我正在处理正在使用的UNNEST查询。以下是查询的示例，我当前得到的结果以及我希望从中得到的结果。
一点点上下文，我当前正在执行的上传操作是将ID's与A隔开，而不是,强制将其作为字符串而不是数字作为同一单元内有多个ID。 Price也被,隔开。正在上传的数据示例：
Name | Date | Item_ID | Price
John | 4/17/2020 | 123A456A678 | 19.99,21.99,30.00
Joe | 4/17/2020 | 555A777A888 | 8.99,10.00,15.99
Jake | 4/18/2020 | 444A333 | 15.99,9.00
John | 4/18/2020 | 432 | 75.99
Megan | 4/18/2020 | 12A890A23A99| 5.99,6.99,9.99,10.00
这是尝试进行UNNEST之前数据在表中的外观的一个示例。下面是当前UNNEST查询的示例，并带有输出示例。
With data AS(
SELECT
Name,
Date,
SPLIT(Item_ID, 'A') AS Item_ID_Split,
SPLIT(Price, ',') AS Price_Split
FROM
Example.Table
SELECT
Name,
Date,
Item_ID_Split,
Price_Split
FROM data,
UNNEST(Item_ID_Split) Item_ID_Split WITH OFFSET pos1
UNNEST(Price_Split) Price_Split WITH OFFSET pos2
当前输出如下所示：
Name | Date | Item_ID_Split | Price_Split
John | 4/17/2020 | 123 | 19.99
John | 4/17/2020 | 456 | 19.99
John | 4/17/2020 | 678 | 19.99
John | 4/17/2020 | 123 | 21.99
John | 4/17/2020 | 456 | 21.99
John | 4/17/2020 | 678 | 21.99
John | 4/17/2020 | 123 | 30.00
John | 4/17/2020 | 456 | 30.00
John | 4/17/2020 | 678 | 30.00
Joe | 4/17/2020 | 555 | 8.99
Joe | 4/17/2020 | 777 | 8.99
Joe | 4/17/2020 | 888 | 8.99
Joe | 4/17/2020 | 555 | 10.00
Joe | 4/17/2020 | 777 | 10.00
Joe | 4/17/2020 | 888 | 10.00
Joe | 4/17/2020 | 555 | 15.99
Joe | 4/17/2020 | 777 | 15.99
Joe | 4/17/2020 | 888 | 15.99
Jake | 4/18/2020 | 444 | 15.99
Jake | 4/18/2020 | 333 | 15.99
Jake | 4/18/2020 | 444 | 9.00
Jake | 4/18/2020 | 333 | 9.00
John | 4/18/2020 | 432 | 75.99
Megan | 4/18/2020 | 12 | 5.99
Megan | 4/18/2020 | 890 | 5.99
Megan | 4/18/2020 | 23 | 5.99
Megan | 4/18/2020 | 99 | 5.99
Megan | 4/18/2020 | 12 | 6.99
Megan | 4/18/2020 | 890 | 6.99
Megan | 4/18/2020 | 23 | 6.99
Megan | 4/18/2020 | 99 | 6.99
Megan | 4/18/2020 | 12 | 9.99
Megan | 4/18/2020 | 890 | 9.99
Megan | 4/18/2020 | 23 | 9.99
Megan | 4/18/2020 | 99 | 9.99
Megan | 4/18/2020 | 12 | 10.00
Megan | 4/18/2020 | 890 | 10.00
Megan | 4/18/2020 | 23 | 10.00
Megan | 4/18/2020 | 99 | 10.00
这是上面查询的当前输出。如您所见，有重复的Item_ID /价格，我想要得到的结果如下：
Name | Date | Item_ID_Split | Price_Split
John | 4/17/2020 | 123 | 19.99
John | 4/17/2020 | 456 | 21.99
John | 4/17/2020 | 678 | 30.00
Joe | 4/17/2020 | 555 | 8.99
Joe | 4/17/2020 | 777 | 10.00
Joe | 4/17/2020 | 888 | 15.99
Jake | 4/18/2020 | 444 | 15.99
Jake | 4/18/2020 | 333 | 9.00
John | 4/18/2020 | 432 | 75.99
Megan | 4/18/2020 | 12 | 5.99
Megan | 4/18/2020 | 890 | 6.99
Megan | 4/18/2020 | 23 | 9.99
Megan | 4/18/2020 | 99 | 10.00
这是我正在寻找Item_ID_Split和Price_Split之间根本没有重复之处的结果。我试图将SPLIT函数放在UNNEST中，但得到的输出是相同的。我不确定如何完成此操作，因此我们将不胜感激！
提前谢谢！
答案 0 :(得分：1)
您可以使用with offset：
SELECT Name, Date, Item_ID_Split, Price_Split
FROM data LEFT JOIN
UNNEST(Item_ID_Split) Item_ID_Split WITH OFFSET pos1
ON 1=1 LEFT JOIN
UNNEST(Price_Split) Price_Split WITH OFFSET pos2
ON pos1 = po2;
答案 1 :(得分：1)
以下是BigQuery标准SQL
#standardSQL
SELECT Name, Day, Splits.*
FROM (
SELECT Name, Day,
ARRAY(
SELECT AS STRUCT Item_ID_Split, Price_Split
FROM UNNEST(SPLIT(Item_ID, 'A')) AS Item_ID_Split WITH OFFSET
JOIN UNNEST(SPLIT(Price, ',')) AS Price_Split WITH OFFSET
USING(OFFSET)
) AS arr
FROM `project.dataset.table`
), UNNEST(arr) Splits
如下面的示例所示，如果要从您的问题中申请样本数据
#standardSQL
WITH `project.dataset.table` AS (
SELECT 'John' Name, '4/17/2020' Day, '123A456A678' Item_ID,'19.99,21.99,30.00' Price UNION ALL
SELECT 'Joe', '4/17/2020', '555A777A888','8.99,10.00,15.99' UNION ALL
SELECT 'Jake', '4/18/2020', '444A333','15.99,9.00' UNION ALL
SELECT 'John', '4/18/2020', '432','75.99' UNION ALL
SELECT 'Megan', '4/18/2020', '12A890A23A99','5.99,6.99,9.99,10.00'
)
SELECT Name, Day, Splits.*
FROM (
SELECT Name, Day,
ARRAY(
SELECT AS STRUCT Item_ID_Split, Price_Split
FROM UNNEST(SPLIT(Item_ID, 'A')) AS Item_ID_Split WITH OFFSET
JOIN UNNEST(SPLIT(Price, ',')) AS Price_Split WITH OFFSET
USING(OFFSET)
) AS arr
FROM `project.dataset.table`
), UNNEST(arr) Splits
输出为
Row Name Day Item_ID_Split Price_Split
1 John 4/17/2020 123 19.99
2 John 4/17/2020 456 21.99
3 John 4/17/2020 678 30.00
4 Joe 4/17/2020 555 8.99
5 Joe 4/17/2020 777 10.00
6 Joe 4/17/2020 888 15.99
7 Jake 4/18/2020 444 15.99
8 Jake 4/18/2020 333 9.00
9 John 4/18/2020 432 75.99
10 Megan 4/18/2020 12 5.99
11 Megan 4/18/2020 890 6.99
12 Megan 4/18/2020 23 9.99
13 Megan 4/18/2020 99 10.00