debezium详解decimal.handling.mode

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decimal.handling.mode配置的作用，是配置数据库中浮点类型映射类型，
数据库浮点类型包含以下：
mysql：double\float\decimal
oracle: number

以下是来自debezium官网的原文介绍：
https://debezium.io/documentation/reference/2.5/connectors/mysql.html#mysql-connector-properties
这个配置项在debezium的版本迭代中几乎没有变化

decimal.handling.mode

precise（默认值）

Specifies how the connector should handle values for DECIMAL and NUMERIC columns:

precise (the default) represents them precisely using java.math.BigDecimal values represented in change events in a binary form.

double represents them using double values, which may result in a loss of precision but is easier to use.

string encodes values as formatted strings, which is easy to consume but semantic information about the real type is lost.

下面提供一些示例数据，及数据使用方法
以mysql为示例

CREATE TABLE `doubleV` (
  `d18_0` decimal(18,0) DEFAULT NULL,
  `d18_5` decimal(18,5) DEFAULT NULL,
  `d18_10` decimal(18,10) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;

INSERT INTO testdb.doubleV (d18_0,d18_5,d18_10)
	VALUES (345678901234567890,456789012345.67890,456789.0123456789);

采集作业配置

        {
            "name":"mysql_04",
            "config":{
                "connector.class":"io.debezium.connector.mysql.MySqlConnector",
                "tasks.max":"1",
                "database.hostname":"192.168.1.226",
                "database.port":"3306",
                "database.user":"root",
                "database.password":"123456",
                "database.server.name":"mysqlcdc",
                "table.include.list":"testdb.doubleV",
                "topic.prefix": "mysqlcdc",
                "database.server.id": "1",
                "decimal.handling.mode":"string",
                "schema.history.internal.kafka.bootstrap.servers":"192.168.1.103:9092",
                "schema.history.internal.kafka.topic":"mysqlcdc.history",
                "snapshot.mode":"schema_only",
                "include.schema.changes": "true"

            }
        }

字段名	原始数据	string	double	precise	precise 反序列化后
d18_0	345678901234567890	“345678901234567890”	3.4567890123456787E17	“BMwZIRJvCtI=”	345678901234567890
d18_5	456789012345.67890	“456789012345.67890”	4.567890123456789E11	“AKJIt/nRCtI=”	456789012345.67890
d18_10	456789.0123456789	“456789.0123456789”	456789.0123456789	“EDp4zC6BFQ==”	456789.0123456789
优点	-	可读性强	类型一致	-	类型一致，精度不丢失
缺点	-	类型不一致	丢失精度，可读性差	可读性差	需反序列化

    
    public static void main(String[] args) {
    	printDePrecise("BMwZIRJvCtI=", 0);
    	printDePrecise("AKJIt/nRCtI=", 5);
    	printDePrecise("EDp4zC6BFQ==", 10);
	}
    
    static void printDePrecise (String encoded, int scale) {
    	final BigDecimal decoded = new BigDecimal(new BigInteger(Base64.getDecoder().decode(encoded)), scale);
    	System.out.println(String.format("encoded: %s, scale: %s, decoded: %s", encoded, scale, decoded));
    }