Hive函数：GROUPING SETS,GROUPING__ID,CUBE,ROLLUP

参考：lxw大数据田地：http://lxw1234.com/archives/2015/04/193.htm

数据准备：

CREATE EXTERNAL TABLE test_data (
month STRING,
day STRING,
cookieid STRING
) ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
stored as textfile location '/user/jc_rc_ftp/test_data';

select * from test_data l;
+----------+-------------+-------------+--+
| l.month  |    l.day    | l.cookieid  |
+----------+-------------+-------------+--+
| 2015-03  | 2015-03-10  | cookie1     |
| 2015-03  | 2015-03-10  | cookie5     |
| 2015-03  | 2015-03-12  | cookie7     |
| 2015-04  | 2015-04-12  | cookie3     |
| 2015-04  | 2015-04-13  | cookie2     |
| 2015-04  | 2015-04-13  | cookie4     |
| 2015-04  | 2015-04-16  | cookie4     |
| 2015-03  | 2015-03-10  | cookie2     |
| 2015-03  | 2015-03-10  | cookie3     |
| 2015-04  | 2015-04-12  | cookie5     |
| 2015-04  | 2015-04-13  | cookie6     |
| 2015-04  | 2015-04-15  | cookie3     |
| 2015-04  | 2015-04-15  | cookie2     |
| 2015-04  | 2015-04-16  | cookie1     |
+----------+-------------+-------------+--+
14 rows selected (0.249 seconds)

GROUPING SETS

在一个GROUP BY查询中，根据不同的维度组合进行聚合，等价于将不同维度的GROUP BY结果集进行UNION ALL

SELECT
month,
day,
COUNT(DISTINCT cookieid) AS uv,
GROUPING__ID
FROM test_data
GROUP BY month,day
GROUPING SETS (month,day)
ORDER BY GROUPING__ID;

等价于
SELECT month,NULL,COUNT(DISTINCT cookieid) AS uv,1 AS GROUPING__ID FROM test_data GROUP BY month
UNION ALL
SELECT NULL,day,COUNT(DISTINCT cookieid) AS uv,2 AS GROUPING__ID FROM test_data GROUP BY day

+----------+-------------+-----+---------------+--+
|  month   |     day     | uv  | grouping__id  |
+----------+-------------+-----+---------------+--+
| 2015-04  | NULL        | 6   | 1             |
| 2015-03  | NULL        | 5   | 1             |
| NULL     | 2015-04-16  | 2   | 2             |
| NULL     | 2015-04-15  | 2   | 2             |
| NULL     | 2015-04-13  | 3   | 2             |
| NULL     | 2015-04-12  | 2   | 2             |
| NULL     | 2015-03-12  | 1   | 2             |
| NULL     | 2015-03-10  | 4   | 2             |
+----------+-------------+-----+---------------+--+
8 rows selected (177.299 seconds)

SELECT
month,
day,
COUNT(DISTINCT cookieid) AS uv,
GROUPING__ID
FROM test_data
GROUP BY month,day
GROUPING SETS (month,day,(month,day))
ORDER BY GROUPING__ID;

等价于
SELECT month,NULL,COUNT(DISTINCT cookieid) AS uv,1 AS GROUPING__ID FROM test_data GROUP BY month
UNION ALL
SELECT NULL,day,COUNT(DISTINCT cookieid) AS uv,2 AS GROUPING__ID FROM test_data GROUP BY day
UNION ALL
SELECT month,day,COUNT(DISTINCT cookieid) AS uv,3 AS GROUPING__ID FROM test_data GROUP BY month,day
+----------+-------------+-----+---------------+--+
|  month   |     day     | uv  | grouping__id  |
+----------+-------------+-----+---------------+--+
| 2015-04  | NULL        | 6   | 1             |
| 2015-03  | NULL        | 5   | 1             |
| NULL     | 2015-03-10  | 4   | 2             |
| NULL     | 2015-04-16  | 2   | 2             |
| NULL     | 2015-04-15  | 2   | 2             |
| NULL     | 2015-04-13  | 3   | 2             |
| NULL     | 2015-04-12  | 2   | 2             |
| NULL     | 2015-03-12  | 1   | 2             |
| 2015-04  | 2015-04-16  | 2   | 3             |
| 2015-04  | 2015-04-12  | 2   | 3             |
| 2015-04  | 2015-04-13  | 3   | 3             |
| 2015-03  | 2015-03-12  | 1   | 3             |
| 2015-03  | 2015-03-10  | 4   | 3             |
| 2015-04  | 2015-04-15  | 2   | 3             |
+----------+-------------+-----+---------------+--+

备注：其中的 GROUPING__ID，表示结果属于哪一个分组集合。

CUBE

根据GROUP BY的维度的所有组合进行聚合。

SELECT
month,
day,
COUNT(DISTINCT cookieid) AS uv,
GROUPING__ID
FROM test_data
GROUP BY month,day
WITH CUBE
ORDER BY GROUPING__ID;

等价于
SELECT NULL,NULL,COUNT(DISTINCT cookieid) AS uv,0 AS GROUPING__ID FROM test_data
UNION ALL
SELECT month,NULL,COUNT(DISTINCT cookieid) AS uv,1 AS GROUPING__ID FROM test_data GROUP BY month
UNION ALL
SELECT NULL,day,COUNT(DISTINCT cookieid) AS uv,2 AS GROUPING__ID FROM test_data GROUP BY day
UNION ALL
SELECT month,day,COUNT(DISTINCT cookieid) AS uv,3 AS GROUPING__ID FROM test_data GROUP BY month,day
+----------+-------------+-----+---------------+--+
|  month   |     day     | uv  | grouping__id  |
+----------+-------------+-----+---------------+--+
| NULL     | NULL        | 7   | 0             |
| 2015-03  | NULL        | 5   | 1             |
| 2015-04  | NULL        | 6   | 1             |
| NULL     | 2015-04-16  | 2   | 2             |
| NULL     | 2015-04-15  | 2   | 2             |
| NULL     | 2015-04-13  | 3   | 2             |
| NULL     | 2015-04-12  | 2   | 2             |
| NULL     | 2015-03-12  | 1   | 2             |
| NULL     | 2015-03-10  | 4   | 2             |
| 2015-04  | 2015-04-12  | 2   | 3             |
| 2015-04  | 2015-04-16  | 2   | 3             |
| 2015-03  | 2015-03-12  | 1   | 3             |
| 2015-03  | 2015-03-10  | 4   | 3             |
| 2015-04  | 2015-04-15  | 2   | 3             |
| 2015-04  | 2015-04-13  | 3   | 3             |
+----------+-------------+-----+---------------+--+

ROLLUP

是CUBE的子集，以最左侧的维度为主，从该维度进行层级聚合。

比如，以month维度进行层级聚合：
SELECT
month,
day,
COUNT(DISTINCT cookieid) AS uv,
GROUPING__ID
FROM test_data
GROUP BY month,day
WITH ROLLUP
ORDER BY GROUPING__ID;
可以实现这样的上钻过程：月天的UV->月的UV->总UV
+----------+-------------+-----+---------------+--+
|  month   |     day     | uv  | grouping__id  |
+----------+-------------+-----+---------------+--+
| NULL     | NULL        | 7   | 0             |
| 2015-04  | NULL        | 6   | 1             |
| 2015-03  | NULL        | 5   | 1             |
| 2015-04  | 2015-04-16  | 2   | 3             |
| 2015-04  | 2015-04-15  | 2   | 3             |
| 2015-04  | 2015-04-13  | 3   | 3             |
| 2015-04  | 2015-04-12  | 2   | 3             |
| 2015-03  | 2015-03-12  | 1   | 3             |
| 2015-03  | 2015-03-10  | 4   | 3             |
+----------+-------------+-----+---------------+--+

--把month和day调换顺序，则以day维度进行层级聚合：
SELECT
day,
month,
COUNT(DISTINCT cookieid) AS uv,
GROUPING__ID
FROM test_data
GROUP BY day,month
WITH ROLLUP
ORDER BY GROUPING__ID;
+-------------+----------+-----+---------------+--+
|     day     |  month   | uv  | grouping__id  |
+-------------+----------+-----+---------------+--+
| NULL        | NULL     | 7   | 0             |
| 2015-04-12  | NULL     | 2   | 1             |
| 2015-04-15  | NULL     | 2   | 1             |
| 2015-03-12  | NULL     | 1   | 1             |
| 2015-04-16  | NULL     | 2   | 1             |
| 2015-03-10  | NULL     | 4   | 1             |
| 2015-04-13  | NULL     | 3   | 1             |
| 2015-04-16  | 2015-04  | 2   | 3             |
| 2015-04-15  | 2015-04  | 2   | 3             |
| 2015-04-13  | 2015-04  | 3   | 3             |
| 2015-03-12  | 2015-03  | 1   | 3             |
| 2015-03-10  | 2015-03  | 4   | 3             |
| 2015-04-12  | 2015-04  | 2   | 3             |
+-------------+----------+-----+---------------+--+

可以实现这样的上钻过程：
天月的UV->天的UV->总UV
（这里，根据天和月进行聚合，和根据天聚合结果一样，因为有父子关系，如果是其他维度组合的话，就会不一样）