create table t_class(
c_Id number(10) primary key ,
stuName varchar2(50), --人名
c_Name varchar2(50), --课程名
c_Score number(10) --得分
)
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" 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使用decode函数进行转变
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" 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DECODE函数相当于一条件语句(IF).它将输入数值与函数中的参数列表相比较,根据输入值返回一个对应值。函数的
参数列表是由若干数值及其对应结果值组成的若干序偶形式。当然,如果未能与任何一个实参序偶匹配成功,则函数
也有默认的返回值。区别于SQL的其它函数,DECODE函数还能识别和操作空值.
其具体的语法格式如下:
DECODE(input_value,value,result[,value,result…][,default_result]);
其中:
input_value 试图处理的数值。DECODE函数将该数值与一系列的序偶相比较,以决定最后的返回结果
value 是一组成序偶的数值。如果输入数值与之匹配成功,则相应的结果将被返回。
对应一个空的返回值,可以使用关键字NULL于之对应
result 是一组成序偶的结果值
default_result 未能与任何一序偶匹配成功时,函数返回的默认值 下面的例子说明了,如何读取用户CHECKUP表SEAPARK中的BLOOD_TEST_FLAG列下的项目,作为DECODE函数的实参支持值。
SELECT checkup_type,
DECODE(blood_test_flag,’Y’,’Yes’,’N’,’No’,NULL,’None’,’Invalid’)
FROM checkup;
select stuName,decode(c_name,'语文',c_score,'数学',c_score,'默认') from t_class;