一、lateral view函数
-
功能:
- 用于和UDTF函数（explode,split）结合使用，把某一行数据拆分成多行数据，再将多行结果组合成一个支持别名的虚拟表。
- 主要解决select使用UDTF做查询的过程中查询只能包含单个UDTF，不能包含其它字段以及多个UDTF的情况。
-
语法：LATERAL VIEW udtf(expression) tableAlias AS columnAlias (‘,’ columnAlias)
- columnAlias是给udtf(expression)列起的别名。
- tableAlias 虚拟表的别名。
-
lateral view函数会将lUDTF生成的结果放到一个虚拟表中，然后这个虚拟表和输入行进行join来达到连接UDTF外的select字段的目的。
使用方式：
举例1：与explode() 函数连用
--测试表的数据结构，可以看到第一列是id(string类型),第二列是rule_array(array<string>类型)
> desc test_2;
--结果：
+-------------+----------------+----------+
| col_name | data_type | comment |
+-------------+----------------+----------+
| id | string | |
| rule_array | array<string> | |
+-------------+----------------+----------+
--查看测试表的内容
> select * from test_2;
--结果：
+------------+----------------------------------------+
| test_2.id | test_2.rule_array |
+------------+----------------------------------------+
| a | ["501","502","503","501","512"] |
| b | ["511","512","513","511","512","511"] |
| c | ["512","513","511","512"] |
+------------+----------------------------------------+
--拆分rule_array
> select id, rule_explode
> from test_2
> lateral view explode(rule_array) adTable AS rule_explode;
--结果：
+-----+---------------+
| id | rule_explode |
+-----+---------------+
| a | 501 |
| a | 502 |
| a | 503 |
| a | 501 |
| a | 512 |
| b | 511 |
| b | 512 |
| b | 513 |
| b | 511 |
| b | 512 |
| b | 511 |
| c | 512 |
| c | 513 |
| c | 511 |
| c | 512 |
+-----+---------------+
举例2：与parse_url_tuple()函数连用
- parse_url_tuple()函数
- 语法：parse_url(string urlString, string partToExtract [, string keyToExtract])
- 功能：UDTF函数，解析URL字符串，它通过一次指定多个参数，从URL中解析出多个参数值返回多列。
- 参数：partToExtract的有效值为：HOST, PATH, QUERY, REF, PROTOCOL, AUTHORITY, FILE, and USERINFO。
- 注意：在使用 select 时不能同时返回其他字段，不能嵌套调用，不能与group by放在一起调用等。为解决此问题，可以通过测试图(Lateral View)搭配调用。
--测试表的数据结构，可以看到第一列是id(int类型),第二列是url(string类型)
> desc tb_url;
--结果：
+-----------+------------+----------+
| col_name | data_type | comment |
+-----------+------------+----------+
| id | int | |
| url | string | |
+-----------+------------+----------+
--查看测试表的内容
> select * from tb_url;
--结果：
+------------+-------------------------------------------------+
| tb_url.id | tb_url.url |
+------------+-------------------------------------------------+
| 1 | http://facebook.com/path/p1.php?query=1 |
| 2 | http://www.baidu.com/news/index.jsp?uuid=frank |
| 3 | http://www.jd.com/index?source=baidu |
+------------+-------------------------------------------------+
--提取tb_url的query部分
> select
> a.id as id,
> c.query as query
> from tb_url a
> lateral view parse_url_tuple(url,"QUERY") c as query
> ;
--结果：
+-----+---------------+
| id | query |
+-----+---------------+
| 1 | query=1 |
| 2 | uuid=frank |
| 3 | source=baidu |
+-----+---------------+
举例3：多个lateral view连用
--提取tb_url的HOST、PATH和QUERY部分
> select
> a.id as id,
> b.host as host,
> b.path as path,
> c.query as query
> from tb_url a
> lateral view parse_url_tuple(url,"HOST","PATH") b as host,path
> lateral view parse_url_tuple(url,"QUERY") c as query
> ;
--结果：
+-----+----------------+------------------+---------------+
| id | host | path | query |
+-----+----------------+------------------+---------------+
| 1 | facebook.com | /path/p1.php | query=1 |
| 2 | www.baidu.com | /news/index.jsp | uuid=frank |
| 3 | www.jd.com | /index | source=baidu |
+-----+----------------+------------------+---------------+
注意：
- lateral view函数的位置在from后where条件前。
- 生成虚拟表的别名不可省略。
- from后可带多个 lateral view函数。
- 如果要拆分的字段有null值，需要使用 lateral view outer替代，避免数据缺失。
二、explode()函数
- 功能：UDTF函数，可以将一个array或者map展开
- 语法：explode(map<string> ,array <string>)
- explode(array)：将array列表里的每个元素生成一行
- explode(map)：每一对元素作为一行，key为一列，value为一列
使用方式:
举例1：直接使用
--explode(array)
> select explode(array(11,22,33)) as item;
--结果：
+-------+
| item |
+-------+
| 11 |
| 22 |
| 33 |
+-------+
--explode(map)
> select explode(map("id",11,"name","lily","age",18)) as (k,v);
--结果：
+-------+-------+
| k | v |
+-------+-------+
| id | 11 |
| name | lily |
| age | 18 |
+-------+-------+
举例2：与lateral view一起使用
- 语法：lateral view explode(字段) 表别名 as 列别名
- 如果字段类型是map：lateral view explode(字段) 表别名 as (key别名,value别名)
> select * from test_2;
--结果：
+------------+----------------------------------------+
| test_2.id | test_2.rule_array |
+------------+----------------------------------------+
| a | ["501","502","503","501","512"] |
| b | ["511","512","513","511","512","511"] |
| c | ["512","513","511","512"] |
+------------+----------------------------------------+
> select id,rule
> from test_2
> lateral view explode(rule_array) tbl as rule
> ;
--结果：
+-----+-------+
| id | rule |
+-----+-------+
| a | 501 |
| a | 502 |
| a | 503 |
| a | 501 |
| a | 512 |
| b | 511 |
| b | 512 |
| b | 513 |
| b | 511 |
| b | 512 |
| b | 511 |
| c | 512 |
| c | 513 |
| c | 511 |
| c | 512 |
+-----+-------+
举例3：使用局限性
- 不能关联原有的表中其它字段。例如：
> select id, explode(rule_array) as rule from test_2;
--报错：
Error: Error while compiling statement: FAILED: SemanticException [Error 10081]: UDTF's are not supported outside the SELECT clause, nor nested in expressions (state=42000,code=10081)
- 不能与group by、cluster by 、distribute by、sort by联用。例如：
> select explode(rule_array) as rule from test_2 group by explode(rule_array);
--报错：
Error: Error while compiling statement: FAILED: SemanticException [Error 10081]: UDTF's are not supported outside the SELECT clause, nor nested in expressions (state=42000,code=10081)
- 不能进行UDTF嵌套。例如：
> select explode(explode(rule_array)) from test_2 ;
--报错：
Error: Error while compiling statement: FAILED: SemanticException [Error 10081]: UDTF's are not supported outside the SELECT clause, nor nested in expressions (state=42000,code=10081)
- 不允许选择其他表达式。例如：
> select explode("1,2,3,4,5") from test_2 ;
--报错：
Error: Error while compiling statement: FAILED: UDFArgumentException explode() takes an array or a map as a parameter (state=42000,code=40000)
三、posexplode()函数
- 功能：UDTF函数，将一个array或者map展开，可以将index（索引）和数据都取出来，使用两次posexplode()并用where语句使两次取到的index相等，从而实现对多列进行多行转换。explode()函数只能将对一列进行行转换。
- 语法：posexplode(map<string> ,array <string>)
使用方式:
举例1：
> desc test_2;
--结果：
+-------------+----------------+----------+
| col_name | data_type | comment |
+-------------+----------------+----------+
| id | string | |
| dt_array | array<string> | |
| rule_array | array<string> | |
+-------------+----------------+----------+
> select * from test_2;
--结果：
+------------+----------------------------------------------------+----------------------------------------+
| test_2.id | test_2.dt_array | test_2.rule_array |
+------------+----------------------------------------------------+----------------------------------------+
| a | ["20230809","20230811","20230812","20230812","20230813"] | ["501","502","503","501","512"] |
| b | ["20230809","20230811","20230812","20230812","20230813","20230809"] | ["511","512","513","511","512","511"] |
| c | ["20230811","20230812","20230812","20230813"] | ["512","513","511","512"] |
+------------+----------------------------------------------------+----------------------------------------+
--注：语句中b.idxb和c.idxc分别是子视图的两个索引，我们where子句中使用b.idxb=c.idxc保证顺序的一致性。
> select a.id,b.cur_day,c.rule
> from test_2 a
> lateral view posexplode(dt_array) b as idxb,cur_day,
> lateral view posexplode(rule_array) c as idxc,rule where b.idxb=c.idxc
> ;
--结果：
+-------+------------+---------+
| a.id | b.cur_day | c.rule |
+-------+------------+---------+
| a | 20230809 | 501 |
| a | 20230811 | 502 |
| a | 20230812 | 503 |
| a | 20230812 | 501 |
| a | 20230813 | 512 |
| b | 20230809 | 511 |
| b | 20230811 | 512 |
| b | 20230812 | 513 |
| b | 20230812 | 511 |
| b | 20230813 | 512 |
| b | 20230809 | 511 |
| c | 20230811 | 512 |
| c | 20230812 | 513 |
| c | 20230812 | 511 |
| c | 20230813 | 512 |
+-------+------------+---------+
四、行转列使用
单列转多行
举例1：使用explode()+lateral view
> select t.id,a.cur_day
> from test_2 t
> lateral view explode(t.dt_array) a as cur_day
> ;
--结果：
+-------+------------+
| t.id | a.cur_day |
+-------+------------+
| b | 20230809 |
| b | 20230811 |
| b | 20230812 |
| b | 20230812 |
| b | 20230813 |
| b | 20230809 |
| c | 20230811 |
| c | 20230812 |
| c | 20230812 |
| c | 20230813 |
| a | 20230809 |
| a | 20230811 |
| a | 20230812 |
| a | 20230812 |
| a | 20230813 |
+-------+------------+
举例2：explode字段是string格式，先split()指定分隔符，如果省略split()则使用默认分隔符是英文逗号。
> desc test_3;
--结果：
+-----------+------------+----------+
| col_name | data_type | comment |
+-----------+------------+----------+
| id | string | |
| dt | string | |
| rule1 | string | |
+-----------+------------+----------+
> select * from test_3;
--结果：
+------------+----------------------------------------------------+--------------------------+
| test_3.id | test_3.dt | test_3.rule1 |
+------------+----------------------------------------------------+--------------------------+
| a | 20230809,20230811,20230812,20230812,20230813 | 501,502,503,501,512 |
| b | 20230809,20230811,20230812,20230812,20230813,20230809 | 511,512,513,511,512,511 |
| c | 20230811,20230812,20230812,20230813 | 512,513,511,512 |
+------------+----------------------------------------------------+--------------------------+
> select t.id,a.cur_day
> from test_3 t
> lateral view explode(split(t.dt,',')) a as cur_day
> ;
--结果：
+-------+------------+
| t.id | a.cur_day |
+-------+------------+
| a | 20230809 |
| a | 20230811 |
| a | 20230812 |
| a | 20230812 |
| a | 20230813 |
| b | 20230809 |
| b | 20230811 |
| b | 20230812 |
| b | 20230812 |
| b | 20230813 |
| b | 20230809 |
| c | 20230811 |
| c | 20230812 |
| c | 20230812 |
| c | 20230813 |
+-------+------------+
多列转多行
举例1：使用posexplode()+lateral view
先测试使用explode(), 看看效果:文章来源：https://www.toymoban.com/news/detail-845609.html
> select a.id,b.cur_day,c.rule
> from test_2 a
> lateral view explode(dt_array) b as cur_day,
> lateral view explode(rule_array) c as rule
> ;
--结果：
+-------+------------+---------+
| a.id | b.cur_day | c.rule |
+-------+------------+---------+
| b | 20230809 | 511 |
| b | 20230809 | 512 |
| b | 20230809 | 513 |
| b | 20230809 | 511 |
| b | 20230809 | 512 |
| b | 20230809 | 511 |
| b | 20230811 | 511 |
| b | 20230811 | 512 |
| b | 20230811 | 513 |
| b | 20230811 | 511 |
| b | 20230811 | 512 |
| b | 20230811 | 511 |
| b | 20230812 | 511 |
| b | 20230812 | 512 |
| b | 20230812 | 513 |
| b | 20230812 | 511 |
| b | 20230812 | 512 |
| b | 20230812 | 511 |
| b | 20230812 | 511 |
| b | 20230812 | 512 |
| b | 20230812 | 513 |
| b | 20230812 | 511 |
| b | 20230812 | 512 |
| b | 20230812 | 511 |
| b | 20230813 | 511 |
| b | 20230813 | 512 |
| b | 20230813 | 513 |
| b | 20230813 | 511 |
| b | 20230813 | 512 |
| b | 20230813 | 511 |
| b | 20230809 | 511 |
| b | 20230809 | 512 |
| b | 20230809 | 513 |
| b | 20230809 | 511 |
| b | 20230809 | 512 |
| b | 20230809 | 511 |
| c | 20230811 | 512 |
| c | 20230811 | 513 |
| c | 20230811 | 511 |
| c | 20230811 | 512 |
| c | 20230812 | 512 |
| c | 20230812 | 513 |
| c | 20230812 | 511 |
| c | 20230812 | 512 |
| c | 20230812 | 512 |
| c | 20230812 | 513 |
| c | 20230812 | 511 |
| c | 20230812 | 512 |
| c | 20230813 | 512 |
| c | 20230813 | 513 |
| c | 20230813 | 511 |
| c | 20230813 | 512 |
| a | 20230809 | 501 |
| a | 20230809 | 502 |
| a | 20230809 | 503 |
| a | 20230809 | 501 |
| a | 20230809 | 512 |
| a | 20230811 | 501 |
| a | 20230811 | 502 |
| a | 20230811 | 503 |
| a | 20230811 | 501 |
| a | 20230811 | 512 |
| a | 20230812 | 501 |
| a | 20230812 | 502 |
| a | 20230812 | 503 |
| a | 20230812 | 501 |
| a | 20230812 | 512 |
| a | 20230812 | 501 |
| a | 20230812 | 502 |
| a | 20230812 | 503 |
| a | 20230812 | 501 |
| a | 20230812 | 512 |
| a | 20230813 | 501 |
| a | 20230813 | 502 |
| a | 20230813 | 503 |
| a | 20230813 | 501 |
| a | 20230813 | 512 |
+-------+------------+---------+
出现这种情况，是因为两个并列的explode()的hql没办法识别cur_day对应的rule是什么，对于多个数组的行转列可以使用posexplode()函数。
例如使用如下查询语句：文章来源地址https://www.toymoban.com/news/detail-845609.html
> select a.id,b.cur_day,c.rule
> from test_2 a
> lateral view posexplode(dt_array) b as idxb,cur_day,
> lateral view posexplode(rule_array) c as idxc,rule where b.idxb=c.idxc
> ;
--结果：
+-------+------------+---------+
| a.id | b.cur_day | c.rule |
+-------+------------+---------+
| b | 20230809 | 511 |
| b | 20230811 | 512 |
| b | 20230812 | 513 |
| b | 20230812 | 511 |
| b | 20230813 | 512 |
| b | 20230809 | 511 |
| c | 20230811 | 512 |
| c | 20230812 | 513 |
| c | 20230812 | 511 |
| c | 20230813 | 512 |
| a | 20230809 | 501 |
| a | 20230811 | 502 |
| a | 20230812 | 503 |
| a | 20230812 | 501 |
| a | 20230813 | 512 |
+-------+------------+---------+
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