Hive内置UDTF
1、UDF、UDAF、UDTF简介
在Hive中，所有的运算符和用户定义函数，包括用户定义的和内置的，统称为UDF（User-Defined Functions）。如下图所示：
UDF官方文档：https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF
其中，用户自定义聚合函数和内置聚合函数统称为UDAF（User-Defined Aggregate Functions），用户自定义表生成函数和内置表生成函数统称为UDTF（User-Defined Table-Generating Functions）
本文将主要通过具体案例详细介绍Hive的内置表生成函数（UDTF）
2、Hive内置UDTF
Hive内置UDTF官方文档：https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF#LanguageManualUDF-Built-inTable-GeneratingFunctions(UDTF)
2.1、explode(array/map)
功能：列转行
示例：
sql
select explode(array(1,2,3))
select explode(split('1,2,3', ','))
'''
col
1
2
3
'''
sql
select explode(map(1,2,3,4))
'''
key value
1 2
3 4
'''2.2、posexplode(array)
功能：列转行，第一列添加元素索引（从0开始）
示例：
sql
select posexplode(array(1,2,3))
'''
pos val
0 1
1 2
2 3
'''2.3、stack(n,v1,v2,...,vk)
功能：将k个数据平均转换成n行，即k/n列，k必须是n的整数倍，空值使用NULL
示例：
sql
-- 将9个元素按顺序分成3行3列
with user_log as (
select stack (
3,
'1001', '2021-12-12', 123,
'1002', '2021-12-12', 145,
'1001', '2021-12-13', 143
)
as (id, dt, lowcarbon)
)
select * from user_log
'''
user_log.id user_log.dt user_log.lowcarbon
1001 2021-12-12 123
1002 2021-12-12 145
1001 2021-12-13 143
'''2.4、lateral view UDTF
功能：UDTF只允许在SELECT后面跟UDTF，不允许在SELECT后跟其他字段，例如：
sql
select 'CN' as country,explode(array(1,2,3))Hive报错，SparkSQL不报错。lateral view可以解决这个问题
示例1：字符串分割
sql
-- 方式1
with shop as (
select '1001' as pid,'1,2,3' as svs
union
select '1002' as pid,'4,5,' as svs
)
select pid,svs,sv from shop
lateral view outer explode(split(svs, ',')) tmp_v as sv
-- 方式2
select pid,svs,sv from (
select * from (
select '1001' as pid,'1,2,3' as svs
union
select '1002' as pid,'4,5,' as svs
) tmp
) shop
lateral view outer explode(split(svs, ',')) tmp_v as sv
'''
pid svs sv
1001 1,2,3 1
1001 1,2,3 2
1001 1,2,3 3
1002 4,5, 4
1002 4,5, 5
1002 4,5,
'''方式1和方式2使用lateral view和lateral view outer效果相同，空缺值显示为空字符串''
示例2：数组
sql
-- 方式1
with shop as (
select '1001' as pid,array(1,2,3) as svs
union
select '1002' as pid,array(4,5,NULL) as svs
)
select pid,svs,sv from shop
lateral view outer explode(svs) tmp_v as sv
-- 方式2
select pid,svs,sv from (
select * from (
select '1001' as pid,array(1,2,3) as svs
union
select '1002' as pid,array(4,5,NULL) as svs
) tmp
) shop
lateral view outer explode(svs) tmp_v as sv
'''
pid svs sv
1001 [1,2,3] 1
1001 [1,2,3] 2
1001 [1,2,3] 3
1002 [4,5,null] 4
1002 [4,5,null] 5
1002 [4,5,null] NULL
'''方式1和方式2使用lateral view和lateral view outer效果相同，空缺值显示为NULL
示例3：数据存在NULL
sql
-- 方式1
with shop as (
select '1001' as pid, '1,2,3' as svs
union
select '1002' as pid, NULL as svs
)
select pid,svs,sv from shop
lateral view outer explode(split(svs, ',')) tmp_v as sv
-- 方式2
select pid,svs,sv from (
select * from (
select '1001' as pid, '1,2,3' as svs
union
select '1002' as pid, NULL as svs
) tmp
) shop
lateral view outer explode(split(svs, ',')) tmp_v as sv
-- lateral view结果：
'''
pid svs sv
1001 1,2,3 1
1001 1,2,3 2
1001 1,2,3 3
'''
-- lateral view outer结果：
'''
pid svs sv
1001 1,2,3 1
1001 1,2,3 2
1001 1,2,3 3
1002 NULL NULL
'''方式1和方式2使用lateral view和lateral view outer效果不同，lateral view空缺值数据丢失，lateral view outer空缺值显示为NULL
lateral view [outer]详解见文章：传送门
2.5、json_tuple(json_str,k1,k2,...)
功能：从json字符串中根据key获取对应的value返回
示例：json_tuple()使用见文章：传送门
2.6、parse_url_tuple(url,p1,p2,...)
功能：从url中根据属性property获取对应的value返回
示例：
sql
select parse_url_tuple('http://facebook.com/path1/p.php?k1=v1&k2=v2#Ref1', 'HOST', 'PATH', 'QUERY', 'REF', 'PROTOCOL', 'QUERY:k1', 'QUERY:k2')
'''
c0 c1 c2 c3 c4 c5 c6
facebook.com /path1/p.php k1=v1&k2=v2 Ref1 http v1 v2
'''参数详解见：https://help.aliyun.com/zh/maxcompute/user-guide/parse-url-tuple
2.7、inline(array<struct>)
功能：将结构体数组并列分解为多行
示例：
sql
select inline(array(struct('A',18,date '2023-10-01'),struct('B',20,date '2023-11-01'))) as (col1,col2,col3)
'''
col1 col2 col3
A 18 2023-10-01
B 20 2023-11-01
'''