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10-18-2021 11:01 AM
You can just use `to_json` to achieve this. Here is an example:
from pyspark.sql import Row
from pyspark.sql.types import *
from pyspark.sql.functions import to_json
data = [(1, Row(Code__c="00001-B",
EAN_Code__c="1111111111.0",
Extra_Information_JSON__c="[{\"name\":\"Action\",\"value\":\"Verifier remplissage\"},{\"name\":\"Stock Disponible\",\"value\":\"18\"}]",
Flag__c="Rupture Ponctuel",
Problematic__c=True))]
df = spark.createDataFrame(data, ("key", "value"))
display(df.select(to_json(df.value).alias("json")))This is just an example to point you in the right direction, you may need to adapt it to your specific input format. This is meant to run in a Databricks notebook, otherwise the final `display` will not work.