手写一个DQC（一）DQC简介及数据解析

一：DQC核心流程

    Define：数据质检规则（指标）的定义。

            你要告警给谁，你要使用什么方式告警(邮件，即时消息)，你的规则是什么（空值，波动）等

    Measure：数据质检任务的执行

            数据在哪存储：hive、mysql是基本的数据库、CK、kylin等

    Analyze：数据质检结果量化及可视化展示。

            分为两种情况：（一）不需要图形化界面，直接在调度里面进行bash配置，使用自定义代码解析（二）有图形化界面，可以操作和查看历史结果

二：DQC标准

    Accuracy：准确性。如是否符合表的加工逻辑。
    Completeness：完备性。如数据是否存在丢失。
    Timeliness：及时性。如表数据是否按时产生。
    Uniqueness：唯一性。如主键字段是否唯一。
    Validity：合规性。如字段长度是否合规、枚举值集合是否合规。
    Consistency：一致性。如表与表之间在某些字段上是否存在矛盾。

三：DQC规则

2.1有效性
    字段长度有效、字段内容有效、字段数值范围有效、枚举值个数有效、枚举值集合有效
    2.2 唯一性
    对主键是否存在重复数据的监控指标。
    2.3 完整性
    字段是否为空或NULL、记录数是否丢失、记录数环比波动、录数波动范围、记录数方差检验、
    2.4 准确性
    数值同比、数值环比、数值方差检验、表逻辑检查
    2.5 一致性
    表级别一致性检查，外键检查
    2.6 时效性
    表级别质量监控指标，数据是否按时产出
    2.7数据剖析
    最大值检查、最小值检查、平均值检查、汇总值检查
    2.8 自定义规则检查
    用户写自定义SQL实现的监控规则
    从有效性、唯一性、完整性、准确性、一致性、时效性、数据剖析和自定义规则检查等几个维度对数据质量进行测量，但对于现在超级大的数据量级监控所有的数据是不符合成本效率的。
    因此，知道哪些数据为最关键的，对这些关键数据进行全链路的数据质量，这样有助于防止错误或揭示改进的机会。

    总结：指定值、空值、外键规范、外键最大最小、行数统计、最大、最小、平均、用户自定义

四：样例代码

String[] argsa={"-alter_user=xiaolong.wu","-alter_type=3","-counttype=A0001","-count_column=tag","-databases=hive.tranadm.adm_fin_paytrigger_revenue_ds","-dt=20220509","-filter_column=easysolar|tag","-filter_column_value=1000|上一节点","-assert_type=eq","-assert_Stringue=200","-assert_rate=0.2"};

MyArgs myArgs = MyArgs.build(argsa);

import java.text.ParseException;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

class MyArgsItemInfo{
    private String optionName  ="";
    private boolean necessary  = false;
    private String datatype  = "";
    private String dataverfiy  = ""; //  String:正则表达式   enum:|分割的枚举类型    float:最大值|最小值   date:日期格式
    private String desc  ="";

    public MyArgsItemInfo(String optionName, boolean necessary,String datetype,String dateverfiy, String desc) {
        this.optionName = optionName;
        this.necessary = necessary;
        this.datatype = datetype;
        this.dataverfiy = dateverfiy;
        this.desc = desc;
    }
    public String getOptionName() {
        return optionName;
    }
    public String getDatatype() {
        return datatype;
    }
    public String getDataverfiy() {
        return dataverfiy;
    }
}

class MyArgsInfo {

    public static MyArgsInfoBuildFactory init(){
        return new MyArgsInfoBuildFactory();
    }
    public static class MyArgsInfoBuildFactory {

        private List buildFactoryerMyArgsItemInfo = new ArrayList();

        public List build(){
            return buildFactoryerMyArgsItemInfo;
        }
        public MyArgsInfoBuildFactory addMyArgsItemInfo(String optionName, boolean necessary,String datetype,String dateverfiy, String desc) {
            buildFactoryerMyArgsItemInfo.add(new MyArgsItemInfo(optionName,necessary,datetype,dateverfiy,desc));
            return this;
        }
    }
}

public class MyArgs{
    private String alter_user = "";              //告警接收人
    private String alter_type = "";              //邮件，企业微信
    private String counttype = "";               //A0003
    private String count_column = "";            //
    private String databases  = "";              // hive.ods.ods_user_active_di  限定数据库类型、库名、表明
    private String dt = "";
    private String filter_column = "";           //,分割    接受多个字段
    private String filter_column_value = "";   //,分割    接受多个字段
    private String sql = "";
    private String assert_type = "";             //eq(==), lt(<), gt(>), le(<=), ge(>=), ne(!=)
    private String assert_Stringue = "";           //,
    private String assert_rate = "";               //,

    public static MyArgs build(String[] args) {
        return new MyArgsBuildFactory().build(args);
    }

    public MyArgs(MyArgsBuildFactory builder) {
        this.alter_user = builder.alter_user;
        this.alter_type = builder.alter_type ;
        this.counttype = builder.counttype;
        this.count_column = builder.count_column;
        this.databases = builder.databases;
        this.dt = builder.dt;
        this.filter_column = builder.filter_column;
        this.filter_column_value = builder.filter_column_value;
        this.sql = builder.sql;
        this.assert_type = builder.assert_type;
        this.assert_Stringue = builder.assert_Stringue;
        this.assert_rate = builder.assert_rate;
    }

    public static class MyArgsBuildFactory{
        private boolean checkFalse = false;

        private String alter_user = "";              //告警接收人
        private String alter_type = "";              //邮件，企业微信
        private String counttype = "";               //count(1) count(distinct )
        private String count_column = "";            //
        private String databases  = "";              // hive.ods.ods_user_active_di  限定数据库类型、库名、表明
        private String dt = "";                      // 默认比较今天和前一天的结果
        private String filter_column = "";           //,分割    接受多个字段
        private String filter_column_value = "";   //,分割    接受多个字段
        private String sql = "";
        private String assert_type = "";             //eq(==), lt(<), gt(>), le(<=), ge(>=), ne(!=)
        private String assert_Stringue = "";           //,
        private String assert_rate = "";               //,

        public void checkArgs(List myArgsInfo){
            for (int i = 0; i < myArgsInfo.size(); i++) {
                MyArgsItemInfo myArgsItemInfo = myArgsInfo.get(i);
                String datatype = myArgsItemInfo.getDatatype();
                String datavalue = getValueByName(myArgsItemInfo.getOptionName());
                //  String:正则表达式   enum:|分割的枚举类型    float:最大值|最小值   date:日期格式
                if(!datavalue.equals("")){   //空值的去掉
                    switch (datatype){
                        case "String" : {
                            if(!datavalue.matches(myArgsItemInfo.getDataverfiy())){
                                System.out.println(myArgsItemInfo.getOptionName()+"参数值存在问题，非"+myArgsItemInfo.getDataverfiy()+"正则表达式");
                                checkFalse = true;
                            }
                        };break;
                        case "enum" : {
                            if(!Arrays.asList(myArgsItemInfo.getDataverfiy().split("\\|")).contains(datavalue)){
                                System.out.println(myArgsItemInfo.getOptionName()+"参数值存在问题，非"+myArgsItemInfo.getDataverfiy()+"枚举值");
                                checkFalse = true;
                            }
                        }break;
                        case "float" : {
                            float minvalue = Float.valueOf(myArgsItemInfo.getDataverfiy().split("\\|")[0]);
                            float maxvalue = Float.valueOf(myArgsItemInfo.getDataverfiy().split("\\|")[0]);
                            if(Float.valueOf(datavalue)>maxvalue || Float.valueOf(datavalue) myArgsItemInfoInit(){
            MyArgsInfo.MyArgsInfoBuildFactory myArgsInfoBuildFactory = MyArgsInfo.init();
            myArgsInfoBuildFactory.addMyArgsItemInfo("alter_user", true,"String","[a-z]*.[a-z]*", "告警接收人")
                    .addMyArgsItemInfo("alter_type", true,"enum","1|2|3", "1:邮件，2:企业微信，3邮件+企业微信")
                    .addMyArgsItemInfo("counttype", true,"enum","A0001|A0002|A0003|A0004|A0005", "计算类型")
                    .addMyArgsItemInfo("count_column", true,"String","[a-zA-Z0-9_]*", "列名")
                    .addMyArgsItemInfo("databases", true,"String","(hive|mysql|kylin|clickhouse|hbase).[a-z_]*.[a-z_]*", "hive.ods.ods_user_active_di  限定数据库类型、库名、表明")
                    .addMyArgsItemInfo("dt", false,"date","yyyyMMdd", "时间")
                    .addMyArgsItemInfo("filter_column", true,"String","[a-zA-Z0-9_\\|]*", "|分割    接受多个字段")
                    .addMyArgsItemInfo("filter_column_value", true,"String","[a-zA-Z0-9_\\|]*", "|分割    接受多个字段")
                    .addMyArgsItemInfo("sql", false,"String","[a-zA-Z\\*\\s]*", "自定义SQL")
                    .addMyArgsItemInfo("assert_type", true,"enum","eq|lt|gt|le|ge|ne", "eq(==), lt(<), gt(>), le(<=), ge(>=), ne(!=)")
                    .addMyArgsItemInfo("assert_Stringue", true,"float","-2099999999|2099999999", "限定数值")
                    .addMyArgsItemInfo("assert_rate", true,"float","0|1", "限定比率");
            return myArgsInfoBuildFactory.build();
        }
        public void myArgsValueInit(String[] args){
            for (int i = 0; i < args.length; i++) {
                String argString = args[i].substring(1,args[i].length());
                String argName = argString.split("=")[0];
                String argValue = argString.split("=")[1];

                switch (argName){
                    case "alter_user" : this.alter_user(argValue);break;
                    case "alter_type" : this.alter_type(argValue);break;
                    case "counttype" : this.counttype(argValue);break;
                    case "count_column" : this.count_column(argValue);break;
                    case "databases" : this.databases(argValue);break;
                    case "dt" : this.dt(argValue);break;
                    case "filter_column" : this.filter_column(argValue);break;
                    case "filter_column_value" : this.filter_column_value(argValue);break;
                    case "sql" : this.sql(argValue);break;
                    case "assert_type" : this.assert_type(argValue);break;
                    case "assert_Stringue" : this.assert_Stringue(argValue);break;
                    case "assert_rate" : this.assert_rate(argValue);break;
                }
            }
        }
        //主要方法
        public MyArgs build(String[] args){
            List myArgsInfo = myArgsItemInfoInit();  //将列信息初始化
            myArgsValueInit(args);                                   //将参数命令行过来的值初始化
            checkArgs(myArgsInfo);                                   //检查命令行过来的值是否符合  列表达式
            return new MyArgs(this);
        }


        public MyArgsBuildFactory alter_user(String alter_user) {
            this.alter_user = alter_user;
            return this;
        }
        public MyArgsBuildFactory alter_type(String alter_type) {
            this.alter_type = alter_type;
            return this;
        }
        public MyArgsBuildFactory counttype(String counttype) {
            this.counttype = counttype;
            return this;
        }
        public MyArgsBuildFactory count_column(String count_column) {
            this.count_column = count_column;
            return this;
        }
        public MyArgsBuildFactory databases(String databases) {
            this.databases = databases;
            return this;
        }
        public MyArgsBuildFactory dt(String dt) {
            this.dt = dt;
            return this;
        }
        public MyArgsBuildFactory filter_column(String filter_column) {
            this.filter_column = filter_column;
            return this;
        }
        public MyArgsBuildFactory filter_column_value(String filter_column_value) {
            this.filter_column_value = filter_column_value;
            return this;
        }
        public MyArgsBuildFactory sql(String sql) {
            this.sql = sql;
            return this;
        }
        public MyArgsBuildFactory assert_type(String assert_type) {
            this.assert_type = assert_type;
            return this;
        }
        public MyArgsBuildFactory assert_Stringue(String assert_Stringue) {
            this.assert_Stringue = assert_Stringue;
            return this;
        }
        public MyArgsBuildFactory assert_rate(String assert_rate) {
            this.assert_rate = assert_rate;
            return this;
        }
    }
    public String getAlter_user() {
        return alter_user;
    }
    public String getAlter_type() {
        return alter_type;
    }
    public String getCounttype() {
        return counttype;
    }
    public String getCount_column() {
        return count_column;
    }
    public String getDatabases() {
        return databases;
    }
    public String getDt() {
        return dt;
    }
    public String getFilter_column() {
        return filter_column;
    }
    public String getFilter_column_value() {
        return filter_column_value;
    }
    public String getSql() {
        return sql;
    }
    public String getAssert_type() {
        return assert_type;
    }
    public String getAssert_Stringue() {
        return assert_Stringue;
    }
    public String getAssert_rate() {
        return assert_rate;
    }
    @Override
    public String toString() {
        return "MyArgs{" +
                "alter_user='" + alter_user + '\'' +
                ", alter_type=" + alter_type +
                ", counttype='" + counttype + '\'' +
                ", count_column='" + count_column + '\'' +
                ", databases='" + databases + '\'' +
                ", dt='" + dt + '\'' +
                ", filter_column='" + filter_column + '\'' +
                ", filter_column_value='" + filter_column_value + '\'' +
                ", sql='" + sql + '\'' +
                ", assert_type='" + assert_type + '\'' +
                ", assert_Stringue=" + assert_Stringue +
                ", assert_rate=" + assert_rate +
                '}';
    }
}