GROUPING SETS,GROUPING__ID,CUBE,ROLLUP
这几个分析函数通常用于OLAP中，不能累加，而且需要根据不同维度上钻和下钻的指标统计，比如，分小时、天、月的UV数。
Hive版本为 apache-hive-0.13.1
数据准备：
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 CREATE EXTERNAL TABLE lxw1234 ( month STRING, day STRING, cookieid STRING ) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' stored as textfile location '/tmp/lxw11/'; hive> select * from lxw1234; OK 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
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 lxw1234 GROUP BY month,day GROUPING SETS (month,day) ORDER BY GROUPING__ID; month day uv GROUPING__ID ------------------------------------------------ 2015-03 NULL 5 1 2015-04 NULL 6 1 NULL 2015-03-10 4 2 NULL 2015-03-12 1 2 NULL 2015-04-12 2 2 NULL 2015-04-13 3 2 NULL 2015-04-15 2 2 NULL 2015-04-16 2 2 等价于 SELECT month,NULL,COUNT(DISTINCT cookieid) AS uv,1 AS GROUPING__ID FROM lxw1234 GROUP BY month UNION ALL SELECT NULL,day,COUNT(DISTINCT cookieid) AS uv,2 AS GROUPING__ID FROM lxw1234 GROUP BY day
再如：
SELECT month, day, COUNT(DISTINCT cookieid) AS uv, GROUPING__ID FROM lxw1234 GROUP BY month,day GROUPING SETS (month,day,(month,day)) ORDER BY GROUPING__ID; month day uv GROUPING__ID ------------------------------------------------ 2015-03 NULL 5 1 2015-04 NULL 6 1 NULL 2015-03-10 4 2 NULL 2015-03-12 1 2 NULL 2015-04-12 2 2 NULL 2015-04-13 3 2 NULL 2015-04-15 2 2 NULL 2015-04-16 2 2 2015-03 2015-03-10 4 3 2015-03 2015-03-12 1 3 2015-04 2015-04-12 2 3 2015-04 2015-04-13 3 3 2015-04 2015-04-15 2 3 2015-04 2015-04-16 2 3 等价于 SELECT month,NULL,COUNT(DISTINCT cookieid) AS uv,1 AS GROUPING__ID FROM lxw1234 GROUP BY month UNION ALL SELECT NULL,day,COUNT(DISTINCT cookieid) AS uv,2 AS GROUPING__ID FROM lxw1234 GROUP BY day UNION ALL SELECT month,day,COUNT(DISTINCT cookieid) AS uv,3 AS GROUPING__ID FROM lxw1234 GROUP BY month,day
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 lxw1234 GROUP BY month,day WITH CUBE ORDER BY GROUPING__ID; month day uv GROUPING__ID -------------------------------------------- NULL NULL 7 0 2015-03 NULL 5 1 2015-04 NULL 6 1 NULL 2015-04-12 2 2 NULL 2015-04-13 3 2 NULL 2015-04-15 2 2 NULL 2015-04-16 2 2 NULL 2015-03-10 4 2 NULL 2015-03-12 1 2 2015-03 2015-03-10 4 3 2015-03 2015-03-12 1 3 2015-04 2015-04-16 2 3 2015-04 2015-04-12 2 3 2015-04 2015-04-13 3 3 2015-04 2015-04-15 2 3 等价于 SELECT NULL,NULL,COUNT(DISTINCT cookieid) AS uv,0 AS GROUPING__ID FROM lxw1234 UNION ALL SELECT month,NULL,COUNT(DISTINCT cookieid) AS uv,1 AS GROUPING__ID FROM lxw1234 GROUP BY month UNION ALL SELECT NULL,day,COUNT(DISTINCT cookieid) AS uv,2 AS GROUPING__ID FROM lxw1234 GROUP BY day UNION ALL SELECT month,day,COUNT(DISTINCT cookieid) AS uv,3 AS GROUPING__ID FROM lxw1234 GROUP BY month,day
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 lxw1234 GROUP BY month,day WITH ROLLUP ORDER BY GROUPING__ID; month day uv GROUPING__ID --------------------------------------------------- NULL NULL 7 0 2015-03 NULL 5 1 2015-04 NULL 6 1 2015-03 2015-03-10 4 3 2015-03 2015-03-12 1 3 2015-04 2015-04-12 2 3 2015-04 2015-04-13 3 3 2015-04 2015-04-15 2 3 2015-04 2015-04-16 2 3 可以实现这样的上钻过程： 月天的UV->月的UV->总UV
--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 lxw1234 GROUP BY day,month WITH ROLLUP ORDER BY GROUPING__ID; day month uv GROUPING__ID ------------------------------------------------------- NULL NULL 7 0 2015-04-13 NULL 3 1 2015-03-12 NULL 1 1 2015-04-15 NULL 2 1 2015-03-10 NULL 4 1 2015-04-16 NULL 2 1 2015-04-12 NULL 2 1 2015-04-12 2015-04 2 3 2015-03-10 2015-03 4 3 2015-03-12 2015-03 1 3 2015-04-13 2015-04 3 3 2015-04-15 2015-04 2 3 2015-04-16 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）
这种函数，需要结合实际场景和数据去使用和研究，只看说明的话，很难理解。
官网的介绍： https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C+Grouping+and+Rollup
点此查看所有Hive窗口分析函数的文章
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