5. kpmg pyspark interview question & answer | databricks scenario based interview question & answer

#Databricks #PysparkInterviewQuestions #deltalake
Azure Databricks #spark #pyspark #azuredatabricks #azure
In this video, I discussed KPMG PySpark scenario based interview questions and answers.

PySpark advanced interview questions answers?
databricks interview questions and answers?
kpmg pyspark interview questions and answers?

Create dataframe:
======================================================
#Employees Salary info
data1=[(100,"Raj",None,1,"01-04-23",50000),
(200,"Joanne",100,1,"01-04-23",4000),(200,"Joanne",100,1,"13-04-23",4500),(200,"Joanne",100,1,"14-04-23",4020)]
schema1=["EmpId","EmpName","Mgrid","deptid","salarydt","salary"]
display(df_salary)
#department dataframe
data2=[(1,"IT"),
(2,"HR")]
schema2=["deptid","deptname"]
display(df_dept)

-----------------------------------------------------------------------------------------------------------------------
display(df)
---------------------------------------------------------------------------------------------------------------------
#display(df1)
col('b.EmpName').alias('ManagerName'),
col('a.EmpName'),
col('a.Newsaldt'),
)
display(df2)
-------------------------------------------------------------------------------------------------------------------

display(df3)
============================================================

Learn PySpark, an interface for Apache Spark in Python. PySpark is often used for large-scale data processing and machine learning.

Azure data factory tutorial playlist:

ADF interview question & answer:

1. pyspark introduction | pyspark tutorial for beginners | pyspark tutorial for data engineers:

2. what is dataframe in pyspark | dataframe in azure databricks | pyspark tutorial for data engineer:

3. How to read write csv file in PySpark | Databricks Tutorial | pyspark tutorial for data engineer:

4. Different types of write modes in Dataframe using PySpark | pyspark tutorial for data engineers:

5. read data from parquet file in pyspark | write data to parquet file in pyspark:

6. datatypes in PySpark | pyspark data types | pyspark tutorial for beginners:

7. how to define the schema in pyspark | structtype & structfield in pyspark | Pyspark tutorial:

8. how to read CSV file using PySpark | How to read csv file with schema option in pyspark:

9. read json file in pyspark | read nested json file in pyspark | read multiline json file:

10. add, modify, rename and drop columns in dataframe | withcolumn and withcolumnrename in pyspark:

11. filter in pyspark | how to filter dataframe using like operator | like in pyspark:

12. startswith in pyspark | endswith in pyspark | contains in pyspark | pyspark tutorial:

13. isin in pyspark and not isin in pyspark | in and not in in pyspark | pyspark tutorial:

14. select in PySpark | alias in pyspark | azure Databricks #spark #pyspark #azuredatabricks #azure

15. when in pyspark | otherwise in pyspark | alias in pyspark | case statement in pyspark:

16. Null handling in pySpark DataFrame | isNull function in pyspark | isNotNull function in pyspark:

17. fill() & fillna() functions in PySpark | how to replace null values in pyspark | Azure Databrick:

18. GroupBy function in PySpark | agg function in pyspark | aggregate function in pyspark:

19. count function in pyspark | countDistinct function in pyspark | pyspark tutorial for beginners:

20. orderBy in pyspark | sort in pyspark | difference between orderby and sort in pyspark:

21. distinct and dropduplicates in pyspark | how to remove duplicate in pyspark | pyspark tutorial:

[roshnisingh]

Thanks SS Unitech, your videos are very easy to understand 😊

[barmalini]

Thank you sir, this is very useful.
I did not quite understand the purpose of joining a dataframe with itself, this part:
Could someone explain?

[azhi]

how to control variable value in dev and prod different values, can you please explain