HiveSQL高级进阶技巧，掌握这10个技巧，你的SQL水平将有一个质的提升！

1.删除

insert overwrite tmp
select * from tmp where id != '666';

2.更新

insert overwrite tmp
select 
    id,
    label,
    if(id = '1' and label = 'grade','25',value) as value
from tmp
where id != '666';

3.列转行

-- Step03：最后将info的内容切分
select id,split(info,':')[0] as label,split(info,':')[1] as value
from
(
    -- Step01：先将数据拼接成“heit:180,weit:60,age:26”
    select id,concat('heit',':',height,',','weit',':',weight,',','age',':',age) as value     from tmp
) as tmp
-- Step02：然后在借用explode函数将数据膨胀至多行
lateral view explode(split(value,',')) mytable as info;

4.行转列1

select
tmp1.idas id,tmp1.valueas height,tmp2.valueas weight,tmp3.valueas age
from
(select id,label,value from tmp2 where label = 'heit') as tmp1
join
on tmp1.id = tmp2.id
(select id,label,value from tmp2 where label = 'weit') as tmp2
join
on tmp1.id = tmp2.id
(select id,label,value from tmp2 where label = 'age') as tmp3
on tmp1.id = tmp3.id;

5.行转列2

select
id,tmpmap['height'] as height,tmpmap['weight'] as weight,tmpmap['age'] as age
from
(
    select id,           
        str_to_map(concat_ws(',',collect_set(concat(label,':',value))),',',':') as tmpmap
    from tmp2 groupby id
) as tmp1;

6.分析函数1

select id,label,value,
       lead(value,1,0)over(partition by id orderby label) as lead,                 
       lag(value,1,999)over(partition by id orderby label) as lag,       
       first_value(value)over(partition by id orderby label) as first_value,       
       last_value(value)over(partition by id orderby label) as last_value
from tmp;

7.分析函数2

select id,label,value,
       row_number()over(partition by id orderby value) as row_number,  --自然顺序     
       rank()over(partition by id orderby value) as rank,--跳跃排序
       dense_rank()over(partition by id orderby value) as dense_rank --等位排序
from tmp;

8.多维分析1

select col1,col2,col3,count(1),
      Grouping__ID
from tmp
groupby col1,col2,col3
grouping sets(col1,col2,col3,(col1,col2),(col1,col3),(col2,col3),())

9.多维分析2

select col1,col2,col3,count(1),
       Grouping__ID
from tmp
groupby col1,col2,col3
with cube;

10.数据倾斜groupby

select label,sum(cnt) as all from
(
    select rd,label,sum(1) as cnt from
    (
        select id,round(rand(),2) as rd,value from tmp1
    ) as tmp
    groupby rd,label
) as tmp
groupby label;

11.数据倾斜join

select label,sum(value) as all from
(
    select rd,label,sum(value) as cnt from
    (
        select tmp1.rdas rd,tmp1.labelas label,tmp1.value*tmp2.valueas value         
        from
        (
            select id,round(rand(),1) as rd,label,value from tmp1
        ) as tmp1
        join
        (
            select id,rd,label,value from tmp2
            lateral view
            explode(split('0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9',',')) mytable as rd
        ) as tmp2
        on tmp1.rd = tmp2.rdand tmp1.label = tmp2.label
    ) as tmp1
    groupby rd,label
) as tmp1
groupby label;