Redshift将单个动态列拆分为新表中的多行 [英] Redshift split single dynamic column into multiple rows in new table

问题描述

使用如下表:

       uid               |            segmentids
-------------------------+----------------------------------------
 f9b6d54b-c646-4bbb-b0ec | 4454918|4455158|4455638|4455878|4455998
 asd7a0s9-c646-asd7-b0ec | 1265899|1265923|1265935|1266826|1266596
 gd3355ff-cjr8-assa-fke0 | 2237557|2237581|2237593
 laksnfo3-kgi5-fke0-b0ec | 4454918|4455158|4455638|4455878

如何使用以下方法创建新表

How to create a new table with:

      uid               |         segmentids
-------------------------+---------------------------
 f9b6d54b-c646-4bbb-b0ec |           4454918
 f9b6d54b-c646-4bbb-b0ec |           1265899
 f9b6d54b-c646-4bbb-b0ec |           2237557
 f9b6d54b-c646-4bbb-b0ec |           4454918
 f9b6d54b-c646-4bbb-b0ec |           4454918
 asd7a0s9-c646-asd7-b0ec |           1265899
 asd7a0s9-c646-asd7-b0ec |           1265923
 asd7a0s9-c646-asd7-b0ec |           1265935 
 asd7a0s9-c646-asd7-b0ec |           1266826
 asd7a0s9-c646-asd7-b0ec |           1266596

段的数量是动态的，可以随每个记录而变化. 我尝试使用带分隔符的Split函数，但是它需要字符串中的索引，在这里是动态的.

The number of segments are dynamic, can vary with each record. I tried the Split function with delimiter, but it requires the index in string, which is dynamic here.

有什么建议吗?

推荐答案

这是Redshift答案，它将与每行多达1万个细分ID值一​​起使用.

Here is the Redshift answer, it will work with up to 10 thousand segment ids values per row.

测试数据

create table test_split (uid varchar(50),segmentids varchar(max));
insert into test_split
    values
      ('f9b6d54b-c646-4bbb-b0ec','4454918|4455158|4455638|4455878|4455998'),
      ('asd7a0s9-c646-asd7-b0ec','1265899|1265923|1265935|1266826|1266596'),
      ('asd7345s9-c646-asd7-b0ec','1235935|1263456|1265675696'),
      ('as345a0s9-c646-asd7-b0ec','12765899|12658883|12777935|144466826|1266226|12345')
;

代码

with ten_numbers as (select 1 as num union select 2 union select 3 union select 4 union select 5 union select 6 union select 7 union select 8 union select 9 union select 0)
  , generted_numbers AS
(
    SELECT (1000 * t1.num) + (100 * t2.num) + (10 * t3.num) + t4.num AS gen_num
    FROM ten_numbers AS t1
      JOIN ten_numbers AS t2 ON 1 = 1
      JOIN ten_numbers AS t3 ON 1 = 1
      JOIN ten_numbers AS t4 ON 1 = 1
)
  , splitter AS
(
    SELECT *
    FROM generted_numbers
    WHERE gen_num BETWEEN 1 AND (SELECT max(REGEXP_COUNT(segmentids, '\\|') + 1)
                                 FROM test_split)
)
  --select * from splitter;
  , expanded_input AS
(
    SELECT
      uid,
      split_part(segmentids, '|', s.gen_num) AS segment
    FROM test_split AS ts
      JOIN splitter AS s ON 1 = 1
    WHERE split_part(segmentids, '|', s.gen_num) <> ''
)
SELECT * FROM expanded_input;

前2个cte步骤(ten_numbers和generate_numbers)用于生成许多行，这是必需的，因为不支持generate_series

the first 2 cte steps (ten_numbers and generated_numbers) are used to generate a number of rows, this is needed because generate_series is not supported

下一步(分隔符)只需要等于最大分隔符+ 1(即段的最大数目)的行数​​

The next step (splitter) just takes a number of rows equal to the max number of delimiters + 1 (which is the max number of segments)

最后，我们将输入数据与交叉分割器交叉，使用split_part获取相关值，然后排除空白部分(这是因为该行的段数小于或等于最大段数)

finally, we cross join splitter with the input data, take the related value using split_part and then exclude blank parts (which are caused where the row has < the max number of segments)

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