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一尘不染

Google BigQuery中具有深度排序的通用数据透视表

sql

这是Google BigQuery中多级数据透视表的后续问题，我想知道是否可以使用单个查询在GoogleBigQuery中构造嵌套数据透视表。是的，因此在这个后续问题中，我想探讨一下一般情况。

这是我正在使用的数据的示例（此共享Google表格中也包含该数据）

现在，我想构建一个具有以下属性的数据透视表：

  • 行级和列级的嵌套级（上一个问题只有嵌套级）
  • 行和列中的小计（前一个只有总计）
  • 多个指标（以前只有一个指标）
  • 多种排序-按深度指标和按字母顺序排序（以前没有任何排序条件）
  • 限制（以前没有任何限制）

这是Google表格中内置的枢轴-

在此处输入图片说明

这里的概念性SQL语句为：

SELECT
    SUM(price),
    COUNT(price) 
BROKEN DOWN BY
    Studio (row),
    Title (row)
    Territory ID (col),
    Type (col)
SORTED/LIMITED BY
    Studio ==> A-Z, LIMIT 3,
    Title ==> SUM(price) in GRAND TOTAL DESC, LIMIT 4,
    Territory ID ==> COUNT(price) in Paramount TOTAL, LIMIT 2
    Type ==> A-Z, NO LIMIT

我不确定如何在概念上显示小计，但我们应该能够为每个细分字段指定小计。

是否可以在Google BigQuery中的单个SQL语句中完成上述操作？生成它的步骤是什么？


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2021-05-16

共1个答案

一尘不染

Q 。如果我们进行汇总并获得1000万个结果怎么办？除非我们在bigquery中应用限制等-否则传输的数据量将需要大量的数据。

让我们在这里阐明挑战：

因此，通常，您将在后端运行以下内容，并将结果上载到可视化工具（前端），以进行进一步的操作，例如排序，限制，旋转等。

#standardSQL
SELECT
  Studio, 
  Title, 
  TerritoryID,
  Type, 
  SUM(Price) AS Price, 
  COUNT(1) AS Volume
FROM YourTable  
GROUP BY Studio, Title, TerritoryID, Type

如您所提到的，这种情况下的结果很容易产生1000万以上的行，并且 您希望减小其大小，而又不影响在前端数据透视/可视化中仍然呈现最终数据的能力

一 。推荐/解决方案

下面显示了如何通过在后端应用排序和限制（从而大大减小结果大小）而没有丢失进行透视的能力并仍然显示总数等来实现此目的。

让我们以简化的一词开始进行最终查询

  • 初始查询（骨架）

假设基于已知标准，我们预先知道应该选择哪些工作室，标题，地区和类型。
在这种情况下，下面的查询将返回所需的数据

#standardSQL
WITH Studios AS (
  SELECT 'Fox' 
  UNION ALL SELECT 'Paramouont' 
),
Titles AS (
  SELECT 'Fox' AS Studio,'Best Laid Plans' AS Title
  UNION ALL SELECT 'Fox','Homecoming'
  UNION ALL SELECT 'Paramount','Titanic'
  UNION ALL SELECT 'Paramount','Homecoming'
),
Territories AS (
  SELECT 'US' AS TerritoryID
  UNION ALL SELECT 'GB'
),
Totals AS (
  SELECT 
    IFNULL(b.Studio,'Other') AS Studio, 
    IFNULL(b.Title,'Other') AS Title, 
    IFNULL(c.TerritoryID,'Other') AS TerritoryID, 
    Type,
    ROUND(SUM(Price), 2) AS Price, COUNT(1) AS Volume
  FROM yourTable AS a 
  LEFT JOIN Titles AS b ON a.Studio = b.Studio AND a.Title = b.Title
  LEFT JOIN Territories AS c ON a.TerritoryID = c.TerritoryID
  GROUP BY Studio, Title, TerritoryID, Type
)
SELECT * FROM Totals
ORDER BY Studio, Title, TerritoryID, Type

输出将如下所示

Studio      Title           TerritoryID Type        Price    Volume  
Fox         Best Laid Plans GB          Movie         87.32    18    
Fox         Best Laid Plans GB          TV Episode    50.17    23    
Fox         Best Laid Plans Other       TV Episode  1131.0      2    
Fox         Best Laid Plans US          Movie        120.82    18    
Fox         Best Laid Plans US          TV Episode    53.76    24    
Fox         Homecoming      GB          TV Episode    60.22    28    
Fox         Homecoming      Other       TV Episode  2262.0      4    
Fox         Homecoming      US          TV Episode   128.45    58    
Other       Other           GB          Movie        142.71    29    
Other       Other           GB          TV Episode    84.8     40    
Other       Other           Other       Movie       3292.0      4    
Other       Other           Other       TV Episode  3282.0     16    
Other       Other           US          Movie         52.92     8    
Other       Other           US          TV Episode   233.05   101    
Paramount   Homecoming      GB          Movie         18.96     4    
Paramount   Homecoming      US          Movie        124.84    16    
Paramount   Titanic         GB          Movie         41.92     8    
Paramount   Titanic         Other       Movie         12.0      4    
Paramount   Titanic         US          Movie        139.84    16

您可以轻松地将其反馈到用户界面，以任何需要的方式对其进行可视化

  • ``最终’‘查询

现在，让我们为每个维度实施实际的标准，而不是在所有涉及的维度中使用硬编码的值。
因此，以下查询（相对于骨架查询）的唯一变化是以下CTE：工作室，标题和地区

#standardSQL
WITH Studios AS (
  SELECT DISTINCT Studio 
  FROM yourTable 
  ORDER BY Studio LIMIT 3
),
Titles AS (
  SELECT Studio, Title 
  FROM (
    SELECT Studio, Title, ROW_NUMBER() OVER(PARTITION BY Studio ORDER BY PRICE DESC) AS pos
    FROM (SELECT Studio, Title, SUM(Price) AS Price FROM yourTable GROUP BY Studio, Title)
  ) WHERE pos <= 4
),
Territories AS (
  SELECT TerritoryID FROM yourTable  
  WHERE Studio = 'Paramount' GROUP BY TerritoryID
  ORDER BY COUNT(1) DESC LIMIT 2
),
Totals AS (
  SELECT 
    IFNULL(b.Studio,'Other') AS Studio, 
    IFNULL(b.Title,'Other') AS Title, 
    IFNULL(c.TerritoryID,'Other') AS TerritoryID, 
    Type,
    ROUND(SUM(Price), 2) AS Price, COUNT(1) AS Volume
  FROM yourTable AS a 
  LEFT JOIN Titles AS b ON a.Studio = b.Studio AND a.Title = b.Title
  LEFT JOIN Territories AS c ON a.TerritoryID = c.TerritoryID
  GROUP BY Studio, Title, TerritoryID, Type
)
SELECT * FROM Totals
WHERE NOT 'Other' IN (TerritoryID)
ORDER BY Studio, TerritoryID DESC, Type, Price DESC, Title

结果是：

Studio      Title           TerritoryID Type        Price  Volume    
Fox         Best Laid Plans         US  Movie       120.82  18   
Fox         Titanic                 US  Movie        52.92   8   
Fox         1:00 P.M. - 2:00 P.M.   US  TV Episode  187.25  81   
Fox         Homecoming              US  TV Episode  128.45  58   
Fox         Best Laid Plans         US  TV Episode   53.76  24   
Fox         Best Laid Plans         GB  Movie        87.32  18   
Fox         Titanic                 GB  Movie        78.84  16   
Fox         1:00 P.M. - 2:00 P.M.   GB  TV Episode   61.42  28   
Fox         Homecoming              GB  TV Episode   60.22  28   
Fox         Best Laid Plans         GB  TV Episode   50.17  23   
Paramount   Titanic                 US  Movie       139.84  16   
Paramount   Homecoming              US  Movie       124.84  16   
Paramount   Titanic                 GB  Movie        41.92   8   
Paramount   Homecoming              GB  Movie        18.96   4   
Sony        Best Laid Plans         US  TV Episode   22.9   10   
Sony        Homecoming              US  TV Episode   22.9   10   
Sony        Best Laid Plans         GB  Movie        63.87  13   
Sony        Homecoming              GB  TV Episode   18.81   9   
Sony        Best Laid Plans         GB  TV Episode    4.57   3

这里的重点是
-尽管BigQuery在分析数十亿行和提取所需信息方面非常高效，但是使用BigQuery实际定制结果数据以反映该结果将如何在客户端UI的表示层中实际呈现是非常无效的。相反，您应该将这些数据传递给UI并使用可视化代码进行处理

2021-05-16