How to flatten nested struct using PySpark?
Link to dataset https://drive.google.com/file/d/1-xOpd2B7MDgS1t4ekfipHSerIm6JMz9e/view?usp=sharing
While I agree with Phantoms that it is very basic to flatten a df still if you still haven't figured it out you can use below function to flatten your df
def flattenNestedData(nestedDF):
from pyspark.sql.functions import col
from pyspark.sql.types import StructType,ArrayType
try:
##Fetching Complex Datatype Columns from Schema
fieldNames = dict([(field.name, field.dataType) for field in nestedDF.schema.fields if type(field.dataType) == ArrayType or type(field.dataType) == StructType])
while len(fieldNames)!=0:
fieldName=list(fieldNames.keys())[0]
print ("Processing :"+fieldName+" Type : "+str(type(fieldNames[fieldName])))
if type(fieldNames[fieldName]) == StructType:
extractedFields = [col(fieldName +'.'+ innerColName).alias(fieldName+"_"+innerColName) for innerColName in [ colName.name for colName in fieldNames[fieldName]]]
nestedDF=nestedDF.select("*", *extractedFields).drop(fieldName)
elif type(fieldNames[fieldName]) == ArrayType:
nestedDF=nestedDF.withColumn(fieldName,explode_outer(fieldName))
fieldNames = dict([(field.name, field.dataType) for field in nestedDF.schema.fields if type(field.dataType) == ArrayType or type(field.dataType) == StructType])
return nestedDF
except Exception as err:
raise Exception("Error Occured at while flattening the dataframe : " + str(err))
You can remove Arraytype check if you don't want to explode those