Question:

How do I flatten a Spark struct field into multiple rows?

Problem:

I've come across documentation and other pages that ask about flattening Spark structs into the same row, but I've been trying to flatten the data into different rows. Say we have the following data:

ID	struct_field
3333	[{"code": 123, "description": "Business Email"}, {"code": 789, "description": "Primary Email"}]
9234	[{"code": 123, "description": "Business Email"}, {"code": 789, "description": "Primary Email"}, {"code": 456, "description": "Secondary Email"}]

And I want it in this format:

ID	Description
3333	Business Email
3333	Primary Email
9234	Business Email
9234	Primary Email
9234	Secondary Email

I've been trying a variety of solutions but haven't been able to get anywhere with doing this all in PySpark.

Solution:

You can use explode with ".*" to get the result:

df.withColumn("struct_field", explode("struct_field")).select("ID", "struct_field.*").show(truncate=False)

Result:

FYI:

explode(): is a function that is used to transform a column of an array into multiple rows.
".*": is used to transform a struct column into columns of fields of that struct.

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