sql - 每组 LIMIT - Google BigQuery/标准 SQL

Question

我有一个如下表(示例 here ):

CREATE TABLE topics (
  name varchar(64),
  url varchar(253),
  statistic integer,
  pubdate timestamp
);

INSERT INTO topics VALUES
('a',  'b',  100,  TIMESTAMP '2011-05-16 15:36:38'),  
('a',  'c',  110,  TIMESTAMP '2014-04-01 00:00:00'),  
('a',  'd',  120,  TIMESTAMP '2014-04-01 00:00:00'),  
('a',  'e',  90,   TIMESTAMP '2011-05-16 15:36:38'), 
('a',  'f',  80,   TIMESTAMP '2014-04-01 00:00:00'), 
('a',  'g',  70,   TIMESTAMP '2011-05-16 15:36:38'), 
('a',  'h',  150,  TIMESTAMP '2014-04-01 00:00:00'),  
('a',  'i',  50,   TIMESTAMP '2011-05-16 15:36:38'), 
('b',  'j',  10,   TIMESTAMP '2014-04-01 00:00:00'), 
('b',  'k',  11,   TIMESTAMP '2011-05-16 15:36:38'), 
('b',  'l',  12,   TIMESTAMP '2014-04-01 00:00:00'), 
('b',  'm',  9,    TIMESTAMP '2011-05-16 15:36:38'),
('b',  'n',  8,    TIMESTAMP '2014-04-01 00:00:00'),
('b',  'o',  7,    TIMESTAMP '2011-05-16 15:36:38'),
('b',  'p',  15,   TIMESTAMP '2014-04-01 00:00:00'), 
('b',  'q',  5,    TIMESTAMP '2011-05-16 15:36:38'),
('b',  'r',  2,    TIMESTAMP '2014-04-01 00:00:00')

我想根据每个 (name, date(pubdate)) 组合的 statistic 值来获取前两行。

换句话说，我想GROUP BY name, date(pubdate)，但没有聚合函数，结果只是根据它们的获取前两行每组的统计。 (所以，我知道它并不是真正的 GROUP BY，而是 greatest-n-per-group。)

我正在使用带有标准 SQL 的 Google Big Query。我看过其他一些 solutions但我不确定在这种情况下如何实现结果。

期望的结果:

name    url     statistic   date

a       b       100         2011-05-16
a       e       90          2011-05-16

a       h       150         2014-04-01
a       d       120         2014-04-01

b       m       9           2011-05-16
b       k       11          2011-05-16

b       l       12          2014-04-01
b       p       15          2014-04-01

Answer 1

以下是 BigQuery 标准 SQL

#standardSQL
SELECT * EXCEPT(arr) FROM (
  SELECT name, DATE(pubdate) day, 
    ARRAY_AGG(STRUCT(url, statistic) ORDER BY statistic DESC LIMIT 2) arr
  FROM `project.dataset.table`   
  GROUP BY name, day
), UNNEST(arr)
-- ORDER BY name, day  

您可以使用问题中的样本数据进行测试，如以下示例所示

#standardSQL
WITH `project.dataset.table` AS (
  SELECT 'a' name, 'b' url,  100 statistic,  TIMESTAMP '2011-05-16 15:36:38' pubdate UNION ALL  
  SELECT 'a', 'c',  110,  '2014-04-01 00:00:00' UNION ALL  
  SELECT 'a', 'd',  120,  '2014-04-01 00:00:00' UNION ALL  
  SELECT 'a', 'e',  90,   '2011-05-16 15:36:38' UNION ALL 
  SELECT 'a', 'f',  80,   '2014-04-01 00:00:00' UNION ALL 
  SELECT 'a', 'g',  70,   '2011-05-16 15:36:38' UNION ALL 
  SELECT 'a', 'h',  150,  '2014-04-01 00:00:00' UNION ALL  
  SELECT 'a', 'i',  50,   '2011-05-16 15:36:38' UNION ALL 
  SELECT 'b', 'j',  10,   '2014-04-01 00:00:00' UNION ALL 
  SELECT 'b', 'k',  11,   '2011-05-16 15:36:38' UNION ALL 
  SELECT 'b', 'l',  12,   '2014-04-01 00:00:00' UNION ALL 
  SELECT 'b', 'm',  9,    '2011-05-16 15:36:38' UNION ALL
  SELECT 'b', 'n',  8,    '2014-04-01 00:00:00' UNION ALL
  SELECT 'b', 'o',  7,    '2011-05-16 15:36:38' UNION ALL
  SELECT 'b', 'p',  15,   '2014-04-01 00:00:00' UNION ALL 
  SELECT 'b', 'q',  5,    '2011-05-16 15:36:38' UNION ALL
  SELECT 'b', 'r',  2,    '2014-04-01 00:00:00' 
)
SELECT * EXCEPT(arr) FROM (
  SELECT name, DATE(pubdate) day, 
    ARRAY_AGG(STRUCT(url, statistic) ORDER BY statistic DESC LIMIT 2) arr
  FROM `project.dataset.table`  
  GROUP BY name, day
), UNNEST(arr)
ORDER BY name, day   

结果

Row name    day         url statistic    
1   a       2011-05-16  b   100  
2   a       2011-05-16  e   90   
3   a       2014-04-01  h   150  
4   a       2014-04-01  d   120  
5   b       2011-05-16  k   11   
6   b       2011-05-16  m   9    
7   b       2014-04-01  p   15   
8   b       2014-04-01  l   12