在PostgreSQL上以正确的顺序对数组元素进行分组

时间:2016-03-16 16:07:37

标签: sql arrays postgresql gaps-and-islands

是否可以在PostgreSQL中对数组元素进行分组?

示例,我有2个这样的相关数组(我说是相关的,因为第一个数组表示动作而第二个数组代表那些动作的时间:

col0 = 'any_value'
col1 = array1['a','b','b','c','c','a','a','a','c']
col2 = array2[1,2,3,4,5,6,7,8,9]

我想输出以下结果:

col0 = 'any_value'
array_result1['a','b','c','a','c']    
array_result2[1,2,4,6,9]

数组可以被取消的方法是使用normalality,这是一个示例查询,但它返回一个不同的数组元素选择,删除重复的数组:

select col0, 
       array_agg(x order by rn) as unique_array1
        from (
              select 
              distinct on (col0, a.x) col0, 
                           a.x, 
                           a.rn
              from table_a, 
                   unnest(array1) with ordinality as a (x,rn)
              order by 1,2,3  
             ) unnested_ordered
group by col0;

所以结果就是:

col0 = 'any_value'
array_result1['a','b','c']    

但是你可以看到它缺少很多元素。

修改

要描述更多我的问题,最后我想知道最初完成每个array_result1操作的时间。 所以对于示例结果

array_result1['a','b','c','a','c']    
*array_result2[1,2,4,6,9]

*我说数组的位置从1开始而不是0,我也修复了最后一个元素,它应该是9而不是7

会帮助我知道,第一次采取行动的时间是什么?'发生了,第二次行动是什么时候发生的?' a'发生这样我就可以计算出行动的时间' a'回到我正在建设的道路上。 所以第一次采取行动' a'发生了= 1 第二次发生的事情是= 6

所以行动' a'在路径(数组)中出现两次,重新出现需要5个时间单位。这就是为什么我需要第二个数组,其中包含动作发生的时间(每个动作第一次发生)

1 个答案:

答案 0 :(得分:1)

您可以使用LATERAL并使用ROW_NUMBER计算群组:

DROP TABLE IF EXISTS table_a;
CREATE TABLE table_a(col0 VARCHAR(10), col1 text[],col2 int[]);

INSERT INTO table_a(col0, col1, col2)
VALUES ('any_value',array['a','b','b','c','c','a','a','a','c'],
        array[1,2,3,4,5,6,7,8,9]);

主要查询:

SELECT col0,
       col1,
       unique_col1
FROM table_a,
LATERAL (SELECT ARRAY_AGG(x ORDER BY grp) AS unique_col1
         FROM ( SELECT DISTINCT x,
                 rn - ROW_NUMBER() OVER(PARTITION BY x ORDER BY rn) AS grp
               FROM unnest(col1) WITH ORDINALITY AS a(x,rn)
         ) AS sub      
) AS lat1

输出:

enter image description here

修改

计算第二个数组:

SELECT col0,
       col1,
       unique_col1,
       col2,
       unique_col2
FROM table_a,
LATERAL (SELECT ARRAY_AGG(x ORDER BY grp) AS unique_col1
         FROM ( SELECT DISTINCT x,
                 rn - ROW_NUMBER() OVER(PARTITION BY x ORDER BY rn) AS grp
               FROM unnest(col1) WITH ORDINALITY AS a(x,rn)
         ) AS sub      
) AS lat1,
LATERAL (
   SELECT array_agg(x ORDER BY rn) AS unique_col2
   FROM unnest(col2) WITH ORDINALITY AS b(x,rn)
   WHERE rn IN (
         SELECT SUM(c) OVER(ORDER BY grp) - (c-1) AS result
         FROM (SELECT grp,  COUNT(*) AS c
               FROM ( SELECT x,
                             rn - ROW_NUMBER() OVER(PARTITION BY x ORDER BY rn)  AS grp
                      FROM unnest(col1) WITH ORDINALITY AS a(x,rn)
               ) AS sub     
          GROUP BY grp) AS s
    )      
) AS lat2

enter image description here

注:

它从值生成第二个数组,而不是它的位置,所以当你有:

col2 = array[9,8,7,6,5,4,3,2,1]

你会得到:

[9,8,6,4,1]

如果您只想要使用的职位:

...
LATERAL (
   SELECT array_agg(result ORDER BY result) AS unique_col2
   FROM (
         SELECT SUM(c) OVER(ORDER BY grp) - (c-1) AS result
         FROM (SELECT grp,  COUNT(*) AS c
               FROM ( SELECT x,
                             rn - ROW_NUMBER() OVER(PARTITION BY x ORDER BY rn) AS grp
                      FROM unnest(col1) WITH ORDINALITY AS a(x,rn)
               ) AS sub     
          GROUP BY grp) AS s
    ) AS s1    
) AS lat2

结果将是:

[1,2,4,6,9]

编辑2

在上面的版本中有一个小错误。 ARRAY_AGG应按rn而不是grp订购:

DROP TABLE IF EXISTS table_a;
CREATE TABLE table_a(col0 VARCHAR(10), col1 text[],col2 int[]);

INSERT INTO table_a(col0, col1, col2)
VALUES ('any_value',array['a','b','b','c','c','a','a','a','c'],
        array[1,2,3,4,5,6,7,8,9]);

INSERT INTO table_a(col0, col1, col2)
VALUES ('any_value2',array['a','b','a','a','c','a'],array[1,2,3,4,5,6]);        


SELECT *
FROM table_a,
LATERAL (SELECT ARRAY_AGG(x ORDER BY rn) AS unique_col1
         FROM
           (SELECT x, grp, MIN(rn) AS rn
            FROM (SELECT  x,
                       rn - ROW_NUMBER() OVER(PARTITION BY x ORDER BY rn) AS grp,
                       rn
                  FROM unnest(col1) WITH ORDINALITY AS a(x,rn)
           ) AS sub
         GROUP BY x, grp) AS s      
        ) AS lat1; 

enter image description here