I have dataframe like below
id contact_persons
-----------------------
1 [[abc, [email protected], 896676, manager],[pqr, [email protected], 89809043, director],[stu, [email protected], 09909343, programmer]]
schema looks like this.
root
|-- id: string (nullable = true)
|-- contact_persons: array (nullable = true)
| |-- element: array (containsNull = true)
| | |-- element: string (containsNull = true)
i need to convert this dataframe like below schema.
root
|-- id: string (nullable = true)
|-- contact_persons: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- emails: string (nullable = true)
| | |-- name: string (nullable = true)
| | |-- phone: string (nullable = true)
| | |-- roles: string (nullable = true)
I know there is struct function in pyspark, but in this scenario, i dont know how to use this as array is dynamic sized.