38. user defined function in pyspark | UDF(user defined function) in PySpark | Azure Databricks

Azure Databricks #spark #pyspark #azuredatabricks #azure
In this video, I discussed How to use user defined function (udf).

1.schema comparison in pyspark
2. How to user defined function (udf) in pyspark

Create dataframe:
======================================================
data1=[(1,"Ram","Male",100),(2,"Radhe","Female",200),(3,"John","Male",250)]
data2=[(101,"John","Male",100),(102,"Joanne","Female",250),(103,"Smith","Male",250)]
data3=[(1001,"Maxwell","IT",200),(2,"MSD","HR",350),(3,"Virat","IT",300)]
schema1=["Id","Name","Gender","Salary"]
schema2=["Id","Name","Gender","Salary"]
schema3=["Id","Name","DeptName","Salary"]
df1=spark.createDataFrame(data1,schema1)
df2=spark.createDataFrame(data2,schema2)
df3=spark.createDataFrame(data3,schema3)
display(df1)
display(df2)
display(df3)
-----------------------------------------------------------------------------------------------------------------------
def schemacompare(df1,df2):
allcol=df1.columns+df2.columns
uniquecol=list(set(allcol))
for i in uniquecol:
from pyspark.sql.functions import lit
if i not in df1.columns:
df1=df1.withColumn(i,lit(None))
if i not in df2.columns:
df2=df2.withColumn(i,lit(None))
return df1,df2
---------------------------------------------------------------------------------------------------------------------
df1,df2=schemacompare(df1,df3)
display(df1)
display(df2)
-------------------------------------------------------------------------------------------------------------------

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37. schema comparison in pyspark | How to Compare Two DataFrames in PySpark | pyspark interview:
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Learn PySpark, an interface for Apache Spark in Python. PySpark is often used for large-scale data processing and machine learning.

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