Clickhouse groupArray/groupUniqArray/arrayJoin/splitByChar
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行列转置一般由由行转为列,或者由列转为行。 CREATE TABLE datasets.t_city ( `province` String, `city` String, `createtime` DateTime, `city_level` Int8 ) ENGINE = MergeTree() ORDER BY province SETTINGS index_granularity = 8192; insert into t_city values('Hubei','Wuhan',now(),2),('Hubei','Xiangyang',now(),3),('Shanghai','Shanghai',now(),1),('Guangdong','Guangzhou',now(),1),('Guangdong','Shenzhen',now(),1),('Guangdong','DOngguan',now(),2),('Guangdong','Zhuhai',now(),3); Clickhouse> select * from t_city; SELECT * FROM t_city ┌─province──┬─city──────┬──────────createtime─┬─city_level─┐ │ Guangdong │ Guangzhou │ 2020-07-07 14:02:53 │ 1 │ │ Guangdong │ Shenzhen │ 2020-07-07 14:02:53 │ 1 │ │ Guangdong │ DOngguan │ 2020-07-07 14:02:53 │ 2 │ │ Guangdong │ Zhuhai │ 2020-07-07 14:02:53 │ 3 │ │ Hubei │ Wuhan │ 2020-07-07 14:02:53 │ 2 │ │ Hubei │ Xiangyang │ 2020-07-07 14:02:53 │ 3 │ │ Shanghai │ Shanghai │ 2020-07-07 14:02:53 │ 1 │ └───────────┴───────────┴─────────────────────┴────────────┘ 7 rows in set. Elapsed: 0.002 sec. 列转行: 查询每个省份用户的城市:groupArray Clickhouse> select province, groupArray(city) from t_city group by province; SELECT province, groupArray(city) FROM t_city GROUP BY province ┌─province──┬─groupArray(city)─────────────────────────────┐ │ Shanghai │ ['Shanghai'] │ │ Hubei │ ['Wuhan','Xiangyang'] │ │ Guangdong │ ['Guangzhou','Shenzhen','Dongguan','Zhuhai'] │ └───────────┴──────────────────────────────────────────────┘ 插入一条重复的记录: insert into t_city values('Hubei','Wuhan',now(),2); 可以看到Hubei有一个重复的wuhan Clickhouse> select province, groupArray(city) from t_city group by province; SELECT province, groupArray(city) FROM t_city GROUP BY province ┌─province──┬─groupArray(city)─────────────────────────────┐ │ Shanghai │ ['Shanghai'] │ │ Hubei │ ['Wuhan','Xiangyang','Wuhan'] │ │ Guangdong │ ['Guangzhou','Shenzhen','Dongguan','Zhuhai'] │ └───────────┴──────────────────────────────────────────────┘ 3 rows in set. Elapsed: 0.002 sec. 可以使用函数groupUniqArray进行去重: Clickhouse> select province, groupUniqArray(city) from t_city group by province; SELECT province, groupUniqArray(city) FROM t_city GROUP BY province ┌─province──┬─groupUniqArray(city)─────────────────────────┐ │ Shanghai │ ['Shanghai'] │ │ Hubei │ ['Wuhan','Xiangyang'] │ │ Guangdong │ ['Zhuhai','Dongguan','Guangzhou','Shenzhen'] │ └───────────┴──────────────────────────────────────────────┘ 3 rows in set. Elapsed: 0.003 sec. 字符串拆分:splitByChar Clickhouse> select splitByChar('#','Hubei_Wuhan#Hubei_Xiangyang#Guangdong_Shenzhen') col; SELECT splitByChar('#', 'Hubei_Wuhan#Hubei_Xiangyang#Guangdong_Shenzhen') AS col ┌─col────────────────────────────────────────────────────┐ │ ['Hubei_Wuhan','Hubei_Xiangyang','Guangdong_Shenzhen'] │ └────────────────────────────────────────────────────────┘ 1 rows in set. Elapsed: 0.002 sec. 可以使用ArrayJoin 函数将一行转为行: Clickhouse> select arrayJoin(splitByChar('#', 'Hubei_Wuhan#Hubei_Xiangyang#Guangdong_Shenzhen')) col; SELECT arrayJoin(splitByChar('#', 'Hubei_Wuhan#Hubei_Xiangyang#Guangdong_Shenzhen')) AS col ┌─col────────────────┐ │ Hubei_Wuhan │ │ Hubei_Xiangyang │ │ Guangdong_Shenzhen │ └────────────────────┘ 3 rows in set. Elapsed: 0.002 sec. 实际示例: SELECT province, groupArray(city) FROM t_city GROUP BY province ┌─province──┬─groupArray(city)─────────────────────────────┐ │ Shanghai │ ['Shanghai'] │ │ Hubei │ ['Wuhan','Xiangyang','Wuhan'] │ │ Guangdong │ ['Guangzhou','Shenzhen','Dongguan','Zhuhai'] │ └───────────┴──────────────────────────────────────────────┘ 3 rows in set. Elapsed: 0.003 sec. Clickhouse> SELECT province, arrayJoin(groupArray(city)) new_city FROM t_city GROUP BY province; SELECT province, arrayJoin(groupArray(city)) AS new_city FROM t_city GROUP BY province ┌─province──┬─new_city──┐ │ Shanghai │ Shanghai │ │ Hubei │ Wuhan │ │ Hubei │ Xiangyang │ │ Hubei │ Wuhan │ │ Guangdong │ Guangzhou │ │ Guangdong │ Shenzhen │ │ Guangdong │ Dongguan │ │ Guangdong │ Zhuhai │ └───────────┴───────────┘ 8 rows in set. Elapsed: 0.003 sec. 结论:在clickhouse中主要使用两个函数groupArray 和ArrayJoin。
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