2

我有两张桌子：

1. 预测表中的原始预测数据，按快照日期拉取，我使用这些数据创建的瀑布看起来像这样

item/snapshot        forecast weeks
123    | 8/25/14 | 9/1/14 | 9/8/14 | 9/15/14
--------------------------------------------
8/24/14|  7661   | 4980   | 588    | 2232
8/31/14|         | 8319   | 1968   | 2760
9/7/14 |         |        | 6931   | 684
9/14/14|         |        |        | 9328

行标签是快照日期，列标签是预测周。基本上，数据有一堆快照日期，每个快照都会提供从这个快照日期开始的预测数据，并且会显示在预测周内。第一个快照日期 x 将预测超出 x 的周数，第二个快照日期 y 将仅预测超出 y 的周数。

然后我有表 2，消费表中的消费数据。我将使用消费表中的周来匹配预测表中的周，以插入消费来填补瀑布中的空白。

如果我在 excel 中手动执行，它将预测第 8/25 周，第 35 周，然后我从消费表中找到第 35 周并在此处插入。因此，所有快照日期的第 35 周将是相同的。

它看起来像这样：

item/snapshot        forecast weeks
123    | 8/25/14 | 9/1/14 | 9/8/14 | 9/15/14
--------------------------------------------
8/24/14|  7661   | 4980   | 588    | 2232
8/31/14|  2222   | 8319   | 1968   | 2760
9/7/14 |  2222   | 333    | 6931   | 684
9/14/14|  2222   | 333    | 444    | 9328

但是这里的问题在我的预测表中，例如，第一个快照日期将预测第 1 周到第 10 周，但第二个快照日期将只有第 2 周到第 10 周的预测。我不知道如何以及是否有可能使这个过程自动化 bigquery sql，因为空白基本上意味着没有数据，没有预测周。

如果有人能给我一些想法，我将不胜感激

这是我的脚本：

 //Get item info from forecast table
DEFINE INLINE TABLE t1
SELECT CONCAT(SUBSTR(snapshot_date, -4, 4),'-',SUBSTR(snapshot_date, -10, 2),'-', SUBSTR(snapshot_date, -7, 2)) snapshot, 
item_name, 
type, 
item_description, 
CONCAT(SUBSTR(forecast_week_start_date, -4, 4),'-',SUBSTR(forecast_week_start_date, -10, 2),'-', SUBSTR(forecast_week_start_date, -7, 2)) forecast_week_start_date, 
SUM(quantity) qty, 
forecast_week_number, 
forecast_year_number,
CONCAT(STRING(forecast_year_number),'-',STRING(forecast_week_number) year_week
FROM forecast
WHERE 
concat(SUBSTR(snapshot_date, -4, 4),'-',SUBSTR(snapshot_date, -10, 2),'-', SUBSTR(snapshot_date, -7, 2)) >= 
strftime_usec(date_add(TIME_USEC_TO_WEEK(date_add(now(),-84 ,'DAY'),1),-1,'DAY'),'%Y-%m-%d')
GROUP BY snapshot, 
item_name, 
type, 
item_description, 
forecast_week_start_date, 
forecast_week_number, 
forecast_year_number,
year_week
ORDER BY sdm_week_start_date

//Get min year_week to use later
DEFINE INLINE TABLE t2
SELECT MIN(year_week) min_year_week
FROM t1


//Get consumption data and apply using dc deploy week
SELECT 
snapshot, 
item_name, 
type, 
item_description, 
forecast_week_start_date, 
qty,
forecast_week_number, 
forecast_year_number,
year_week
IF(t2.min_year_week!= year_week, qty+ABS(consumption_qty),qty)) quantity,

FROM t1
LEFT JOIN ALL 
 (SELECT item_name, week,sum(transaction_quantity) consumption_qt
  FROM consumption 
  GROUP BY item_name,week) inv
ON t1.year_week=inv.week AND t1.item_name=inv.item_name
CROSS JOIN t2
4

1 回答 1

1

我对此很感兴趣。

这两个查询会生成包含示例中值的表。假设第一个查询的输出被写入consumption_table。

SELECT *
FROM
  (SELECT 123 AS item, '8/25/14' AS date, 2222 AS quantity),
  (SELECT 123 AS item, '9/1/14' AS date, 333 AS quantity),
  (SELECT 123 AS item, '9/8/14' AS date, 444 AS quantity),
  (SELECT 123 AS item, '9/15/14' AS date, 0 AS quantity);

第二个查询的输出被写入forecast_table。

SELECT *
FROM
  (SELECT 123 AS item, '8/24/14' AS snapshot, '8/25/14' AS forecast, 7661 AS quantity),
  (SELECT 123 AS item, '8/24/14' AS snapshot, '9/1/14' AS forecast, 4980 AS quantity),
  (SELECT 123 AS item, '8/24/14' AS snapshot, '9/8/14' AS forecast, 588 AS quantity),
  (SELECT 123 AS item, '8/24/14' AS snapshot, '9/15/14' AS forecast, 2232 AS quantity),
  (SELECT 123 AS item, '8/31/14' AS snapshot, '9/1/14' AS forecast, 8319 AS quantity),
  (SELECT 123 AS item, '8/31/14' AS snapshot, '9/8/14' AS forecast, 1968 AS quantity),
  (SELECT 123 AS item, '8/31/14' AS snapshot, '9/15/14' AS forecast, 2760 AS quantity),
  (SELECT 123 AS item, '9/7/14' AS snapshot, '9/8/14' AS forecast, 6931 AS quantity),
  (SELECT 123 AS item, '9/7/14' AS snapshot, '9/15/14' AS forecast, 684 AS quantity),
  (SELECT 123 AS item, '9/14/14' AS snapshot, '9/15/14' AS forecast, 9328 AS quantity);

然后下面的查询会产生你想要的东西：

SELECT
    Consumed.item AS item,
    Consumed.snapshot AS snapshot,
    Consumed.date AS date,
    IF (Forecast.quantity IS NULL, Consumed.quantity, Forecast.quantity) AS quantity
FROM
    (SELECT
        C.item     AS item,
        S.snapshot AS snapshot,
        C.date     AS date,
        C.quantity AS quantity
     FROM
        (SELECT *
         FROM
            (SELECT '8/24/14' AS snapshot),
            (SELECT '8/31/14' AS snapshot),
            (SELECT '9/7/14' AS snapshot),
            (SELECT '9/14/14' AS snapshot)) AS S
     CROSS JOIN
        consumption_table AS C) AS Consumed
LEFT JOIN
    forecast_table AS Forecast
ON Consumed.item = Forecast.item AND 
   Consumed.snapshot = Forecast.snapshot AND
   Consumed.date = Forecast.forecast;

此查询的关键是 CROSS JOIN 生成所有所需的输出行，其中已包含消耗的数量。然后 LEFT JOIN 保留所有这些行并在可用时选择预测数量。

于 2014-11-25T06:48:15.803 回答