+                        "    AND del_flag = '0' " +
+                        "    GROUP BY coil_id" +
+                        ") t2 ON t1.coil_id = t2.coil_id AND t1.create_time = t2.max_time " +
+                        "WHERE t1.del_flag = '0' AND t1.rejudge_reason IS NOT NULL";
                     
-            if (allRejudges != null && !allRejudges.isEmpty()) {
+            List<Map<String, Object>> results = wmsCoilQualityRejudgeMapper.selectMapsBySql(sql);
-                // 按钢卷ID分组，每组取最新的一条
+            if (results != null) {
-                Map<Long, List<WmsCoilQualityRejudge>> rejudgeGroupMap = allRejudges.stream()
+                for (Map<String, Object> result : results) {
-                    .collect(Collectors.groupingBy(WmsCoilQualityRejudge::getCoilId));
+                    Long coilId = (Long) result.get("coil_id");
-                
+                    String rejudgeReason = (String) result.get("rejudge_reason");
-                for (Map.Entry<Long, List<WmsCoilQualityRejudge>> entry : rejudgeGroupMap.entrySet()) {
+                    if (coilId != null && rejudgeReason != null) {
-                    List<WmsCoilQualityRejudge> rejudges = entry.getValue();
+                        rejudgeReasonMap.put(coilId, rejudgeReason);
-                    if (!rejudges.isEmpty()) {
-                        // 由于已按创建时间降序排列，第一条就是最新的
-                        WmsCoilQualityRejudge latestRejudge = rejudges.get(0);
-                        if (latestRejudge.getRejudgeReason() != null) {
-                            rejudgeReasonMap.put(entry.getKey(), latestRejudge.getRejudgeReason());
-                        }
                     }
                 }
             }

klp-wms/src/main/resources/mapper/klp/WmsCoilQualityRejudgeMapper.xml

@@ -18,5 +18,9 @@
         <result property="remark" column="remark"/>
     </resultMap>
 
+    <!-- 执行原生SQL查询，返回Map列表 -->
+    <select id="selectMapsBySql" resultType="java.util.HashMap">
+        ${sql}
+    </select>
 
 </mapper>