LATERAL VIEW 使用总结

• • • 使用案例一（单个LATERAL VIEW）：split + explode + LATERAL VIEW
    • 使用案例二（多个LATERAL VIEW）：explode + LATERAL VIEW

The LATERAL VIEW clause is used in conjunction with generator functions such as EXPLODE, which will generate a virtual table containing one or more rows. LATERAL VIEW will apply the rows to each original output row.

LATERAL VIEW Clause - Spark 3.2.0 documentation (apache.org)

求出每个技能对应的最大的用户的年龄

表和数据

cache table user_info
select '1356' user_id, 'kyle' user_name, 23 age, 'Hadoop-Hive-Spark'  skills
union
select '1357' user_id, 'Jack' user_name, 22 age, 'Hadoop-Hive' skills
union
select '1358' user_id, 'Sam' user_name, 26 age, 'Mysql-Oracle'  skills
union
select '1359' user_id, 'Luc' user_name, 28 age, 'Redis-Mysql' skills
union
select '1360' user_id, 'Rose' user_name, 32 age, 'Hadoop-Hive-Spark-Flink-Hbase' skills
union
select '1361' user_id, 'Harry' user_name, 25 age, 'Flink-Hbase-ClickHouse-Kafka'  skills
union
select '1362' user_id, 'Kelly' user_name, 27 age, 'Spark-Flink-Hbase' skills;

需求分析

先从 skills 字段把每个技能分割出来，然后按照 user_id 和 skills 字段分组，求出最大的年龄

with t1 as (
    -- 对 skills 字段进行切割并实现列转行
    select user_id,
           user_name,
           age,
           skill
    from user_info
    lateral view explode(split(skills,'-')) skill_table as skill
),
     t2 as (
     -- 按照 skill 分组 age 排序，为了标记每个技能对应的最大的用户信息
     select *,
            row_number() over(partition by skill order by age desc) rn
     from t1
)

select
       user_id,
       user_name,
       age,
       skill
from t2
where rn = 1;

将 skills 和 mark 字段全部转为列

表和数据

需求分析

由于 skills 和 mark 字段全部都是 Array 类型，所以可以直接使用 explode 函数处理

select 
    user_id,
    user_name,
    age,
    skill,
    mark
FROM baseTable
LATERAL VIEW explode(skills) view1 AS skill
LATERAL VIEW explode(mark) view2 AS mark;