数字营销实训算法第二轮修改

src/main/java/com/sztzjy/marketing/config/Constant.java

@@ -25,6 +25,10 @@ public class Constant {
     public static final String INPUT_TYPE_TEACHER= "0";
     public static final String INPUT_TYPE_BUILT_IN= "1";
 
+    public static final String LINEAR_REGRESSION="线性回归";
+
+    public static final String LOGISTIC_REGRESSION="逻辑回归";
+
 
 
 

src/main/java/com/sztzjy/marketing/controller/stu/StuDigitalMarketingModelController.java

@@ -1,6 +1,8 @@
 package com.sztzjy.marketing.controller.stu;
 
+import cn.hutool.core.util.IdUtil;
 import com.sztzjy.marketing.annotation.AnonymousAccess;
+import com.sztzjy.marketing.config.Constant;
 import com.sztzjy.marketing.config.exception.handler.DigitalEconomyxception;
 import com.sztzjy.marketing.entity.StuSpendingLevel;
 import com.sztzjy.marketing.entity.StuTrainingOperateStepExample;
@@ -25,6 +27,7 @@ import org.springframework.web.bind.annotation.*;
 import org.springframework.web.multipart.MultipartFile;
 
 import javax.annotation.Resource;
+import javax.servlet.http.HttpServletResponse;
 import java.io.IOException;
 import java.math.BigDecimal;
 import java.text.DecimalFormat;
@@ -194,7 +197,7 @@ public class StuDigitalMarketingModelController {
         Apriori.iteration(Apriori.C,Apriori.L,support);
 
         //根据最终的关联集，根据公式计算出各个关联事件
-        List<String> connection = Apriori.connection(confidence);
+        List<AssociationRulesDTO> connection = Apriori.connection(confidence);
 
 
         return new ResultEntity(HttpStatus.OK,"成功",connection);
@@ -212,14 +215,11 @@ public class StuDigitalMarketingModelController {
         LinearRegression regression=new LinearRegression();
         regression.fit(x,y);
 
-        double[] slopes = regression.getSlopes();
 
         RAnalysisDTO rAnalysisDTO=new RAnalysisDTO();
         rAnalysisDTO.setIntercept(regression.getIntercept());
-        for (int i = 0; i < slopes.length; i++) {
-            rAnalysisDTO.setSlopes(slopes[i]);
-        }
-
+        rAnalysisDTO.setSlopes(regression.getSlopes());
+        rAnalysisDTO.setType("线性回归");
 
         return new ResultEntity(HttpStatus.OK,"成功",rAnalysisDTO);
     }
@@ -240,22 +240,51 @@ public class StuDigitalMarketingModelController {
         RAnalysisDTO rAnalysisDTO=new RAnalysisDTO();
 
         rAnalysisDTO.setIntercept(Double.parseDouble(df.format(model.getIntercept())));
-        rAnalysisDTO.setSlopes(Double.parseDouble(df.format(model.getCoefficient())));
+        rAnalysisDTO.setSlope(Double.parseDouble(df.format(model.getCoefficient())));
+        rAnalysisDTO.setType("逻辑回归");
 
         return new ResultEntity(HttpStatus.OK,"成功",rAnalysisDTO);
     }
 
 
+    @ApiOperation("线性回归/逻辑回归--预测")
+    @PostMapping("/prediction")
+    @AnonymousAccess
+    public ResultEntity prediction(@RequestBody LogisticPredictDTO logisticPredictDTO) {
+
+        DecimalFormat df = new DecimalFormat("#.0");
+        if(logisticPredictDTO.getType().equals(Constant.LINEAR_REGRESSION)){
+            // 创建线性回归模型
+            LinearRegression regression=new LinearRegression();
+            double predict = regression.predict(logisticPredictDTO.getRaX(), logisticPredictDTO.getIntercept(), logisticPredictDTO.getSlopes());
+            return new ResultEntity(HttpStatus.OK,"成功",df.format(predict));
+
+        }else {
+            // 创建一个逻辑回归模型实例,0.1学习率
+            LogisticRegression model = new LogisticRegression(0.1);
+            double predict = model.predict(logisticPredictDTO.getLX(), logisticPredictDTO.getSlope(), logisticPredictDTO.getIntercept());//预测
+            return new ResultEntity(HttpStatus.OK,"成功",df.format(predict));
+        }
+
+    }
+
+
+
     @ApiOperation("情感分析/文本挖掘")
     @PostMapping("/emotionalAnalysis")
     @AnonymousAccess
-    public ResultEntity emotionalAnalysis(@ApiParam("用户ID") String userId,
-                                          @ApiParam("模型类别") String modelType,
-                                          @ApiParam("输入内容") String content) throws IOException {
-
-        return modelService.emotionalAnalysis(userId,modelType,content);
+    public ResultEntity emotionalAnalysis(@RequestBody EmotionalAnalysisDto emotionalAnalysisDto) throws IOException {
+        String id = emotionalAnalysisDto.getId();
+        String modelType = emotionalAnalysisDto.getModelType();
+        String content = emotionalAnalysisDto.getContent();
+        String userId = emotionalAnalysisDto.getUserId();
+        return modelService.emotionalAnalysis(userId,modelType,content,id);
     }
 
+
+
+
+
     @ApiOperation("批量导入")
     @PostMapping("/batchImport")
     @AnonymousAccess

src/main/java/com/sztzjy/marketing/controller/stu/StuOnAnalysisController.java

@@ -0,0 +1,229 @@
+package com.sztzjy.marketing.controller.stu;
+
+import cn.hutool.core.util.IdUtil;
+import com.sztzjy.marketing.annotation.AnonymousAccess;
+import com.sztzjy.marketing.config.Constant;
+import com.sztzjy.marketing.entity.dto.*;
+import com.sztzjy.marketing.util.excel.FilePortUtil;
+import io.swagger.annotations.Api;
+import io.swagger.annotations.ApiOperation;
+import org.apache.poi.ss.usermodel.Cell;
+import org.apache.poi.ss.usermodel.Row;
+import org.apache.poi.ss.usermodel.Sheet;
+import org.apache.poi.ss.usermodel.Workbook;
+import org.apache.poi.xssf.usermodel.XSSFWorkbook;
+import org.checkerframework.checker.units.qual.C;
+import org.springframework.web.bind.annotation.*;
+
+import javax.servlet.http.HttpServletResponse;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+
+/**
+ * @author tz
+ * @date 2024/8/19 10:14
+ */
+@Api(tags = "分析结果下载")
+@RequestMapping("api/analysis")
+@RestController
+public class StuOnAnalysisController {
+
+    @ApiOperation("描述性统计表格下载")
+    @PostMapping("/dSExport")
+    @AnonymousAccess
+    public void dSExport(HttpServletResponse response, @RequestBody List<DescriptiveStatisticsDTO> dtoList) {
+        //导出的表名
+        String title = IdUtil.simpleUUID();
+
+
+//        List<String> list=new ArrayList<>();
+//        list.add(""); //表头第一个元素为空
+//        for (DescriptiveStatisticsDTO dto: dtoList) {
+//            list.add(dto.getStatistic());
+//        }
+//        //表中第一行表头字段
+//        String[] headers=list.toArray(new String[list.size()]); // 使用 list.toArray() 转换为 String数组
+
+        String[] headers={"", "平均数", "中位数", "众数", "标准差", "方差", "标准误差",
+                "峰度", "偏度", "最大值", "最小值", "求和", "观测数"};
+
+
+        List<DescriptiveStatistics> descriptiveStatistics=new ArrayList<>();
+        //实际数据结果集
+        for (DescriptiveStatisticsDTO dto: dtoList) {
+            descriptiveStatistics.add(dto.getStatistics());
+        }
+
+
+
+        //具体需要写入excel需要哪些字段，这些字段取自UserReward类，也就是上面的实际数据结果集的泛型
+        List<String> listColumn = Arrays.asList("field", "average", "median", "mode", "standardDeviation", "variance", "standardError",
+                "kurtosis", "skewness", "max", "min", "summation", "observations");
+        try {
+            FilePortUtil.exportExcel(response, title, headers, descriptiveStatistics, listColumn);
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+
+    @ApiOperation("聚类分析表格下载")
+    @PostMapping("/cAMExport")
+    @AnonymousAccess
+    public void cAMExport(HttpServletResponse response,@RequestBody List<List<Object>> data ) {
+//        Workbook workbook = new XSSFWorkbook();
+//        Sheet sheet = workbook.createSheet("Sheet1");
+//
+//        for (int rowIndex = 0; rowIndex < data.size(); ++rowIndex) {
+//            Row row = sheet.createRow(rowIndex);
+//            for (int colIndex = 0; colIndex < data.get(rowIndex).size(); ++colIndex) {
+//                Object value = data.get(rowIndex).get(colIndex);
+//                if (value == null) {
+//                    // 使用空字符串或其他显示文本代替 null 值
+//                    Cell cell = row.createCell(colIndex);
+//                    cell.setCellValue("");
+//                } else {
+//                    Cell cell = row.createCell(colIndex);
+//                    cell.setCellValue(value.toString());
+//                }
+//            }
+//        }
+//
+//        try (FileOutputStream outputStream = new FileOutputStream("output.xlsx")) {
+//            workbook.write(outputStream);
+//        } catch (IOException e) {
+//            org.slf4j.Logger logger = org.slf4j.LoggerFactory.getLogger(cAMExport.class);
+//            logger.error("An error occurred while writing the Excel file.", e);
+//        }
+        //导出的表名
+        String title = IdUtil.simpleUUID();
+
+
+        //取到表头
+        List<String> list=new ArrayList<>();
+        for (int i = 0; i < data.size(); i++) {
+            for (int j = 0; j < data.get(i).size(); j++) {
+                list.add("field"+j);
+            }
+
+        }
+
+        //表中第一行表头字段
+        String[] headers=list.toArray(new String[list.size()]); // 使用 list.toArray() 转换为 String数组
+
+
+
+
+
+
+        //具体需要写入excel需要哪些字段，这些字段取自UserReward类，也就是上面的实际数据结果集的泛型
+        List<String> listColumn=new ArrayList<>();
+
+        //实际数据结果集
+
+
+
+
+
+
+        try {
+            FilePortUtil.exportExcel(response, title, headers, data, listColumn);
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+    @ApiOperation("关联规则挖掘表格下载")
+    @PostMapping("/aRMExport")
+    @AnonymousAccess
+    public void aRMExport(HttpServletResponse response, @RequestBody List<AssociationRulesDTO>  dtoList) {
+        //导出的表名
+        String title = IdUtil.simpleUUID();
+
+        //表中第一行表头字段
+        String[] headers={"关联", "被关联", "置信度"};
+
+
+
+        //实际数据结果集
+        List<AssociationRules> list=new ArrayList<>();
+
+        for (int i = 0; i < dtoList.size(); i++) {
+
+            // 使用String.join()方法将元素以逗号和空格分隔
+            String correlation = String.join(", ", dtoList.get(i).getCorrelation());
+
+            String associated= String.join(", ", dtoList.get(i).getAssociated());
+
+
+            AssociationRules associationRules=new AssociationRules();
+
+            associationRules.setCorrelation(correlation);
+            associationRules.setAssociated(associated);
+            associationRules.setConfidenceLevel(dtoList.get(i).getConfidenceLevel());
+
+            list.add(associationRules);
+        }
+
+
+
+
+
+
+
+        //具体需要写入excel需要哪些字段，这些字段取自UserReward类，也就是上面的实际数据结果集的泛型
+        List<String> listColumn = Arrays.asList("correlation", "associated", "confidenceLevel");
+        try {
+            FilePortUtil.exportExcel(response, title, headers, list, listColumn);
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+
+
+    @ApiOperation("回归分析表格下载")
+    @PostMapping("/rAMExport")
+    @AnonymousAccess
+    public void rAMExport(HttpServletResponse response, @RequestBody RAnalysisExportDTO  rAnalysisExportDTO) {
+        //导出的表名
+        String title = IdUtil.simpleUUID();
+
+        List<String> list=new ArrayList<>();
+        List<String> listColumn=new ArrayList<>();
+        list.add("回归系数值");
+
+
+        if(rAnalysisExportDTO.getType().equals(Constant.LINEAR_REGRESSION)){
+
+            list.add("线性回归常数项值");
+            //具体需要写入excel需要哪些字段，这些字段取自UserReward类，也就是上面的实际数据结果集的泛型
+            listColumn = Arrays.asList("intercept", "slopes", "type","prediction");
+
+
+        }else {
+            list.add("逻辑回归常数项值");
+            //具体需要写入excel需要哪些字段，这些字段取自UserReward类，也就是上面的实际数据结果集的泛型
+            listColumn = Arrays.asList("intercept", "slope", "type","prediction");
+        }
+        list.add("回归类型");
+        list.add("预测值");
+
+        //表中第一行表头字段
+        String[] headers=list.toArray(new String[list.size()]); // 使用 list.toArray() 转换为 String数组
+
+
+        //实际数据结果集
+        List<RAnalysisExportDTO> rAnalysisExportDTOS=new ArrayList<>();
+        rAnalysisExportDTOS.add(rAnalysisExportDTO);
+
+
+        try {
+            FilePortUtil.exportExcel(response, title, headers, rAnalysisExportDTOS, listColumn);
+        } catch (Exception e) {
+            e.printStackTrace();
+        }
+    }
+}

src/main/java/com/sztzjy/marketing/entity/StuUserAttribute.java

@@ -2,7 +2,6 @@ package com.sztzjy.marketing.entity;
 
 import java.util.Date;
 
-import io.swagger.annotations.ApiModel;
 import io.swagger.annotations.ApiModelProperty;
 /**
  * 用户属性表
@@ -10,7 +9,6 @@ import io.swagger.annotations.ApiModelProperty;
  * @author whb
  * stu_user_attribute
  */
-@ApiModel("用户属性表")
 public class StuUserAttribute {
     @ApiModelProperty("id")
     private Integer id;
@@ -57,6 +55,9 @@ public class StuUserAttribute {
     @ApiModelProperty("所在地")
     private String location;
 
+    @ApiModelProperty("文本")
+    private String text;
+
     public Integer getId() {
         return id;
     }
@@ -176,4 +177,12 @@ public class StuUserAttribute {
     public void setLocation(String location) {
         this.location = location == null ? null : location.trim();
     }
+
+    public String getText() {
+        return text;
+    }
+
+    public void setText(String text) {
+        this.text = text == null ? null : text.trim();
+    }
 }

src/main/java/com/sztzjy/marketing/entity/StuUserBehavior.java

@@ -47,7 +47,7 @@ public class StuUserBehavior {
     private String goodsSubcategories;
 
     @ApiModelProperty("用户行为类型")
-    private String userBehaviorType;
+    private Integer userBehaviorType;
 
     @ApiModelProperty("行为日期")
     private Date behaviorDate;
@@ -58,6 +58,9 @@ public class StuUserBehavior {
     @ApiModelProperty("更新时间")
     private Date updateTime;
 
+    @ApiModelProperty("文本")
+    private String text;
+
     public Integer getId() {
         return id;
     }
@@ -154,12 +157,12 @@ public class StuUserBehavior {
         this.goodsSubcategories = goodsSubcategories == null ? null : goodsSubcategories.trim();
     }
 
-    public String getUserBehaviorType() {
+    public Integer getUserBehaviorType() {
         return userBehaviorType;
     }
 
-    public void setUserBehaviorType(String userBehaviorType) {
-        this.userBehaviorType = userBehaviorType == null ? null : userBehaviorType.trim();
+    public void setUserBehaviorType(Integer userBehaviorType) {
+        this.userBehaviorType = userBehaviorType;
     }
 
     public Date getBehaviorDate() {
@@ -185,4 +188,12 @@ public class StuUserBehavior {
     public void setUpdateTime(Date updateTime) {
         this.updateTime = updateTime;
     }
+
+    public String getText() {
+        return text;
+    }
+
+    public void setText(String text) {
+        this.text = text == null ? null : text.trim();
+    }
 }

src/main/java/com/sztzjy/marketing/entity/StuUserBehaviorExample.java

@@ -945,62 +945,52 @@ public class StuUserBehaviorExample {
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeEqualTo(String value) {
+        public Criteria andUserBehaviorTypeEqualTo(Integer value) {
             addCriterion("user_behavior_type =", value, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeNotEqualTo(String value) {
+        public Criteria andUserBehaviorTypeNotEqualTo(Integer value) {
             addCriterion("user_behavior_type <>", value, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeGreaterThan(String value) {
+        public Criteria andUserBehaviorTypeGreaterThan(Integer value) {
             addCriterion("user_behavior_type >", value, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeGreaterThanOrEqualTo(String value) {
+        public Criteria andUserBehaviorTypeGreaterThanOrEqualTo(Integer value) {
             addCriterion("user_behavior_type >=", value, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeLessThan(String value) {
+        public Criteria andUserBehaviorTypeLessThan(Integer value) {
             addCriterion("user_behavior_type <", value, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeLessThanOrEqualTo(String value) {
+        public Criteria andUserBehaviorTypeLessThanOrEqualTo(Integer value) {
             addCriterion("user_behavior_type <=", value, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeLike(String value) {
-            addCriterion("user_behavior_type like", value, "userBehaviorType");
-            return (Criteria) this;
-        }
-
-        public Criteria andUserBehaviorTypeNotLike(String value) {
-            addCriterion("user_behavior_type not like", value, "userBehaviorType");
-            return (Criteria) this;
-        }
-
-        public Criteria andUserBehaviorTypeIn(List<String> values) {
+        public Criteria andUserBehaviorTypeIn(List<Integer> values) {
             addCriterion("user_behavior_type in", values, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeNotIn(List<String> values) {
+        public Criteria andUserBehaviorTypeNotIn(List<Integer> values) {
             addCriterion("user_behavior_type not in", values, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeBetween(String value1, String value2) {
+        public Criteria andUserBehaviorTypeBetween(Integer value1, Integer value2) {
             addCriterion("user_behavior_type between", value1, value2, "userBehaviorType");
             return (Criteria) this;
         }
 
-        public Criteria andUserBehaviorTypeNotBetween(String value1, String value2) {
+        public Criteria andUserBehaviorTypeNotBetween(Integer value1, Integer value2) {
             addCriterion("user_behavior_type not between", value1, value2, "userBehaviorType");
             return (Criteria) this;
         }

src/main/java/com/sztzjy/marketing/entity/StuUserConsumptionAbility.java

@@ -3,7 +3,6 @@ package com.sztzjy.marketing.entity;
 import java.math.BigDecimal;
 import java.util.Date;
 
-import io.swagger.annotations.ApiModel;
 import io.swagger.annotations.ApiModelProperty;
 /**
  * 用户消费能力表
@@ -11,8 +10,6 @@ import io.swagger.annotations.ApiModelProperty;
  * @author whb
  * stu_user_consumption_ability
  */
-
-@ApiModel("用户消费能力表")
 public class StuUserConsumptionAbility {
     @ApiModelProperty("id")
     private Integer id;
@@ -68,6 +65,9 @@ public class StuUserConsumptionAbility {
     @ApiModelProperty("更新时间")
     private Date updateTime;
 
+    @ApiModelProperty("文本")
+    private String text;
+
     public Integer getId() {
         return id;
     }
@@ -211,4 +211,12 @@ public class StuUserConsumptionAbility {
     public void setUpdateTime(Date updateTime) {
         this.updateTime = updateTime;
     }
+
+    public String getText() {
+        return text;
+    }
+
+    public void setText(String text) {
+        this.text = text == null ? null : text.trim();
+    }
 }

src/main/java/com/sztzjy/marketing/entity/StuUserLoginActive.java

@@ -55,6 +55,9 @@ public class StuUserLoginActive {
     @ApiModelProperty("更新时间")
     private Date updateTime;
 
+    @ApiModelProperty("文本")
+    private String text;
+
     public Integer getId() {
         return id;
     }
@@ -174,4 +177,12 @@ public class StuUserLoginActive {
     public void setUpdateTime(Date updateTime) {
         this.updateTime = updateTime;
     }
+
+    public String getText() {
+        return text;
+    }
+
+    public void setText(String text) {
+        this.text = text == null ? null : text.trim();
+    }
 }

src/main/java/com/sztzjy/marketing/entity/dto/AssociationRules.java

@@ -0,0 +1,22 @@
+package com.sztzjy.marketing.entity.dto;
+
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+import java.util.List;
+
+/**
+ * @author tz
+ * @date 2024/8/19 14:38
+ */
+@Data
+public class AssociationRules {
+    @ApiModelProperty("关联")
+    private String correlation;
+
+    @ApiModelProperty("被关联")
+    private String associated;
+
+    @ApiModelProperty("置信度")
+    private double confidenceLevel;
+}

src/main/java/com/sztzjy/marketing/entity/dto/AssociationRulesDTO.java

@@ -19,4 +19,7 @@ public class AssociationRulesDTO {
 
     @ApiModelProperty("置信度")
     private double confidenceLevel;
+
+    @ApiModelProperty("规则")
+    private String rule;
 }

src/main/java/com/sztzjy/marketing/entity/dto/DSExportDTO.java

@@ -0,0 +1,19 @@
+package com.sztzjy.marketing.entity.dto;
+
+import io.swagger.annotations.Api;
+import io.swagger.annotations.ApiModelProperty;
+import io.swagger.annotations.ApiParam;
+import lombok.Data;
+
+/**
+ * @author tz
+ * @date 2024/8/19 10:33
+ */
+@Data
+@Api(tags = "描述性统计下载表格数据")
+public class DSExportDTO extends DescriptiveStatistics{
+
+    @ApiModelProperty("字段名")
+    private String field;
+
+}

src/main/java/com/sztzjy/marketing/entity/dto/DescriptiveStatistics.java

@@ -46,4 +46,7 @@ public class DescriptiveStatistics {
 
     @ApiModelProperty("观测数")
     private Integer observations;
+
+    @ApiModelProperty("字段名")
+    private String field;
 }

src/main/java/com/sztzjy/marketing/entity/dto/DescriptiveStatisticsDTO.java

@@ -1,5 +1,6 @@
 package com.sztzjy.marketing.entity.dto;
 
+import io.swagger.annotations.ApiModelProperty;
 import lombok.Data;
 
 /**
@@ -11,4 +12,5 @@ public class DescriptiveStatisticsDTO {
     private String field;
 
     private DescriptiveStatistics statistics;
+
 }

src/main/java/com/sztzjy/marketing/entity/dto/EmotionalAnalysisDto.java

@@ -0,0 +1,22 @@
+package com.sztzjy.marketing.entity.dto;
+
+import io.swagger.annotations.ApiParam;
+import lombok.Data;
+import org.springframework.web.bind.annotation.RequestParam;
+
+import javax.persistence.Column;
+import javax.xml.bind.annotation.XmlElement;
+
+/**
+ * @author tz
+ * @date 2024/8/19 16:09
+ */
+@Data
+public class EmotionalAnalysisDto {
+
+    private String userId;
+    private String modelType;
+    private String content;
+    @XmlElement(name = "optionalField", required = false)
+    private String id;
+}

src/main/java/com/sztzjy/marketing/entity/dto/LogisticPredictDTO.java

@@ -0,0 +1,18 @@
+package com.sztzjy.marketing.entity.dto;
+
+import lombok.Data;
+import lombok.EqualsAndHashCode;
+import org.ujmp.core.util.R;
+
+/**
+ * @author tz
+ * @date 2024/8/19 9:38
+ */
+@EqualsAndHashCode(callSuper = true)
+@Data
+public class LogisticPredictDTO extends RAnalysisDTO {
+    private double[] raX;
+
+    private double lX;
+
+}

src/main/java/com/sztzjy/marketing/entity/dto/RAnalysisDTO.java

@@ -1,5 +1,6 @@
 package com.sztzjy.marketing.entity.dto;
 
+import io.swagger.annotations.ApiModelProperty;
 import lombok.Data;
 
 /**
@@ -8,6 +9,12 @@ import lombok.Data;
  */
 @Data
 public class RAnalysisDTO {
+    @ApiModelProperty("回归系数值")
     private double intercept;
-    private double slopes;
+    @ApiModelProperty("线性回归常数项值")
+    private double[] slopes;
+    @ApiModelProperty("逻辑回归常数项值")
+    private double slope;
+    @ApiModelProperty("线性回归/逻辑回归")
+    private String type;
 }

src/main/java/com/sztzjy/marketing/entity/dto/RAnalysisExportDTO.java

@@ -0,0 +1,16 @@
+package com.sztzjy.marketing.entity.dto;
+
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+import lombok.EqualsAndHashCode;
+
+/**
+ * @author tz
+ * @date 2024/8/19 14:55
+ */
+@EqualsAndHashCode(callSuper = true)
+@Data
+public class RAnalysisExportDTO extends RAnalysisDTO{
+    @ApiModelProperty("预测值")
+    private double prediction;
+}

src/main/java/com/sztzjy/marketing/entity/dto/cAMExport.java

@@ -0,0 +1,25 @@
+package com.sztzjy.marketing.entity.dto;
+
+import lombok.Data;
+
+import java.util.List;
+
+/**
+ * @author tz
+ * @date 2024/8/19 11:38
+ */
+@Data
+public class cAMExport {
+    private double fieldOne;
+    private double fieldTow;
+    private double fieldThree;
+    private double fieldFour;
+    private double fieldFive;
+    private double fieldSix;
+    private double fieldSeven;
+    private double fieldEight;
+    private double fieldNine;
+    private double fieldTen;
+
+    private String type;
+}

src/main/java/com/sztzjy/marketing/entity/dto/cAMExportDTO.java

@@ -0,0 +1,17 @@
+package com.sztzjy.marketing.entity.dto;
+
+import lombok.Data;
+
+import java.util.List;
+
+/**
+ * @author tz
+ * @date 2024/8/19 11:12
+ */
+@Data
+public class cAMExportDTO {
+    private String field;
+
+    private List<cAMExport> cAMExports;
+
+}

src/main/java/com/sztzjy/marketing/mapper/StuUserAttributeMapper.java

@@ -3,10 +3,10 @@ package com.sztzjy.marketing.mapper;
 import com.sztzjy.marketing.entity.StuUserAttribute;
 import com.sztzjy.marketing.entity.StuUserAttributeExample;
 import java.util.List;
-import java.util.Map;
 
+import org.apache.ibatis.annotations.Mapper;
 import org.apache.ibatis.annotations.Param;
-
+@Mapper
 public interface StuUserAttributeMapper {
     long countByExample(StuUserAttributeExample example);
 
@@ -18,17 +18,21 @@ public interface StuUserAttributeMapper {
 
     int insertSelective(StuUserAttribute record);
 
+    List<StuUserAttribute> selectByExampleWithBLOBs(StuUserAttributeExample example);
+
     List<StuUserAttribute> selectByExample(StuUserAttributeExample example);
 
     StuUserAttribute selectByPrimaryKey(Integer id);
 
     int updateByExampleSelective(@Param("record") StuUserAttribute record, @Param("example") StuUserAttributeExample example);
 
+    int updateByExampleWithBLOBs(@Param("record") StuUserAttribute record, @Param("example") StuUserAttributeExample example);
+
     int updateByExample(@Param("record") StuUserAttribute record, @Param("example") StuUserAttributeExample example);
 
     int updateByPrimaryKeySelective(StuUserAttribute record);
 
-    int updateByPrimaryKey(StuUserAttribute record);
+    int updateByPrimaryKeyWithBLOBs(StuUserAttribute record);
 
-    List<Map<String,StuUserAttribute>> selectByFields(List<String> fieldList, String table);
+    int updateByPrimaryKey(StuUserAttribute record);
 }

src/main/java/com/sztzjy/marketing/mapper/StuUserBehaviorMapper.java

@@ -3,8 +3,10 @@ package com.sztzjy.marketing.mapper;
 import com.sztzjy.marketing.entity.StuUserBehavior;
 import com.sztzjy.marketing.entity.StuUserBehaviorExample;
 import java.util.List;
-import org.apache.ibatis.annotations.Param;
 
+import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
+@Mapper
 public interface StuUserBehaviorMapper {
     long countByExample(StuUserBehaviorExample example);
 
@@ -16,15 +18,21 @@ public interface StuUserBehaviorMapper {
 
     int insertSelective(StuUserBehavior record);
 
+    List<StuUserBehavior> selectByExampleWithBLOBs(StuUserBehaviorExample example);
+
     List<StuUserBehavior> selectByExample(StuUserBehaviorExample example);
 
     StuUserBehavior selectByPrimaryKey(Integer id);
 
     int updateByExampleSelective(@Param("record") StuUserBehavior record, @Param("example") StuUserBehaviorExample example);
 
+    int updateByExampleWithBLOBs(@Param("record") StuUserBehavior record, @Param("example") StuUserBehaviorExample example);
+
     int updateByExample(@Param("record") StuUserBehavior record, @Param("example") StuUserBehaviorExample example);
 
     int updateByPrimaryKeySelective(StuUserBehavior record);
 
+    int updateByPrimaryKeyWithBLOBs(StuUserBehavior record);
+
     int updateByPrimaryKey(StuUserBehavior record);
 }

src/main/java/com/sztzjy/marketing/mapper/StuUserConsumptionAbilityMapper.java

@@ -3,8 +3,10 @@ package com.sztzjy.marketing.mapper;
 import com.sztzjy.marketing.entity.StuUserConsumptionAbility;
 import com.sztzjy.marketing.entity.StuUserConsumptionAbilityExample;
 import java.util.List;
-import org.apache.ibatis.annotations.Param;
 
+import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
+@Mapper
 public interface StuUserConsumptionAbilityMapper {
     long countByExample(StuUserConsumptionAbilityExample example);
 
@@ -16,17 +18,21 @@ public interface StuUserConsumptionAbilityMapper {
 
     int insertSelective(StuUserConsumptionAbility record);
 
+    List<StuUserConsumptionAbility> selectByExampleWithBLOBs(StuUserConsumptionAbilityExample example);
+
     List<StuUserConsumptionAbility> selectByExample(StuUserConsumptionAbilityExample example);
 
     StuUserConsumptionAbility selectByPrimaryKey(Integer id);
 
     int updateByExampleSelective(@Param("record") StuUserConsumptionAbility record, @Param("example") StuUserConsumptionAbilityExample example);
 
+    int updateByExampleWithBLOBs(@Param("record") StuUserConsumptionAbility record, @Param("example") StuUserConsumptionAbilityExample example);
+
     int updateByExample(@Param("record") StuUserConsumptionAbility record, @Param("example") StuUserConsumptionAbilityExample example);
 
     int updateByPrimaryKeySelective(StuUserConsumptionAbility record);
 
-    int updateByPrimaryKey(StuUserConsumptionAbility record);
+    int updateByPrimaryKeyWithBLOBs(StuUserConsumptionAbility record);
 
-    List<StuUserConsumptionAbility> selectByFields(List<String> fieldList, String table);
+    int updateByPrimaryKey(StuUserConsumptionAbility record);
 }

src/main/java/com/sztzjy/marketing/mapper/StuUserLoginActiveMapper.java

@@ -3,8 +3,10 @@ package com.sztzjy.marketing.mapper;
 import com.sztzjy.marketing.entity.StuUserLoginActive;
 import com.sztzjy.marketing.entity.StuUserLoginActiveExample;
 import java.util.List;
-import org.apache.ibatis.annotations.Param;
 
+import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
+@Mapper
 public interface StuUserLoginActiveMapper {
     long countByExample(StuUserLoginActiveExample example);
 
@@ -16,15 +18,21 @@ public interface StuUserLoginActiveMapper {
 
     int insertSelective(StuUserLoginActive record);
 
+    List<StuUserLoginActive> selectByExampleWithBLOBs(StuUserLoginActiveExample example);
+
     List<StuUserLoginActive> selectByExample(StuUserLoginActiveExample example);
 
     StuUserLoginActive selectByPrimaryKey(Integer id);
 
     int updateByExampleSelective(@Param("record") StuUserLoginActive record, @Param("example") StuUserLoginActiveExample example);
 
+    int updateByExampleWithBLOBs(@Param("record") StuUserLoginActive record, @Param("example") StuUserLoginActiveExample example);
+
     int updateByExample(@Param("record") StuUserLoginActive record, @Param("example") StuUserLoginActiveExample example);
 
     int updateByPrimaryKeySelective(StuUserLoginActive record);
 
+    int updateByPrimaryKeyWithBLOBs(StuUserLoginActive record);
+
     int updateByPrimaryKey(StuUserLoginActive record);
 }

src/main/java/com/sztzjy/marketing/service/StuDigitalMarketingModelService.java

@@ -15,7 +15,7 @@ import java.util.Map;
 public interface StuDigitalMarketingModelService {
     List<String> dropdownBox(String userId);
 
-    ResultEntity emotionalAnalysis(String userId, String modelType, String content) throws IOException;
+    ResultEntity emotionalAnalysis(String userId, String modelType, String content,String id) throws IOException;
 
 
     ResultEntity descriptiveStatistics(Map<String, List<Double>> map, List<String> statistic, String userId);

src/main/java/com/sztzjy/marketing/service/impl/StuDigitalMarketingModelServiceImpl.java

@@ -25,6 +25,8 @@ import java.time.LocalDateTime;
 import java.time.ZoneId;
 import java.time.ZonedDateTime;
 import java.util.*;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
 
 import static com.sztzjy.marketing.util.algorithm.BaiDuZhiNengYun.getAccessToken;
 
@@ -78,7 +80,7 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
     }
 
     @Override
-    public ResultEntity emotionalAnalysis(String userId, String modelType, String content) throws IOException {
+    public ResultEntity emotionalAnalysis(String userId, String modelType, String content,String id) throws IOException {
 
 
         MediaType mediaType = MediaType.parse("application/json");
@@ -122,8 +124,10 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
 
         if(modelType.equals(Constant.WORD_FREQUENCY)){ //词频分析
 
+            String string = this.filterPunctuation(content);
+
             // 使用 HanLP 分词
-            List<Term> terms = HanLP.segment(content);
+            List<Term> terms = HanLP.segment(string);
             // 创建词汇表
             Map<String, Integer> wordCount = new HashMap<>();
             // 统计词频
@@ -166,6 +170,18 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
         return null;
     }
 
+    // 过滤标点符号的函数
+    private String filterPunctuation(String originalContent) {
+        // 创建一个正则表达式，用于匹配所有标点符号
+        String punctuationPattern = "[\\p{Punct}]";
+        // 创建一个 Pattern 对象
+        Pattern pattern = Pattern.compile(punctuationPattern);
+        // 创建一个 Matcher 对象
+        Matcher matcher = pattern.matcher(originalContent);
+        // 使用 Matcher 的 replaceAll 方法替换所有匹配的标点符号为 ""
+        return matcher.replaceAll("");
+    }
+
     @Override
     public ResultEntity descriptiveStatistics(Map<String, List<Double>> map, List<String> statistic, String userId) {
 
@@ -179,36 +195,38 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
 
             DescriptiveStatistics statistics=new DescriptiveStatistics();
 
+            DecimalFormat df = new DecimalFormat("#.0");
+
             for (int i = 0; i < statistic.size(); i++) {
                 if(statistic.get(i).equals("平均数")){
                     double mean = statisticsUtil.getMean(map.get(key));
-                    statistics.setAverage(mean);
+                    statistics.setAverage(Double.parseDouble(df.format(mean)));
 
                 }
                 if(statistic.get(i).equals("中位数")){
                     double median = statisticsUtil.getMedian(map.get(key));
-                    statistics.setMedian(median);
+                    statistics.setMedian(Double.parseDouble(df.format(median)));
 
                 }
                 if(statistic.get(i).equals("众数")){
                     Double mode = statisticsUtil.getMode(map.get(key));
-                    statistics.setMode(mode);
+                    statistics.setMode(Double.parseDouble(df.format(mode)));
 
                 }
                 if(statistic.get(i).equals("标准差")){
                     double standardDeviation = statisticsUtil.getStandardDeviation(map.get(key));
-                    DecimalFormat df = new DecimalFormat("#.0");
+
                     statistics.setStandardDeviation(Double.parseDouble(df.format(standardDeviation)));
 
                 }
                 if(statistic.get(i).equals("方差")){
                     double variance = statisticsUtil.getVariance(map.get(key));
-                    statistics.setVariance(variance);
+                    statistics.setVariance(Double.parseDouble(df.format(variance)));
 
                 }
                 if(statistic.get(i).equals("标准误差")){
                     double standardError = statisticsUtil.getStandardError(map.get(key));
-                    statistics.setStandardError(standardError);
+                    statistics.setStandardError(Double.parseDouble(df.format(standardError)));
 
                 }
                 if(statistic.get(i).equals("峰度")){
@@ -217,7 +235,7 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
                     if(Double.isNaN(kurtosis)){
                         statistics.setKurtosis(0);
                     }else {
-                        statistics.setKurtosis(kurtosis);
+                        statistics.setKurtosis(Double.parseDouble(df.format(kurtosis)));
 
                     }
 
@@ -228,24 +246,24 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
                     if(Double.isNaN(skewness)){
                         statistics.setSkewness(0);
                     }else {
-                        statistics.setSkewness(skewness);
+                        statistics.setSkewness(Double.parseDouble(df.format(skewness)));
                     }
 
 
                 }
                 if(statistic.get(i).equals("最大值")){
                     double max = statisticsUtil.getMax(map.get(key));
-                    statistics.setMax(max);
+                    statistics.setMax(Double.parseDouble(df.format(max)));
 
                 }
                 if(statistic.get(i).equals("最小值")){
                     double min = statisticsUtil.getMin(map.get(key));
-                    statistics.setMin(min);
+                    statistics.setMin(Double.parseDouble(df.format(min)));
 
                 }
                 if(statistic.get(i).equals("求和")){
                     double sum = statisticsUtil.getSum(map.get(key));
-                    statistics.setSummation(sum);
+                    statistics.setSummation(Double.parseDouble(df.format(sum)));
 
                 }
                 if(statistic.get(i).equals("观测数")){
@@ -263,43 +281,51 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
 
     @Override
     public List<String> viewMetrics(String userId, String tableName,String algorithmName) {
+
+
         List<String> list=new ArrayList<>();
 
-        if(tableName.equals(Constant.YHSXB)){
+        if(algorithmName.equals("情感分析")){
+            list.add("text");
+        }else {
+            if(tableName.equals(Constant.YHSXB)){
 //           list=indicatorsMapper.getYHSXB();
-            list.add("id");
-            list.add("role_gender");
-            list.add("role_age");
-        }
-        if(tableName.equals(Constant.YHDLHYB)){
+                list.add("id");
+                list.add("role_gender");
+                list.add("role_age");
+            }
+            if(tableName.equals(Constant.YHDLHYB)){
 //            list=indicatorsMapper.getYHDLHYB();
-            list.add("id");
-            list.add("login_frequency");
-            list.add("login_duration");
+                list.add("id");
+                list.add("login_frequency");
+                list.add("login_duration");
 
-        }
-        if(tableName.equals(Constant.YHXFNLB)){
+            }
+            if(tableName.equals(Constant.YHXFNLB)){
 //            list=indicatorsMapper.getYHXFNLB();
                 if(algorithmName.equals("关联规则挖掘")){
                     list.add("consumer_goods");
                 } else {
-                list.add("id");
-                list.add("consumer_amount");
-                list.add("consumer_number");
-                list.add("consumer_past_seven_days_amount");
-                list.add("consumer_past_seven_days_number");
-            }
+                    list.add("id");
+                    list.add("consumer_amount");
+                    list.add("consumer_number");
+                    list.add("consumer_past_seven_days_amount");
+                    list.add("consumer_past_seven_days_number");
+                }
 
-        }
-        if(tableName.equals(Constant.YHPLB) || tableName.equals(Constant.YHXWB)){
+            }
+            if(tableName.equals(Constant.YHPLB) || tableName.equals(Constant.YHXWB)){
 //            list=indicatorsMapper.getYHPLB();
                 if(algorithmName.equals("关联规则挖掘")){
                     list.add("goods_name");
-            }else {
-                list.add("id");
-                list.add("user_behavior_type");
+                }else {
+                    list.add("id");
+                    list.add("user_behavior_type");
+                }
             }
         }
+
+
         return list;
     }
 
@@ -331,17 +357,17 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
 
 
 
-        //将日期类型转为时间戳返回
-        for (Map<String, Object> row : attributes) {
-            for (Map.Entry<String, Object> entry : row.entrySet()) {
-                if (entry.getValue() instanceof LocalDateTime) {
-                    LocalDateTime localDateTime = (LocalDateTime) entry.getValue();
-                    ZonedDateTime zonedDateTime = localDateTime.atZone(ZoneId.systemDefault());
-                    Instant instant = zonedDateTime.toInstant();
-                    entry.setValue(instant.toEpochMilli());
-                }
-            }
-        }
+//        //将日期类型转为时间戳返回
+//        for (Map<String, Object> row : attributes) {
+//            for (Map.Entry<String, Object> entry : row.entrySet()) {
+//                if (entry.getValue() instanceof LocalDateTime) {
+//                    LocalDateTime localDateTime = (LocalDateTime) entry.getValue();
+//                    ZonedDateTime zonedDateTime = localDateTime.atZone(ZoneId.systemDefault());
+//                    Instant instant = zonedDateTime.toInstant();
+//                    entry.setValue(instant.toEpochMilli());
+//                }
+//            }
+//        }
 
 
         return new ResultEntity(HttpStatus.OK,attributes);
@@ -349,11 +375,20 @@ public class StuDigitalMarketingModelServiceImpl implements StuDigitalMarketingM
 
     @Override
     public ResultEntity dataPreprocessing(String userId, String method, List<Map<String, Object>> mapList) {
+
+        if(mapList.isEmpty()){
+            return null;
+        }
+
         //数据去重
         Set<String> set = new HashSet<>();
         List<Map<String, Object>> deduplicatedDataList = new ArrayList<>();
 
+
         for (Map<String, Object> map : mapList) {
+            if(map.isEmpty()){
+                continue;
+            }
             String mapString = map.toString();
             if (!set.contains(mapString)) {
                 set.add(mapString);

src/main/java/com/sztzjy/marketing/util/algorithm/Apriori.java

@@ -212,7 +212,7 @@ public class Apriori {
 	/**
 	 * 根据最终的关联集，根据公式计算出各个关联事件
 	 */
-	public static List<String> connection(double min_confident) {
+	public static List<AssociationRulesDTO> connection(double min_confident) {
 
 		List<AssociationRulesDTO> list=new ArrayList<>();
 
@@ -249,6 +249,9 @@ public class Apriori {
 								associationRulesDTO.setAssociated(item_post);
 								associationRulesDTO.setConfidenceLevel(confident);
 
+								String string=item_pre + "==>" + item_post+"==>" + confident;
+								associationRulesDTO.setRule(string);
+
 								list.add(associationRulesDTO);
 
 
@@ -256,7 +259,7 @@ public class Apriori {
 								System.out.print(item_pre + "==>" + item_post );// 则是一个关联事件
 								System.out.println("==>" + confident);
 
-								String string=item_pre + "==>" + item_post+"==>" + confident;
+
 
 								lists.add(string);
 							}
@@ -266,7 +269,7 @@ public class Apriori {
 				}
 			}
 		}
-		return lists;
+		return list;
 	}
 	
 	public static void main(String[] args) {

src/main/java/com/sztzjy/marketing/util/algorithm/LinearRegression.java

@@ -53,11 +53,11 @@ public class LinearRegression {
     }
  
     // 预测方法
-    public double predict(double[] x) {
-        if (x.length != this.slopes.length) {
+    public double predict(double[] x,double intercept,double[] slopes) {
+        if (x.length != slopes.length) {
             throw new IllegalArgumentException("输入的x维度与模型不匹配");
         }
-        return this.intercept + dotProduct(this.slopes, x);
+        return intercept + dotProduct(slopes, x);
     }
  
     // 获取截距
@@ -70,29 +70,29 @@ public class LinearRegression {
         return this.slopes;
     }
  
-    public static void main(String[] args) {
-        // 示例数据
-        double[][] x = {{1, 19}, {1, 21}, {2, 20}, {2, 23}, {2, 31}};
-        double[] y = {15, 15, 16, 16, 17};
- 
-        // 创建线性回归模型
-        LinearRegression lr = new LinearRegression();
-        lr.fit(x, y);
-
-        DecimalFormat df = new DecimalFormat("#.0");
-
-        List<String> list=new ArrayList<>();
-        for (int i = 0; i < lr.getSlopes().length; i++) {
-            String format = df.format(lr.getSlopes()[i]);
-            list.add(format);
-        }
-        // 输出模型参数
-        System.out.println("常数项值: " + df.format(lr.getIntercept()));
-        System.out.println("第一个特征系数值: " + list.get(0));
- 
-        // 预测新数据
-        double[] newX = {2, 88};
-        double predictedY = lr.predict(newX);
-        System.out.println("输入x: " + java.util.Arrays.toString(newX) + "预测y=" + df.format(predictedY));
-    }
+//    public static void main(String[] args) {
+//        // 示例数据
+//        double[][] x = {{1, 19}, {1, 21}, {2, 20}, {2, 23}, {2, 31}};
+//        double[] y = {15, 15, 16, 16, 17};
+//
+//        // 创建线性回归模型
+//        LinearRegression lr = new LinearRegression();
+//        lr.fit(x, y);
+//
+//        DecimalFormat df = new DecimalFormat("#.0");
+//
+//        List<String> list=new ArrayList<>();
+//        for (int i = 0; i < lr.getSlopes().length; i++) {
+//            String format = df.format(lr.getSlopes()[i]);
+//            list.add(format);
+//        }
+//        // 输出模型参数
+//        System.out.println("常数项值: " + df.format(lr.getIntercept()));
+//        System.out.println("第一个特征系数值: " + list.get(0));
+//
+//        // 预测新数据
+//        double[] newX = {2, 88};
+//        double predictedY = lr.predict(newX);
+//        System.out.println("输入x: " + java.util.Arrays.toString(newX) + "预测y=" + df.format(predictedY));
+//    }
 }

src/main/java/com/sztzjy/marketing/util/algorithm/LogisticRegression.java

@@ -41,12 +41,12 @@ public class LogisticRegression {
     }
 
     // 预测函数
-    public double predict(double x) {
+    public double predict(double x,double slopes,double intercept) {
         BigDecimalUtils bigDecimalUtils=new BigDecimalUtils();
 
-        Double mul = bigDecimalUtils.mul(this.theta0, x);
+        Double mul = bigDecimalUtils.mul(intercept, x);
 
-        return bigDecimalUtils.add(this.theta1, mul);
+        return bigDecimalUtils.add(slopes, mul);
 
     }
 
@@ -57,14 +57,14 @@ public class LogisticRegression {
         }
         return result;
     }
-
-    // 梯度下降更新参数
-    public void updateParameters(double x, double y) {
-        double h = predict(x);
-        double error = y - h;
-        theta1 += learningRate * error * h * (1 - h) * x;
-        theta0 += learningRate * error * h * (1 - h);
-    }
+//
+//    // 梯度下降更新参数
+//    public void updateParameters(double x, double y) {
+//        double h = predict(x);
+//        double error = y - h;
+//        theta1 += learningRate * error * h * (1 - h) * x;
+//        theta0 += learningRate * error * h * (1 - h);
+//    }
     private double exponentialDecayLearningRate(double currentEpoch, int totalEpochs) {
         return learningRate * Math.exp(-(currentEpoch / totalEpochs));
     }
@@ -96,26 +96,26 @@ public class LogisticRegression {
         return loss / data.length;
     }
 
-    public static void main(String[] args) {
-        LogisticRegression model = new LogisticRegression(0.1); // 创建一个逻辑回归模型实例
-
-        double[][] data = {{1}, {2}, {3}, {4}, {5}};
-        double[] labels = {0, 0, 1, 1, 1}; // 假设这是一个二分类问题
-
+//    public static void main(String[] args) {
+//        LogisticRegression model = new LogisticRegression(0.1); // 创建一个逻辑回归模型实例
+//
+////        double[][] data = {{1}, {2}, {3}, {4}, {5}};
+////        double[] labels = {0, 0, 1, 1, 1}; // 假设这是一个二分类问题
+//
 //        double[][] data = {{1, 19}, {1, 21}, {2, 20}, {2, 23}, {2, 31}};
 //        double[] labels = {15, 15, 16, 16, 17};
-
-         model.train(data, labels, 1000); // 训练模型
-
-        DecimalFormat df = new DecimalFormat("#.0");
-
-        // 获取并打印截距项和系数
-        double intercept = model.getIntercept();
-        double coefficient = model.getCoefficient();
-        System.out.println("常数项值: " + df.format(intercept));
-        System.out.println("系数值 " + df.format(coefficient));
-
-        double prediction = model.predict(2);
-        System.out.println("x=3.5的预测： " + df.format(prediction));
-    }
+//
+//         model.train(data, labels, 1000); // 训练模型
+//
+//        DecimalFormat df = new DecimalFormat("#.0");
+//
+//        // 获取并打印截距项和系数
+//        double intercept = model.getIntercept();
+//        double coefficient = model.getCoefficient();
+//        System.out.println("常数项值: " + df.format(intercept));
+//        System.out.println("系数值 " + df.format(coefficient));
+//
+//        double prediction = model.predict(2);
+//        System.out.println("x=3.5的预测： " + df.format(prediction));
+//    }
 }

src/main/resources/mappers/StuUserAttributeMapper.xml

@@ -18,6 +18,9 @@
     <result column="backups" jdbcType="VARCHAR" property="backups" />
     <result column="location" jdbcType="VARCHAR" property="location" />
   </resultMap>
+  <resultMap extends="BaseResultMap" id="ResultMapWithBLOBs" type="com.sztzjy.marketing.entity.StuUserAttribute">
+    <result column="text" jdbcType="LONGVARCHAR" property="text" />
+  </resultMap>
   <sql id="Example_Where_Clause">
     <where>
       <foreach collection="oredCriteria" item="criteria" separator="or">
@@ -80,6 +83,25 @@
     id, user_id, login_name, user_name, student_id, stu_class, major, school, role_name, 
     role_gender, create_time, role_age, update_time, backups, location
   </sql>
+  <sql id="Blob_Column_List">
+    text
+  </sql>
+  <select id="selectByExampleWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserAttributeExample" resultMap="ResultMapWithBLOBs">
+    select
+    <if test="distinct">
+      distinct
+    </if>
+    <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
+    from stu_user_attribute
+    <if test="_parameter != null">
+      <include refid="Example_Where_Clause" />
+    </if>
+    <if test="orderByClause != null">
+      order by ${orderByClause}
+    </if>
+  </select>
   <select id="selectByExample" parameterType="com.sztzjy.marketing.entity.StuUserAttributeExample" resultMap="BaseResultMap">
     select
     <if test="distinct">
@@ -94,9 +116,11 @@
       order by ${orderByClause}
     </if>
   </select>
-  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="BaseResultMap">
+  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="ResultMapWithBLOBs">
     select 
     <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
     from stu_user_attribute
     where id = #{id,jdbcType=INTEGER}
   </select>
@@ -115,14 +139,14 @@
       user_name, student_id, stu_class, 
       major, school, role_name, 
       role_gender, create_time, role_age, 
-      update_time, backups, location
-      )
+      update_time, backups, location, 
+      text)
     values (#{id,jdbcType=INTEGER}, #{userId,jdbcType=VARCHAR}, #{loginName,jdbcType=VARCHAR}, 
       #{userName,jdbcType=VARCHAR}, #{studentId,jdbcType=VARCHAR}, #{stuClass,jdbcType=VARCHAR}, 
       #{major,jdbcType=VARCHAR}, #{school,jdbcType=VARCHAR}, #{roleName,jdbcType=VARCHAR}, 
       #{roleGender,jdbcType=INTEGER}, #{createTime,jdbcType=TIMESTAMP}, #{roleAge,jdbcType=INTEGER}, 
-      #{updateTime,jdbcType=TIMESTAMP}, #{backups,jdbcType=VARCHAR}, #{location,jdbcType=VARCHAR}
-      )
+      #{updateTime,jdbcType=TIMESTAMP}, #{backups,jdbcType=VARCHAR}, #{location,jdbcType=VARCHAR}, 
+      #{text,jdbcType=LONGVARCHAR})
   </insert>
   <insert id="insertSelective" parameterType="com.sztzjy.marketing.entity.StuUserAttribute">
     insert into stu_user_attribute
@@ -172,6 +196,9 @@
       <if test="location != null">
         location,
       </if>
+      <if test="text != null">
+        text,
+      </if>
     </trim>
     <trim prefix="values (" suffix=")" suffixOverrides=",">
       <if test="id != null">
@@ -219,6 +246,9 @@
       <if test="location != null">
         #{location,jdbcType=VARCHAR},
       </if>
+      <if test="text != null">
+        #{text,jdbcType=LONGVARCHAR},
+      </if>
     </trim>
   </insert>
   <select id="countByExample" parameterType="com.sztzjy.marketing.entity.StuUserAttributeExample" resultType="java.lang.Long">
@@ -275,11 +305,36 @@
       <if test="record.location != null">
         location = #{record.location,jdbcType=VARCHAR},
       </if>
+      <if test="record.text != null">
+        text = #{record.text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     <if test="_parameter != null">
       <include refid="Update_By_Example_Where_Clause" />
     </if>
   </update>
+  <update id="updateByExampleWithBLOBs" parameterType="map">
+    update stu_user_attribute
+    set id = #{record.id,jdbcType=INTEGER},
+      user_id = #{record.userId,jdbcType=VARCHAR},
+      login_name = #{record.loginName,jdbcType=VARCHAR},
+      user_name = #{record.userName,jdbcType=VARCHAR},
+      student_id = #{record.studentId,jdbcType=VARCHAR},
+      stu_class = #{record.stuClass,jdbcType=VARCHAR},
+      major = #{record.major,jdbcType=VARCHAR},
+      school = #{record.school,jdbcType=VARCHAR},
+      role_name = #{record.roleName,jdbcType=VARCHAR},
+      role_gender = #{record.roleGender,jdbcType=INTEGER},
+      create_time = #{record.createTime,jdbcType=TIMESTAMP},
+      role_age = #{record.roleAge,jdbcType=INTEGER},
+      update_time = #{record.updateTime,jdbcType=TIMESTAMP},
+      backups = #{record.backups,jdbcType=VARCHAR},
+      location = #{record.location,jdbcType=VARCHAR},
+      text = #{record.text,jdbcType=LONGVARCHAR}
+    <if test="_parameter != null">
+      <include refid="Update_By_Example_Where_Clause" />
+    </if>
+  </update>
   <update id="updateByExample" parameterType="map">
     update stu_user_attribute
     set id = #{record.id,jdbcType=INTEGER},
@@ -346,9 +401,31 @@
       <if test="location != null">
         location = #{location,jdbcType=VARCHAR},
       </if>
+      <if test="text != null">
+        text = #{text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     where id = #{id,jdbcType=INTEGER}
   </update>
+  <update id="updateByPrimaryKeyWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserAttribute">
+    update stu_user_attribute
+    set user_id = #{userId,jdbcType=VARCHAR},
+      login_name = #{loginName,jdbcType=VARCHAR},
+      user_name = #{userName,jdbcType=VARCHAR},
+      student_id = #{studentId,jdbcType=VARCHAR},
+      stu_class = #{stuClass,jdbcType=VARCHAR},
+      major = #{major,jdbcType=VARCHAR},
+      school = #{school,jdbcType=VARCHAR},
+      role_name = #{roleName,jdbcType=VARCHAR},
+      role_gender = #{roleGender,jdbcType=INTEGER},
+      create_time = #{createTime,jdbcType=TIMESTAMP},
+      role_age = #{roleAge,jdbcType=INTEGER},
+      update_time = #{updateTime,jdbcType=TIMESTAMP},
+      backups = #{backups,jdbcType=VARCHAR},
+      location = #{location,jdbcType=VARCHAR},
+      text = #{text,jdbcType=LONGVARCHAR}
+    where id = #{id,jdbcType=INTEGER}
+  </update>
   <update id="updateByPrimaryKey" parameterType="com.sztzjy.marketing.entity.StuUserAttribute">
     update stu_user_attribute
     set user_id = #{userId,jdbcType=VARCHAR},
@@ -367,11 +444,4 @@
       location = #{location,jdbcType=VARCHAR}
     where id = #{id,jdbcType=INTEGER}
   </update>
-  <select id="selectByFields" resultType="java.util.Map">
-    SELECT
-    <foreach collection="fieldList" item="field" separator=",">
-      ${field}
-    </foreach>
-    FROM ${table}
-  </select>
 </mapper>

src/main/resources/mappers/StuUserBehaviorMapper.xml

@@ -14,11 +14,14 @@
     <result column="goods_name" jdbcType="VARCHAR" property="goodsName" />
     <result column="goods_type" jdbcType="VARCHAR" property="goodsType" />
     <result column="goods_subcategories" jdbcType="VARCHAR" property="goodsSubcategories" />
-    <result column="user_behavior_type" jdbcType="VARCHAR" property="userBehaviorType" />
+    <result column="user_behavior_type" jdbcType="INTEGER" property="userBehaviorType" />
     <result column="behavior_date" jdbcType="TIMESTAMP" property="behaviorDate" />
     <result column="create_time" jdbcType="TIMESTAMP" property="createTime" />
     <result column="update_time" jdbcType="TIMESTAMP" property="updateTime" />
   </resultMap>
+  <resultMap extends="BaseResultMap" id="ResultMapWithBLOBs" type="com.sztzjy.marketing.entity.StuUserBehavior">
+    <result column="text" jdbcType="LONGVARCHAR" property="text" />
+  </resultMap>
   <sql id="Example_Where_Clause">
     <where>
       <foreach collection="oredCriteria" item="criteria" separator="or">
@@ -82,6 +85,25 @@
     goods_name, goods_type, goods_subcategories, user_behavior_type, behavior_date, create_time, 
     update_time
   </sql>
+  <sql id="Blob_Column_List">
+    text
+  </sql>
+  <select id="selectByExampleWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserBehaviorExample" resultMap="ResultMapWithBLOBs">
+    select
+    <if test="distinct">
+      distinct
+    </if>
+    <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
+    from stu_user_behavior
+    <if test="_parameter != null">
+      <include refid="Example_Where_Clause" />
+    </if>
+    <if test="orderByClause != null">
+      order by ${orderByClause}
+    </if>
+  </select>
   <select id="selectByExample" parameterType="com.sztzjy.marketing.entity.StuUserBehaviorExample" resultMap="BaseResultMap">
     select
     <if test="distinct">
@@ -96,9 +118,11 @@
       order by ${orderByClause}
     </if>
   </select>
-  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="BaseResultMap">
+  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="ResultMapWithBLOBs">
     select 
     <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
     from stu_user_behavior
     where id = #{id,jdbcType=INTEGER}
   </select>
@@ -118,13 +142,13 @@
       major, school, role_name, 
       goods_name, goods_type, goods_subcategories, 
       user_behavior_type, behavior_date, create_time, 
-      update_time)
+      update_time, text)
     values (#{id,jdbcType=INTEGER}, #{userId,jdbcType=VARCHAR}, #{loginName,jdbcType=VARCHAR}, 
       #{userName,jdbcType=VARCHAR}, #{studentId,jdbcType=VARCHAR}, #{stuClass,jdbcType=VARCHAR}, 
       #{major,jdbcType=VARCHAR}, #{school,jdbcType=VARCHAR}, #{roleName,jdbcType=VARCHAR}, 
       #{goodsName,jdbcType=VARCHAR}, #{goodsType,jdbcType=VARCHAR}, #{goodsSubcategories,jdbcType=VARCHAR}, 
-      #{userBehaviorType,jdbcType=VARCHAR}, #{behaviorDate,jdbcType=TIMESTAMP}, #{createTime,jdbcType=TIMESTAMP}, 
-      #{updateTime,jdbcType=TIMESTAMP})
+      #{userBehaviorType,jdbcType=INTEGER}, #{behaviorDate,jdbcType=TIMESTAMP}, #{createTime,jdbcType=TIMESTAMP}, 
+      #{updateTime,jdbcType=TIMESTAMP}, #{text,jdbcType=LONGVARCHAR})
   </insert>
   <insert id="insertSelective" parameterType="com.sztzjy.marketing.entity.StuUserBehavior">
     insert into stu_user_behavior
@@ -177,6 +201,9 @@
       <if test="updateTime != null">
         update_time,
       </if>
+      <if test="text != null">
+        text,
+      </if>
     </trim>
     <trim prefix="values (" suffix=")" suffixOverrides=",">
       <if test="id != null">
@@ -216,7 +243,7 @@
         #{goodsSubcategories,jdbcType=VARCHAR},
       </if>
       <if test="userBehaviorType != null">
-        #{userBehaviorType,jdbcType=VARCHAR},
+        #{userBehaviorType,jdbcType=INTEGER},
       </if>
       <if test="behaviorDate != null">
         #{behaviorDate,jdbcType=TIMESTAMP},
@@ -227,6 +254,9 @@
       <if test="updateTime != null">
         #{updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="text != null">
+        #{text,jdbcType=LONGVARCHAR},
+      </if>
     </trim>
   </insert>
   <select id="countByExample" parameterType="com.sztzjy.marketing.entity.StuUserBehaviorExample" resultType="java.lang.Long">
@@ -275,7 +305,7 @@
         goods_subcategories = #{record.goodsSubcategories,jdbcType=VARCHAR},
       </if>
       <if test="record.userBehaviorType != null">
-        user_behavior_type = #{record.userBehaviorType,jdbcType=VARCHAR},
+        user_behavior_type = #{record.userBehaviorType,jdbcType=INTEGER},
       </if>
       <if test="record.behaviorDate != null">
         behavior_date = #{record.behaviorDate,jdbcType=TIMESTAMP},
@@ -286,11 +316,37 @@
       <if test="record.updateTime != null">
         update_time = #{record.updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="record.text != null">
+        text = #{record.text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     <if test="_parameter != null">
       <include refid="Update_By_Example_Where_Clause" />
     </if>
   </update>
+  <update id="updateByExampleWithBLOBs" parameterType="map">
+    update stu_user_behavior
+    set id = #{record.id,jdbcType=INTEGER},
+      user_id = #{record.userId,jdbcType=VARCHAR},
+      login_name = #{record.loginName,jdbcType=VARCHAR},
+      user_name = #{record.userName,jdbcType=VARCHAR},
+      student_id = #{record.studentId,jdbcType=VARCHAR},
+      stu_class = #{record.stuClass,jdbcType=VARCHAR},
+      major = #{record.major,jdbcType=VARCHAR},
+      school = #{record.school,jdbcType=VARCHAR},
+      role_name = #{record.roleName,jdbcType=VARCHAR},
+      goods_name = #{record.goodsName,jdbcType=VARCHAR},
+      goods_type = #{record.goodsType,jdbcType=VARCHAR},
+      goods_subcategories = #{record.goodsSubcategories,jdbcType=VARCHAR},
+      user_behavior_type = #{record.userBehaviorType,jdbcType=INTEGER},
+      behavior_date = #{record.behaviorDate,jdbcType=TIMESTAMP},
+      create_time = #{record.createTime,jdbcType=TIMESTAMP},
+      update_time = #{record.updateTime,jdbcType=TIMESTAMP},
+      text = #{record.text,jdbcType=LONGVARCHAR}
+    <if test="_parameter != null">
+      <include refid="Update_By_Example_Where_Clause" />
+    </if>
+  </update>
   <update id="updateByExample" parameterType="map">
     update stu_user_behavior
     set id = #{record.id,jdbcType=INTEGER},
@@ -305,7 +361,7 @@
       goods_name = #{record.goodsName,jdbcType=VARCHAR},
       goods_type = #{record.goodsType,jdbcType=VARCHAR},
       goods_subcategories = #{record.goodsSubcategories,jdbcType=VARCHAR},
-      user_behavior_type = #{record.userBehaviorType,jdbcType=VARCHAR},
+      user_behavior_type = #{record.userBehaviorType,jdbcType=INTEGER},
       behavior_date = #{record.behaviorDate,jdbcType=TIMESTAMP},
       create_time = #{record.createTime,jdbcType=TIMESTAMP},
       update_time = #{record.updateTime,jdbcType=TIMESTAMP}
@@ -350,7 +406,7 @@
         goods_subcategories = #{goodsSubcategories,jdbcType=VARCHAR},
       </if>
       <if test="userBehaviorType != null">
-        user_behavior_type = #{userBehaviorType,jdbcType=VARCHAR},
+        user_behavior_type = #{userBehaviorType,jdbcType=INTEGER},
       </if>
       <if test="behaviorDate != null">
         behavior_date = #{behaviorDate,jdbcType=TIMESTAMP},
@@ -361,9 +417,32 @@
       <if test="updateTime != null">
         update_time = #{updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="text != null">
+        text = #{text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     where id = #{id,jdbcType=INTEGER}
   </update>
+  <update id="updateByPrimaryKeyWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserBehavior">
+    update stu_user_behavior
+    set user_id = #{userId,jdbcType=VARCHAR},
+      login_name = #{loginName,jdbcType=VARCHAR},
+      user_name = #{userName,jdbcType=VARCHAR},
+      student_id = #{studentId,jdbcType=VARCHAR},
+      stu_class = #{stuClass,jdbcType=VARCHAR},
+      major = #{major,jdbcType=VARCHAR},
+      school = #{school,jdbcType=VARCHAR},
+      role_name = #{roleName,jdbcType=VARCHAR},
+      goods_name = #{goodsName,jdbcType=VARCHAR},
+      goods_type = #{goodsType,jdbcType=VARCHAR},
+      goods_subcategories = #{goodsSubcategories,jdbcType=VARCHAR},
+      user_behavior_type = #{userBehaviorType,jdbcType=INTEGER},
+      behavior_date = #{behaviorDate,jdbcType=TIMESTAMP},
+      create_time = #{createTime,jdbcType=TIMESTAMP},
+      update_time = #{updateTime,jdbcType=TIMESTAMP},
+      text = #{text,jdbcType=LONGVARCHAR}
+    where id = #{id,jdbcType=INTEGER}
+  </update>
   <update id="updateByPrimaryKey" parameterType="com.sztzjy.marketing.entity.StuUserBehavior">
     update stu_user_behavior
     set user_id = #{userId,jdbcType=VARCHAR},
@@ -377,7 +456,7 @@
       goods_name = #{goodsName,jdbcType=VARCHAR},
       goods_type = #{goodsType,jdbcType=VARCHAR},
       goods_subcategories = #{goodsSubcategories,jdbcType=VARCHAR},
-      user_behavior_type = #{userBehaviorType,jdbcType=VARCHAR},
+      user_behavior_type = #{userBehaviorType,jdbcType=INTEGER},
       behavior_date = #{behaviorDate,jdbcType=TIMESTAMP},
       create_time = #{createTime,jdbcType=TIMESTAMP},
       update_time = #{updateTime,jdbcType=TIMESTAMP}

src/main/resources/mappers/StuUserConsumptionAbilityMapper.xml

@@ -21,6 +21,9 @@
     <result column="create_time" jdbcType="TIMESTAMP" property="createTime" />
     <result column="update_time" jdbcType="TIMESTAMP" property="updateTime" />
   </resultMap>
+  <resultMap extends="BaseResultMap" id="ResultMapWithBLOBs" type="com.sztzjy.marketing.entity.StuUserConsumptionAbility">
+    <result column="text" jdbcType="LONGVARCHAR" property="text" />
+  </resultMap>
   <sql id="Example_Where_Clause">
     <where>
       <foreach collection="oredCriteria" item="criteria" separator="or">
@@ -84,6 +87,25 @@
     consumer_goods, consumer_goods_type, consumer_amount, consumer_number, consumer_past_seven_days_amount, 
     consumer_past_seven_days_number, recent_consumption_time, create_time, update_time
   </sql>
+  <sql id="Blob_Column_List">
+    text
+  </sql>
+  <select id="selectByExampleWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserConsumptionAbilityExample" resultMap="ResultMapWithBLOBs">
+    select
+    <if test="distinct">
+      distinct
+    </if>
+    <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
+    from stu_user_consumption_ability
+    <if test="_parameter != null">
+      <include refid="Example_Where_Clause" />
+    </if>
+    <if test="orderByClause != null">
+      order by ${orderByClause}
+    </if>
+  </select>
   <select id="selectByExample" parameterType="com.sztzjy.marketing.entity.StuUserConsumptionAbilityExample" resultMap="BaseResultMap">
     select
     <if test="distinct">
@@ -98,9 +120,11 @@
       order by ${orderByClause}
     </if>
   </select>
-  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="BaseResultMap">
+  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="ResultMapWithBLOBs">
     select 
     <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
     from stu_user_consumption_ability
     where id = #{id,jdbcType=INTEGER}
   </select>
@@ -121,14 +145,16 @@
       consumer_goods, consumer_goods_type, consumer_amount, 
       consumer_number, consumer_past_seven_days_amount, 
       consumer_past_seven_days_number, recent_consumption_time, 
-      create_time, update_time)
+      create_time, update_time, text
+      )
     values (#{id,jdbcType=INTEGER}, #{userId,jdbcType=VARCHAR}, #{loginName,jdbcType=VARCHAR}, 
       #{userName,jdbcType=VARCHAR}, #{studentId,jdbcType=VARCHAR}, #{stuClass,jdbcType=VARCHAR}, 
       #{major,jdbcType=VARCHAR}, #{school,jdbcType=VARCHAR}, #{roleName,jdbcType=VARCHAR}, 
       #{consumerGoods,jdbcType=VARCHAR}, #{consumerGoodsType,jdbcType=VARCHAR}, #{consumerAmount,jdbcType=DECIMAL}, 
       #{consumerNumber,jdbcType=INTEGER}, #{consumerPastSevenDaysAmount,jdbcType=DECIMAL}, 
       #{consumerPastSevenDaysNumber,jdbcType=INTEGER}, #{recentConsumptionTime,jdbcType=TIMESTAMP}, 
-      #{createTime,jdbcType=TIMESTAMP}, #{updateTime,jdbcType=TIMESTAMP})
+      #{createTime,jdbcType=TIMESTAMP}, #{updateTime,jdbcType=TIMESTAMP}, #{text,jdbcType=LONGVARCHAR}
+      )
   </insert>
   <insert id="insertSelective" parameterType="com.sztzjy.marketing.entity.StuUserConsumptionAbility">
     insert into stu_user_consumption_ability
@@ -187,6 +213,9 @@
       <if test="updateTime != null">
         update_time,
       </if>
+      <if test="text != null">
+        text,
+      </if>
     </trim>
     <trim prefix="values (" suffix=")" suffixOverrides=",">
       <if test="id != null">
@@ -243,6 +272,9 @@
       <if test="updateTime != null">
         #{updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="text != null">
+        #{text,jdbcType=LONGVARCHAR},
+      </if>
     </trim>
   </insert>
   <select id="countByExample" parameterType="com.sztzjy.marketing.entity.StuUserConsumptionAbilityExample" resultType="java.lang.Long">
@@ -251,8 +283,7 @@
       <include refid="Example_Where_Clause" />
     </if>
   </select>
-
-    <update id="updateByExampleSelective" parameterType="map">
+  <update id="updateByExampleSelective" parameterType="map">
     update stu_user_consumption_ability
     <set>
       <if test="record.id != null">
@@ -309,11 +340,39 @@
       <if test="record.updateTime != null">
         update_time = #{record.updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="record.text != null">
+        text = #{record.text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     <if test="_parameter != null">
       <include refid="Update_By_Example_Where_Clause" />
     </if>
   </update>
+  <update id="updateByExampleWithBLOBs" parameterType="map">
+    update stu_user_consumption_ability
+    set id = #{record.id,jdbcType=INTEGER},
+      user_id = #{record.userId,jdbcType=VARCHAR},
+      login_name = #{record.loginName,jdbcType=VARCHAR},
+      user_name = #{record.userName,jdbcType=VARCHAR},
+      student_id = #{record.studentId,jdbcType=VARCHAR},
+      stu_class = #{record.stuClass,jdbcType=VARCHAR},
+      major = #{record.major,jdbcType=VARCHAR},
+      school = #{record.school,jdbcType=VARCHAR},
+      role_name = #{record.roleName,jdbcType=VARCHAR},
+      consumer_goods = #{record.consumerGoods,jdbcType=VARCHAR},
+      consumer_goods_type = #{record.consumerGoodsType,jdbcType=VARCHAR},
+      consumer_amount = #{record.consumerAmount,jdbcType=DECIMAL},
+      consumer_number = #{record.consumerNumber,jdbcType=INTEGER},
+      consumer_past_seven_days_amount = #{record.consumerPastSevenDaysAmount,jdbcType=DECIMAL},
+      consumer_past_seven_days_number = #{record.consumerPastSevenDaysNumber,jdbcType=INTEGER},
+      recent_consumption_time = #{record.recentConsumptionTime,jdbcType=TIMESTAMP},
+      create_time = #{record.createTime,jdbcType=TIMESTAMP},
+      update_time = #{record.updateTime,jdbcType=TIMESTAMP},
+      text = #{record.text,jdbcType=LONGVARCHAR}
+    <if test="_parameter != null">
+      <include refid="Update_By_Example_Where_Clause" />
+    </if>
+  </update>
   <update id="updateByExample" parameterType="map">
     update stu_user_consumption_ability
     set id = #{record.id,jdbcType=INTEGER},
@@ -392,9 +451,34 @@
       <if test="updateTime != null">
         update_time = #{updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="text != null">
+        text = #{text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     where id = #{id,jdbcType=INTEGER}
   </update>
+  <update id="updateByPrimaryKeyWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserConsumptionAbility">
+    update stu_user_consumption_ability
+    set user_id = #{userId,jdbcType=VARCHAR},
+      login_name = #{loginName,jdbcType=VARCHAR},
+      user_name = #{userName,jdbcType=VARCHAR},
+      student_id = #{studentId,jdbcType=VARCHAR},
+      stu_class = #{stuClass,jdbcType=VARCHAR},
+      major = #{major,jdbcType=VARCHAR},
+      school = #{school,jdbcType=VARCHAR},
+      role_name = #{roleName,jdbcType=VARCHAR},
+      consumer_goods = #{consumerGoods,jdbcType=VARCHAR},
+      consumer_goods_type = #{consumerGoodsType,jdbcType=VARCHAR},
+      consumer_amount = #{consumerAmount,jdbcType=DECIMAL},
+      consumer_number = #{consumerNumber,jdbcType=INTEGER},
+      consumer_past_seven_days_amount = #{consumerPastSevenDaysAmount,jdbcType=DECIMAL},
+      consumer_past_seven_days_number = #{consumerPastSevenDaysNumber,jdbcType=INTEGER},
+      recent_consumption_time = #{recentConsumptionTime,jdbcType=TIMESTAMP},
+      create_time = #{createTime,jdbcType=TIMESTAMP},
+      update_time = #{updateTime,jdbcType=TIMESTAMP},
+      text = #{text,jdbcType=LONGVARCHAR}
+    where id = #{id,jdbcType=INTEGER}
+  </update>
   <update id="updateByPrimaryKey" parameterType="com.sztzjy.marketing.entity.StuUserConsumptionAbility">
     update stu_user_consumption_ability
     set user_id = #{userId,jdbcType=VARCHAR},
@@ -416,11 +500,4 @@
       update_time = #{updateTime,jdbcType=TIMESTAMP}
     where id = #{id,jdbcType=INTEGER}
   </update>
-  <select id="selectByFields" resultType="com.sztzjy.marketing.entity.StuUserConsumptionAbility" resultMap="BaseResultMap">
-    SELECT
-    <foreach collection="fieldList" item="field" separator=",">
-      ${field}
-    </foreach>
-    FROM ${table}
-  </select>
 </mapper>

src/main/resources/mappers/StuUserLoginActiveMapper.xml

@@ -18,6 +18,9 @@
     <result column="create_time" jdbcType="TIMESTAMP" property="createTime" />
     <result column="update_time" jdbcType="TIMESTAMP" property="updateTime" />
   </resultMap>
+  <resultMap extends="BaseResultMap" id="ResultMapWithBLOBs" type="com.sztzjy.marketing.entity.StuUserLoginActive">
+    <result column="text" jdbcType="LONGVARCHAR" property="text" />
+  </resultMap>
   <sql id="Example_Where_Clause">
     <where>
       <foreach collection="oredCriteria" item="criteria" separator="or">
@@ -81,6 +84,25 @@
     frequent_login_location, last_login_date, login_frequency, login_duration, create_time, 
     update_time
   </sql>
+  <sql id="Blob_Column_List">
+    text
+  </sql>
+  <select id="selectByExampleWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserLoginActiveExample" resultMap="ResultMapWithBLOBs">
+    select
+    <if test="distinct">
+      distinct
+    </if>
+    <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
+    from stu_user_login_active
+    <if test="_parameter != null">
+      <include refid="Example_Where_Clause" />
+    </if>
+    <if test="orderByClause != null">
+      order by ${orderByClause}
+    </if>
+  </select>
   <select id="selectByExample" parameterType="com.sztzjy.marketing.entity.StuUserLoginActiveExample" resultMap="BaseResultMap">
     select
     <if test="distinct">
@@ -95,9 +117,11 @@
       order by ${orderByClause}
     </if>
   </select>
-  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="BaseResultMap">
+  <select id="selectByPrimaryKey" parameterType="java.lang.Integer" resultMap="ResultMapWithBLOBs">
     select 
     <include refid="Base_Column_List" />
+    ,
+    <include refid="Blob_Column_List" />
     from stu_user_login_active
     where id = #{id,jdbcType=INTEGER}
   </select>
@@ -117,13 +141,13 @@
       major, school, role_name, 
       frequent_login_location, last_login_date, 
       login_frequency, login_duration, create_time, 
-      update_time)
+      update_time, text)
     values (#{id,jdbcType=INTEGER}, #{userId,jdbcType=VARCHAR}, #{loginName,jdbcType=VARCHAR}, 
       #{userName,jdbcType=VARCHAR}, #{studentId,jdbcType=VARCHAR}, #{stuClass,jdbcType=VARCHAR}, 
       #{major,jdbcType=VARCHAR}, #{school,jdbcType=VARCHAR}, #{roleName,jdbcType=VARCHAR}, 
       #{frequentLoginLocation,jdbcType=VARCHAR}, #{lastLoginDate,jdbcType=TIMESTAMP}, 
       #{loginFrequency,jdbcType=INTEGER}, #{loginDuration,jdbcType=DOUBLE}, #{createTime,jdbcType=TIMESTAMP}, 
-      #{updateTime,jdbcType=TIMESTAMP})
+      #{updateTime,jdbcType=TIMESTAMP}, #{text,jdbcType=LONGVARCHAR})
   </insert>
   <insert id="insertSelective" parameterType="com.sztzjy.marketing.entity.StuUserLoginActive">
     insert into stu_user_login_active
@@ -173,6 +197,9 @@
       <if test="updateTime != null">
         update_time,
       </if>
+      <if test="text != null">
+        text,
+      </if>
     </trim>
     <trim prefix="values (" suffix=")" suffixOverrides=",">
       <if test="id != null">
@@ -220,6 +247,9 @@
       <if test="updateTime != null">
         #{updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="text != null">
+        #{text,jdbcType=LONGVARCHAR},
+      </if>
     </trim>
   </insert>
   <select id="countByExample" parameterType="com.sztzjy.marketing.entity.StuUserLoginActiveExample" resultType="java.lang.Long">
@@ -276,11 +306,36 @@
       <if test="record.updateTime != null">
         update_time = #{record.updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="record.text != null">
+        text = #{record.text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     <if test="_parameter != null">
       <include refid="Update_By_Example_Where_Clause" />
     </if>
   </update>
+  <update id="updateByExampleWithBLOBs" parameterType="map">
+    update stu_user_login_active
+    set id = #{record.id,jdbcType=INTEGER},
+      user_id = #{record.userId,jdbcType=VARCHAR},
+      login_name = #{record.loginName,jdbcType=VARCHAR},
+      user_name = #{record.userName,jdbcType=VARCHAR},
+      student_id = #{record.studentId,jdbcType=VARCHAR},
+      stu_class = #{record.stuClass,jdbcType=VARCHAR},
+      major = #{record.major,jdbcType=VARCHAR},
+      school = #{record.school,jdbcType=VARCHAR},
+      role_name = #{record.roleName,jdbcType=VARCHAR},
+      frequent_login_location = #{record.frequentLoginLocation,jdbcType=VARCHAR},
+      last_login_date = #{record.lastLoginDate,jdbcType=TIMESTAMP},
+      login_frequency = #{record.loginFrequency,jdbcType=INTEGER},
+      login_duration = #{record.loginDuration,jdbcType=DOUBLE},
+      create_time = #{record.createTime,jdbcType=TIMESTAMP},
+      update_time = #{record.updateTime,jdbcType=TIMESTAMP},
+      text = #{record.text,jdbcType=LONGVARCHAR}
+    <if test="_parameter != null">
+      <include refid="Update_By_Example_Where_Clause" />
+    </if>
+  </update>
   <update id="updateByExample" parameterType="map">
     update stu_user_login_active
     set id = #{record.id,jdbcType=INTEGER},
@@ -347,9 +402,31 @@
       <if test="updateTime != null">
         update_time = #{updateTime,jdbcType=TIMESTAMP},
       </if>
+      <if test="text != null">
+        text = #{text,jdbcType=LONGVARCHAR},
+      </if>
     </set>
     where id = #{id,jdbcType=INTEGER}
   </update>
+  <update id="updateByPrimaryKeyWithBLOBs" parameterType="com.sztzjy.marketing.entity.StuUserLoginActive">
+    update stu_user_login_active
+    set user_id = #{userId,jdbcType=VARCHAR},
+      login_name = #{loginName,jdbcType=VARCHAR},
+      user_name = #{userName,jdbcType=VARCHAR},
+      student_id = #{studentId,jdbcType=VARCHAR},
+      stu_class = #{stuClass,jdbcType=VARCHAR},
+      major = #{major,jdbcType=VARCHAR},
+      school = #{school,jdbcType=VARCHAR},
+      role_name = #{roleName,jdbcType=VARCHAR},
+      frequent_login_location = #{frequentLoginLocation,jdbcType=VARCHAR},
+      last_login_date = #{lastLoginDate,jdbcType=TIMESTAMP},
+      login_frequency = #{loginFrequency,jdbcType=INTEGER},
+      login_duration = #{loginDuration,jdbcType=DOUBLE},
+      create_time = #{createTime,jdbcType=TIMESTAMP},
+      update_time = #{updateTime,jdbcType=TIMESTAMP},
+      text = #{text,jdbcType=LONGVARCHAR}
+    where id = #{id,jdbcType=INTEGER}
+  </update>
   <update id="updateByPrimaryKey" parameterType="com.sztzjy.marketing.entity.StuUserLoginActive">
     update stu_user_login_active
     set user_id = #{userId,jdbcType=VARCHAR},