将PySpark数据框列类型转换为字符串并替换方括号

Question

我需要将PySpark df列类型从数组转换为字符串，还要删除方括号。这是数据框的架构。需要处理的列是CurrencyCode和TicketAmount

>>> plan_queryDF.printSchema()

>>> plan_queryDF.printSchema()

来自数据框的样本数据

root
 |-- event_type: string (nullable = true)
 |-- publishedDate: string (nullable = true)
 |-- plannedCustomerChoiceID: string (nullable = true)
 |-- assortedCustomerChoiceID: string (nullable = true)
 |-- CurrencyCode: array (nullable = true)
 |    |-- element: string (containsNull = true)
 |-- TicketAmount: array (nullable = true)
 |    |-- element: string (containsNull = true)
 |-- currentPlan: boolean (nullable = true)
 |-- originalPlan: boolean (nullable = true)
 |-- globalId: string (nullable = true)
 |-- PlanJsonData: string (nullable = true)

我该怎么做？目前，我正在执行字符串转换，然后用regexp_replace替换方括号。但是当我处理大量数据时，这种方法会失败。

我还有其他方法可以做到吗？

这就是我要的。

+--------------------+--------------------+-----------------------+------------------------+------------+------------+-----------+------------+------------+--------------------+
|          event_type|       publishedDate|plannedCustomerChoiceID|assortedCustomerChoiceID|CurrencyCode|TicketAmount|currentPlan|originalPlan|    globalId|        PlanJsonData|
+--------------------+--------------------+-----------------------+------------------------+------------+------------+-----------+------------+------------+--------------------+
|PlannedCustomerCh...|2016-08-23T04:46:...|   087d1ff1-5f3a-496...|    2539cc4a-37e5-4f3...|       [GBP]|         [0]|      false|       false|000576015000|{"httpStatus":200...|
|PlannedCustomerCh...|2016-08-23T04:30:...|   0a1af217-d1e8-4ab...|    61bc5fda-0160-484...|       [CNY]|       [329]|       true|       false|000189668017|{"httpStatus":200...|
|PlannedCustomerCh...|2016-08-23T05:49:...|   1028b477-f93e-47f...|    c6d5b761-94f2-454...|       [JPY]|      [3400]|       true|       false|000576058003|{"httpStatus":200...|

Answer 1

您可以尝试getItem(0)：

df \
    .withColumn("CurrencyCode", df["CurrencyCode"].getItem(0).cast("string")) \
    .withColumn("TicketAmount", df["TicketAmount"].getItem(0).cast("string")) 

最后强制转换为字符串是可选的。