Hive的CTE 公共表达式

目录

1.语法

[2. 使用场景](#2. 使用场景)

select语句

[chaining CTEs 链式](#chaining CTEs 链式)

union语句

[insert into 语句](#insert into 语句)

[create table as 语句](#create table as 语句)

前言

Common Table Expressions(CTE):公共表达式是一个临时的结果集,该结果集是从with子句中指定的查询派生而来的,紧跟在select 或 insert关键字之前。CTE可以在 select,insert, create table as select 等语句中使用。

1.语法

sql 复制代码
[wtih CommonTableExpression]
select
        column1,
        column2, ...
from table 
[where 条件] 
[group by column]
[order by column] 
[cluster by column| [distribute by column] [sort by column] 
[limit [offset,] rows];

2. 使用场景

select语句

sql 复制代码
with tmp as (
    select
        oid,
        uid,
        otime,
        date_format(otime, 'yyyy-MM') as dt,
        oamount,
        ---计算rk的目的是为了获取记录中的第一条
        row_number() over (partition by uid,date_format(otime, 'yyyy-MM') order by otime) rk
    from t_order
)
 select
    uid,
    --每个用户一月份的订单数
    sum(if(dt = '2018-01', 1, 0)) as  m1_count,
    --每个用户二月份的订单数
    sum(if(dt = '2018-02', 1, 0)) as  m2_count
from tmp
 group by uid
 having m1_count >0 and m2_count=0;

chaining CTEs 链式

sql 复制代码
with tmp1 as (
    select
        oid,
        uid,
        otime,
        date_format(otime, 'yyyy-MM') as dt,
        oamount,
        ---计算rk的目的是为了获取记录中的第一条
        row_number() over (partition by uid,date_format(otime, 'yyyy-MM') order by otime) as rk
    from t_order
),
     tmp2 as
         (select
              uid,
              --每个用户一月份的订单数
              sum(if(dt = '2018-01', 1, 0)) as m1_count,
              --每个用户二月份的订单数
              sum(if(dt = '2018-02', 1, 0)) as m2_count
          from tmp1
          group by uid
          having m1_count > 0
             and m2_count = 0)
select * from tmp2 limit 1;

union语句

sql 复制代码
with q1 as (select * from student where num = 95002),
     q2 as (select * from student where num = 95004)
select * from q1 union all select * from q2;

insert into 语句

sql 复制代码
with tmp1 as (
    select
        oid,
        uid,
        otime,
        date_format(otime, 'yyyy-MM') as dt,
        oamount,
        ---计算rk的目的是为了获取记录中的第一条
        row_number() over (partition by uid,date_format(otime, 'yyyy-MM') order by otime) as rk
    from t_order
),
     tmp2 as
         (select
              uid,
              --每个用户一月份的订单数
              sum(if(dt = '2018-01', 1, 0)) as m1_count,
              --每个用户二月份的订单数
              sum(if(dt = '2018-02', 1, 0)) as m2_count
          from tmp1
          group by uid
          having m1_count > 0
             and m2_count = 0)

insert into tmp3
select * from tmp2 limit 10;

create table as 语句

sql 复制代码
--- 从tmp2 表中取10条数据,基于此创建表tmp3 
create table tmp3 as 
with tmp1 as (
    select
        oid,
        uid,
        otime,
        date_format(otime, 'yyyy-MM') as dt,
        oamount,
        ---计算rk的目的是为了获取记录中的第一条
        row_number() over (partition by uid,date_format(otime, 'yyyy-MM') order by otime) as rk
    from t_order
),
     tmp2 as
         (select
              uid,
              --每个用户一月份的订单数
              sum(if(dt = '2018-01', 1, 0)) as m1_count,
              --每个用户二月份的订单数
              sum(if(dt = '2018-02', 1, 0)) as m2_count
          from tmp1
          group by uid
          having m1_count > 0
             and m2_count = 0)
select * from tmp2 limit 10;
相关推荐
RestCloud2 小时前
数据同步零中断:ETL服务宕机重启后异常任务自动重跑
数据仓库·mysql·etl·etlcloud·数据传输·etl工具
泡干脆面就番茄5 小时前
Hive分区表与分桶表:大数据查询提速的第一把钥匙
大数据·数据仓库·hive·hadoop
SelectDB技术团队1 天前
Apache Doris 基于 Lance 的向量检索深度解析
数据库·数据仓库·数据分析·湖仓一体·apache doris·lakehouse·多模湖仓
泡干脆面就番茄1 天前
Hive-DML:Load-Insert-Export-Import四种数据进出方式
大数据·数据仓库·hive·hadoop
SelectDB技术团队1 天前
日志场景 Elasticsearch 替换实操:建表、索引、写入链路与查询改写的完整参数
大数据·数据库·数据仓库·elasticsearch·全文检索·日志分析·apache doris
省钱兄--zs2 天前
深圳24小时自助健身房软硬件解决方案实战指南与开发流程详解
java·数据仓库·spring boot·小程序·架构
省钱兄--zs2 天前
无人自助拼豆系统架构设计与功能实现落地部署全流程实战指南
java·数据仓库·spring boot·系统架构·需求分析
棣廷2 天前
初识Hive(1)
数据仓库·hive·hadoop
Francek Chen2 天前
【大数据处理与分析】数据仓库Hive:07 Hive HA基本原理
大数据·数据仓库·hive·hadoop·数据分析
这个DBA有点耶2 天前
ELT工具选型:ETL与ELT差异、CDC同步机制与主流工具对比`
数据库·数据仓库·sql·database·dba·etl·数据库管理员