基于CTE的雪花匹配识别 [英] MATCH_RECOGNIZE with CTE in Snowflake

问题描述

我在带有几个CTE的查询中使用MATCH_RECOGNIZE函数。运行查询时，我收到以下错误：

SQL编译错误：此上下文不支持Match_Recognition。

在我的查询中，Match_Recognition Partial前后有几个CTE，如下所示。

WITH cte1 AS (
SELECT *
FROM dataset
WHERE ID IS NOT NULL AND STATUS IS NOT NULL ),

cte2 AS (
SELECT *
FROM cte1
QUALIFY FIRST_VALUE(STATUS) OVER (PARTITION BY ID ORDER BY CREATED_AT) = 'created' )

mr as (
SELECT *
    FROM cte2
    MATCH_RECOGNIZE (
      PARTITION BY ID
      ORDER BY CREATED_AT
      MEASURES MATCH_NUMBER() AS mn,
               MATCH_SEQUENCE_NUMBER AS msn
      ALL ROWS PER MATCH
      PATTERN (c+m+)
      DEFINE
         c AS status='created'
        ,m AS status='missing_info'
        ,p AS status='pending'
    ) m1
    QUALIFY (ROW_NUMBER() OVER(PARTITION BY mn, ID ORDER BY msn) = 1)
          OR(ROW_NUMBER() OVER(PARTITION BY mn, ID ORDER BY msn DESC)=1)
    ORDER BY ID, CREATED_AT ),

cte3 as (
SELECT *
FROM mr
-- some other operations
)

解决此问题的理想方法是什么？例如，创建常规视图、实例化视图或临时表等。我尝试创建视图，但遇到错误，不确定是否支持该视图。 如何在以后的其他CTE中使用MATCH_RECOGNIZE的结果？

当我添加以下内容时，出现此错误：

位置0处的语法错误行xx意外为‘CREATE’。

create view filtered_idents AS

SELECT *
FROM cte2
MATCH_RECOGNIZE (

)

推荐答案

这似乎是一个未记录的限制(我要求我们的AWOWE文档团队解决此问题)。

同时，我可以建议将流程分成几个步骤来使用match_recognize结果。

复制错误：

with data as (
    select $1 company, $2 price_date, $3 price
    from values('a',1,10), ('a',2,15)
), cte as (

    select *
    from data match_recognize(
        partition by company
        order by price_date
        measures match_number() as "MATCH_NUMBER"
        all rows per match omit empty matches
        pattern(overavg*)
        define
            overavg as price > avg(price) over (rows between unbounded
                                      preceding and unbounded following)
    )
) 
select * from cte

-- 002362 (0A000): SQL compilation error: MATCH_RECOGNIZE not supported in this context.

两步解决方案：

with data as (
    select $1 company, $2 price_date, $3 price
    from values('a',1,10), ('a',2,15)
)

select *
from data match_recognize(
    partition by company
    order by price_date
    measures match_number() as "MATCH_NUMBER"
    all rows per match omit empty matches
    pattern(overavg*)
    define
        overavg as price > avg(price) over (rows between unbounded
                                  preceding and unbounded following)
)
;


with previous_results as (
    select *
    from table(result_scan(last_query_id()))
)

select * 
from previous_results
;

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