存储分数

.idea/dictionaries/23778.xml

@@ -1,6 +1,7 @@
 <component name="ProjectDictionaryState">
   <dictionary name="23778">
     <words>
+      <w>lxjf</w>
       <w>tencent</w>
     </words>
   </dictionary>

src/main/java/com/ccsens/braintraining/api/BrainController.java

@@ -32,6 +32,15 @@ public class BrainController {
     @Resource
     private IBrainService brainService;
 
+    @ApiOperation(value = "脑力测评排名")
+    @RequestMapping(value = "/rank", method = RequestMethod.POST, produces = {"application/json;charset=UTF-8"})
+    public JsonResponse<BrainVo.Rank> rank(@ApiParam @Validated @RequestBody QueryDto<BrainDto.Rank> params) {
+        log.info("脑力测评排名：{}", params);
+
+        log.info("脑力测评排名结束:{}");
+        return JsonResponse.newInstance().ok();
+    }
+
     @MustLogin
     @ApiOperation(value = "脑力测评生成")
     @RequestMapping(value = "/generate", method = RequestMethod.POST, produces = {"application/json;charset=UTF-8"})
@@ -50,4 +59,14 @@ public class BrainController {
         log.info("查询指定类型题目结束:{}", classify);
         return JsonResponse.newInstance().ok(classify);
     }
+
+    @MustLogin
+    @ApiOperation(value = "保存答案")
+    @RequestMapping(value = "/saveAnswer", method = RequestMethod.POST, produces = {"application/json;charset=UTF-8"})
+    public JsonResponse saveAnswer(@ApiParam @Validated @RequestBody QueryDto<BrainDto.Answer> params) {
+        log.info("保存答案：{}", params);
+        brainService.saveAnswer(params.getParam(), params.getUserId());
+        log.info("保存答案结束");
+        return JsonResponse.newInstance().ok();
+    }
 }

src/main/java/com/ccsens/braintraining/bean/dto/BrainDto.java

@@ -4,7 +4,10 @@ import io.swagger.annotations.ApiModel;
 import io.swagger.annotations.ApiModelProperty;
 import lombok.Data;
 
+import javax.validation.constraints.Max;
+import javax.validation.constraints.Min;
 import javax.validation.constraints.NotNull;
+import java.util.List;
 
 /**
  * @description:
@@ -14,7 +17,7 @@ import javax.validation.constraints.NotNull;
 public class BrainDto {
     @Data
     @ApiModel("脑力训练活动-请求")
-    public class Equipment {
+    public static class Equipment {
         @NotNull(message="请输入设备信息")
         @ApiModelProperty("设备ID")
         private Long equipmentId;
@@ -22,12 +25,68 @@ public class BrainDto {
 
     @Data
     @ApiModel("脑力训练活动-请求")
-    public class Question {
+    public static class Question {
         @ApiModelProperty("活动用户ID")
         private Long activeUserId;
         @ApiModelProperty("分类ID")
         private Long classifyId;
-//        @ApiModelProperty("上一题结束的原因 0:无上一题 1:完成切换 2:到时切换")
-//        private Byte finishReason = 0;
+    }
+
+    @Data
+    @ApiModel("脑力训练答案保存-请求")
+    public static class Answer {
+        @NotNull
+        @ApiModelProperty("活动用户ID")
+        private Long activeUserId;
+        @NotNull
+        @ApiModelProperty("分类ID")
+        private Long classifyId;
+        @ApiModelProperty("结束的原因  2:完成切换 3:到时切换")
+        @Min(2)
+        @Max(3)
+        private byte finishReason = 2;
+        @ApiModelProperty("题目")
+        @NotNull
+        private List<UserAnswer> questions;
+    }
+
+    @Data
+    @ApiModel("题目和选项-请求")
+    public static class UserAnswer {
+        @ApiModelProperty("活动题目ID")
+        private Long questionId;
+        @ApiModelProperty("题目内容,连续减法需要传值")
+        private String questionContent;
+        @ApiModelProperty("分类ID")
+        private List<OptionTime> timeAndOptions;
+    }
+
+    @Data
+    @ApiModel("选项和操作时间-请求")
+    public static class OptionTime {
+        @NotNull
+        @ApiModelProperty("操作ID")
+        private Long operateTime;
+        @ApiModelProperty("答案内容")
+        private String content;
+    }
+
+    @Data
+    @ApiModel("脑力测评活动排名-请求")
+    public static class Rank {
+        @NotNull(message="请输入设备信息")
+        @ApiModelProperty("设备ID")
+        private Long equipmentId;
+        @ApiModelProperty("前多少名")
+        private Integer levelSeveral = 20;
+    }
+
+    @Data
+    @ApiModel("脑力测评活动排名-请求")
+    public static class QuestionAnswer {
+        @ApiModelProperty("活动题目ID")
+        private Long questionId;
+        @ApiModelProperty("答案")
+        private String answer;
     }
 }

src/main/java/com/ccsens/braintraining/bean/po/TrainActiveScore.java

@@ -1,6 +1,7 @@
 package com.ccsens.braintraining.bean.po;
 
 import java.io.Serializable;
+import java.math.BigDecimal;
 import java.util.Date;
 
 public class TrainActiveScore implements Serializable {
@@ -12,7 +13,7 @@ public class TrainActiveScore implements Serializable {
 
     private Long questionId;
 
-    private Integer score;
+    private BigDecimal score;
 
     private Long operator;
 
@@ -56,11 +57,11 @@ public class TrainActiveScore implements Serializable {
         this.questionId = questionId;
     }
 
-    public Integer getScore() {
+    public BigDecimal getScore() {
         return score;
     }
 
-    public void setScore(Integer score) {
+    public void setScore(BigDecimal score) {
         this.score = score;
     }
 

src/main/java/com/ccsens/braintraining/bean/po/TrainActiveScoreExample.java

@@ -1,5 +1,6 @@
 package com.ccsens.braintraining.bean.po;
 
+import java.math.BigDecimal;
 import java.util.ArrayList;
 import java.util.Date;
 import java.util.List;
@@ -355,52 +356,52 @@ public class TrainActiveScoreExample {
             return (Criteria) this;
         }
 
-        public Criteria andScoreEqualTo(Integer value) {
+        public Criteria andScoreEqualTo(BigDecimal value) {
             addCriterion("score =", value, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreNotEqualTo(Integer value) {
+        public Criteria andScoreNotEqualTo(BigDecimal value) {
             addCriterion("score <>", value, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreGreaterThan(Integer value) {
+        public Criteria andScoreGreaterThan(BigDecimal value) {
             addCriterion("score >", value, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreGreaterThanOrEqualTo(Integer value) {
+        public Criteria andScoreGreaterThanOrEqualTo(BigDecimal value) {
             addCriterion("score >=", value, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreLessThan(Integer value) {
+        public Criteria andScoreLessThan(BigDecimal value) {
             addCriterion("score <", value, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreLessThanOrEqualTo(Integer value) {
+        public Criteria andScoreLessThanOrEqualTo(BigDecimal value) {
             addCriterion("score <=", value, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreIn(List<Integer> values) {
+        public Criteria andScoreIn(List<BigDecimal> values) {
             addCriterion("score in", values, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreNotIn(List<Integer> values) {
+        public Criteria andScoreNotIn(List<BigDecimal> values) {
             addCriterion("score not in", values, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreBetween(Integer value1, Integer value2) {
+        public Criteria andScoreBetween(BigDecimal value1, BigDecimal value2) {
             addCriterion("score between", value1, value2, "score");
             return (Criteria) this;
         }
 
-        public Criteria andScoreNotBetween(Integer value1, Integer value2) {
+        public Criteria andScoreNotBetween(BigDecimal value1, BigDecimal value2) {
             addCriterion("score not between", value1, value2, "score");
             return (Criteria) this;
         }

src/main/java/com/ccsens/braintraining/bean/po/TrainQuestionOption.java

@@ -12,8 +12,6 @@ public class TrainQuestionOption implements Serializable {
 
     private Byte showType;
 
-    private Byte pageType;
-
     private Integer sort;
 
     private Long operator;
@@ -58,14 +56,6 @@ public class TrainQuestionOption implements Serializable {
         this.showType = showType;
     }
 
-    public Byte getPageType() {
-        return pageType;
-    }
-
-    public void setPageType(Byte pageType) {
-        this.pageType = pageType;
-    }
-
     public Integer getSort() {
         return sort;
     }
@@ -116,7 +106,6 @@ public class TrainQuestionOption implements Serializable {
         sb.append(", questionId=").append(questionId);
         sb.append(", content=").append(content);
         sb.append(", showType=").append(showType);
-        sb.append(", pageType=").append(pageType);
         sb.append(", sort=").append(sort);
         sb.append(", operator=").append(operator);
         sb.append(", createdAt=").append(createdAt);

src/main/java/com/ccsens/braintraining/bean/po/TrainQuestionOptionExample.java

@@ -355,66 +355,6 @@ public class TrainQuestionOptionExample {
             return (Criteria) this;
         }
 
-        public Criteria andPageTypeIsNull() {
-            addCriterion("page_type is null");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeIsNotNull() {
-            addCriterion("page_type is not null");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeEqualTo(Byte value) {
-            addCriterion("page_type =", value, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeNotEqualTo(Byte value) {
-            addCriterion("page_type <>", value, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeGreaterThan(Byte value) {
-            addCriterion("page_type >", value, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeGreaterThanOrEqualTo(Byte value) {
-            addCriterion("page_type >=", value, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeLessThan(Byte value) {
-            addCriterion("page_type <", value, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeLessThanOrEqualTo(Byte value) {
-            addCriterion("page_type <=", value, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeIn(List<Byte> values) {
-            addCriterion("page_type in", values, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeNotIn(List<Byte> values) {
-            addCriterion("page_type not in", values, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeBetween(Byte value1, Byte value2) {
-            addCriterion("page_type between", value1, value2, "pageType");
-            return (Criteria) this;
-        }
-
-        public Criteria andPageTypeNotBetween(Byte value1, Byte value2) {
-            addCriterion("page_type not between", value1, value2, "pageType");
-            return (Criteria) this;
-        }
-
         public Criteria andSortIsNull() {
             addCriterion("sort is null");
             return (Criteria) this;

src/main/java/com/ccsens/braintraining/bean/po/TrainRuleScore.java

@@ -6,7 +6,7 @@ import java.util.Date;
 public class TrainRuleScore implements Serializable {
     private Long id;
 
-    private String code;
+    private Long activeId;
 
     private Long classifyId;
 
@@ -32,12 +32,12 @@ public class TrainRuleScore implements Serializable {
         this.id = id;
     }
 
-    public String getCode() {
-        return code;
+    public Long getActiveId() {
+        return activeId;
     }
 
-    public void setCode(String code) {
-        this.code = code == null ? null : code.trim();
+    public void setActiveId(Long activeId) {
+        this.activeId = activeId;
     }
 
     public Long getClassifyId() {
@@ -103,7 +103,7 @@ public class TrainRuleScore implements Serializable {
         sb.append(" [");
         sb.append("Hash = ").append(hashCode());
         sb.append(", id=").append(id);
-        sb.append(", code=").append(code);
+        sb.append(", activeId=").append(activeId);
         sb.append(", classifyId=").append(classifyId);
         sb.append(", calculateType=").append(calculateType);
         sb.append(", calculateParam=").append(calculateParam);

src/main/java/com/ccsens/braintraining/bean/po/TrainRuleScoreExample.java

@@ -165,73 +165,63 @@ public class TrainRuleScoreExample {
             return (Criteria) this;
         }
 
-        public Criteria andCodeIsNull() {
-            addCriterion("code is null");
+        public Criteria andActiveIdIsNull() {
+            addCriterion("active_id is null");
             return (Criteria) this;
         }
 
-        public Criteria andCodeIsNotNull() {
-            addCriterion("code is not null");
+        public Criteria andActiveIdIsNotNull() {
+            addCriterion("active_id is not null");
             return (Criteria) this;
         }
 
-        public Criteria andCodeEqualTo(String value) {
-            addCriterion("code =", value, "code");
+        public Criteria andActiveIdEqualTo(Long value) {
+            addCriterion("active_id =", value, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeNotEqualTo(String value) {
-            addCriterion("code <>", value, "code");
+        public Criteria andActiveIdNotEqualTo(Long value) {
+            addCriterion("active_id <>", value, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeGreaterThan(String value) {
-            addCriterion("code >", value, "code");
+        public Criteria andActiveIdGreaterThan(Long value) {
+            addCriterion("active_id >", value, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeGreaterThanOrEqualTo(String value) {
-            addCriterion("code >=", value, "code");
+        public Criteria andActiveIdGreaterThanOrEqualTo(Long value) {
+            addCriterion("active_id >=", value, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeLessThan(String value) {
-            addCriterion("code <", value, "code");
+        public Criteria andActiveIdLessThan(Long value) {
+            addCriterion("active_id <", value, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeLessThanOrEqualTo(String value) {
-            addCriterion("code <=", value, "code");
+        public Criteria andActiveIdLessThanOrEqualTo(Long value) {
+            addCriterion("active_id <=", value, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeLike(String value) {
-            addCriterion("code like", value, "code");
+        public Criteria andActiveIdIn(List<Long> values) {
+            addCriterion("active_id in", values, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeNotLike(String value) {
-            addCriterion("code not like", value, "code");
+        public Criteria andActiveIdNotIn(List<Long> values) {
+            addCriterion("active_id not in", values, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeIn(List<String> values) {
-            addCriterion("code in", values, "code");
+        public Criteria andActiveIdBetween(Long value1, Long value2) {
+            addCriterion("active_id between", value1, value2, "activeId");
             return (Criteria) this;
         }
 
-        public Criteria andCodeNotIn(List<String> values) {
-            addCriterion("code not in", values, "code");
-            return (Criteria) this;
-        }
-
-        public Criteria andCodeBetween(String value1, String value2) {
-            addCriterion("code between", value1, value2, "code");
-            return (Criteria) this;
-        }
-
-        public Criteria andCodeNotBetween(String value1, String value2) {
-            addCriterion("code not between", value1, value2, "code");
+        public Criteria andActiveIdNotBetween(Long value1, Long value2) {
+            addCriterion("active_id not between", value1, value2, "activeId");
             return (Criteria) this;
         }
 

src/main/java/com/ccsens/braintraining/bean/vo/BrainVo.java

@@ -1,6 +1,7 @@
 package com.ccsens.braintraining.bean.vo;
 
 import cn.hutool.core.collection.CollectionUtil;
+import cn.hutool.core.util.StrUtil;
 import com.alibaba.fastjson.JSONArray;
 import com.alibaba.fastjson.JSONObject;
 import com.ccsens.braintraining.bean.po.TrainActiveQuestion;
@@ -91,11 +92,29 @@ public class BrainVo {
         @JsonIgnore
         @ApiModelProperty("生成题目")
         private Byte generate;
-        @JsonIgnore
         @ApiModelProperty("生成题目的参数")
         private String generateParam;
         @ApiModelProperty("共多少道题")
         private Integer total;
+        @ApiModelProperty("分类,仅抽象分类使用")
+        private List<RuleGenerateVo.ChildRandom> classifies;
+
+        public List<RuleGenerateVo.ChildRandom> getClassifies() {
+            if (classifies != null) {
+                return classifies;
+            }
+            if (generate == null || StrUtil.isEmpty(generateParam)) {
+                return null;
+            }
+            if (generate == BrainTrainingConstant.Train.RULE_GENERATE_CHILD_RANDOM) {
+                classifies = JSONArray.parseArray(generateParam, RuleGenerateVo.ChildRandom.class);
+            }
+            return classifies;
+        }
+
+        public String getGenerateParam() {
+            return generate == BrainTrainingConstant.Train.RULE_GENERATE_CONTINUE_SUB ? generateParam : null;
+        }
 
         public Integer getTotal() {
             if (total != null || generate == null) {
@@ -133,7 +152,7 @@ public class BrainVo {
     @Data
     @ApiModel("训练题目-返回")
     public static class Question {
-        @ApiModelProperty("题目ID")
+        @ApiModelProperty("活动题目ID")
         private Long questionId;
         @ApiModelProperty("题干")
         private List<QuestionContent> contents;
@@ -144,16 +163,58 @@ public class BrainVo {
     @Data
     @ApiModel("题干-返回")
     public static class QuestionContent {
+        @ApiModelProperty("题干ID")
         private Long contentId;
+        @ApiModelProperty("题干内容")
         private String content;
+        @ApiModelProperty("题干类型 0:文字 1:图片 2:语音")
         private Byte showType;
     }
 
     @Data
     @ApiModel("选项-返回")
     private static class QuestionOption {
+        @ApiModelProperty("选项ID")
         private Long optionId;
+        @ApiModelProperty("选项内容")
         private String content;
+        @ApiModelProperty("选项类型 0:文字 1:图片 2:语音")
         private Byte showType;
     }
+
+    @Data
+    @ApiModel("脑力测评活动排名-返回")
+    public static class Rank {
+        @ApiModelProperty("活动用户ID")
+        private Long activeUserId;
+        @ApiModelProperty("头像，无，则给默认头像")
+        private String avatarUrl;
+        @ApiModelProperty("用户名")
+        private String userName;
+        @ApiModelProperty("总分数")
+        private Integer totalScore;
+        @ApiModelProperty("操作时间")
+        private Long operationTime;
+    }
+    @Data
+    @ApiModel("脑力测评活动排名-返回")
+    public static class QuestionAnswer {
+        @ApiModelProperty("活动题目ID")
+        private Long questionId;
+        @ApiModelProperty("答案")
+        private String content;
+    }
+    @Data
+    @ApiModel("脑力测评活动-返回")
+    public static class ClassifyAnswer {
+        @ApiModelProperty("分类ID")
+        private Long classifyId;
+        @ApiModelProperty("活动题目ID")
+        private Long questionId;
+        @ApiModelProperty("答案状态 0:错误 1:正确")
+        private Byte answer;
+
+        public static final byte ANSWER_RIGHT = 1;
+    }
+
 }

src/main/java/com/ccsens/braintraining/bean/vo/RuleGenerateVo.java

@@ -25,6 +25,10 @@ public class RuleGenerateVo {
         private Long classifyId;
         @ApiModelProperty("生成几题")
         private int num;
+        @ApiModelProperty("类型code")
+        private String classifyCode;
+        @ApiModelProperty("类型名字")
+        private String classifyName;
     }
     @Data
     @ApiModel("组题规则-等级随机")

src/main/java/com/ccsens/braintraining/bean/vo/RuleScoreVo.java

@@ -0,0 +1,72 @@
+package com.ccsens.braintraining.bean.vo;
+
+import io.swagger.annotations.ApiModel;
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.math.BigDecimal;
+import java.util.List;
+
+/**
+ * @description:
+ * @author: whj
+ * @time: 2022/3/28 15:11
+ */
+public class RuleScoreVo {
+
+    @Data
+    @ApiModel("分数规则-对加错减")
+    public static class WrongSub{
+        @ApiModelProperty("正确的分数")
+        private BigDecimal rightScore;
+        @ApiModelProperty("错误的分数")
+        private BigDecimal wrongScore;
+        @ApiModelProperty("时间增加分数")
+        private List<TimeAndScore> timeScores;
+    }
+
+    @Data
+    @ApiModel("分数规则-正确个数")
+    public static class RightNum{
+        @ApiModelProperty("时间增加分数")
+        private List<NumAndScore> numScores;
+        @ApiModelProperty("时间增加分数")
+        private List<TimeAndScore> timeScores;
+    }
+    @Data
+    @ApiModel("分数规则-对加错0")
+    public static class WrongZero{
+        @ApiModelProperty("正确的分数")
+        private BigDecimal rightScore;
+        @ApiModelProperty("时间增加分数")
+        private List<TimeAndScore> timeScores;
+    }
+    @Data
+    @ApiModel("分数规则-分类")
+    public static class Classify{
+        @ApiModelProperty("正确的分数")
+        private Long classifyId;
+        @ApiModelProperty("时间增加分数")
+        private BigDecimal score;
+    }
+
+
+
+    @Data
+    @ApiModel("个数和分数")
+    public static class NumAndScore {
+        @ApiModelProperty("正确的分数")
+        private int num;
+        @ApiModelProperty("对应的分数")
+        private BigDecimal score;
+    }
+
+    @Data
+    @ApiModel("时间和分数")
+    public static class TimeAndScore {
+        @ApiModelProperty("操作时间，单位：秒")
+        private Byte operationTime;
+        @ApiModelProperty("增加的分数")
+        private BigDecimal addScore;
+    }
+}

src/main/java/com/ccsens/braintraining/persist/dao/BrainDao.java

@@ -1,6 +1,9 @@
 package com.ccsens.braintraining.persist.dao;
 
+import com.ccsens.braintraining.bean.dto.BrainDto;
+import com.ccsens.braintraining.bean.po.TrainActiveLog;
 import com.ccsens.braintraining.bean.po.TrainActiveQuestion;
+import com.ccsens.braintraining.bean.po.TrainActiveScore;
 import com.ccsens.braintraining.bean.vo.BrainVo;
 import com.ccsens.braintraining.bean.vo.RuleGenerateVo;
 import org.apache.ibatis.annotations.Param;
@@ -14,11 +17,11 @@ import java.util.List;
 public interface BrainDao {
     /**
      * 查询该类型下的随机若干道题目
-     * @param activeId 类型ID
+     * @param classifyId 类型ID
      * @param num 题目数量
      * @return 题目ID
      */
-    List<Long> queryRandom(@Param("activeId") Long activeId, @Param("num") int num);
+    List<Long> queryRandom(@Param("classifyId") Long classifyId, @Param("num") int num);
 
     /**
      * 查询指定类型下的随机若干道题目
@@ -29,11 +32,11 @@ public interface BrainDao {
 
     /**
      * 查询指定类型下指定等级的的随机若干道题
-     * @param activeId 类型
+     * @param classifyId 类型
      * @param gradeRandom 等级和题目数量
      * @return 题目ID
      */
-    List<Long> queryGradeRandom(@Param("activeId") Long activeId, @Param("list") List<RuleGenerateVo.GradeRandom> gradeRandom);
+    List<Long> queryGradeRandom(@Param("classifyId") Long classifyId, @Param("list") List<RuleGenerateVo.GradeRandom> gradeRandom);
 
     /**
      * 根据活动ID查询活动信息
@@ -63,4 +66,49 @@ public interface BrainDao {
      * @return 题目
      */
     BrainVo.QuestionClassify getQuestion(@Param("activeUserId") Long activeUserId, @Param("classifyId") Long classifyId);
+
+    /**
+     * 统计正确的答案个数
+     *
+     * @param activeUserId 用户活动ID
+     * @param answerParams 题目和选项
+     * @return 个数
+     */
+    Integer countRight(@Param("activeUserId") Long activeUserId, @Param("list") List<BrainDto.QuestionAnswer> answerParams);
+
+    /**
+     * 查询类型下的答案是否正确
+     * @param activeUserId 用户活动ID
+     * @param answerParams 答案
+     * @return 类型+答案状态
+     */
+    List<BrainVo.ClassifyAnswer> queryClassifyScores(@Param("activeUserId") Long activeUserId, @Param("list")List<BrainDto.QuestionAnswer> answerParams);
+
+    /**
+     * 查询答案，并按顺序排列
+     * @param activeQuestionId 活动题目ID
+     * @return 答案
+     */
+    List<String> queryAnswerSort(@Param("activeQuestionId") Long activeQuestionId);
+
+    /**
+     * 批量添加分数
+     * @param scores 分数
+     */
+    void batchInsertScore(List<TrainActiveScore> scores);
+
+    /**
+     * 批量添加日志
+     * @param logs 日志
+     */
+    void batchInsertLog(List<TrainActiveLog> logs);
+
+    /**
+     *
+     * 查询活动题目对应的答案
+     * @param activeUserId 活动用户ID
+     * @param questionIds 题目
+     * @return 答案
+     */
+    List<BrainVo.QuestionAnswer> queryQuestionAnswers(@Param("activeUserId") Long activeUserId, @Param("list")List<Long> questionIds);
 }

src/main/java/com/ccsens/braintraining/service/BrainService.java

@@ -2,19 +2,19 @@ package com.ccsens.braintraining.service;
 
 import cn.hutool.core.collection.CollectionUtil;
 import cn.hutool.core.lang.Snowflake;
+import cn.hutool.core.util.StrUtil;
 import com.alibaba.fastjson.JSONArray;
 import com.alibaba.fastjson.JSONObject;
 import com.ccsens.braintraining.bean.dto.BrainDto;
 import com.ccsens.braintraining.bean.po.*;
 import com.ccsens.braintraining.bean.vo.BrainVo;
 import com.ccsens.braintraining.bean.vo.RuleGenerateVo;
+import com.ccsens.braintraining.bean.vo.RuleScoreVo;
 import com.ccsens.braintraining.persist.dao.BrainDao;
-import com.ccsens.braintraining.persist.mapper.TrainActiveLogMapper;
-import com.ccsens.braintraining.persist.mapper.TrainActiveMapper;
-import com.ccsens.braintraining.persist.mapper.TrainActiveScoreMapper;
-import com.ccsens.braintraining.persist.mapper.TrainActiveUserMapper;
+import com.ccsens.braintraining.persist.mapper.*;
 import com.ccsens.braintraining.util.BrainTrainingCodeError;
 import com.ccsens.braintraining.util.BrainTrainingConstant;
+import com.ccsens.util.RedisUtil;
 import com.ccsens.util.exception.BaseException;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.stereotype.Service;
@@ -22,9 +22,8 @@ import org.springframework.transaction.annotation.Propagation;
 import org.springframework.transaction.annotation.Transactional;
 
 import javax.annotation.Resource;
-import java.util.ArrayList;
-import java.util.List;
-import java.util.Random;
+import java.math.BigDecimal;
+import java.util.*;
 
 /**
  * @description:
@@ -38,15 +37,21 @@ public class BrainService implements IBrainService {
     @Resource
     private Snowflake snowflake;
     @Resource
+    private RedisUtil redisUtil;
+    @Resource
     private BrainDao brainDao;
     @Resource
     private TrainActiveMapper trainActiveMapper;
     @Resource
     private TrainActiveUserMapper trainActiveUserMapper;
     @Resource
-    private TrainActiveScoreMapper trainActiveScoreMapper;
+    private TrainActiveQuestionMapper trainActiveQuestionMapper;
     @Resource
     private TrainActiveLogMapper trainActiveLogMapper;
+    @Resource
+    private TrainRuleScoreMapper trainRuleScoreMapper;
+    @Resource
+    private TrainClassifyMapper trainClassifyMapper;
 
     @Override
     public BrainVo.Active generateTest(BrainDto.Equipment param, Long userId) {
@@ -75,18 +80,17 @@ public class BrainService implements IBrainService {
         trainActiveUserMapper.insertSelective(activeUser);
         // 遍历规则，查询试题
         List<TrainActiveQuestion> questions = new ArrayList<>();
-        rules.forEach(rule -> generateQuestion(userId, active, questions, rule));
+        rules.forEach(rule -> generateQuestion(activeUser.getId(), questions, rule));
         // 批量添加题库内容
         if (CollectionUtil.isNotEmpty(questions)) {
             log.info("批量生成活动题目");
             brainDao.batchInsertActiveQuestion(questions);
         }
-        return new BrainVo.Active(active.getId(), rules);
+        return new BrainVo.Active(activeUser.getId(), rules);
     }
 
     @Override
     public BrainVo.QuestionClassify queryByClassify(BrainDto.Question param, Long userId) {
-        long now = System.currentTimeMillis();
         // 判断是否已经做过
         Integer score = brainDao.getScore(param.getActiveUserId(), param.getClassifyId());
         log.info("参数：{}，{}，分数：{}", param.getActiveUserId(), param.getClassifyId(), score);
@@ -107,33 +111,433 @@ public class BrainService implements IBrainService {
         return question;
     }
 
+    @Override
+    public void saveAnswer(BrainDto.Answer param, Long userId) {
+        Long now = System.currentTimeMillis();
+        if (CollectionUtil.isEmpty(param.getQuestions())) {
+            log.info("保存答案时没有保存题目的信息");
+            throw new BaseException(BrainTrainingCodeError.PARAM_ERROR);
+        }
+        // 判断有无正在进行的分数保存
+        String key = StrUtil.format(BrainTrainingConstant.Train.REDIS_SAVE_ANSWER, param.getActiveUserId(), param.getClassifyId(), param.getQuestions().get(0).getQuestionId());
+        Object o = redisUtil.get(key);
+        if (o != null) {
+            throw new BaseException(BrainTrainingCodeError.BRAIN_ACTIVE_QUESTION_ANSWER_SAVING);
+        }
+        // 存储当前正在进行的题目
+        redisUtil.set(key, param.getActiveUserId(), BrainTrainingConstant.Train.REDIS_TIME_DEFAULT);
+        try {
+            // 判断是否已经做过
+            Integer score = brainDao.getScore(param.getActiveUserId(), param.getClassifyId());
+            log.info("参数：{}，{}，分数：{}", param.getActiveUserId(), param.getClassifyId(), score);
+            if (score != null) {
+                throw new BaseException(BrainTrainingCodeError.BRAIN_ACTIVE_QUESTION_ANSWER_YES);
+            }
+            // 查询分类
+            TrainClassify classify = trainClassifyMapper.selectByPrimaryKey(param.getClassifyId());
+            if (classify == null) {
+                throw new BaseException(BrainTrainingCodeError.PARAM_ERROR);
+            }
+            // 后续使用的参数处理
+            List<BrainDto.QuestionAnswer> answerParams = new ArrayList<>();
+            List<TrainActiveLog> logs = new ArrayList<>();
+            List<TrainActiveQuestion> activeQuestions = new ArrayList<>();
+            initNeedData(classify, param, userId, answerParams, logs, activeQuestions);
+
+            // 查询用户活动信息
+            TrainActiveUser activeUser = trainActiveUserMapper.selectByPrimaryKey(param.getActiveUserId());
+            if (activeUser == null) {
+                log.info("没有找到用户活动信息：{}", param.getActiveUserId());
+                throw new BaseException(BrainTrainingCodeError.PARAM_ERROR);
+            }
+            // 查询类型计分规则
+            TrainRuleScore ruleScore = getTrainRuleScore(activeUser.getActiveId(), param.getClassifyId());
+            // 分数计算
+            List<TrainActiveScore> scores = getTrainActiveScores(param, now, answerParams, ruleScore);
+
+            //存储分数
+            if (CollectionUtil.isNotEmpty(scores)) {
+                brainDao.batchInsertScore(scores);
+            }
+            // 存储日志
+            TrainActiveLog log = initFinishLog(param, userId);
+            logs.add(log);
+            brainDao.batchInsertLog(logs);
+        }finally {
+            redisUtil.del(key);
+        }
+
+    }
+
+    private TrainActiveLog initFinishLog(BrainDto.Answer param, Long userId) {
+        TrainActiveLog log = new TrainActiveLog();
+        log.setId(snowflake.nextId());
+        log.setActiveUserId(param.getActiveUserId());
+        log.setClassifyId(param.getClassifyId());
+        log.setQuestionId(0L);
+        log.setOptionContent("");
+        log.setTime(System.currentTimeMillis());
+        log.setOperationType(param.getFinishReason());
+        log.setOperator(userId);
+        return log;
+    }
+
+    private List<TrainActiveScore> getTrainActiveScores(BrainDto.Answer param, Long now, List<BrainDto.QuestionAnswer> answerParams, TrainRuleScore ruleScore) {
+        List<TrainActiveScore> scores = new ArrayList<>();
+        switch (ruleScore.getCalculateType()) {
+            case BrainTrainingConstant.Train.RULE_SCORE_NO:break;
+            case BrainTrainingConstant.Train.RULE_SCORE_WRONG_SUB:
+                BigDecimal wrongSubScore = getWrongSubScore(param.getActiveUserId(), param.getClassifyId(), now, answerParams, ruleScore.getCalculateParam());
+                TrainActiveScore wrongSubActiveScore = initScore(param.getActiveUserId(), param.getClassifyId(), 0L, wrongSubScore);
+                scores.add(wrongSubActiveScore);
+                break;
+            case BrainTrainingConstant.Train.RULE_SCORE_RIGHT_NUMBER:
+                BigDecimal rightNumScore = getRightNumScore(param.getActiveUserId(), param.getClassifyId(), now, answerParams, ruleScore.getCalculateParam());
+                TrainActiveScore rightNumActiveScore = initScore(param.getActiveUserId(), param.getClassifyId(), 0L, rightNumScore);
+                scores.add(rightNumActiveScore);
+                break;
+            case BrainTrainingConstant.Train.RULE_SCORE_WRONG_ZERO:
+                BigDecimal wrongZeroScore = getWrongZeroScore(param.getActiveUserId(), param.getClassifyId(), now, answerParams, ruleScore.getCalculateParam());
+                TrainActiveScore wrongZeroActiveScore = initScore(param.getActiveUserId(), param.getClassifyId(), 0L, wrongZeroScore );
+                scores.add(wrongZeroActiveScore);
+                break;
+            case BrainTrainingConstant.Train.RULE_SCORE_CLASSIFY:
+                initClassifyScore(param, answerParams, ruleScore, scores);
+                break;
+            case BrainTrainingConstant.Train.RULE_SCORE_CONTINUE_SUB:
+                BigDecimal continueSubScore = getContinueSubScore(param.getActiveUserId(), param.getClassifyId(), now, param.getQuestions(), ruleScore.getCalculateParam());
+                scores.add(initScore(param.getActiveUserId(), param.getClassifyId(), 0L, continueSubScore));
+                break;
+            case BrainTrainingConstant.Train.RULE_SCORE_SORT:
+                BigDecimal sortScore = getSortScore(param.getActiveUserId(), param.getClassifyId(), now, param.getQuestions().get(0), ruleScore.getCalculateParam());
+                scores.add(initScore(param.getActiveUserId(), param.getClassifyId(), param.getQuestions().get(0).getQuestionId(), sortScore));
+                break;
+            case BrainTrainingConstant.Train.RULE_SCORE_SPACE:
+                BigDecimal spaceScore = getSpaceScore(param.getActiveUserId(), param.getClassifyId(), now, param.getQuestions(), ruleScore.getCalculateParam());
+                scores.add(initScore(param.getActiveUserId(), param.getClassifyId(), 0L, spaceScore));
+                break;
+            default:
+
+        }
+        return scores;
+    }
+
+    /**
+     * 按照个数计算分数
+     * @param activeUserId 活动ID
+     * @param classifyId 类型ID
+     * @param now 时间
+     * @param answerParams 答案
+     * @param calculateParam 规则
+     * @return 分数
+     */
+    private BigDecimal getSpaceScore(Long activeUserId, Long classifyId, Long now, List<BrainDto.UserAnswer> answerParams, String calculateParam) {
+        // 正确的个数
+        List<Long> questionIds = new ArrayList<>();
+        answerParams.forEach(answerParam->{
+            questionIds.add(answerParam.getQuestionId());
+        });
+        List<BrainVo.QuestionAnswer> answers = brainDao.queryQuestionAnswers(activeUserId, questionIds);
+        Map<Long, List<String>> answerMap = new HashMap<>();
+        answers.forEach(questionAnswer->{
+            List<String> answerList = answerMap.getOrDefault(questionAnswer.getQuestionId(), new ArrayList<>());
+            answerList.add(questionAnswer.getContent());
+            answerMap.put(questionAnswer.getQuestionId(), answerList);
+        });
+        int rightNum = 0;
+        for (BrainDto.UserAnswer userAnswer:answerParams) {
+            List<String> options = answerMap.get(userAnswer.getQuestionId());
+            if (CollectionUtil.isEmpty(options) || CollectionUtil.isEmpty(userAnswer.getTimeAndOptions())
+                    || options.size() !=  userAnswer.getTimeAndOptions().size()) {
+                continue;
+            }
+            boolean current = true;
+            for (BrainDto.OptionTime optionTime: userAnswer.getTimeAndOptions()) {
+                if (!options.contains(optionTime.getContent())) {
+                    current = false;
+                    break;
+                }
+            }
+            rightNum += current ? 1 : 0;
+        }
+        return getByNum(activeUserId, classifyId, now, calculateParam, rightNum);
+    }
+
+    /**
+     * 计算对加错减类型的分数
+     * @param activeUserId 活动用户ID
+     * @param classifyId 类型ID
+     * @param now 保存答案时间
+     * @param question 题目
+     * @param calculateParam 计分规则字符串
+     * @return 分数
+     */
+    private BigDecimal getSortScore(Long activeUserId, Long classifyId, Long now, BrainDto.UserAnswer question, String calculateParam) {
+        // 查询正确的答案
+        List<String> answerSorts = brainDao.queryAnswerSort(question.getQuestionId());
+        // 比较答案并计算分数
+        int rightNum = 0;
+        int wrongNum = 0;
+        int j = 0;
+        List<BrainDto.OptionTime> options = question.getTimeAndOptions();
+        for (int i = 0; i < answerSorts.size() && j < options.size(); i++) {
+            for (; j < options.size() ; j++) {
+                if (answerSorts.get(i).equals(options.get(j).getContent())) {
+                    rightNum++;
+                    j++;
+                    break;
+                } else {
+                    wrongNum++;
+                }
+            }
+        }
+        return calculateWrongSubScore(activeUserId, classifyId, now, calculateParam, rightNum, wrongNum);
+    }
+
+    private BigDecimal getContinueSubScore(Long activeUserId, Long classifyId, Long now, List<BrainDto.UserAnswer> answerParams, String calculateParam) {
+        // 判断正误
+
+        TrainActiveQuestion question = trainActiveQuestionMapper.selectByPrimaryKey(answerParams.get(0).getQuestionId());
+        if (question == null) {
+            log.info("连续减法题目错误：{}", answerParams.get(0).getQuestionId());
+            throw new BaseException(BrainTrainingCodeError.PARAM_ERROR);
+        }
+        int totalNums = question.getQuestionAnswer().equals(answerParams.get(0).getTimeAndOptions().get(0).getContent()) ? 1 : 0;
+        for (int i = 1; i<answerParams.size(); i++) {
+            BrainDto.UserAnswer answer = answerParams.get(i);
+            int right = getAnswer(answer.getQuestionContent());
+            totalNums += right == Integer.parseInt(answer.getTimeAndOptions().get(0).getContent()) ? 1 : 0;
+        }
+        log.info("{}连续减法正确的个数：{}", activeUserId, totalNums);
+        // 根据个数计算规则
+        return getByNum(activeUserId, classifyId, now, calculateParam, totalNums);
+    }
+
+    /**
+     * 查询计分规则
+     * @param activeId 用户ID
+     * @param classifyId 分类ID
+     * @return 计分规则
+     */
+    private TrainRuleScore getTrainRuleScore(Long activeId, Long classifyId) {
+        TrainRuleScoreExample scoreExample = new TrainRuleScoreExample();
+        scoreExample.createCriteria().andActiveIdEqualTo(activeId)
+                .andClassifyIdEqualTo(classifyId);
+        scoreExample.setOrderByClause("id desc limit 1");
+        List<TrainRuleScore> ruleScores = trainRuleScoreMapper.selectByExample(scoreExample);
+        if (CollectionUtil.isEmpty(ruleScores) || ruleScores.get(0).getCalculateType() == null) {
+            log.info("没有找到计分规则,活动：{}, 类型：{}", activeId, classifyId);
+            throw new BaseException(BrainTrainingCodeError.SETTING_ERROR);
+        }
+        // 根据计分规则
+        return ruleScores.get(0);
+    }
+
+    /**
+     *  对加错0
+     * @param activeUserId 活动ID
+     * @param classifyId 类型ID
+     * @param now 时间
+     * @param answerParams 答案
+     * @param calculateParam 规则
+     * @return 分数
+     */
+    private BigDecimal getWrongZeroScore(Long activeUserId, Long classifyId, Long now, List<BrainDto.QuestionAnswer> answerParams, String calculateParam) {
+        // 和答案比较，判断正确的个数和错误的个数
+        int rightNum = brainDao.countRight(activeUserId, answerParams);
+        RuleScoreVo.WrongZero wrongZeroRule = JSONObject.parseObject(calculateParam, RuleScoreVo.WrongZero.class);
+        // 根据规则加减
+        BigDecimal wrongZeroScore = wrongZeroRule.getRightScore().multiply(new BigDecimal(rightNum));
+        // 判断规则中有无时间加减分
+        return addTimeScore(activeUserId, classifyId, now, wrongZeroScore, wrongZeroRule.getTimeScores());
+    }
+
+    /**
+     * 按照个数计算分数
+     * @param activeUserId 活动ID
+     * @param classifyId 类型ID
+     * @param now 时间
+     * @param answerParams 答案
+     * @param calculateParam 规则
+     * @return 分数
+     */
+    private BigDecimal getRightNumScore(Long activeUserId, Long classifyId, Long now, List<BrainDto.QuestionAnswer> answerParams, String calculateParam) {
+        // 正确的个数
+        int rightNum = brainDao.countRight(activeUserId, answerParams);
+        return getByNum(activeUserId, classifyId, now, calculateParam, rightNum);
+    }
+
+    /**
+     * 计算对加错减类型的分数
+     * @param activeUserId 活动用户ID
+     * @param classifyId 类型ID
+     * @param now 保存答案时间
+     * @param answerParams 答案
+     * @param calculateParam 计分规则字符串
+     * @return 分数
+     */
+    private BigDecimal getWrongSubScore(Long activeUserId, Long classifyId, Long now, List<BrainDto.QuestionAnswer> answerParams, String calculateParam) {
+        // 和答案比较，判断正确的个数和错误的个数
+        int rightNum = brainDao.countRight(activeUserId, answerParams);
+        int wrongNum = answerParams.size() - rightNum;
+        return calculateWrongSubScore(activeUserId, classifyId, now, calculateParam, rightNum, wrongNum);
+    }
+
+    private BigDecimal getByNum(Long activeUserId, Long classifyId, Long now, String calculateParam, int rightNum) {
+        RuleScoreVo.RightNum ruleScore = JSONObject.parseObject(calculateParam, RuleScoreVo.RightNum.class);
+        BigDecimal totalScore = new BigDecimal(0);
+        for (int i = ruleScore.getNumScores().size() - 1; i >= 0 ; i--) {
+            RuleScoreVo.NumAndScore rule = ruleScore.getNumScores().get(i);
+            if (rightNum >= rule.getNum()) {
+                totalScore = rule.getScore();
+                break;
+            }
+        }
+        return addTimeScore(activeUserId, classifyId, now, totalScore, ruleScore.getTimeScores());
+    }
+
+    /**
+     * 初始化分数对象
+     * @param activeUserId 活动用户ID
+     * @param classifyId 分类ID
+     * @param totalScore 分数
+     * @return 分数
+     */
+    private TrainActiveScore initScore(Long activeUserId, Long classifyId, Long questionId, BigDecimal totalScore) {
+        TrainActiveScore score = new TrainActiveScore();
+        score.setId(snowflake.nextId());
+        score.setActiveUserId(activeUserId);
+        score.setClassifyId(classifyId);
+        score.setQuestionId(questionId);
+        score.setScore(totalScore);
+        return score;
+    }
+
+    private void initClassifyScore(BrainDto.Answer param, List<BrainDto.QuestionAnswer> answerParams, TrainRuleScore ruleScore, List<TrainActiveScore> scores) {
+        // {classifyId:score}
+        List<BrainVo.ClassifyAnswer> classifyAnswers = brainDao.queryClassifyScores(param.getActiveUserId(), answerParams);
+        JSONObject scoreRule = JSONObject.parseObject(ruleScore.getCalculateParam());
+        classifyAnswers.forEach(answer -> {
+            BigDecimal questionScore = answer.getAnswer() == BrainVo.ClassifyAnswer.ANSWER_RIGHT ? scoreRule.getBigDecimal(answer.getClassifyId() + "") : new BigDecimal(0);
+            TrainActiveScore activeScore = initScore(param.getActiveUserId(), param.getClassifyId(), answer.getQuestionId(), questionScore);
+            scores.add(activeScore);
+        });
+    }
+
+    private void initNeedData(TrainClassify classify, BrainDto.Answer param, Long userId, List<BrainDto.QuestionAnswer> answerParams, List<TrainActiveLog> logs, List<TrainActiveQuestion> activeQuestions) {
+
+        param.getQuestions().forEach(question -> {
+            question.getTimeAndOptions().forEach(optionTime -> {
+                BrainDto.QuestionAnswer answer = new BrainDto.QuestionAnswer();
+                answer.setQuestionId(question.getQuestionId());
+                answer.setAnswer(optionTime.getContent());
+                answerParams.add(answer);
+                TrainActiveLog log = new TrainActiveLog();
+                log.setId(snowflake.nextId());
+                log.setActiveUserId(param.getActiveUserId());
+                log.setClassifyId(param.getClassifyId());
+                log.setQuestionId(question.getQuestionId());
+                log.setOptionContent(optionTime.getContent());
+                log.setTime(optionTime.getOperateTime());
+                log.setOperationType(BrainTrainingConstant.Train.LOG_OPERATE_OPERATE);
+                log.setOperator(userId);
+                logs.add(log);
+            });
+            // 动态生成题目
+            String content = question.getQuestionContent();
+            if (StrUtil.isEmpty(content) || !(question.getQuestionId() != null && question.getQuestionId() != 0)) {
+                return;
+            }
+
+            switch (classify.getCode()) {
+                case BrainTrainingConstant.Train.CLASSIFY_CONTINUE_SUB:
+                    TrainActiveQuestion activeQuestion = new TrainActiveQuestion();
+                    activeQuestion.setId(snowflake.nextId());
+                    activeQuestion.setActiveUserId(param.getActiveUserId());
+                    activeQuestion.setClassifyId(param.getClassifyId());
+                    activeQuestion.setQuestionContent(content);
+                    int answer = getAnswer(content);
+                    activeQuestion.setQuestionAnswer(answer + "");
+                    activeQuestions.add(activeQuestion);
+                    break;
+                default:
+                    break;
+            }
+
+        });
+    }
+
+    private int getAnswer(String content) {
+        return Integer.parseInt(content.split(BrainTrainingConstant.Train.SYMBOL_SUB)[0]) - Integer.parseInt(content.split(BrainTrainingConstant.Train.SYMBOL_SUB)[1]);
+    }
+
+    private BigDecimal calculateWrongSubScore(Long activeUserId, Long classifyId, Long now, String calculateParam, int rightNum, int wrongNum) {
+        RuleScoreVo.WrongSub wrongSubRule = JSONObject.parseObject(calculateParam, RuleScoreVo.WrongSub.class);
+        // 根据规则加减
+        BigDecimal wrongSubScore = wrongSubRule.getRightScore().multiply(new BigDecimal(rightNum))
+                .add(wrongSubRule.getWrongScore().multiply(new BigDecimal(wrongNum)));
+        // 判断规则中有无时间加减分
+        return addTimeScore(activeUserId, classifyId, now, wrongSubScore, wrongSubRule.getTimeScores());
+    }
+
+    /**
+     * 快速提交加分
+     * @param activeUserId 活动用户ID
+     * @param classifyId 类型ID
+     * @param now 提交时间
+     * @param totalScore 分数
+     * @param timeScores 时间分数规则
+     */
+    private BigDecimal addTimeScore(Long activeUserId, Long classifyId, Long now, BigDecimal totalScore, List<RuleScoreVo.TimeAndScore> timeScores) {
+        if (CollectionUtil.isEmpty(timeScores)) {
+            return totalScore;
+        }
+        // 计算当前时间 - 查询试题的时间
+        // 查询试题的日志
+        TrainActiveLogExample logExample = new TrainActiveLogExample();
+        logExample.createCriteria().andActiveUserIdEqualTo(activeUserId)
+                .andClassifyIdEqualTo(classifyId)
+                .andOperationTypeEqualTo(BrainTrainingConstant.Train.LOG_OPERATE_QUERY);
+        logExample.setOrderByClause("id desc limit 1");
+        List<TrainActiveLog> queryLogs = trainActiveLogMapper.selectByExample(logExample);
+        if (CollectionUtil.isNotEmpty(queryLogs)) {
+            TrainActiveLog log = queryLogs.get(0);
+            long time = now - log.getTime();
+            for (RuleScoreVo.TimeAndScore timeAndScore: timeScores) {
+                if (time <= timeAndScore.getOperationTime() * 1000) {
+                    return totalScore.add(timeAndScore.getAddScore());
+                }
+            }
+        }
+        return totalScore;
+    }
+
     /**
      * 按照规则生成题目，并添加到questions中
-     * @param userId 操作者ID
-     * @param active 活动信息
+     * @param activeUserId 用户活动ID
      * @param questions 题目
      * @param rule 规则
      */
-    private void generateQuestion(Long userId, TrainActive active, List<TrainActiveQuestion> questions, BrainVo.GenerateRule rule) {
+    private void generateQuestion(Long activeUserId, List<TrainActiveQuestion> questions, BrainVo.GenerateRule rule) {
         switch (rule.getGenerate()) {
             case BrainTrainingConstant.Train.RULE_GENERATE_RANDOM:
                 RuleGenerateVo.Random random = JSONObject.parseObject(rule.getGenerateParam(), RuleGenerateVo.Random.class);
-                List<Long> randomIds = brainDao.queryRandom(rule.getActiveId(), random.getNum());
-                addQuestion(questions, randomIds, active.getId(), userId);
+                List<Long> randomIds = brainDao.queryRandom(rule.getClassifyId(), random.getNum());
+                addQuestion(questions, randomIds, activeUserId, rule.getClassifyId());
                 break;
             case BrainTrainingConstant.Train.RULE_GENERATE_CHILD_RANDOM:
                 List<RuleGenerateVo.ChildRandom> childRandom = JSONArray.parseArray(rule.getGenerateParam(), RuleGenerateVo.ChildRandom.class);
                 List<Long> childRandomIds = brainDao.queryChildRandom(childRandom);
-                addQuestion(questions, childRandomIds, active.getId(), userId);
+                addQuestion(questions, childRandomIds, activeUserId, rule.getClassifyId());
                 break;
             case BrainTrainingConstant.Train.RULE_GENERATE_GRADE_RANDOM:
                 List<RuleGenerateVo.GradeRandom> gradeRandom = JSONArray.parseArray(rule.getGenerateParam(), RuleGenerateVo.GradeRandom.class);
-                List<Long> ids = brainDao.queryGradeRandom(rule.getActiveId(), gradeRandom);
-                addQuestion(questions, ids, active.getId(), userId);
+                List<Long> ids = brainDao.queryGradeRandom(rule.getClassifyId(), gradeRandom);
+                addQuestion(questions, ids, activeUserId, rule.getClassifyId());
                 break;
             case BrainTrainingConstant.Train.RULE_GENERATE_CONTINUE_SUB:
                 RuleGenerateVo.ContinuousSub continueSub = JSONObject.parseObject(rule.getGenerateParam(), RuleGenerateVo.ContinuousSub.class);
-                TrainActiveQuestion question = initContinueSubQuestion(active.getId(), rule.getClassifyId(), continueSub, userId);
+                TrainActiveQuestion question = initContinueSubQuestion(activeUserId, rule.getClassifyId(), continueSub);
                 questions.add(question);
                 break;
             default:
@@ -141,12 +545,26 @@ public class BrainService implements IBrainService {
         }
     }
 
-    private TrainActiveQuestion initContinueSubQuestion(Long activeUserId, Long classifyId, RuleGenerateVo.ContinuousSub continueSub, Long userId) {
+    /**
+     * 初始化连续减法
+     * @param activeUserId  用户活动ID
+     * @param classifyId 分类ID
+     * @param continueSub 连续减法规则
+     * @return 题目
+     */
+    private TrainActiveQuestion initContinueSubQuestion(Long activeUserId, Long classifyId, RuleGenerateVo.ContinuousSub continueSub) {
         Random randomNum = new Random();
         // 在指定范围内随机生成被减数
         int minuend = randomNum.nextInt(continueSub.getMinuendMax() - continueSub.getMinuendMin() + 1) + continueSub.getMinuendMin();
         // 在指定范围内随机生成被减数
         int subtrahend = randomNum.nextInt(continueSub.getSubtrahendMax() - continueSub.getSubtrahendMin() + 1) + continueSub.getSubtrahendMin();
+        String partition = BrainTrainingConstant.Train.SYMBOL_DOT;
+        String nonNums = continueSub.getNonNums();
+        while (StrUtil.isNotEmpty(nonNums) && (nonNums.equals(subtrahend) || nonNums.endsWith(partition + subtrahend)
+            || nonNums.startsWith(subtrahend + partition) || nonNums.contains(partition + subtrahend + partition))) {
+            subtrahend = randomNum.nextInt(continueSub.getSubtrahendMax() - continueSub.getSubtrahendMin() + 1) + continueSub.getSubtrahendMin();
+        }
+        log.info("{}的连续减法首道题：{}-{}", activeUserId, minuend, subtrahend);
         TrainActiveQuestion question = new TrainActiveQuestion();
         question.setId(snowflake.nextId());
         question.setActiveUserId(activeUserId);
@@ -154,11 +572,18 @@ public class BrainService implements IBrainService {
         question.setQuestionId(0L);
         question.setQuestionContent(minuend + BrainTrainingConstant.Train.SYMBOL_SUB + subtrahend);
         question.setQuestionAnswer(minuend - subtrahend + "");
-        question.setOperator(userId);
+        question.setOperator(0L);
         return question;
     }
 
-    private void addQuestion(List<TrainActiveQuestion> questions, List<Long> questionIds, Long activeUserId, Long userId) {
+    /**
+     * 添加题目信息
+     * @param questions 题目列表
+     * @param questionIds 题目ID
+     * @param activeUserId 用户活动ID
+     * @param classifyId 分类ID
+     */
+    private void addQuestion(List<TrainActiveQuestion> questions, List<Long> questionIds, Long activeUserId, Long classifyId) {
         if (CollectionUtil.isEmpty(questionIds)) {
             log.info("没有查找到题目，不添加该题型的题目");
             return;
@@ -167,8 +592,9 @@ public class BrainService implements IBrainService {
             TrainActiveQuestion question = new TrainActiveQuestion();
             question.setId(snowflake.nextId());
             question.setActiveUserId(activeUserId);
+            question.setClassifyId(classifyId);
             question.setQuestionId(id);
-            question.setOperator(userId);
+            question.setOperator(0L);
             question.setQuestionContent("");
             question.setQuestionAnswer("");
             questions.add(question);

src/main/java/com/ccsens/braintraining/service/IBrainService.java

@@ -25,4 +25,11 @@ public interface IBrainService {
      * @return 题目信息
      */
     BrainVo.QuestionClassify queryByClassify(BrainDto.Question param, Long userId);
+
+    /**
+     * 保存答案
+     * @param param 答案
+     * @param userId 答题人
+     */
+    void saveAnswer(BrainDto.Answer param, Long userId);
 }

src/main/java/com/ccsens/braintraining/util/BrainTrainingCodeError.java

@@ -17,6 +17,7 @@ public class BrainTrainingCodeError extends CodeError {
     public static final Code BRAIN_ACTIVE_NOT_OPEN = new Code(506,"当前没有正在进行的脑力活动，请咨询管理人员开放时间。",true);
     public static final Code BRAIN_ACTIVE_RULE_NO = new Code(507,"活动还没有配置规则，请联系管理人员配置。",true);
     public static final Code BRAIN_ACTIVE_QUESTION_ANSWER_YES = new Code(508,"该类型您已经完成，不能重复进行。",true);
+    public static final Code BRAIN_ACTIVE_QUESTION_ANSWER_SAVING = new Code(509,"答案在保存中，无需重复提交。",true);
 
 
 }

src/main/java/com/ccsens/braintraining/util/BrainTrainingConstant.java

@@ -21,8 +21,29 @@ public class BrainTrainingConstant extends WebConstant {
         public final static byte RULE_GENERATE_GRADE_RANDOM = 2;
         /**脑力测评组题规则：连续减法*/
         public final static byte RULE_GENERATE_CONTINUE_SUB = 3;
+        /**脑力测评计分规则：不计分*/
+        public final static byte RULE_SCORE_NO = 0;
+        /**脑力测评组题规则：对加错减*/
+        public final static byte RULE_SCORE_WRONG_SUB = 1;
+        /**脑力测评组题规则：按个数计分*/
+        public final static byte RULE_SCORE_RIGHT_NUMBER = 2;
+        /**脑力测评组题规则：正确计分，错误不计分*/
+        public final static byte RULE_SCORE_WRONG_ZERO = 3;
+        /**脑力测评组题规则：根据题目的分类不同给分*/
+        public final static byte RULE_SCORE_CLASSIFY = 4;
+        /**脑力测评组题规则：连续减法*/
+        public final static byte RULE_SCORE_CONTINUE_SUB = 5;
+        /**脑力测评组题规则：按顺序判断对错，且对加错减*/
+        public final static byte RULE_SCORE_SORT = 6;
+        public final static byte RULE_SCORE_SPACE = 7;
+
+        /**类型：连续减法*/
+        public final static String CLASSIFY_CONTINUE_SUB = "LXJF";
+
         /**符号：减法*/
         public final static String SYMBOL_SUB = "-";
+        /**符号：逗号*/
+        public final static String SYMBOL_DOT = ",";
         /**日志操作类型:查看题目*/
         public final static byte LOG_OPERATE_QUERY = 0;
         /**日志操作类型:操作过程*/
@@ -31,8 +52,10 @@ public class BrainTrainingConstant extends WebConstant {
         public final static byte LOG_OPERATE_SAVE = 2;
         /**日志操作类型:到时切换*/
         public final static byte LOG_OPERATE_TIME = 3;
-
-
+        /**redis key：保存答案_用户活动ID_类型ID_题目ID*/
+        public final static String REDIS_SAVE_ANSWER = "save_answer_{}_{}_{}";
+        /**默认有效时长：10分钟*/
+        public final static long REDIS_TIME_DEFAULT = 10 * 60;
     }
 
     public static class User{

src/main/resources/application-dev.yml

@@ -45,7 +45,7 @@ swagger:
 #  timeout: 1000
 
 file:
-  path: /home/cloud/braintraining/uploads/
+  path: /home/cloud/braintraining/server/uploads/
   domain: http://127.0.0.1:7280/v1.0/
   imgDomain: http://127.0.0.1:7280/v1.0/uploads/
 url:

src/main/resources/application-prod.yml

@@ -11,7 +11,7 @@ swagger:
   enable: true
 
 file:
-  path: /home/cloud/braintraining/uploads/
+  path: /home/cloud/braintraining/server/uploads/
   domain: https://www.tall.wiki/braintraining/v1.0/
   imgDomain: https://www.tall.wiki/braintraining/v1.0/uploads/
 url:

src/main/resources/application-test.yml

@@ -11,7 +11,7 @@ swagger:
   enable: true
 
 file:
-  path: /home/cloud/braintraining/uploads/
+  path: /home/cloud/braintraining/server/uploads/
   domain: http://test.tall.wiki/braintraining/v1.0/
   imgDomain: http://test.tall.wiki/braintraining/v1.0/uploads/
 url:

src/main/resources/application.yml

@@ -1,4 +1,4 @@
 spring:
   profiles:
-    active: test
+    active: dev
     include: common

src/main/resources/logback-spring.xml

@@ -9,7 +9,7 @@
 
     <contextName>logback</contextName>
     <!-- name的值是变量的名称，value的值时变量定义的值。通过定义的值会被插入到logger上下文中。定义变量后，可以使“${}”来使用变量。 -->
-    <property name="log.path" value="/home/cloud/braintraining/log/" />
+    <property name="log.path" value="/home/cloud/braintraining/server/log/" />
 
     <!-- 彩色日志 -->
     <!-- 彩色日志依赖的渲染类 -->

src/main/resources/mapper_dao/BrainDao.xml

@@ -26,7 +26,21 @@
         INSERT INTO t_train_active_question ( id, active_user_id, classify_id, question_id, question_content, question_answer, operator )
         VALUES
         <foreach collection="list" item="item" separator=",">
-            (#{id}, #{activeUserId}, #{classifyId}, #{questionId}, #{questionContent}, #{questionAnswer}, #{operator})
+            (#{item.id}, #{item.activeUserId}, #{item.classifyId}, #{item.questionId}, #{item.questionContent}, #{item.questionAnswer}, #{item.operator})
+        </foreach>
+    </insert>
+    <insert id="batchInsertScore">
+        INSERT INTO t_train_active_score ( id, active_user_id, classify_id, question_id, score )
+        VALUES
+        <foreach collection="list" item="item" separator=",">
+            ( #{item.id}, #{item.activeUserId}, #{item.classifyId}, #{item.questionId}, #{item.score} )
+        </foreach>
+    </insert>
+    <insert id="batchInsertLog">
+        INSERT INTO t_train_active_log ( id, active_user_id, classify_id, question_id, option_content, time, operation_type, operator )
+        VALUES
+        <foreach collection="list" item="item" separator=",">
+            ( #{item.id}, #{item.activeUserId}, #{item.classifyId}, #{item.questionId}, #{item.optionContent}, #{item.time}, #{item.operationType}, #{item.operator} )
         </foreach>
     </insert>
     <select id="queryRandom" resultType="java.lang.Long">
@@ -35,40 +49,44 @@
         FROM
             t_train_question
         WHERE
-            classify_id = #{activeId}
+            classify_id = #{classifyId}
             AND rec_status = 0
         ORDER BY
             rand()
             LIMIT ${num}
     </select>
     <select id="queryChildRandom" resultType="java.lang.Long">
+        select * from (
         <foreach collection="list" item="item" separator="union">
-            SELECT
-                id
+            (SELECT
+            id
             FROM
-                t_train_question
+            t_train_question
             WHERE
-                classify_id = #{item.activeId}
-                AND rec_status = 0
+            classify_id = #{item.classifyId}
+            AND rec_status = 0
             ORDER BY
-                rand()
-                LIMIT ${item.num}
+            rand()
+            LIMIT ${item.num})
         </foreach>
+        )t order by rand()
     </select>
     <select id="queryGradeRandom" resultType="java.lang.Long">
+        select * from (
         <foreach collection="list" item="item" separator="union">
-            SELECT
+            (SELECT
                 id
             FROM
                 t_train_question
             WHERE
-                classify_id = #{item.activeId}
+                classify_id = #{classifyId}
                 AND grade = #{item.grade}
                 AND rec_status = 0
             ORDER BY
                 rand()
-                LIMIT ${item.num}
+                LIMIT ${item.num})
         </foreach>
+        )t order by rand()
     </select>
     <select id="queryGenerateRules" resultType="com.ccsens.braintraining.bean.vo.BrainVo$GenerateRule">
         SELECT
@@ -109,9 +127,9 @@
             g.generate,
             g.generate_param AS generateParam,
             q.id AS questionId,
-            qc.id AS contentId,
-            qc.content AS questionContent,
-            qc.show_type AS questionShowType,
+            IFNULL(qc.id,0) AS contentId,
+            IFNULL(qc.content, q.question_content) AS questionContent,
+            IFNULL(qc.show_type,0) AS questionShowType,
             o.id AS optionId,
             o.content AS optionContent,
             o.show_type AS optionShowType
@@ -130,4 +148,74 @@
             AND q.classify_id = #{classifyId}
             AND q.rec_status = 0
     </select>
+    <select id="countRight" resultType="java.lang.Integer">
+        SELECT
+            count(*)
+        FROM
+            t_train_question_answer a,
+            t_train_active_question q
+        <where>
+            a.question_id = q.question_id
+            AND q.active_user_id = #{activeUserId}
+            <foreach collection="list" item="item" open="AND (" separator="or" close=")">
+                ( q.id = #{item.questionId} AND a.content = #{item.answer} )
+            </foreach>
+            AND a.rec_status = 0
+            AND q.rec_status = 0
+        </where>
+    </select>
+    <select id="queryClassifyScores" resultType="com.ccsens.braintraining.bean.vo.BrainVo$ClassifyAnswer">
+        SELECT
+            q.classify_id AS classifyId,
+            aq.id AS questionId,
+            CASE
+                <foreach collection="list" item="item">
+                    WHEN aq.id = #{item.questionId} THEN IF( a.content = #{item.answer}, 1, 0 )
+                </foreach>
+                ELSE 0
+            END AS answer
+        FROM
+            t_train_active_question aq,
+            t_train_question q,
+            t_train_question_answer a
+        WHERE
+            aq.question_id = q.id
+            AND q.id = a.question_id
+            AND aq.active_user_id = #{activeUserId}
+            <foreach collection="list" item="item" open="AND aq.id IN ("  close=")" separator=",">
+                #{item.questionId}
+            </foreach>
+            AND aq.rec_status = 0
+            AND q.rec_status = 0
+    </select>
+    <select id="queryAnswerSort" resultType="java.lang.String">
+        SELECT
+            a.content
+        FROM
+            t_train_active_question q,
+            t_train_question_answer a
+        WHERE
+            q.question_id = a.question_id
+            AND q.id = #{activeQuestionId}
+            AND q.rec_status = 0
+            AND a.rec_status = 0
+        ORDER BY
+            a.sort ASC
+    </select>
+    <select id="queryQuestionAnswers" resultType="com.ccsens.braintraining.bean.vo.BrainVo$QuestionAnswer">
+        SELECT
+            q.id AS questionId,
+            a.content
+        FROM
+            t_train_active_question q,
+            t_train_question_answer a
+        WHERE
+            q.question_id = a.question_id
+            AND q.active_user_id = #{activeUserId}
+            <foreach collection="list" item="item" open="AND q.id IN (" separator="," close=")">
+                #{item}
+            </foreach>
+            AND a.rec_status = 0
+            AND q.rec_status = 0
+    </select>
 </mapper>

src/main/resources/mapper_raw/TrainActiveScoreMapper.xml

@@ -6,7 +6,7 @@
     <result column="active_user_id" jdbcType="BIGINT" property="activeUserId" />
     <result column="classify_id" jdbcType="BIGINT" property="classifyId" />
     <result column="question_id" jdbcType="BIGINT" property="questionId" />
-    <result column="score" jdbcType="INTEGER" property="score" />
+    <result column="score" jdbcType="DECIMAL" property="score" />
     <result column="operator" jdbcType="BIGINT" property="operator" />
     <result column="created_at" jdbcType="TIMESTAMP" property="createdAt" />
     <result column="updated_at" jdbcType="TIMESTAMP" property="updatedAt" />
@@ -110,7 +110,7 @@
       created_at, updated_at, rec_status
       )
     values (#{id,jdbcType=BIGINT}, #{activeUserId,jdbcType=BIGINT}, #{classifyId,jdbcType=BIGINT}, 
-      #{questionId,jdbcType=BIGINT}, #{score,jdbcType=INTEGER}, #{operator,jdbcType=BIGINT}, 
+      #{questionId,jdbcType=BIGINT}, #{score,jdbcType=DECIMAL}, #{operator,jdbcType=BIGINT}, 
       #{createdAt,jdbcType=TIMESTAMP}, #{updatedAt,jdbcType=TIMESTAMP}, #{recStatus,jdbcType=TINYINT}
       )
   </insert>
@@ -159,7 +159,7 @@
         #{questionId,jdbcType=BIGINT},
       </if>
       <if test="score != null">
-        #{score,jdbcType=INTEGER},
+        #{score,jdbcType=DECIMAL},
       </if>
       <if test="operator != null">
         #{operator,jdbcType=BIGINT},
@@ -197,7 +197,7 @@
         question_id = #{record.questionId,jdbcType=BIGINT},
       </if>
       <if test="record.score != null">
-        score = #{record.score,jdbcType=INTEGER},
+        score = #{record.score,jdbcType=DECIMAL},
       </if>
       <if test="record.operator != null">
         operator = #{record.operator,jdbcType=BIGINT},
@@ -222,7 +222,7 @@
       active_user_id = #{record.activeUserId,jdbcType=BIGINT},
       classify_id = #{record.classifyId,jdbcType=BIGINT},
       question_id = #{record.questionId,jdbcType=BIGINT},
-      score = #{record.score,jdbcType=INTEGER},
+      score = #{record.score,jdbcType=DECIMAL},
       operator = #{record.operator,jdbcType=BIGINT},
       created_at = #{record.createdAt,jdbcType=TIMESTAMP},
       updated_at = #{record.updatedAt,jdbcType=TIMESTAMP},
@@ -244,7 +244,7 @@
         question_id = #{questionId,jdbcType=BIGINT},
       </if>
       <if test="score != null">
-        score = #{score,jdbcType=INTEGER},
+        score = #{score,jdbcType=DECIMAL},
       </if>
       <if test="operator != null">
         operator = #{operator,jdbcType=BIGINT},
@@ -266,7 +266,7 @@
     set active_user_id = #{activeUserId,jdbcType=BIGINT},
       classify_id = #{classifyId,jdbcType=BIGINT},
       question_id = #{questionId,jdbcType=BIGINT},
-      score = #{score,jdbcType=INTEGER},
+      score = #{score,jdbcType=DECIMAL},
       operator = #{operator,jdbcType=BIGINT},
       created_at = #{createdAt,jdbcType=TIMESTAMP},
       updated_at = #{updatedAt,jdbcType=TIMESTAMP},

src/main/resources/mapper_raw/TrainQuestionOptionMapper.xml

@@ -6,7 +6,6 @@
     <result column="question_id" jdbcType="BIGINT" property="questionId" />
     <result column="content" jdbcType="VARCHAR" property="content" />
     <result column="show_type" jdbcType="TINYINT" property="showType" />
-    <result column="page_type" jdbcType="TINYINT" property="pageType" />
     <result column="sort" jdbcType="INTEGER" property="sort" />
     <result column="operator" jdbcType="BIGINT" property="operator" />
     <result column="created_at" jdbcType="TIMESTAMP" property="createdAt" />
@@ -72,8 +71,7 @@
     </where>
   </sql>
   <sql id="Base_Column_List">
-    id, question_id, content, show_type, page_type, sort, operator, created_at, updated_at, 
-    rec_status
+    id, question_id, content, show_type, sort, operator, created_at, updated_at, rec_status
   </sql>
   <select id="selectByExample" parameterType="com.ccsens.braintraining.bean.po.TrainQuestionOptionExample" resultMap="BaseResultMap">
     select
@@ -107,13 +105,13 @@
   </delete>
   <insert id="insert" parameterType="com.ccsens.braintraining.bean.po.TrainQuestionOption">
     insert into t_train_question_option (id, question_id, content, 
-      show_type, page_type, sort, 
-      operator, created_at, updated_at, 
-      rec_status)
+      show_type, sort, operator, 
+      created_at, updated_at, rec_status
+      )
     values (#{id,jdbcType=BIGINT}, #{questionId,jdbcType=BIGINT}, #{content,jdbcType=VARCHAR}, 
-      #{showType,jdbcType=TINYINT}, #{pageType,jdbcType=TINYINT}, #{sort,jdbcType=INTEGER}, 
-      #{operator,jdbcType=BIGINT}, #{createdAt,jdbcType=TIMESTAMP}, #{updatedAt,jdbcType=TIMESTAMP}, 
-      #{recStatus,jdbcType=TINYINT})
+      #{showType,jdbcType=TINYINT}, #{sort,jdbcType=INTEGER}, #{operator,jdbcType=BIGINT}, 
+      #{createdAt,jdbcType=TIMESTAMP}, #{updatedAt,jdbcType=TIMESTAMP}, #{recStatus,jdbcType=TINYINT}
+      )
   </insert>
   <insert id="insertSelective" parameterType="com.ccsens.braintraining.bean.po.TrainQuestionOption">
     insert into t_train_question_option
@@ -130,9 +128,6 @@
       <if test="showType != null">
         show_type,
       </if>
-      <if test="pageType != null">
-        page_type,
-      </if>
       <if test="sort != null">
         sort,
       </if>
@@ -162,9 +157,6 @@
       <if test="showType != null">
         #{showType,jdbcType=TINYINT},
       </if>
-      <if test="pageType != null">
-        #{pageType,jdbcType=TINYINT},
-      </if>
       <if test="sort != null">
         #{sort,jdbcType=INTEGER},
       </if>
@@ -203,9 +195,6 @@
       <if test="record.showType != null">
         show_type = #{record.showType,jdbcType=TINYINT},
       </if>
-      <if test="record.pageType != null">
-        page_type = #{record.pageType,jdbcType=TINYINT},
-      </if>
       <if test="record.sort != null">
         sort = #{record.sort,jdbcType=INTEGER},
       </if>
@@ -232,7 +221,6 @@
       question_id = #{record.questionId,jdbcType=BIGINT},
       content = #{record.content,jdbcType=VARCHAR},
       show_type = #{record.showType,jdbcType=TINYINT},
-      page_type = #{record.pageType,jdbcType=TINYINT},
       sort = #{record.sort,jdbcType=INTEGER},
       operator = #{record.operator,jdbcType=BIGINT},
       created_at = #{record.createdAt,jdbcType=TIMESTAMP},
@@ -254,9 +242,6 @@
       <if test="showType != null">
         show_type = #{showType,jdbcType=TINYINT},
       </if>
-      <if test="pageType != null">
-        page_type = #{pageType,jdbcType=TINYINT},
-      </if>
       <if test="sort != null">
         sort = #{sort,jdbcType=INTEGER},
       </if>
@@ -280,7 +265,6 @@
     set question_id = #{questionId,jdbcType=BIGINT},
       content = #{content,jdbcType=VARCHAR},
       show_type = #{showType,jdbcType=TINYINT},
-      page_type = #{pageType,jdbcType=TINYINT},
       sort = #{sort,jdbcType=INTEGER},
       operator = #{operator,jdbcType=BIGINT},
       created_at = #{createdAt,jdbcType=TIMESTAMP},

src/main/resources/mapper_raw/TrainRuleScoreMapper.xml

@@ -3,7 +3,7 @@
 <mapper namespace="com.ccsens.braintraining.persist.mapper.TrainRuleScoreMapper">
   <resultMap id="BaseResultMap" type="com.ccsens.braintraining.bean.po.TrainRuleScore">
     <id column="id" jdbcType="BIGINT" property="id" />
-    <result column="code" jdbcType="VARCHAR" property="code" />
+    <result column="active_id" jdbcType="BIGINT" property="activeId" />
     <result column="classify_id" jdbcType="BIGINT" property="classifyId" />
     <result column="calculate_type" jdbcType="TINYINT" property="calculateType" />
     <result column="calculate_param" jdbcType="VARCHAR" property="calculateParam" />
@@ -71,8 +71,8 @@
     </where>
   </sql>
   <sql id="Base_Column_List">
-    id, code, classify_id, calculate_type, calculate_param, operator, created_at, updated_at, 
-    rec_status
+    id, active_id, classify_id, calculate_type, calculate_param, operator, created_at, 
+    updated_at, rec_status
   </sql>
   <select id="selectByExample" parameterType="com.ccsens.braintraining.bean.po.TrainRuleScoreExample" resultMap="BaseResultMap">
     select
@@ -105,11 +105,11 @@
     </if>
   </delete>
   <insert id="insert" parameterType="com.ccsens.braintraining.bean.po.TrainRuleScore">
-    insert into t_train_rule_score (id, code, classify_id, 
+    insert into t_train_rule_score (id, active_id, classify_id, 
       calculate_type, calculate_param, operator, 
       created_at, updated_at, rec_status
       )
-    values (#{id,jdbcType=BIGINT}, #{code,jdbcType=VARCHAR}, #{classifyId,jdbcType=BIGINT}, 
+    values (#{id,jdbcType=BIGINT}, #{activeId,jdbcType=BIGINT}, #{classifyId,jdbcType=BIGINT}, 
       #{calculateType,jdbcType=TINYINT}, #{calculateParam,jdbcType=VARCHAR}, #{operator,jdbcType=BIGINT}, 
       #{createdAt,jdbcType=TIMESTAMP}, #{updatedAt,jdbcType=TIMESTAMP}, #{recStatus,jdbcType=TINYINT}
       )
@@ -120,8 +120,8 @@
       <if test="id != null">
         id,
       </if>
-      <if test="code != null">
-        code,
+      <if test="activeId != null">
+        active_id,
       </if>
       <if test="classifyId != null">
         classify_id,
@@ -149,8 +149,8 @@
       <if test="id != null">
         #{id,jdbcType=BIGINT},
       </if>
-      <if test="code != null">
-        #{code,jdbcType=VARCHAR},
+      <if test="activeId != null">
+        #{activeId,jdbcType=BIGINT},
       </if>
       <if test="classifyId != null">
         #{classifyId,jdbcType=BIGINT},
@@ -187,8 +187,8 @@
       <if test="record.id != null">
         id = #{record.id,jdbcType=BIGINT},
       </if>
-      <if test="record.code != null">
-        code = #{record.code,jdbcType=VARCHAR},
+      <if test="record.activeId != null">
+        active_id = #{record.activeId,jdbcType=BIGINT},
       </if>
       <if test="record.classifyId != null">
         classify_id = #{record.classifyId,jdbcType=BIGINT},
@@ -219,7 +219,7 @@
   <update id="updateByExample" parameterType="map">
     update t_train_rule_score
     set id = #{record.id,jdbcType=BIGINT},
-      code = #{record.code,jdbcType=VARCHAR},
+      active_id = #{record.activeId,jdbcType=BIGINT},
       classify_id = #{record.classifyId,jdbcType=BIGINT},
       calculate_type = #{record.calculateType,jdbcType=TINYINT},
       calculate_param = #{record.calculateParam,jdbcType=VARCHAR},
@@ -234,8 +234,8 @@
   <update id="updateByPrimaryKeySelective" parameterType="com.ccsens.braintraining.bean.po.TrainRuleScore">
     update t_train_rule_score
     <set>
-      <if test="code != null">
-        code = #{code,jdbcType=VARCHAR},
+      <if test="activeId != null">
+        active_id = #{activeId,jdbcType=BIGINT},
       </if>
       <if test="classifyId != null">
         classify_id = #{classifyId,jdbcType=BIGINT},
@@ -263,7 +263,7 @@
   </update>
   <update id="updateByPrimaryKey" parameterType="com.ccsens.braintraining.bean.po.TrainRuleScore">
     update t_train_rule_score
-    set code = #{code,jdbcType=VARCHAR},
+    set active_id = #{activeId,jdbcType=BIGINT},
       classify_id = #{classifyId,jdbcType=BIGINT},
       calculate_type = #{calculateType,jdbcType=TINYINT},
       calculate_param = #{calculateParam,jdbcType=VARCHAR},