优化打分 内存溢出问题

src/main/java/com/biutag/supervisiondata/service/impl/RiskScoreRuleServiceImpl.java

@@ -1,10 +1,6 @@
 package com.biutag.supervisiondata.service.impl;
 
-import cn.hutool.core.util.NumberUtil;
 import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
-import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
-import com.biutag.supervisiondata.config.cache.RedisDao;
-import com.biutag.supervisiondata.pojo.constants.RedisKey;
 import com.biutag.supervisiondata.pojo.entity.mine.Model;
 import com.biutag.supervisiondata.pojo.entity.mine.RiskModelTaskClue;
 import com.biutag.supervisiondata.pojo.entity.mine.RiskPersonal;
@@ -13,8 +9,6 @@ import com.biutag.supervisiondata.repository.ModelRepository;
 import com.biutag.supervisiondata.repository.RiskModelTaskClueRepository;
 import com.biutag.supervisiondata.repository.RiskPersonalRepository;
 import com.biutag.supervisiondata.repository.RiskScoreRuleRepository;
-import com.biutag.supervisiondata.service.RiskPersonalControlRecordService;
-import com.biutag.supervisiondata.service.RiskPersonalService;
 import com.biutag.supervisiondata.service.RiskScoreRuleService;
 import lombok.AllArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
@@ -25,6 +19,7 @@ import java.math.RoundingMode;
 import java.util.*;
 import java.util.function.Function;
 import java.util.stream.Collectors;
+import java.util.stream.IntStream;
 
 /**
  * @author kami on 2024-11-18 19:38:10
@@ -48,7 +43,7 @@ public class RiskScoreRuleServiceImpl implements RiskScoreRuleService {
     public void runScore(List<String> idCodes, String weight) {
         LambdaQueryWrapper<RiskPersonal> queryWrapper = new LambdaQueryWrapper<RiskPersonal>()
                 .select(RiskPersonal::getIdCode, RiskPersonal::getId, RiskPersonal::getRickScore);
-        if(idCodes != null && !idCodes.isEmpty()) {
+        if (idCodes != null && !idCodes.isEmpty()) {
             queryWrapper.in(RiskPersonal::getIdCode, idCodes);
         }
 
@@ -62,93 +57,73 @@ public class RiskScoreRuleServiceImpl implements RiskScoreRuleService {
                 .select(Model::getId, Model::getRiskScoreRuleId));
         Map<Integer, Model> modelMap = models.stream().collect(Collectors.toMap(Model::getRiskScoreRuleId, Function.identity(), (oldValue, newValue) -> newValue));
 
-        List<RiskModelTaskClue> clues = riskModelTaskClueRepository.list(new LambdaQueryWrapper<RiskModelTaskClue>()
+        List<List<RiskPersonal>> personals = IntStream.range(0, (riskPersonals.size() + 99999) / 100000)
-                .select(RiskModelTaskClue::getId, RiskModelTaskClue::getScoreCalc)
+                .mapToObj(i -> riskPersonals.subList(i * 100000, Math.min((i + 1) * 100000, riskPersonals.size())))
+                .toList();
+        log.info("本次打分将对{}人进行算分,分{}批进行", riskPersonals.size(), personals);
+        calc(personals, weight, rulesV1, ruleMap, modelMap);
+    }
+
+    void calc(List<List<RiskPersonal>> personals, String weight, List<RiskScoreRule> rulesV1, Map<Integer, List<RiskScoreRule>> ruleMap, Map<Integer, Model> modelMap) {
+        List<RiskModelTaskClue> clues;
+        List<RiskModelTaskClue> updates;
+        for (int i = 0; i < personals.size(); i++) {
+            List<String> idCodes = personals.get(i).stream().map(RiskPersonal::getIdCode).distinct().toList();
+            clues = riskModelTaskClueRepository.list(new LambdaQueryWrapper<RiskModelTaskClue>()
+                    .select(RiskModelTaskClue::getId, RiskModelTaskClue::getIdCode, RiskModelTaskClue::getModelId, RiskModelTaskClue::getScoreCalc)
+                    .in(RiskModelTaskClue::getIdCode, idCodes)
                     .eq(RiskModelTaskClue::getDel, 0));
-        log.info("计算分项倍分");
+            log.info("第{}批总风险项{}条", i, clues.size());
-        List<RiskModelTaskClue> updates = new ArrayList<>();
+            updates = new ArrayList<>();
-        if(weight != null && !weight.equals("1")) {
             for (RiskModelTaskClue clue : clues) {
                 RiskModelTaskClue update = new RiskModelTaskClue();
                 update.setId(clue.getId());
                 update.setScoreResult(new BigDecimal(clue.getScoreCalc().toString()).multiply(new BigDecimal(weight)).divide(new BigDecimal("1"), 2, RoundingMode.HALF_UP).doubleValue());
                 updates.add(update);
+                clue.setScoreResult(update.getScoreResult());
             }
-            log.info("修改每项得分");
+            log.info("第{}批修改得分数量{}条", i, updates.size());
             riskModelTaskClueRepository.updateBatchById(updates, 100000);
-        }
-        clues = riskModelTaskClueRepository.list(new LambdaQueryWrapper<RiskModelTaskClue>()
-                .select(RiskModelTaskClue::getIdCode, RiskModelTaskClue::getModelId, RiskModelTaskClue::getScoreResult)
-                .eq(RiskModelTaskClue::getDel, 0));
-        log.info("开始算分");
 
+            log.info("第{}批开始算分", i);
             Map<String, Map<Integer, List<RiskModelTaskClue>>> clueMap = new HashMap<>();
-        for (RiskModelTaskClue clue : clues) {
+            clues.forEach(clue -> clueMap
-            Map<Integer, List<RiskModelTaskClue>> tmp = Optional.ofNullable(clueMap.get(clue.getIdCode())).orElse(new HashMap<>());
+                    .computeIfAbsent(clue.getIdCode(), k -> new HashMap<>()) // 获取或初始化内部 Map
-            List<RiskModelTaskClue> list = Optional.ofNullable(tmp.get(clue.getModelId())).orElse(new ArrayList<>());
+                    .computeIfAbsent(clue.getModelId(), k -> new ArrayList<>()) // 获取或初始化 List
-            list.add(clue);
+                    .add(clue));
-            tmp.put(clue.getModelId(), list);
+
-            clueMap.put(clue.getIdCode(), tmp);
-        }
             List<RiskPersonal> toUpdates = new ArrayList<>();
-        int count = 0;
-        int size = riskPersonals.size();
             RiskPersonal update;
-        for (RiskPersonal person : riskPersonals) {
+            for (RiskPersonal person : personals.get(i)) {
-            BigDecimal total = new BigDecimal("0.0");
+                BigDecimal total = BigDecimal.ZERO;
                 for (RiskScoreRule rule : rulesV1) {
                     List<RiskScoreRule> r = Optional.ofNullable(ruleMap.get(rule.getId())).orElse(new ArrayList<>());
-                BigDecimal score = new BigDecimal("0.00");
+                    BigDecimal score = BigDecimal.ZERO;
                     for (RiskScoreRule riskScoreRule : r) {
                         Model model = modelMap.get(riskScoreRule.getId());
-                    if(model == null) {
-                        continue;
-                    }
                         Map<Integer, List<RiskModelTaskClue>> tmp = clueMap.get(person.getIdCode());
-                    if(tmp == null) {
+                        if (tmp == null || model == null) {
                             continue;
                         }
                         List<RiskModelTaskClue> temp = tmp.get(model.getId());
-                    if(temp == null) {
+                        if (temp == null) {
                             continue;
                         }
-
+                        double ruleScore = temp.stream().mapToDouble(RiskModelTaskClue::getScoreResult).sum();
-                    //二次改造
-//                    Integer ruleScore = temp.stream().mapToInt(RiskModelTaskClue::getScore).sum();
-//                    BigDecimal n2 = new BigDecimal(Double.toString(Math.min(ruleScore.doubleValue(), riskScoreRule.getScore())));
-//
-//                    BigDecimal weight = new BigDecimal(Double.toString(riskScoreRule.getWeight()));
-//                    n2 = n2.multiply(weight).divide(new BigDecimal("100"), 2, RoundingMode.HALF_UP);
-                    Double ruleScore = temp.stream().mapToDouble(RiskModelTaskClue::getScoreResult).sum();
                         BigDecimal rScore = new BigDecimal(riskScoreRule.getScore().toString()).multiply(new BigDecimal(weight)).divide(new BigDecimal("1"), 2, RoundingMode.HALF_UP);
                         BigDecimal n2 = new BigDecimal(Double.toString(Math.min(ruleScore, rScore.doubleValue())));
-                    score=score.add(n2);
+                        score = score.add(n2);
                     }
-//                BigDecimal ruleScore = new BigDecimal(Double.toString(rule.getScore()));
-//                BigDecimal weight = new BigDecimal(Double.toString(rule.getWeight()));
-//                score = score.multiply(weight).divide(ruleScore, 2, RoundingMode.HALF_UP);
                     total = total.add(score);
                 }
-            //二次改造
-//            total = total.multiply(new BigDecimal("20"));
-            if(person.getRickScore() == null || person.getRickScore().compareTo(total.doubleValue()) != 0) {
                 update = new RiskPersonal();
                 update.setId(person.getId());
                 update.setRickScore(total.doubleValue());
+                update.setDel(total.doubleValue() <= 0.0?1:0);
                 toUpdates.add(update);
             }
-            if(total.doubleValue() <= 0.0) {
+            log.info("第{}批完成打分完成,共计:{}", i, toUpdates.size());
-                update = new RiskPersonal();
-                update.setId(person.getId());
-                update.setDel(1);
-                toUpdates.add(update);
-            }
-            count++;
-            if(count%100000 == 0) {
-                log.info("已完成打分: {},共计:{}", count,size);
-            }
-        }
-
             personalRepository.updateBatchById(toUpdates, 10000);
         }
+    }
 }