視窗框架

Snowflake 的 Window Functions

Jake Roach

Field Data Engineer

視窗框架

輸出顯示由所有紀錄組成的視窗。

視窗框架

輸出顯示使用 member_id 欄位分割紀錄所建立的視窗。

動態視窗框架

輸出顯示「滑動」視窗框架。

尋找累積計算

SELECT
    ...

    AVG(<1>) OVER(
        PARTITION BY ...
        ORDER BY <2>

        -- Window between the first
        -- and current row


        ROWS BETWEEN UNBOUNDED PRECEDING 
            AND CURRENT ROW

    )
...

ROWS BETWEEN 可用來建立動態視窗框架

UNBOUNDED PRECEEDING AND CURRENT ROW
從序列第 1 筆到目前這筆
為「累積」計算，非滾動
CURRENT ROW AND UNBOUNDED FOLLOWING

<1>：要計算的欄位

<2>：決定序列並建立視窗框架

燃燒熱量的累積總和

SELECT
    member_id AS m_id, 
    calories_burned AS cb,

    -- Running total!
    SUM(calories_burned) OVER(
        PARTITION BY member_id
        ORDER BY workout_date


        ROWS BETWEEN UNBOUNDED PRECEDING
            AND CURRENT ROW


    ) AS running_total

FROM fitness.workouts;


         m_id  |    cb   |  running_total
       ------- | ------- | --------------
        m_192  |   105   |      105 
        m_192  |   156   |      261 
        m_192  |    69   |      330 
        m_192  |   102   |      432  

        m_74   |   374   |      374  
        m_74   |   396   |      770  
        m_74   |   504   |     1274  

        m_233  |    51   |       51  
        m_233  |    81   |      132

CURRENT ROW AND UNBOUNDED FOLLOWING

SELECT
    member_id AS m_id, 
    calories_burned AS cb,

    SUM(calories_burned) OVER(
        PARTITION BY member_id
        ORDER BY workout_date

        -- Window between current row and last

        ROWS BETWEEN CURRENT ROW
            AND UNBOUNDED FOLLOWING


    ) AS left_to_burn

FROM fitness.workouts;


         m_id  |    cb   |  left_to_burn
       ------- | ------- | --------------
        m_192  |   105   |      432 
        m_192  |   156   |      327 
        m_192  |    69   |      171 
        m_192  |   102   |      102  

        m_74   |   374   |     1274  
        m_74   |   396   |      900 
        m_74   |   504   |      504  

        m_233  |    51   |      132  
        m_233  |    81   |       81

燃燒熱量趨勢

SELECT
    member_id,
    workout_date,
    calories_burned,

    AVG(calories_burned) OVER(   -- Running average of calories burned
        PARTITION BY member_id

        -- Crate a window by workout date, from the first workout to the current workout 
        ORDER BY workout_date
        ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW

    ) AS avg_calories_burned

FROM FITNESS.workouts;

燃燒熱量趨勢


            member_id  |  workout_date  |  calories_burned  |  average_calories_burned
           ----------- | -------------- | ----------------- | -------------------------
              m_192    |   2025-01-01   |        105        |          105.0
              m_192    |   2025-01-03   |        156        |          130.5
              m_192    |   2025-01-04   |         69        |          110.0
              m_192    |   2025-01-10   |        102        |          108.0

               m_74    |   2025-02-10   |        374        |          374.0
               m_74    |   2025-02-13   |        396        |          385.0
               m_74    |   2025-02-14   |        504        |          426.7

              m_233    |   2025-03-05   |         51        |           51.0
              m_233    |   2025-03-12   |         81        |           66.0

一起來練習吧！

Snowflake 的 Window Functions