红移.将逗号分隔的值转换为行 [英] Redshift. Convert comma delimited values into rows
问题描述
我想知道如何在Redshift中将以逗号分隔的值转换为行.恐怕我自己的解决方案不是最佳的.请指教.我有带有逗号分隔值的列之一的表.例如:
I am wondering how to convert comma-delimited values into rows in Redshift. I am afraid that my own solution isn't optimal. Please advise. I have table with one of the columns with coma-separated values. For example:
我有:
user_id|user_name|user_action
-----------------------------
1 | Shone | start,stop,cancell...
我想看
user_id|user_name|parsed_action
-------------------------------
1 | Shone | start
1 | Shone | stop
1 | Shone | cancell
....
推荐答案
对现有答案的一点改进是使用第二个数字"表,该表枚举了所有可能的列表长度,然后使用cross join
进行查询更加紧凑.
A slight improvement over the existing answer is to use a second "numbers" table that enumerates all of the possible list lengths and then use a cross join
to make the query more compact.
我知道,Redshift没有创建数字表的简单方法,但是我们可以使用
Redshift does not have a straightforward method for creating a numbers table that I am aware of, but we can use a bit of a hack from https://www.periscope.io/blog/generate-series-in-redshift-and-mysql.html to create one using row numbers.
具体来说,如果我们假设cmd_logs
中的行数大于user_action
列中的最大逗号数,则可以通过对行进行计数来创建数字表.首先,假设user_action
列中最多有99个逗号:
Specifically, if we assume the number of rows in cmd_logs
is larger than the maximum number of commas in the user_action
column, we can create a numbers table by counting rows. To start, let's assume there are at most 99 commas in the user_action
column:
select
(row_number() over (order by true))::int as n
into numbers
from cmd_logs
limit 100;
如果想花哨的话,我们可以从cmd_logs
表中计算逗号的数量,以在numbers
中创建更精确的行集:
If we want to get fancy, we can compute the number of commas from the cmd_logs
table to create a more precise set of rows in numbers
:
select
n::int
into numbers
from
(select
row_number() over (order by true) as n
from cmd_logs)
cross join
(select
max(regexp_count(user_action, '[,]')) as max_num
from cmd_logs)
where
n <= max_num + 1;
一旦有一个numbers
表,我们就可以做到:
Once there is a numbers
table, we can do:
select
user_id,
user_name,
split_part(user_action,',',n) as parsed_action
from
cmd_logs
cross join
numbers
where
split_part(user_action,',',n) is not null
and split_part(user_action,',',n) != '';
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