What is the method for Java to automatically generate trend comparison data?

Background

Pairwise trend comparison between data is a very common application scenario in data analysis applications, as shown below:

##202302 Class Three Years张小明130145133 202302三级一王二小128138140202302Class Three Three YearsXie Chunhua136142139202301Three-Year ClassZhang Xiaoming132140128202301Class Three Three Years王二小125146142202301Class Three Three YearsXie Chunhua138143140202212Three-Year ClassZhang Xiaoming135138120 202212三级一级王二小123145138202212Class Three Three YearsXie Chunhua136140142

Mock test Batch	Class	Student	Chinese	Mathematics	English

Now there is a need: the progress and decline of each student's performance in each subject in different exam batches for each student in each class. The data obtained are as follows

Mock test batchClassStudentChineseMathematicsEnglish##Comparison between 202302 and 202301Comparison between 202302 and 202301Comparison between 202302 and 202301##Comparison between 202301 and 202212Three-year class 张小明-328Comparison between 202301 and 202212三一级王二小214202301 and 202212 ComparisonClass Three YearsXie Chunhua23-2Detailed design and implementation

Three-Year Class	Zhang Xiaoming	-2	5	5
三级一级	王二小	3	-8	#-2
Class Three Three Years	Xie Chunhua	-2	-1	-1

Trend comparison definition class TrendCompare

public class TrendCompare {
    /**
     * 主体的字段列表（如三年一班的张小明，那么主体字段列表为 班级 + 学生姓名）
     */
    private String[] subjectFields;
    /**
     * 在某个字段的（介词） 如三年一班张晓明在不同考试批次的成绩对比结果
     */
    private String atField;

    /**
     * 参与趋势比较的字段集合
     */
    private String[] compareFields;

    /**
     * 赋值映射集合：给结果数据中指定的key设置指定的值
     */
    private Map<String, String> assignValMap;

    public String[] subjectFields() {
        return this.subjectFields;
    }

    public TrendCompare subjectFields(String... fields) {
        this.subjectFields = fields;
        return this;
    }

    public String atField() {
        return this.atField;
    }

    public TrendCompare atField(String field) {
        this.atField = field;
        return this;
    }

    public String[] compareFields() {
        return this.compareFields;
    }

    public TrendCompare compareFields(String... fields) {
        this.compareFields = fields;
        return this;
    }

    /**
     * 赋值操作
     *
     * @param field
     * @param valueEL 值表达式
     * @return
     */
    public TrendCompare assignVal(String field, String valueEL) {
        if (assignValMap == null) {
            assignValMap = new HashMap<>();
        }
        assignValMap.put(field, valueEL);
        return this;
    }

    public Map<String, String> assignValMap() {
        return this.assignValMap;
    }
}

This class defines the following attributes:

The subject's Field list

• Preposition field

• Compared field list

• For example:
The progress and decline of each student

in each class in different

examination batcheseach subjectThe results of mapping the above requirements to the defined class are as follows :

Subject field list (

Class, student
• )
  Preposition field (
Exam batch
• )
  Comparison field list (various subjects:
Chinese, mathematics, English
• )
  Trend ratio For the execution class

, this class provides a method for external calls as follows

public static <T> List<T> compare(List<T> dataList, TrendCompare trendCompare) {
    Map<String, List<T>> groupMap = group(dataList, null, trendCompare.subjectFields());
    List<T> resultList = new ArrayList<>();
    for (List<T> groupDataList : groupMap.values()) {
        List<T> diffValueList = new ArrayList<>();
        int size = groupDataList.size();
        if (size > 1) {
            for (int i = 0; i < size - 1; i++) {
                //数据之间两两比较 diffValue = minuend - subtrahend
                T minuend = groupDataList.get(i);
                T subtrahend = groupDataList.get(i + 1);
                T diffValue = minus(trendCompare.compareFields(), minuend, subtrahend);
                //设置主体信息
                if (trendCompare.subjectFields() != null) {
                    for (String subjectField : trendCompare.subjectFields()) {
                        setFieldValue(diffValue, subjectField, getFieldValue(minuend, subjectField));
                    }
                }
                //设置介词字段信息
                String atField = trendCompare.atField();
                if (StringUtils.isNotEmpty(atField)) {
                    setFieldValue(diffValue, atField, getFieldValue(minuend, atField) + "与" + getFieldValue(subtrahend, atField) + "对比增减");
                }
                diffValueList.add(diffValue);
            }
        }
        if (diffValueList.size() > 0) {
            T firstData = groupDataList.get(0);
            Map<String, Object> valMap = new HashMap<>();
            //指定的赋值集合进行赋值
            if (trendCompare.assignValMap() != null) {
                for (Map.Entry<String, String> stringStringEntry : trendCompare.assignValMap().entrySet()) {
                    String field = stringStringEntry.getKey();
                    if (!StringUtils.equalsAny(field, trendCompare.compareFields())) {
                        String valueEL = stringStringEntry.getValue();
                        valMap.put(field, executeSpEL(valueEL, firstData));
                    }
                }
            }
            for (Map.Entry<String, Object> entry : valMap.entrySet()) {
                for (T diffValue : diffValueList) {
                    setFieldValue(diffValue, entry.getKey(), entry.getValue());
                }
            }
        }
        resultList.addAll(diffValueList);
    }
    return resultList;
}

As you can see, this method requires the incoming

data collection

• Trend comparison defines

• two parameters, and finally returns the result set after trend comparison.

The internal logic of this method can be divided into the following 2 steps:

Group by subject

• After grouping, within the group The data is compared pairwise and the comparison result is finally returned.

• Use case

Suppose there is a set of data as follows

Define a student class:

public class Student {
    private String batch;
    private String banji;
    private String studentNo;
    private String name;
    private String sex;
    private Double yuwen;
    private Double math;
    private Double english;
    private Double physics;
    //extra
    private String maxScoreName1;
    public Student(String batch, String banji, String studentNo, String name, String sex, Double yuwen, Double math, Double english, Double physics) {
        this.batch = batch;
        this.banji = banji;
        this.studentNo = studentNo;
        this.name = name;
        this.sex = sex;
        this.yuwen = yuwen;
        this.math = math;
        this.english = english;
        this.physics = physics;
    }
}

We write a method to return the above data:

public List<Student> getDataList() {
    List<Student> dataList = new ArrayList<>();
    dataList.add(new Student("202302", "三年一班", "20001001", "张小明", "男", 130.0, 145.0, 133.0, 92.0));
    dataList.add(new Student("202302", "三年一班", "20001002", "王二小", "男", 128.0, 138.0, 140.0, 98.0));
    dataList.add(new Student("202302", "三年一班", "20001003", "谢春花", "女", 136.0, 142.0, 139.0, 95.0));
    dataList.add(new Student("202302", "三年二班", "20002001", "冯世杰", "男", 129.0, 144.0, 138.0, 96.0));
    dataList.add(new Student("202302", "三年二班", "20002002", "马功成", "男", 130.0, 132.0, 133.0, 98.0));
    dataList.add(new Student("202302", "三年二班", "20002003", "魏翩翩", "女", 136.0, 142.0, 137.0, 92.0));
    dataList.add(new Student("202301", "三年一班", "20001001", "张小明", "男", 132.0, 142.0, 134.0, 92.0));
    dataList.add(new Student("202301", "三年一班", "20001002", "王二小", "男", 126.0, 136.0, 135.0, 94.0));
    dataList.add(new Student("202301", "三年一班", "20001003", "谢春花", "女", 136.0, 145.0, 139.0, 95.0));
    dataList.add(new Student("202301", "三年二班", "20002001", "冯世杰", "男", 124.0, 143.0, 148.0, 90.0));
    dataList.add(new Student("202301", "三年二班", "20002002", "马功成", "男", 140.0, 133.0, 138.0, 90.0));
    dataList.add(new Student("202301", "三年二班", "20002003", "魏翩翩", "女", 126.0, 136.0, 135.0, 92.0));
    return dataList;
}

Trend comparison definition and execution comparison:

List<Student> dataList = getDataList();
TrendCompare trendCompare = new TrendCompare()
        .subjectFields("banji", "name")
        .atField("batch")
        .compareFields("yuwen", "math", "english")
        //.assignVal("batch", "&#39;环比增减&#39;")
        ;
List<Student> resultList = DataProcessUtil.compare(dataList, trendCompare);
for (Student result : resultList) {
    System.out.println(JSON.toJSONString(result));
}

The results are as follows:

{"banji":"三年一班","batch":"202302与202301对比增减","english":-1.0,"math":3.0,"name":"张小明","yuwen":-2.0}
{"banji":"三年一班","batch":"202302与202301对比增减","english":5.0,"math":2.0,"name":"王二小","yuwen":2.0}
{"banji":"三年一班","batch":"202302与202301对比增减","english":0.0,"math":-3.0,"name":"谢春花","yuwen":0.0}
{"banji":"三年二班","batch":"202302与202301对比增减","english":-10.0,"math":1.0,"name":"冯世杰","yuwen":5.0}
{"banji":"三年二班","batch":"202302与202301对比增减","english":-5.0,"math":-1.0,"name":"马功成","yuwen":-10.0}
{"banji":"三年二班","batch":"202302与202301对比增减","english":2.0,"math":6.0,"name":"魏翩翩","yuwen":10.0}

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