pyspark.sql.functions.schema_of_json(json: ColumnOrName, options: Optional[Dict[str, str]] = None) → pyspark.sql.column.Column

Parses a JSON string and infers its schema in DDL format.

jsonColumn or str

a JSON string or a foldable string column containing a JSON string.

optionsdict, optional

options to control parsing. accepts the same options as the JSON datasource. See Data Source Option in the version you use.


>>> df = spark.range(1)
>>>'{"a": 0}')).alias("json")).collect()
[Row(json='STRUCT<a: BIGINT>')]
>>> schema = schema_of_json('{a: 1}', {'allowUnquotedFieldNames':'true'})
[Row(json='STRUCT<a: BIGINT>')]