PL/pgSQL:更新触发器中N列的一般方法? [英] PL/pgSQL: General Way to Update N Columns in Trigger?
问题描述
我正在尝试创建一个将采用常规表并将N列转换为大写的函数.对于这种类型的问题,我还没有运气,但是我能够提出以下建议:
I am attempting create a function that will take a general table and convert N columns to upper case. I haven't had any luck finding a solution to this type of problem, but I was able to come up with the following:
create or replace function uc_on_insert()
returns trigger as
$$
declare
p_tbl varchar = TG_TABLE_NAME;
p_sch varchar = TG_TABLE_SCHEMA;
i varchar;
begin
for i in
(select column_name
from INFORMATION_SCHEMA.COLUMNS
where 1=1
and table_name ilike p_tbl
and table_schema ilike p_sch
and data_type ='character varying')
loop
execute 'new.' || i || ' = upper(new.' || i || ');';
return new;
end loop;
end;
$$ language plpgsql;
我当前收到此错误:
ERROR: syntax error at or near "new"
LINE 1: new.c1 = upper(new.c1);
^
QUERY: new.c1 = upper(new.c1);
预期输入将是在任何具有此触发器的表上:
The expected input would be, on any table I have this trigger:
insert into table_one('a', 'b');
>> A, B
,如果我将此触发器放在另一个表上:
and if I put this trigger on another table:
insert into table_two ('a', 3);
>> A, 3
等
推荐答案
这是一个非常棘手的问题.
This is a very tricky question.
您的尝试必然会失败,因为当前行变量NEW
在EXECUTE
内部不可见.即使是,NEW
也是行类型(记录),而不是数组.与数组元素不同,行的字段不能由数字索引引用.这将导致SQL中的各种问题,因为(与数组相反)每个字段都可以具有不同的数据类型,并且SQL希望知道该数据类型可以事先处理.确实非常棘手.
Your attempt is bound to fail, because the current row variable NEW
is not visible inside EXECUTE
. And even if it was, NEW
is a row type (a record), not an array. Unlike array elements, fields of a row cannot be referenced by numerical index. This would cause all kinds of problems in SQL, because (as opposed to an array) each field can have a different data type, and SQL expects to know the data type to deal with beforehand. Very tricky indeed.
幸运的是,我们之前也处理过类似的问题:
Fortunately, we have dealt with a similar problem before:
您会在此处找到足够的说明.
适用于触发功能,并根据列的数据类型,它看起来像这样:
You'll find ample explanation there.
Adapted for a trigger function and depending on the data type of columns, it could look like this:
CREATE OR REPLACE FUNCTION trg_uc_on_insert()
RETURNS trigger AS
$func$
BEGIN
EXECUTE 'SELECT ' || array_to_string(ARRAY(
SELECT CASE WHEN atttypid = 'varchar'::regtype
-- atttypid = ANY('{text, bpchar, varchar}'::regtype[])
THEN 'upper(($1).' || quote_ident(attname)
|| ')::' || atttypid::regtype::text
ELSE '($1).' || quote_ident(attname)
END AS fld
FROM pg_catalog.pg_attribute
WHERE attrelid = pg_typeof(NEW)::text::regclass
AND attnum > 0
AND attisdropped = FALSE
ORDER BY attnum
), ',')
USING NEW
INTO NEW;
RETURN NEW;
END
$func$ LANGUAGE plpgsql;
如果您也想对其他基本字符类型应用相同的规则,请使用带注释的替代项.
If you want to apply the same rule to other basic character types as well, use the commented alternative.
CREATE TRIGGER trg_t_insbef
BEFORE INSERT
ON t -- works for any table
FOR EACH ROW
EXECUTE PROCEDURE trg_uc_on_insert();
只要您仅在表中使用简单类型,并且要大写所有字符数据,还有另一种粗略,快速且简单的方法:将整行强制转换为text
,将大写文本表示形式转换为行类型,并用结果更新NEW
.有关表格行类型的详细信息
As long as you are using simple types in your tables only and want to upper-case all character data, there is another crude, fast and simple method: Cast the whole row to text
, upper-case the text representation, cast back to the row type and update NEW
with the result. Details about the row type of a table
触发功能
CREATE OR REPLACE FUNCTION trg_uc_simple_on_insert()
RETURNS trigger AS
$func$
BEGIN
EXECUTE 'SELECT ($1::' || pg_typeof(NEW) || ').*'
USING upper(NEW::text)
INTO NEW;
RETURN NEW;
END
$func$ LANGUAGE plpgsql;
我们必须分解行类型,因为SELECT INTO
一对一地分配目标行类型的各个字段.我们不能一次分配整行.如果仔细观察,通用"解决方案的效果相同,不太明显.
We have to decompose the row type, because SELECT INTO
assigns individual fields of a target row type one-by-one. We cannot assign the whole row at once. If you look closely, the "generic" solution does the same, less obvious.
尽管字符数据在文本表示中区分大小写,但其他基本数字或日期/时间数据类型则不区分大小写.因此,简单的方法可以可靠地工作.可能也适用于大多数其他类型.但是我没有与其他人一起测试,当然也有例外.您必须验证所使用的数据类型.
While character data is case-sensitive in text representation, other basic numeric or date / time data types are not. So the simple method works reliably. Probably with most other types, too. But I did not test with others, and there certainly are exception. You'll have to verify for the data types you use.
此外,尽管代码比通用方法短得多并且更简单,但这不一定会更快,尤其是对于许多未受影响的列.不过,在简单的情况下,它可能要快得多.
Also, while the code is much shorter and simpler than with the generic method, this is not necessarily faster, especially with lots of unaffected columns. It's probably a lot faster in simple cases, though.
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