Spark and Hadoop Developer interview Questions [Updated]

1. What is DAG? and explain how it works in Spark?

2. What is Lineage Graph? and explain it in an entire cluster?

3. What are RDD and its advantages and disadvantages?

4. What are DataFrame and Dataset? and their advantages and disadvantages?

5.Difference between Colasie vs Persistence in Spark?

6. Explain the major difference between OrderBy vs SortBy in Hive?

7. Differentiate different storage level’s in the Hadoop eco-system?

8. Is it Apache Spark really need Hadoop, if yes Why? if No why?

9. How to remove the first two lines from the file using ApacheSpark either Scala or Python?

10. What will happens if we load data from Local and Hadoop?

11. What is the different type of files you are using in your project?

12. Explain Sqoop incremental command while using the Hadoop File System to Database?

13. Write the WordCount program in Spark using Scala or Python? and explain step by step processing?

14. What is Hive Serialization and Deserialization? and give a real-time example?

15. why you choose Big Data engineer role in your career? and explain?

16. How to do data processing getting raw data in a huge amount of data?

17. Daily we get 1 GB data suddenly you will get 10 GB data on how to handle it? and explain how it is processing?

18. Explain HDFS components and differentiate Hadoop 1.X version and Hadoop 2.X version?

19. Do you know the idea about different cluster modes in Hadoop? and explain pseudo-distributed? Single node cluster? differentiate between these two distributions?

20. Which one is the best RDD? DataFrame? DataSet? and explain how it is best as compared to the remaining two?

21. Which version using spark? what is your cluster size?

22.Difference between Parquet and Avro and ORC file formats in the Hadoop eco-system?

23. What is Spark Context? What Spark Session Context? explain both terms with examples?

24. Why Hadoop is degraded as compared to Spark with AWS? can you explain? why? how?

25. How much your project daily data from Splunk or any source? how to process that data using Spark explains with architecture?