Hive 行列转换

行列转换
列转行

使用 lateral view + explode(array|map)lateral view + inline(array_struct) 可以将列转换为行。

  • 单列转多行,降维(单列数组或键值对)

示例1:explode(array(...))

sql 复制代码
select ..., A
from T
lateral view explode(ARRAY_FIELD) as A;
sql 复制代码
select explode(`array`(88.2,98.3,67.1)) AS (price);

示例2:explode(map(...))

sql 复制代码
select ..., K, V
from T
lateral view explode(MAP_FIELD) as K, V;
sql 复制代码
select explode(`map`("java",56,"mysql",88,"javascript",66)) AS (subject, score);

示例3:inline(array_struct)

sql 复制代码
select ..., 
from T
lateral view inline(STRUCT_ARRAY_FIELD)V as F1,...,FN;
sql 复制代码
with tmp as (
select array(
	named_struct('name','henry','age',22,'is_member','true'),
	named_struct('name','pola','age',20,'is_member','true'),
	named_struct('name','ariel','age',19,'is_member','true')
   ) AS array_struct
)
select name,age,is_member
from tmp
lateral view inline(array_struct)V as name,age,is_member;

lateral view inline(array_struct)将结构体数组的每个元素都转化为一行,每一行都包含结构体字段的值.

前:

后:

  • 多列转多行
sql 复制代码
select ..., A
from T
lateral view explode(array|map(F1,...,FN))V as A;

示例:

sql 复制代码
SELECT name, class, Scores.subject, Scores.score
FROM Students
LATERAL VIEW EXPLODE(ARRAY(
	named_struct('subject','math','score',math_score),
	named_struct('subject','science','score',science_score)
	)
) V AS Scores;

前:

后:

行转列
  • 多行转多列
    条件聚合,通常用于将多行数据中满足条件的某个值聚合到单个行中。
sql 复制代码
select
		F1,...,
		sum(if(C1,0,V1)) as A1,
		sum(if(C2,0,V2)) as A2,
		sum(if(C3,0,V3)) as A3
	from TABLE_NAME
	group by F1,...
	
	drop table if exists lateral_view_stack_test1w;
	create table lateral_view_stack_test1w as
	select year,
		   sum(if(month(order_time)=1,order_amount,0)) as sum_jan,
		   sum(if(month(order_time)=2,order_amount,0)) as sum_feb,
		   sum(if(month(order_time)=3,order_amount,0)) as sum_mar,
		   sum(if(month(order_time)=4,order_amount,0)) as sum_apr,
		   sum(if(month(order_time)=5,order_amount,0)) as sum_may,
		   sum(if(month(order_time)=6,order_amount,0)) as sum_jun,
		   sum(if(month(order_time)=7,order_amount,0)) as sum_jul,
		   sum(if(month(order_time)=8,order_amount,0)) as sum_aug,
		   sum(if(month(order_time)=9,order_amount,0)) as sum_sep,
		   sum(if(month(order_time)=10,order_amount,0)) as sum_oct,
		   sum(if(month(order_time)=11,order_amount,0)) as sum_nov,
		   sum(if(month(order_time)=12,order_amount,0)) as sum_dec
	from hive_internal_par_regex_test1w
	where year>=2014
	group by year;
相关推荐
RestCloud5 小时前
Informatica迁移国产ETL完整实施指南:ETLCloud自动化平滑替换方案
数据仓库·etl·etlcloud·数据传输·数据集成工具·informatica·国产化替代
Database_Cool_2 天前
云数据仓库开通指南:阿里云 AnalyticDB MySQL 10 分钟从 0 到分析实战教程
数据仓库·mysql·阿里云
罗政3 天前
基于AI工作流的多渠道销售数据仓库清洗统计实践
数据仓库
迈巴赫车主5 天前
湖仓一体(Data Lakehouse)简介
大数据·数据仓库·数据湖·湖仓一体
humbinal6 天前
同时支持 gui & cli 的 parquet 文件查看工具,高性能小清新!
hive·python·rust·spark·开源·github·parquet
RestCloud7 天前
ETL是什么?全域数据集成平台核心能力解析
数据仓库·etl·数据清洗·数据处理·etlcloud·数据集成工具
Gent_倪7 天前
万字详解:数据库、数据仓库、数据湖、湖仓一体
数据库·数据仓库·spark
Microsoft Word8 天前
把RAG从 “能跑” 做到上线
数据仓库·人工智能
吾AI科技8 天前
基于Tez引擎的 Hive SQL 性能优化
大数据·hive·性能优化·tez