问题描述
使用Redshift时遇到了独特的问题.请参见以下说明性示例:
I encountered unique problem when using Redshift. Please see the below illustrative example:
drop table if exists joinTrim_temp1;
create table joinTrim_temp1(rowIndex1 int, charToJoin1 varchar(20));
insert into joinTrim_temp1 values(1, 'Sudan' );
insert into joinTrim_temp1 values(2, 'Africa' );
insert into joinTrim_temp1 values(3, 'USA' );
drop table if exists joinTrim_temp2;
create table joinTrim_temp2(rowIndex2 int, charToJoin2 varchar(20));
insert into joinTrim_temp2 values(1, 'Sudan ' );
insert into joinTrim_temp2 values(2, 'Africa ' );
insert into joinTrim_temp2 values(3, 'USA ' );
select * from joinTrim_temp1 a join joinTrim_temp2 b on a.charToJoin1 = b.charToJoin2;
查询的输出如下:
在查询中，您可以看到第二个表中有一个尾随空格.因此，不应进行内部连接.但是似乎Redshift在加入时能够修剪尾随的空格.
In the query you can see that there is a trailing space in the second table. So no inner join should take place. But it seems that Redshift is able to trim the trailing whitespaces when joining.
在将现有的Redshift sql代码转换为PySpark时遇到了这个问题.
I encountered this problem, while converting the existing Redshift sql code to PySpark.
关于，库马尔
推荐答案
啊！确实，这是一个非常有趣的发现！
Ah! Indeed, a very interesting find!
来自字符类型-亚马逊Redshift :
看来，如果您想强制比较，是否需要避免尾随空格，例如:
It appears that, if you wish to force the comparison, would you need to avoid the trailing space, such as:
SELECT *
FROM joinTrim_temp1 a
JOIN joinTrim_temp2 b
ON a.charToJoin1 || '.' = b.charToJoin2 || '.';
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