try_parse_json
Parses a column containing a JSON string into a VariantType. Returns None if a string contains an invalid JSON value.
Syntax
Python
from pyspark.sql import functions as sf
sf.try_parse_json(col)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| A column or column name JSON formatted strings. |
Returns
pyspark.sql.Column: a new column of VariantType.
Examples
Python
from pyspark.sql import functions as sf
df = spark.createDataFrame([ {'json': '''{ "a" : 1 }'''}, {'json': '''{a : 1}'''} ])
df.select(sf.to_json(sf.try_parse_json(df.json))).collect()
Output
[Row(to_json(try_parse_json(json))='{"a":1}'), Row(to_json(try_parse_json(json))=None)]