pyspark transform json array into multiple columns - python-3.x

Question

I'm using the below code to read data from an api where the payload is in json format using pyspark in azure databricks. All the fields are defined as string but keep running into json_tuple requires that all arguments are strings error.
Schema:
root
|-- Payload: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- ActiveDate: string (nullable = true)
| | |-- BusinessId: string (nullable = true)
| | |-- BusinessName: string (nullable = true)
JSON:
{
"Payload":
[
{
"ActiveDate": "2008-11-25",
"BusinessId": "5678",
"BusinessName": "ACL"
},
{
"ActiveDate": "2009-03-22",
"BusinessId": "6789",
"BusinessName": "BCL"
}
]
}
PySpark:
from pyspark.sql import functions as F
df = df.select(F.col('Payload'), F.json_tuple(F.col('Payload'), 'ActiveDate', 'BusinessId', 'BusinessName') \.alias('ActiveDate', 'BusinessId', 'BusinessName'))
df.write.format("delta").mode("overwrite").saveAsTable("delta_payload")
Error:
AnalysisException: cannot resolve 'json_tuple(`Payload`, 'ActiveDate', 'BusinessId', 'BusinessName')' due to data type mismatch: json_tuple requires that all arguments are strings;

Answer 1

From your schema it looks like the JSON is already parsed, so Payload is of ArrayType rather than StringType containing JSON, hence the error.
You probably need explode instead of json_tuple:
>>> from pyspark.sql.functions import explode
>>> df = spark.createDataFrame([{
... "Payload":
... [
... {
... "ActiveDate": "2008-11-25",
... "BusinessId": "5678",
... "BusinessName": "ACL"
... },
... {
... "ActiveDate": "2009-03-22",
... "BusinessId": "6789",
... "BusinessName": "BCL"
... }
... ]
... }])
>>> df.schema
StructType(List(StructField(Payload,ArrayType(MapType(StringType,StringType,true),true),true)))
>>> df.select(explode("Payload").alias("x")).select("x.ActiveDate", "x.BusinessName", "x.BusinessId").show()
+----------+------------+----------+
|ActiveDate|BusinessName|BusinessId|
+----------+------------+----------+
|2008-11-25| ACL| 5678|
|2009-03-22| BCL| 6789|
+----------+------------+----------+