将客户数据汇总为一行答案

【问题标题】：Rolling Up Customer Data into One Row将客户数据汇总为一行
【发布时间】：2022-01-01 04:33:10
【问题描述】：

我在 Apache Spark 中创建了一个查询，希望获取多行客户数据并将其汇总为一行，以显示他们打开了哪些类型的产品。所以看起来像这样的数据：

Customer   Product
1           Savings
1           Checking
1           Auto

最终看起来像这样：

Customer     Product
1            Savings/Checking/Auto

查询当前仍有多行。我尝试了 group by，但这并没有显示客户拥有的多种产品，而是只显示一种产品。

有没有办法做到这一点是 Apache Spark 或 SQL（它真的类似于 apache）？不幸的是，我没有 MYSQL，也不认为 IT 会为我安装它。

SELECT
"ACCOUNT"."account_customerkey" AS "account_customerkey",
max(
concat(case when Savings=1 then ' Savings'end,
 case when Checking=1 then ' Checking  'end,
 case when CD=1 then ' CD /'end,
 case when IRA=1 then ' IRA /'end,
 case when StandardLoan=1 then ' SL /'end,
 case when Auto=1 then ' Auto /'end,
 case when Mortgage=1 then ' Mortgage /'end,
 case when CreditCard=1 then ' CreditCard 'end)) AS Description

FROM "ACCOUNT" "ACCOUNT" 
inner join (
SELECT 
  "ACCOUNT"."account_customerkey" AS "customerkey",


CASE WHEN "ACCOUNT"."account_producttype"  = 'Savings' THEN 1 ELSE NULL END AS Savings,
CASE WHEN "ACCOUNT"."account_producttype"  = 'Checking' THEN 1 ELSE NULL END AS Checking,
CASE WHEN "ACCOUNT"."account_producttype"  = 'CD' THEN 1 ELSE NULL END AS CD,
CASE WHEN "ACCOUNT"."account_producttype"  = 'IRA' THEN 1 ELSE NULL END AS IRA,
CASE WHEN "ACCOUNT"."account_producttype"  = 'Standard Loan' THEN 1 ELSE NULL END AS StandardLoan,
CASE WHEN "ACCOUNT"."account_producttype"  = 'Auto' THEN 1 ELSE NULL END AS Auto,
CASE WHEN "ACCOUNT"."account_producttype"  = 'Mortgage' THEN 1 ELSE NULL END AS Mortgage,
CASE WHEN "ACCOUNT"."account_producttype"  = 'Credit Card' THEN 1 ELSE NULL END AS CreditCard

FROM "ACCOUNT" "ACCOUNT" 
)a on "account_customerkey" =a."customerkey"
GROUP BY
"ACCOUNT"."account_customerkey"

【问题讨论】：

您能分享一下您的预期结果吗？

标签： sql apache-spark apache-spark-sql

【解决方案1】：

请试试这个。

scala> df.show()
+--------+--------+
|Customer| Product|
+--------+--------+
|       1| Savings|
|       1|Checking|
|       1|    Auto|
|       2| Savings|
|       2|    Auto|
|       3|Checking|
+--------+--------+


scala> df.groupBy($"Customer").agg(collect_list($"Product").as("Product")).select($"Customer",concat_ws(",",$"Product").as("Product")).show(false)
+--------+---------------------+
|Customer|Product              |
+--------+---------------------+
|1       |Savings,Checking,Auto|
|3       |Checking             |
|2       |Savings,Auto         |
+--------+---------------------+


scala>

【讨论】：

【解决方案2】：

见https://docs.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/collect_list及相关功能

您需要使用collect_list，它可用于 SQL 或 %sql。

%sql 
    select id, collect_list(num) 
      from t1
  group by id

我用的是我自己的数据，你需要剪裁。只是以更原生的 SQL 形式演示。

【讨论】：